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Air Quality, Atmosphere & Health
Journal Prestige (SJR): 0.862  Citation Impact (citeScore): 3 Number of Followers: 8  Hybrid journal (It can contain Open Access articles)ISSN (Print) 1873-9326 - ISSN (Online) 1873-9318 Published by Springer-Verlag  [2469 journals]
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- Spatial heterogeneity and estimation of PM10 concentration over
Brahmaputra Valley using geographic weighted regression model assimilating
surface, MODIS, and ERA-interim reanalysis data-
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Abstract: The geographic weighted regression (GWR) model is utilized to estimate PM10 from a 3-year (2016 to 2018) collocated monthly mean of predictive variables, aerosol optical depth (AOD 550 nm), planetary boundary layer (PBL), and air temperature (AT) over the intermontane Brahmaputra River Valley (BRV). The coefficient of determination (R2 = 0.62) and the root mean square error (RMSE = 22.74 µg/m3) obtained from the GWR model fitting decreased by 0.09 (R2 = 0.53) and 0.14 µg/m3 (RMSE = 22.60) in cross-validation analysis. Regression coefficient (β) values computed by GWR reflect the heterogeneity of relationship among the variables. The PM10-AOD 550-nm relationship showed asymmetry (strong positive to negative β values) at spatial scale from the west (β1 = 5.94 to 23.91), central (β1 = − 2.92 to − 17.68), to the east (β1 = − 4.19 to − 27.27) valleys of the BRV due to the effect of local meteorological conditions. Results of monthly mean value of PM10 and the predictive variables indicate surface PM10 and AOD 550-nm mean values vary strongly in sites over the valley. This variation is dependent on the proximity to sources and dispersal mechanisms within the PBL. Further in this study, the PM10 (µg/m3) is predicted at valley site scale for 2016 based on annual mean of AT, PBL, and AOD 550 nm at higher spatial resolution. The results show interesting spatial contrast of AOD 550 nm and PM10 with PBL.
PubDate: 2022-01-24
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- Effects of air pollution on daily hospital admissions for cardiovascular
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Abstract: Adverse impacts of air pollution on human health have been well documented in Spain; however, very few have been conducted in the Spanish region of Castilla-La Mancha (CLM). CLM is an extensive region with a low population density, little industrial production, and moderate air pollution level. The aim of the study was to assess the relationship between the risk of hospital admission for cardiovascular disease (CVD) and exposure to PM2.5, PM10, and NO2 in CLM during 2006–2015. Daily air pollution concentration, temperature, and relative humidity were monitored from the air quality monitoring stations in CLM. A time-series analysis with generalized linear model was used to examine the effects of air pollution on hospital admissions by controlling for long-term trend and other potential confounders. The effect modifications by sex and age (15–64; ≥ 65 years) were examined. Lagging exposure concept was used to analyze a possible latency period in cumulative exposure-pollution analyses. Relative risks (RR) of CVD admissions at the same day (lag 0) and to 7 days after exposure (lag 7) were calculated. Relative risks of CVD admissions (for an increase of 10 µg m−3 in concentration of air pollutant) were calculated. The elderly group (≥ 65 years) were the most susceptible group to the effect of air pollution, whereas the estimated effect by sex was significantly different depending on the age group. The potential utility of these results may help for syndromic surveillance during future similar air pollutant concentrations, where an increase in the use of health services among the vulnerable groups could be unexpected by the emergency department.
PubDate: 2022-01-24
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- Using crowd-sourced low-cost sensors in a land use regression of PM2.5 in
6 US cities-
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Abstract: Assessing exposure to ambient fine particulate matter (PM2.5) is important for improving human health. With rapidly expanding low-cost sensor networks globally, it is possible for monitoring networks to be located by a variety of users (i.e., crowd sourcing) to increase measurement density and coverage for use in exposure assessment, e.g., national land use regression (LUR) models. Few studies have integrated low-cost sensors into LUR models across multiple cities, limiting the ability of modelers to fully utilize growing low-cost sensor networks worldwide. We developed five LUR models to predict annual average PM2.5 concentrations using combinations of regulatory (six cities: n = 68; national: n = 757) and low-cost monitors (n = 149) from six US cities. We found that developing Hybrid LURs that include the low-cost (i.e., PurpleAir) network may better capture within-city variation. LURs with the PurpleAir data only (tenfold CV R2 = 0.66, MAE = 2.01 µg/m3) performed slightly worse than a conventional LUR based on regulatory data only (tenfold CV R2 = 0.67, MAE = 0.99 µg/m3). Hybrid models that included both low-cost and regulatory data performed similarly to existing national models that rely on regulatory data (hybrid models: tenfold CV R2 = 0.85, MAE = 1.02 µg/m3; regulatory monitor models: R2 = 0.83, MAE = 0.72 µg/m3). Integrating crowd-sourced low-cost sensor networks in LUR models has promising applications to help identify intra-city exposure patterns especially for regions with limited regulatory networks internationally.
PubDate: 2022-01-23
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- Using indoor plants as biomonitors for detection of toxic metals by
tobacco smoke-
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Abstract: Clean air is an indispensable resource for modern world. Many people are indifferent to the seriousness of air pollution or have only recently realized the problem. The air pollution continues deteriorating with several emissions every year on global scale. Beside various sources, tobacco smoke has caused the indoor air pollution. One of the most important of these factors is smoking. Especially indoor air pollution occurs depending on tobacco use. Exposure to cigarette smoke is recognized as the most significant health problem in indoor air. The study aims to evaluate the toxic metal accumulation due to tobacco smoke indoors by using some indoor ornamental plants. In this study, Dieffenbachia amoena, Dracena marginata, Ficus elastica, Spathiphyllum wallisii, and Yucca massengena were used houseplants as biomonitors. Accumulation of some toxic metals can be easily seen in indoor plants. Cadmium (Cd), chrome (Cr), and lead (Pb) were selected that high emissions from tobacco smoke. They were determined by taking the leaves of the plant species and analyzed with inductively coupled plasma-optical emission spectrometry (ICP-OES). The Cd, Cr, and Pb concentrations (Pb > Cr > Cd) were higher with tobacco than non-tobacco in all species. The results showed that Spathiphyllum wallisii was selected to be most suitable as biomonitor.
PubDate: 2022-01-23
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- Dust particles transport during the rare strong sandstorm process in
Northern China in early year 2021-
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Abstract: Several sandstorms occured in northern China in early 2021, especially the rare serious one on March 15. The maximum hourly mean concentrations of PM10 in three sandstorm processes in Beijing reached 7506, 2567, and 1456 μg/m3, respectively. The maximum daily mean concentration of PM10 reached 1630 μg/m3. Consecutive days of high PM10 concentrations in mid-to-late March led to the monthly mean concentration exceeding 150 μg/m3 for the first time since 2017, and it also to be the highest monthly mean concentration in recent years. Air mass transport analysis results showed that the strong uplift of dust particles from desertification areas and the long-range transport of dust particles should be the important reasons for the outbreak of large-scale serious sandstorms. The development and eastward movement of the Mongolian cyclone should be mainly responsible for the sandstorms on March 15 and 28. The desertification in Mongolia should be an important cause of these two serious sandstorms. And the arid areas in northern China might have contributed to the intensification of the sandstorms. The arid areas in southern Mongolia and northern Inner Mongolia might be important sources of dust particles for the sandstorm on April 15. Graphical abstract
PubDate: 2022-01-21
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- Evidence for reduced performance discrepancy of improved cookstoves at
laboratory and field-
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Abstract: The discrepancy in the performance of improved cookstoves (ICSs) in laboratory and field settings has been well demonstrated, with field results portraying considerable decrease in performance resulting in partial fulfilment of claims due to various factors. This study aims at determining possible discrepancy causing factors—categorised as controllable and uncontrollable. Additionally, performance discrepancy of various cookstoves was explored by testing them in both the settings, keeping the controllable factors consistent. The testing method was in line with Bureau of Indian Standards protocol for testing one traditional cookstove (TCS), three natural draft ICS and one forced-draft (FD) ICS; the cookstoves were evaluated for total particulate matter (TPM), carbon monoxide (CO) concentration measured in the proximity of the cookstove and thermal efficiency. Results reveal TCS to be the major TPM and CO emitter in both the settings, while FD stove was the cleanest. Average increase of TPM and CO in field was found 31% and 33%, respectively, with 10% decrease in thermal efficiency compared to laboratory. Statistical analysis shows substantially less laboratory and field performance variations as compared to previous studies. However, deviations in the results were attributed to uncontrollable factors like kitchen aspect ratio, air exchange rate and local weather among others which are dissimilar to laboratory conditions. Findings from the study are helpful in synchronising the laboratory and field performance by strictly adhering to the controllable factors and outlining the uncontrollable factors while testing before certifying stoves.
PubDate: 2022-01-20
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- Characterisation of errors in an urban scale atmospheric dispersion model
through clustering of performance metrics-
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Abstract: This work introduces a methodology to perform a comprehensive analysis of the performance of atmospheric dispersion models, using the urban scale DAUMOD-GRS model as a testing ground. The estimation of NO2 concentration of this model at an urban background site in the city of Buenos Aires is compared with long-term observed concentration series. Days are classified through clustering analysis according to their model performance level on a three-dimensional metric space (fractional bias, normalised mean square error and correlation coefficient), and four clusters are obtained. An assessment of whether or not classes occur under different typical meteorological conditions is then performed. The largest statistical differences amongst clusters occur for wind speed and air temperature. The method is also used to assess the performance of a modified version of DAUMOD-GRS. The modification leads to a general improvement, mostly due to greater accuracy during night-time, which improves the ability of the model to estimate the NO2 peak concentration values, occurring at early morning and late evening hours. This is an example of how clustering techniques can be used to identify specific conditions under which a model underperforms, understand its causes and test potential model improvements.
PubDate: 2022-01-16
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- PM2.5-PAHs and PM10-PAHs at roadside environment: levels, meteorological
impact, source apportionment, and health risks-
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Abstract: Polycyclic aromatic hydrocarbon (PAH) concentrations in PM10 and PM2.5 were measured at the roadside of 4 typical urban roads in Tianjin from January to August 2015. The medium flow samplers with pretreated quartz filters were used for particulate matter sampling. Eighteen PAHs were analyzed by gas chromatography-mass spectrometry. The concentrations of PM2.5-PAHs and PM10-PAHs in winter were 74.98 ng/m3 and 94.22 ng/m3, followed by spring and the lowest in summer. The traffic flow is positively correlated with benzo(a)pyrene, benzo(g,h,i)perylene, and coronene. The vehicle speed and temperature are significantly positively correlated with low-ring polycyclic aromatic hydrocarbons and negatively correlated with the middle- and high-cyclic aromatic hydrocarbons. The ratio analysis of some PM2.5-PAHs and PM10-PAHs suggests that gasoline and diesel vehicles were the major sources of the studied area. Industrial emission, vehicle exhaust, and vehicle non-exhaust (tire wear, brake pad wear, and road dust) were identified as the major sources of roadside PAHs using positive matrix factorization analysis. The incremental lifetime cancer risk of ingestion and dermal contact were higher than that of inhalation, indicating that ingestion and dermal contact were the primary exposure routes for cancer. Therefore, it is necessary to take measures to strictly control the PM-PAHs pollution emitted by motor vehicles and formulate standards for PM-PAHs emitted by vehicles. Graphical abstract
PubDate: 2022-01-13
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- COP26 – time for action
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PubDate: 2022-01-12
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- Passenger exposure to aerosols on intra-European train travel
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Abstract: Knowledge about personal aerosol exposure in different environments is fundamental for individual and common decision-making, shaping the way we build our infrastructure or change our social behaviours. Aerosols are a leading cause of death and well-known vector for infectious diseases. Yet, passenger exposure to aerosols during long-distance train travel is surprisingly underexplored. Two small, light-weight personal monitoring instruments were employed during a train journey across Europe, to measure the fine particle (PM2.5) and equivalent black carbon (eBC) passenger exposure, respectively. The journey was divided into three legs, inside three different trains, and two layovers in city environments. Highest mean concentrations of PM2.5 and eBC were found within the oldest train type, and revealed PM2.5 concentrations of 58.4 ± 12.7 μg m−3 and eBC of 5.4 ± 2.9 μg m−3. The more modern the train system was, the lower the measured concentrations were to be found. In the newest tested system, the air quality was considerably better inside the train than outdoor air measured by a monitoring network, or simulated by the Copernicus Atmosphere Monitoring Service (CAMS) model ensemble analysis. The mean PM2.5 concentration was roughly 20% lower inside the train than the outdoor air simulated by CAMS. Both the light-weight personal monitoring and the monitoring network indicate that the CAMS ensemble substantially underestimates PM2.5 concentrations for the day of the journey. Effective ventilation and air filtration significantly decrease the passenger’s aerosol exposure, as compared to a stay in outdoor air, leading to a small statistical increase in life expectancy. If this could also reduce the risk of contagion with an infectious disease remains to be explored.
PubDate: 2022-01-12
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- Modeling future asthma attributable to fine particulate matter (PM2.5) in
a changing climate: a health impact assessment-
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Abstract: Exposure to fine particulate matter (PM2.5) is associated with asthma development as well as asthma exacerbation in children. PM2.5 can be directly emitted or can form in the atmosphere from pollutant precursors. PM2.5 emitted and formed in the atmosphere is influenced by meteorology; future changes in climate may alter the concentration and distribution of PM2.5. Our aim is to estimate the future burden of climate change and PM2.5 on new and exacerbated cases of childhood asthma. Projected concentrations of PM2.5 are based on the Geophysical Fluid Dynamics Laboratory Coupled Model version 3 climate model, the Representative Concentration Pathway 8.5 greenhouse gas scenario, and two air pollution emissions datasets: a 2011 emissions dataset and a 2040 emissions dataset that reflects substantial reductions in emissions of PM2.5 as compared to the 2011 inventory. We estimate additional PM2.5-attributable asthma as well as PM2.5-attributable albuterol inhaler use for four future years (2030, 2050, 2075, and 2095) relative to the year 2000. Exacerbations, regardless of the trigger, are counted as attributable to PM2.5 if the incident disease is attributable to PM2.5. We project 38 thousand (95% CI 36, 39 thousand) additional PM2.5-attributable incident childhood asthma cases and 29 million (95% CI 27, 31 million) additional PM2.5-attributable albuterol inhaler uses per year in 2030, increasing to 200 thousand (95% CI 190, 210 thousand) additional incident cases and 160 million (95% CI 150, 160 million) inhaler uses per year by 2095 relative to 2000 under the 2011 emissions dataset. These additional PM2.5-attributable incident asthma cases and albuterol inhaler use would cost billions of additional U.S. dollars per year by the late century. These outcomes could be mitigated by reducing air pollution emissions.
PubDate: 2022-01-10
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- Combined effects of different leaf traits on foliage dust-retention
capacity and stability-
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Abstract: The combined effects of different leaf traits determine their deposition and release processes, resulting in complex dynamics of particulate matter (PM) retention on foliage. Foliar dust from six common species in Jinzhong City, China, during three periods was investigated to analyze the combined effect of different leaf traits on PM retention and stability. A single leaf trait could not override all other leaf traits to determine the PM retention capacity; alternatively, the combined effects of different leaf traits (leaf morphometric characteristics and leaf surface microstructures) determined the PM retention capacity and retention stability. Small leaf size enhanced PM retention per unit area but had a negative impact on PM retention per leaf. Leaf hair had higher potential for PM retention than other rough microstructures on the leaf surface. Leaf species with a high PM retention capacity retained more PM100 than other species, and PM which adhered to the leaves was more stable than others. The stability of PM>100 was significantly affected by the leaf hair, and leaves with hard texture or leaf hair could improve the stability of PM retention. These results provide valuable information regarding the relationships between the combined effects of different leaf traits, PM retention capacity, and retention stability. Moreover, the results provide valuable insights into the selection of plant species to alleviate air pollution.
PubDate: 2022-01-10
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- Adopting urban morphological indicators to land use regression modeling of
seasonal mean PM2.5 concentrations for a high-density city-
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Abstract: As a common air pollutant, particulate matter (PM2.5) can lead to serious health risks when inhaled over a long period of time, and it is therefore especially important for urban residents to understand the distribution characteristics of PM2.5 within the urban space. To predict long-term PM2.5 exposure at high resolution in high-density cities and quantify the influence of urban spatial morphological characteristics on the distribution of PM2.5 concentration produced under long-term conditions. The seasonal mean values of PM2.5 concentration from 23 monitoring stations in Shenzhen, China were used as dependent variables, and 6 categories of 502 potential predictor variables including urban/building spatial morphological indicators were used as independent variables. The seasonal land use regression models were developed by combining stepwise supervision and Akaike information criterion (AIC) selection with a leave-one-out-cross-validation (LOOCV) to test the prediction performance of the model. The adjusted R2 values were 0.86, 0.70, 0.70 and LOOCV R2 values were 0.83, 0.58, 0.68 in the first three seasons, respectively. In addition to the variables of land use category (i.e., the proportion of land for industrial and manufacturing, the proportion of land for green space and square, and the proportion of land for municipal utilities) and physical geography category (i.e., the count of parks and squares, average elevation), building coverage ratio and the diversity of building volume were also selected into the model as predictor variables. The R2 contributions of urban/building spatial morphology factors exceeded 10% for all three seasonal models. This study developed seasonal land use regression (LUR) models with good prediction performance for a high-density city and provided high-resolution spatial mapping of PM2.5 under steady-state conditions. The contribution of urban/building spatial morphological indicators to the interpretation of R2 for LUR models confirmed the effect of high-density urban morphology on the distribution of PM2.5 concentration. The quantitative correlation between PM2.5 concentration and spatial morphological factors such as building coverage and building volume diversity can provide a basis for incorporating air pollution dispersion considerations to urban planning at early stage.
PubDate: 2022-01-08
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- Effects of ambient fine particulate matter on oxidative stress,
inflammation, and janus kinase/signal transducer and activator of
transcription signal molecules: a panel study of asthmatic adults in
Taiyuan, China-
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Abstract: This panel study attempted to assess the effects of ambient fine particulate matter (PM2.5) exposure on oxidative stress, inflammation, and janus kinase (JAK)/signal transducer and activator of transcription (STAT) signal molecules. Twenty-nine nonsmoking adults with asthma were followed up for three seasons. Lung function was measured four times and peripheral blood was collected one time per season. The markers of oxidative stress, inflammation, and JAK/STAT were detected. Daily concentration of ambient PM2.5 was recorded from the China National Environmental Monitoring Center. Linear mixed-effects regression models were used to investigate the relationships of ambient PM2.5 with the index of lung function, oxidative stress, inflammation, and JAK/STAT. Mediation analyses were used to explore the mediation effect of JAK. The concentration of PM2.5 was the highest in spring, with a median of 151 μg/m3. In the analyses of oxidative stress, the malonaldehyde (MDA) increased by 3.80% (95% CI: 2.43 to 5.17%; p<0.001) for each 10 μg/m3 increase in lag4 PM2.5 exposure. Furthermore, we detected a significant association in cytokines. Lag4 PM2.5 exposure was associated with an increased interleukin-4 (IL-4) by 3.00% (95% CI: 0.26 to 5.74%; p<0.05). Besides, we found mediation of JAK2 in the associations between superoxide dismutase (SOD)/IL-12 and STAT4, JAK3 in the association between MDA and STAT6. The injury of pulmonary function in asthmatic adults induced by ambient PM2.5 exposure is most likely to occur at lag 4 days. Ambient PM2.5 aggravates asthma by systemic oxidative stress and inflammation, in which JAK/STAT signal molecules may be involved. Graphical abstract
PubDate: 2022-01-08
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- European Union policies and their role in combating climate change over
the years-
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Abstract: The worrying environmental situation and increased public awareness in recent years have led many countries to take measures to reduce negative impacts on the environment. The European Union (EU) has been one of the most active in environmental protection with the formulation of policies aimed at preserving the health and well-being of citizens and protecting natural resources. One of the objectives of environmental policies is to make the economy of its member states more environmentally friendly, although this requires finding solutions to major challenges such as climate change, the scarcity of natural resources, the emission of polluting gases, and unsustainable consumption and production. This article reviews the main policies that have been implemented in the EU to reduce environmental problems and the scope of climate change conferences. It offers solutions to promote sustainability that could be adopted by companies, individuals, and governmental institutions to jointly contribute to achieving a more sustainable world, where problems such as climate change or the emission of polluting gases are minimized. The aim is to follow the principles of the Circular Economy and the European Green Deal.
PubDate: 2022-01-08
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- Analysis and research of absorbing aerosols in Beijing-Tianjin-Hebei
region-
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Abstract: In the Beijing-Tianjin-Hebei (BTH) urban agglomeration, the atmospheric particulate matter (PM) pollution has become exacerbated year by year. In an attempt to understand the current condition of aerosol particulate pollution in the BTH region, the temporal and spatial distribution, future trend changes, and potential source areas of absorbing aerosols in the BTH region from 2005 to 2019 were analyzed based on Ozone Monitoring Instrument/Aura Near UV Aerosol Optical Depth and Single Scattering Albedo 1-orbit L2 Swath 13 × 24 km V003 (OMAERUV) daily product data; besides, relevant influencing factors were explored in this study. As per the analysis of results, the ultraviolet aerosol index (UVAI) increased by 3.03% in the time series from 2005 to 2019. Spatially, the absorbing aerosol in the North China Plain was always maintained in a high-value area, and the15-year average annual UVAI value has been as high as 0.45. In the monthly time series, a “V” shape started from January. The peak value of seasonal characteristics reached the highest in winter, followed by autumn and spring, and the lowest in summer. The external potential sources in the BTH region are mainly sand and dust sources generated in the northwest, while those of absorbing aerosols are mainly carbon sources in spring, with the lowest external absorbing aerosols in summer. The potential sources of absorbing aerosols in autumn are relatively complicated. The potential sources of absorbing aerosols are mainly sand and dust sources in the north. The time series of absorbing aerosols mainly showed an anti-continuous rise, and 54.23% of absorbing aerosols indicated an upward trend that would occur in the future. The relationship between absorbing aerosols and PM2.5 is mutual conversion. According to the path coefficient, industrial production activities are important sources of atmospheric absorbing aerosols, and precipitation can reduce the content of absorbing aerosols in the atmosphere caused by industrial production.
PubDate: 2022-01-08
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- Mutagenicity of PM10-bound PAHs from non-exhaust sources
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Abstract: Road traffic is a major source of airborne particles. While exhaust emissions have been deeply scrutinised, non-exhaust emissions deserved less attention despite their rising contribution to particle emissions from traffic. The mutagenicity of particulate matter (PM10) samples from wear between pavements and tyres and from road dust resuspension was determined by the Ames test with two Salmonella typhimurium strains (TA98 and TA100) with or without metabolic activation. After sequential extraction of PM10 samples in dichloromethane and methanol, the extracts were separated via flash chromatography and the subfraction that contained polycyclic aromatic compounds (PAHs) was used in the assays. Additionally, the samples were analysed by gas chromatography-mass spectrometry (GC–MS). The analysed extracts contained predominantly high molecular weight PAHs with varying concentrations. The non-exhaust traffic-related source samples did not reveal mutagenic potential at the doses examined. Given the compositional complexity of the samples, aggregating multiple metals and organic compounds of different polarities, an integrated assessment of the toxicity of non-exhaust particles should include other in vitro toxicity assays.
PubDate: 2022-01-07
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- Analysis of the impact of multiscale green landscape on urban PM2.5
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Abstract: PM2.5 is a serious threat to human health. Greenspace landscape patterns, which have a major impact on urban air quality, have recently attracted much attention, but most recent studies have focused only on — area configurations or structures, and there is a lack of research on the factors that influence PM2.5 concentrations and their spatial differentiation characteristics at seasonal and spatial scales. Based on the data of air quality monitoring stations in Beijing and remote sensing data, this paper selects indicators and data on five kinds of landscape variables and explores the response characteristics of PM2.5 to surrounding environmental factors from multiple perspectives through the least absolute shrinkage and selection operator (LASSO), multiple regression, Spearman grade correlation, and geographical detector techniques. The results show that the response of PM2.5 to landscape patterns in autumn is more obvious than that in other seasons. The PM2.5 concentration is positively correlated with relative humidity in four seasons and temperature in summer and negatively correlated with wind speed in spring. The contribution of green landscape composite factors to PM2.5 concentration is higher than that of single factors. The research results can provide references for Beijing’s urban planning and design.
PubDate: 2022-01-06
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- Implosion–demolitions: impact on the local environment in a tropical
humid Ramsar site located in southwestern India-
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Abstract: Implosion–demolitions are used to bring down tall-storied structures in urban centers. This technique was employed to raze four residential complexes constructed against the law in India’s tropical coastal city (Kochi). The demolitions were carried out in an ecologically fragile area. It is the first of a kind experiment in India and the highest structure to be ever demolished. Our study is also the first detailed report regarding the potential threat from implosion to local biological communities. This study involved analysis of the particulate matter, dustfalls, road dust, and water samples. This study further demonstrates the application of statistical indices (geo-accumulation index, (Igeo), contamination factor (CF), pollution load index (PLI), and potential ecological risk index (PERI)) for effective prediction of environmental impacts due to implosion events. The results indicated an acute impact on local PM10 concentration, a substantial increase in the metal/metalloid concentration of dust falls, and conductivity and ion concentration of road dust and water samples. The Igeo values showed high pollution of dustfalls with Cd and Zn. Similarly, the CF values revealed very high contamination of dustfalls by Zn, Cr, Pb, and Cd. The PLI (1.93) > 1 confirmed the site quality deterioration. Furthermore, the high PERI (1181.78) indicated that the local biological communities were exposed to severe risk.
PubDate: 2022-01-04
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- Health risks of adults in Hong Kong related to inhalation of
particle-bound heavy metal(loid)s-
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Abstract: Heterogeneity between ambient and personal exposure to heavy metals has been documented. However, few studies have investigated potential health risks posed by inhalational exposure to airborne heavy metal(loid)s at the individual level. A total of 404 personal fine particles (PM2.5) samples were collected from 61 adult residents (aged 18–63 years) in Hong Kong during 2014–2015. Heavy metal(loid)s were analyzed using energy dispersive X-ray fluorescence. Among the analyzed heavy metal(loid)s, zinc (Zn) was the most abundant component in personal PM2.5, followed by lead (Pb), copper (Cu), and vanadium (V); cobalt (Co) and cadmium (Cd) were not detectable. Health risks of personal exposure to heavy metal(loid)s via inhalation were assessed for adults, including non-cancer risks that were characterized by hazard quotient (HQ) and hazard index (HI). The results indicated that non-cancer risks of heavy metal(loid)s were attributable to Cu, with a 95th HQ value > 1. Arsenic (As) and hexavalent chromium [Cr (VI)] were also significant contributors to inhalation cancer risks (> 1 × 10−6) for the adult participants. Finally, we employed a Monte Carlo simulation to evaluate the uncertainty associated with health risk assessment. The mean and median upper-bound lifetime cancer risk associated with inhalation exposure to carcinogenic heavy metal(loid)s exceeded the acceptable level (1 × 10−6) for adults. Traffic emission (including non-tailpipe exhaust), shipping emission, and regional pollution were significant sources of heavy metals. These findings suggest that emission controls targeting local vehicles and vessels should be given priority in Hong Kong.
PubDate: 2022-01-01
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