Influence of urban morphological parameters on the distribution and diffusion of air pollutants: A case study in China

Air pollution has a serious fallout on human health, and the influences of the different urban morphological characteristics on air pollutants cannot be ignored. In this study, the relationship between urban morphology and air quality (wind speed, CO, and PM_2.5) in residential neighborhoods at the meso-microscale was investigated. The changes in the microclimate and pollutant diffusion distribution in the neighborhood under diverse weather conditions were simulated by Computational Fluid Dynamics (CFD). This study identified five key urban morphological parameters (Building Density, Average Building Height, Standard Deviation of Building Height, Mean Building Volume, and Degree of Enclosure) which significantly impacted the diffusion and distribution of pollutants in the neighborhood. The findings of this study suggested that three specific strategies (e.g. volume of a single building should be reduced, DE should be increased) and one comprehensive strategy (the width and height of the single building should be reduced while the number of single buildings should be increased) could be illustrated as an optimized approach of urban planning to relief the air pollution. The result of the combined effects could provide a reference for mitigating air pollution in sustainable urban environments.     

Cross-boundary transport and source apportionment for PM2.5 in a typical industrial city in the Hebei Province, China: A modeling study

Cross-boundary transport of air pollution is a difficult issue in pollution control for the North China Plain. In this study, an industrial district (Shahe City) with a large glass manufacturing sector was investigated to clarify the relative contribution of fine particulate matter (PM_2.5) to the city's high levels of pollution. The Nest Air Quality Prediction Model System (NAQPMS), paired with Weather Research and Forecasting (WRF), was adopted and applied with a spatial resolution of 5 km. During the study period, the mean mass concentrations of PM_2.5, SO₂, and NO₂ were observed to be 132.0, 76.1, and 55.5 μg/m³, respectively. The model reproduced the variations in pollutant concentrations in Shahe at an acceptable level. The simulation of online source-tagging revealed that pollutants emitted within a 50-km radius of downtown Shahe contributed 63.4% of the city's total PM_2.5 concentration. This contribution increased to 73.9±21.2% when unfavorable meteorological conditions (high relative humidity, weak wind, and low planetary boundary layer height) were present; such conditions are more frequently associated with severe pollution (PM_2.5 ≥ 250 μg/m³). The contribution from Shahe was 52.3±21.6%. The source apportionment results showed that industry (47%), transportation (10%), power (17%), and residential (26%) sectors were the most important sources of PM_2.5 in Shahe. The glass factories (where chimney stack heights were normally < 70 m) in Shahe contributed 32.1% of the total PM_2.5 concentration in Shahe. With an increase in PM_2.5 concentration, the emissions from glass factories accumulated vertically and narrowed horizontally. At times when pollution levels were severe, the horizontally influenced area mainly covered Shahe. Furthermore, sensitivity tests indicated that reducing emissions by 20%, 40%, and 60% could lead to a decrease in the mass concentration of PM_2.5 of of 12.0%, 23.8%, and 35.5%, respectively.     

PM2.5 and water-soluble inorganic ion concentrations decreased faster in urban than rural areas in China

We investigated variations of PM_2.5 and water-soluble inorganic ions chemical characteristics at nine urban and rural sites in China using ground-based observations. From 2015 to 2019, mean PM_2.5 concentration across all sites decreased by 41.9 µg/m³ with a decline of 46% at urban sites and 28% at rural sites, where secondary inorganic aerosol (SIAs) contributed to 21% (urban sites) and 17% (rural sites) of the decreased PM_2.5. SIAs concentrations underwent a decline at urban locations, while sulfate (SO₄^2–), nitrate (NO₃^–), and ammonium (NH₄⁺) decreased by 49.5%, 31.3% and 31.6%, respectively. However, only SO₄^2– decreased at rural sites, NO₃^– increased by 21% and NH₄⁺ decreased slightly. Those changes contributed to an overall SIAs increase in 2019. Higher molar ratios of NO₃^– to SO₄^2– and NH₄⁺ to SO₄^2– were observed at urban sites than rural sites, being highest in the heavily polluted days. Mean molar ratios of NH₃/NH_x were higher in 2019 than 2015 at both urban and rural sites, implying increasing NH_x remained as free NH₃. Our observations indicated a slower transition from sulfate-driven to nitrate-driven aerosol pollution and less efficient control of NO_x than SO₂ related aerosol formation in rural regions than urban regions. Moreover, the common factor at urban and rural sites appears to be a combination of lower SO₄^2– levels and an increasing fraction of NO₃^– to PM_2.5 under NH₄⁺-rich conditions. Our findings imply that synchronous reduction in NO_x and NH₃ emissions especially rural areas would be effective to mitigate NO₃^–-driven aerosol pollution.     

Seasonal differences in sources and formation processes of PM2.5 nitrate in an urban environment of North China

Nitrate (NO₃⁻) has been the dominant ion of secondary inorganic aerosols (SIAs) in PM_2.5 in North China. Tracking the formation mechanisms and sources of particulate nitrate are vital to mitigate air pollution. In this study, PM_2.5 samples in winter (January 2020) and in summer (June 2020) were collected in Jiaozuo, China, and water-soluble ions and (δ¹⁵N, δ¹⁸O)-NO₃⁻ were analyzed. The results showed that the increase of NO₃⁻ concentrations was the most remarkable with increasing PM_2.5 pollution level. δ¹⁸O-NO₃⁻ values for winter samples (82.7‰ to 103.9‰) were close to calculated δ¹⁸O-HNO₃ (103‰ ± 0.8‰) values by N₂O₅ pathway, while δ¹⁸O-NO₃⁻ values (67.8‰ to 85.7‰) for summer samples were close to calculated δ¹⁸O-HNO₃ values (61‰ ± 0.8‰) by OH oxidation pathway, suggesting that PM_2.5 nitrate is largely from N₂O₅ pathway in winter, while is largely from OH pathway in summer. Averaged fractional contributions of P_N2O5+H2O were 70% and 39% in winter and summer sampling periods, respectively, those of P_OH were 30% and 61%, respectively. Higher δ¹⁵N-NO₃⁻ values for winter samples (3.0‰ to 14.4‰) than those for summer samples (-3.7‰ to 8.6‰) might be due to more contributions from coal combustion in winter. Coal combustion (31% ± 9%, 25% ± 9% in winter and summer, respectively) and biomass burning (30% ± 12%, 36% ± 12% in winter and summer, respectively) were the main sources using Bayesian mixing model. These results provided clear evidence of particulate nitrate formation and sources under different PM_2.5 levels, and aided in reducing atmospheric nitrate in urban environments.     

Temporal and spatial characteristics of PM2.5 transport fluxes of typical inland and coastal cities in China

Local pollution and the cross-boundary transmission of pollutants between cities have an inevitable impact on the atmosphere. Quantitative assessments of the contribution of transport to pollution in inland and coastal cities are necessary for the implementation of practical, regional, and joint emission control strategies. In this study, the Comprehensive Air Quality Model (CAMx), together with the Weather Research and Forecasting model (WRF), was used to simulate the contributions to pollution of different cities in 2016. The monthly inflow, outflow, and net flux from the ground to the extended layers served as the three main indicators for the analysis of the interactions of PM_2.5 transport between adjacent cities. Between inland and coastal cities, the magnitude of inflow and outflow are larger in the former than in the latter. The inflow flux in the inland cities (Beijing and Shijiazhuang) was 10.6 and 10.7 kt/day, respectively, while that in the coastal cities (Tianjin, Shanghai, Hefei, Nanjing, and Hangzhou) was 9.1, 3.3, 5.8, 4.4, and 3.7 kt/day, respectively. In terms of variation over the year, the strongest inflow in the BTH region occurred in April, followed by October, July, and January, while that in the coastal cities in YRD occurred in January, followed by October, April, and July. Therefore, based on the flux intensity calculations and the transport flux pathways, effective joint control measures can be provided with scientific support, and a better understanding of the evolutionary mechanism among inland and coastal cities can be acquired.     

Synergetic PM2.5 and O3 control strategy for the Yangtze River Delta, China

PM_2.5 concentrations have dramatically reduced in key regions of China during the period 2013–2017, while O₃ has increased. Hence there is an urgent demand to develop a synergetic regional PM_2.5 and O₃ control strategy. This study develops an emission-to-concentration response surface model and proposes a synergetic pathway for PM_2.5 and O₃ control in the Yangtze River Delta (YRD) based on the framework of the Air Benefit and Cost and Attainment Assessment System (ABaCAS). Results suggest that the regional emissions of NOx, SO₂, NH₃, VOCs (volatile organic compounds) and primary PM_2.5 should be reduced by 18%, 23%, 14%, 17% and 33% compared with 2017 to achieve 25% and 5% decreases of PM_2.5 and O₃ in 2025, and that the emission reduction ratios will need to be 50%, 26%, 28%, 28% and 55% to attain the National Ambient Air Quality Standard. To effectively reduce the O₃ pollution in the central and eastern YRD, VOCs controls need to be strengthened to reduce O₃ by 5%, and then NOx reduction should be accelerated for air quality attainment. Meanwhile, control of primary PM_2.5 emissions shall be prioritized to address the severe PM_2.5 pollution in the northern YRD. For most cities in the YRD, the VOCs emission reduction ratio should be higher than that for NOx in Spring and Autumn. NOx control should be increased in summer rather than winter when a strong VOC-limited regime occurs. Besides, regarding the emission control of industrial processes, on-road vehicle and residential sources shall be prioritized and the joint control area should be enlarged to include Shandong, Jiangxi and Hubei Province for effective O₃ control.     

Chemical characteristics, oxidative potential, and sources of PM2.5 in wintertime in Lahore and Peshawar, Pakistan

The chemical characteristics, oxidative potential, and sources of PM_2.5 were analyzed at the urban sites of Lahore and Peshawar, Pakistan in February 2019. Carbonaceous species, water soluble ions, and metal elements were measured to investigate the chemical composition and sources of PM_2.5. The dithiothreitol (DTT) consumption rate was measured to evaluate the oxidative potential of PM_2.5. Both cities showed a high exposure risk of PM_2.5 regarding its oxidative potential (DTT_v). Carbonaceous and some of the elemental species of PM_2.5 correlated well with DTT_v in both Lahore and Peshawar. Besides, the DTT_v of PM_2.5 in Lahore showed significant positive correlation with most of the measured water soluble ions, however, ions were DTT-inactive in Peshawar. Due to the higher proportions of carbonaceous species and metal elements, Peshawar showed higher mass-normalized DTT activity of PM_2.5 compared to Lahore although the average PM_2.5 concentration in Peshawar was lower. The high concentrations of toxic metals also posed serious non-carcinogenic and carcinogenic risks to the residents of both cities. Principle component analysis coupled with multiple linear regression was applied to investigate different source contributions to PM_2.5 and its oxidative potential. Mixed sources of traffic and road dust resuspension and coal combustion, direct vehicle emission, and biomass burning and formation of secondary aerosol were identified as the major sources of PM_2.5 in both cities. The findings of this study provide important data for evaluation of the potential health risks of PM_2.5 and for formulation of efficient control strategies in major cities of Pakistan.     

Investigation of PM2.5 pollution during COVID-19 pandemic in Guangzhou, China

The COVID-19 pandemic has raised awareness about various environmental issues,including PM_2.5 pollution.Here,PM_2.5 pollution during the COVID-19 lockdown was traced and analyzed to clarify the sources and factors influencing PM_2.5 in Guangzhou,with an emphasis on heavy pollution.The lockdown led to large reductions in industrial and traffic emissions,which significantly reduced PM_2.5 concentrations in Guangzhou.Interestingly,the trend of PM_2.5     

A land use regression for predicting NO2 and PM10 concentrations in different seasons in Tianjin region,China

Land use regression (LUR) model was employed to predict the spatial concentration distribution of NO2 and PM10 in the Tianjin region based on the environmental air quality monitoring data. Four multiple linear regression (MLR) equations were established based on the most significant variables for NO2 in heating season (R2 = 0.74), and non-heating season (R2 = 0.61) in the whole study area; and PM10 in heating season (R2 = 0.72), and non-heating season (R2 = 0.49). Maps of spatial concentration distribution for NO2 and PM10 were obtained based on the MLR equations (resolution is 10 km). Intercepts of MLR equations were 0.050 (NO2, heating season), 0.035 (NO2, non-heating season), 0.068 (PM10, heating season), and 0.092 (PM10, non-heating season) in the whole study area. In the central area of Tianjin region, the intercepts were 0.042 (NO2, heating season), 0.043 (NO2, non-heating season), 0.087 (PM10, heating season), and 0.096 (PM10, non-heating season). These intercept values might imply an area’s background concentrations. Predicted result derived from LUR model in the central area was better than that in the whole study area. R2 values increased 0.09 (heating season) and 0.18 (non-heating season) for NO2, and 0.08 (heating season) and 0.04 (non-heating season) for PM10. In terms of R2, LUR model performed more effectively in heating season than non-heating season in the study area and gave a better result for NO2 compared with PM10.     

Impacts of meteorological parameters on the occurrence of air pollution episodes in the Sichuan basin

Episodes of fine-particulate matter(PM_2.5) pollution are a widespread and common occurrence in China, and have potentially serious implications for human health. Meteorological conditions play an important role in air quality and influence the formation of regional air pollution episodes. This study applied a new classification method and daily PM_2.5 concentration data to(a) evaluate different levels of air pollution in the Sichuan–Chongqing region between 2015 and 2017, an...