Transport Of PM2 Research Articles

Modeling the transport of PM10, PM2.5, and O3 from South Asia to the Tibetan Plateau

South Asian air pollutants exert substantial effect on the climate and environment change over the Tibetan Plateau (TP). This paper investigates the trans-boundary transport of PM10, PM2.5, and O3 from South Asia to the TP via WRF-Chem sensitive analysis. It is found that PM10, PM2.5, and O3 over South Asia are mainly sourced from anthropogenic sources. South Asian emissions contribute up to 54% of PM10 (PM2.5) in the TP in the pre-monsoon season. For O3, the highest contribution of 18.13% is in the monsoon season, while the lowest contribution of 8.67% is in the winter season. To evaluate the respective contributions of anthropogenic and biomass burning emissions in South Asia to PM10, PM2.5, and O3 in the TP, anthropogenic and biomass burning emissions in South Asia are considered separately. The results show that the largest percentage contribution of PM10 (PM2.5) from South Asian anthropogenic emissions to PM10 (PM2.5) in the TP with value of 35.86% (37.77%) occurs in winter, while the lowest percentage contribution of 16.52% (16.77%) appears in the monsoon season. For O3, the largest contribution of 17.74% from South Asian anthropogenic emissions appears in the monsoon season, whereas the lowest contribution of 8.59% occurs in winter. Compared to the anthropogenic emissions, the biomass burning emissions in South Asia have a relative less contribution to PM10, PM2.5, and O3 in the TP. The largest contribution of PM10 (PM2.5) from South Asian biomass burning emissions to PM10 (PM2.5) in the TP is 20.04% (18.37%) in the pre-monsoon season. Conversely, the lowest contribution of 0.58% (0.53) appears in the monsoon season. O3 from South Asian biomass burning emissions contributes <1% to O3 in the TP in each season, implying that the biomass burning emissions in South Asia have little effect on O3 in the TP. This study is of great significance to the ecological environment protection for the TP.

Impact assessment of spatial-temporal distribution of riverine dust on air quality using remote sensing data and numerical modeling.

Soil erosion is a severe problem in Taiwan due to the steep terrain, fragile geology, and extreme climatic events resulting from global warming. Due to the rapidly changing hydrological conditions affecting the locations and the amount of transported sand and fine particles, timely impact evaluation and riverine dust control are difficult, particularly when resources are limited. To comprehend the impact of desertification in estuarine areas on the variation of air pollutant concentrations, this study utilized remote sensing technology coupled with an air pollutant dispersion model to determine the unit contribution of potential pollution sources and quantify the effect of riverine dust on air quality. The images of the downstream area of the Beinan River basin captured by Formosat-2 in May 2006 were used to analyze land use and land cover (LULC) composition. Subsequently, the diffusion model ISCST-3 based on Gaussian distribution was utilized to simulate the transport of PM across the study area. Finally, a mixed-integer programming model was developed to optimize resource allocation for dust control. Results reveal that sand deposition in specific river sections significantly influences regional air quality, owing to the unique local topography and wind field conditions. The present optimal plan model for regional air quality control further showed that after implementing engineering measures including water cover, revegetation, armouring cover, and revegetation, total PM concentrations would be reduced by 51%. The contribution equivalent calculation, using the air pollution diffusion model, was effectively integrated into the optimization model to formulate a plan for reducing riverine dust with limited resources based on air quality requirements.

Dynamic characteristics of wind and PM10 over desert-oasis transition zone during dust events

Dust storm events generate aeolian dust as one of the main aerosols in the atmosphere, with significant impacts on air quality and human health. Further study is needed on the dust emission processes in source regions and the impacts of underlying surfaces with forested windbreaks on the transport of wind flow and PM10 to develop more accurate dust concentration forecasts. Synchronized monitoring of wind velocity and the PM10 concentration was performed along the dust transport pathway crossing the desert and oasis in Minqin County, Gansu Province, China. Results indicated that the PM10 concentration and flux responded quickly to wind velocity in the desert with both having obvious power function relationships. The addition of supra-regional transport of PM10 particles led to an abnormal increase in PM10 concentration and flux. Between desert and oasis, a positive linear function relationship of PM10 concentrations and quadratic function relationship of PM10 flux exist. The dynamic transfer process of PM10 in the oasis roughly depends on the condition of PM10 in the desert area. Forested windbreaks significantly reduced the mean wind velocity and PM10 flux by 65.02% and 67.63%, respectively. However, forests had a weak influence on the mean PM10 concentration. The effects of forested windbreaks on the PM10 concentration are related to the windward wind velocity. With increasing velocity, difference of PM10 concentration from desert to oasis turned from negative to positive, while the positive effects of the forested windbreak system can be enhanced by an increase in the windward wind velocity.

Quantifying the seasonal variations in and regional transport of PM2.5 in the Yangtze River Delta region, China: characteristics, sources, and health risks

Abstract. Given the increasing complexity of the chemical composition of PM2.5, identifying and quantitatively assessing the contributions of pollution sources has played an important role in formulating policies to control particle pollution. This study provides a comprehensive assessment between PM2.5 chemical characteristics, sources, and health risks based on sampling data conducted over 1 year (March 2018 to February 2019) in Nanjing. Results show that PM2.5 exhibits a distinct variation across different seasons, which is primarily driven by emissions, meteorological conditions, and the chemical conversion of gaseous pollutants. First, the chemical mass reconstruction shows that secondary inorganic aerosols (62.5 %) and carbonaceous aerosols (21.3 %) contributed most to the PM2.5 mass. The increasing oxidation rates of SO2 and NO2 from summer to winter indicate that the secondary transformation of gaseous pollutants is strongly positively correlated with relative humidity. Second, the positive matrix factorization (PMF) method shows that identified PM2.5 sources include secondary inorganic aerosol source (SIS, 42.5 %), coal combustion (CC, 22.4 %), industry source (IS, 17.3 %), vehicle emission (VE, 10.7 %), fugitive dust (FD, 5.8 %), and other sources (1.3 %). The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model and the concentration-weighted trajectory (CWT) analysis are used to further explore different spatial distributions and regional transport of sources. The concentrations (10–11 µg m−3) of SIS and CC distribute in Nanjing and central China in winter. The concentrations (8–10 µg m−3) of IS and VE are potentially located north of Jiangsu, Anhui, and Jiangxi. Finally, the health risk assessment indicates that the carcinogenic and non-carcinogenic risks of toxic elements (Cr, As, Ni, Mn, V, and Pb) mainly come from IS, VE, and CC, which are within the tolerance or acceptable level. Although the main source of pollution in Nanjing is SIS at present, we should pay more attention to the health burden of vehicle emissions, coal combustion, and industrial processes.

Spatial prediction of PM[formula omitted] concentration using hyper-parameter optimization XGBoost model in China

High-fine particulate matter (PM2.5) pollution has become the main object of damaging the atmospheric environment and endangering human health. Accurate prediction of the spatial variability of PM2.5 concentrations using high-performance models is crucial for the prevention and control of atmospheric pollution. In this paper, in order to avoid the uncertainty caused by artificially setting the parameters of the prediction model, a new hyper-parameter optimization extreme gradient boosting (HPO-XGBoost) model for spatial prediction of PM2.5 concentration was proposed. We used aerosol optical depth (AOD) data of Himawari-8 satellite combined with the HPO-XGBoost model to predict and mapping the spatial variability of PM2.5 concentrations during the COVID-19 lockdown in China. The results showed that the maximum concentration of PM2.5 exhibited a downward trend and a significant seasonal fluctuation from 2015 to 2020. Compared with grid search (GS) and random grid search (RGS) optimization algorithms, the tree-structured Parzen estimator-XGBoost (TPE-XGBoost) approach has the highest prediction accuracy (R2) of 89.37% (January), 85.58% (February), 80.02% (March), and 83.68% (April) for PM2.5 concentrations in 2020, respectively. Spatial mapping of the monthly average PM2.5 concentration from January to April using the TPE-XGBoost model showed that the regions with higher PM2.5 concentrations are concentrated in northern China, eastern China and northeastern China, where PM2.5 concentrations exceed 150 μg m−3 in January. Furthermore, the spatial correlation analysis showed that factors with the highest driving effect of PM2.5 concentrations during the COVID-19 lockdown were factory (FAC) and traffic (TRA), and the strongest contribution of the double-factor synergy (q > 0.8) for all four months included factory-residence (FAC-RES) and factory-population (FAC-POP). The contribution source of PM2.5 transport showed a long-distance channel in Taiyuan, Xi’an and Shijiazhuang, while the cluster-like distribution and mixed distribution of contribution sources were embodied in Zhengzhou, Changchun and Harbin based on concentration-weighted trajectory (CWT) analysis. The above results showed that the TPE-XGBoost has strong nonlinear explanation and effective feasibility for spatial prediction of PM2.5 concentrations, and the transport of PM2.5 was dynamic effect which should be considered into account when developing prevention and control measures of atmospheric pollution in epidemic period.

Stable Isotopes Unravel the Sources and Transport of PM2.5 in the Yangtze River Delta, China

Stable Isotopes Unravel the Sources and Transport of PM2.5 in the Yangtze River Delta, China

Impacts of Complex Terrain Features on Local Wind Field and PM2.5 Concentration

Complex topography has nonnegligible effects on local meteorological conditions as well as the transportation of atmospheric pollutants, which deserves more extensive study. In this study, the impacts of complex terrain features (mountains and river valleys) on local wind field and PM2.5 concentration in a typically developed mega city along the Yangtze River were studied numerically using the WRFCALMET-CALPUFF system. The impacts of different model grid and terrain horizontal resolutions were firstly investigated against observations. Then, the impacts of terrain features, specifically the impacts of Mt. LS and the Yangtze River, on wind field and PM2.5 transportation were analyzed by “removing” Mt. LS and the Yangtze River from the meteorological diagnostic model and simulating the dispersion of PM2.5 from three virtual point sources in the chemical model. Results showed that: (i) higher terrain elevation and model horizontal resolutions, and updated land cover types, can effectively improve the prediction of wind direction where terrain features are complex; (ii) Mt. LS mainly acts as a barrier, and ridge wind is weakened after “removing” Mt. LS; (iii) after “removing” the Yangtze River, the transport of PM2.5 along the Yangtze River is weakened; (iv) the simulation of PM2.5 from virtual point sources showed that Mt. LS could have an effect of up to 55% on the PM2.5 concentration in Nanjing. This study showed that the local complex topographies have an obvious effect on the local wind field and the concentration of PM2.5. Therefore, it is important to consider the influence of local topographies and land cover types when predicting local wind field and air quality.

Pollutant concentrations and exposure variability in four urban microenvironments of London

We compared various pollutant concentrations (PM1, PM2.5, PM10, PNC, BC) at four different urban microenvironments (MEs) in London (Indoor, IN; Traffic Intersection, TI; Park, PK; and Street Canyon, SC). The physico-chemical characteristics of particles were analysed, and the respiratory deposition doses (RDD) were estimated. Field measurements were conducted over a period of 121 days. The mean PM2.5 (PNC) concentrations were found to be 9.47 ± 7.05 (16366 ± 11815), 8.09 ± 4.57 (10951 ± 6445), 5.11 ± 2.96 (7717 ± 4576), 3.88 ± 3.06 (5672 ± 2934) μg m−3 (# cm−3) at TI, SC, PK and IN, respectively. PM2.5, PM10 and PNC exhibited a trend of TI > SC > PK > IN; higher concentrations for PM1 and BC were observed at IN than PK due to the emissions from printers, producing a trend of TI > SC > IN > PK. We observed 12%–30% higher fine PM concentrations at TI and SC sites during morning peak (07:00–09:30) than the evening peak hours (16:00–19:00); while IN showed a smaller variation in fine PM concentrations compared with outdoor TI, PK and SC sites owing to their prevalence in the IN for a longer time. Fine and ultrafine PM containing potentially toxic trace transition metals including Fe, Ti, Cr, Mn, Al and Mg were detected by high resolution electron microscopy at all sites. There was a similar relative abundance of different elements at the TI, IN and PK sites, which suggests a transport of PM between MEs. RDD for PM1 was highest (2.45 ± 2.27 μg h−1) at TI for females during running; PM2.5 and PM10 were highest at SC (11.23 ± 6.34 and 37.17 ± 20.82 μg h−1, respectively). The results show that the RDD variation between MEs does not follow the PM concentration trend. RDD at PK was found to be 39%–53% lower than TI and SC during running for all the PM fractions. Overall, the study findings show the air quality variation at different MEs and reveals the exposure inequalities around the city, which enable the management of personal exposure by selecting appropriate MEs for different activities.

Loss of surface transport is a main cellular pathomechanism of CRB2 variants causing podocytopathies.

Crumbs2 (CRB2) is a central component of the renal filtration barrier and part of the slit diaphragm, a unique cell contact formed by glomerular podocytes. Some CRB2 variants cause recessive inherited forms of steroid-resistant nephrotic syndrome. However, the disease-causing potential of numerous CRB2 variants remains unknown. Here, we report the establishment of a live-cell imaging-based assay, allowing a quantitative evaluation of the pathogenic potential of so far non-categorized CRB2 variants. Based on in silico data analysis and protein prediction software, putative disease-associated CRB2 missense variants were selected, expressed as CRB2-GFP fusion proteins, and analyzed in reporter cell lines with BFP-labeled plasma membrane. We found that in comparison with PM-localized WT, disease-associated CRB2 variants remained predominantly at the ER. Accumulation at the ER was also present for several non-characterized CRB2 variants and variants in which putative disulfide bridge-forming cysteines were replaced. Strikingly, WT CRB2 retained inside the ER in cells lacking protein disulfide isomerase A3, indicating that posttranslational modification, especially the formation of disulfide bridges, is a crucial step for the CRB2 PM transport.

Modeling study on the roles of the deposition and transport of PM2.5 in air quality changes over central-eastern China

The role of PM2.5 (particles with aerodynamic diameters ≤ 2.5 µm) deposition in air quality changes over China remains unclear. By using the three-year (2013, 2015, and 2017) simulation results of the WRF/CUACE v1.0 model from a previous work (Zhang et al., 2021), a non-linear relationship between the deposition of PM2.5 and anthropogenic emissions over central-eastern China in cold seasons as well as in different life stages of haze events was unraveled. PM2.5 deposition is spatially distributed differently from PM2.5 concentrations and anthropogenic emissions over China. The North China Plain (NCP) is typically characterized by higher anthropogenic emissions compared to southern China, such as the middle-low reaches of Yangtze River (MLYR), which includes parts of the Yangtze River Delta and the Midwest. However, PM2.5 deposition in the NCP is significantly lower than that in the MLYR region, suggesting that in addition to meteorology and emissions, lower deposition is another important factor in the increase in haze levels. Regional transport of pollution in central-eastern China acts as a moderator of pollution levels in different regions, for example by bringing pollution from the NCP to the MLYR region in cold seasons. It was found that in typical haze events the deposition flux of PM2.5 during the removal stages is substantially higher than that in accumulation stages, with most of the PM2.5 being transported southward and deposited to the MLYR and Sichuan Basin region, corresponding to a latitude range of about 24°N-31°N.

Source identification with high-temporal resolution data from low-cost sensors using bivariate polar plots in urban areas of Ghana

The emergence of low-cost sensors for atmospheric observations presents a new opportunity for identifying atmospheric emission sources based on high-resolution data reporting. Low-cost sensors have been widely assessed for use in source monitoring and identification of hotspots of key atmospheric species in advanced countries (e.g., for CO, NOx, CO2, SO2, O3, VOCs and PM (PM10, PM2.5 including emerging PM1). In contrast, research in recent years has focused on their utility for real-time monitoring, understanding precision and associated calibration requirements in technologically lagging environments. This leads to limited evidence on the utility of high-resolution data from low-cost sensor networks for air pollution source identification in Ghana and more widely across the African continent. In this paper, we demonstrate the potential of low-cost sensors for emission source apportionment in urban areas of Ghana when used with analytical tools such as sectoral and cluster analysis. With a 14-week dataset from a low-cost sensor deployment study at Cape Coast in the Central Region of Ghana, we aimed to identify sources of particulate matter (PM2.5 and PM10). PM pollution was local (associated with increased PM at wind speeds of ≤2 m s−1). High levels of PM during this study were associated with transport from the NNE. For coarse PM, hourly levels as high as 125 μg m−3 were observed at higher wind speeds (7-8 m s−1) indicating the importance of meteorology in the transport of PM. This study suggests that low-cost sensors could be deployed to (1) augment any existing sparsely distributed air quality monitoring and (2) undertake air quality monitoring for source apportionment studies in areas with no existing air quality observational capability (with appropriate calibration and operation in both cases). The urban landscape monitored in this study is typical of both Ghana and wider areas across Sub-Saharan Africa demonstrating the reproducibility of this study.

Haze Pollution in the Unstable Atmospheric Boundary Layer Over the West Bank of Taiwan Strait Induced by Regional Transport of PM2.5

AbstractThis study investigated the regional transport of particulate matter (PM2.5) leading to air pollution in Fuzhou, in the west bank of the Taiwan Strait (WBTS), which has a relatively good air quality with a lower aerosol optical depth than that of East China. The continental polluted aerosol zone over the coast of East China was identified as an aerosol transport belt, and the daily aerosol dynamics observed by MODIS remote sensing indicated the southward transport of fine particulate matter to the WBTS along the coast. The external air pollutants from regional transport contributed 84% of the PM2.5 detected in Fuzhou, while only 16% due to local emissions of air pollutants. The northerly winds of the cold front drove the southward transport of polluted air masses along the coast of the northwest Pacific from the Yangtze River Delta (YRD) to the WBTS. The vertical mixing of air pollutants from the upper boundary layer to the surface layer could be conducive to regional‐transport‐induced haze pollution in this coastal area of the WBTS. Fuzhou is considered a receptor region of PM2.5 transport in Eastern China, and the source region is mainly from the YRD. The results of this study have significant implications on determining the source of pollution and controlling local air quality for good air quality regions. This study also shed some light on using multi‐satellites to fill the surface observation gaps in coast or nearshore areas, and to confirm the characteristics and passways of aerosol transport.

Source apportionment of air pollution in European urban areas: Lessons from the ClairCity project

Air pollution has become a major threat to human health in the last decades, with an increase of acute air pollution episodes in many cities worldwide. Source apportionment modelling provides valuable information on the contribution from different emission source sectors and source regions to distinct air pollutants concentrations. In this study, the CAMx model, with its PSAT tool, was applied to quantify the contribution of multiple source areas, categories and pollutant types to ambient air pollution, namely to PM and NO2 concentrations, over six European urban areas: Bristol (United Kingdom), Amsterdam (The Netherlands), Ljubljana (Slovenia), Liguria Region (Italy), Sosnowiec (Poland) and Aveiro Region (Portugal). Results indicate overall higher annual NO2 and PM concentrations located in the urban centres of the case studies. A comparison between the different areas showed that Liguria is the region with highest NO2 annual mean concentrations, while Ljubljana, Liguria Region and Sosnowiec are the case studies with the highest PM annual mean concentrations. The annual average contributions denote a major influence from road transport to NO2 concentrations, with up to 50%, except in Aveiro region, where road transport presents a lower contribution to NO2 concentrations, and the greatest contributor is the industrial combustion and processes sector with 45%. These results indicate a negligible contribution of the transboundary transport to NO2 concentrations, highlighting the relevance of local sources, while for PM concentrations the transboundary transport is the major contributor. The results highlight the relevance of long-range transport of PM across Europe. The transboundary transport reduces its importance during winter, when residential and commercial combustion increases its contribution. In the case of the Aveiro region, the industrial combustion and processes sector also plays an important contribution to PM concentrations.

Impact of Sea Breeze on the Transport of Ship Emissions: A Comprehensive Study in the Bohai Rim Region, China

Air pollutants from ship exhaust have a negative impact on air quality in coastal areas, which can be greatly exacerbated by sea breeze circulation. However, our understanding of this issue is still limited, especially in coastal areas with a complex topography and winding coastlines, such as the Bohai Rim region in China. In order to fill this knowledge gap, the Weather Research and Forecast model coupled with the chemistry (WRF/Chem) modeling system was employed to investigate the influence of sea breeze circulation on the transport of PM2.5 emitted by ships from April to September in 2014. The major findings are as follows: (1) The concentration of PM2.5 due to ship emissions was 2.94 μg/m3 on days with a sea breeze and 2.4 times higher than on days without a sea breeze in coastal cities in the region. (2) The difference in the contribution of ship emissions during days with a sea breeze and days without a sea breeze decreases with increasing distance from the coastline but remains non-negligible up to 50 km inland. (3) The shape of the coastline, the topographic height of the land area, and the latitude have a significant impact on sea breeze circulation and thus on the transport of ship emissions. (4) The differences in the contribution of ship emissions under days with a sea breeze versus days without a sea breeze were more evident than those under onshore versus alongshore and offshore winds, indicating that sea breeze circulation can cause cyclic accumulation of pollutants and thus reinforce the impact of ship emissions on coastal air quality more than by onshore winds. It should be emphasized that during the switching from sea breeze to a non-sea breeze, the pollutants that have been transported to the land area by sea breeze have not yet been carried back to sea, resulting in the ship contribution value still not significantly reduced even if the wind is a non-sea breeze at that moment. In addition, other factors e.g., emissions, precipitation, and chemistry can also play an important role in the observed trends in this study.

Regional Transport of PM2.5 and O3 Based on Complex Network Method and Chemical Transport Model in the Yangtze River Delta, China

AbstractGround‐level ozone (O3) and atmospheric fine particulate matter (PM2.5) pollution are the major challenges for continually improving air quality in the Yangtze River Delta (YRD) region of China. Understanding regional transport patterns of PM2.5 and O3 pollution is essential for the development of regional cooperative prevention strategies. This study shows the annual concentration of PM2.5 in the YRD decreased by 18.5% from 2015 to 2018, while the mean values of the daily maximum 8‐hr average (MDA8) O3 concentration from March to October increased by 16.3%. A complex network method is utilized to investigate the regional transport of PM2.5 and O3 in different grid cells (nodes). The source apportionment method within the chemistry transport model is applied to verify the reliability of the complex network method. Interregional and intraregional transport play an important role in both PM2.5 and O3 over the YRD. The northern part of the YRD contributes much more than other areas, while the central part of the YRD, especially the southern part of Jiangsu, is the largest contributor of O3 in the YRD in the summer, accounting for about 70%. Intraregional transport plays more of a major role in increasing PM2.5 pollution than O3 pollution. This study not only verifies the transport patterns of heavy pollution through the complex network method and traditional source apportionment technology, it also reveals that both methods provide great potential in understanding transport patterns and air pollution relationships, which are the solid foundation for emission mitigation in the YRD region.

Transboundary Air Pollution Transport of PM10 and Benzo[a]pyrene in the Czech–Polish Border Region

The article is occupied with the evaluation of the transboundary transport of pollutants in the Czech–Polish border region (between the Moravian-Silesian region and the Silesian Voivodeship) in Central Europe. It focuses on the evaluation of concentrations of benzo[a]pyrene (BaP) and suspended particles of PM10 depending on meteorological conditions, especially wind direction. The whole area of interest is heavily affected with air pollution of BaP and PM10. Limits of BaP and PM10 are still exceeded. Annual concentrations of benzo[a]pyrene are even several times higher than the value of its annual limit. The elaboration follows the results of the Czech–Polish project “Air Silesia”, which dealt with air pollution and the transboundary transport of pollutants in this area and took place in 2010 to 2013. Within this project, a higher transport of pollutants from Poland to the Czech Republic was established. The evaluation of the dependences of PM10 concentrations is based on hourly and daily data of PM10 and hourly data of meteorological quantities. To assess the dependences of daily BaP and PM10 concentrations, a methodology for evaluating daily types of wind direction was implemented into the processing. The results confirm that the problem of above-limit concentrations of BaP and PM10 in the Moravian-Silesian Region in the Czech Republic and the Silesian Voivodeship in Poland remains. The article confirms there is a higher transport of PM10 concentrations from Poland to the Czech Republic in the area of interest. Higher transport in the same direction is also predicted for daily concentrations of benzo[a]pyrene, although this cannot be clearly confirmed due to the lack of more detailed and identifiable data.

A National-Scale 1-km Resolution PM2.5 Estimation Model over Japan Using MAIAC AOD and a Two-Stage Random Forest Model

Satellite-based models for estimating concentrations of particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5) have seldom been developed in islands with complex topography over the monsoon area, where the transport of PM2.5 is influenced by both the synoptic-scale winds and local-scale circulations compared with the continental regions. We validated Multi-Angle Implementation of Atmospheric Correction (MAIAC) aerosol optical depth (AOD) with ground observations in Japan and developed a 1-km-resolution national-scale model between 2011 and 2016 to estimate daily PM2.5 concentrations. A two-stage random forest model integrating MAIAC AOD with meteorological variables and land use data was applied to develop the model. The first-stage random forest model was used to impute the missing AOD values. The second-stage random forest model was then utilised to estimate ground PM2.5 concentrations. Ten-fold cross-validation was performed to evaluate the model performance. There was good consistency between MAIAC AOD and ground truth in Japan (correlation coefficient = 0.82 and 74.62% of data falling within the expected error). For model training, the model showed a training coefficient of determination (R2) of 0.98 and a root mean square error (RMSE) of 1.22 μg/m3. For the 10-fold cross-validation, the cross-validation R2 and RMSE of the model were 0.86 and 3.02 μg/m3, respectively. A subsite validation was used to validate the model at the grids overlapping with the AERONET sites, and the model performance was excellent at these sites with a validation R2 (RMSE) of 0.94 (1.78 μg/m3). Additionally, the model performance increased as increased AOD coverage. The top-ten important predictors for estimating ground PM2.5 concentrations were day of the year, temperature, AOD, relative humidity, 10-m-height zonal wind, 10-m-height meridional wind, boundary layer height, precipitation, surface pressure, and population density. MAIAC AOD showed high retrieval accuracy in Japan. The performance of the satellite-based model was excellent, which showed that PM2.5 estimates derived from the model were reliable and accurate. These estimates can be used to assess both the short-term and long-term effects of PM2.5 on health outcomes in epidemiological studies.

Distribution and transport characteristics of fine particulate matter in beijing with mobile lidar measurements from 2015 to 2018

Accurately quantifying the concentration and transport flux of atmospheric fine particulate matter (PM2.5) is vital when attempting to thoroughly identify the pollution formation mechanism. In this study, the mobile lidar measurements in Beijing on heavily polluted days in December from 2015 to 2018 are presented. The lidar was mounted on a vehicle, which could perform measurements along designated routes. On the basis of mobile lidar measurements along closed circuits of the 6th Ring Road around Beijing, the spatial distribution and transport flux of PM2.5 in Beijing were determined with information of wind field. In the spatial distribution, both the concentration and transport of PM2.5 were revealed to be more significant in the southern section of Beijing. The regional transport layer at heights < 1.3 km plays an important role in pollution formation. The maximum transport flux reached 1600 μg/(m2*sec) on 11 December 2016. With the aerosol boundary layer height determined from the image edge detection (IED) method, the inter-annual variations of the aerosol boundary layer height (ABLH) were also analysed. The ABLH decreased from 0.73 to 0.46 km during the same heavy pollution period from 2015 to 2018. Increasingly adverse aerosol boundary layer (ABL) meteorological factors, including lower ABLH, light winds, temperature inversions, and accumulated moisture, have become necessary for pollution formation in Beijing.

Three‐Dimensional Distribution of PM2.5 over the Yangtze River Delta as Cold Fronts Moving Through

AbstractLong‐range transport of PM2.5 from the North China Plain (NCP) by cold frontal passage is considered to be an important haze formation mechanism in the Yangtze River Delta (YRD). However, detailed 3D distributions of PM2.5 and meteorological fields during the front moving through are not fully understood. Herein, in situ observations showed that most haze events in autumn and winter in the YRD were associated with cold frontal passages. A typical cold front episode on November 2–3, 2017, was investigated with unmanned aerial vehicle sounding and model simulations, which both revealed that PM2.5 in the upper air (∼1.0 km) reached the YRD earlier than that moving at the ground level. When the cold front reached the NCP, air pollutants ahead of the front was lifted from the ground level to the upper air. Subsequently, increased PM2.5 concentrations and higher wind speed in the upper air resulted in stronger PM2.5 outflow from the NCP to YRD compared to that at ground level. The maximum PM2.5 mass contribution from the NCP to YRD was 15.6 μg m−3 (accounted for 31.5% of the total PM2.5 in the YRD), which appeared at ∼1.0 km altitude. Compared to the noncold front period, the PM2.5 mass transported from the NCP was 10–15 times higher during the cold front episode. Results indicate that the combination of multisite sounding and elaborate simulation can effectively explain the impact of synoptic processes on the transport, distribution, and evolution of air pollution and provide precise pollution control directives.

Atmospheric Age Distribution of Primary and Secondary Inorganic Aerosols in a Polluted Atmosphere.

The community multiscale air quality (CMAQ) model was modified to track the evolution of the atmospheric age (τ) distribution of primary particulate matter (PPM) and secondary inorganic aerosol components (nitrate, sulfate, and ammonium ion, NSA). The modified CMAQ gas and aerosol mechanisms represent the same species emitted at different times as an age-resolved mixture, using multiple age-tagged variables and a dynamic age-bin advancing scheme. The model was applied to study the spatial and temporal evolution of τ for PPM and NSA in January 2013 to understand the formation and regional transport of PM and the precursor gases during severe winter pollution episodes in China. The results showed that increases in PPM and NSA concentrations during high pollution periods in polluted urban areas were typically associated with increases in the mean atmospheric age (τ̅) due to the accumulation of local emissions and regional transport of aged pollutants. Some of the rapid sulfate growth events at the beginning of multiday air pollution episodes were driven by regional transport of aged particles. In heavily polluted cities, while most of the monthly average PPM had τ less than 10 h, more than half of the sulfate had τ greater than 20-30 h. Regional distributions showed that very aged sulfate particles with τ > 96 h accounted for a significant portion of the total sulfate and had a very broad spatial distribution. However, aged ammonium ions had very low concentrations. Aged nitrate also had lower concentrations and more limited spatial distributions than sulfate due to differences in the atmospheric lifetime between SO2 and NOx. The estimated NOx lifetime of approximately ∼24 h in China agrees with a satellite-based estimation of 21 h. Potential applications of the age distribution analysis include evaluating the impacts of meteorology on air quality and developing short-term emission control strategies.