An iteratively optimized downscaling method for city-scale air quality forecast emission inventory establishment.

Air quality models (AQMs) are pivotal in forecasting air quality and shaping pollution control strategies. Nonetheless, the effectiveness of AQMs is often compromised in many cities due to the absence of accurate local emission inventories. To address this gap, this study presents a novel AQM-ready emission inventory generation technique with iterative optimization ability for city-scale applications in China. An efficient emission processing tool was introduced in this study, which utilizes the High-Resolution Multi-resolution Emission Inventory for China (HR-MEIC) as input. Using environmental observations and a region map, the tool can justify emissions of different regions iteratively. With the iterative optimization method, the model performance can be notably improved even without local emissions. The optimization was realized by splitting model-ready emissions into different regions and adjusting the emissions using scale factors calculated with the modeling results and the observations of each region. This methodology was applied to the Eight Cities in the Chengdu Plain (CP8C), located in the western margin of Sichuan Basin with complex topography and meteorological conditions, southwestern China, monthly throughout 2023. Air quality modeling was carried out using Weather Forecast and Research Model (WRF) and the Community Multiscale Air Quality Model (CMAQ). The results showed that the optimization acquired a good performance after five cycles for PM2.5 and NO2, with correlation coefficients (R values) surging from 0.62 and 0.37 to 0.77 and 0.73, respectively, while their normalized mean bias (NMB) substantially decreased from 22.8 % and 100.4 % to 3.6 % and 3.3 %. The underestimation on O3 concentration was also improved by the optimization, although enhancements in O3 modeling remained modest. This technique provides an easy-to-copy method to generate reasonable AQM-ready emission files with open emission data and observation data, which would be beneficial for the cities' air quality forecast in cities without local emission inventories.

Impacts of different vehicle emissions on ozone levels in Beijing: Insights into source contributions and formation processes.

Beijing, with the highest number of motor vehicles in China, significantly contributes to O3 pollution through substantial NOx and VOC emissions in the on-road transportation sector. Understanding the unique impact of emissions from different vehicle types on O3 levels is crucial for developing targeted strategies for O3 pollution. This study applied the Community Multiscale Air Quality Modeling System (CMAQ) to comprehensively investigate the impacts of emissions from different vehicle types on O3 levels in various regions of Beijing and to provide valuable insights into source contributions and formation processes. The results revealed that various vehicle types exhibited different spatial-temporal emission patterns, with medium-heavy duty trucks (HDT) and mini-light passenger vehicles (LDPV) identified as the primary contributors to NOx (36.1 %) and VOC (57.6 %) emissions. Using the Integrated Source Apportionment Method (ISAM) coupled in CMAQ, we found the total vehicle emissions contributed to over 20 % of daily maximum 8-h average O3 (MDA8 O3) concentration, ranked as the second largest contributor after regional transport. Contributions to O3 formation from LDPV and medium-large passenger vehicles (MDPV) were 2.6-4.0 and 4.2-6.8 ppb and mainly concentrated in urban areas, while the contributions from mini-light duty trucks (LDT) and HDT were 3.5-4.8 and 3.7-6.2 ppb and mainly concentrated in suburban areas. Through scenario analysis that removed emissions from specific types of vehicles, we found removing LDPV emissions led to decreases in daytime O3 concentration by 0.3-3.8 ppb. In contrast, removing MDPV emissions led to notable O3 increases by 4.0-11.8 ppb at rush hours. Removing LDT and HDT emissions resulted in 0.6-8.0 ppb increases in nocturnal O3 concentrations while 0.8-2.0 ppb decreases during the afternoon. This research highlights the necessity of tailoring control strategies for different vehicle types to effectively reduce O3 levels in Beijing and provides useful information for decision-makers to formulate effective measures of vehicle management in the future.

Investigation into the nocturnal ozone in a typical industrial city in North China Plain, China.

Ozone (O3) concentrations usually peak at midday by photochemical reactions and gradually decline after sunset due to chemical destruction and dry deposition. However, an increase in the frequency of elevated nocturnal ozone enhancement (NOE) and high nocturnal ozone value (HNOV) has been frequently observed in urban areas of eastern China, but the reasons are not well understood. In this study, taking a typical industrial city, ZiBo as a case study, we analyzed the trends, characteristics, and causes of the NOE and HNOV events in historical years by combining observations and model simulations. During the warm season (April-September) of 2017-2023, HNOV events are accompanied by low humidity, high temperature, large friction velocity, and a high boundary layer (52 days in total), whereas NOE events coincide with increases in humidity, wind speed, friction velocity, and boundary layer height (141 days in total). During the HNOV and NOE events, the nighttime average concentrations of Ox were 77 ± 7 and 12 ± 6 µg m-3 higher than the non-nocturnal O3 period, indicating enhanced atmospheric oxidizing capacity during nighttime. The modeling results indicate that both the HNOV and NOE events were mainly driven by vertical mixing and regional transport. We selected a typical period with high O3 pollution and frequent NOE and HNOV events to conduct the modeling study. Three typical nocturnal O3 events are identified: Case I was mainly driven by horizontal transport; while in the two subsequent cases, the vertical transport contribution was 80 µg m-3 h-1 (20:00 LT on June 21, 2021) and 35 µg m-3 h-1 (02:00 LT on June 26, 2021), respectively. Our study reveals that the O3 pollution in industrial cities has been extending to nighttime, primarily attributed to vertical mixing and horizontal transport within the boundary layer. This highlights the critical role of implementing regional joint control action to reduce primary emissions and eliminate residual ozone.

Implications of ozone transport on air quality in the Sichuan Basin, China.

Ozone pollution is formed through complex chemical and physical processes closely associated with emissions, photochemical reactions, and meteorological conditions. The objective of this study is to quantify the contributions of meteorological chemical formation, vertical transport, and horizontal transport to air quality during spring and summer in different regions of the Sichuan Basin. The Community Multi-scale Air Quality (CMAQ) with the Integrated Process Rate (IPR) was employed to simulate the months of April and July 2021 in the Sichuan Basin. The results indicate that both the spring and summer chemical formation of ozone in the urban centre show negative values, while the surrounding urban areas contribute positively, with chemical formation ranging from 0 to 10 µg·m-3. The maximum ozone level due to horizontal transport in the urban centre exceeds 20 µg·m-3, whereas horizontal transport in the surrounding urban areas exhibits negative values, with transport contributions concentrated within the range of -5 to 0 µg·m-3. The vertical transport in the central and southern parts of the basin shows positive values, with transport contributions ranging from 0 to 10 µg·m-3, and the urban centre exhibits relatively stronger vertical transport with contributions ranging from 10 to 20 µg·m-3. Although the chemical formation contribution in the urban centre is relatively small due to high nitrogen oxide emissions, vertical and horizontal transport play significant roles and are among the key factors contributing to ozone pollution formation.

Source emission contributions to particulate matter and ozone, and their health impacts in Southeast Asia.

Southeast Asia has been experiencing severe air pollution due to its substantial local emissions and transboundary air pollution (TAP), causing significant health impacts. While literature focused on air pollution episodes in Southeast Asia, we have yet to fully understand the contributions of local emission sectors and TAP to air quality in the region annually. Herein we employed air quality modeling with the species tagging method to first assess the contributions of source sectors and locations to fine particulate matter (PM2.5) and ozone (O3) in Southeast Asia and to hence quantify the resultant health impacts. Our results show that air pollutant exposure was associated with âˆ¼ 900 thousand premature mortalities in Southeast Asia every year. Of which, 77 % and 23 % were due to local emissions and TAP in the region, respectively. âˆ¼ 87 % of the premature mortalities due to local emissions were induced by PM2.5 exposure, whereas the remaining were due to O3 exposure. PM2.5-related health impacts were dominated by industrial (45 %) and residential (17 %) emissions, and O3-related impacts were mainly due to biogenic (40 %) and road transport (24 %) emissions. Furthermore, the health impacts of TAP were particularly adverse in Brunei, East Timor, Singapore, Laos, and border regions.

[Impacts of Anthropogenic Emission Reduction on Urban Atmospheric Oxidizing Capacity During the COVID-19 Lockdown].

In recent years， regional compound air pollution events caused by fine particles （PM2.5） and ozone （O3） have occurred frequently in economically developed areas of China， in which atmospheric oxidizing capacity （AOC） has played an important role. In this study， the WRF-CMAQ model was used to study the impacts of anthropogenic emission reduction on AOC during the COVID-19 lockdown period. Three representative cities in eastern China （Shijiazhuang， Nanjing， and Guangzhou） were selected for an in-depth analysis to quantify the contribution of meteorology and emissions to the changes in AOC and oxidants and to discuss the impact of AOC changes on the formation of secondary pollutants. The results showed that， compared with that in the same period in 2019， the urban average AOC in Shijiazhuang， Nanjing， and Guangzhou in 2020 increased by 60%， 48.7%， and 12.6%， respectively. The concentrations of O3， hydroxyl radical （·OH）， and nitrogen trioxide （NO3·ï¼‰ increased by 1.6%-26.4%， 14.8%-73.3%， and 37.9%-180%， respectively. The AOC in the three cities increased by 0.06×10-4， 0.12×10-4， and 0.33×10-4 min-1， respectively， due to emission reduction. The meteorological change increased AOC in Shijiazhuang and Nanjing by 20% and 17.9%， respectively， but decreased AOC in Guangzhou by -9.3%. Enhanced AOC led to an increase in the nitrogen oxidation ratio （NOR） and VOCs oxidation ratio （VOR） and promoted the transformation of primary pollutants to secondary pollutants. This offset the effects of primary emission reduction and resulted in a nonlinear decline in secondary pollutants compared to emissions during the COVID-19 lockdown.

Insights into the source contributions to the elevated fine particulate matter in Nigeria using a source-oriented chemical transport model.

In 2021, Nigeria was ranked by the World Health Organization (WHO) as one of the top countries with highly deteriorating air quality in the world. To date, no study has elucidated the sources of elevated fine particulate matter (PM2.5) concentrations over the entire Nigeria. In this study, the Community Multiscale Air Quality (CMAQ) model was applied to quantify the contributions of seven emissions sectors to PM2.5 and its components in Nigeria in 2021. Residential, industry, and agriculture were the major sources of primary PM (PPM) during the four seasons, elemental carbon (EC) and primary organic carbon (POC) were dominated by residential and industry, while residential, industry, transportation, and agriculture were the important sources of secondary inorganic aerosols (SIA) and its components in most regions. PM2.5 was up to 150 µg/m3 in the north in all the seasons, while it reached ∼80 µg/m3 in the south in January. Residential contributed most to PM2.5 (∼80 µg/m3), followed by industry (∼40 µg/m3), transportation (∼20 µg/m3), and agriculture (∼15 µg/m3). The large variation in the sources of PM2.5 and its components across Nigeria suggests that emissions control strategies should be separately designed for different regions. The results imply that urgent control of PM2.5 pollution in Nigeria is highly necessitated.

Unraveling the influence of biogenic volatile organic compounds and their constituents on ozone and SOA formation within the Yellow River Basin, China.

Biogenic volatile organic compounds (BVOC) assume a pivotal role during the formation stages of ozone (O3) and secondary organic aerosols (SOA), serving as their primary precursors. We used the latest MEGAN3.1 model, updated vegetation data and emission factors, combined with MODIS data analysis to simulate and estimate the integrated emissions of BVOC from nine provinces in China's Yellow River Basin in 2018. Following an extensive evaluation of the WRF-CMAQ model utilizing diverse parameters, the simulated and observed values had correlation coefficients between them that ranged from 0.94 to 0.99, implying a favorable outcome in terms of simulation efficacy. The findings from the simulation analysis reveal that the combined BVOC emissions from the nine provinces in the Yellow River Basin reached a total of 6.51 Tg in 2018. Among these provinces, Sichuan, Henan, and Shaanxi ranked highest, with emissions of 1.28 Tg, 1.04 Tg, and 0.96 Tg, respectively. BVOC emissions led to concentrations of 36.72 µg/m³ in the daily maximum 8-h ozone and 0.59 µg/m³ in the average SOA in nine provinces of the Yellow River Basin in July. Isoprene contributed the most to the O3 production with 6.31 µg/m3, and monoterpenes contributed the most to SOA production with 0.45 µg/m3. ΔSOA and ΔOzone are mainly distributed in the belts of central Sichuan Province, southern Shaanxi Province, western Henan Province, northern Qinghai Province, central Inner Mongolia, and southern Shanxi Province, and most of these areas are located 50 km around the Yellow River. O3 and SOA in Taiyuan, Xi'an, Chengdu, and Zhengzhou cities are strongly influenced by the generation of BVOCs. This study provides a reliable scientific basis for the prevention and control of air pollution in the Yellow River Basin.

Improved estimation of CO2 emissions from thermal power plants based on OCO-2 XCO2 retrieval using inline plume simulation.

CO2 emissions from power plants are the dominant source of global CO2 emissions, thus in the context of global warming, accurate estimation of CO2 emissions from power plants is essential for the effective control of carbon emissions. Based on the XCO2 retrievals from the Orbiting Carbon Observatory 2 (OCO-2) and the Gaussian Plume Model (GPM), a series of studies have been carried out to estimate CO2 emission from power plants. However, the GPM is an ideal model, and there are a number of assumptions that need to be made when using this model, resulting in large uncertainties in the inverted emissions. Here, based on 6 cases of power plant plumes observed by the OCO-2 satellite over the Yangtze River Delta, China, we use an inline plume rise module coupled in the Community Multi-scale Air Quality model (CMAQ) to simulate the plumes and invert the emissions, and compare the simulated plumes and inverted emissions using the GPM model. We found that CO2 emissions can be significantly overestimated or underestimated based on the GPM simulations, and that the CMAQ inline plume simulation could significantly improve the estimates. However, the simulation bias in wind speed can significantly affect the inversion results. These results indicate that accurate meteorological field and plume simulations are critical for future inversion of point source emissions.

The impacts of ship emissions on ozone in eastern China.

Tropospheric ozone (O3), which is one of the main pollutants impeding air quality compliance, has received considerable attention in China. As maritime transportation continues to expand, the effect of ship emissions on air quality is becoming increasingly important. In this study, the Weather Research and Forecast model (WRF), the Community Multiscale Air Quality model (CMAQ), and the integrated process rate (IPR) module provided in the CMAQ are applied to evaluate the impacts of ship emissions on O3 concentration at a national scale in China, including the spatiotemporal characteristics and influencing pathways. Ship emissions can increase or decrease O3 concentrations, with varying effects in different seasons and regions. In the winter, spring, and fall, ship emissions were predicted to decrease O3 concentrations in most areas, whereas in the summer, they increase the O3 concentration, even in regions far away from the coastline, thus adversely affecting the Yangtze River Delta (YRD) and Pearl River Delta (YRD). Additionally, owing to differences in the emissions of volatile organic compounds and nitrogen oxides, the northern and southern regions of the YRD respond differently to ship emissions. Additionally, the influence of ship emissions on the diurnal variation of O3 in the summer was investigated, where significant differences were indicated between cities. The IPR was used to investigate the individual processes contributing to changes in the O3 concentration caused by ship emissions. The transport process appears to be the primary contributor to O3 production, whereas chemistry and dry deposition played key roles in O3 loss. This study provides an in-depth insight into the impacts of ship emissions on O3 in China, which can facilitate the formulation of corresponding environmental policies.

Assessment of rice yield and economic losses caused by ground-level O3 exposure in the Mekong delta region, Vietnam.

The Lower Mekong Delta region (LMD) accounts for 90% of Vietnam's rice exports; however, the air quality in the LMD is remarkably reduced by ground-level ozone (O3) pollution. This study aimed to quantify the relative yield and economic value losses in rice-growing crop seasons affected by ground-level O3 concentrations across the LMD. The results of this study can serve as a basis for extensive assessments for the following years and support environmental managers to propose control measures of O3 precursor emissions (NOx and VOCs) from man-made sectors, as well as build protective solutions for rice farming in LMD. Two ground-level O3 exposure metrics of M7 and AOT40 reflecting ground-level O3 pollution impacts, combined with the model of exposure-relative yield relationship (or surface O3-crop models), were used to assess losses of crop production (CPL) and economic cost losses (ECL) caused by rice crop yield reductions. For the M7 metric of ground-level O3 exposure, the average value was 14.746 ppbV, with levels ranging from 13.959 ppbV to 15.502 ppbV, and the affected area was spread across 1309.39 thousand hectares. The AOT40 exposure metric reached an average value of 11.490 ppbV, with a range of 0.000-31.665 ppbV. The highest exposure level was 17.503-31.653 ppbV, covering an area of 747.01 thousand hectares. The total CPL of the three rice crops over the LMD was 9593.52 tonnes (accounting for 0.039% of the total value of rice production in the region), with a total corresponding EPL of 62.405 billion VND (equivalent to 2761.01 thousand USD). The results are considered a baseline study to serve as a basis for extensive assessments for the following years and support for the environmental managers to propose control measures of O3 precursor emissions (NOx and VOCs) from man-made sectors as well as build protective solutions in rice farming in LMD shortly.

Significant land cover change in China during 2001-2019: Implications for direct and indirect effects on surface ozone concentration.

China has become one of the most prominent areas of global land cover change during the past few decades. These changes can directly influence meteorological parameters thus further regulating tropospheric ozone (O3) formation. Moreover, changes in biogenic emissions due to land cover variation can also have an indirect effect on O3 concentration. This study applied the Community Multiscale Air Quality model to comprehensively evaluate the impacts of significant land cover change on O3 levels in China during summertime between 2001 and 2019. The results showed that the daily maximum 8-h average O3 concentration (MDA8 O3) increased by 3.6-8.9 µg/m3, 2.8-8.0 µg/m3, 3.8-9.6 µg/m3, -1.5-6.2 µg/m3, and -0.6-2.5 µg/m3 in Beijing-Tianjin-Hebei region, Yangtze River Delta, Pearl River Delta, Sichuan Basin, and Fenwei Plain, respectively, in response to land cover variation. The research identified that the direct effect was the primary factor in raising O3 levels which mainly altered O3 concentration by changing vertical import and dry deposition velocity. Moreover, land cover variation tended to decrease biogenic nitric oxide emission and increase biogenic volatile organic compounds emission on the whole, and cause an obvious increase of MDA8 O3 by 1.8-4.9 µg/m3 in Pearl River Delta due to the indirect effect. This study offered valuable insights into the impacts of land cover change on O3 levels, highlighting the need for policymakers to consider land cover variation on air pollutants concentration for devising comprehensive multi-pollutant control strategies.

Impact analysis of meteorological variables on PM2.5 pollution in the most polluted cities in China.

With the continuous promotion of urbanization in China, air pollution problems have become increasingly prominent in recent years. Various factors, such as emissions, meteorology, and physical and chemical reactions, jointly affect the severity of PM2.5 pollution to a large extent. This study selected five meteorological variables (planetary boundary layer height (PBLH), wind speed (WS), temperature(T), water vapor mixing ratio(Q), and precipitation (PCP)) for perturbation, and 21 different scenarios were set up. In this study, the effects of changes in a single meteorological variable on the pollutants produced in the area were represented by subtracting the baseline scenario (i.e., without perturbation of meteorological variables) simulated in January 2017 separately from each post-disturbance scenario. The results showed that Handan (HD) has the highest annual mean PM2.5 concentration of 85.75 µg/m3 in 2017, while all cities in study area exceeded the secondary concentration limit of urban atmospheric particulate matter. The correlation coefficient (R) between the simulation values of models and the actual monitoring values ranges from 0.41 to 0.74, indicating good model performance and acceptable simulation errors. PBLH (±10%-±20%), WS(±10%-±20%), and PCP(±10%-±20%) all showed a single adverse effect among the five meteorological variables, meaning that a reduction in these three factors led to an increase in PM2.5 concentrations. However, T (±1 K-±1.5 K) and Q (±10%-±20%) could indicate a positive impact under certain conditions. From the sensitivity calculations of single meteorological variables, it is clear that WS, PBLH, and PCP show a highly linear trend in all cities at the 0.01 level of significance. The hypothesis that T changes linearly in 10 cities in the study area is valid, while for Q, the hypothesis that Q changes linearly only occurs in Shijiazhuang and Baoding. When different meteorological variables are disturbed, there are significant spatial differences in the main affected areas of PM2.5 concentrations. By discussing the impact of meteorological variable disturbance on air quality in critically polluted cities in China, this study identified the meteorological variables that can substantially affect PM2.5 concentration. The more complex T and Q should be considered when formulating relevant emission measures.

O3 transport characteristics in eastern China in 2017 and 2021 based on complex networks and WRF-CMAQ-ISAM.

Increasingly prominent pollution levels and strong regional characteristics of O3, especially in economically developed eastern China, called for a regional cooperation strategy based on transport quantification. This study adopted the complex networks to construct the O3 Transport Network (OTN) to explore characteristics in eastern China in the summer of 2017 and 2021, whose results were afterward verified with spatial source apportionment results simulated with WRF-CMAQ-ISAM. As OTN suggested, O3 transport showed stronger and faster characteristics in eastern China in 2021 than in 2017, judging from changes in the network density, number of connections, transport ranges, and transport paths. Among all cluster communities, inland Shandong was the most important O3 transport hub, the Central Community was the largest community, and the Southern Community showed the closest inter-city transport relationships. In- and out-weighted degrees in OTN showed relatively superior consistency with the transport matrix obtained with WRF-CMAQ-ISAM, and can be explained by wind fields. Generally, O3 pollution in the whole eastern China showed more frequent intra-regional transport and more strengthened inter-city correlations in 2021 than in 2017, meanwhile, northerly and southerly cities exhibited strengthening and weakening trends in O3 transport, respectively. Despite the completely different principles of complex networks and air quality models, their results were mutually verifiable. This study presented a comprehensive understanding of O3 transport in eastern China for further formulation of regional collaborative strategies and provided the methodological verification for applying complex networks in the atmospheric environment field.

Quantifying the air quality impact of ship emissions in China's Bohai Bay.

Bohai Bay, as a significant economic bay area in China, has experienced considerable ecological consequences during its rapid economic development. One of the major environmental challenges is the emission of air pollutants from ships, which has had a severe impact on regional air quality and the health of residents. To assess the influence of pollutants on the air quality around the Bohai Bay area, a Weather Research and Forecasting and Community Multiscale Air Quality (WRF-CMAQ) model was established using a 9 km × 9 km high-resolution ship emission gridded inventory from 2018. The WRF-CMAQ model was employed to compare two scenarios: vessel emissions and non-vessel emissions, in order to evaluate the impact of ship emissions. By analyzing the pollutant concentrations in Bohai Bay and the degree of change in pollutant concentration in six cities under these two scenarios, significant differences were observed. Furthermore, a comparison of the hourly concentration contributions of ship emissions between port cities and inland cities within the same region revealed that inland cities were less affected by ship emissions. The main contributing factors to this disparity were identified as wind direction and wind speed.

Chronic and acute health effects of PM2.5 exposure and the basis of pollution control targets.

Ho Chi Minh City (HCMC) is changing and expanding quickly, leading to environmental consequences that seriously threaten human health. PM2.5 pollution is one of the main causes of premature death. In this context, studies have evaluated strategies to control and reduce air pollution; such pollution-control measures need to be economically justified. The objective of this study was to assess the socio-economic damage caused by exposure to the current pollution scenario, taking 2019 as the base year. A methodology for calculating and evaluating the economic and environmental benefits of air pollution reduction was implemented. This study aimed to simultaneously evaluate the impacts of both short-term (acute) and long-term (chronic) PM2.5 pollution exposure on human health, providing a comprehensive overview of economic losses attributable to such pollution. Spatial partitioning (inner-city and suburban) on health risks of PM2.5 and detailed construction of health impact maps by age group and sex on a spatial resolution grid (3.0 km × 3.0 km) was performed. The calculation results show that the economic loss from premature deaths due to short-term exposure (approximately 38.86 trillion VND) is higher than that from long-term exposure (approximately 14.89 trillion VND). As the government of HCMC has been developing control and mitigation solutions for the Air Quality Action Plan towards short- and medium-term goals in 2030, focusing mainly on PM2.5, the results of this study will help policymakers develop a roadmap to reduce the impact of PM2.5 during 2025-2030.

Building and optimising an automatic monitoring system network for outdoor PM2.5: a case study of Ho Chi Minh City.

PM2.5 exposure data are important for air quality management. Optimal planning and determination of locations where PM2.5 is continuously monitored are important for urban areas in Ho Chi Minh City (HCMC), a megacity with specific environmental problems. Objectives of the study to propose an automatic monitoring system network (AMSN) to measure outdoor PM2.5 concentrations in HCMC using low-cost sensors. Data related to the current monitoring network, population, population density, threshold reference standards set by the National Ambient Air Quality Standard (NAAQS) and the World Health Organisation (WHO), and inventory emissions from various sources, both anthropogenic and biogenic, were obtained. Coupled WRF/CMAQ models were used to simulate PM2.5 concentrations in HCMC. The simulation results were extracted from the grid cells, from which the values of points exceeding the set thresholds were determined. The population coefficient was calculated to determine the corresponding total score (TS). Optimisation of the monitoring locations was statistically performed using Student's t-test to select the official locations for the monitoring network. TS values ranged from 0.0031 to 3215.9. The TSmin value was reached in the Can Gio district and the TSmax value was reached in SG1. Based on the t-test results, 26 initial locations were proposed for a preliminary configuration, from which 10 optimal monitoring sites were selected to develop the AMSN of outdoor PM2.5 concentration measurements in HCMC towards 2025.

Analysis of Pollution Characteristics and Emissions Reduction Measures in the Main Cotton Area of Xinjiang.

With cotton production in Xinjiang increasing annually, the impact on the environment of agricultural waste produced to improve production has been reflected. This study selected Bozhou of Xinjiang, the main cotton producing region in northern Xinjiang, as the research object, and collected hourly concentration data of six pollutants from 2017 to 2021, and analyzed the spatial and temporal distribution characteristics of each pollutant. At the same time, Morlet wavelet analysis was used to further analyze the variation period of PM2.5 (PM particles with aerodynamic diameters less than 2.5 µm) concentration. The Weather Research and Forecasting model coupled with the Community Multiscale Air Quality (WRF-CMAQ) model was used to evaluate the emissions reduction measures for the most polluted month. The results showed that the concentration of particulate matter (PM particles with aerodynamic diameters less than 2.5 µm and 10 µm) decreased from the southern mountains to the north; moreover, the concentrations of CO (carbon monoxide), NO2 (nitrogen dioxide), and SO2 (sulfur dioxide) in the suburbs were higher than those in the urban center. The concentration of O3 (Ozone) was the highest in summer, while the concentrations of other pollutants were high in autumn and winter. Under the time scale of a = 13, 24, PM2.5 had significant periodic fluctuation. The health risk values of PM2.5 and PM10 in this study were within the scope of the United States Environmental Protection Agency (USEPA) criteria, but it is still necessary to keep a close watch on them. In the context of emissions reduction measures, agricultural sources reduced by 20%, residential sources by 40%, industrial sources by 20%, and transportation sources by 20%; no change in the power source remains. Under these conditions, the daily average value of each pollutant met the first level of the national ambient air quality standard. The research results provide a reference for the local government to formulate heavy pollution emissions reduction policies.

Atmospheric dry deposition fluxes of trace metals over the Eastern China Marginal Seas: Impact of emission controls.

Atmospheric deposition is an important exogenous input of trace metals to Eastern China Marginal Seas (ECMS), which is strongly affected by human activities. With emission control practices implemented in China, it still remains unknown what changes have taken place in the atmospheric dry depositions of the trace metals over ECMS. This study aimed to estimate the atmospheric dry depositions of Zn, Pb, Cu, and Cd over ECMS via Weather Research and Forecasting Model-Community Multiscale Air Quality Modeling System (WRF-CMAQ) in the two winter periods of January 2012 and January 2019 as well as to explore the impacts of emission control on the depositions. The anthropogenic metal emissions from China, the Korean Peninsula, Japan, and marine ships were investigated in this study. In 2012, the dry deposition fluxes of Zn, Pb, Cu, and Cd over ECMS were in the ranges of 0.50-3.4 µg m-2 d-1, 0.22-1.9 µg m-2 d-1, 0.14-0.90 µg m-2 d-1, and 12-88 ng m-2 d-1, respectively. The deposition fluxes of the four metals over Bohai Sea (BS) and Yellow Sea (YS) were 2-3 times those over East China Sea (ECS). Outflow of polluted air masses from East Asia increased the metal depositions by 3- 5-fold relative to clear days. Compared with 2012, a 5-85 % reduction in the metal depositions over ECMS were estimated in 2019, largest reductions were found over YS and BS. Meteorological variation was able to decrease or increase the metal depositions. However, the emission control only caused a reduction in the entire study region. The metal inputs to the sea were significantly lower from the ship emissions than from the continental anthropogenic emissions, although the proportion of the ship emissions in the total metal depositions rose slightly from 2012 to 2019.

Striking impacts of biomass burning on PM2.5 concentrations in Northeast China through the emission inventory improvement.

Biomass burning exerts substantial influences on air quality and climate, which in turn to further aggravate air quality. The biomass burning emissions in particular of the agricultural burning may suffer large uncertainties which limits the understanding of their impact on air quality. Based on an improved emission inventory of the Visible Infrared Imaging Radiometer Suite (VIIRS) relative to commonly used Global Fire Emissions Database (GFED), we thoroughly evaluate the impact of biomass burning on air quality and climate during the episodes of November 2017 in Northeast China which is rich in agriculture burning. The results first indicate substantial underestimates in simulated PM2.5 concentrations without the inclusion of biomass burning emission inventory, based on a regional air quality model Weather Research and Forecasting model and Community Multiscale Air Quality model (WRF-CMAQ). The addition of biomass burning emissions from GFED then reduces the bias to a certain extent, which is further reduced by replacing the agricultural fires data in GFED with VIIRS. Numerical sensitivity experiments show that based on the improved emission inventory, the contribution of biomass burning emissions to PM2.5 concentrations in Northeast China reaches 32%, contrasting to 15% based on GFED, during the episode from November 1 to 7, 2017. Aerosol direct radiative effects from biomass burning are finally elucidated, which not only reduce downward surface shortwave radiation and planetary boundary layer height, but also affect the vertical distribution of air temperature, wind speed and relative humidity, favorable to the accumulation of PM2.5. During November 1-7, 2017, the mean daily PM2.5 enhancement due to aerosol radiative effects from VIIRS_G is 16 µg m-3, a few times higher than that of 2.8 µg m-3 from GFED. The study stresses the critical role of biomass burning, particularly of small fires easily missed in the traditional low-resolution satellite products, on air quality.