A  B  C  D  E  F  G  H  I  J  K  L  M  N  O  P  Q  R  S  T  U  V  W  X  Y  Z  

              [Sort alphabetically]   [Restore default list]

  Subjects -> METEOROLOGY (Total: 106 journals)
Showing 1 - 36 of 36 Journals sorted by number of followers
Journal of Atmospheric and Solar-Terrestrial Physics     Hybrid Journal   (Followers: 159)
Nature Climate Change     Full-text available via subscription   (Followers: 151)
Journal of the Atmospheric Sciences     Hybrid Journal   (Followers: 80)
Atmospheric Research     Hybrid Journal   (Followers: 73)
Atmospheric Environment     Hybrid Journal   (Followers: 72)
Climatic Change     Open Access   (Followers: 71)
Bulletin of the American Meteorological Society     Open Access   (Followers: 63)
Advances in Climate Change Research     Open Access   (Followers: 60)
Journal of Climate     Hybrid Journal   (Followers: 56)
Climate Policy     Hybrid Journal   (Followers: 53)
Climate Change Economics     Hybrid Journal   (Followers: 50)
Climate Dynamics     Hybrid Journal   (Followers: 45)
Advances in Atmospheric Sciences     Hybrid Journal   (Followers: 44)
Atmospheric Chemistry and Physics (ACP)     Open Access   (Followers: 43)
Weather and Forecasting     Hybrid Journal   (Followers: 43)
American Journal of Climate Change     Open Access   (Followers: 42)
Journal of Applied Meteorology and Climatology     Hybrid Journal   (Followers: 41)
Atmospheric Science Letters     Open Access   (Followers: 40)
Nature Reports Climate Change     Full-text available via subscription   (Followers: 40)
Journal of Hydrology and Meteorology     Open Access   (Followers: 39)
Atmosphere     Open Access   (Followers: 33)
Journal of Atmospheric and Oceanic Technology     Hybrid Journal   (Followers: 33)
International Journal of Climate Change Strategies and Management     Hybrid Journal   (Followers: 32)
The Quarterly Journal of the Royal Meteorological Society     Hybrid Journal   (Followers: 32)
Journal of Space Weather and Space Climate     Open Access   (Followers: 30)
Boundary-Layer Meteorology     Hybrid Journal   (Followers: 30)
Monthly Weather Review     Hybrid Journal   (Followers: 30)
Meteorology and Atmospheric Physics     Hybrid Journal   (Followers: 29)
International Journal of Climatology     Hybrid Journal   (Followers: 28)
Climate Change Responses     Open Access   (Followers: 27)
Space Weather     Full-text available via subscription   (Followers: 27)
Energy & Environment     Hybrid Journal   (Followers: 26)
Climate Resilience and Sustainability     Open Access   (Followers: 26)
International Journal of Atmospheric Sciences     Open Access   (Followers: 25)
Journal of Climate Change     Full-text available via subscription   (Followers: 25)
Advances in Meteorology     Open Access   (Followers: 25)
International Journal of Environment and Climate Change     Open Access   (Followers: 24)
Environmental Dynamics and Global Climate Change     Open Access   (Followers: 24)
Journal of Atmospheric Chemistry     Hybrid Journal   (Followers: 23)
Current Climate Change Reports     Hybrid Journal   (Followers: 22)
Agricultural and Forest Meteorology     Hybrid Journal   (Followers: 21)
Tellus A     Open Access   (Followers: 21)
Journal of Economic Literature     Hybrid Journal   (Followers: 20)
Tellus B     Open Access   (Followers: 20)
Global Meteorology     Open Access   (Followers: 19)
Dynamics of Atmospheres and Oceans     Hybrid Journal   (Followers: 19)
Journal of Meteorology and Climate Science     Full-text available via subscription   (Followers: 19)
Weatherwise     Hybrid Journal   (Followers: 18)
Weather and Climate Extremes     Open Access   (Followers: 18)
Economics of Disasters and Climate Change     Hybrid Journal   (Followers: 16)
Atmosphere-Ocean     Full-text available via subscription   (Followers: 16)
Atmospheric Chemistry and Physics Discussions (ACPD)     Open Access   (Followers: 15)
Theoretical and Applied Climatology     Hybrid Journal   (Followers: 14)
Monthly Notices of the Royal Astronomical Society     Hybrid Journal   (Followers: 13)
Climate Risk Management     Open Access   (Followers: 12)
Advances in Statistical Climatology, Meteorology and Oceanography     Open Access   (Followers: 12)
Atmospheric and Oceanic Science Letters     Open Access   (Followers: 11)
Journal of Hydrometeorology     Hybrid Journal   (Followers: 10)
Climate Research     Hybrid Journal   (Followers: 8)
Climate and Energy     Full-text available via subscription   (Followers: 8)
The Cryosphere (TC)     Open Access   (Followers: 8)
Journal of the Meteorological Society of Japan     Partially Free   (Followers: 7)
Climate of the Past (CP)     Open Access   (Followers: 7)
Climate     Open Access   (Followers: 7)
Aeolian Research     Hybrid Journal   (Followers: 7)
Climate Law     Hybrid Journal   (Followers: 6)
Dynamics and Statistics of the Climate System     Open Access   (Followers: 6)
Journal of Climate Change and Health     Open Access   (Followers: 6)
Carbon Balance and Management     Open Access   (Followers: 6)
Open Atmospheric Science Journal     Open Access   (Followers: 5)
Bulletin of Atmospheric Science and Technology     Hybrid Journal   (Followers: 5)
Open Journal of Modern Hydrology     Open Access   (Followers: 5)
Urban Climate     Hybrid Journal   (Followers: 5)
Meteorological Applications     Open Access   (Followers: 4)
Journal of Integrative Environmental Sciences     Hybrid Journal   (Followers: 4)
Frontiers in Climate     Open Access   (Followers: 4)
Journal of Weather Modification     Full-text available via subscription   (Followers: 4)
Russian Meteorology and Hydrology     Hybrid Journal   (Followers: 4)
Meteorologische Zeitschrift     Full-text available via subscription   (Followers: 4)
Climate Services     Open Access   (Followers: 4)
Acta Meteorologica Sinica     Hybrid Journal   (Followers: 4)
Journal of Climatology     Open Access   (Followers: 4)
Atmospheric Environment : X     Open Access   (Followers: 3)
npj Climate and Atmospheric Science     Open Access   (Followers: 3)
Oxford Open Climate Change     Open Access   (Followers: 3)
Environmental and Climate Technologies     Open Access   (Followers: 3)
International Journal of Biometeorology     Hybrid Journal   (Followers: 3)
International Journal of Image and Data Fusion     Hybrid Journal   (Followers: 3)
Atmósfera     Open Access   (Followers: 2)
GeoHazards     Open Access   (Followers: 2)
Journal of Meteorological Research     Full-text available via subscription   (Followers: 2)
Mediterranean Marine Science     Open Access   (Followers: 2)
Meteorologica     Open Access   (Followers: 2)
气候与环境研究     Full-text available via subscription   (Followers: 2)
Weather and Climate Dynamics     Open Access   (Followers: 1)
Modeling Earth Systems and Environment     Hybrid Journal   (Followers: 1)
Michigan Journal of Sustainability     Open Access   (Followers: 1)
Earth Perspectives - Transdisciplinarity Enabled     Open Access   (Followers: 1)
Tropical Cyclone Research and Review     Open Access   (Followers: 1)
Ciencia, Ambiente y Clima     Open Access   (Followers: 1)
Climate of the Past Discussions (CPD)     Open Access   (Followers: 1)
Nīvār     Open Access   (Followers: 1)
Meteorological Monographs     Hybrid Journal   (Followers: 1)
Studia Geophysica et Geodaetica     Hybrid Journal   (Followers: 1)
Revista Iberoamericana de Bioeconomía y Cambio Climático     Open Access   (Followers: 1)
Journal of Agricultural Meteorology     Open Access  
Mètode Science Studies Journal : Annual Review     Open Access  

              [Sort alphabetically]   [Restore default list]

Similar Journals
Journal Cover
Atmosphere
Number of Followers: 33  

  This is an Open Access Journal Open Access journal
ISSN (Online) 2073-4433
Published by MDPI Homepage  [84 journals]
  • Atmosphere, Vol. 13, Pages 1193: Time-Lagged Ensemble Quantitative
           Precipitation Forecasts for Three Landfalling Typhoons in the Philippines
           Using the CReSS Model, Part I: Description and Verification against
           Rain-Gauge Observations

    • Authors: Chung-Chieh Wang, Chien-Hung Tsai, Ben Jong-Dao Jou, Shirley J. David
      First page: 1193
      Abstract: In this study, the 2.5 km Cloud-Resolving Storm Simulator was applied to forecast the rainfall by three landfalling typhoons in the Philippines at high resolution: Mangkhut (2018), Koppu (2015), and Melor (2015), using a time-lagged strategy for ensemble. The three typhoons penetrated northern Luzon, central Luzon, and the middle of the Philippine Archipelago, respectively, and the present study verified the track and quantitative precipitation forecasts (QPFs) using categorical statistics against observations at 56 rain-gauge sites at seven thresholds up to 500 mm. The predictability of rainfall is the highest for Koppu, followed by Melor, and the lowest for Mangkhut, which had the highest peak rainfall amount. Targeted at the most-rainy 24 h of each case, the threat score (TS) within the short range (≤72 h) could reach 1.0 for Koppu at 350 mm in many runs (peak observation = 502 mm), and 1.0 for Mangkhut and 0.25 for Melor (peak observation = 407 mm) both at 200 mm in the best member, when the track errors were small enough. For rainfall from entire events (48 or 72 h), TS hitting 1.0 could also be achieved regularly at 500 mm for Koppu (peak observation = 695 mm), and 0.33 at 350 mm for Melor (407 mm) and 0.46 at 200 mm for Mangkhut (786 mm) in the best case. At lead times beyond the short range, one third of these earlier runs also produced good QPFs for both Koppu and Melor, but such runs were fewer for Mangkhut and the quality of QPFs was also not as high due to larger northward track biases. Overall, the QPF results are very encouraging, and comparable to the skill level for typhoon rainfall in Taiwan (with similar peak rainfall amounts). Thus, at high resolution, there is a fair chance to make decent QPFs even at lead times of 3–7 days before typhoon landfall in the Philippines, with useful information on rainfall scenarios for early preparation.
      Citation: Atmosphere
      PubDate: 2022-07-28
      DOI: 10.3390/atmos13081193
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1194: Volatile Organic Compound Emission Status
           and Control Perspectives in the Petroleum Refining Industry in China

    • Authors: Sha Sha, Siming Liu, Minchao Huang, Na Fan, Na Wang, Mei Cai
      First page: 1194
      Abstract: Given the increasingly serious ozone pollution, petroleum refining has received more attention, since it is one of the dominant volatile organic compound-emitting industries in China. Volatile organic compound emission source identification, control efficiency classification, emissions calculation, emission factor generation and uncertainty analysis were performed in this study. According to the VOC emission control level, petroleum refining enterprises were divided into three levels, accounting for 10.6%, 54.4% and 35% of the total refining capacity, and 0.6%, 1.2%, and 3% were generated as the emission factor for each designed level, respectively. The total volatile organic compound emissions of the China petroleum refining industry in 2020 are estimated to be 1150 Kt by applying the hierarchical accounting method. Furthermore, the spatial distribution of volatile organic compound emissions was analyzed. The emission intensity of 15 cities is greater than the national average value of 0.12 tons/km2, where the highest level is approximately 2.7 tons/km2. To reduce the volatile organic compound emissions of PR enterprises, the collection efficiency and operation effect of treatment facilities are the most important points based on the analysis of the current situation of volatile organic compound emissions in the PR industry in China.
      Citation: Atmosphere
      PubDate: 2022-07-28
      DOI: 10.3390/atmos13081194
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1195: A GDM-GTWR-Coupled Model for
           Spatiotemporal Heterogeneity Quantification of CO2 Emissions: A Case of
           the Yangtze River Delta Urban Agglomeration from 2000 to 2017

    • Authors: Zhen Zhu, Junyan Yu, Jinhui Luo, Huiyuan Zhang, Qilong Wu, Yuhua Chen
      First page: 1195
      Abstract: CO2 emissions from fossil energy have caused global climate problems and threatened human survival. However, there are few studies on the spatiotemporal distribution and driving factors of carbon emissions. This paper takes the Yangtze River Delta (YRD) urban agglomeration as the research object and analyzes the spatiotemporal heterogeneity of carbon dioxide emissions and their driving factors from 2000 to 2017. First, a series of preprocessing, such as resample, interpolation, and image clipping, are conducted on the CO2 emission data and nighttime light remote sensing images. Second, the dynamic time wrapping (DTW) and hierarchical clustering algorithms were involved in manipulating the CO2 emission data. Consequently, the cities’ and CO2 emissions’ time series were classified into four categories and three stages separately. Finally, the geographical detector model (GDM) and geographical and temporal weighted regression (GTWR) are coupled to evaluate the spatiotemporal heterogeneity and quantify the driving factors. The results show the following: (1) The spatiotemporal distribution of CO2 emissions has spatial consistency from 2000 to 2017. High-emission areas are concentrated in economically developed areas such as Shanghai, Suzhou, and Wuxi. The results are consistent with previous research. (2) Regional aggregation is a revealed new trend. CO2 emissions in the target urban areas are gradually converging into economic center cities and diverse class cities, e.g., Shanghai and Ningbo. (3) In cities of different economic development levels, the driving factors of CO2 emissions are different. The secondary sector and urban infrastructure dominate in the early stages of developed cities. On top of that, the influence of the tertiary industry is more significant in the later development stages. According to the results, in the urban development process, humans should not only pursue the increase in speed but also pay attention to the negative impact of the economic development process on the ecological environment. Besides, since the spatiotemporal characteristics and dominant factors of urban carbon emissions are different in each stage of development, the formulation of carbon reduction policies should be associated with urban features.
      Citation: Atmosphere
      PubDate: 2022-07-28
      DOI: 10.3390/atmos13081195
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1196: Regeneration of Pinus sibirica Du Tour in
           the Mountain Tundra of the Northern Urals against the Background of
           Climate Warming

    • Authors: Natalya Ivanova, Nikolai Tantsyrev, Guoqing Li
      First page: 1196
      Abstract: Climate is one of the key drivers of the plant community’s structure and trends. However, the regional vegetation-climate features in the ecotone have not yet been sufficiently studied. The aim of the research is to study features of Pinus sibirica Du Tour germination, survival, and growth in the mountain tundra of the Northern Urals against the background of a changing climate. The following research objectives were set: To determine the abundance and age structure of P. sibirica undergrowth on the mountain tundra plateau, identify the features of P. sibirica growth in the mountain tundra, and examine the correlation between the multi-year air temperature pattern, precipitation, and P. sibirica seedling emergence. A detailed study of the Pinus sibirica natural regeneration in the mountain stony shrub-moss-lichen tundra area at an altitude of 1010–1040 m above sea level on the Tri Bugra mountain massif plateau (59°30′ N, 59°15′ E) in the Northern Urals (Russia) has been conducted. The research involved the period between 1965 and 2017. Woody plant undergrowth was considered in 30 plots, 5 × 5 m in size. The first generations were recorded from 1967–1969. The regeneration has become regular since 1978 and its intensity has been increasing since then. Climate warming is driving these processes. Correlation analysis revealed significant relationships between the number of Pinus sibirica seedlings and the minimum temperature in August and September of the current year, the minimum temperatures in May, June, and November of the previous year, the maximum temperatures in May and August of the current year, and precipitation in March of both the current and previous years. However, the young tree growth rate remains low to date (the height at an age of 45–50 years is approximately 114 ± 8.8 cm). At the same time, its open crowns are rare single lateral shoots. The length of the side shoots exceeds its height by 4–5 times, and the length of the lateral roots exceeds its height by 1.2–1.5 times. This is an indicator of the extreme conditions for this tree species. With the current rates of climate warming and the Pinus sibirica tree growth trends, the revealed relationships allow for the prediction that in 20–25 years, the mountain tundra in the studied Northern Urals plateau could develop underground-closed forest communities with a certain forest relationship. The research results are of theoretical importance for clarifying the forest-tundra ecotone concept. From a practical point of view, the revealed relationship can be used to predict the trend in forest ecosystem formation in the mountain forest-tundra ecotone.
      Citation: Atmosphere
      PubDate: 2022-07-29
      DOI: 10.3390/atmos13081196
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1197: Spatial and Temporal Analysis of Extreme
           Climate Events over Northeast China

    • Authors: Xingyang Yu, Yuanyuan Ma
      First page: 1197
      Abstract: In recent years, the frequent occurrence of extreme climate disasters has seriously affected agriculture in Northeast China. Based on precipitation data derived from 83 geographical stations in the study area for 60 years (1960–2019), we chose the reliable statistical methods of the Mann–Kendall test, Sen’s slope, and the Standardized Precipitation Index, and regarded drought and flood as a whole in this paper, to identify the temporal and spatial variation characteristics of precipitation and extreme climate events in Northeast China. The results show that an increasing trend of disasters was detected at the 95% confidence level (Z = 2.3). According to the timescale analysis, abrupt climate changes started in 2006. Temporal and spatial distribution of extreme climate disasters, mainly drought and flood disasters, showed a significant upward trend from 2006 to 2019. According to the spatial analysis, the precipitation in Northeast China decreased from south to north and fluctuated less from east to west. Moreover, stations with extreme climate trends (trend of climatic anomaly with confidence level > 90%) followed the same spatial pattern as those with a high frequency of extreme climate disasters (more than 17.87 times/decade). The severity and frequency of extreme climate have increasingly threatened Northeast China in the past decade. In particular, the Northeast Plain experienced the most severe and extreme climate events that seriously threatened the study area in 2007, 2009, 2010, and 2019. Our results highlight the urgent need for the development of monitoring and early warning of droughts and flood disasters to reduce economic losses.
      Citation: Atmosphere
      PubDate: 2022-07-29
      DOI: 10.3390/atmos13081197
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1198: Joint Pattern Analysis of Forest Fire and
           Drought Indicators in Southeast Asia Associated with ENSO and IOD

    • Authors: Sri Nurdiati , Ardhasena Sopaheluwakan, Pandu Septiawan
      First page: 1198
      Abstract: Land and forest fires in Southeast Asia often coincide with severe dry seasons in the specific region caused by the warm phase of an El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). This research aims to identify and quantify the ENSO–IOD effect on a joint pattern between the dry season and land and forest fires in Southeast Asia. This research provides a quantitative result which represents the ENSO–IOD’s impact in Southeast Asia for hotspots, dry spells, and precipitation anomalies. The methods used in this research are singular value decomposition, probability density skill score, and coherence analysis. Cambodia, Myanmar, and Thailand gave a similar result with less than a 25% increasing severity in the hotspots from normal to either El Niño, positive IOD, or El Niño–positive IOD years. The maximum increase in hotspot severity in North Sumatra was 13.06% and happened during a weak El Niño and positive IOD. Meanwhile, South Sumatra had a maximum accumulation of more than 89% and Kalimantan had more than a 72% increase during the strong El Niño in 2015. Even though the relationship between the ENSO and IOD was inconsistent, the occurrence of both phenomena in the same year can lead to fires and need to be considered.
      Citation: Atmosphere
      PubDate: 2022-07-29
      DOI: 10.3390/atmos13081198
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1199: Variations in Sulfur and Nitrogen
           Oxidation Rates in Summer Aerosols from 2014 to 2020 in Wuhan, China

    • Authors: Jinhui Zhao, Chiyuan Ma, Chao He, Zhouxiang Zhang, Taotao Jiang, Rui Tang, Qiang Chen
      First page: 1199
      Abstract: To date, research regarding the changes of the sulfur and nitrogen rates in Wuhan during the summer is limited. In this study, we analyzed the air quality in Wuhan, China, using water-soluble ion, gaseous precursor, and weather data. A Spearman correlation analysis was then performed to investigate the temporal changes in air quality characteristics and their driving factors to provide a reference for air pollution control in Wuhan. The results indicate that SO2 in the atmosphere at Wuhan undergoes secondary conversion and photo-oxidation, and the conversion degree of SO2 is higher than that of NO2. During the summers of 2016 and 2017, secondary inorganic atmospheric pollution was more severe than during other years. The fewest oxidation days occurred in summer 2020 (11 days), followed by the summers of 2017 and 2014 (25 and 27 days, respectively). During the study period, ion neutralization was the strongest in summer 2015 and the weakest in August 2020. The aerosols in Wuhan were mostly acidic and NH4+ was an important neutralizing component. The neutralization factors of all cations showed little change in 2015. K+, Mg2+, and Ca2+ level changes were the highest in 2017 and 2020. At low temperature, high humidity, and low wind speed conditions, SO2 and NO2 were more easily converted into SO42− and NO3−.
      Citation: Atmosphere
      PubDate: 2022-07-29
      DOI: 10.3390/atmos13081199
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1200: Impacts of Soil Moisture and Fertilizer
           on N2O Emissions from Cornfield Soil in a Karst Watershed, SW China

    • Authors: Lai Wei, Xiaolong Liu, Caiqing Qin, Wencong Xing, Yongbo Gu, Xiaoxia Wang, Li Bai, Jun Li
      First page: 1200
      Abstract: Incubation experiments using a typical cornfield soil in the Wujiang River watershed, SW China, were conducted to examine the impacts of soil moisture and fertilizer on N2O emissions and production mechanisms. According to the local fertilizer type, we added NH4NO3 (N) and glucose (C) during incubation to simulate fertilizer application in the cornfield soil. The results showed that an increase in soil moisture and fertilizer significantly stimulated N2O emissions in cornfield soil in the karst area, and it varied with soil moisture. The highest N2O emission fluxes were observed in the treatment with nitrogen and carbon addition at 70% water-filled pore space (WFPS), reaching 6.6 mg kg−1 h−1, which was 22,310, 124.9, and 1.4 times higher than those at 5%, 40%, and 110% WFPS, respectively. The variations of nitrogen species indicated that the production of extremely high N2O at 70% WFPS was dominated by nitrifier denitrification and denitrification, and N2O was the primary form of soil nitrogen loss when soil moisture was >70% WFPS. This study provides a database for estimating N2O emissions in cropland soil in the karst area, and further helped to promote proper soil nitrogen assessment and management of agricultural land of the karst watersheds.
      Citation: Atmosphere
      PubDate: 2022-07-29
      DOI: 10.3390/atmos13081200
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1201: Winter and Wildfire Season Optical
           Characterization of Black and Brown Carbon in the El Paso-Ciudad
           Juárez Airshed

    • Authors: Pamela Lara, Rosa M. Fitzgerald, Nakul N. Karle, Jose Talamantes, Miranda Miranda, Darrel Baumgardner, William R. Stockwell
      First page: 1201
      Abstract: Black (EBC) and Brown (BrC) Carbon are ubiquitous constituents of atmospheric particulate matter that affect people’s health, disrupt ecosystems, and modulate local and global climate. Tracking the local deposition and sources of these aerosol particles is essential to better understanding their multidimensional environmental impact. The main goal of the current study is to measure the absorption coefficient (Babs) of particles within the Planetary Boundary Layer (PBL) of the El Paso (US)–Ciudad Juárez (Mexico) airshed and assess the contribution of black and brown carbon particles to the optical absorption. Measurements were taken during a summer, wildfire, and winter season to evaluate the optical properties of BC and non-volatile BrC. The winter season presented a variation from the background Babs in the late evening hours (3:00 PM to midnight) due to an increase in biomass burning driven by lower temperatures. The wildfire season presents the greatest variation in the Babs from the background absorption due to EBC- and BrC-rich smoke plumes arriving at this region from the US West seasonal wildfires. It was found that the international bridges’ vehicular traffic, waiting time to cross back and forth between both cities, added to other local anthropogenic activities, such as brick kiln emissions in Ciudad Juarez, have created a background of air pollution in this region. These pollutants include carbon monoxide, sulfur dioxide, nitrogen and nitric oxides, coarse and fine particulate matter dominated by BC and BrC. The absorption coefficients due to EBC and BrC of this background constitute what we have called a baseline EBC and BrC. Aided by two photoacoustic Extinctiometers (PAX), operating at 405 nm and 870 nm wavelengths, connected to a 340 °C thermal denuder to remove volatile organics, the optical properties were documented and evaluated to identify the impact of long-range transported emissions from western wildfires. The Single Scattering Albedo and the Absorption Ångstrom exponent were calculated for the winter and summer season. The Angstrom exponent showed a decrease during the wildfire events due to the aging process. The High-Resolution Rapid Refresh Smoke model, HRRR, and the Hybrid Single-Particle Lagrangian Integrated Trajectory model, HYSPLIT, were used to estimate the sources of the particles. In addition, a Vaisala Ceilometer was employed to study the vertical profile of particulate matter within the planetary boundary layer.
      Citation: Atmosphere
      PubDate: 2022-07-29
      DOI: 10.3390/atmos13081201
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1202: Variability of Precipitation Recycling
           and Moisture Sources over the Colombian Pacific Region: A
           Precipitationshed Approach

    • Authors: Angelica M. Enciso, Olga Lucia Baquero, Daniel Escobar-Carbonari, Jeimar Tapasco, Wilmar L. Cerón
      First page: 1202
      Abstract: This study assessed the precipitation recycling and moisture sources in the Colombian Pacific region between 1980–2017, based on the monitoring of moisture in the atmosphere through the Eulerian Water Accounting Model-2 layer (WAM2 layer) and the delimitation of the area contributing to terrestrial and oceanic moisture in the region is performed using the “precipitationshed” approach. The results indicate a unimodal precipitation recycling ratio for the North and Central Pacific and Patía-Mira regions, with the highest percentages between March and April, reaching 30% and 34%, respectively, and the lowest between September and October (between 19% and 21%). Moreover, monthly changes in the circulation of the region promote a remarkable variability of the sources that contribute to the precipitation of the study area and the spatial dynamics of the precipitationshed. From December to April, the main contributions come from continental sources in eastern Colombia and Venezuela, the tropical North Atlantic, and the Caribbean Sea, a period of high activity of the Orinoco Low-Level jet. In September, the moisture source region is located over the Pacific Ocean, where a southwesterly cross-equatorial circulation predominates, converging in western Colombia, known as the Choco Jet (CJ), decreasing the continental contribution. An intensified Caribbean Low-Level Jet inhibits moisture sources from the north between June and August, strengthening a southerly cross-equatorial flow from the Amazon River basin and the southeastern tropical Pacific. The March–April (September–October) season of higher (lower) recycling of continental precipitation is related to the weakening (strengthening) of the CJ in the first (second) half of the year, which decreases (increases) the contribution of moisture from the Pacific Ocean to the region, increasing (decreasing) the influence of land-based sources in the study area.
      Citation: Atmosphere
      PubDate: 2022-07-30
      DOI: 10.3390/atmos13081202
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1203: High Resolution Modelling of Traffic
           Emissions Using the Large Eddy Simulation Code Fluidity

    • Authors: Huw Woodward, Anna K. Schroeder, Clemence M. A. Le Cornec, Marc E. J. Stettler, Helen ApSimon, Alan Robins, Christopher Pain, Paul F. Linden
      First page: 1203
      Abstract: The large eddy simulation (LES) code Fluidity was used to simulate the dispersion of NOx traffic emissions along a road in London. The traffic emissions were represented by moving volume sources, one for each vehicle, with time-varying emission rates. Traffic modelling software was used to generate the vehicle movement, while an instantaneous emissions model was used to calculate the NOx emissions at 1 s intervals. The traffic emissions were also modelled as a constant volume source along the length of the road for comparison. A validation of Fluidity against wind tunnel measurements is presented before a qualitative comparison of the LES concentrations with measured roadside concentrations. Fluidity showed an acceptable comparison with the wind tunnel data for velocities and turbulence intensities. The in-canyon tracer concentrations were found to be significantly different between the wind tunnel and Fluidity. This difference was explained by the very high sensitivity of the in-canyon tracer concentrations to the precise release location. Despite this, the comparison showed that Fluidity was able to provide a realistic representation of roadside concentration variations at high temporal resolution, which is not achieved when traffic emissions are modelled as a constant volume source or by Gaussian plume models.
      Citation: Atmosphere
      PubDate: 2022-07-30
      DOI: 10.3390/atmos13081203
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1204: Analysis of TRWP Particle Distribution in
           Urban and Suburban Landscapes, Connecting Real Road Measurements with
           Particle Distribution Simulation

    • Authors: Miles Kunze, Toni Feißel, Valentin Ivanov, Thomas Bachmann, David Hesse, Sebastian Gramstat
      First page: 1204
      Abstract: This article deals with methods and measurements related to environmental pollution and analysis of particle distribution in urban and suburban landscapes. Therefore, an already-invented sampling method for tyre road wear particles (TRWP) was used to capture online emission factors from the road. The collected particles were analysed according to their size distribution, for use as an input for particle distribution simulations. The simulation model was a main traffic intersection, because of the high vehicle dynamic related to the high density of start–stop manoeuvres. To compare the simulation results (particle mass (PM) and particle number (PN)) with real-world emissions, measuring points were defined and analysed over a measuring time of 8 h during the day. Afterwards, the collected particles were analysed in terms of particle shape, appearance and chemical composition, to identify the distribution and their place of origin. As a result of the investigation, the appearance of the particles showed a good correlation to the vehicle dynamics, even though there were a lot of background influences, e.g., resuspension of dust. Air humidity also showed a great influence on the recorded particle measurements. In areas of high vehicle dynamics, such as heavy braking or accelerating, more tyre and brake particles could be found.
      Citation: Atmosphere
      PubDate: 2022-07-30
      DOI: 10.3390/atmos13081204
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1205: Data-Driven Prediction of COVID-19 Daily
           New Cases through a Hybrid Approach of Machine Learning Unsupervised and
           Deep Learning

    • Authors: Ulises Manuel Ramirez-Alcocer, Edgar Tello-Leal, Bárbara A. Macías-Hernández, Jaciel David Hernandez-Resendiz
      First page: 1205
      Abstract: Air pollution is associated with respiratory diseases and the transmission of infectious diseases. In this context, the association between meteorological factors and poor air quality possibly contributes to the transmission of COVID-19. Therefore, analyzing historical data of particulate matter (PM2.5, and PM10) and meteorological factors in indoor and outdoor environments to discover patterns that allow predicting future confirmed cases of COVID-19 is a challenge within a long pandemic. In this study, a hybrid approach based on machine learning and deep learning is proposed to predict confirmed cases of COVID-19. On the one hand, a clustering algorithm based on K-means allows the discovery of behavior patterns by forming groups with high cohesion. On the other hand, multivariate linear regression is implemented through a long short-term memory (LSTM) neural network, building a reliable predictive model in the training stage. The LSTM prediction model is evaluated through error metrics, achieving the highest performance and accuracy in predicting confirmed cases of COVID-19, using data of PM2.5 and PM10 concentrations and meteorological factors of the outdoor environment. The predictive model obtains a root-mean-square error (RMSE) of 0.0897, mean absolute error (MAE) of 0.0837, and mean absolute percentage error (MAPE) of 0.4229 in the testing stage. When using a dataset of PM2.5, PM10, and meteorological parameters collected inside 20 households from 27 May to 13 October 2021, the highest performance is obtained with an RMSE of 0.0892, MAE of 0.0592, and MAPE of 0.2061 in the testing stage. Moreover, in the validation stage, the predictive model obtains a very acceptable performance with values between 0.4152 and 3.9084 for RMSE, and a MAPE of less than 4.1%, using three different datasets with indoor environment values.
      Citation: Atmosphere
      PubDate: 2022-07-31
      DOI: 10.3390/atmos13081205
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1206: Temporal Variation and Source Analysis of
           Atmospheric CH4 at Different Altitudes in the Background Area of Yangtze
           River Delta

    • Authors: Meng Shan, Honghui Xu, Lujie Han, Yuting Pang, Juncheng Ma, Chao Zhang
      First page: 1206
      Abstract: Through an analysis of CH4 data observed at different altitudes at the atmospheric background station in Lin’an from 2016 to 2020, in combination with back-trajectory and distribution characteristics of potential source areas, the CH4 concentration variations at higher and lower altitudes and their relationships with sources and sinks were studied. The results showed that the CH4 concentration was characterized by notable diurnal variations. The largest concentration difference occurred between 5 and 7 a.m.; the concentration difference in summer was higher than that in the other three seasons. Background filtering of the hourly CH4 concentration was carried out using a numerical method. The results showed that the difference in the CH4 background concentration between the two altitudes was 4.6 ppb (SD = 7.9). The CH4 background concentrations at the two altitudes had the same seasonal variation: double peaks and valleys. The peaks appeared in May and December, and the valleys appeared in March and July. In spring and summer, the potential CH4 source areas were mainly distributed in the rice planting and wetland discharge regions. In autumn, they were mainly distributed in regions affected by fugitive emissions from rice planting and coal mining. In winter, they were mainly distributed in livestock and poultry management regions.
      Citation: Atmosphere
      PubDate: 2022-07-31
      DOI: 10.3390/atmos13081206
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1207: Atmospheric Factors Affecting Global
           Solar and Photosynthetically Active Radiation Relationship in a
           Mediterranean Forest Site

    • Authors: Nikolaos D. Proutsos, Aristotle Liakatas, Stavros G. Alexandris, Ioannis X. Tsiros, Dimitris Tigkas, George Halivopoulos
      First page: 1207
      Abstract: Light availability and its composition in components affecting plant growth as photosynthetically active radiation (PAR), are of critical importance in agricultural and environmental research. In this work, radiation data for the period 2009–2014 in a forest site in Greece were analyzed to identify the effect of meteorological variables on the formation of the photosynthetically active to global solar radiation ratio. The temporal changes of the ratio are also discussed. Results showed that the ratio values are higher in summer (0.462) and lower in autumn (0.432), resulting in an annual average of 0.446. In addition, for the investigated site, which was characterized by relatively high water content in the atmosphere, the atmospheric water content and clearness were found to be the most influential factors in the composition of the global solar radiation in the wavelengths of PAR. On the contrary, temperature and related meteorological attributes (including relative humidity, vapor pressure deficit and saturation vapor pressure) were found to have minor effect.
      Citation: Atmosphere
      PubDate: 2022-07-31
      DOI: 10.3390/atmos13081207
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1208: Daily Weather Forecasting Based on Deep
           Learning Model: A Case Study of Shenzhen City, China

    • Authors: Guici Chen, Sijia Liu, Feng Jiang
      First page: 1208
      Abstract: Daily weather conditions are closely related to every field of production and life, and the forecasting of weather conditions plays an important role in social development. Based on the data characteristics of urban weather conditions, a deep learning network was designed to forecast urban weather conditions, and its feasibility was proved by experiments. In view of the non-stationary and seasonal fluctuation of the time series of daily weather conditions in Shenzhen from 2015 to 2019, empirical mode decomposition (EMD) was used to carry out the stationary processing for the daily minimum humidity, minimum pressure, maximum temperature, maximum pressure, maximum wind speed and minimum temperature. The decomposed components, residual sequence and original sequence were reconstructed according to the degree of relevance. On this basis, a long short-term memory (LSTM) neural network for the Shenzhen daily weather forecast was used, using the advantages of the LSTM model in time-series data processing, using the grid search algorithm to find the optimal combination of the above parameters and combining with the gradient descent optimization algorithm to find optimal weights and bias, so as to improve the prediction accuracy of Shenzhen weather characteristics. The experimental results show that our design of the EMD-LSTM model has higher forecasting precision and efficiency than traditional models, which provides new ideas for the weather forecast.
      Citation: Atmosphere
      PubDate: 2022-08-01
      DOI: 10.3390/atmos13081208
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1209: Stratospheric Chemical Lifetime of
           Aviation Fuel Incomplete Combustion Products

    • Authors: William Bains, Eleanor Viita, Janusz J. Petkowski, Sara Seager
      First page: 1209
      Abstract: The stratosphere contains haze rich in sulfuric acid, which plays a significant role in stratospheric chemistry and in global climate. Commercial aircraft deposit significant amounts of incomplete combustion products into the lower stratosphere. We have studied the stability of these incomplete combustion products to reaction with sulfuric acid, using a predictive model based on experimental reaction kinetics. We demonstrate that sulfuric acid chemistry is likely to be a significant component of the chemistry of organics in the stratosphere. We find that at least 25 of the 40 known incomplete combustion products from aviation fuel have lifetimes to reaction with aerosol sulfuric acid of at least months. We estimate that ~109 kg of long-lived products could be deposited per year in the lower stratosphere. We suggest that the high molecular weight organic compounds formed as incomplete combustion products of commercial long-haul aviation could play a significant role in the stratosphere.
      Citation: Atmosphere
      PubDate: 2022-08-01
      DOI: 10.3390/atmos13081209
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1210: Chemical Characteristics of Water-Soluble
           Inorganic Ions in Different Types of Asian Dust in Wajima, a Background
           Site in Japan

    • Authors: Pengchu Bai, Hao Zhang, Xuan Zhang, Yan Wang, Lulu Zhang, Seiya Nagao, Bin Chen, Ning Tang
      First page: 1210
      Abstract: Two Asian dust (AD) events were observed in March 2021 (AD1: 16 March 2021 00:00 UTC~17 March 2021 12:00 UTC and AD2: 28 March 2021 00:00 UTC~31 March 2021 12:00 UTC). To determine the chemical characteristics of water-soluble inorganic ions (WSIIs) in different types of Asian dust, the total suspended particulates (TSP) were collected at Kanazawa University Wajima Air Monitoring Station (KUWAMS), a background site in Japan from 27 February to 4 March, 2021. Based on the lidar observations and the backwards trajectory analysis results, AD events were divided into two types: ADN (aerosols were mainly mineral dust) and ADP (aerosols were mixtures of spherical particles). During ADs, the concentrations of the TSP and WSII increased, with the highest TSP concentration in ADN (38.6 μg/m3) and the highest WSII concentration in ADP (5.82 μg/m3). The increase in (cations)/(anions) during AD indicates that the input of AD aerosol buffered the aerosol acidity. Additionally, a significant increase in Cl depletion, along with ADN events, was found (Cl depletion = 73.8%). To comprehensively analyse the different types of ADs on WSIIs, we refer to the previous data from 2010 to 2015 at KUWAMS. As a result, the increased Cl depletion was caused by the heterogeneous reaction of HNO3 with sea salt when the air mass passed over the Japanese Sea. Additionally, the chemical form of SO42− was highly dependent on the source and pathway, while SO42− mainly came from natural soil dust in ADN and from anthropogenic emissions in ADP. The enhancement of secondary NO3− was observed in AD via the heterogeneous hydrolysis of N2O5.
      Citation: Atmosphere
      PubDate: 2022-08-01
      DOI: 10.3390/atmos13081210
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1211: Error Characteristic Analysis of
           Satellite-Based Precipitation Products over Mainland China

    • Authors: Hanjia Fu, Li Zhu, Vincent Nzabarinda, Xiaoyu Lv, Hao Guo
      First page: 1211
      Abstract: Satellite-based precipitation products (SPPs) provide valuable precipitation information for various applications. Their performance, however, varies significantly from region to region due to various data sources and production processes. This paper aims to evaluate four selected SPPs (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks Climate Data Record (PERSIANN-CDR), Multi-Source Weighted-Ensemble Precipitation (MSWEP), Gauge-adjusted Global Satellite Mapping of Precipitation (GSMAP-gauge), and Global Precipitation Measurement (GPM)) over mainland China from 2016 to 2019. Both conventional statistical indicators (e.g., correlation coefficients (CC), root mean square error (RMSE), mean absolute error (MAE), relative bias (RB), and Nash–Sutcliffe efficiency (NSE)) and categorical indicators (probability of detection (POD), probability of true detection (POTD), false-alarm rate (FAR), and critical success index (CSI)) are used for quantitative analysis. The results show that: (1) GSMAP-gauge and GPM perform best in reproducing the spatial distribution pattern of precipitation over mainland China, whereas SPPs generally underestimate summer precipitation with a high frequency of no-rain cases. (2) MSWEP has the best capability for recording precipitation events, although some parts of northern China exhibit abnormal overestimations for winter precipitation. (3) All SPPs, especially the PERSIANN-CDR, significantly underestimate the precipitation in the mountainous areas of southwestern China. (4) The GSMAP-gauge and GPM outperformed the other two of the four SPPs, in terms of the probability density function of daily precipitation for cases (PDFc) and the probability density function of daily precipitation for volume (PDFv). Generally, PERSIANN-CDR shows the poorest performance when compared to the other three products. The product’s algorithm for estimating heavy precipitation and mountainous precipitation needs further improvement.
      Citation: Atmosphere
      PubDate: 2022-08-01
      DOI: 10.3390/atmos13081211
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1212: Airborne Prokaryotic, Fungal and
           Eukaryotic Communities of an Urban Environment in the UK

    • Authors: Hokyung Song, Nicholas Marsden, Jonathan R. Lloyd, Clare H. Robinson, Christopher Boothman, Ian Crawford, Martin Gallagher, Hugh Coe, Grant Allen, Michael Flynn
      First page: 1212
      Abstract: Bioaerosols often contain human pathogens and allergens affecting public health. However, relatively little attention has been given to bioaerosols compared with non-biological aerosols. In this study, we aimed to identify bioaerosol compositions in Manchester, UK by applying high throughput sequencing methods and to find potential sources. Samples were collected at Manchester Air Quality Super Site at the Firs Environmental Research Station in November 2019 and in February 2020. Total DNA has been extracted and sequenced targeting the 16S rRNA gene of prokaryotes, ITS region of fungal DNA and 18S rRNA gene of eukaryotes. We found marine environment-associated bacteria and archaea were relatively more abundant in the February 2020 samples compared with the November 2019 samples, consistent with the North West marine origin based on wind back-trajectory analysis. In contrast, an OTU belonging to Methylobacterium, which includes many species resistant to heavy metals, was relatively more abundant in November 2019 when there were higher metal concentrations. Fungal taxa that fruit all year were relatively more abundant in the February 2020 samples while autumn fruiting species generally had higher relative abundance in the November 2019 samples. There were higher relative abundances of land plants and algae in the February 2020 samples based on 18S rRNA gene sequencing. One of the OTUs belonging to the coniferous yew genus Taxus was more abundant in the February 2020 samples agreeing with the usual pollen season of yews in the UK which is from mid-January until late April. The result from this study suggests a potential application of bioaerosol profiling for tracing the source of atmospheric particles.
      Citation: Atmosphere
      PubDate: 2022-08-01
      DOI: 10.3390/atmos13081212
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1213: Analysis of Extreme Rain and Snow Weather
           Dynamic and Water Vapor Conditions in Northeast China from 17 to 19
           November 2020

    • Authors: Chao Yu, Hengde Zhang, Yu Gong, Ning Hu, Tao Chen, Meng Wang, Fanghua Zhang, Liang He
      First page: 1213
      Abstract: Based on hourly precipitation data from 2413 national ground observation stations in China and ERA5 (0.25° × 0.25°), this study analyzes the characteristics and causes of extreme rainfall and snow in northeast China from 17–19 November 2020. The results show that extreme precipitation is mainly attributed to the abnormally strong large-scale low vortex and ground cyclone. The significant high-level and low-level coupling in areas with strong rain and snow is conducive to the continuous upward motion, which provides favorable dynamic conditions for the generation and development of extreme precipitation. The frontogenesis effect below the 850 hPa level is obvious, and the extreme precipitation period corresponds to the meeting of the north and south front areas. The symmetrical unstable atmosphere of 925 hPa~700 hPa is forced by the frontogenesis, which strengthens the oblique rising of the low layer and increases the instability, leading to the strengthened development of precipitation. For heavy rainfall and snow in early winter in China, water vapor transport is crucial. The extremely strong low-level jet also provides extremely strong water vapor conditions for the occurrence of heavy rain and snow. The analysis of the extreme rain and snow characteristics and formation mechanism of this weather process can deepen the understanding of extreme weather processes, and provide a useful reference for the research and prediction of extreme precipitation processes.
      Citation: Atmosphere
      PubDate: 2022-08-01
      DOI: 10.3390/atmos13081213
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1214: Clutter Suppression and Rotor Blade
           Feature Extraction of a Helicopter Based on Time–Frequency Flash
           Shifts in a Passive Bistatic Radar

    • Authors: Zibo Zhou, Zhihui Wang, Binbin Wang, Saiqiang Xia, Jianwei Liu
      First page: 1214
      Abstract: This paper presents a passive bistatic radar (PBR) configuration using a global navigation satellite system as an illuminator of opportunity for the rotor blade feature extraction of a helicopter. Aiming at the strong fixed clutter in the surveillance channel of the PBR, a novel iteration clutter elimination method-based singular-value decomposition approach is proposed. Instead of the range elimination method used in the classic extended cancellation algorithm, the proposed clutter elimination method distinguishes the clutter using the largest singular value and by remove this value. At the same time, the fuselage echo of the hovering helicopter can also be suppressed along with the ground clutter, then the rotor echo of this can be obtained. In the micro-motion feature extraction, the mathematic principle of the flash generation process in the time–frequency distribution (TFD) is derived first. Next, the phase compensation method is applied to achieve the time–frequency flash shift in the TFD. After this, the center frequencies of the standard flashes in the TFD are compared with the standard frequency dictionary. The mean l1 norm is utilized to estimate the feature parameters of the helicopter rotor. In the experiments, the scattering point model and the physical optics facet model demonstrate that the proposed method can obtain more accurate parameter estimation results than some classic algorithms.
      Citation: Atmosphere
      PubDate: 2022-08-01
      DOI: 10.3390/atmos13081214
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1215: Characteristics of Resuspended Road Dust
           with Traffic and Atmospheric Environment in South Korea

    • Authors: Sungjin Hong, Hojun Yoo, Jeongyeon Cho, Gyumin Yeon, Intai Kim
      First page: 1215
      Abstract: Characterizing the influencing factors of resuspended dust on paved roads according to the atmospheric environment and traffic conditions is important to provide a basis for road atmospheric pollution control measures suitable for various road environments in the future. This study attempts to identify factors in the concentration of resuspended dust according to the level of road dust loading and PM10 emission characteristics according to atmospheric weather environment and traffic conditions using real-time vehicle-based resuspended PM10 concentration measuring equipment. This study mainly focuses on the following main topics: (1) the increased level of resuspended dust according to vehicle speed and silt loading (sL) level; (2) difference between atmospheric pollution at adjacent monitoring station concentration and background concentration levels on roads due to atmospheric weather changes; (3) the correlation between traffic and weather factors with resuspended dust levels; (4) the evaluation of resuspended dust levels by road section. Based on the results, the necessity of research to more appropriately set the focus of analysis in order to characterize the resuspended dust according to changes in the traffic and weather environment in urban areas is presented.
      Citation: Atmosphere
      PubDate: 2022-08-01
      DOI: 10.3390/atmos13081215
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1216: Sub-23 nm Particle Emissions from China-6
           GDI Vehicle: Impacts of Drive Cycle and Ambient Temperature

    • Authors: Dongdong Guo, Yunshan Ge, Xin Wang, Haixu Liu, Sheng Su, Chunbo Li, Tinghong Tao
      First page: 1216
      Abstract: Both the EU and China are evaluating the feasibility of lowering the detection limit of particle number (PN) measurement to 10 nm in future legislations, making it necessary to better understand the sub-23 nm particle emission characteristics from state-of-the-art vehicles. In this study, solid PN emissions with a diameter larger than 10 nm and 23 nm (known as SPN10 and SPN23) were compared over the WLTC, RTS95, and a so-called “worst-case” real driving emission (RDE) cycle (highly dynamic/0 °C) using two certification-level particle number counters (PNCs) employing evaporation tube (ET) and catalytic stripper (CS) as volatile particle remover (VPR). The results show that SPN10 emissions were 31.7%, 27.8%, and 15.2% higher than SPN23 over the WLTC, RTS95, and laboratory RDE cycles. Sub-23 nm particles were almost not identified within the engine cold-start phase and tended to be a hot-running pollutant favored by aggressive driving styles (frequent accelerations and high engine loads), fuel-cut during decelerations, and long idles. Lower testing temperature delayed the light-off of catalyst and, therefore, significantly reduced the formation of sub-23 nm particles within the engine warm-up stage. Lowering the detection limit to 10 nm is deemed to provide more public health protection since it will guide manufacturers to pay more attention to vehicle hot-running emissions.
      Citation: Atmosphere
      PubDate: 2022-08-01
      DOI: 10.3390/atmos13081216
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1217: Branching Morphology of Negative Leaders
           with Different Propagation Directions in Natural Lightning

    • Authors: Yang Liu, Xiankang Wang, Xiaopeng Liu, Lei Liu, Gang Liu, Mingchuan Liao, Lu Qu, Bing Luo, Hansheng Cai, Junjia He, Lixue Chen
      First page: 1217
      Abstract: Comparing the branching features of negative leaders with different propagation directions could provide insight into the common tendency of development pathways and the formation pattern of branches in natural lightning. This paper reports an upward negative leader (UNL) and a downward negative leader (DNL), and their branching features are analyzed and compared. The UNL is classified into vertical (UNL-V) and horizontal (UNL-H) segments based on propagation directions at different stages. The downward negative leader (DNL) is classified into main (DNL-M) and secondary (DNL-S) channels based on whether the channel is ultimately connected to the upward connecting leader. The vital angle parameters characterizing the branching morphology are investigated. For the strong branch eventually forming a section of the main channel, its deflection angle conforms to the lognormal distribution with a mean range of 22–36°. The included angle between the branches and the deflection angle of weak branches conform to the normal distribution with means close to 40° and 60°, respectively. Moreover, the velocity for four categories of negative leaders decreases noticeably by two or more branching behaviors in a frame interval of about 80 μs. In particular, similarities in branching morphology have been found in UNL-H, UNL-V, and DNL-S, with a semblable distribution in deflection and included angles. Statistical results indicate that branches of DNL-M tend to follow the previous direction of leader development, and the branching behavior has minimal impact on its velocity.
      Citation: Atmosphere
      PubDate: 2022-08-01
      DOI: 10.3390/atmos13081217
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1218: Comparative Study on the Use of Some
           Low-Cost Optical Particulate Sensors for Rapid Assessment of Local Air
           Quality Changes

    • Authors: László Bencs, Béla Plósz, Albert Geoffrey Mmari, Norbert Szoboszlai
      First page: 1218
      Abstract: Official air quality (AQ) stations are sporadically located in cities to monitor the anthropogenic pollutant levels. Consequently, their data cannot be used for further locations to estimate hidden changes in AQ and local emissions. Low-cost sensors (LCSs) of particulate matter (PM) in a network can help in solving this problem. However, the applicability of LCSs in terms of analytical performance requires careful evaluation. In this study, two types of pocket-size LCSs were tested at urban, suburban and background sites in Budapest, Hungary, to monitor PM1, PM2.5, PM10, and microclimatic parameters at high resolutions (1 s to 5 min). These devices utilize the method of laser irradiation and multi-angle light scattering on air-suspended particulates. A research-grade AQ monitor was applied as a reference. The LCSs showed acceptable accuracy for PM species in indoor/outdoor air even without calibration. Low PM readings (<10 μg/m3) were generally handicapped by higher bias, even between sensors of the same type. The relative humidity (RH) slightly affected the PM readings of LCSs at RHs higher than 85%, necessitating field calibration. The air quality index was calculated to classify the extent of air pollution and to make predictions for human health effects. The LCSs were useful for detecting peaks stemming from emissions of motor vehicular traffic and residential cooking/heating activities.
      Citation: Atmosphere
      PubDate: 2022-08-02
      DOI: 10.3390/atmos13081218
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1219: Numerical Simulation of a
           Giant-Hail-Bearing Mediterranean Supercell in the Adriatic Sea

    • Authors: Alessandro Tiesi, Simone Mazzà, Dario Conte, Antonio Ricchi, Luca Baldini, Mario Montopoli, Errico Picciotti, Gianfranco Vulpiani, Rossella Ferretti, Mario Marcello Miglietta
      First page: 1219
      Abstract: On 10 July 2019, a giant hail-bearing supercell hit the Adriatic coast of central Italy. Hailstones with a maximum diameter of 14 cm were reported in the city of Pescara between 10:00 and 11:00 UTC. In this work, the main synoptic and mesoscale features, responsible for the triggering and the development of the supercell, are analyzed using the WRF model. The intrusion of Bora wind over the northern and central Adriatic was relevant for two reasons: on the one side, the arrival of low-level cold air produced an uplift of the pre-existing warm air and favored the triggering of convection; on the other side, the strong vertical wind shear, also due to the presence of intense upper-level southwesterlies, created conditions favorable to the formation of the supercell. The predictability of the event is also discussed, comparing simulations starting at different initial times and forced with GFS and IFS forecasts. The model results show that the runs initialized at earlier times reproduced more accurately the track and the time evolution of the supercell. The HAILCAST module of WRF was also used to simulate hailstorm characteristics, such as the average hailstone diameter. WRF-HAILCAST simulations proved to be in fair agreement with the radar reflectivity retrievals and with local reports.
      Citation: Atmosphere
      PubDate: 2022-08-02
      DOI: 10.3390/atmos13081219
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1220: Assessment of Temperature and
           Precipitation Forecasts of the WRF Model in the Bahía de Banderas
           Region (Mexico)

    • Authors: Antonio Velázquez-Ruiz, María Carolina Rodríguez-Uribe, Fátima Maciel Carrillo-González, Julio Cesar Morales-Hernández, Bartolo Cruz-Romero, Myrna Leticia Bravo-Olivas
      First page: 1220
      Abstract: The Centro de Ciencias de la Atmósfera at UNAM, in Mexico, uses the Water Research and Forecasting model to provide weather forecasts to the country. In this study, we downloaded the mean temperature and precipitation forecasts of the first 24 h generated by the WRF model in the center of the country. Only the time series of our study region (Bahía de Banderas) was processed from this database, from June to October 2010, and these data were compared with the data recorded in six stations to evaluate the performance of the model at a local level. Data from 12 stations were used to construct the observed temperature and precipitation maps for spatial validation. The results show that the model performance was partially acceptable. The correlation coefficient for hourly temperatures was an average of r=0.84. Errors were less than 2 °C with a BIAS of ±1 °C. For the accumulated 24 h precipitation, however, the results were not satisfactory (r=0.26). The model predicted only 25.7% of the rainy days observed. In terms of spatial distribution, ~2.3 times more rain was observed than had been predicted by the model.
      Citation: Atmosphere
      PubDate: 2022-08-02
      DOI: 10.3390/atmos13081220
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1221: Prediction of Monthly PM2.5 Concentration
           in Liaocheng in China Employing Artificial Neural Network

    • Authors: Zhenfang He, Qingchun Guo, Zhaosheng Wang, Xinzhou Li
      First page: 1221
      Abstract: Fine particulate matter (PM2.5) affects climate change and human health. Therefore, the prediction of PM2.5 level is particularly important for regulatory planning. The main objective of the study is to predict PM2.5 concentration employing an artificial neural network (ANN). The annual change in PM2.5 in Liaocheng from 2014 to 2021 shows a gradual decreasing trend. The air quality in Liaocheng during lockdown and after lockdown periods in 2020 was obviously improved compared with the same periods of 2019. The ANN employed in the study contains a hidden layer with 6 neurons, an input layer with 11 parameters, and an output layer. First, the ANN is used with 80% of data for training, then with 10% of data for verification. The value of correlation coefficient (R) for the training and validation data is 0.9472 and 0.9834, respectively. In the forecast period, it is demonstrated that the ANN model with Bayesian regularization (BR) algorithm (trainbr) obtained the best forecasting performance in terms of R (0.9570), mean absolute error (4.6 μg/m3), and root mean square error (6.6 μg/m3), respectively. The ANN model has produced accurate results. These results prove that the ANN is effective in monthly PM2.5 concentration predicting due to the fact that it can identify nonlinear relationships between the input and output variables.
      Citation: Atmosphere
      PubDate: 2022-08-02
      DOI: 10.3390/atmos13081221
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1222: Influence of 30–60 Days
           Intraseasonal Oscillation of East Asian Summer Monsoon on Precipitation in
           Southwest China

    • Authors: Yingsi Wang, Tiangui Xiao, Xuefeng Dong, Yueqing Li, Wei Huang, Jie Tan
      First page: 1222
      Abstract: The intraseasonal oscillation (ISO) of the East Asian summer monsoon (EASM) is an important factor affecting summer precipitation in China, but the relationship between the ISO of the EASM and summer precipitation in southwest China is currently still unclear. The relationship between the two is discussed, and the following conclusions are drawn: (1) there is a significant positive correlation between East Asian monsoon surge intensity and summer precipitation in southwest China. When the monsoon surge is stronger (weaker), the precipitation in southwest China is more (less). However, the areas where the monsoon surge has a more obvious effect on the summer precipitation in southwest China are mainly located east of 105° E, and the monsoon surge has no obvious effect on the area west of 105° E. This may be more (less) the case in monsoon surge years, when a low-frequency oscillation of 30–60 days (10–20 days) plays a dominant role. The East Asian region has a longitudinal wave train of “+ − +” (“− + −“), the western Pacific subtropical high is westerly (easterly), the South China Sea and western Pacific is affected by anticyclone (cyclone), the EASM is active (suppressive), eastern southwest China has water vapor convergence (divergence) and upward (downward) airflow. (2) We found that 1998 was a typical year for the 30–60 days ISO of the EASM. There are two obvious 30–60 days oscillation cycles. In this year, when the intensity of the ISO of the EASM increases (decreases), the range of positive precipitation anomaly region in southwest China extends (decreases). The atmospheric circulation characteristics show that, when the western Pacific subtropical high is west (east) and south (north), and there is obvious anticyclonic (cyclonic) circulation in China–western Pacific, and the EASM is stronger (weaker), which leads to more (less) precipitation in southwest China.
      Citation: Atmosphere
      PubDate: 2022-08-02
      DOI: 10.3390/atmos13081222
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1223: Investigation of a Gaussian Plume in the
           Vicinity of an Urban Cyclotron Using Helium as a Tracer Gas

    • Authors: Philippe Laguionie, Olivier Connan, Thinh Lai Tien, Sophie Vecchiola, Johann Chardeur, Olivier Cazimajou, Luc Solier, Perrine Charvolin-Volta, Liying Chen, Irène Korsakissok, Malo Le Guellec, Lionel Soulhac, Amita Tripathi, Denis Maro
      First page: 1223
      Abstract: Studies focusing on the radiological impact of fluorine 18 on populations living near to cyclotrons (<200 m) frequently assume normal distribution of atmospheric concentration for simplification purposes. On this basis, Gaussian models are used, despite their limits, as deployment requires little input data and computing resources. To estimate the ability of a Gaussian model to predict atmospheric dispersion in an urban environment, we used helium as a new passive tracer of atmospheric dispersion in the near-field range (<500 m) of the Beuvry hospital cyclotron (France). The atmospheric transfer coefficients measured in the field were compared with those modeled using a Gaussian equation. According to the results, helium is an effective tracer of atmospheric dispersion when attempting to determine atmospheric transfer coefficients ( downwind of a discharge point. The Briggs-rural, Briggs-urban and Doury Gaussian models underestimate and sometimes maximum in the prevailing weather conditions during the experiments. By compiling the results of this study with data from the literature, it appears that the maximum observed obey a power law as a function of the distance from the discharge point, for distances from the discharge point in excess of 20 m.
      Citation: Atmosphere
      PubDate: 2022-08-02
      DOI: 10.3390/atmos13081223
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1224: Comparative Analysis, Use
           Recommendations, and Application Cases of Methods for Develop Ship
           Emission Inventories

    • Authors: Yue Li, Yonglin Zhang, Jinxiang Cheng, Chaohui Zheng, Mingjun Li, Honglei Xu, Renjie Wang, Dongsheng Chen, Xiaotong Wang, Xinyi Fu, Yuehua Zhao, Rui Wu, Xiaowen Yang, Lan Shi
      First page: 1224
      Abstract: Ship exhaust emissions have been considered as a significant source of air pollution that has an adverse impact on the global climate and human health. It is of vital importance to create an accurate ship emission inventory for the purpose of formulating effective control measures. A wide range of inventory compilation methods have been proposed around the globe, and there has long been a pressing need to analyze and compare these methods in depth. This study sorted out and categorized inventory compilation methods of ship emissions in recent decades. Five main methods were compared and analyzed by their applicability, complexity, time of calculation, accuracy of results, etc. In addition, a new method was proposed to develop an emission inventory based on a vessel energy consumption reporting system. This method is believed to have the potential advantages to produce results of higher accuracy and temporal and spatial resolutions. To perform the validation, three cases at different scales were selected in part of China and surrounding maritime waters (large-scale), the Yangtze River Delta region (medium-scale), and Tianjin Port (small-scale), respectively. The analysis results show that: each of methods have different technical characteristics. Computed results significantly between methods, with the maximum deviation of up to 87%. It is advisable that the optimal method should be chosen based on the actual needs in inventory compilation and the data available. In terms of accuracy of results, Methods 1 and 5 offer moderately high accuracy; Method 2 provides average accuracy; while Methods 3 and 4 produce low accuracy. In terms of resolution of results, Methods 1 and 5 provide high-resolution temporal and spatial distribution of ship emissions; Method 2 delivers low-resolution spatial distribution; while Methods 3 and 4 are incapable of spatial distribution. In terms of applicability, Method 1 applies to the calculation of inventories of varying scales; Method 2 is more applicable to small-scale calculations, such as a port; Methods 3, 4, and 5 are more desirable for large-scale calculations, such as a country. The author recommends Methods 5, 1, 3, and 2/4 in a descending order of preference for large-scale ship emissions inventory compilations; recommends Method 5 (if accuracy is the first priority) or Method 1 (if temporal and spatial resolutions are given first priority), followed by Methods 2, 3, and 4 in a descending order of preference for small/medium-scale ship emissions inventory compilations. These results may serve to help inventory compilers choose an applicable method and support improvements in inventory compilation methods.
      Citation: Atmosphere
      PubDate: 2022-08-03
      DOI: 10.3390/atmos13081224
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1225: Calibration by Air in Polarization
           Sensing

    • Authors: Sergei N. Volkov, Ignatii V. Samokhvalov, Duk-Hyeon Kim
      First page: 1225
      Abstract: Scattered light polarization serves as an indicator and a characteristic of various processes in the atmosphere. The polarization measurements of all scattering matrix elements provide an adequate description of the optical and morphological parameters and orientation of particles in clouds. In this article, we consider the problem of the calibration of matrix polarization lidar (MPL) parameters. Calibration by air is an effective alternative to the technique for correcting optical element parameters and among the calibration parameters of the MPL optical path are the relative transmission coefficient of a two-channel receiver, the angular positions of the transmission axes of the optical elements of the transmitter and receiver units, including the polarizers and wave plates, and the retardance of wave plates. For the first time, the method of calibration by air was partially implemented in the MPL to study Asian dust in the atmosphere. We considered the calibration problem more generally and this was due to the need to calibrate different MPL modifications from stationary to mobile ones. The calibration equations have been derived in terms of instrumental vectors, and the method of their solution by the generalized least squares method has been proposed. The method has been verified on a numerical MPL model and validated using MPL measurements in Daejeon, Republic of Korea.
      Citation: Atmosphere
      PubDate: 2022-08-02
      DOI: 10.3390/atmos13081225
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1226: Atmospheric Modelling of Mercury in the
           Southern Hemisphere and Future Research Needs: A Review

    • Authors: Jorge Leiva González, Luis A. Diaz-Robles, Francisco Cereceda-Balic, Ernesto Pino-Cortés, Valeria Campos
      First page: 1226
      Abstract: Mercury is a toxic pollutant that can negatively impact the population’s health and the environment. The research on atmospheric mercury is of critical concern because of the diverse process that this pollutant suffers in the atmosphere as well as its deposition capacity, which can provoke diverse health issues. The Minamata Convention encourages the protection of the adverse effects of mercury, where research is a part of the strategies and atmospheric modelling plays a critical role in achieving the proposed aim. This paper reviews the study of modelling atmospheric mercury based on the southern hemisphere (SH). The article discusses diverse aspects focused on the SH such as the spatial distribution of mercury, its emissions projections, interhemispheric transport, and deposition. There has been a discrepancy between the observed and the simulated values, especially concerning the seasonality of gaseous elemental mercury and total gaseous mercury. Further, there is a lack of research about the emissions projections in the SH and mercury deposition, which generates uncertainty regarding future global scenarios. More studies on atmospheric mercury behaviour are imperative to better understand the SH’s mercury cycle.
      Citation: Atmosphere
      PubDate: 2022-08-02
      DOI: 10.3390/atmos13081226
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1227: Impact of NH3 Emissions on Particulate
           Matter Pollution in South Korea: A Case Study of the Seoul Metropolitan
           Area

    • Authors: Changsub Shim, Jihyun Han, Daven K. Henze, Mark W. Shephard, Liye Zhu, Nankyoung Moon, Shailesh K. Kharol, Enrico Dammers, Karen Cady-Pereira
      First page: 1227
      Abstract: We analyzed the multi-year relationship between particulate matter (PM10 and PM2.5) concentrations and possible precursors including NO2, SO2, and NH3 based on local observations over the Seoul Metropolitan Area (SMA) from 2015 to 2017. Surface NH3 concentrations were obtained from Cross-track Infrared Sounder (CrIS) retrievals, while other pollutants were observed at 142 ground sites. We found that NH3 had the highest correlation with PM2.5 (R = 0.51) compared to other precursors such as NO2 and SO2 (R of 0.16 and 0.14, respectively). The correlations indicate that NH3 emissions are likely a limiting factor in controlling PM2.5 over the SMA in a high-NOx environment. This implies that the current Korean policy urgently requires tools for controlling local NH3 emissions from the livestock industry (for example, from hog manure). These findings provide the first satellite-based trace gas evidence that implementing an NH3 control strategy could play a key role in improving air quality in the SMA.
      Citation: Atmosphere
      PubDate: 2022-08-02
      DOI: 10.3390/atmos13081227
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1228: Impact of Shale Gas Exploration and
           Exploitation Activities on the Quality of Ambient Air—The Case Study
           of Wysin, Poland

    • Authors: Janusz Jarosławski, Izabela Pawlak, Jakub Guzikowski, Aleksander Pietruczuk
      First page: 1228
      Abstract: The continuous two-year monitoring of a set of air pollutants, as well as gases directly related to shale gas exploration processes (methane, non-methane hydrocarbons, carbon dioxide), was carried out at Stary Wiec village in the vicinity (1100 m) of the shale gas wells area in Wysin (Pomeranian voivodeship, north of P44. Poland), covering the stages of preparation, drilling, hydrofracturing and closing of wells. The results of analysis of air pollution data from Stary Wiec and nearby urban and rural stations, over the period 2012–2017 (starting three years before preparations for hydraulic fracturing) indicated that Stary Wiec represents a clean rural environment with an average concentration of nitrogen oxides, carbon monoxide and particulate matter that is one of the lowest in the Pomeranian region. The aim of this study was to explore the range of potential impact of shale gas exploration on local ambient air quality. Analysis of dependence of the concentration level of pollutants on the wind direction indicated that during the drilling period, when the air was coming directly from the area of the wells, nitrogen oxide concentration increased by 13%. Increases of concentration during the hydro-fracturing period, recorded at the Stary Wiec station, were equal to 108%, 21%, 18%, 12%, 7%, 4%, 1% for nitrogen oxide, non-methane hydrocarbons, carbon monoxide, nitrogen dioxide, particulate matter, carbon dioxide and methane. The results of one-minute concentration values for the period 1–4 September 2016 showed a series of short peaks up to 7.45 ppm for methane and up to 3.03 ppm for non-methane hydrocarbons, being probably the result of operations carried out at the area of the wells.
      Citation: Atmosphere
      PubDate: 2022-08-02
      DOI: 10.3390/atmos13081228
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1229: GIS-Based Spatial Modeling of Snow
           Avalanches Using Analytic Hierarchy Process. A Case Study of the
           Šar Mountains, Serbia

    • Authors: Uroš Durlević, Aleksandar Valjarević, Ivan Novković, Nina B. Ćurčić, Mirjana Smiljić, Cezar Morar, Alina Stoica, Danijel Barišić, Tin Lukić
      First page: 1229
      Abstract: Snow avalanches are one of the most devastating natural hazards in the highlands that often cause human casualties and economic losses. The complex process of modeling terrain susceptibility requires the application of modern methods and software. The prediction of avalanches in this study is based on the use of geographic information systems (GIS), remote sensing, and multicriteria analysis—analytic hierarchy process (AHP) on the territory of the Šar Mountains (Serbia). Five indicators (lithological, geomorphological, hydrological, vegetation, and climatic) were processed, where 14 criteria were analyzed. The results showed that approximately 20% of the investigated area is highly susceptible to avalanches and that 24% of the area has a medium susceptibility. Based on the results, settlements where avalanche protection measures should be applied have been singled out. The obtained data can will help local self-governments, emergency management services, and mountaineering services to mitigate human and material losses from the snow avalanches. This is the first research in the Republic of Serbia that deals with GIS-AHP spatial modeling of snow avalanches, and methodology and criteria used in this study can be tested in other high mountainous regions.
      Citation: Atmosphere
      PubDate: 2022-08-03
      DOI: 10.3390/atmos13081229
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1230: Review: Particulate Matter Emissions from
           Aircraft

    • Authors: Bethan Owen, Julien G. Anet, Nicolas Bertier, Simon Christie, Michele Cremaschi, Stijn Dellaert, Jacinta Edebeli, Ulf Janicke, Jeroen Kuenen, Ling Lim, Etienne Terrenoire
      First page: 1230
      Abstract: The contribution of aircraft operations to ambient ultrafine particle (UFP) concentration at and around airports can be significant. This review article considers the volatile and non-volatile elements of particulate matter emissions from aircraft engines, their characteristics and quantification and identifies gaps in knowledge. The current state of the art emission inventory methods and dispersion modelling approaches are reviewed and areas for improvement and research needs are identified. Quantification of engine non-volatile particulate matter (nvPM) is improving as measured certification data for the landing and take-off cycle are becoming available. Further work is needed: to better estimate nvPM emissions during the full-flight; to estimate non-regulated (smaller) engines; and to better estimate the emissions and evolution of volatile particles (vPM) in the aircraft exhaust plume. Dispersion modelling improvements are also needed to better address vPM. As the emissions inventory data for both vPM and nvPM from aircraft sources improve, better estimates of the contribution of aircraft engine emissions to ambient particulate concentrations will be possible.
      Citation: Atmosphere
      PubDate: 2022-08-03
      DOI: 10.3390/atmos13081230
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1231: Assessment and Impacts of Air Pollution
           from Brick Kilns on Public Health in Northern Pakistan

    • Authors: Muhammad Subhanullah, Siddique Ullah, Muhammad Faisal Javed, Rafi Ullah, Tahir Ali Akbar, Waheed Ullah, Shams Ali Baig, Mubashir Aziz, Abdullah Mohamed, Raja Umer Sajjad
      First page: 1231
      Abstract: Brick kilns add enormous quantities of organic pollutants to the air that can cause serious health issues, especially in developing countries; poor air quality is associated with community health problems, yet receives no attention in Northern Pakistan. The present study, therefore, assessed the chemical composition and investigated the impacts of air pollution from brick kilns on public health. A field-based investigation of air pollutants, i.e., PM1, PM2.5 and PM10, CO2, CO, NO, NO2, H2S, and NH3 using mobile scientific instruments was conducted in selected study area locations. Social surveys were conducted to investigate the impacts of air pollution on community health. The results reveal the highest concentrations of PM1, PM2.5, and PM10, i.e., 3377, 2305, and 3567.67 µg/m3, respectively, in specific locations. Particulate matter concentrations in sampling points exceeded the permissible limits of the Pakistan National Environmental Quality Standard and, therefore, may risk the local population’s health. The highest mean value of CO2 was 529 mg/L, and other parameters, such as CO, NO, NO2, H2S, and NH3 were within the normal range. The social survey’s findings reveal that particulate matter was directly associated with respiratory diseases such as asthma, which was reported in all age groups selected for sampling. The study concluded by implementing air pollution reduction measures in brick kiln industries to protect the environment and community health. In addition, the region’s environmental protection agency needs to play an active role in proper checking and integrated management to improve air quality and protect the community from air hazards.
      Citation: Atmosphere
      PubDate: 2022-08-03
      DOI: 10.3390/atmos13081231
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1232: Assessment of Changing Agroclimatic
           Conditions in Poland Based on Selected Indicators

    • Authors: Katarzyna Szyga-Pluta
      First page: 1232
      Abstract: The change in the spatial distribution of agroclimatic conditions based on the sum of active temperatures (SAT), growing degree days (GDD), and latitude–temperature index (LTI) is discussed in this article. Data from 20 meteorological stations of IMGW-PIB (Institute of Meteorology and Water Management—National Research Institute) in Poland from the years 1966–2020 were used. The temporal and spatial diversity of mean air temperature and the chosen indices were analyzed for the period from April to October. Designating areas of diverse thermal conditions with respect to plant comfort on the basis of agroclimatic indices was attempted, together with mean air temperature and its temporal changes. The clustering, using the Ward’s method, yielded four regions with different thermal resources in Poland. The study period showed an increase in the values of all agroclimatic indices and air temperature during the growing season, suggesting an increase in the thermal resources in the territory of Poland.
      Citation: Atmosphere
      PubDate: 2022-08-03
      DOI: 10.3390/atmos13081232
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1233: Development of Two-Dimensional Visibility
           Estimation Model Using Machine Learning: Preliminary Results for South
           Korea

    • Authors: Wonei Choi, Junsung Park, Daewon Kim, Jeonghyun Park, Serin Kim, Hanlim Lee
      First page: 1233
      Abstract: A two-dimensional visibility estimation model was developed, based on random forest (RF), a machine learning-based technique. A geostatistical method was introduced into the visibility estimation model for the first time to interpolate point measurement data to gridded data spatially with a pixel size of 10 km. The RF-based model was trained using gridded visibility data, as well as meteorological and air pollution input variable data, for each location in South Korea, which were characterized by complex geographical features and high air pollution levels. Generally, relative humidity was the most important input variable for the visibility estimation (average mean decrease accuracy: 35%). However, PM2.5 tended to be the most crucial variable in polluted regions. The spatial interpolation was found to result in an additional visibility estimation error of 500 m in locations where no adjacent visibility observations within 0.2° were available. The performance of the proposed model was preliminarily assessed. Generally, the best detection performance was achieved in good visibility conditions (visibility range: 10 to 20 km). This study is the first to demonstrate a visibility estimation model based on a geostatistical method and machine learning, which can provide visibility information in locations for which no observations exist.
      Citation: Atmosphere
      PubDate: 2022-08-03
      DOI: 10.3390/atmos13081233
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1234: Identification and Risk Characteristics
           of Agricultural Drought Disaster Events Based on the Copula Function in
           Northeast China

    • Authors: Shujie Zhang, Ping Wang, Dongni Wang, Yushu Zhang, Ruipeng Ji, Fu Cai
      First page: 1234
      Abstract: Accurate feature identification of drought disaster events is required for proper risk management in agriculture. This study improved the crop water deficit index (CWDI) by including the daily meteorological, crop development stage, soil moisture content, and yield data for 1981–2020 in northeastern China. Two drought characteristic variables (drought duration and intensity) were extracted using the theory of runs to produce the improved crop water deficit index (CWDIwp). Thresholds for the bivariate indicators were also determined for agricultural drought events of varying severity. A joint distribution model for drought variables was constructed based on five types of Archimedean copulas. The joint probability and the joint recurrence period for agricultural drought events were analyzed for drought events with varying intensities in northeast China. The results suggest that the CWDIwp can reliably identify the onset, duration, and intensity of drought events over the study area and can be used to monitor agricultural drought events. The conditional probability of drought intensity (duration) decreased as the drought duration (intensity) threshold increased, whereas the drought recurrence period increased as the threshold for drought duration and intensity rose. In the period (1981–2020), drought intensity in the three Northeastern provinces showed an increasing trend in the order Jilin Province > Liaoning Province > Heilongjiang Province. The spatial distribution of the joint probability and the joint recurrence period was obvious, and the joint probability showed a decreasing distribution trend from west to east. The distribution trend for the joint probability was opposite to that of the joint recurrence period. Furthermore, the areas with high drought probability values corresponded to the areas with low values for the recurrence period, indicating that the drought occurrence probability was higher, and the recurrence period value was lower in the drought-prone areas. The high-risk drought areas (60–87%) were in western Liaoning and western Jilin, with a recurrence period of 1–3 years, whereas the low-risk areas (<40%) were located in the mountainous areas of eastern Liaoning and eastern Jilin. The joint probability and joint recurrence period for agricultural drought events of varying severity were quite different, with the probability following the order light drought > moderate drought > severe drought > extreme drought. The order for the recurrence period was light drought < moderate drought < severe drought < extreme drought. The results provide technical support for disaster prevention and mitigation in drought risk management.
      Citation: Atmosphere
      PubDate: 2022-08-03
      DOI: 10.3390/atmos13081234
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1235: The Influences of the Desert Photovoltaic
           Power Station on Local Climate and Environment: A Case Study in Dunhuang
           Photovoltaic Industrial Park, Dunhuang City, China in 2019

    • Authors: Yaping Hua, Juan Chai, Long Chen, Puxing Liu
      First page: 1235
      Abstract: Based on the meteorological observation data of air temperature, surface temperature and albedo data retrieved from remote sensing images inside and outside the photovoltaic station, as well as the measured soil moisture content and bulk density at different locations of the photovoltaic power station in 2019, the impact of large-scale desert photovoltaic power plants on climate and environment was studied. The results show that air temperature, surface temperature and albedo inside the photovoltaic power station are lower than those outside the station, which are obvious in winter and not obvious in summer. Therefore, the photovoltaic power station is a cold source and an energy sink. The soil moisture content under and between the photovoltaic arrays is larger than other sampling points, and the soil bulk density gradually decreases with the distance from the center of the photovoltaic power station. Therefore, future plans for desert photovoltaic power station construction should take into account the impacts on local climate and environment.
      Citation: Atmosphere
      PubDate: 2022-08-03
      DOI: 10.3390/atmos13081235
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1236: The Different Impact of PM2.5 on
           Atherogenesis in Overseas vs. Native Chinese in the CATHAY Study

    • Authors: Kam Sang Woo, Shu Wing Chan, Timothy C. Y. Kwok, Yue Hui Yin, Ping Chook, Chang Qing Lin, David S. Celermajer
      First page: 1236
      Abstract: Air pollution (PM2.5) has been associated with cardiovascular disease (CVD) globally and with early atherosclerosis surrogate markers in modernized China. A sizeable number of Chinese have migrated overseas, with an increase in their vulnerability to CVD. To evaluate the impact of PM2.5 air pollution on atherogenesis in native vs. overseas Chinese, we recruited 756 asymptomatic native Chinese and 507 age- and gender-matched overseas Chinese from Sydney and San Francisco. Their cardiovascular profiles were evaluated. PM2.5 was derived from remote sensing technology; atherosclerosis surrogate markers, flow-mediated dilation (FMD) and carotid intima-media thickness (IMT) were measured by ultrasound. The native Chinese had a higher proportion of smokers as well as higher blood pressure, glucose, metabolic syndrome and PM2.5 exposure (p < 0.001), but lower lipids and folate than the overseas Chinese (p < 0.0001). Carotid IMT was lower in the native Chinese (p < 0.0001), but the other vascular parameters were similar. A multivariate regression revealed that FMD in the native Chinese was related to the male gender, age and location; in the overseas Chinese, it was related to age, but not to PM2.5. Carotid IMT in the native Chinese was related to PM2.5, independent of atherosclerotic risk factors and location (R2 = 0.384, F = 34.5, p < 0.0001) whereas in the overseas Chinese, IMT was related to the male gender and age, but not to PM2.5 or overseas location (R2 = 0.282, F = 19.7, p < 0.0001). PM2.5 had a greater impact on atherogenesis in the native Chinese, independent of traditional risk factors, with implications for preventive strategies.
      Citation: Atmosphere
      PubDate: 2022-08-03
      DOI: 10.3390/atmos13081236
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1237: A Real-Time Approach to Detect PM2.5 in a
           Seriously Polluted Environment Based on Pressure Drop

    • Authors: Jialin Li, Lina Zheng, Peng Xuan, Ruiyan Huo
      First page: 1237
      Abstract: A differential pressure-based low-cost PM2.5 detection system was developed for particulate matter measurement in polluted environments. The PM2.5 monitor consists of a sampling device, a pump, a pressure sensor, and a control circuit. Two sampling devices including a foam penetration-filter tube and a cyclone-filter holder were applied. Tests were conducted in a haze environment and laboratory particle chambers with varying PM2.5 concentration. The pressure data were related to the PM2.5 concentration recorded by Dusttrak to show the calibration process and the performance of this instrument. Results showed the concentration information given by the instrument was consistent with the actual concentration in the experiment, and this instrument was more suitable for seriously polluted environment detection. Concentration oscillation of the pressure-based PM2.5 monitor caused by turbulent flow could be reduced by a longer calculation interval and data averaging in the calculation process. As a low-cost sensor, the pressure-based PM2.5 monitor still has good performance and application value for detecting high-concentration PM2.5 in atmospheric environments or workplaces.
      Citation: Atmosphere
      PubDate: 2022-08-04
      DOI: 10.3390/atmos13081237
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1238: Hydrogenation of Carbon Dioxide to
           Value-Added Liquid Fuels and Aromatics over Fe-Based Catalysts Based on
           the Fischer–Tropsch Synthesis Route

    • Authors: Qiang Wang, Kehao Hu, Ruxing Gao, Leiyu Zhang, Lei Wang, Chundong Zhang
      First page: 1238
      Abstract: Hydrogenation of CO2 to value-added chemicals and fuels not only effectively alleviates climate change but also reduces over-dependence on fossil fuels. Therefore, much attention has been paid to the chemical conversion of CO2 to value-added products, such as liquid fuels and aromatics. Recently, efficient catalysts have been developed to face the challenge of the chemical inertness of CO2 and the difficulty of C–C coupling. Considering the lack of a detailed summary on hydrogenation of CO2 to liquid fuels and aromatics via the Fischer–Tropsch synthesis (FTS) route, we conducted a comprehensive and systematic review of the research progress on the development of efficient catalysts for hydrogenation of CO2 to liquid fuels and aromatics. In this work, we summarized the factors influencing the catalytic activity and stability of various catalysts, the strategies for optimizing catalytic performance and product distribution, the effects of reaction conditions on catalytic performance, and possible reaction mechanisms for CO2 hydrogenation via the FTS route. Furthermore, we also provided an overview of the challenges and opportunities for future research associated with hydrogenation of CO2 to liquid fuels and aromatics.
      Citation: Atmosphere
      PubDate: 2022-08-04
      DOI: 10.3390/atmos13081238
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1239: The Performance of ECMWF Ensemble
           Prediction System for European Extreme Fires: Portugal/Monchique in 2018

    • Authors: Rita Durão, Catarina Alonso, Célia Gouveia
      First page: 1239
      Abstract: At the beginning of August 2018, Portugal experienced a severe heat episode over a few days that consequently increased the probability of wildfire events. Due to the advection of an anomalous very hot and dry air mass, severe fire-prone meteorological conditions were forecasted mainly over southern Portugal, in the Monchique region. Together with the significant fuel amount accumulated since the last extreme wildfire in August 2003, all the unfavorable conditions were set to drive a severe fire over this region. The Monchique fire started on 3 August 2018, being very hard to suppress and lasting for seven days, with a burnt area of 27,000 ha. Regarding the need to have operational early warning tools, this work aims to evaluate the reliability of fire probabilistic products, up to 72 h ahead, together with the use of fire radiative power products, as support tools in fire monitoring and resource activities. To accomplish this goal, we used the fire probabilistic products of the Ensemble Prediction System, provided by the Copernicus Atmosphere Monitoring Service. Among available fire danger rating systems, the Fire Weather Index and the Fine Fuels Moisture Code of the Canadian Forest Fire Weather Index System were selected to assess the meteorological fire danger. The assessment of the fire intensity was based on the Fire Radiative Energy released, considering the Fire Radiative Power, delivered in near real-time, by EUMETSAT Land Surface Analysis Satellite Applications Facility. The exceptional fire danger over southern Portugal that favors the ignition of the Monchique fire and its severity was essential driven by two important factors: (i) the anomalous fire weather danger, before and during the event; (ii) the accumulated fuel amount, since the last severe event occurred in 2003, over the region. Results show that the selected fire probabilistic products described the meteorological fire danger observed well, and the LSA-SAF products revealed the huge amount of fire energy emitted, in line with the difficulties faced by authorities to suppress the Monchique fire.
      Citation: Atmosphere
      PubDate: 2022-08-04
      DOI: 10.3390/atmos13081239
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1240: Urban Residential CO2 from Spatial and
           Non-Spatial Perspectives: Regional Difference between Northern and
           Southern China

    • Authors: Jincai Zhao, Shixin Ren
      First page: 1240
      Abstract: Urban residential carbon dioxide (CO2) emissions have increased sharply along with the rapid urbanization process. Few studies have considered the different effects of influencing factors between Northern and Southern China, and the analysis of CO2 per unit area from the spatial perspective is also rarely involved. Using the spatial Durbin model (SDM), this study aimed at revealing the influencing factors (including income, inequality, population density, urban morphology, etc.) on CO2 per capita and CO2 per unit area during 2001–2018 between Northern and Southern China. The results showed that the Northern cities had higher carbon emissions and a faster growth rate, and the high-high clusters were also mainly located in the Northern cities. The Gini coefficient was correlated adversely with CO2, while income imposed a positive effect on carbon emissions. The negative coefficients of the quadratic term of the GDP per capita demonstrated that the residential carbon emissions have the potential to decrease when the income increases to a certain level. The indirect effects of income and the Gini showed that spatial spillover effects exist. Urban population density and the ratio of residential area to built-up area had an opposite effect on CO2 per capita and CO2 per unit area, and they have a bigger impact on the CO2 per unit area. This study revealed the different roles of various factors in reducing CO2 per unit area from the spatial perspective and CO2 per capita from the non-spatial perspective between the Northern and Southern regions, which could help policymakers to design targeted mitigation measures in the residential sector in China, providing references for developing countries to jointly reduce carbon emissions to promote the mitigation of global climate change.
      Citation: Atmosphere
      PubDate: 2022-08-05
      DOI: 10.3390/atmos13081240
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1241: Study on Volatile Organic Compound (VOC)
           Emission Control and Reduction Potential in the Pesticide Industry in
           China

    • Authors: Na Wang, Mali Shi, Shengmin Wu, Xinyan Guo, Xiaohui Zhang, Ni Ni, Sha Sha, Houhu Zhang
      First page: 1241
      Abstract: The pesticide industry is one of the primary industries with large and complex VOC emissions. The present study examined the emission characteristics and whole-process control of VOCs in the pesticide industry in China by reviewing pollutant discharge permits, questionnaires, and site investigations. After evaluating the effectiveness of current treatment technologies, the potential of VOC emission reduction in China was analyzed. The results indicate that there are 41 key VOC substances in the pesticide industry that should be given considerable attention. Among treatment facilities, incineration was found to be the most efficient technology, with a removal rate of 53–98% and coverage rate of 23.3%. Multistage absorption–adsorption is a universal technology that had a removal rate of 35–95% and coverage rate of 64.14%. Multistage absorption was used most frequently, with a coverage rate of 71.99%, but its removal rate was between 16 and 85%. Pesticide factories were divided into three levels according to their pollution control capability; the comprehensive removal rates of benchmark, moderate, and poor factories were 81%, 46%, and 8%, respectively, and the emission reduction ratios for high, moderate, and low targets were 41.55%, 32.12%, and 24.32% with corresponding emission reduction costs of $0.653, $0.505, and $0.038 billion/year. The results and prospects from this study will provide support for policy development in industrial VOC emission control in China during the “14th Five-Year Plan” period.
      Citation: Atmosphere
      PubDate: 2022-08-05
      DOI: 10.3390/atmos13081241
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1242: Analysis of MONARC and ACTIVATE Airborne
           Aerosol Data for Aerosol-Cloud Interaction Investigations: Efficacy of
           Stairstepping Flight Legs for Airborne In Situ Sampling

    • Authors: Hossein Dadashazar, Ewan Crosbie, Yonghoon Choi, Andrea F. Corral, Joshua P. DiGangi, Glenn S. Diskin, Sanja Dmitrovic, Simon Kirschler, Kayla McCauley, Richard H. Moore, John B. Nowak, Claire E. Robinson, Joseph Schlosser, Michael Shook, Kenneth Lee Thornhill, Christiane Voigt, Edward L. Winstead, Luke D. Ziemba, Armin Sorooshian
      First page: 1242
      Abstract: A challenging aspect of conducting airborne in situ observations of the atmosphere is how to optimize flight plans for specific objectives and constraints associated with weather and flight restrictions. For aerosol-cloud interaction research, two recent campaigns utilized a “stairstepping” approach whereby an aircraft conducts level legs at various altitudes while moving forward with each subsequent leg: the 2019 MONterey Aerosol Research Campaign (MONARC) over the northeast Pacific and the 2020–2022 Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE) over the northwest Atlantic. We examine the homogeneity of several atmospheric variables both vertically and horizontally in the marine boundary layer with a focus on the sub-cloud environment. In well-mixed boundary layers, there was generally good horizontal and vertical homogeneity in potential temperature, winds, water vapor mixing ratio, various trace gases, and many aerosol variables. Selected aerosol variables exhibited the most variability owing to sensitivity to humidity and near-cloud conditions (supermicrometer aerosol concentrations), coastal pollution gradients (e.g., organic aerosol mass), and small spatial scale phenomena such as new particle formation (aerosol number concentration for particles with diameter >3 nm). Illustrative cases are described when stairstepping can pose issues requiring extra caution for data analysis: (i) poor vertical mixing and layers decoupled from those below; (ii) multiple cloud layers; (iii) fluctuating cloud base/top and boundary layer top heights; and (iv) horizontal variability across specific features leading to sharp gradients such as right near coastlines and over the Gulf Stream with strong sea surface temperature changes. Results from this study provide a guide both for future studies aiming to examine these mission datasets and for designing new airborne campaigns.
      Citation: Atmosphere
      PubDate: 2022-08-05
      DOI: 10.3390/atmos13081242
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1243: Using an Ensemble Filter to Improve the
           Representation of Temporal Source Variations in a Volcanic Ash Forecasting
           System

    • Authors: Meelis J. Zidikheri
      First page: 1243
      Abstract: The use of ensemble models to forecast the dispersion and transport of airborne volcanic ash in operational contexts is increasingly being explored. The ensemble members are usually constructed to represent a priori uncertainty estimates in meteorological fields and volcanic ash source parameters. Satellite data can be used to further filter ensemble members within an analysis time window by rejecting poorly performing members, leading to improved forecasts. In this study, the ensemble filtering technique is used to improve the representation of temporal source variations. Ensemble members are initially created by representing the source time variations as random functions of time that are modulated by crude initial estimates of the variations estimated from satellite imagery. Ensemble filtering is then used to remove members whose fields match poorly with observations within a specified analysis time window that are represented by satellite retrievals of volcanic ash properties such as mass load, effective radius, and cloud top height. The filtering process leads to an ensemble with statistics in closer agreement with the observations. It is shown in the context of the 30 May 2014 Sangeang Api eruption case study that this method leads to significantly enhanced forecasting skill beyond the analysis time window—about 20% improvement on average—when compared to a system that assumes constant emission rates for the duration of the eruption, as is the case in many operational volcanic ash forecasting systems.
      Citation: Atmosphere
      PubDate: 2022-08-05
      DOI: 10.3390/atmos13081243
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1244: A Parameterized Design Method for
           Building a Shading System Based on Climate Adaptability

    • Authors: Shiliang Wang, Qun Zhang, Peng Liu, Rui Liang, Zitian Fu
      First page: 1244
      Abstract: The relationship between environmental factors and the indoor physical environment is very close, and external shading is considered an effective way to adjust the interaction between the indoor and outdoor environment. However, determining how to set up an external shading system remains a notable issue. In the early design stage, architects have adopted the process of designing the form and function first and then checking whether those characteristics meet the energy-saving specifications. However, this process involves a great deal of repetitive and inefficient work and cannot meet the requirements of energy savings and emission reductions in a global context. Therefore, it is particularly important to seek a design method that combines energy-saving design with form-based design. This paper takes a construction project in Northwest China as its research object. In this study, typical parametric models for external shading are designed. Furthermore, indoor performance objectives based on light environment analysis are proposed, and Ladybug Tools and the genetic algorithm (GA) are used for optimization and verification. The optimization results show that the adaptive shading system can significantly reduce the total cooling energy consumption per unit area in summer by 20% and 15%, respectively. The comfort level throughout the year improved by 14.8% (air conditioning on) and 4.7% (air conditioning off). This study proposes a fast and effective shading parametric design method for architects in the early stage, improving the efficiency and accuracy of performance-based design.
      Citation: Atmosphere
      PubDate: 2022-08-05
      DOI: 10.3390/atmos13081244
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1245: Study of Chemical Substances Emitted
           during Paint Manufacturing through VOC Speciation

    • Authors: Min-Gyu Kim, Ji Yun Lee, Jeong Hun Kim, Hyo Eun Lee, Sung Hwan Cho, Jeong Ung Yu, Cheon Woong Kang, Kyong Whan Moon
      First page: 1245
      Abstract: Volatile organic compounds (VOCs) emitted from the paint manufacturing industry include substances that are highly volatile, such as toluene, and highly carcinogenic, such as benzene. In the Republic of Korea, the emission of volatile organic compounds is regulated under the Clean Air Conservation Act, but it is found that individual substances are systematically insufficient. Although the Pollutant Release and Transfer Register (PRTR) is maintained to report the expected emissions from each plant every year, actual measurements are not performed. This study measured and analyzed VOCs at the site fenceline boundary. The ratio of PRTR and VOCs speciation results for xylene and toluene was similar to that of xylene 29% and toluene 28%, but ethylbenzene accounted for 2% in PRTR. Still, the actual measurement result showed a big difference of 11%. Because it is a solvent that is treated in large quantities in the resin manufacturing process and the reactivity of ethylbenzene, it is vaporized at high temperature and high pressure, resulting in many measurements. This study classified a large amount of VOCs emitted through the fence line monitoring system in the paint manufacturing industry and confirmed which VOCs were emitted the most. We compared whether this produced similar results to the actual emission survey method conducted by the EPA. Some substances have produced similar results, but certain substances have significant differences. This indicates that priority VOCs should be selected for each location through continuous measurement.
      Citation: Atmosphere
      PubDate: 2022-08-05
      DOI: 10.3390/atmos13081245
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1246: Variations in Summer Precipitation
           according to Different Grades and Their Effects on Summer Drought/Flooding
           in Haihe River Basin

    • Authors: Shanjun Cheng, Jun Xie, Ning Ma, Sujie Liang, Jun Guo, Ning Fu
      First page: 1246
      Abstract: The variations in summer precipitation according to different grades and their effects on summer drought/flooding in the Haihe River basin were analyzed using the daily precipitation data from 161 meteorological stations from 1972 to 2021. The results showed that the number of rainy days (NRD) in summer in the Haihe River basin significantly declined in the past 50 years, mainly due to the reduction in the number of light-rain days. The precipitation amount (PA) exhibited prominent interdecadal characteristics, showing an upward tendency in the past 20 years accompanied by a remarkable increase in the proportion of torrential rain. The NRD in the northern part of the basin significantly decreased, while the PA in the southeast showed an increasing trend. Summer drought/flooding was strongly linked to the changes in the NRD and was predominantly affected by intense precipitation, with contribution rates of 5.5%, 16.8%, 31.2%, and 46.5% from light, moderate, heavy, and torrential rain, respectively. The effects of torrential rain increased in recent decades, particularly in the flooding scenarios. In addition, July was the critical period for summer drought/flooding, with the major influence of heavy and torrential rain. The most intense summer rainfall event in the Haihe River basin could contribute from 15% to 29% of total precipitation, resulting in changes in the severity and state of summer drought/flooding, which indicated that the precipitation process had a decisive impact on seasonal drought/flooding. Therefore, when predicting summer precipitation in the Haihe River basin, it is necessary to pay attention to the intense rainfall events during critical periods.
      Citation: Atmosphere
      PubDate: 2022-08-05
      DOI: 10.3390/atmos13081246
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1247: Investigation of the Gas-Phase Reaction
           of Nopinone with OH Radicals: Experimental and Theoretical Study

    • Authors: Gisèle El Dib, Angappan Mano Priya, Senthilkumar Lakshmipathi
      First page: 1247
      Abstract: Monoterpenes are the most essential reactive biogenic volatile organic compounds. Their removal from the atmosphere leads to the formation of oxygenated compounds, such as nopinone (C9H14O), one of the most important first-generation β-pinene oxidation products that play a pivotal role in environmental and biological applications. In this study, experimental and theoretical rate coefficients were determined for the gas-phase reaction of nopinone with hydroxyl radicals (OH). The absolute rate coefficient was measured for the first time using a cryogenically cooled cell along with the pulsed laser photolysis–laser-induced fluorescence technique at 298 K and 7 Torr. The hydrogen abstraction pathways were found by using electronic structure calculations to determine the most favourable H-abstraction position. Pathway 5 (bridgehead position) was more favourable, with a small barrier height of −1.23 kcal/mol. The rate coefficients were calculated based on the canonical variational transition state theory with the small-curvature tunnelling method (CVT/SCT) as a function of temperature. The average experimental rate coefficient (1.74 × 10−11 cm3 molecule−1 s−1) was in good agreement with the theoretical value (2.2 × 10−11 cm3 molecule−1 s−1). Conclusively, the results of this study pave the way to understand the atmospheric chemistry of nopinone with OH radicals.
      Citation: Atmosphere
      PubDate: 2022-08-05
      DOI: 10.3390/atmos13081247
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1248: Assessing the Impact of Lightning NOx
           Emissions in CMAQ Using Lightning Flash Data from WWLLN over the
           Contiguous United States

    • Authors: Daiwen Kang, Christian Hogrefe, Golam Sarwar, James D. East, J. Mike Madden, Rohit Mathur, Barron H. Henderson
      First page: 1248
      Abstract: Comparison of lightning flash data from the National Lightning Detection Network (NLDN) and from the World Wide Lightning Location Network (WWLLN) over the contiguous United States (CONUS) for the 2016–2018 period reveals temporally and spatially varying flash rates that would influence lightning NOx (LNOx) production due to known detection efficiency differences especially during summer months over land (versus over ocean). However, the lightning flash density differences between the two networks show persistent seasonal patterns over geographical regions (e.g., land versus ocean). Since the NLDN data are considered to have higher accuracy (lightning detection with >95% efficiency), we developed scaling factors for the WWLLN flash data based on the ratios of WWLLN to NLDN flash data over time (months of year) and space. In this study, sensitivity simulations using the Community Multiscale Air Quality (CMAQ) model are performed utilizing the original data sets (both NLDN and WWLLN) and the scaled WWLLN flash data for LNOx production over the CONUS. The model performance of using the different lightning flash datasets for ambient O3 and NOx mixing ratios that are directly impacted by LNOx emissions and the wet and dry deposition of oxidized nitrogen species that are indirectly impacted by LNOx emissions is assessed based on comparisons with ground-based observations, vertical profile measurements, and satellite products. During summer months, the original WWLLN data produced less LNOx emissions (due to its lower lightning detection efficiency) compared to the NLDN data, which resulted in less improvement in model performance than the simulation using NLDN data as compared to the simulation without any LNOx emissions. However, the scaled WWLLN data produced LNOx estimates and model performance comparable with the NLDN data, suggesting that scaled WWLLN may be used as a substitute for the NLDN data to provide LNOx estimates in air quality models when the NLDN data are not available (e.g., due to prohibitive cost or lack of spatial coverage).
      Citation: Atmosphere
      PubDate: 2022-08-06
      DOI: 10.3390/atmos13081248
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1249: Measuring Greenhouse Gas Emissions from
           Point Sources with Mobile Systems

    • Authors: Mengyang Cai, Huiqin Mao, Cuihong Chen, Xvpeng Wei, Tianqi Shi
      First page: 1249
      Abstract: The traditional least squares method for the retrieval of CO2 emissions from CO2 emission sources is affected by the nonlinear characteristics of the Gaussian plume model, which leads to the optimal estimation of CO2 emissions easily falling into local minima. In this study, ACA−IPFM (ant colony algorithm and interior point penalty function) is proposed to remedy the shortcomings of the traditional least squares method, which makes full use of the global search property of the ant colony algorithm and the local exact search capability of the interior point penalty function to make the optimal estimation of CO2 emissions closer to the global optimum. We evaluate the errors of several parameters that are most likely to affect the accuracy of the CO2 emission retrieval and analyze these errors jointly. These parameters include wind speed measurement error, wind direction measurement error, CO2 concentration measurement error, and the number of CO2 concentration measurements. When the wind speed error is less than 20%, the inverse error of CO2 concentration emission is less than 1% and the uncertainty is less than 3%, when the wind direction error is less than 55 degrees, the inverse error is less than 1% and the uncertainty is less than 3%, when the CO2 concentration measurement error is less than 10%, the inverse error is less than 1% and the uncertainty is less than 3.3%, and when the measurement quantity is higher than 60, the inverse error is less than 1% and the uncertainty is less than 3%. In addition, we simulate the concentration observations on different paths under the same conditions, and invert the CO2 emissions based on these simulated values. Through the retrieval results, we evaluate the errors caused by different paths of measurements, and have demonstrated that different paths are affected by different emission sources to different degrees, resulting in different inversion accuracies for different paths under the same conditions in the end, which can provide some reference for the actual measurement route planning of the mobile system. Combined with the characteristics of the agility of the mobile system, ACA−IPFM can extend the monitoring of CO2 emissions to a wider area.
      Citation: Atmosphere
      PubDate: 2022-08-06
      DOI: 10.3390/atmos13081249
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1250: Narratives and Benefits of Agricultural
           Technology in Urban Buildings: A Review

    • Authors: Michael G. Parkes, Duarte Leal Azevedo, Tiago Domingos, Ricardo F. M. Teixeira
      First page: 1250
      Abstract: The literature on agricultural technology (ag-tech) for urban agriculture (UA) offers many narratives about its benefits in addressing the challenges of sustainability and food security for urban environments. In this paper, we present a literature review for the period 2015–2022 of research carried out on currently active UA installations. We aim to systematise the most common narratives regarding the benefits of controlled environment agriculture (CEA) and soil-less growing systems in urban buildings and assess the existence of peer-reviewed data supporting these claims. The review was based on 29 articles that provided detailed information about 68 active UA installations depicting multiple types of ag-tech and regions. The results show that most research conducted for commercial UA-CEA installations was carried out in North America. Standalone CEA greenhouses or plant factories as commercial producers for urban areas were mostly found in Asia and Europe. The most often cited benefits are that the integration of multiple CEA technologies with energy systems or building climate systems enables the transfer of heat through thermal airflow exchange and CO2 fertilisation to improve commercial production. However, this review shows that the data quantifying the benefits are limited and, therefore, the exact environmental effects of CEA are undetermined.
      Citation: Atmosphere
      PubDate: 2022-08-06
      DOI: 10.3390/atmos13081250
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1251: Hydrogen Sulfide Emission Properties from
           Two Large Landfills in New York State

    • Authors: Alexandra M. Catena, Jie Zhang, Roisin Commane, Lee T. Murray, Margaret J. Schwab, Eric M. Leibensperger, Joseph Marto, Mackenzie L. Smith, James J. Schwab
      First page: 1251
      Abstract: Landfills are a source of malodors, greenhouse gases, harmful pollutants, pests, noise, and litter. To reduce their impact on neighboring communities, landfill facilities and the policies they follow must reduce emissions of trace gases such as hydrogen sulfide (H2S) and methane (CH4). However, a comprehensive understanding of the spatial variability of both pollutants at landfills should first be established to obtain a clear picture of emissions at landfills. This study measured the mixing ratios of H2S and CH4 at two landfills in New York State (Fresh Kills Landfill and Seneca Meadows Landfill) in November 2021 using laser-based methods deployed in a mobile lab. H2S emission fluxes were estimated based on a mass balance calculation. The highest mixing ratios of both H2S and CH4 were measured at Fresh Kills Landfill, at up to 7 parts per billion (ppb) and ~140 parts per million (ppm), respectively, yet these values resulted in a low ΔH2S/ΔCH4 ratio, at approximately 5.2 ± 2.6 × 10−5 mol mol−1 and a H2S emission flux of 0.02 ± 0.01 mg m−2 day−1. The highest ΔH2S/ΔCH4 ratio was observed at the Seneca Meadows Landfill at 8.6 ± 4.3 × 10−4 mol mol−1 and yielded a H2S emission flux estimate of 17.7 ± 12.9 mg m−2-day−1. The variability in mixing ratios and ΔH2S/ΔCH4 ratios measured at the landfills can be attributed to various factors, including facility operations and design, landfill age, meteorology, types of waste, and pH levels, but further multiday measurements are needed at each landfill to improve emission estimates and determine a more accurate and resolute reasoning behind these variations.
      Citation: Atmosphere
      PubDate: 2022-08-06
      DOI: 10.3390/atmos13081251
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1252: Statistical Research on
           Seismo-Ionospheric Ion Density Enhancements Observed via DEMETER

    • Authors: Lin Zheng, Rui Yan, Michel Parrot, Keying Zhu, Zeren Zhima, Dapeng Liu, Song Xu, Fangxian Lv, Xuhui Shen
      First page: 1252
      Abstract: In this paper, in order to investigate the correlation between seismic activity and ionospheric density variation, nighttime ion density (Ni) data from IAP onboard the Detection of Electro-Magnetic Emissions Transmitted from Earthquake Regions (DEMETER) satellite from 2005 to 2010 are used to carry out statistical analysis. Only data with kp ≤ 3 are selected to avoid density perturbations due to magnetic activity. The aftershocks are also carefully removed. The earthquake-related data were further strictly screened, and the apparent position of anomalies were normalized using Dobrovolsky’s radius. Real and pseudorandom earthquakes are compared and analyzed. The statistical results show that the postseismic effect is obvious; the Ni enhancements are more focused 3–5 days, 9–10 days, and 13–14 days before the earthquake; as the magnitude of earthquake increases, the apparent range and intensity of the ion density enhancements is also increased; and for medium–strong earthquakes, the position of disturbance will exceed Dobrovolsky’s radius.
      Citation: Atmosphere
      PubDate: 2022-08-07
      DOI: 10.3390/atmos13081252
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1253: Data Quality Analysis of Multi-GNSS
           Signals and Its Application in Improving Stochastic Model for Precise
           Orbit Determination

    • Authors: Chao Huang, Shuli Song, Na Cheng, Zhitao Wang
      First page: 1253
      Abstract: Currently, there are more Global Navigation Satellite System (GNSS) signals available for civilians. Many types of GNSS receivers have been updated and several new receivers have been developed for new signals. To know about the performance of these signals and receivers and their stochastic model for data processing, in this study, the data quality of all GNSS signals, especially the new signals are analyzed, and two modified stochastic models with observation noise statistics (STA) and post-fit residuals (RES) are formed. The results show that for all the new signals, the corresponding carrier phase noise is at the same level as other old signals. The pseudorange noise of B2a, L5, E5a, and E5b is within 4 cm and significantly smaller than other signals for receivers without a smooth algorithm, and the multipath error of these signals is about 0.1 m which is also better than other signals. For B1C, the pseudorange multipath error is about 0.4 m, which is close to L1 and E1. Stochastic models are validated for precise orbit determination (POD). Compared with the empirical stochastic model (EMP), both modified models are helpful to reduce the mean unit weight square error and obtain high accuracy orbits with reduced iteration. The 3D orbit accuracy improvement can reach 0.27 cm (7%) for the STA model, and 0.40 cm (10%) for the RES model when compared with the final products from the international GNSS service (IGS). For BDS-3 POD by using B1C and B2a observations, the improvements in the 3D orbit consistency of two adjacent three-day solutions are 0.21 cm (3%) for the STA model and 0.29 cm (4%) for the RES model. In addition, the STA model based on the observation noise of globally distributed stations is less affected by stations with problematic observations and with reduced computation burden.
      Citation: Atmosphere
      PubDate: 2022-08-07
      DOI: 10.3390/atmos13081253
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1254: Narx Neural Networks Models for
           Prediction of Standardized Precipitation Index in Central Mexico

    • Authors: Rafael Magallanes-Quintanar, Carlos E. Galván-Tejada, Jorge I. Galván-Tejada, Santiago de Jesús Méndez-Gallegos, Antonio García-Domínguez, Hamurabi Gamboa-Rosales
      First page: 1254
      Abstract: Some of the effects of climate change may be related to a change in patterns of rainfall intensity or scarcity. Therefore, humanity is facing environmental challenges due to an increase in the occurrence and intensity of droughts. The forecast of droughts can be of great help when trying to reduce the adverse effects that the scarcity of water brings, particularly in agriculture. When evaluating the conditions of water scarcity, as well as in the identification and characterization of droughts, the use of predictive models of drought indices could be a very useful tool. In this research, the utility of Artificial Neural Networks with exogenous inputs was tested, with the aim of predicting the monthly Standardized Precipitation Index in 4 regions (Semi-desert, Highlands, Canyons and Mountains) of north-central México using predictor data from 1979 to 2014. The best model was found using the scaled conjugate gradient backpropagation algorithm as the optimization method and was set to the following architecture: 6-25-1 network. The correlation coefficient of predicted and observed Standardized Precipitation Index values for the test dataset was between 0.84 and 0.95. As a result, the Artificial Neural Network models performed successfully in predicting Standardized Precipitation Index at the four analyzed regions. The developed and tested Artificial Neural Network models in this research suggest remarkable prediction abilities of the monthly Standardized Precipitation Index in the study region.
      Citation: Atmosphere
      PubDate: 2022-08-08
      DOI: 10.3390/atmos13081254
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1255: Accelerated Glacier Mass Loss over
           Svalbard Derived from ICESat-2 in 2019–2021

    • Authors: Junhao Wang, Yuande Yang, Chuya Wang, Leiyu Li
      First page: 1255
      Abstract: The glaciers in Arctic Archipelago of Svalbard, located in the hotspot of global warming, are sensitive to climate change. The assessment of glacier mass balance in Svalbard is one of the hotspots in Arctic research. In this study, we use the laser altimetry ICESat-2 data to investigate the elevation and mass change of Svalbard from 2019 to 2021 by a hypsometric approach. It is shown that the Svalbard-wide elevation change rate is −0.775 ± 0.225 m yr−1 in 2019–2021, corresponding to the mass change of −14.843 ± 4.024 Gt yr−1. All regions exhibit a negative mass balance, and the highest mass loss rates are observed at Northwestern Spitsbergen. Compared with ICESat/ICESat-2 (2003–2008 to 2019) and Cryosat-2 (2011–2017) periods, the elevation change from 2019 to 2021 has accelerated, with an increase by 158.3% and 31.5%, respectively, leading to equilibrium line altitude increasing to 750 m. Among the seven subregions, four are accelerated. It is shown that the overall accelerated glacier mass loss in Svalbard is expected to be caused by increasing surge events and temperature rise.
      Citation: Atmosphere
      PubDate: 2022-08-08
      DOI: 10.3390/atmos13081255
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1256: Atmospheric Degradation of Two
           Hydrofluoroketones: Theoretical Rate Constants for the Gas-Phase
           OH-Oxidation of HFK-447mcc and HFK-465mc

    • Authors: Luís Pedro Viegas
      First page: 1256
      Abstract: Accurate calculation of rate constants for gas-phase OH-oxidation reactions of fluorinated compounds is crucial for the understanding of atmospheric processes that are subject of the Kigali Agreement. Here, we have determined two such rate constants for two hydrofluoroketones, HFK-447mcc and HFK-465mc. The calculations were performed with a cost-effective multiconformer transition state theory protocol coupled with the constrained transition state randomization sampling method. The calculated rate constants of k(HO•+HFK-447mcc)=3.1×10−15cm3molecule−1s−1 and k(HO•+HFK-465mc)=3.2×10−14cm3molecule−1s−1 at 298.15 K imply an atmospheric lifetime of 10 years and 1 year, respectively. To our knowledge, these rate constants have never been determined experimentally or theoretically, and the similarity between the ratios of these two rate constants and of the well-studied acetone and diethyl ketone suggest the validity of our approach toward obtaining accurate rate constants and branching ratios.
      Citation: Atmosphere
      PubDate: 2022-08-08
      DOI: 10.3390/atmos13081256
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1257: Methodology and Case Study for Validation
           of Aircraft-Induced Clouds from Hyperspectral Imagery

    • Authors: Amy Tal Rose, Lance Sherry, Donglian Sun
      First page: 1257
      Abstract: Aircraft-Induced Clouds (AICs), colloquially called contrails, form from the emission of soot from jet engines during cruise flight in favorable atmospheric conditions. AICs absorb, scatter, and reflect shortwave and longwave radiation. This radiative transfer has a cooling effect during the day; however, the night experiences an overwhelming warming effect, which leads to an overall warming effect on Earth, contributing to anthropogenically propelled climate change. Reducing AICs significantly mitigates aviation’s contribution to climate change by reducing the disruption in Earth’s radiation budget. Researchers have proposed AIC Abatement Programs (AAPs) to increase cruise flight levels without additional fuel burn. In order to effectively implement AAPs, it is crucial to be able to accurately identify AICs from publicly available aerial and satellite imagery. This study aims at the identification of AICs from hyperspectral imagery to help the effective implementation of an AAP and to mitigate climate change. This paper describes a method for the hyperspectral analysis of aerial images in order to accurately identify AICs through a case study based in West Virginia. The results show that both the Adaptive Coherence Estimator and the Matched Filter algorithms based on unique in-scene spectra were successful in the isolation of the AICs from other cloud types and the background. It is found that AICs can be identified with 84% confidence in this case study. The method, a case study, and future works are provided.
      Citation: Atmosphere
      PubDate: 2022-08-08
      DOI: 10.3390/atmos13081257
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1258: A Systematic Literature Review on
           Controlled-Environment Agriculture: How Vertical Farms and Greenhouses Can
           Influence the Sustainability and Footprint of Urban Microclimate with
           Local Food Production

    • Authors: Christos Vatistas, Dafni Despoina Avgoustaki, Thomas Bartzanas
      First page: 1258
      Abstract: The rapidly growing population and increasing urbanization have created the need to produce more food and transport it safely to urban areas where the majority of global consumers live. Open-field agriculture and food distribution systems have a lot of food waste, and, in parallel, the largest percentage of available arable land is already occupied. In most cases, food produced by compatible agricultural methods needs to be frozen and travel several miles until it reaches the consumer, with high amounts of greenhouse gas (GHG) emissions produced by this process, making it an unsustainable method with huge amounts of CO2 emissions related with fresh food products. This research contains an extensive literature review based on 165 international publications (from 2006–2022) describing and analyzing the efficiency and impact of controlled-environment agriculture (CEA) methods, and more precisely, greenhouses (GHs) and vertical farms (VFs), in the environmental footprint of food production and consumption. Based on various publications, we could draw the conclusion that VFs could highly influence a greener transition to the sustainability of urban consumption with reduced CO2 emissions sourcing from food transportation and limited post-harvest processes. However, there is a significant demand for further energy efficiency, specifically when it comes to artificial lighting operations inside VFs. A large-scale implementation of VFs that operate with renewable energy sources (RES) could lead to significant urban decarbonization by providing the opportunity for integrated energy–food nexus systems. Under this direction, VFs could optimize the way that cities interact with meeting the food and energy demand in densely urbanized areas.
      Citation: Atmosphere
      PubDate: 2022-08-08
      DOI: 10.3390/atmos13081258
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1259: Anthropogenic Vehicular Heat and Its
           Influence on Urban Planning

    • Authors: Ruth M. Grajeda-Rosado, Elia M. Alonso-Guzmán, Carlos Escobar-Del Pozo, Carlos J. Esparza-López, Cristina Sotelo-Salas, Wilfrido Martínez-Molina, Max Mondragon-Olan, Alfonso Cabrera-Macedo
      First page: 1259
      Abstract: Anthropogenic heat (QF) is one of the parameters that contributes to the urban heat island (UHI) phenomenon. Usually, this variable is studied holistically, among other anthropogenic flux such as industrial, vehicular, buildings, and human metabolism, due to the complexity of data collection through field measurements. The aim of this paper was to weigh vehicular anthropogenic heat and its impact on the thermal profile of an urban canyon. A total of 108 simulations were carried out, using the ANSYS Fluent ® software, incorporating variables such as the number of vehicles, wind speed, urban canyon orientation, and urban canyon aspect ratio. The results were compared with a database of 61 American cities in 2015 and showed that orientation is the main factor of alteration in vehicular heat flow, increasing it in a range of 2 °C to 6.5 °C, followed by the wind speed (1.2 to 2.2 m/s), which allows for decreases of 1 to 3.8 °C. The exploration of these variables and their weighing in the definition of urban street canyon temperature profiles at the canopy level of urban structures provides valuable information on the hygrothermal comfort of its inhabitants; its appropriate quantification can be an example of many urban energy balances altering processes.
      Citation: Atmosphere
      PubDate: 2022-08-08
      DOI: 10.3390/atmos13081259
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1260: Electric Field-Driven Air Purification
           Filter for High Efficiency Removal of PM2.5 and SO2: Local Electric Field
           Induction and External Electric Field Enhancement

    • Authors: Jian Li, Qingyun Sun, Zhongxin Ping, Yihong Gao, Peiyu Chen, Fangzhi Huang
      First page: 1260
      Abstract: Removal rate and durability are the two most important parameters of an ideal air purification filter to remove inhalable particles and toxic gases. Here, based on the interaction of a local electric field and an external electric field, a novel coaxial core–shell CuO@NH2-MIL-53(Al) nanowire array was synthesized on a rigid copper net, which was used to remove PM2.5 and SO2 simultaneously. The removal rates of PM2.5 by the filter with and without an external electric field can reach 98.72% and 44.41%, respectively, and the adsorption capacity of SO2 can reach 4.87 mol/m2. After repeated filtration and cleaning for 10 cycles, the air pollution removal efficiency can be kept almost stable.
      Citation: Atmosphere
      PubDate: 2022-08-09
      DOI: 10.3390/atmos13081260
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1261: The Impact of El-Niño and
           La-Niña on the Pre-Monsoon Convective Systems over Eastern India

    • Authors: Rajesh Kumar Sahu, Goutam Choudhury, Naresh Krishna Vissa, Bhishma Tyagi, Sridhara Nayak
      First page: 1261
      Abstract: El-Niño and La-Niña are believed to change the intensity and frequencies of extreme weather events globally. The present study aims to analyse the impact of El-Niño and La-Niña on the lightning activities of cloud systems and their associated precipitation and thermodynamic indices over the Eastern India regions (Odisha, Jharkhand, and West Bengal) during the pre-monsoon season (March–May). Eastern India receives catastrophic thunderstorm events during the pre-monsoon season. The results suggest that the number of lightning flashes was higher in the El-Niño years than in the La-Niña periods, which helps convective activities to be developed over the study region. The precipitation variations showed similar patterns during El-Niño and La-Niña periods, but the magnitudes were higher in the latter. Results from the analysis of thermodynamic indices show that, during the La-Niña phase, the convective available potential energy (CAPE), convective inhibition (CIN), severe weather threat index (SWEAT), humidity index (HI), and total totals index (TTI) values increased, while the cross total index (CTI) and K index (KI) decreased. In contrast, the vertical total index (VTI) and Boyden index (BI) values showed less significant changes in both El-Niño and La-Niña periods. The anomalies of flash rate densities over most parts of our domain were positive during the El-Niño years and negative during the La-Niña years. Precipitation anomalies had a higher positive magnitude during the La-Niña phase, but had spatial variability similar to the El-Niño phase. The anomalies of most of the thermodynamic indices also showed noticeable differences between El-Niño and La-Niña periods, except for the HI index. El-Niño periods showed higher lightning and increased values of associated thermodynamic indices over eastern India, indicating more pronounced convective systems.
      Citation: Atmosphere
      PubDate: 2022-08-09
      DOI: 10.3390/atmos13081261
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1262: Comparison of Methods for Sampling
           Particulate Emissions from Tires under Different Test Environments

    • Authors: David Hesse, Toni Feißel, Miles Kunze, Eric Bachmann, Thomas Bachmann, Sebastian Gramstat
      First page: 1262
      Abstract: Traffic-related emissions are strongly criticised by the public because they contribute to climate change and are classified as hazardous to health. Combustion engine emissions have been regulated by limit values for almost three decades. There is currently no legal limit for non-exhaust emissions, which include tire wear particle emissions and resuspension. As a result, the percentage of total vehicle emissions has risen continuously. Some of the particles emitted can be assigned to the size classes of particulate matter (≤10 µm) and are therefore of particular relevance to human health. The literature describes a wide range of concepts for sampling and measuring tire wear particle emissions. Because of the limited number of studies, the mechanisms involved in on-road tests and their influence on the particle formation process, particle transport and the measuring ability can only be described incompletely. The aim of this study is to compare test bench and on-road tests and to assess the influence of selected parameters. The first part describes the processes of particle injection and particle distribution. Based on this, novel concepts for sampling and measurement in the laboratory and in the field are presented. The functionality and the mechanisms acting in each test environment are evaluated on the basis of selected test scenarios. For example, emissions from external sources, the condition of the road surface and the influence of the driver are identified as influencing factors. These analyzes are used to illustrate the complexity and limited reproducibility of on-road measurements, which must be taken into account for future regulations.
      Citation: Atmosphere
      PubDate: 2022-08-09
      DOI: 10.3390/atmos13081262
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1263: Health Exposure Assessment of
           Firefighters Caused by PAHs in PM4 and TSP after Firefighting Operations

    • Authors: Joanna Rakowska, Marzena Rachwał, Agata Walczak
      First page: 1263
      Abstract: Among the many different chemicals in the air, polycyclic aromatic hydrocarbons (PAHs) pose a serious threat to human health. Firefighters are exposed to them both during fire suppression and in fire vehicles and fire stations due to inhalation of the fumes from contaminated clothing and personal protective equipment. This study aimed to estimate the exposure and cancer risk caused by suspended particulate matter and PAHs present in these particles. Air samples were collected for 4 months in a garage of the fire station in a small town, located in an urban–rural area. PAH concentrations were measured using the gas chromatography method with mass spectrometry (GC/MS). The concentration of PM4 (particulate matter with a diameter below 4µm) and TSP (total suspended particulate) in the fire station garage was 7 and 9 times higher than outside, respectively. The calculated values of health hazard risks associated with the exposure to PAHs in PM4 and TSP are: a toxic equivalent (TEQ) up to 10.36 and 23.3, incremental lifetime cancer risk (ILCR) up to 3.45 and 4.65 and hazard quotient (HQ) up to 0.42 and 0.57, respectively. A significantly increased risk of cancers in the professional group of firefighters was found.
      Citation: Atmosphere
      PubDate: 2022-08-10
      DOI: 10.3390/atmos13081263
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1264: Assessment of Drought Severity and Their
           Spatio-Temporal Variations in the Hyper Arid Regions of Kingdom of Saudi
           Arabia: A Case Study from Al-Lith and Khafji Watersheds

    • Authors: Nuaman Ejaz, Jarbou Bahrawi
      First page: 1264
      Abstract: The goal of this study is to calculate meteorological drought using the Standard Precipitation Index (SPI) and Standard Precipitation Evapotranspiration Index (SPEI) for the Al-Lith and Khafji basins of the Kingdom of Saudi Arabia (KSA) from 2001 to 2020. The in situ (rain gauges, RGs) and Integrated Multi-satellite Retrievals for GPM (IMERG) data are used in the current study. The meteorological drought is monitored across the AL-Lith and Khafji watersheds. The climate of the Khafji watershed is like the climate of Al-Lith to some extent. Still, due to complex terrain, Al-Lith receives relatively high precipitation and has a higher average temperature than the Khafji watershed. Results show that the total drought periods observed are 166 and 139 months based on SPEI and SPI on a multiple time scale (1, 3, 6, and 12 months) in the Al-Lith watershed, respectively. While, based on SPEI and SPI, the Khafji watershed experienced a drought of 129 and 72 months, respectively. This finding indicates that the SPEI-calculated drought is more severe and persistent in both watersheds than the SPI-calculated drought. Additionally, the correlation coefficient (CC) between SPI and SPEI is investigated; a very low correlation is observed at a smaller scale. CC values of 0.86 and 0.93 for Al-Lith and 0.61 and 0.79 for the Khafji watershed are observed between SPEI-1/SPI-1 and SPEI-3/SPI-3. However, the correlation is significant at high temporal scales, i.e., 6 and 12 months, with CC values of 0.95 and 0.98 for Al-Lith and 0.86 to 0.94 for the Khafji watershed. Overall, the study compared the performance of IMERG with RGs to monitor meteorological drought, and IMERG performed well across both watersheds during the study period. Therefore, the current study recommends the application of IMERG for drought monitoring across data-scarce regions of KSA. Furthermore, SPEI estimates a more severe and long-lasting drought than SPI because of the temperature factor it considers.
      Citation: Atmosphere
      PubDate: 2022-08-10
      DOI: 10.3390/atmos13081264
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1265: Modelling Cloud Cover Climatology over
           Tropical Climates in Ghana

    • Authors: Felicia Dogbey, Prince Junior Asilevi, Joshua Fafanyo Dzrobi, Hubert Azoda Koffi, Nana Ama Browne Klutse
      First page: 1265
      Abstract: Clouds play a crucial role in Earth’s climate system by modulating radiation fluxes via reflection and scattering, and thus the slightest variation in their spatial coverage significantly alters the climate response. Until now, due to the sparse distribution of advanced observation stations, large uncertainties in cloud climatology remain for many regions. Therefore, this paper estimates total cloud cover (TCC) by using sunshine duration measured in different tropical climates in Ghana. We used regression tests for each climate zone, coupled with bias correction by cumulative distribution function (CDF) matching, to develop the estimated TCC dataset from nonlinear empirical equations. It was found that the estimated percentage TCC, 20.8–84.7 ± 3.5%, compared well with station-observed TCC, 21.9–84.4 ± 3.5%, with root mean square errors of 1.08–9.13 ± 1.8% and correlation coefficients of 0.87–0.99 ± 0.03. Overall, spatiotemporal characteristics were preserved, establishing that denser clouds tended to prevail mostly over the southern half of the forest-type climate during the June–September period. Moreover, the model and the observations show a non-normality, indicating a prevalence of above-average TCC over the study area. The results are useful for weather prediction and application in meteorology.
      Citation: Atmosphere
      PubDate: 2022-08-10
      DOI: 10.3390/atmos13081265
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1266: Long-Term Variability of Aerosol
           Concentrations and Optical Properties over the Indo-Gangetic Plain in
           South Asia

    • Authors: Imran Shahid, Muhammad Zeeshaan Shahid, Zhi Chen, Zunaira Asif
      First page: 1266
      Abstract: Emissions of atmospheric pollutants are rapidly increasing over South Asia. A greater understanding of seasonal variability in aerosol concentrations over South Asia is a scientific challenge and has consequences due to a lack of monitoring and modelling of air pollutants. Therefore, this study investigates aerosol patterns and trends over some major cities in the Indo-Gangetic Plain of the South Asia, i.e., Islamabad, Lahore, Delhi, and Dhaka, by using simulations from the Modern -Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) model and satellite measurements (Moderate Resolution Imaging Spectroradiometer, (MODIS)) from 2000 to 2020. The results show that seasonal MODIS–aerosol optical depth (AOD) during 2000−2020 in Lahore is 0.5, 0.52, 0.92, and 0.71, while in Islamabad 0.25, 0.32, 0.45, and 0.38, in Delhi 0.68, 0.6, 1.0, and 0.77, and in Dhaka 0.79, 0.75, 0.78 and 0.55 values are observed during different seasons, i.e., winter, spring, summer, and autumn, respectively. The analysis reveals a significant increase in aerosol concentrations by 25%, 24%, 19%, and 14%, and maximum AOD increased by 15%, 14%, 19%, and 22% during the winter of the last decade (2011–2020) over Islamabad, Lahore, Delhi, and Dhaka, respectively. In contrast, AOD values decreased during spring by −5%, −12%, and −5 over Islamabad, Lahore, and Delhi, respectively. In Dhaka, AOD shows an increasing trend for all seasons. Thus, this study provides the aerosol spatial and temporal variations over the South Asian region and would help policymakers to strategize suitable mitigation measurements.
      Citation: Atmosphere
      PubDate: 2022-08-10
      DOI: 10.3390/atmos13081266
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1267: Evaluating Skill of the
           Keetch–Byram Drought Index, Vapour Pressure Deficit and Water
           Potential for Determining Bushfire Potential in Jamaica

    • Authors: Candice Charlton, Tannecia Stephenson, Michael A. Taylor, Jayaka Campbell
      First page: 1267
      Abstract: Bushfire management which incorporates fire potential indices is still in its infancy in Jamaica and the Caribbean. In this study three bushfire potential indices—Keetch–Byram Drought Index (KBDI), Vapour Pressure Deficit (VPD) and Water Potential (Ψw)—are calculated for south-central Jamaica where bushfire frequencies are highest. The skills of the indices are evaluated using their representation of the normalised bushfire climatology, monthly and seasonal (December–March/DJFM; April–June/AMJ; July–August/JA and September–November/SON) fire variability for the periods 2013–2017, 2010–2019 and 2001–2019. Fire data are obtained from the MODIS C6 Archive and Jamaica Fire Brigade (JFB). The relationship between the fire indices and large-scale oceanic and atmospheric features are also examined. The results suggest that Ψw exhibits strong correlations with the MODIS and JFB climatologies and represents well the maxima in March and July and the local minima in May–June and October. Ψw and VPDI also show good hit rates for moderate and high-risk categories in south-central Jamaica (though with relatively high false alarm rates). Regression models premised on Ψw and VPD respectively show good skill in representing AMJ (R2 = 57–58%), SON (R2 = 57–58%) and JA (R2 = 57–60%) fire variability. Variability during DJFM is poorly captured by any fire index. Although the KBDI represents the normalised climatology reasonably well its peaks occur one month later, that is, in April and August. KBDI exhibits strong and statistically significant correlations with JFB and MODIS climatologies, but seasonal models premised on KBDI do not perform as well as for the other two indices except in JA. All indices had a statistically significant relationship on both monthly and 1 month lag time scales for NINO3 and TNA-NINO3 large-scale climate indices. The indices, and in particular Ψw, show good prospects for producing seasonal bushfire outlooks for south-central Jamaica and Jamaica in general. These results also suggest the usefulness of monitoring large-scale oceanic patterns as part of the monitoring framework for bushfires in the island.
      Citation: Atmosphere
      PubDate: 2022-08-10
      DOI: 10.3390/atmos13081267
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1268: Reactivity and Loss Mechanisms of NO3 and
           N2O5 at a Rural Site on the North China Plain

    • Authors: Dan Wang, Pinhua Xie, Renzhi Hu, Zhiyan Li, Hao Chen, Huawei Jin
      First page: 1268
      Abstract: NO3, NO2, O3, and relevant parameters were measured at a rural site on the North China Plain during June 2014. During the campaign, the average concentrations of NO3 and N2O5 were 4.8 ± 3.3 pptv and 30.5 ± 35.4 pptv, respectively. The average NO3 production rate was 1.03 ± 0.48 ppbvh−1, and the steady-state lifetimes of NO3 and N2O5 were 26 s and 162 s, respectively, indicating that the NOx chemistry in the rural site during summer was active. The uptake coefficient range of N2O5 was 0.023 to 0.118, with an average value of 0.062 ± 0.035. Meanwhile, the fitting for kNO3 was 0.013 ± 0.016 s−1, corresponding to the shorter NO3 lifetime below 1 min. The results show that the indirect loss pathways caused by the heterogonous uptake of N2O5 contributed 64–90% of the overall NO3 loss, with an average of 81%, suggesting that the N2O5 heterogeneous reaction dominated the nocturnal NOx loss over this region.
      Citation: Atmosphere
      PubDate: 2022-08-10
      DOI: 10.3390/atmos13081268
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1269: The Impacts of Low-Carbon City Pilot
           Projects on Carbon Emissions in China

    • Authors: Zhengge Tu, Yu Cao, Jiayang Kong
      First page: 1269
      Abstract: Here, we assessed the impact of low-carbon city pilot projects on carbon emissions across China through application of a series of econometric techniques to data on these three waves of low-carbon city construction. Our baseline results are obtained from a difference-in-differences estimator, comparing cities with and without introducing low-carbon city pilot projects, and show that low-carbon city pilot projects reduce carbon emissions by about 2 percentage points. We found a similar impact of low-carbon city pilot projects on carbon emissions when we controlled for the estimated propensity of a city to launch the low-carbon city pilot project based on a series of urban characteristics. We obtained comparable estimates when we instrumented whether a city would launch the low-carbon city pilot projects using regional waves of low-carbon city pilot projects. Our results also show that low-carbon city pilot projects have a larger impact on carbon emissions in northern, poorer, and less industrialized cities than those with the opposite characteristics. We found little evidence for the persistence of this impact on carbon emissions, implying that it is necessary to dynamically adjust the low-carbon city pilot projects for cities that have launched the project.
      Citation: Atmosphere
      PubDate: 2022-08-10
      DOI: 10.3390/atmos13081269
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1270: Characterization of Propane Fueled
           Flames: A Significant Source of Brown Carbon

    • Authors: Jai Prakash, Kalyan Mitra, Harsh Raj Mishra, Xiangyu Pei, Evert Ljungström, Ravi Kant Pathak
      First page: 1270
      Abstract: In this study, we developed a framework for interpreting the in situ morphological properties of black carbon (BC, also referred to as “soot” due to combustion relevance) mixed with primary organic aerosol. Integration of the experiment considering primary organic aerosol (POA) evaporation from the soot particles was examined using a Differential mass–mobility analyzer (DMA) and showed the untold story of the mixing of BC and POA. We also hypothesize that morphological transformation of soots and determined such as (i) the evaporation of externally and internally mixed POA led to a decline in the particle number and size of monodisperse aerosol; (ii) presence of externally mixed BC was interpreted from the occurrence of two peaks of soot upon heating; (iii) heat-induced collapse of the BC core possibly resulted from the evaporation of material from the voids and effect of heat; (iv) volume equivalent to changes in the mobility diameter represented evaporation of POA from the surface and collapse upon heating. POA constituted a high fraction (20–40% by mass) of aerosol mass from these flames and was predominantly (i.e., 92–97% by mass) internally mixed with BC. POA was found to be highly light absorptive, i.e., an Ångström absorption exponent (AAE) value of (in general) >1.5 was estimated for BC + POA at 405/781 nm wavelengths. Interestingly, a much more highly absorptive POA [mass absorption cross-section (MAC)-5 m2 g−1] at 405 nm was discovered under a specific flame setting, which was comparable to MACs of BC particles (8–9 m2 g−1).
      Citation: Atmosphere
      PubDate: 2022-08-10
      DOI: 10.3390/atmos13081270
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1271: The Ionospheric Responses from Satellite
           Observations within Middle Latitudes to the Strong Magnetic Storm on
           25–26 August 2018

    • Authors: Xuemin Zhang, Lei Dong, Lei Nie
      First page: 1271
      Abstract: The multi observations from the China Seismo-Electromagnetic Satellite (CSES) were presented and analyzed during the biggest magnetic storm on 25–26 August in the quiet solar activity year of 2018, together with the Swarm satellite and GNSS TEC (Global Navigation Satellite System, Total Electron Content). The whole tempo-spatial evolutional process was demonstrated in electromagnetic fields and in-situ plasma parameters within the whole magnetic storm time period of three phases, the main phase with quick decrease in SYM-H, the quick recovery phase, and the slow recovery phase. Strong correlations were revealed in time and space between electric fields and electron density. During the main phase, the penetrated electric field was the major factor to induce the injection of electric fields to low latitudes even to the equator and contribute to constructing the double peaks of Ne at altitudes above 500 km of CSES in daytime. In the quick recovery phase, Ne depletion was found in low middle and low latitudes in the daytime, associated with a quick decrease in solar wind dynamic pressure, but in the nightside Ne maintained or increased. Due to the high solar wind speed following the quick recovery phase, it controlled the enhancements in an electric field below 1125 Hz at medium and low latitudes in daytime and produced similar structures in a 225 Hz electric field with the mid-latitude trough of Ne in local nighttime and maintained their equator-ward movements in this time period. Ne/TEC showed typical local time-dependence in this magnetic storm, which illustrated that although the electron density in the ionosphere was mainly caused by this solar activity event, local background environments must also not be ignored for their final evolutional modes.
      Citation: Atmosphere
      PubDate: 2022-08-11
      DOI: 10.3390/atmos13081271
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1272: Impacts of Air Pollution and Dampness on
           Occupant Respiratory Health in Unplanned Houses: A Case Study of Bandung,
           Indonesia

    • Authors: Hanief Sani, Tetsu Kubota, Jumpei Sumi, Usep Surahman
      First page: 1272
      Abstract: This paper presents the results from field measurements and household surveys on the severity of indoor mold risk and its impact on respiratory health in a typical unplanned neighborhood of kampungs in Bandung, Indonesia. Mold risk was investigated using fungal risk detectors (n = 102), while air pollution levels were established with total suspended particulate (TSP) and particulate matter (PM2.5) (n = 38). The self-reported prevalence of respiratory diseases was obtained using a questionnaire form (ATS-DLD-78) (n = 599). The results showed that respiratory health problems were higher in the rainy season, particularly among children. Most houses suffered from severe mold risk, primarily due to extreme humid weather conditions, especially during rainy season (97%) where water leakage was prevalent (60%). In addition, the TSP and PM2.5 concentrations exceeded the WHO standards in most kampung houses, where around 58% of the houses recorded higher outdoor mean PM2.5 concentrations than indoors. Further, the path analysis showed that allergies followed by humidity rate and smell, which were affected by window-opening duration, directly impacted children’s respiratory health. Smoking behavior and building-related health problems, due to exposure to outdoor air pollution, affected the respiratory health of those aged 15 years old and over.
      Citation: Atmosphere
      PubDate: 2022-08-11
      DOI: 10.3390/atmos13081272
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1273: Estimating PM2.5 Concentrations Using an
           Improved Land Use Regression Model in Zhejiang, China

    • Authors: Sheng Zheng, Chengjie Zhang, Xue Wu
      First page: 1273
      Abstract: Fine particulate matter (PM2.5) pollution affects the environment and poses threat to human health. The study of the influence of land use and other factors on PM2.5 is crucial for the rational development and utilization of territorial space. To explore the intrinsic mechanism between PM2.5 pollution and related factors, this study used the land use regression (LUR) model, and introduced geographically weighted regression (GWR), and random forest (RF) to optimize the basic LUR model. The basic LUR model was constructed to predict the annual average PM2.5 concentrations using three elements: artificial surfaces, forest land, and wind speed as explanatory variables, with adjusted R2 of 0.645. The improved LUR models based on GWR and RF, with an adjusted R2 of 0.767 and 0.821, respectively, show better fitting effects. The LUR simulation results show that the PM2.5 pollution in the northern Zhejiang is more serious and concentrated. The concentrations are also higher in regions such as the river valley plains in central Zhejiang and the coastal plains in southeastern Zhejiang. These findings show that pollution emissions should be further reduced and environmental protection should be strengthened.
      Citation: Atmosphere
      PubDate: 2022-08-11
      DOI: 10.3390/atmos13081273
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1274: Emission Characteristics and the
           Environmental Impact of VOCs from Typical FRP Manufacture Industry

    • Authors: Run Hao, Song Xue, Hao Sun, Tao Yang, Hailin Wang
      First page: 1274
      Abstract: The VOC emission characteristics of the typical fiber-reinforced plastics (FRPs) industry were studied for an assessment of the impact on the environment. The results showed that the VOC emissions of the typical FRP industry mainly come from grille, sheet, winding, molding, and pultrusion process links, including ketones, aldehydes, alcohols, and benzene series. The benzene series’ concentration represented by styrene was much higher than that of other species. The generation potential of ozone and the SOA in the typical production process were evaluated: in terms of ozone impact, the OFP values of the winding process were the highest, accounting for 65.9% of the total contribution. For the component contribution, the OFP contribution of the benzene series represented by styrene was far more than that of other VOC species, and the styrene mainly came from the use of unsaturated resin. In terms of the SOA impact, the pultrusion process contributed the most to the generation of SOA, accounting for 63.9% of the total SOA contribution. In terms of the component contribution, the contribution of SOA mainly came from the benzene series, accounting for nearly 95% of the total contribution of VOCs. Therefore, FRP enterprises should give priority to controlling the emission of the benzene series.
      Citation: Atmosphere
      PubDate: 2022-08-11
      DOI: 10.3390/atmos13081274
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1275: Warming Climate and Elevated CO2 Will
           Enhance Future Winter Wheat Yields in North China Region

    • Authors: Muhammad Rizwan Shoukat, Dongyu Cai, Muhammad Shafeeque, Muhammad Habib-ur-Rahman, Haijun Yan
      First page: 1275
      Abstract: The projected climate change substantially impacts agricultural productivity and global food security. The cropping system models (CSM) can help estimate the effects of the changing climate on current and future crop production. The current study evaluated the impact of a projected climate change under shared socioeconomic pathways (SSPs) scenarios (SSP2-4.5 and SSP5-8.5) on the grain yield of winter wheat in the North China Plain by adopting the CSM-DSSAT CERES-Wheat model. The model was calibrated and evaluated using observed data of winter wheat experiments from 2015 to 2017 in which nitrogen fertigation was applied to various growth stages of winter wheat. Under the near-term (2021–2040), mid-term (2041–2060), and long-term (2081–2100) SSP2-4.5 and SSP5-8.5 scenarios, the future climate projections were based on five global climate models (GCMs) of the sixth phase of the Coupled Model Intercomparison Project (CMIP6). The GCMs projected an increase in grain yield with increasing temperature and precipitation in the near-term, mid-term, and long-term projections. In the mid-term, 13% more winter wheat grain yield is predicted under 1.3 °C, and a 33 mm increase in temperature and precipitation, respectively, compared with the baseline period (1995–2014). The increasing CO2 concentration trends projected an increase in average grain yield from 4 to 6%, 4 to 14%, and 2 to 34% in the near-term, mid-term, and long-term projections, respectively, compared to the baseline. The adaptive strategies were also analyzed, including three irrigation levels (200, 260, and 320 mm), three nitrogen fertilizer rates (275, 330, and 385 kg ha−1), and four sowing times (September 13, September 23, October 3, and October 13). An adaptive strategy experiments indicated that sowing winter wheat on October 3 (traditional planting time) and applying 275 kg ha−1 nitrogen fertilizer and 260 mm irrigation water could positively affect the grain yield in the North China Plain. These findings are beneficial in decision making to adopt and implement the best management practices to mitigate future climate change impacts on wheat grain yields.
      Citation: Atmosphere
      PubDate: 2022-08-11
      DOI: 10.3390/atmos13081275
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1276: A Methodological Review of Tools That
           Assess Dust Microbiomes, Metatranscriptomes and the Particulate Chemistry
           of Indoor Dust

    • Authors: Yousef Nazzal, Fares M. Howari, Aya Yaslam, Jibran Iqbal, Lina Maloukh, Lakshmi Kesari Ambika, Ahmed A. Al-Taani, Ijaz Ali, Eman M. Othman, Arshad Jamal, Muhammad Naseem
      First page: 1276
      Abstract: Indoor house dust is a blend of organic and inorganic materials, upon which diverse microbial communities such as viruses, bacteria and fungi reside. Adequate moisture in the indoor environment helps microbial communities multiply fast. The outdoor air and materials that are brought into the buildings by airflow, sandstorms, animals pets and house occupants endow the indoor dust particles with extra features that impact human health. Assessment of the health effects of indoor dust particles, the type of indoor microbial inoculants and the secreted enzymes by indoor insects as allergens merit detailed investigation. Here, we discuss the applications of next generation sequencing (NGS) technology which is used to assess microbial diversity and abundance of the indoor dust environments. Likewise, the applications of NGS are discussed to monitor the gene expression profiles of indoor human occupants or their surrogate cellular models when exposed to aqueous solution of collected indoor dust samples. We also highlight the detection methods of dust allergens and analytical procedures that quantify the chemical nature of indoor particulate matter with a potential impact on human health. Our review is thus unique in advocating the applications of interdisciplinary approaches that comprehensively assess the health effects due to bad air quality in built environments.
      Citation: Atmosphere
      PubDate: 2022-08-11
      DOI: 10.3390/atmos13081276
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1277: Effects of Low-Frequency Oscillation at
           Different Latitudes on Summer Precipitation in Flood and Drought Years in
           Southern China

    • Authors: Lu Liu, Liping Li, Guanhua Zhu
      First page: 1277
      Abstract: Based on the daily precipitation data from 753 meteorological stations provided by the National Meteorological Information Center (China) and the daily reanalysis data from NCEP/NCAR and ERA5 during the period from 1980 to 2020, the low-frequency (LF) precipitation characteristics of the typical summer flood and drought years in southern China and their relation to the LF atmospheric circulation at different latitudes are compared and analyzed, and extended-range forecasting signals are given. The results show that: (a) In both flood and drought years, summer precipitation in southern China is controlled by 10–20 day oscillation (quasi-biweekly oscillation, QBWO); (b) LF convection is active in southern China in both flood and drought years, but the convective center is southward in flood years, and the vertical meridional circulation is stronger. The key circulation systems of 500 hPa LF height field in flood and drought years include LF “two ridges and one trough” and LF “+”, “−”, “+” East Asia Pacific (EAP) teleconnection wave train in mid-high latitudes of Eurasia. However, the “two ridges and one trough” in flood years are more westward and meridional than in drought years, and the LF Subtropical High is stronger and more extensive, with more significant westward extension; (c) In flood (drought) years, there is northerly and then westerly (central westerly) dry-cold, northeasterly wet-cold, southwesterly (none), and southeasterly (including southerly across the equator) wet-warm water vapor channels. The sources of dry and wet cold air in flood (drought) years are located near Novaya Zemlya (the eastern West Siberian Plain), the Yellow Sea, and the Bohai Sea (Sea of Japan). Additionally, the sources of wet-warm water vapor include the Arabian Sea, the Bay of Bengal, the western Pacific Ocean, and the sea area of northeastern Australia (the western Pacific Ocean and the northern sea area of Australia); and (d) The LF predictive signals of outgoing longwave radiation (OLR) appear on −11 days, while the signals of the 500 hPa height field are on −9 days. There are both westward and eastward propagation predictive signals in flood years, and only westward spread signals in drought years.
      Citation: Atmosphere
      PubDate: 2022-08-11
      DOI: 10.3390/atmos13081277
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1278: Temporal and Spatial Variation of Land
           Surface Temperature in Recent 20 Years and Analysis of the Effect of Land
           Use in Jiangxi Province, China

    • Authors: Qiongbing Xiong, Wenbo Chen, Shiqi Luo, Lei He, Haifeng Li
      First page: 1278
      Abstract: Under the background of global warming, it is of great significance to study the temporal and spatial evolution of land surface temperature (LST) on long-time scale and the impacts of land use in the fields of urban thermal environment and regional climate change. Based on MODIS LST long time series remote sensing data, the temporal and spatial evolution characteristics of pixel-wise LST in Jiangxi Province, the middle inland province of China from 2000 to 2020 were analyzed by using Theil-Sen + Mann-Kendall, coefficient of variation and Hurst index, and the response of LST to land use was identified by combining the contribution and diversity index. The results showed as follows: (1) LST was generally distributed as "high in Middle-East-West-South and low in North-northwest-southeast direction". LST showed an overall downward trend, indicating a weakening of the warming trend. The dynamic trend of LST was characterized by more descending than ascending tendency. The dynamic stability showed a coexistence of high and low fluctuation tendency, with a higher proportion of medium and low fluctuation areas having obvious spatial differences. The overall dynamic sustainability was characterized by uncertainty of future change trend. (2) The LST were strongly affected by land use in the past 20 years. Firstly, the areas of high LST were mostly located in construction land and unused land, while the areas of low LST were mostly in water area and forest land. However, forest land and water area of high temperature were gradually turned to construction land later on. Secondly, the land use structure and pattern had an strong effects on LST. With the increase of the area proportion of different land use, the LST showed significant differences. The more complex the spatial pattern of land use, the more obvious its impact on LST. The research results will provide some reference for the regions with the same characteristics as Jiangxi Province to deal with LST under the background of global climate change.
      Citation: Atmosphere
      PubDate: 2022-08-11
      DOI: 10.3390/atmos13081278
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1279: Coherent Backscattering by Large Ice
           Crystals of Irregular Shapes in Cirrus Clouds

    • Authors: Natalia Kustova, Alexander Konoshonkin, Victor Shishko, Dmitry Timofeev, Anatoli Borovoi, Zhenzhu Wang
      First page: 1279
      Abstract: All elements of the scattering matrix have been numerically studied for particles of irregular shapes whose size is much larger than incident wavelength. The calculations are performed in the physical optics approximation for a particle size of 20 μm at a wavelength of 0.532 μm. Here the scattered intensity reveals the backscattering coherent peak. It is shown that the polarization elements of the matrix reveal the surges within the backscattering peak. The angular width of the surges does not practically depend on particle shape, but depends on the particle size. It is shown that these surges are created by interference between the conjugate scattered waves propagating in the inverse directions. The results obtained are of interest for interpretation of lidar measurements in cirrus clouds.
      Citation: Atmosphere
      PubDate: 2022-08-12
      DOI: 10.3390/atmos13081279
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1280: A Systematic Review on Farmers’
           Adaptation Strategies in Pakistan toward Climate Change

    • Authors: Naeem Saddique, Muhammad Jehanzaib, Abid Sarwar, Ehtesham Ahmed, Muhammad Muzammil, Muhammad Imran Khan, Muhammad Faheem, Noman Ali Buttar, Sikandar Ali, Christian Bernhofer
      First page: 1280
      Abstract: Pakistan is among the countries that are highly vulnerable to climate change. The country has experienced severe floods and droughts during recent decades. The agricultural sector in Pakistan is adversely affected by climate change. This systematic review paper set out to analyze the existing literature on adaptation measures at the farm level toward climate change in Pakistan. Adopting a Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method, a total of 62 articles were identified from the Web of Science and Scopus databases. The review paper indicates that the main adaptation strategies adopted by farmers are as follows: changing cropping practices, changing farm management techniques, advanced land use management practices, and nonagriculture livelihood options. Further, this review shows the factors influencing the farmer’s adaptation measures to climate change. Influencing factors were examined and classified into three groups: demographic, socioeconomic, and resources and institutional. Barriers hindering farmers’ adaptive capacity were identified as lack of access to information and knowledge, lack of access to extension services, lack of access to credit facility, and lack of farm resources.
      Citation: Atmosphere
      PubDate: 2022-08-11
      DOI: 10.3390/atmos13081280
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1281: Occupational Microbial Risk among
           Embalmers

    • Authors: Loïc Wingert, Maximilien Debia, Stéphane Hallé, Geneviève Marchand
      First page: 1281
      Abstract: Embalmers are exposed to many pathogens present in bodily fluids. However, the risk posed by these pathogens has yet to be defined in terms of the nature of the hazard and the intensity of the exposure. The objective of this project was to monitor the exposure of embalmers to biological particles in real time and to characterize the microbiota found in the air during embalming activities in three thanatopraxy laboratories. An innovative approach, using a laser-induced fluorescence aerosol spectrometer (WIBS-NEO), made it possible to measure the concentrations and particle size distributions of the aerosols (biological and non-biological) emitted during embalming. At the same time, an Andersen impactor was used to sample the culturable microbiota present in the air and perform its characterization. The preferential aerosolization of the biological (fluorescent) fraction during embalming procedures, which was compared to the non-biological (non-fluorescent) fraction, showed that most of the tasks performed by the embalmer are likely to lead to microbial exposure via bioaerosols. The concentrations measured represented the equivalent of 2000 to 10,000 biological particles inhaled per minute. Although Mycobacterium tuberculosis was not identified in the air during this study, the presence of Streptococcus pneumoniae in some of the samples demonstrated that if a pathogen is present in the lungs of the deceased it can be aerosolized and inhaled by the embalmers. The size distribution showed that embalmers are exposed to a high proportion of small particles in the aerosols produced during their work. Thus, the respirable/total ratios calculated are between 58% and 78%. Finally, the detection of airborne Enterobacter, Serratia, Leclercia, and Hafnia tended to demonstrate the aerosolization of intestinal bacteria and their possible inhalation or ingestion. Due to the difficulty of identifying the presence of pathogenic agents before embalming, the presence of faecal bacteria in the air, the proximity of the embalmer to the body, and the limitations associated with the dilution of contaminants by general ventilation in the near field, local ventilation must be provided. Otherwise, minimally, a fitted N95-type respirator should be recommended.
      Citation: Atmosphere
      PubDate: 2022-08-12
      DOI: 10.3390/atmos13081281
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1282: Modelling Hourly Particulate Matter
           (PM10) Concentrations at High Spatial Resolution in Germany Using Land Use
           Regression and Open Data

    • Authors: Wallek, Langner, Schubert, Schneider
      First page: 1282
      Abstract: Air pollution is a major health risk factor worldwide. Regular short- and long-time exposures to ambient particulate matter (PM) promote various diseases and can lead to premature death. Therefore, in Germany, air quality is assessed continuously at approximately 400 measurement sites. However, knowledge about this intermediate distribution is either unknown or lacksa high spatial–temporal resolution to accurately determine exposure since commonly used chemical transport models are resource intensive. In this study, we present a method that can provide information about the ambient PM concentration for all of Germany at high spatial (100 m × 100 m) and hourly resolutions based on freely available data. To do so we adopted and optimised a method that combined land use regression modelling with a geostatistical interpolation technique using ordinary kriging. The land use regression model was set up based on CORINE (Coordination of Information on the Environment) land cover data and the Germany National Emission Inventory. To test the model’s performance under different conditions, four distinct data sets were used. (1) From a total of 8760 (365 × 24) available h, 1500 were randomly selected. From those, the hourly mean concentrations at all stations (ca. 400) were used to run the model (n = 566,326). The leave-one-out cross-validation resulted in a mean absolute error (MAE) of 7.68 μg m−3 and a root mean square error (RMSE) of 11.20 μg m−3. (2) For a more detailed analysis of how the model performs when an above-average number of high values are modelled, we selected all hourly means from February 2011 (n = 256,606). In February, measured concentrations were much higher than in any other month, leading to a slightly higher MAE of 9.77 μg m−3 and RMSE of 14.36 μg m−3, respectively. (3) To enable better comparability with other studies, the annual mean concentration (n = 413) was modelled with a MAE of 4.82 μg m−3 and a RMSE of 6.08 μg m−3. (4) To verify the model’s capability of predicting the exceedance of the daily mean limit value, daily means were modelled for all days in February (n = 10,845). The exceedances of the daily mean limit value of 50 μg m−3 were predicted correctly in 88.67% of all cases. We show that modelling ambient PM concentrations can be performed at a high spatial–temporal resolution for large areas based on open data, land use regression modelling, and kriging, with overall convincing results. This approach offers new possibilities in the fields of exposure assessment, city planning, and governance since it allows more accurate views of ambient PM concentrations at the spatial–temporal resolution required for such assessments.
      Citation: Atmosphere
      PubDate: 2022-08-12
      DOI: 10.3390/atmos13081282
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1283: Research Progress on Heterogeneous
           Reactions of Pollutant Gases on the Surface of Atmospheric Mineral
           Particulate Matter in China

    • Authors: Fei Zheng, Faqin Dong, Lin Zhou, Yunzhu Chen, Jieyu Yu, Xijie Luo, Xingyu Zhang, Zhenzhen Lv, Xue Xia, Jingyuan Xue
      First page: 1283
      Abstract: Haze is the phenomenon of visibility degradation caused by extinction effects related to the physicochemical properties of atmospheric particulate matter (APM). Atmosphere heterogeneous reactions can alter the physicochemical properties of APM. Therefore, it is important to understand the atmospheric heterogeneous reactions of APM in order to reveal the cause of haze. Herein, the current situation, developmental trend, source, and composition of APM pollution in China are reviewed. Additionally, we introduce the reaction characteristics and key chemical processes of common inorganic, organic, and mixed pollutant gases on the surface of mineral particles. The effects of mineral particulate matter on aggregation, regulation, and catalysis in the formation of atmospheric aerosols and the synergistic reaction mechanism of SO2, NO2, O3, and VOCs on the surfaces of different mineral particles are summarized. The problems existing in the current research on heterogeneous reactions on the surfaces of mineral particles are also evaluated. This paper aims to gain a deep understanding of the mechanism of mineral particulate matter promoting the formation of secondary aerosols and attempts to provide theoretical support for effective haze control.
      Citation: Atmosphere
      PubDate: 2022-08-12
      DOI: 10.3390/atmos13081283
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1284: Decoupling Emission Reductions and
           Trade-Offs of Policies in Norway Based on a Bottom-Up Traffic Emission
           Model

    • Authors: Henrik Grythe, Susana Lopez-Aparicio, Harald Høyem, Torleif Weydahl
      First page: 1284
      Abstract: The way Norway is spearheading electrification in the transport sector is of global interest. In this study, we used the Norwegian Emissions from Road Vehicle Exhaust (NERVE) model, a bottom-up high-resolution traffic emission model, to calculate all emissions in Norway (2009–2020) and evaluate potential co-benefit and trade-offs of policies to target climate change mitigation, air quality and socioeconomic factors. Results for municipal data with regard to traffic growth, road network influences, vehicle composition, emissions and energy consumption are presented. Light vehicle CO2 emissions per kilometer have been reduced by 22% since 2009, mainly driven by an increasing bio-fuel mixing and battery electric vehicles (BEV) share. BEVs are mostly located in and around the main cities, areas with young vehicle fleets, and strong local incentives. Beneficiaries of BEVs incentives have been a subset of the population with strong economic indicators. The incentivized growth in the share of diesel-fuelled passenger vehicles has been turned, and together with Euro6 emission standards, light vehicle NOx emissions have been halved since peaking in 2014. BEVs represent an investment in emission reductions in years to come, and current sales set Norway up for an accelerated decline in all exhaust emissions despite the continual growth in traffic.
      Citation: Atmosphere
      PubDate: 2022-08-12
      DOI: 10.3390/atmos13081284
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1285: Influence of Urban Road Green Belts on
           Pedestrian-Level Wind in Height-Asymmetric Street Canyons

    • Authors: Fanhao Zeng, David Simeja, Xinyi Ren, Zhonggou Chen, Hanyi Zhao
      First page: 1285
      Abstract: This study was conducted to examine the effect on airflow of the shape of an urban road green belt in an asymmetrical street canyon. In this paper, the airflow field at pedestrian height in an asymmetrical street with different building height ratios (ASF) on both sides of the street is modeled and simulated using computational fluid dynamics (CFD) software, ANSYS FLUENT, and the flow rate characteristic distribution index and the average airflow intensity index are used to evaluate and analyze the airflow at the pedestrian level. The study shows that: (1) in an empty street scheme with different building ratios, the static wind area is located on the roof of the downstream building; the closer to the ground in a street with an ASF = 1/3, the lower the airflow rate. However, the situation is the opposite of that in other streets (2/3, 3/1, and 3/2). (2) The position of the green belt makes the windward side flow rate in the step-up street higher than that of the leeward side, and the flow rate of the leeward side in the step-down street is higher than that of the windward side. (3) Compared with other green belt forms, the use of two plates and three belts in the incremental street can increase the circumferential sinking at the roofs of the windward side of the street, thereby improving the wind environment in the entire street. The use of one plate, two-belt and three-plate, four-belt scenarios in the step-down street allows the two ends of the corner vortex to carry more airflow into the interior of the street and reduces both the “wind shadow effect” area in the middle of the street and the “air outlet effect” at both ends.
      Citation: Atmosphere
      PubDate: 2022-08-12
      DOI: 10.3390/atmos13081285
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1286: Accuracy Assessment of a Satellite-Based
           Rain Estimation Algorithm Using a Network of Meteorological Stations over
           Epirus Region, Greece

    • Authors: Stavros Kolios, Nikos Hatzianastassiou, Christos J. Lolis, Aristides Bartzokas
      First page: 1286
      Abstract: The study concerns the quantitative evaluation of a satellite-based rain rate (RR) estimation algorithm using measurements from a network of ground-based meteorological stations across the Epirus Region, Greece, an area that receives among the maximum precipitation amounts over the country. The utilized version of the rain estimation algorithm uses the Meteosat-11 Brightness Temperature in five spectral regions ranging from 6.0 to 12.0 μm (channels 5–7, 9 and 10) to estimate the rain intensity on a pixel basis, after discriminating the rain/non-rain pixels with a simple thresholding method. The rain recordings of the meteorological stations’ network were spatiotemporally correlated with the satellite-based rain estimations, leading to a dataset of 2586 pairs of matched values. A statistical analysis of these pairs of values was conducted, revealing a Mean Error (ME) of −0.13 mm/hr and a correlation coefficient (CC) of 0.52. The optimal computed Probability of False Detection (POFD), Probability of Detection (POD), the False Alarm Ratio (FAR) and the bias score (BIAS) are equal to 0.32, 0.88, 0.12 and 0.94, respectively. The study of the extreme values of the RR (the highest 10%) also shows satisfactory results (i.e., ME of 1.92 mm/hr and CC of 0.75). The evaluation statistics are promising for operationally using this algorithm for rain estimation on a real-time basis.
      Citation: Atmosphere
      PubDate: 2022-08-12
      DOI: 10.3390/atmos13081286
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1287: The Proportional Characteristics of
           Daytime and Nighttime Precipitation Based on Daily Precipitation in Huai
           River Basin, China

    • Authors: Ying Zhu, Xiaoli Liu, Yuqing Zhang, Changchun Chen, Liucheng Shen, Qin Ju, Ting Zhou, Ping Xia
      First page: 1287
      Abstract: The daytime and nighttime precipitation proportions of daily total precipitation (especially extreme daily precipitation) are important indicators that help to understand the process of precipitation formation, which in turn helps to evaluate and improve models and reanalysis precipitation data. In this study, we used the Huai River Basin (HRB) as a case to explore the daytime and nighttime precipitation proportions of daily total precipitation based on 135 meteorological stations during 1961–2018. The total, daytime, and nighttime precipitation showed zonal distributions with high and low values in the southern and northern parts of the basin, respectively. The nighttime precipitation was slightly greater than the daytime precipitation. With the increase in precipitation intensity, the seasonal cycles of the total, daytime, and nighttime precipitation were more distinct, and precipitation mainly occurred in summer. The annual range of precipitation differences between daytime and nighttime in wet seasons showed a downward trend in 1961–2003 followed by an upward trend in 2003–2018. This reversal of annual range of precipitation around 2003 may be related to the changes in annual range of convective precipitation differences between daytime and nighttime in wet seasons. The decrease of light precipitation mainly depended on the decrease of nighttime precipitation. The contributions of nighttime precipitation events to torrential precipitation events were greater than those of daytime precipitation. The days of extreme precipitation events accounted for a very low proportion of total precipitation days, but their precipitation amount accounted for relatively high proportions of total precipitation amount. Annual extreme precipitation amount showed a slightly upward trend, which was caused by the increased nighttime precipitation. Under extreme precipitation conditions, large proportions of daytime precipitation were mainly concentrated in the southeastern parts of the HRB, whereas large proportions of nighttime precipitation were mainly concentrated in the northwestern parts of the basin. The concurrent daytime and nighttime precipitation showed slightly increasing trends, especially in the southeastern part of the basin. With the increase in daytime and nighttime precipitation, the risk of concurrent precipitation extremes in the southern part of the basin increased (shorter return period means higher risk).
      Citation: Atmosphere
      PubDate: 2022-08-13
      DOI: 10.3390/atmos13081287
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1288: Spatiotemporal Changes in Precipitation
           during the Summer Maize Growing Season in the North China Plain and
           Analysis of Its Causes

    • Authors: Wei Wang, Shinan Tang, Hongbao Han, Yiting Xu
      First page: 1288
      Abstract: The North China Plain is an important summer maize production region in China. Investigating spatiotemporal variation patterns of precipitation during the summer maize growing season will guide the prevention of droughts and floods and ensure food production. Daily precipitation data during the summer maize growing season in the North China Plain from 1960–2020 were used to analyze spatiotemporal changes in precipitation, examine the migration patterns of precipitation barycenters, and quantitatively analyze the effects of ENSO (El Niño-Southern Oscillation) warm and cold events on precipitation variation characteristics. Results revealed that in the past 61 years, precipitation showed an insignificant decreasing trend; however, there were considerable differences detected in the spatial distribution layouts of precipitation between different developmental stages. The precipitation distribution layout during the sowing–jointing stage was mainly “North–South”, the zero contour was near 36° N, and the other developmental stages were mainly “global” with phases that were the opposite of one another. Moreover, the precipitation barycenter during the jointing–flowering stage showed a significant southward migration. Precipitation during the three developmental stages negatively correlated with warm events, precipitation during the flowering–maturation stage positively correlated with cold events, the relationship between precipitation changes during warm and cold events and the intensity of warm and cold events was not significant, and Pacific Decadal Oscillation (PDO) was the main climatic factor that affected precipitation changes during the summer maize-growing season in the North China Plain.
      Citation: Atmosphere
      PubDate: 2022-08-13
      DOI: 10.3390/atmos13081288
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1289: WHCNS-Veg Modelling of N2O, NH3 and
           NO3− Dynamics in a Vegetable Production System under Different
           Fertilization and Irrigation Regimes

    • Authors: Guihua Li, Haikuan Xie, Jianfeng Zhang, Hu Li
      First page: 1289
      Abstract: Greenhouse vegetable production in China not only increases farmers’ income, but also increases the risk of nitrogen losses due to excessive water and fertilizer input. Nitrogen losses, including the potent greenhouse gas nitrous oxide (N2O), are driven by water content, soil temperature and pH; regulated by available organic carbon and inorganic nitrogen (N); and affected by management. Therefore, a process-based model was applied to explain the complex interaction of the factors affecting N losses in the form of N2O, NH3 and NO3− from a greenhouse vegetable production system in a northeast suburb of Beijing, China. We designed four treatments: two equal N input treatments with one flooding (FP) and the other drip irrigation (FPD) and two equal water input treatments (drip irrigation) with one 100% chemical N input (FPD) and the other 50% N input (OPTD). The last one was CK treatment (flooding without chemical N). We calibrated the WHCNS-veg model using year-round measurements of soil temperature, N2O emission, NH3volatilization, NO3− distribution and yields for greenhouse cucumber–tomato cultivation under farmers’ practice (flooding + 100% chemical N, FP). Then, we validated the model using the data sets under drip irrigation (70% of flooding amount + 100% chemical N, FPD), reduced chemical N by 50% (drip + 50% chemical N, OPTD) and CK treatment. The WHCNS-veg model was able to capture the above processes under different treatments. Annual N2O emissions were 5.47 and 3.76kg N ha−1 for the cucumber and tomato seasons under FP, respectively. Compared to FP, drip irrigation (FPD) decreased N2O emissions by 19.0% and 45.5% in the two seasons, respectively. Compared to FPD, applying a lower rate of N (OPTD) further reduced N2O emissions by 13.7% and 40.5%, respectively. According to the model simulation, N2O emission was mainly controlled by nitrification/denitrification in the cucumber/tomato seasons, respectively. Compared to FP, drip irrigation (FPD) increased NH3 volatilization by 54.2% in the cucumber season, while in the tomato season, there were no significant differences inNH3 volatilization under the three fertilizer treatments. The nitrate leaching levels were 48.5 and 81.0 kg N ha−1 for the two seasons under FP treatment. Drip irrigation (FPD) decreased NO3− leaching by 20.6% in the cucumber season. Drip irrigation (FPD) and/or reducing chemical N (OPTD) did not compromise vegetable yields. In all, WHCNS-veg performed well in simulating N2O, NH3 and NO3− dynamics from the greenhouse vegetable field, which means that the model can be used to manage water and nitrogen precisely in greenhouse vegetable production systems by scenario analysis, and drip irrigation and/or lower N input can be applied in this area to secure yield and reduce N losses.
      Citation: Atmosphere
      PubDate: 2022-08-13
      DOI: 10.3390/atmos13081289
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1290: Chemical Characterization and Health Risk
           Assessment of Particulate Matter from Household Activities in Bamako,
           Mali, Western Sub-Saharan Africa

    • Authors: Alimata Sidibe, Yosuke Sakamoto, Kentaro Murano, Keiichi Sato, Akie Yuba, Mari Futami, Ousmane A. Koita, Ibrahim Traore, Yoshizumi Kajii
      First page: 1290
      Abstract: Household particulate matter (PM) is a major health concern, especially in developing regions, where biomass fuels are used quantitatively in households. Additionally, the combustion of incense (ICS) and insecticide (IST) is common. This study characterized the PM chemical composition to evaluate its health effects, as such information is lacking in developing regions, including Bamako, Mali. The composition of PM emitted from typical household activities, including cooking and combustion of ICS and IST, was characterized. These contained ions, organic carbon (OC), elemental carbon (EC), and metals. The results revealed that the chemical composition varied with emission source and combustion conditions. The dominant ions were Ca2+ (charcoal cooking), K+ (wood cooking) and F− (in ICS and IST). The OC/EC ratio for IST, ICS, wood, and charcoal cooking was 59, 30, 8, and 7, respectively. Moreover, US EPA (United States Environmental Protection Agency) health risk assessment models indicated a higher hazard index (≤6.04) than the recommended limit (1) for nearly all emission sources. Total-CR was higher than the lower boundary limit (10−6) in adults and children. Wood cooking activity and ICS combustion exceeded the unacceptable limit (10−4) in children. Our findings highlight the need to develop effective air pollution mitigation strategies for health safety.
      Citation: Atmosphere
      PubDate: 2022-08-13
      DOI: 10.3390/atmos13081290
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1291: Weather Radar Nowcasting for Extreme
           Precipitation Prediction Based on the Temporal and Spatial Generative
           Adversarial Network

    • Authors: Xunlai Chen, Mingjie Wang, Shuxin Wang, Yuanzhao Chen, Rui Wang, Chunyang Zhao, Xiao Hu
      First page: 1291
      Abstract: Since strong convective weather is closely related to heavy precipitation, the nowcasting of convective weather, especially the nowcasting based on weather radar data, plays an essential role in meteorological operations for disaster prevention and mitigation. The traditional optical flow method and cross-correlation method have a low forecast accuracy and a short forecast leading time, while deep learning methods show remarkable advantages in nowcasting. However, most of the current forecasting methods based on deep learning suffer from the drawback that the forecast results become increasingly blurred as the forecast time increases. In this study, a weather radar nowcasting method based on the Temporal and Spatial Generative Adversarial Network (TSGAN) is proposed, which can obtain accurate forecast results, especially in terms of spatial details, by extracting spatial-temporal features, combining attention mechanisms and using a dual-scale generator and a multi-scale discriminator. The case studies on the forecast results of strong convective weather demonstrate that the GAN method performs well in terms of forecast accuracy and spatial detail representation compared with traditional optical flow methods and popular deep learning methods. Therefore, the GAN method proposed in this study can provide strong decision support for forecasting heavy precipitation processes. At present, the proposed method has been successfully applied to the actual weather forecasting business system.
      Citation: Atmosphere
      PubDate: 2022-08-14
      DOI: 10.3390/atmos13081291
      Issue No: Vol. 13, No. 8 (2022)
       
  • Atmosphere, Vol. 13, Pages 1292: Predictability and Predictions

    • Authors: Richard A. Anthes
      First page: 1292
      Abstract: This essay describes the author’s lifetime experiences with predictability theory and weather predictions.
      Citation: Atmosphere
      PubDate: 2022-08-14
      DOI: 10.3390/atmos13081292
      Issue No: Vol. 13, No. 8 (2022)
       
 
JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
 


Your IP address: 18.208.126.232
 
Home (Search)
API
About JournalTOCs
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-