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PM2.5 and PM10 in the atmosphere seriously affect human health and air quality, a situation which has aroused widespread concern. In this paper, we analyze the temporal and spatial distribution of PM2.5 and PM10 concentrations from 2016 to 2021 based on real-time monitoring data. In addition, we also explore the influence of meteorological conditions on pollutants. The results show that PM2.5 and PM10 concentrations are similarly distribution in temporal and spatial from 2016 to 2021, and the average concentrations of both show a decreasing trend. The ratio of PM2.5 to PM10 is decreasing, indicating that the proportion of fine particles is declining. PM2.5 and PM10 concentrations are higher in spring and winter, but lower in summer. Spatially, it shows a gradual shift from the characteristic of "high in the south and low in the north" to a uniform homogenization across districts. The spatial distribution of PM2.5 and PM10 mass concentrations is synchronous by applying empirical orthogonal functions (EOF). The first EOF pattern exhibits a consistent characteristic of high in the southeast and low in the northwest. The second pattern EOF reflects the effect of impairing PM2.5 concentrations in the southeast during the winter of 2016–2018. The PM2.5 and PM10 concentrations are significantly negatively correlated with wind speed and precipitation in both spring and winter. On the other hand, from the perspective of the circulation situation, the southeasterly and weak westerly wind in spring produce convergence resulting in higher particulate matter concentrations in the south than in the north in Beijing. The westerly wind is flatter at 700 hPa geopotential height, which is conducive to the formation of stationary weather. The vertical direction of airflow in spring and winter is dominated by convergence and sinking, indicating the weak dispersion ability of the atmosphere. The reason for the accumulation of particulate matter at the surface is investigated, which is beneficial to provide the theoretical basis for air quality management and pollution control in Beijing. [ABSTRACT FROM AUTHOR]

The concentration series of PM2.5 (particulate matter ≤ 2.5 μm) is nonlinear, nonstationary, and noisy, making it difficult to predict accurately. This paper presents a new PM2.5 concentration prediction method based on a hybrid model of complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and bi-directional long short-term memory (BiLSTM). The new method was applied to predict the same kind of particulate pollutant PM10 and heterogeneous gas pollutant O3, proving that the prediction method has strong generalization ability. First, CEEMDAN was used to decompose PM2.5 concentrations at different frequencies. Then, the fuzzy entropy (FE) value of each decomposed wave was calculated, and the near waves were combined by K-means clustering to generate the input sequence. Finally, the combined sequences were put into the BiLSTM model with multiple hidden layers for training. We predicted the PM2.5 concentrations of Seoul Station 116 by the hour, with values of the root mean square error (RMSE), the mean absolute error (MAE), and the symmetric mean absolute percentage error (SMAPE) as low as 2.74, 1.90, and 13.59%, respectively, and an R2 value as high as 96.34%. The "CEEMDAN-FE" decomposition-merging technology proposed in this paper can effectively reduce the instability and high volatility of the original data, overcome data noise, and significantly improve the model's performance in predicting the real-time concentrations of PM2.5. [ABSTRACT FROM AUTHOR]

As fleet electrification progresses, vehicles are continuously becoming heavier, while the used electric motors, with their high torques, enable longitudinal dynamics to be maintained or even increased. This raises the question of what effect electric vehicles have on the emission of tire–road particulate matter (PM). To answer this question, investigations were carried out in this study on a tire internal drum test bench with real road surfaces. In addition to the vertical load, the tire inflation pressure and the driving speed were varied. PM emissions were recorded in real time, resulting in emission factors (emission per kilometer driven) for different load conditions. This allows statements to be made about both the effect on the total emission and on the particle size distribution. It was shown that the PM emission increases linearly with the vertical load at constant longitudinal dynamics. If the tire inflation pressure is increased, the emission also increases linearly, and the increases in emission are equally large for both influences. A clear influence of the driving speed on the emission factor could not be determined. With regard to the particle size distribution, the following correlations were found: higher vertical load and higher tire inflation pressure result in a larger mean particle diameter, while a higher driving speed reduces it. Thus, this study contributes to a better understanding of the expected changes in tire-road PM emissions as a result of electrification. [ABSTRACT FROM AUTHOR]

The objective of this study was to experimentally determine the mathematical correlations between the loading of the tire, being longitudinal and lateral forces, and the emission of particulate matter (PM) from the tire–road contact. Existing emission factors (EF, emission per vehicle and distance traveled) are the result of long-term measurements, which means that no conclusion can be drawn about the exact driving condition. To determine meaningful emission factors, extensive driving tests were conducted on an internal drum test bench while measuring PM emissions from the tire–road contact in real-time. This showed that the increases in emission over longitudinal and lateral forces can be approximated with fourth-order functions, with lateral forces leading to significantly higher emissions than longitudinal forces for the summer tire investigated. Using the emission functions obtained, a three-dimensional map was created that assigns an EF to each load condition consisting of different longitudinal and lateral forces for one vertical load. With known driving data, the map can be used for future simulation models to predict the total emission of real driving cycles. Furthermore, the results show that the average particle size increases with increasing horizontal force. The particles collected during the tests were analyzed to determine the proportions of tire and road material. According to the results, the tire contributes only about 20% of the particle mass, while 80% is attributable to the road surface. In terms of volume, these shares are 32% and 68%, respectively. [ABSTRACT FROM AUTHOR]

Respirable particulate matter (PM10) is atmospheric particulate matter with a kinetic diameter of less than or equal to 10 μm in air. According to the definition of the World Health Organization, it is called thoracic-enterable particulate matter because it can enter the body through the respiratory tract and be deposited into the lungs or absorbed into the blood and lymphatic systems. The toxic substances in it can enter the bloodstream directly and cause serious harm to human health. In addition, PM10 has unique physiological and biological effects, making it an important area of atmospheric chemistry research. In this study, two urban neighborhoods and sports companies were selected for the purpose of investigating the effects of PM10 concentrations in the air of neighborhoods and workplaces on people living and working in these environments for a long period of time, as well as synergistic effects between PM10 concentrations and changes in temperature and the incidence of related diseases. By assessing the extent of PM10's impact on the respiratory system, this study provides basic data for assessing the health hazards of particulate matter in community environments. This study also analyzed the synergistic effects between air pollutant concentrations, temperature changes, and the incidence of related diseases in two cities to investigate the spatial and temporal distribution characteristics of air pollution and the meteorological causes of pollution in China. On this basis, we established a prediction model for related sensitivity diseases to provide theoretical and technical support for the prediction of related sensitivity diseases on a nationwide scale. Meanwhile, our study also provides support to relevant government departments to formulate a scientific basis and preventive and control measures for dealing with air pollution and its effects on human health. [ABSTRACT FROM AUTHOR]

PM10 prediction has attracted special legislative and scientific attention due to its harmful effects on human health. Statistical techniques have the potential for high-accuracy PM10 prediction and accordingly, previous studies on statistical methods for temporal, spatial and spatio-temporal prediction of PM10 are reviewed and discussed in this paper. A review of previous studies demonstrates that Support Vector Machines, Artificial Neural Networks and hybrid techniques show promise for suitable temporal PM10 prediction. A review of the spatial predictions of PM10 shows that the LUR (Land Use Regression) approach has been successfully utilized for spatial prediction of PM10 in urban areas. Of the six introduced approaches for spatio-temporal prediction of PM10, only one approach is suitable for high-resolved prediction (Spatial resolution < 100 m; Temporal resolution ≼ 24 h). In this approach, based upon the LUR modeling method, short-term dynamic input variables are employed as explanatory variables alongside typical non-dynamic input variables in a non-linear modeling procedure. [ABSTRACT FROM AUTHOR]

While the district of Mae Moh, Thailand has been well known for its atmospheric pollution associated with coal power production, economic assessment of demand for improved air quality has not been conducted to date. This study estimated local residents' individual and aggregate willingness to pay (WTP) for mitigation of atmospheric pollution in Mae Moh using the contingent valuation method (CVM), and analyzed the factors associated with the individual WTP using the bivariate tobit and double-hurdle regression techniques. Primary data were collected through face-to-face interviews with a stratified sample of 200 residents. The hypothetical scenarios used in the CVM module were 50% and 80% mitigation of atmospheric concentrations of major pollutants. The weighted average WTP was found to be THB 251.3 and 307.9 per annum (USD 8.4 and 10.3) for the 50% and 80% reduction scenarios, respectively. The aggregate WTP for the entire population of Mae Moh was THB 10,008,733 and 12,264,761 per annum (USD 336,294 and 412,096), respectively. Education, occupation type, income, expenses, satisfaction with ambient quality, and perceived sources of pollution had significant associations with the individual WTP. The paper concludes by discussing policy implications for atmospheric pollution management and avenues for future research. [ABSTRACT FROM AUTHOR]

This study focuses on particulate matter emissions from tire–road contact and their investigation using an internal drum test bench. The test bench is equipped with real-road surfaces and has been upgraded to enable real-time measurements of particulate matter. It was found that the road surface changes during the tests due to constant rolling over, influencing the level of emissions significantly. To account for this effect, the micro roughness was characterized before, during, and after the tests. Specific emission values consisting of particle mass and number were determined with summer, all-season, and winter tires for different road conditions, as well as specific longitudinal and lateral forces. It turned out that emissions increase disproportionately with load for both force directions. The winter tire led to the highest emissions across all loads, and the summer tire led to the lowest ones. While lateral forces caused emissions many times higher than longitudinal forces for the summer tire, forces in both directions led to comparable emissions for the all-season and winter tires. Regarding the ambient temperature, a lower one seems to be favorable for summer tires and a higher one seems to be favorable for winter tires. Lastly, particle size distributions during different load conditions show a dependence on load, such that larger particles are emitted with increasing load. [ABSTRACT FROM AUTHOR]

Air quality (AQ) in urban areas is deteriorating, thus having negative effects on people's everyday lives. Official air quality monitoring stations provide the most reliable information, but do not always depict air pollution levels at scales reflecting human activities. They also have a high cost and therefore are limited in number. This issue can be addressed by deploying low cost AQ monitoring devices (LCAQMD), though their measurements are of far lower quality. In this paper we study the correlation of air pollution levels reported by such a device and by a reference station for particulate matter, ozone and nitrogen dioxide in Thessaloniki, Greece. On this basis, a corrective factor is modeled via seven machine learning algorithms in order to improve the quality of measurements for the LCAQMD against reference stations, thus leading to its on-field computational improvement. We show that our computational intelligence approach can improve the performance of such a device for PM10 under operational conditions. [ABSTRACT FROM AUTHOR]

Exhaust regulations and improved exhaust gas treatment systems have already initiated the trend that brings emissions from brakes and tires to the forefront of traffic-induced particulate matter. The health and environmental relevance of particulate matter has resulted in regulators, industry, and research institutions prioritising the mitigation of non-exhaust particle emissions. To this end, under the umbrella of the United Nations Economic Commission for Europe World Forum for Harmonisation of Vehicle Regulations (UNECE WP.29), the Working Party on Pollution and Energy (GRPE) mandated the Particle Measurement Programme Informal Working Group (PMP-IWG) to develop a Global Technical Regulation (GTR) for measuring brake dust. The standards and procedures defined within the GTR should eventually form the basis for the introduction of a Euro 7 limit value for brake emissions. The purpose of this measurement campaign is to provide an exemplary overview of the emission behaviour of wheel brakes and friction pairings currently available on the market and to identify possible reduction potential with regard to particulate emissions. All measurements were carried out taking into account the draft GTR valid at the time of execution. For the investigations, brakes were selected using the example of different vehicle classes, brake concepts (disc and drum brake), vehicle axles (front and rear axle), and alternative friction materials (brake disc and pads/shoes). Thus, the use of wear-resistant discs and improved brake pad compositions are able to achieve significantly lower emissions. In addition, the measurement of brake dust emissions from vehicles with different levels of electrification was considered. Electrical braking was modelled and applied to the Worldwide Harmonised Light-Duty Vehicles Test Procedure (WLTP) Brake Cycle, which has demonstrated high emission reduction potentials depending on the electrification level. [ABSTRACT FROM AUTHOR]

Handan is a typical city affected by regional particulate pollution. In order to investigate particulate matter (PM) characterization, source contributions and health risks for the general populations, we collected PM samples at two sites affected by a pollution event (12–18 May 2020) during the COVID-19 pandemic and analyzed the major components (SNA, OCEC, WSIIs, and metal elements). A PCA-MLR model was used for source apportionment. The carcinogenic and non-carcinogenic risks caused by metal elements in the PM were assessed. The results show that the renewal of old neighborhoods significantly influences local PM, and primarily the PM10; the average contribution to PM10 was 27 μg/m3. The source apportionment has indicated that all other elements came from dust, except Cd, Pb and Zn, and the contribution of the dust source to PM was 60.4%. As PM2.5 grew to PM10, the PM changed from basic to acidic, resulting in a lower NH4+ concentration in PM10 than PM2.5. The carcinogenic risk of PM10 was more than 1 × 10−6 for both children and adults, and the excess mortality caused by the renewal of the community increased by 23%. Authorities should pay more attention to the impact of renewal on air quality. The backward trajectory and PSCF calculations show that both local sources and short-distance transport contribute to PM—local sources for PM10, and short-distance transport in southern Hebei, northern Henan and northern Anhui for PM2.5, SO2 and NO2. [ABSTRACT FROM AUTHOR]

Malaysia has been facing transboundary haze events repeatedly, in which the air contains extremely high particulate matter, particularly PM10, which affects human health and the environment. Therefore, it is crucial to understand the characteristics of PM10 concentration and develop a reliable PM10 forecasting model for early information and warning alerts to the responsible parties in order for them to mitigate and plan precautionary measures during such events. This study aims to analyze PM10 variation and investigate the performance of quantile regression in predicting the next-day, the next two days, and the next three days of PM10 levels during a high particulate event. Hourly secondary data of trace gases and the weather parameters at Pasir Gudang, Melaka, and Petaling Jaya during historical haze events in 1997, 2005, 2013, and 2015. The Pearson correlation was calculated to find the correlation between PM10 level and other parameters. Moderate correlated parameters (r > 0.3) with PM10 concentration were used to develop a Pearson–QR model with percentiles of 0.25, 0.50, and 0.75 and were compared using quantile regression (QR) and multiple linear regression (MLR). Several performance indicators, namely mean absolute error (MAE), root mean squared error (RMSE), coefficient of determination (R2), and index of agreement (IA), were calculated to evaluate and compare the performances of the predictive model. The highest daily average of PM10 concentration was monitored in Melaka within the range of 69.7 and 83.3 µg/m3. CO and temperature were the most significant parameters associated with PM10 level during haze conditions. Quantile regression at p = 0.75 shows high efficiency in predicting PM10 level during haze events, especially for the short-term prediction in Melaka and Petaling Jaya, with an R2 value of >0.85. Thus, the QR model has high potential to be developed as an effective method for forecasting air pollutant levels, especially during unusual atmospheric conditions when the overall mean of the air pollutant level is not suitable for use as a model. [ABSTRACT FROM AUTHOR]

Studies on air quality frequently adopt clustering, in particular the k-means technique, owing to its simplicity, ease of implementation and efficiency. The aim of the present paper was the assessment of air quality in a winter season (December–February) in the conditions of temperature inversion using the k-means method, representing a non-hierarchical algorithm of cluster analysis. The air quality was assessed on the basis of the concentrations of particulate matter (PM10, PM2.5). The studies were conducted in four winter seasons (2015/16, 2016/17, 2017/18, 2019/20) in Wrocław (Poland). As a result of the application of the v-fold cross test, six clusters for each fraction of PM were identified. Even though the analysis covers only four winter seasons, the applied method has unequivocally revealed that the characteristics of surface-based (SBI) and elevated inversions (ELI) affect the concentration level of both fractions of particulate matter. In the case of PM10, the average lowest daily concentration (15.5 µg·m−3) was recorded in the conditions of approx. 205 m in thickness, 0.5 °C intensity of the SBI and at the height of the base of the ELI at approx. 1700 m a.g.l., a thickness of 148 m and an intensity of 1.2 °C. In turn, the average highest concentration (136 µg·m−3) was recorded at a thickness of SBI of approx. 400 m and an intensity of 1.4 °C. Such high concentration occurred when the lowest location of ELI formed at 764 m a.g.l. with a thickness of 308 m and an intensity of 0.96 °C. A marked role of the thickness of the SBI and ELI as well as the height of the base of the lowest location of ELI was also manifested with respect to PM2.5 concentrations. [ABSTRACT FROM AUTHOR]

This paper presents a statistical comparison of parallel hourly measurements of particulate matter smaller than 10 μ m (PM 10 ) from two monitoring stations that are located 560 m from each other in the northern part of Brno City. One monitoring station is located in a park, the other in a built-up area. The authors' aim is to describe the influence of a built-up area geometry and nearby traffic intensity on modeling of PM 10 pollution levels in the respective part of Brno. Furthermore, the purpose of this study is also to examine the influence of meteorological factors on the pollution levels; above all, to assess the influence of wind speed and direction, temperature change, and humidity change. In order to evaluate the obtained data, the following methods of mathematical statistics were applied: descriptive statistics, regression analysis, analysis of variance, and robust statistical tests. According to the results of the Passing–Bablok test, it can be stated that the parallel measurements of PM 10 are significantly different. A regression model for PM 10 pollution prediction was created and tested in terms of applicability; subsequently, it was used in order to compare measurements from both stations. It shows that in addition to the monitored meteorological factors, pollution levels are influenced mainly by traffic intensity and the geometry of the monitored built-up area. [ABSTRACT FROM AUTHOR]

Ambient bioaerosols affect ecosystems and public health, but their seasonal variations and their contributions to aerosol particles are limitedly understood. Ambient bioaerosols in PM2.5 and PM10 samples were measured in Huangshi City, Hubei Province of China from April 2018 to December 2018. Bioaerosols were measured using a fluorescence microscope after staining with 4′, 6-diamino-2-phenylindole dihydrochloride (DAPI) following a direct staining technique. The bioaerosol number concentrations ranged from 0.12 to 15.69 # cm−3 for PM2.5 and 0.22 to 18.20 # cm−3 for PM10, with averages of 2.79 # cm−3 and 4.66 # cm−3, respectively. The bioaerosol concentrations of PM2.5 and PM10 varied significantly by seasons and were arranged in the following descending order: spring > fall > winter > summer. Bioaerosol numbers were dominated by fine particles of 0.37–2.5 μm diameter, while the spring bioaerosol particles were detected at the peak concentration of 0.56–1 μm diameter. Bioaerosol fractions accounted for 18.3 ± 10.6% PM10 mass and 13.7 ± 12.5% PM2.5 mass. Bioaerosol concentrations were increased during the haze event, but the increased amounts were not as large as those of the dust event, and higher bioaerosol contributions to PM were observed in the dust event than in the haze event. As enhanced emission controls have reduced PM concentrations in China, bioaerosols can be important contributors to PM mass. [ABSTRACT FROM AUTHOR]

The dispersion of air pollutants and the spatial representation of meteorological variables are subject to complex atmospheric local parameters. To reduce the impact of particulate matter (PM2.5) on human health, it is of great significance to know its concentration at high spatial resolution. In order to monitor its effects on an exposed population, geostatistical analysis offers great potential to obtain high-quality spatial representation mapping of PM2.5 and meteorological variables. The purpose of this study was to define the optimal spatial representation of PM2.5, relative humidity, temperature and wind speed in the urban district in Cartagena, Colombia. The lack of data due to the scarcity of stations called for an ad hoc methodology, which included the interpolation implementing an ordinary kriging (OK) model, which was fed by data obtained through the inverse distance weighting (IDW) model. To consider wind effects, empirical Bayesian kriging regression prediction (EBK) was implemented. The application of these interpolation methods clarified the areas across the city that exceed the recommended limits of PM2.5 concentrations (Zona Franca, Base Naval and Centro district), and described in a continuous way, on the surface, three main weather variables. Positive correlations were obtained for relative humidity (R2 of 0.47), wind speed (R2 of 0.59) and temperature (R2 of 0.64). [ABSTRACT FROM AUTHOR]

The increasing frequency of human activities has accelerated changes in land use types and consequently affected the atmospheric environment. In this manuscript, we analyze the relationships between the particulate matter concentration and land use changes in the Beijing–Tianjin–Hebei (BTH) region, China, from 2015 to 2018. The experimental results indicate that (1) an improved sine function model can suitably fit the periodic changes in the particulate matter concentration, with the average R2 value increasing to 0.65 from the traditional model value of 0.49, while each model coefficient effectively estimates the change characteristics of each stage. (2) Among all land use types, the particulate matter concentrations in construction land and farmland are high, with a large annual difference between high and low values. The concentration decreases slowly in spring and summer but increases rapidly in autumn and winter. The concentrations in forestland and grassland are the lowest; the difference between high and low values is small for these land use types, and the concentration fluctuation pattern is relatively uniform. Natural sources greatly influence the concentration fluctuations, among which frequent dusty weather conditions in spring impose a greater influence on forestland and grassland than on the other land use types. (3) The landscape pattern of land use exerts a significant influence on the particulate matter concentration. Generally, the lower the aggregation degree of patches is, the higher the fragmentation degree is, the more complex the shape is, the higher the landscape abundance is, and the lower the particulate matter concentration is. The higher the construction land concentration is, the more easily emission sources can be aggregated to increase the particulate matter concentration. However, when forestland areas are suitably connected, this land use type can play a notable role in inhibiting particulate matter concentration aggravation. This conclusion is of great relevance to urban land use planning and sustainable development. [ABSTRACT FROM AUTHOR]

Dust emission from the Gobi desert is one of the major sources of global atmospheric aerosols. However, the main factors affecting dust emission from Gobi remain poorly understood. In this paper, field wind tunnel experiments were performed atop the Mogao Grottoes to determine the variation characteristics of the vertical dust flux (F) of particulate matter less than 10 μm (PM10) for Gobi surfaces with different dust content and wind speeds under external sand supply. The results demonstrate that F obeyed a power function with increasing friction velocity ( U * ), and increased exponentially with the increasing surface dust content (C). The index of n-value in the formula F∝ U * n is taken in the range of 2.02–2.63 under the surface of 27.3–47.3% dust content (<100 µm), and the dust emission rate was significantly enhanced when the surface dust content exceeded approximately 37%. This study indicates that wind force is the primary dynamic condition affecting Gobi dust emission, and that surface dust content is a significant factor in determining the quantity of dust emission. Furthermore, the contribution of wind force to PM10 emission is greater than the surface dust content, and the higher the height, the greater the weight of friction velocity. [ABSTRACT FROM AUTHOR]

An increased burden due to polycyclic aromatic hydrocarbons (PAH) is a long-term air quality problem in Central and Eastern Europe. Extensive PAH monitoring has been implemented at the National Atmospheric Observatory Košetice (NAOK), a rural background site in the Czech Republic, as a representative for Central Europe. Data from NAOK are used for evaluation of PAH concentration trends and source apportionment. In total, concentrations of 14 PAHs in particulate matter (PM10) and in the gas phase between 2006 and 2016 were evaluated. The highest concentrations were measured at the beginning of the study period in 2006. Mean annual concentrations of benzo(a)pyrene, for example, showed a weak, however statistically significant decreasing trend. The positive matrix factorization (PMF) was used to determine the sources of PAHs at NAOK, with three factors resolved. The probable origin areas of PMF factors were identified by the conditional bivariate probability function (CBPF) and the potential source contribution function (PSCF) methods. The NAOK is affected by local sources of PAHs, as well as by regional and long-range transport. The PAH concentrations correlate negatively with industrial production and traffic intensity. High PAH emissions have been linked to local heating, suggesting that the planned replacement of obsolete combustion sources in the households could improve the overall air quality situation, not only with respect to PAHs. [ABSTRACT FROM AUTHOR]

The present research has been focused on the evaluation of seasonal changes in mass concentrations and compositions of heavy metals in Particular Matters (PM)10 collected from a typical urban-industrial site in Acerra, a city located in an area called "triangle of death". No significant (p < 0.05) seasonal variation was evidenced for the PM10 concentration, but in all the seasons (except for autumn) exceedances of daily concentrations (50 μg m-3) were observed. Airborne PM was analyzed for these heavy metals: Al, As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Sb, V and Zn, which represented about 8% of the PM10 concentrations. None of the metals classified by IARC as carcinogenic in humans (group 1) exceeded on average the annual EU's and Italy's limit. For the mentioned heavy metals the enrichment factors (EnFs) were analyzed and highlighted high enrichment for Cd, Sb, Pb, As, Cu and Zn. Principal component analysis (PCA) for the heavy metals in PM10 identified oil combustion, vehicle and industrial emissions as major sources. To assess the health risk related to the inhalation to airborne PM10 metals, we applied the Cancer Risk (CR) and Target Hazard Quotient (THQ). The results showed that the CR was similar for a child and an adult, while the THQ proved to be higher for a child than for an adult. The low PM metals risk in the urban industrial site was in agreement with the ongoing lowering trend of metals in Italy and Europe. [ABSTRACT FROM AUTHOR]

A study of spatial variability of PM10 elemental components was conducted in Terni city (Central Italy), situated in an intramountain depression characterized by the presence of several particulate matter emission sources. The meteorological conditions of the Terni basin limit the dispersion and enhance the accumulation of atmospheric pollutants. Thanks to the utilization of new smart samplers, used for the first time and working in parallel at 23 sampling sites, spatially resolved data were obtained. Localizations of the samplers were chosen in order to evaluate the impact of different local PM10 sources. Chemical composition of the samples was determined in combination with a chemical fractioning procedure that allowed us to discriminate water-soluble and residual fractions of analyzed elements in which proved to be a valuable approach for increasing selectivity of elements as source tracers. Spatial variability of elements underlined the contribution of local emission sources and the different dispersion capacity of each element. The city of Terni resulted to be an ideal area to test and validate a new experimental method for the acquisition of spatially resolved data providing the possibility to properly evaluate the spatial variability of PM10 and its chemical components. [ABSTRACT FROM AUTHOR]

Background: Air pollution is a major global environmental risk factor. Since people spend most of their time indoors, the sole measure of outdoor concentrations is not sufficient to assess total exposure to air pollution. Therefore, the arising interest by the international community to indoor-outdoor relationships has led to the development of various techniques for the study of emission and exchange parameters among ambient and non-ambient pollutants. However, a standardised method is still lacking due to the complex release and dispersion of pollutants and the site conditions among studies. Methods: This review attempts to fill this gap to some extent by focusing on the analysis of the variety of site-specific approaches for the assessment of particulate matter in work and life environments. Results: First, the main analogies and differences between indoor and outdoor particles emerging from several studies are briefly described. Commonly-used indicators, sampling methods, and other approaches are compared. Second, recommendations for further studies based on recent results in order to improve the assessment and management of those issues are provided. Conclusions: This review is a step towards a comprehensive understanding of indoor and outdoor exposures which may stimulate the development of innovative tools for further epidemiological and multidisciplinary research. [ABSTRACT FROM AUTHOR]

Here, we report the chemical characterization and identification of the possible sources of particulate matter (fraction PM10) at two different sites in Naples. PM10 concentration and its chemical composition were studied using the crustal enrichment factor (EF) and principal component analysis (PCA). In all of the seasons, the PM10 levels, were significantly higher (p < 0.01) in the urban-traffic site (denominated NA02) than in the urban-background site (denominated NA01). In order to reconstruct the particle mass, the components were classified into seven classes as follows: mineral dust (MD), trace elements (TE), organic matter (OM), elemental carbon (EC), sea salt (SS), secondary inorganic aerosol (SIA) and undetermined parts (unknown (UNK)). According to the chemical mass closure obtained, the major contribution was OM, which was higher (p < 0.01) during summer than in other seasons. In both sites, a good correlation (R² > 0.8) was obtained between reconstructed mass and gravimetric mass. PCA analysis explained 76% and 79% of the variance in NA01 and NA02, respectively. The emission sources were the same for both sites; but, the location of the site, the different distances from the sources and the presence and absence of vegetation proved the different concentrations and compositions of PM10. [ABSTRACT FROM AUTHOR]

New ambient air quality standards were released in 2012 and implemented in 2013 with real time monitoring data publication of six atmospheric pollutants: particulate matter (PM)2.5, PM10, O3, SO2, NO2and CO. According to the new standards, Beijing began to publicize real-time monitoring data of 35 monitoring stations in 2013. In this study, real time concentrations of all six atmospheric pollutants of all 35 monitoring stations were collected from September 2014 to August 2015 to investigate the spatial and temporal pattern of the air quality and atmospheric pollutants. By comparing the annual and seasonal variations of all six pollutants' concentrations, it was found that particulate matter, especially PM2.5, is still the major contributor to the deterioration of air quality in Beijing. Although the NO2 and O3 concentrations of some stations were still high under certain circumstances, their contributions to air quality index (AQI) were not comparable to those of PM2.5 and PM10. SO2 and CO concentrations have dropped to well below the qualification standards. Winter and autumn were the most polluted seasons for all pollutants except O3, whose concentrations are higher in summer. South and southeast stations were the most polluted compared with the rest of the stations, especially for particulate matter. Wind profile analysis with heavy pollution situations indicates that low speed southwest or east wind situations have the higher possibility of heavy pollution, suggesting that it is highly possible that long-range transportation of air pollutants from south or east neighboring provinces played an important role in the worsening air conditions in Beijing. [ABSTRACT FROM AUTHOR]

Hourly average monitoring data for mass concentrations of PM1, PM2.5, PM10, and black carbon (BC) were measured in Wuhan from December 2013 to December 2014, which has a flourishing steel industry, to analyze the characteristics of PM and their relation to BC, using statistical methods. The results indicate that variations in the monthly average mass concentrations of PM have similar concave parabolic shapes, with the highest values occurring in January and the lowest values appearing in August or September. The correlation coefficient of the linear regression model between PM1 and PM2.5 is quite high, reaching 0.99. Furthermore, the proportion of PM1 contained within PM2.5 is roughly 90%, directly proving that ultrafine particles whose diameter less than 1 µm may be a primary component of PM2.5 in Wuhan. Additionally, better seasonal correlation between PM and BC occurs only in summer and autumn, due to multiple factors such as topography, temperature, and the atmosphere in winter and spring. Finally, analysis of the diurnal variation of PM and BC demonstrates that the traffic emissions during rush hour, exogenous pollutants, and the shallow PBLH with stagnant atmosphere, all contribute to the severe pollution of Wuhan in winter. [ABSTRACT FROM AUTHOR]

A survey was conducted to effectively investigate the characteristics of airborne particulate pollutants PM10 and PM2.5 during the peak tourist season at Mount Wutai Buddhism scenic spot, Shanxi, China. Characteristics of the PM10 and PM2.5 in Wu Ye Temple (core incense burners), Manjusri Temple (a traffic hub), Yang Bai Lin Village (a residential district), and Nan Shan Temple (located in a primitive forest district), were determined. The results showed that the PM10 concentration was more than 1.01-1.14 times higher than the threshold (50 μg/m³) of World Health Organization Air Quality Guidelines (2005), and the PM2.5 concentration was 1.75-2.70 times higher than the above standard (25 μg/m³). Particle size analysis indicated that the distribution of fine particulate matter in Wu Ye Temple ranged from 0 to 3.30 μm. In other sampling points, the fine particulate was mainly distributed in the range of 0-5.90 μm. The particulates in Wu Ye Temple were mainly characterized by spherical, rod-like, and irregular soot aggregates (PM10) and spherical particles of dust (PM2.5). Manjusri Temple and Yang Bai Lin Village predominantly exhibited irregular soil mineral particulate matter (PM10), and amorphous ultrafine soot particulate matter (PM2.5). [ABSTRACT FROM AUTHOR]

Based on measurement data from air quality monitoring stations, the spatio-temporal characteristics of the concentrations of particles with aerodynamic equivalent diameters smaller than 2.5 and 10 μm (PM2.5 and PM10, respectively) in the Beijing–Tianjin–Hebei (BTH) region from 2015 to 2018 were analysed at yearly, seasonal, monthly, daily and hourly scales. The results indicated that (1) from 2015 to 2018, the annual average values of PM2.5 and PM10 concentrations and the PM2.5/PM10 ratio in the study area decreased each year; (2) the particulate matter (PM) concentration in winter was significantly higher than that in summer, and the PM2.5/PM10 ratio was highest in winter and lowest in spring; (3) the PM2.5 and PM10 concentrations exhibited a pattern of double peaks and valleys throughout the day, reaching peak values at night and in the morning and valleys in the morning and afternoon; and (4) with the use of an improved sine function to simulate the change trend of the monthly mean PM concentration, the fitting R2 values for PM2.5 and PM10 in the whole study area were 0.74 and 0.58, respectively. Moreover, the high-value duration was shorter, the low-value duration was longer, and the concentration decrease rate was slower than the increase rate. [ABSTRACT FROM AUTHOR]

In large urban agglomerations, car traffic is one of the main sources of particulate matter. It consists of particulate matter directly generated in the process of incomplete liquid fuel burning in vehicle engine, secondary aerosols formed from exhaust gaseous pollutants (NOx, SO2) as well as products of tires, brake pads and pavement abrasion. Krakow is one of the cities in Europe with the highest concentrations of particulate matter. The article presents the results of combined elemental, chemical and isotopic analyses of particulate matter PM10 at two contrasting urban environments during winter and summer seasons. Daily PM10 samples were collected during the summer and winter seasons of 2018/2019 at two stations belonging to the network monitoring air quality in the city. Mean PM10 concentrations at traffic-dominated stations were equal to 35 ± 7 µg/m3 and 76 ± 28 µg/m3 in summer and winter, respectively, to be compared with 25.6 ± 5.7 µg/m3 and 51 ± 25 µg/m3 in summer and winter, respectively, recorded at the urban background station. The source attribution of analyzed PM10 samples was carried out using two modeling approaches: (i) The Positive Matrix Factorization (PMF) method for elemental and chemical composition (concentrations of elements, ions, as well as organic and elemental carbon in daily PM10 samples), and (ii) Isotope Mass Balance (IMB) for 13C and 14C carbon isotope composition of carbonaceous fraction of PM10. For PMF application, five sources of particulate matter were identified for each station: fossil fuel combustion, secondary inorganic aerosols, traffic exhaust, soil, and the fifth source which included road dust, industry, construction work. The IMB method allowed the partitioning of the total carbon reservoir of PM10 into carbon originating from coal combustion, from biogenic sources (natural emissions and biomass burning) and from traffic. Both apportionment methods were applied together for the first time in the Krakow agglomeration and they gave consistent results. [ABSTRACT FROM AUTHOR]

Road and industrial origin particulate matters (PM) are a significant source of potentially toxic elements (PTEs), with health risks to the surrounding residents. In Korea for 60 years, although industries, roads and automobiles have increased aggressively, there are still few PTEs data in PM in road-deposited sediment (RDS) of industrial complexes (ICs). Therefore, this study aimed to investigate the PTE composition of on-road PM10 from nine major ICs and its pollution degree in Korea and evaluate its human health risks. The geo-accumulation index (Igeo) and pollution load index (PLI) elucidated that on-road PM10 were severely polluted by Sb, Zn, Ag and Pb. A combination of principal component analysis (PCA) and chemical tracers was used to define the PTEs sources. The results showed that non-exhaust emission from vehicles' activity is the primary source of PTEs in on-road PM10, and industrial emissions are the secondary source. The riskiest pathway on carcinogenic and non-carcinogenic by on-road PM10 with PTEs was in-gestion. Traffic origin PTEs including Pb, As, Sb and Cd had a more significant impact on carcinogenic and non-carcinogenic health than those of industrial origins. These results could help mitigate public health risks arising from on-road PM10 and improve air quality in ICs. [ABSTRACT FROM AUTHOR]

Road dust (RD) resuspension is one of the main sources of particulate matter in cities with adverse impacts on air quality, health, and climate. Studies on the variability of the deposited PM10 fraction of RD (RD10) have been limited in Latin America, whereby our understanding of the central factors that control this pollutant remains incomplete. In this study, forty-one RD10 samples were collected in two Andean cities (Bogotá and Manizales) and analyzed for ions, minerals, and trace elements. RD10 levels varied between 1.8–45.7 mg/m2, with an average of 11.8 mg/m2, in Bogotá and between 0.8–26.7 mg/m2, with an average of 5.7 mg/m2, in Manizales. Minerals were the most abundant species in both cities, with a fraction significantly larger in Manizales (38%) than Bogotá (9%). The difference could be explained mainly by the complex topography and the composition of soil derived from volcanic ash in Manizales. The volcanic activity was also associated with SO4−2 and Cl−. Enrichment factors and principal component analysis were conducted to explore potential factors associated to sources of RD10. Elements such as Cu, Pb, Cr, Ni, V, Sb, and Mo were mainly associated with exhaust and non-exhaust traffic emissions. [ABSTRACT FROM AUTHOR]

Heatwaves are an extreme meteorological event in which affected populations may also be exposed to deteriorated air quality conditions due to the increase in air pollutant concentrations, such as PM10 (particulate matter < 10 µg/m3). In order to identify heatwaves (1973–2019) in the region of Faro (Algarve) during the hot season (April–September), the Excess Heat Factor (EHF) index was applied. The Mann–Kendall test revealed an upward trend in three heatwave metrics in Faro, and the trend of accumulated heat load (EHF load) was also positive as would be expected, but its signal was not statistically significant. An inventory of North African dust events (2006–2019) was made, and their simultaneous occurrence with heatwaves was assessed, pointing to only 20% of dust events of the Sahara occurring simultaneously with heatwave days. A cluster analysis was conducted on daily geopotential height fields at 850 hPa level over the 2006–2019 period, and four distinct patterns were identified as the most prominent synoptic circulations promoting both heatwave conditions and North African dust over the Algarve. [ABSTRACT FROM AUTHOR]

Low-cost air quality stations can provide useful data that can offer a complete picture of urban air quality dynamics, especially when integrated with daily measurements from reference air quality stations. However, the success of such deployment depends on the measurement accuracy and the capability of resolving spatial and temporal gradients within a spatial domain. In this work, an ensemble of three low-cost stations named "AirQino" was deployed to monitor particulate matter (PM) concentrations over three different sites in an area affected by poor air quality conditions. Data of PM2.5 and PM10 concentrations were collected for about two years following a protocol based on field calibration and validation with a reference station. Results indicated that: (i) AirQino station measurements were accurate and stable during co-location periods over time (R2 = 0.5–0.83 and RMSE = 6.4–11.2 μg m−3; valid data: 87.7–95.7%), resolving current spatial and temporal gradients; (ii) spatial variability of anthropogenic emissions was mainly due to extensive use of wood for household heating; (iii) the high temporal resolution made it possible to detect time occurrence and strength of PM10 concentration peaks; (iv) the number of episodes above the 1-h threshold of 90 μg m−3 and their persistence were higher under urban and industrial sites compared to the rural area. [ABSTRACT FROM AUTHOR]

Nature-based solutions can represent beneficial tools in the field of urban transformation for their contribution to important environmental services such as air quality improvement. To evaluate the impact on urban air pollution of a CityTree (CT), an innovative wall-type green infrastructure in passive (deposition) and active (filtration) modes of operation, a study was conducted in a real urban setting in Modena (Italy) during 2017 and 2018, combining experimental measurements with modelling system evaluations. In this work, relying on the computational resources of CRESCO (Computational Centre for Research on Complex Systems)/ENEAGRID High Performance Computing infrastructure, we used the air pollution microscale model PMSS (Parallel Micro-SWIFT-Micro SPRAY) to simulate air quality during the experimental campaigns. The spatial characteristics of the impact of the CT on local air pollutants concentrations, specifically nitrogen oxides (NOx) and particulate matter (PM10), were assessed. In particular, we used prescribed bulk deposition velocities provided by the experimental campaigns, which tested the CT both in passive (deposition) and in active (filtration) mode of operation. Our results showed that the PM10 and NOx concentration reductions reach from more than 0.1% up to about 0.8% within an area of 10 × 20 m2 around the infrastructure, when the green infrastructure operates in passive mode. In filtration mode the CT exhibited higher performances in the abatement of PM10 concentrations (between 1.5% and 15%), within approximately the same area. We conclude that CTs may find an application in air quality hotspots within specific urban settings (i.e., urban street canyons) where a very localized reduction of pollutants concentration during rush hours might be of interest to limit population exposure. The optimization of the spatial arrangement of CT modules to increment the "clean air zone" is a factor to be investigated in the ongoing development of the CT technology. [ABSTRACT FROM AUTHOR]

Particulate matter smaller than 10 μm (PM10) is an important air pollutant that adversely affects human health by increasing the risk of respiratory and cardiovascular diseases. Recent studies reported multiple extreme PM10 levels at high altitude Peruvian cities, which resulted from a combination of high emissions and limited atmospheric circulation at high altitude. However, the emission sources of the PM10 still remain unclear. In this study, we collected PM10 samples from four sites (one industrial site, one urban site, and two rural sites) at the city of Arequipa, Peru, during the period of February 2018 to December 2018. To identify the origins of PM10 at each site and the spatial distribution of PM10 emission sources, we analyzed major and trace element concentrations of the PM10. Of the observed daily PM10 concentrations at Arequipa during our sampling period, 91% exceeded the World Health Organization (WHO) 24-h mean PM10 guideline value, suggesting the elevated PM10 strongly affected the air quality at Arequipa. The concentrations of major elements, Na, K, Mg, Ca, Fe, and Al, were high and showed little variation, suggesting that mineral dust was a major component of the PM10 at all the sites. Some trace elements, such as Mn and Mo, originated from the mineral dust, while other trace elements, including Pb, Sr, Cu, Ba, Ni, As and V, were from additional anthropogenic sources. The industrial activities at Rio Seco, the industrial site, contributed to significant Pb, Cu, and possibly Sr emissions. At two rural sites, Tingo Grande and Yarabamba, strong Cu emissions were observed, which were likely associated with mining activities. Ni, V, and As were attributed to fossil fuel combustion emissions, which were strongest at the Avenida Independencia urban site. Elevated Ba and Cu concentrations were also observed at the urban site, which were likely caused by heavy traffic in the city and vehicle brake wear emissions. [ABSTRACT FROM AUTHOR]

Lima is considered one of the cities with the highest air pollution in Latin America. Institutions such as DIGESA, PROTRANSPORTE and SENAMHI are in charge of permanently monitoring air quality; therefore, the air quality visualization system must manage large amounts of data of different concentrations. In this study, a spatio-temporal visualization approach was developed for the exploration of data of the PM 10 concentration in Metropolitan Lima, where the spatial behavior, at different time scales, of hourly concentrations of PM 10 are analyzed using basic and specialized charts. The results show that the stations located to the east side of the metropolitan area had the highest concentrations, in contrast to the stations located in the center and north that reported better air quality. According to the temporal variation, the station with the highest average of biannual and annual PM 10 was the HCH station. The highest PM 10 concentrations were registered in 2018, during the summer, highlighting the month of March with daily averages that reached 435 μ g/m 3 . During the study period, the CRB was the station that recorded the lowest concentrations and the only one that met the Environmental Quality Standard for air quality. The proposed approach exposes a sequence of steps for the elaboration of charts with increasingly specific time periods according to their relevance, and a statistical analysis, such as the dynamic temporal correlation, that allows to obtain a detailed visualization of the spatio-temporal variations of PM 10 concentrations. Furthermore, it was concluded that the meteorological variables do not indicate a causal relationship with respect to PM 10 levels, but rather that the concentrations of particulate material are related to the urban characteristics of each district. [ABSTRACT FROM AUTHOR]

Long and short-term exposure to atmospheric particulate matter (PM) has detrimental effects on human health. The effective mechanisms leading to PM toxicity are still not fully understood, even if it is known that physical-chemical properties, strongly influenced by sources and atmospheric processes, are known to play an important role. In this work, PM10 samples were collected, at an urban background site in southern Italy, to determine cytotoxicity (using MTT test on A549 cells), genotoxicity (using the comet assay), and intracellular oxidative stress on A549 cells exposed for 24 h to aqueous extracts of PM10 samples. Organic carbon (OC) and elemental carbon (EC) content of PM10 and acellular determination of oxidative potential with DTT assay were performed to compare results of acellular and cellular biological assays. Cellular (OSGCV and MTTV) and acellular (OPDTTV) outcomes, normalized in volume, are well correlated (statistically significant results) with carbon content suggesting that combustion sources play an important role in determining cellular oxidative stress and cytotoxicity of PM10. Even if the number of data is limited, genotoxicity results are well correlated (Pearson r > 0.95) with OSGCV and MTTV, and a weaker, but statistically significant correlation was observed with OPDTTV. OSGCV is well correlated with the cell mortality observed with the MTTV test and a lower, but still statistically significant correlation is observed between MTTV and OPDDTV. A statistically significant correlation was found between OPDTTV and OSGCV results. When the outcomes of the cellular and acellular assay are compared normalized in mass (i.e., intrinsic values), the correlations become significantly weaker suggesting that the different sources acting on the site produces particulate matter with different toxicological potential influencing differently the biological tests studied. [ABSTRACT FROM AUTHOR]

Air pollution is an important issue that can have significant implications for human health. Consequently, air quality control is matter of great interest, and the ΕU has established strict legislation with respect to public health protection. A work package of the EMPIR project AEROMET focused on the investigation of traceable validated methods for chemical composition of airborne particulate matter (PM), including heavy metals. Incineration ash typically contains quantities of heavy and toxic metals in excess of the limits imposed for airborne PM, so it provides a candidate source for a Standard Reference Material (SRM). In this work, a method for loading incinerator ash (PM10 and PM2.5 fractions) on quartz filters with a good reproducibility and homogeneity was developed. An intercomparison exercise involving three separate laboratories was conducted for the elemental analysis of the prepared candidate reference material. The filters were treated by acid digestion and analyzed by Inductively Coupled Plasma–Mass Spectrometry (ICP-MS) according to the European standard EN 14902:2005. Eleven elements, including the regulated metals (As, Cd, Ni and Pb), were determined using different ICP-MS instruments and standardization methods. Data evaluation showed a good agreement between the results, with deviations below 10–15%. The development of a Standard Reference Material seems auspicious. [ABSTRACT FROM AUTHOR]

This study analyzes the relationship between various atmospheric fields and the observed PM10 concentrations in the Seoul metropolitan area, South Korea, during the winters of the 2001–2014 period to find suitable atmospheric indices for predicting high PM10 episodes in the region. The analysis shows that PM10 concentration in the metropolitan area is mainly affected by the intensity of horizontal ventilation and the 500 hPa high-pressure system over the Korean peninsula. The modified Korea particulate matter index (MKPI) is proposed based on a 10 m wind speed for surface ventilation and 500 hPa zonal wind for the intensity of a 500 hPa high-pressure system over the Korean peninsula. It is found that a positive MKPI value is closely correlated with the occurrence of high PM10 concentration episodes, and hence, can be used as a predictor for high PM10 episodes in the area. A future projection of the MKPI using two three-member general circulation model (GCM) ensembles with four shared socioeconomic pathway (SSP) scenarios in Coupled Model Intercomparison Project Phase 6 (CMIP6) shows that positive MKPI events and high PM10 episodes are expected to increase by 5.4−16.4% depending on the SSP scenarios in the 2081−2100 period from the present-day period of 1995−2014. [ABSTRACT FROM AUTHOR]

The dispersion of particulate matter emitted by road transport to the vicinity of roads is predominantly influenced by the character of the air velocity field. The air flow depends on factors such as the speed and direction of the blowing wind, the movement of cars, and the geometries of the buildings around a road. Numerical modeling based on the control volume method was used in this study to describe the relevant processes closely. Detailed air velocity fields were identified in the vicinity of a straight road surrounded by various patterns of built-up urban land. The evaluation of the results was generalized to exponential expressions, affecting the decrease of the mass concentration of fine particles with the increasing distance from the road. The obtained characteristics of the mass concentration fields express the impact of the building geometries and configurations on the dispersion of particulate matter into the environment. These characteristics are presented for two wind speeds, namely, 2 m·s−1 and 4 m·s−1. Furthermore, the characteristics are introduced in relation to three wind directions: perpendicularly, obliquely, and in parallel to the road. The results of the numerical simulations are compared with those obtained via the in-situ measurements, for verification of the validity of the linear emission source calculation. [ABSTRACT FROM AUTHOR]

We examined windblown dust within the Imperial Valley (CA) during strong springtime west-southwesterly (WSW) wind events. Analysis of routine agency meteorological and ambient particulate matter (PM) measurements identified 165 high WSW wind events between March and June 2013 to 2019. The PM concentrations over these days are higher at northern valley monitoring sites, with daily PM mass concentration of particles less than 10 micrometers aerodynamic diameter (PM10) at these sites commonly greater than 100 μg/m3 and reaching around 400 μg/m3, and daily PM mass concentration of particles less than 2.5 micrometers aerodynamic diameter (PM2.5) commonly greater than 20 μg/m3 and reaching around 60 μg/m3. A detailed analysis utilizing 1 km resolution multi-angle implementation of atmospheric correction (MAIAC) aerosol optical depth (AOD), Identifying Violations Affecting Neighborhoods (IVAN) low-cost PM2.5 measurements and 500 m resolution sediment supply fields alongside routine ground PM observations identified an area of high AOD/PM during WSW events spanning the northwestern valley encompassing the Brawley/Westmorland through the Niland area. This area shows up most clearly once the average PM10 at northern valley routine sites during WSW events exceeds 100 μg/m3. The area is consistent with high soil sediment supply in the northwestern valley and upwind desert, suggesting local sources are primarily responsible. On the basis of this study, MAIAC AOD appears able to identify localized high PM areas during windblown dust events provided the PM levels are high enough. The use of the IVAN data in this study illustrates how a citizen science effort to collect more spatially refined air quality concentration data can help pinpoint episodic pollution patterns and possible sources important for PM exposure and adverse health effects. [ABSTRACT FROM AUTHOR]

Residential dust is recognized as a major source of environmental contaminants, including polycyclic aromatic hydrocarbons (PAHs) and plasticizers, such as phthalic acid esters (PAEs). A sampling campaign was carried out to characterize the dust fraction of particulate matter with an aerodynamic diameter smaller than 10 µm (PM10), using an in situ resuspension chamber in three rooms (kitchen, living room, and bedroom) of four Spanish houses. Two samples per room were collected with, at least, a one-week interval. The PM10 samples were analyzed for their carbonaceous content by a thermo-optical technique and, after solvent extraction, for 20 PAHs, 8 PAEs and one non-phthalate plasticizer (DEHA) by gas chromatography-mass spectrometry. In general, higher dust loads were observed for parquet flooring as compared with tile. The highest dust loads were obtained for rugs. Total carbon accounted for 9.3 to 51 wt% of the PM10 mass. Plasticizer mass fractions varied from 5 µg g−1 to 17 mg g−1 PM10, whereas lower contributions were registered for PAHs (0.98 to 116 µg g−1). The plasticizer and PAH daily intakes for children and adults via dust ingestion were estimated to be three to four orders of magnitude higher than those via inhalation and dermal contact. The thoracic fraction of household dust was estimated to contribute to an excess of 7.2 to 14 per million people new cancer cases, which exceeds the acceptable risk of one per million. [ABSTRACT FROM AUTHOR]

The evidence linking ozone and particulate matter with adverse health impacts is increasing. The goal of this study was to assess the impact of air pollution on the mortality rate from respiratory disease in Seoul, Korea, between 2008 and 2017. The analysis was conducted using a decision tree model in two ways: using 24-h average concentrations and using 1-h maximum values to compare any health impacts from the different times of exposure to pollution. Results show that in spring an elevated level of ozone is one of the most important factors, but in summer temperature has a greater impact than air pollution. Nitrogen dioxide is one of the most important factors in fall, while high levels of particles less than 2.5 μm (PM2.5) and 10 μm in size (PM10) and cooler temperatures are key factors in winter. We checked the accuracy of our results through a 10-fold cross validation method. Error rates using 24-h average and 1-h maximum concentrations were in the ranges of 24.9–42% and 27.6–42%, respectively, indicating that 24-h average concentrations are slightly more directly related with mortality rate. These results could be useful for policy makers in determining the temporal scale of predicted pollutant concentrations for an air quality warning system to help minimize the adverse impacts of air pollution. [ABSTRACT FROM AUTHOR]

With Changchun's economic development, atmospheric particulate pollution has become a significant challenge in Changchun. The spatiotemporal patterns of particulate matter emissions are an inherent characteristic for particulate matter emissions. By using hourly PM (particulate matter) mass concentration measured at 10 atmospheric automatic monitoring stations and meteorological parameters, the spatiotemporal distribution characteristics of particulate matter (PM10 and PM2.5) and its relationship with meteorological parameters of Changchun have been analyzed. Pollution pathways and source distribution were investigated using HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory) model and cluster analysis. Results indicated that the quarterly average PM2.5 and PM10 mass concentrations in Changchun were higher in the first quarter and the fourth quarter. PM concentrations observed in all seasons generally exhibited two peaks, at 07:00–10:00 and 21:00–23:00, with the exception of PM10 in spring. PM pollution was concentrated mainly in the central, northern, and western areas of Changchun in most seasons, mainly due to anthropogenic activities and soil dust transported outside the region. PM concentrations were negatively correlated with relative humidity and temperature. PM2.5 concentrations were negatively correlated with wind speed, while PM10 concentrations were positively correlated with wind speed. The results of backward trajectory clustered showed that the northwest airflow had the greatest impact on PM of Changchun, except summer. [ABSTRACT FROM AUTHOR]

Vehicle-related particulate matter (PM) emissions may arise from both exhaust and non-exhaust mechanisms, such as brake wear, tire wear, and road pavement abrasion, each of which may be emitted directly and indirectly through resuspension of settled road dust. Several researchers have indicated that the proportion of PM2.5 attributable to vehicle traffic will increasingly come from non-exhaust sources. Currently, very little empirical data is available to characterize tire and road wear particles (TRWP) in the PM2.5 fraction. As such, this study was undertaken to quantify TRWP in PM2.5 at roadside locations in urban centers including London, Tokyo and Los Angeles, where vehicle traffic is an important contributor to ambient air PM. The samples were analyzed using validated chemical markers for tire tread polymer based on a pyrolysis technique. Results indicated that TRWP concentrations in the PM2.5 fraction were low, with averages ranging from < 0.004 to 0.10 µg/m3, representing an average contribution to total PM2.5 of 0.27%. The TRWP levels in PM2.5 were significantly different between the three cities, with significant differences between London and Los Angeles and Tokyo and Los Angeles. There was no significant correlation between TRWP in PM2.5 and traffic count. This study provides an initial dataset to understand potential human exposure to airborne TRWP and the potential contribution of this non-exhaust emission source to total PM2.5. [ABSTRACT FROM AUTHOR]

Aerosol measurements were collected at fifteen homes over the course of one year in Colorado (USA) to understand the temporal variability of indoor air particulate matter and bacterial concentrations and their relationship with home characteristics, inhabitant activities, and outdoor air particulate matter (PM). Indoor and outdoor PM2.5 concentrations averaged (±st. dev.) 8.1 ± 8.1 μg/m3 and 6.8 ± 4.5 μg/m3, respectively. Indoor PM2.5 was statistically significantly higher during summer compared to spring and winter; outdoor PM2.5 was significantly higher for summer compared to spring and fall. The PM2.5 I/O ratio was 1.6 ± 2.4 averaged across all homes and seasons and was not statistically significantly different across the seasons. Average indoor PM10 was 15.4 ± 18.3 μg/m3 and was significantly higher during summer compared to all other seasons. Total suspended particulate bacterial biomass, as determined by qPCR, revealed very little seasonal differences across and within the homes. The qPCR I/O ratio was statistically different across seasons, with the highest I/O ratio in the spring and lowest in the summer. Using one-minute indoor PM10 data and activity logs, it was observed that elevated particulate concentrations commonly occurred when inhabitants were cooking and during periods with elevated outdoor concentrations. [ABSTRACT FROM AUTHOR]