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Air Quality, Atmosphere & Health
Journal Prestige (SJR): 0.862  Citation Impact (citeScore): 3 Number of Followers: 11  Hybrid journal (It can contain Open Access articles)ISSN (Print) 1873-9326 - ISSN (Online) 1873-9318 Published by Springer-Verlag  [2467 journals]
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- BTEX proportions as an indicator of benzene hotspots and dispersion tends
in cities where sea and land breezes dominate-
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Abstract: Abstract There are certain spatial configurations in cities that generate areas with reduced ventilation where, consequently, air pollution can reach hazardous levels. Although urban forms have already been flagged as a factor affecting air pollution, its role in the accumulation of volatile organic compounds has not been extensively evaluated with field measurements. In order to investigate the effect of urban morphology on air pollution levels, we measured the concentration of benzene, toluene, ethylbenzene, and xylenes (BTEX) in 44 different city sites, using Radiello® diffusive passive samplers during a 1-week campaign. This work presents a method that maps a city in zones with different levels of atmospheric dispersion by analyzing the proportions of BTEX in the ambient air. The method applied to a coastal city (characterized by uniform wind patterns) revealed the existence of two clearly differentiated zones. In one of them, the mean benzene concentration was 3.26 times higher than in the other. However, the mean concentrations of the rest of BTEX were barely the same in both areas. These findings suggest that slow degradation pollutants (i.e., benzene) accumulate in poor ventilated areas, whereas faster degradation pollutants do not show accumulation. The conclusions of this study can be particularly useful in designing personal exposure assessments, optimizing the urban morphology, and improving the location of air quality monitoring stations.
PubDate: 2023-01-20
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- Probabilistic human health risk assessment and contributions to ozone and
SOA formation potentials associated with BTEX and formaldehyde emissions
in a tropical city (Salvador, Bahia, Brazil)-
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Abstract: Abstract The BTEX compounds (benzene, toluene, ethylbenzene, and xylenes) and formaldehyde (FA) have harmful impacts on human health and are also important precursors of tropospheric ozone and secondary organic aerosols (SOA). Thus, the objective of this study was to perform a human health risk assessment considering the lifetime carcinogenic (LCR) and non-carcinogenic (as hazard quotient (HQ)) risks for 3 different age groups associated with exposure to BTEX and FA by inhalation using a probabilistic approach with Monte Carlo simulation, as well as to evaluate the contributions of these compounds to ozone formation potential (OFP) and SOA formation potential (SOAFP), at seven sites in the city of Salvador, Bahia, Brazil, during the dry and rainy periods. The HQ values associated with BTEX and FA compounds were below the limit set by the USEPA (HQ = 1) for all groups in both periods. The LCR values for benzene and FA at the 95th percentile considering 3 evaluated groups were 2.49 × 10−6, 3.56 × 10−6, 9.16 × 10−6 and 1.83 × 10−5, 2.53 × 10−5, 6.55 × 10−5 in the dry period and 2.83 × 10−6, 3.94 × 10−6, 1.01 × 10−5 and 7.97 × 10−6, 1.02 × 10−5, 2.40 × 10−5 in the rainy period, respectively, being all values above the acceptable limit by the USEPA (1.0 × 10−6). For all 3 groups of the population, the LCR values for benzene and FA were higher during the rainy period and dry period, respectively, following the same pattern as the concentrations. FA, xylenes, and toluene accounted for up to 97.0% of total OFP, whereas toluene, benzene, and xylenes contributed up to 88.5% of total SOAFP. The results obtained showed the need to adopt measures to reduce BTEX and FA emissions in order to minimize the impacts on health of the exposed population and on air quality.
PubDate: 2023-01-19
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- Association between short-term exposure to PM and cardiovascular mortality
in Iran: a systematic review and meta-analysis-
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Abstract: Abstract Given the limited evidence on the effect of particulate matter (PM) on health in Middle Eastern countries and especially Iran, this study aimed to systematically review all the studies on the relationship between short-term exposure to PM and cardiovascular (CVD) mortality in Iranian cities. We searched three databases of Scopus, PubMed, and Web of Science in February 2022. The data required for the meta-analysis were extracted from the articles. Four sets of the meta-analysis were performed, including PM10-total CVD mortality, PM10-ischemic heart disease (IHD) mortality, PM2.5-total CVD mortality, and PM2.5-IHD mortality. Of 228 documents, nine studies were eligible for the qualitative assessment, while eight were included in the meta-analysis. PM2.5 had stronger and positive effects on total CVD mortality than PM10. Meta-analysis showed that non-cumulative exposure to 10 μg/m3 PM2.5 was significantly associated with CVD mortality in lag 1 (1.01, 95% CI: 1.01, 1.02), lag 2 (1.01, 95% CI: 1.00, 1.01), lag 3 (1.01, 95% CI: 1.00, 1.01), and lag 7 (1.01, 95% CI: 1.00, 1.01). In addition, cumulative exposure to PM2.5 had significant effects on CVD mortality in all lag days, by RRs ranging from 1.01 (95% CI: 1.00, 1.02) in lag 0-1 to 1.02 (95% CI: 1.01, 1.03) in lag 0-7. No significant association were found between PM10 and CVD and IHD mortality. Given the positive effects of PM2.5 on mortality, special considerations should be taken into action to control the emissions and reduce the exposure to PM2.5 in Iranian cities.
PubDate: 2023-01-18
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- Light absorption properties of black carbon and brown carbon emitted from
biomass combustion at the typical rural cooking stoves in Bangladesh-
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Abstract: Understanding and improving inventories regarding the optical characteristics of light-absorbing carbonaceous aerosols is critical due to their effect on local and regional climate. The optical properties of aerosol particles collected during the combustion of nine different biomasses at the typical rural cooking stove in Bangladesh were examined in the laboratory setting. The absorption Ångström exponent (AAE) values were found between 1.05 and 5.45, which indicated that the presence of both brown carbon (BrC) and black carbon (BC)–rich aerosols was from biomass-burning emission. On average, BrC contributed about 59 ± 35% to the overall aerosol absorption at 370 nm. The mass absorption efficiency (MAE) values of BC (880 nm) and BrC (370 nm) ranged from 1.46 to 15.06 m2g−1 (average: 7.46 ± 4.09 m2g−1) and 1.35 to 26.45 m2 g−1 (average: 13.19 ± 7.28 m2 g−1), respectively. The projected absorption emission factors (AEF) (per kilogram of fuel) at 370 nm and 880 nm varied from 0.57 to 18.56 m2 kg−1 (average: 4.87 ± 5.30 m2 kg−1), 0.01 to 1.22 m2 kg−1, (average: 0.38 ± 0.26 m2 kg−1), respectively. The prospective climatic influence of biomass-burning events in rural Southeast Asia was illustrated by the projected considerable attribution of BrC to overall light absorption. Graphical abstract
PubDate: 2023-01-18
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- Surface, satellite ozone variations in Northern South America during low
anthropogenic emission conditions: a machine learning approach-
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Abstract: Abstract 2020 presented the ideal conditions for studying the air quality response to several emission reductions due to the COVID-19 lockdowns. Numerous studies found that the tropospheric ozone increased even in lockdown conditions, but its reasons are not entirely understood. This research aims to better understand the ozone variations in Northern South America. Satellite and reanalysis data were used to analyze regional ozone variations. An analysis of two of the most polluted Colombian cities was performed by quantifying the changes of ozone and its precursors and by doing a machine learning decomposition to disentangle the contributions that precursors and meteorology made to form O3. The results indicated that regional ozone increased in most areas, especially where wildfires are present. Meteorology is associated with favorable conditions to promote wildfires in Colombia and Venezuela. Regarding the local analysis, the machine learning ensemble shows that the decreased titration process associated with the NO plummeting owing to mobility reduction is the main contributor to the O3 increase (≈50%). These tools lead to conclude that (i) the increase in O3 produced by the reduction of the titration process that would be associated with an improvement in mobile sources technology has to be considered in the new air quality policies, (ii) a boost in international cooperation is essential to control wildfires since an event that occurs in one country can affect others and (iii) a machine learning decomposition approach coupled with sensitivity experiments can help us explain and understand the physicochemical mechanism that drives ozone formation.
PubDate: 2023-01-13
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- Reliability and stability of a statistical model to predict ground-based
PM2.5 over 10 years in Karachi, Pakistan, using satellite observations-
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Abstract: Abstract Understanding the complex mechanisms of climate change and its environmental consequences requires the collection and subsequent analysis of geospatial data from observations and numerical modeling. Multivariable linear regression and mixed-effects models were used to estimate daily surface fine particulate matter (PM2.5) levels in the megacity of Pakistan. The main parameters for the multivariable linear regression model were the 10-km-resolution satellite aerosol optical depth (AOD) and daily averaged meteorological parameters from ground monitoring (temperature, dew point, relative humidity, wind speed, wind direction, and planetary boundary layer height). Ground-based PM2.5 was measured in two stations in the city, Korangi (industrial/residential) and Tibet Center (commercial/residential). The initial linear regression model was modified using a stepwise selection procedure and adding interaction parameters. Finally, the modified model showed a strong correlation between the PM2.5–satellite AOD and other meteorological parameters (R2 = 0.88–0.92 and p-value = 10−7 depending on the season and station). The mixed-effect technique improved the model performance by increasing the R2 values to 0.99 and 0.93 for the Korangi and Tibet Center sites, respectively. Cross-validation methods were used to confirm the reliability of the model to predict PM2.5 after 10 years.
PubDate: 2023-01-03
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- Characteristics, diffusion, and exposure risk of bioaerosol pollution
during haze period on a campus of central China-
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Abstract: Teachers and students work and study on campus for a long time, so the campus’s air quality needs attention. This study focuses on the microbial pollution in the air of campus from the beginning to the end of the haze. The total suspended particulate sampler and high-throughput sequencing were used to analyze the concentration and diversity of microorganisms. Then, the concentrations of particles and ions were calculated and compared with normal weather. PICRUSt software was used to predict functional gene composition. The spreading character of haze was described by Principal Component Analysis and The Hybrid Single-Particle Lagrangian Integrated Trajectory Model. The hazard index was calculated to assess the health risk of haze. The results showed that the average concentration of bacteria (88 CFU/m3) was higher during the haze than in normal weather (59 CFU/m3). Bacterial concentration in the air is the highest at the later stage. The diversity of bacteria during the haze was 1.6 times that in normal weather. The main intestinal bacteria during haze are Bacteroides. The haze did not change the functional genes of bacteria. Fungi changed slightly in haze weather compared with normal weather. The average concentration of particulate matter (508.72 μg/m3) during haze weather was higher than that in normal weather (291.67 μg/m3). The proportion of primary ions in the air decreased during the haze. The relative humidity is an essential factor affecting bioaerosols. One hour after the haze passed through the sampling point, the diffusion range was about 233.35km2. The risk of bioaerosol for men is higher than that for women. Therefore, personal protection should be strengthened during the haze. Graphical abstract
PubDate: 2023-01-01
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- High-resolution impacts of green areas on air quality in Madrid
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Abstract: Abstract This study numerically investigates the influence of trees on air quality in Madrid urban area (Spain). Simulations are performed using the mesoscale model WRF/Chem (EPA, US) and the microclimate computational fluid dynamics (CFD) model PALM4U (IMUK, DE) configured as LES (Large Eddy Simulation). PALM4U is running over one of the 1 km × 1 km grid cells with 5 m very high spatial resolution using three different scenarios. In the simulation domain, there is a zone (approximately 25% of the domain) of vegetation where the dominant species are broadleaf trees included in the BAU (Business as Usual) scenario. The second scenario is focused on changing the type of the tree from broad leaf at BAU scenario to needle leaf the so-called ND scenario and the third scenario called NOTREE which comprise the replacement of the trees located in the green zone. The base simulations (BAU) are compared with data from the Madrid air quality monitoring network for the evaluation of the simulation results. The effects of the trees are calculated comparing scenarios (BAU-NOTREE and BAU-ND), so a brute force methodology has been used. This paper shows that the effects of the trees and type of trees are not uniform across the urban area because there are variations in the energy fluxes and the aerodynamic effect and there are important interactions of trees with wind flow dynamics. The mitigation potential effect of trees on gaseous air pollutants concentrations is showed and also may enhance substantially air pollution in other areas.
PubDate: 2023-01-01
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- Comparison of two turbulence parameterisations for the simulation of the
concentration variance dispersion-
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Abstract: Abstract In this work, we compare two different parameterisations for the wind velocity–component standard deviations. The first one is the (Hanna 1982) parameterisation, while the second is the (Scire et al. 2000) parameterisation, which provide the proper values and vertical structure for the wind standard deviations in the convective, neutral and stable layers, needed as input the Lagrangian stochastic model SPRAYWEB. The results of the model simulations carried out using the two parameterisations are compared, in terms of both mean concentration and concentration standard deviation, by evaluating some statistical indexes and trough scatter- and qq-plots.
PubDate: 2023-01-01
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- Chemical characterization, source apportionment, and human health risk
assessment of PM2.5 in an urban area in Hanoi, Vietnam-
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Abstract: Abstract Forty-seven ambient 24-h PM2.5 samples were collected during summer and fall at a typical inner-city sampling site in Hanoi, a metropolitan city in Vietnam for characterization, inorganic chemical fractionation, source apportionment, and potential health risk assessment of airborne PM2.5. The average 24-h PM2.5 concentrations observed in this study were substantially higher than the World Health Organization (WHO) guidelines. The most abundant elements in PM2.5 were Al, Fe, Pb, and Zn accounting for 85.14% and 89.06% of the total obtained elements in summer and fall, respectively. Noticeably, the levels of Cd were 40.33 times in summer and 26.64 times in fall higher than WHO guidelines. The obtained results from principal component analysis (PCA) combined with enrichment factor (EF) analysis showed good agreement and suggested that the major sources of PM2.5 were non-exhaust traffic emission and crustal dust, exhaust traffic emission, coal combustion, and industrial source. Both the hazard index (HI) and carcinogenic risk (CR) values of all investigated elements were lower than the safe levels for adults and children in the two seasons. However, the carcinogenic risks of Cr for both adults and children were close to the acceptable values, implying potential carcinogenic risks caused by this metal. Besides, both the non-carcinogenic and carcinogenic risks for children were substantially higher than that for adults, suggesting more attention on children’s health adverse effects resulting from exposure to trace metals bounded with PM2.5 in Hanoi should be paid.
PubDate: 2023-01-01
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- Performance assessment of air quality monitoring networks. A specific case
study and methodological approach-
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Abstract: Abstract This work presents a new methodological approach to evaluating the long-term performance of an existing air quality monitoring network (AQMN). The AQMN is essential in controlling human beings’ exposure to air pollutants, and the performance should be assessed over time. Still, there is not a harmonised method at the legislative level. In this work, 2008–2016 NO2 data recorded by the Community of Madrid’s AQMN were used for developing the suggested methodology, and 2007, 2017, and 2020 NO2 data were involved in testing the aptitude of the proposed methodology to check the performance along the time. Chemometric techniques were employed to suggest the most representative non-redundant fixed stations within the target AQMN, reducing up to ~ 80% of the original number of fixed monitoring stations (from 23 to 5 fixed stations). The influence of the temporal frame used in developing the exposed methodology showed a variability lower than 5%. The spatial NO2 distribution pictured by the current versus recommended fixed stations showed a higher than 95% similarity. This recommended approach can also be applied to short-time data. The exhibited methodology is a valuable tool for supporting AQMN managers in decision-making concerning AQMN management and complementing European Legislation guidelines concerning air pollutants monitoring using AQMN.
PubDate: 2023-01-01
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- Links between the concentrations of gaseous pollutants measured in
different regions of Estonia-
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Abstract: Abstract The factors that determine the concentrations of air pollutants (NO, NO2, SO2, O3), measured in 8 monitoring stations (4 rural background, 3 urban, and 1 industrial) in Estonia, are studied applying the factor analysis. The factor analysis reveals remarkable impact of COVID-19 lockdown, effects caused by dramatic decrease in oil-shale based energy production in Estonia provoked by new socio-economic conditions such as elevated price for CO2 emission quota, differences between rural and urban stations, maritime-continental difference for NO2 and ozone, and specific industrial impact in case of SO2. The multiple regression analysis to predict the ozone concentration in one rural background station at Tahkuse was performed, based on the ozone concentrations measured in other stations and the concentrations of NO, NO2, and CO2, recorded in the same station. It was found that the ozone concentration at Tahkuse is rather well predictable (determination coefficient, i.e., correlation coefficient squared, R2 = 0.714), using only the concentrations from another rural station at Saarejärve that is about 110 km away from Tahkuse. Adding all the available data into the list of regression analysis arguments, the model predictability is improved moderately (determination coefficient R2 = 0.795). Large model residuals above all tend to occur with the values measured and predicted at summer nights. Surprisingly, neither NO nor NO2 concentration measured in the Tahkuse station did appear a good predictor for ozone (R2 = 0.02 and 0.05, respectively), possibly long-range transport of ozone (that has also experienced NO and/or NO2 influence during transport) overrides the local effects of NO and/or NO2.
PubDate: 2023-01-01
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- The concentration of potentially toxic elements (zinc, iron, manganese)
bound PM2.5 in the indoor air of urban schools: a global systematic review
and meta-analysis-
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Abstract: Abstract Exposure to potentially toxic elements (PTEs) bound to PM2.5 can cause various health effects, including cardiovascular disease, allergies, and other related diseases. There have been several studies on the concentration of PTEs, including zinc (Zn), iron (Fe), and manganese (Mn) bound PM2.5 in the indoor air of urban schools. In this study, the concentration of Zn, Fe, and Mn in the indoor air of schools bound PM2.5 were meta-analyzed. PubMed and Scopus were used to retrieve papers related to the concentration of PTEs bound PM2.5 in the indoor air of urban schools from January 1, 2000 to March 10, 2020. The concentration of PTEs in PM2.5 was meta-analyzed based on the country subgroup in the random-effects model (REM). Thirty papers with 25 data reports were included in the study. The rank order of PTEs bound PM2.5 was Zn (17.32 ng/m3) > Fe (14.49 ng/m3) > Mn (7.40 ng/m3). The rank order of countries based on the concentration of Fe-bound PM2.5 in the indoor air of urban schools was China > Poland > Italy > Spain > Taiwan > Turkey > Iran) > Chile; Zn, Poland > Iran > Taiwan > Turkey > Spain > Italy > Chile; and for Mn, Poland > China > Iran > Taiwan > Spain > Italy > Chile. The pooled concentration of PTEs (Fe, Mn, and Zn) bound PM2.5 in the indoor air of urban schools in Poland and China was higher than in other countries, hence, therefore, it is recommended to carry out a PM2.5 concentration reduction program in the indoor air of schools in these countries.
PubDate: 2023-01-01
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- Assessment of personal deposited dose of bioaerosols and particles in a
wastewater treatment plant facility-
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Abstract: Abstract The daily deposited dose of bioaerosols and particle mass or number in the human respiratory tract using an exposure dose model (ExDoM2) was quantified in the present study. The dose was calculated for the extrathoracic (ET), tracheobronchial (TB), and alveolar-interstitial (AI) regions of the human respiratory tract. The calculations were performed for viable, cultivable airborne heterotrophic bacteria, mesophilic fast-growing fungi, and total coliforms at a municipal wastewater treatment plant (WWTP) located at a suburban area at a Mediterranean site. The human dose was determined using data from two locations at the WWTP which correspond to two different wastewater treatment stages (aerated grit chamber (indoor) and primary settling tanks (outdoor)) and one outdoor location at the urban background site. In addition, the model simulations were performed for two exposure periods (March to April and May to June 2008). Higher daily deposited dose in the total human respiratory tract was observed for heterotrophic bacteria at the aerated grit chamber, whereas lower values of heterotrophic bacteria were observed at the primary settling tanks. These findings were associated with the corresponding stage of wastewater treatment activities and may be valuable information for determining future dose–response relationships. In addition, higher daily deposited dose was determined in the ET region for the three categories of bioaerosols. Regarding PM10 and PN1, the higher daily deposited dose received by a worker at the aerated grit chamber. Finally, the hazard quotients were estimated and the results showed that the non-carcinogenic effects can be ignored for bioaerosols and PM10 except for workers present at aerated grit chamber. Regarding PM2.5, the non-carcinogenic effects are of concern and cannot be ignored for all cases.
PubDate: 2023-01-01
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- Quantifying the impact of a smart farming system application on
local-scale air quality of smallhold farms in Greece-
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Abstract: Abstract Smart farming (SF) has emerged as a scientific approach exploiting technology advances for the management of agricultural practices, focusing on the control of resources and chemicals used. There is still limited evidence in the scientific literature in regard to the efficiency of SF, particularly for targeted environmental issues, such as air pollutant emissions from agricultural activities. The present paper expoits quantitative data collected from questionnaires to farmers of 6 pilot areas in Greece, participating in the LIFE GAIA Sense project. Emissions and pollutant levels were calculated for two consecutive years in these pilot areas, namely 2019 (baseline year) and 2020, which is the first SF application year. The methodology for calculating realistic emissions data, following a combined tier 1/tier2 approach is presented. To this purpose, detailed activity data of the specific SF application areas related to agricultural activities were acquired, based on the responses of participating farmers to targeted questionnaires. Calculated emissions were used as input data for air quality modeling simulations to examine the efficiency of SF in reducing local pollutant concentrations. The results show significant emissions and concentrations reductions in five out of the six pilot areas, for all pollutants and greenhouse gases studied, due to the decrease in fuel consumption and N fertilizer applied, as a result of the farmers following the SF advice. Particularly for NH3, which is an agricultural air pollutant of concern due to its health and environmental impacts, emission reductions of around 30% (and by up to almost 60%) were calculated.
PubDate: 2023-01-01
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- Air quality index prediction via multi-task machine learning technique:
spatial analysis for human capital and intensive air quality monitoring
stations-
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Abstract: Abstract Air, an essential natural resource, has been compromised in terms of quality by economic activities. Air pollution has become a critical environmental issue in recent decades. Forecasts of air quality play an important role in warning people about and controlling air pollution. Considerable research has been devoted to predicting instances of poor air quality, but most studies are limited by insufficient longitudinal data, making it difficult to account for seasonal and other factors. Several prediction models have been developed using an 8-year dataset collected by Beijing Environmental Protection Monitoring Center (BEPMC). The small spatial and temporal scales and nonlinearity of climate effects are significant challenges to precise Air Quality Index (AQI) prediction. As a result, data normalization is applied to enhance air quality features without distorting divergences. Machine learning methods, including simple linear regression (SLR), support vector regressor (SVR), random forest (RF), and probabilistic voting ensemble, were used to build regression models for predicting the AQI of six central and outskirt regions of Beijing city. The mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R2) were used to evaluate the performance of the regression models. Experimental results showed that the max probabilistic voting ensemble performed better in the prediction of the AQI in terms of R2, whereas RF performed better in the prediction of the AQI in terms of MAE and RMSE scores. The overall performance of the proposed model in terms of MAE and RMSE is between 0.0128 to 0.0194 and 0.0230 to 0.0326, respectively. This work also illustrates that combining ensemble learning consisting of various classifiers’ output weights with air quality prediction is an efficient and convenient way to solve certain significant environmental problems.
PubDate: 2023-01-01
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- Study of regional air pollutant dispersion scenarios and atmospheric
capacity changes based on spatial structure analysis of source
intensity—the case of Hohhot, China-
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Abstract: Abstract This paper takes Hohhot as the research area, aiming at the four typical atmospheric pollutants of PM2.5, PM10, SO2, and NOx, and targeting the spatial layout scenarios of different pollution sources. Based on the topological structure analysis method, the CALPUFF model was used to simulate and analyze the linear, divergent, and circular distribution scenarios of pollution sources. ArcGIS and Surfer were used to characterize the diffusion scenarios of four air pollutants under three different spatial structure scenarios and the influence of different spatial structures on the exceeding rate and extreme value of pollutant emissions in small and large regions. A comparison of the results showed that for the small area, the linear distribution of pollution sources has the smallest impact on the environment of the small area by integrating the four pollutants. For the whole region of Hohhot, the residual environmental capacity of PM2.5, PM10, and NOx is the largest under the linear distribution scenario of pollution sources. Considering the residual environmental capacity of the four pollutants, the spatial carrying capacity of the linear distribution scenario of pollution sources is the best for large regions. This paper adopted the method of spatial layout regulation to improve the regional environmental capacity and provided feasible analysis method reference and technical implementation route. Finally, different air pollutant load shedding strategies were proposed according to the distribution characteristics of pollution sources in the study area, providing scientific references and suggestions for different industrial state site selection.
PubDate: 2023-01-01
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- Organic profiles of particulate matter emissions from a Euro VI diesel
city bus-
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Abstract: Abstract To perform a detailed organic speciation, particulate matter emitted by a Euro VI diesel city bus was collected combining chassis dynamometer and on-road testing. Dynamometer exhaust emission tests were performed following the Braunschweig and the world harmonised vehicle cycle (WHVC). On-road testing was done on two routes representing typical city bus operation and an additional circuit following the in-service conformity (ISC) requirements. Amongst other constituents, exhaust particles included polycyclic aromatic hydrocarbons (PAHs), alkyl-PAHs, alcohols, various types of acids, glycerol derivatives, and glycols. Particulate matter mass fractions of these compounds were much higher in samples from on-road driving tests compared to chassis dynamometer cycles. Retene and 5-ring PAHs were the dominant compounds within this family. Alkyl-naphthalenes and alkyl-phenanthrenes were also detected. On average, 20% of the analysed PAHs were found to contribute to the carcinogenic potency of the particulate material. For many compounds, in the dynamometer tests, the highest particulate mass fractions were obtained for the WHVC with hot start. Compounds from fuel additives (e.g. levulinic acid), components of the cooling system fluids (e.g. ethylene glycols), by-products of after-treatment technologies (isocyanic acid) and antioxidants leached from polymeric materials (e.g. oxidised Irgafos® 168) were observed in the exhaust particles. The detection of constituents such as monoglycerides and hydroxytoluene suggests the use of diesel/biodiesel blends by bus drivers.
PubDate: 2023-01-01
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- Emission estimates and air quality simulation on Lombardy during lockdown
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Abstract: Abstract This paper illustrates the study carried out by ARPA Lombardia to quantify the variation in daily emissions of the main pollutants and their impacts on air quality in Lombardy during the anti-COVID-19 lockdown between the end of February and the end of May 2020. A methodology for emission estimates was developed over Lombardy for this purpose and later was extended to larger areas: the Po-basin, (LIFE PREPAIR 2020) and the entire Italy (PULVIRUS 2021). In this study, the daily emissions estimates were derived by combining data from air emission inventory of Lombardy and a set of indicators that allowed to update the estimates and describe the temporal and spatial variations of the emission sources. The calculation of emission variation was conducted for all the main pollutants (PM10, NH3, NOx, SO2, NMVOC) and the greenhouse gases; then, the impact on air quality concentrations was simulated by the chemical and transport model FARM, that also allows to track secondary particulate and its variability in time and space on the basis of nonlinear processes and weather conditions. The estimated emission reduction, compared to the expected average value in the absence of anti-COVID-19 measures, daily varies depending on pollutants and is mainly affected by reductions in road traffic emissions and an estimated increase in domestic heating emissions. Simulations confirm strong reductions of NO2 atmospheric average concentrations, slightly variations of PM10 averages and a potential growth of tropospheric ozone.
PubDate: 2023-01-01
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- The role of murine models in the study of the respiratory tract immune
response induced by particulate matter-
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Abstract: Abstract Environmental air pollution is a global problem. Among the main types of air pollutants that harm human health are ozone, particulate matter (PM), nitrogen, carbon dioxide, sulfur dioxide, and carbon monoxide. These have a significant effect on human health across the world. PM can penetrate the respiratory tract, induce inflammation, and cause permanent damage. In addition, correlations have been found between PM inhalation and the development of cardiovascular diseases, various types of cancer, asthma, and lower respiratory infections. Murine models provide us with the experimental tools to understand the immunoinflammatory response to the inhalation of PM and develop preventive measures that can be extrapolated to humans. Here, we present an overview of the current understanding of the PM immune response and discuss the different experimental strategies used in research on this subject with murine models.
PubDate: 2023-01-01
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