Air Pollution Control Policies Research Articles

The impact of environmental regulation on firms’ markups: evidence from China

ABSTRACT A comprehensive evaluation of the costs and benefits of environmental regulations provides empirical evidence for policymakers to formulate and introduce environmental policies. Firms’ profitability and competitiveness manifest their market power and provide the micro foundation for economic development and social stability. Therefore, this paper focus on investigating the impact of air pollution environmental regulation on manufacturing firms’ market power, measured by markups, with a difference-in-differences (DID) method. Using air pollution control policy, requiring China’s Key Cities for Air Pollution Control (KCAPC) to meet air quality standards within a specified time limit as a natural experiment, our DID estimations show that air pollution regulation significantly leads to an increase in firms’ markup rate by 0.002 in key cities that did not meet air quality standards. Heterogeneous effects show that this impact is larger for polluting firms, private-owned and foreign-owned firms, and firms located in western and central cities and cities with high marketization. Productivity and market share may be two main influencing channels to explain the positive impact of air pollution environmental regulation on firms’ markups. Our findings suggest that strengthening environmental regulation is conducive to improving the competitiveness and market power of manufacturing firms, lending support to the enforcement of environmental regulations.

Air pollution control and carbon reduction policies: Assessing effectiveness in alleviating PM2.5-associated mortality in China

To confront the challenges posed by air pollution and climate change, China has undertaken significant initiatives to develop strategies that address both issues concurrently. However, the health benefits of these initiatives have not been clearly articulated. In this study, the dynamic changes in health impacts under air pollution and carbon reduction actions in China are evaluated by employing the latest concentration–response models and projected PM2.5 concentrations under future scenarios. From 2020 to 2060, the enforcement of clean air and climate mitigation policies is expected to increase the percentage of the population living with PM2.5 concentrations meeting the 10 μg/m3 standard by 79 %. Without the implementation of relevant mitigation measures, PM2.5-associated deaths are projected to double due to an aging population. In comparison to the 2060 reference scenario, the joint implementation of clean air and carbon neutrality measures is expected to reduce nationwide PM2.5-associated mortality by 62 %, equivalent to 2.15 (95 % CI: 1.80–2.48) million deaths. Stringent pollution controls are crucial for reducing PM2.5-associated deaths before 2030, after which carbon neutrality actions become increasingly significant from 2030 to 2060. The challenges of mitigating future PM2.5-associated deaths vary greatly across regions, showing a critical response to pollution control and carbon reduction. The research proves the effectiveness of China's future air pollution control and carbon reduction policies in mitigating PM2.5-associated deaths.

Daily scale air quality index forecasting using bidirectional recurrent neural networks: Case study of Delhi, India

This research was established to accurately forecast daily scale air quality index (AQI) which is an essential environmental index for decision-making. Researchers have projected different types of models and methodologies for AQI forecasting, such as statistical techniques, machine learning (ML), and most recently deep learning (DL) models. The modelling development was adopted for Delhi city, India which is a major city with air pollution issues simialir to entire urban cities of India especially during winter seasons. This research was predicted AQI using different versions of DL models including Long-Short Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM) and Bidirectional Recurrent Neural Networks (Bi-RNN) in addition to Kernel Ridge Regression (KRR). Results indicated that Bi-RNN model consistently outperformed the other models in both training and testing phases, while the KRR model consistently displayed the weakest performance. The outstanding performance of the models development displayed the requirement of adequate data to train the models. The outcomes of the models showed that LSTM, BI-LSTM, KRR had lower performance compared with Bi-RNN models. Statistically, Bi-RNN model attained maximum cofficient of determination (R2 = 0.954) and minimum root mean square error (RMSE = 25.755). The proposed model in this research revealed the robust predictable to provide a valuable base for decision-making in the expansion of combined air pollution anticipation and control policies targeted at addressing composite air pollution problems in the Delhi city.

Challenges and perspectives of air pollution control in China

Air pollution is one of the most challenging environmental issues in the world. China has achieved remarkable success in improving air quality in last decade as a result of aggressive air pollution control policies. However, the average fine particulate matter (PM2.5) concentration in China is still about six times of the World Health Organization (WHO) Global Air Quality Guidelines (AQG) and causing significant human health risks. Extreme emission reductions of multiple air pollutants are required for China to achieve the AQG. Here we identify the major challenges in future air quality improvement and propose corresponding control strategies. The main challenges include the persistently high health risk attributed to PM2.5 pollution, the excessively loose air quality standards, and coordinated control of air pollution, greenhouse gases (GHGs) emissions and emerging pollutants. To further improve air quality and protect human health, a health-oriented air pollution control strategy shall be implemented by tightening the air quality standards as well as optimizing emission reduction pathways based on the health risks of various sources. In the meantime, an “one-atmosphere” concept shall be adopted to strengthen the synergistic control of air pollutants and GHGs and the control of non-combustion sources and emerging pollutants shall be enhanced.

Exploring role-playing as a tool for involving citizens in air pollution mitigation urban policies

The design of air pollution control policies is a complex decision-making process. Public participation can enhance the legitimacy and effectiveness of environmental urban regulations but does not always occur naturally. This article presents the experience of the use of role-playing in six mid-sized cities in southern Chile to evaluate how residents affected by high concentrations of fine particulate matter perceive the problem and debate possible solutions. For this, the participants were asked to assume the role of advisors. On that premise, they had to prioritize between a series of mitigation measures and reach a consensus with other advisors. The results show the potential of role-playing games, on the one hand, to promote critical thinking and argument skills among the general public and, on the other, to help policymakers in the design of more operative and fair plans of action.

Unveiling global land fine- and coarse-mode aerosol dynamics from 2005 to 2020 using enhanced satellite-based monthly inversion data

Accurate fine-mode and coarse-mode aerosol knowledge is crucial for understanding their impacts on the climate and Earth's ecosystems. However, current satellite-based Fine-Mode Aerosol Optical Depth (FAOD) and Coarse-Mode Aerosol Optical Depth (CAOD) methods have drawbacks including inaccuracies, low spatial coverage, and limited temporal duration. To overcome these issues, we developed new global-scale FAOD and CAOD from 2005 to 2020 using a novel deep learning model capable of the synergistic retrieval of two aerosol sizes. After validation with the aerosol robotic network (AERONET) and sky radiometer network (SKYNET), the new monthly FAOD and CAOD showed significant improvements in accuracy and spatial coverage. From 2005 to 2020, the new data showed that China had the greatest decrease in FAOD and CAOD. In contrast, India and South Latin America had a significant increase in FAOD versus North Africa in CAOD. FAOD in the regions of Argentina, Paraguay, and Uruguay in South America have shown an upward trend. The results reveal that FAOD and CAOD display distinct patterns of change in the same regions, particularly on the west coast of the United States where FAOD is increasing, while CAOD is decreasing. Aside from the year 2020 due to the global COVID-19 pandemic, the analysis showed that although China has seen at least an +85% increase in energy consumption and urban expansion in 2019 compared to 2005 due to the needs of development and construction, the implementation of China's air pollution control policies has led to a significant decrease in FAOD (−46%) and CAOD (−65%) after 2013. This research enriches our comprehension of global fine and coarse aerosol patterns, additional investigations are needed to determine the potential global implications of these changes.

Vertical Profiles of Aerosols Induced by Dust, Smoke, and Fireworks in the Cold Region of Northeast China

Despite the long-term implementation of air pollution control policies in northeast China, severe haze pollution continues to occur frequently. With the adoption of a megacity (Changchun) in northeast China, we analysed the vertical characteristics of aerosols and the causes of aerosol pollution throughout the year using multisource data for providing recommendations for controlling pollution events (i.e., straw burning and fireworks). Based on a ground-based LiDAR, it was found that the extinction coefficient (EC) of aerosols at a height of 300 m in Changchun was highest in winter (0.44 km−1), followed by summer (0.28 km−1), with significant differences from those in warmer regions, such as the Yangtze River Delta. Therefore, it is recommended that air pollution control policies be differentiated between winter and summer. On Chinese New Year’s Eve in Changchun, the ignition of firecrackers during the day and night caused increases in the EC at a height of 500 m to 0.37 and 0.88 km−1, respectively. It is suggested that the regulation of firecracker ignition should be reduced during the day and strengthened at night. Based on the CALIPSO and backward trajectory analysis results, two events of dust–biomass-burning composite pollution were observed in March and April. In March, the primary aerosol component was dust from western Changchun, whereas in April, the main aerosol component was biomass-burning aerosols originating from northern and eastern Changchun. Hence, reducing the intensity of spring biomass burning can mitigate the occurrence of dust–biomass-burning composite pollution. These findings can provide emission policy suggestions for areas facing similar issues regarding biomass-burning transmission pollution and firework emissions.

Advancing nuanced pollution control: Local improvements and spatial spillovers of policies on key enterprises

This paper examines the impact of air pollution control policies targeting key polluting enterprises, highlighting a strategic shift towards precision pollution control that concentrates on high-emission, high-risk businesses. The paper explores the efficacy of these policies and their potential spatial spillover effects, utilizing panel data from 259 Chinese cities from 2013 to 2021. Employing the difference-in-differences (DID) model and spatial Durbin model, the study analyzes both the direct local effects and the broader spatial consequences of these regulatory measures on air quality. The findings indicate a significant reduction in air pollutant concentrations in urban areas, attributing this improvement to factors such as industrial restructuring, increased investment in science and technology, and economic growth. Spatial econometric analysis further reveals a substantial positive correlation in air quality among Chinese cities. However, estimates of the spillover effect indicate that while such policies successfully reduce pollution locally, they could unintentionally degrade air quality in adjacent areas. The study highlights the need for nuanced policy strategies to mitigate unintended spatial spillovers and enhance overall effectiveness. It recommends tailored policies that integrate environmental and socioeconomic objectives, national and regional coordination for consistent enforcement, technology-driven compliance strategies, and incentives for sustainable enterprise practices.

Assessment of CO2 Co-benefits of Air Pollution Control Policies in Taiyuan's 14th Five-Year Plan

To quantitatively evaluate the co-benefits of air pollution reduction and carbon dioxide reduction of Taiyuan's 14th Five-Year Plan air pollution prevention and control policies, this study used the Beijing-Tianjin-Hebei Greenhouse Gas-Air Pollution Interaction and Synergy Model (GAINS-JJJ) to simulate and evaluate the emission reduction potential and CO2 co-benefit of 13 air pollution control measures. The emission reductions of PM2.5, PM10, SO2, NOx, VOCs, and NH3 in 2025 were 1.8 (5%, compared with that in the baseline scenario), 2.5 (2%), 3.7 (16%), 20.0 (27%), 13.6 (15%), and 0.0 kt (0%), respectively. The reduction in CO2 emissions was 9.0 Mt (13%), whereas CH4 emissions increased by 203.3 kt (25% increase relative to that in the baseline scenario). SO2, NOx, and VOCs emission reductions derived from the power, industrial combustion, and solvent use sectors. CO2 reduction occurred mainly in the industrial combustion sector, and CH4 emission increased mainly due to the increase in coal mining activity. The highest synergistic CO2 reductions were achieved by restricting energy consumption in the high energy-consuming and high-emitting sectors; prohibiting new capacity in the steel, coke, cement, and flat glass industries; and replacing coal-fired power generation with renewable energy. Furthermore, the CO2 reduction co-benefit was highest for VOCs. In addition, this study suggests that promoting the policy of terminal electrification and simultaneously increasing the share of clean energy and the ability to consume renewable energy generation in the power sector are the keys to decreasing the emissions in Taiyuan.

Impact of comprehensive air pollution control policies on six criteria air pollutants and acute myocardial infarction morbidity, Weifang, China: A quasi-experimental study

Comprehensive air pollution control policies may reduce pollutant emissions. However, the impact on disease morbidity of the change for the concentration of air pollutants following the policies has been insufficiently studied. We aim to assess the impact of comprehensive air pollution control policies on the levels of six criteria air pollutants and acute myocardial infarction (AMI) morbidity in Weifang, China. This study performed an interrupted time series analysis. The linear model with spline terms and generalized additive quasi-Poisson model were used to estimate the immediate change from 2016 to 2019 in the daily concentration of six air pollutants (PM2.5, PM10, SO2, NO2, O3, and, CO) and AMI incident cases (Age ≥35) associated with the implementation of air pollution control policies in Weifang, respectively. After the implementation of air pollution control policies, air quality in Weifang had been improved. Specifically, the daily concentrations of PM2.5, PM10, SO2, and, CO immediately decreased by 27.9 % (95 % CI: 6.6 % to 44.3 %), 32.9 % (95 % CI: 17.5 % to 45.5 %), 14.6 % (95 % CI: 0.4 % to 26.8 %), and 33.9 % (95 % CI: 22.0 % to 44.0 %), respectively. In addition, the policies implementation was also associate with the immediate decline in the AMI morbidity (−6.5 %, 95 % CI: −10.4 % to −2.3 %). And subgroup analyses indicate that the health effects of the policy intervention were only observed in female (−9.4 %, 95 % CI: −14.4 % to −4.2 %) and those aged ≥65 years (−10.5 %, 95 % CI: −14.6 % to −6.2 %). During the final 20 months of the study period, the policy intervention was estimated to prevent 1603 (95 % CI: 574 to 2587) cases of incident AMI in Weifang. Our results provide strong rationale that the policy intervention significantly reduced ambient pollutant concentrations and AMI morbidity, which highlighted the importance for a comprehensive and rigorous air pollution control policy in regions with severe air pollution.

Spatial–temporal distribution patterns and influencing factors analysis of comorbidity prevalence of chronic diseases among middle-aged and elderly people in China: focusing on exposure to ambient fine particulate matter (PM2.5)

ObjectiveThis study describes regional differences and dynamic changes in the prevalence of comorbidities among middle-aged and elderly people with chronic diseases (PCMC) in China from 2011–2018, and explores distribution patterns and the relationship between PM2.5 and PCMC, aiming to provide data support for regional prevention and control measures for chronic disease comorbidities in China.MethodsThis study utilized CHARLS follow-up data for ≥ 45-year-old individuals from 2011, 2013, 2015, and 2018 as research subjects. Missing values were filled using the random forest machine learning method. PCMC spatial clustering investigated using spatial autocorrelation methods. The relationship between macro factors and PCMC was examined using Geographically and Temporally Weighted Regression, Ordinary Linear Regression, and Geographically Weighted Regression.ResultsPCMC in China showing a decreasing trend. Hotspots of PCMC appeared mainly in western and northern provinces, while cold spots were in southeastern coastal provinces. PM2.5 content was a risk factor for PCMC, the range of influence expanded from the southeastern coastal areas to inland areas, and the magnitude of influence decreased from the southeastern coastal areas to inland areas.ConclusionPM2.5 content, as a risk factor, should be given special attention, taking into account regional factors. In the future, policy-makers should develop stricter air pollution control policies based on different regional economic, demographic, and geographic factors, while promoting public education, increasing public transportation, and urban green coverage.

Effects of China's Clean Air Act on Frailty Levels Among Middle-Aged and Older Adults: A Population-Based Quasi-Experimental Study.

Air pollution is a frailty risk factor, yet the frailty-related health benefits of China's air pollution control policy, the Clean Air Action (CCAA), are unclear. Frailty progression and transitions differ among robust, prefrail, and frail adults. This study aimed to evaluate the CCAA's effect on frailty levels among robust, prefrail, and frail Chinese adults. Using propensity score matching with difference-in-differences analysis, we studied 9788 adults aged ≥45 from the 2011 and 2018 China Health and Retirement Longitudinal Study. The Frailty Index (FI), summarizing 32 health deficits, quantifies frailty level (range: 0-1 scores). Frailty was defined as FI ≥ 0.25, prefrailty as FI 0.10-0.25, and robust as FI ≤ 0.10. We examined frailty transitions between these states (robust, prefrail, and frail) from 2011 to 2018. Based on provincial particulate matter reduction targets, participants were assigned to intervention (>10% reduction) or control (≤10%) groups and categorized as robust, prefrail, or frail pre-CCAA implementation. The CCAA significantly reduced FI scores among preimplementation robust individuals by 0.0205 and among prefrail individuals by 0.0114, with no significant changes in frail individuals. Frailty transition analyses confirmed specific benefits of the CCAA, which significantly reduced worsening from robust to prefrail or frail by 7.0% and prefrail to frail by 3.9%. However, it did not facilitate the improvement from frail to prefrail/robust or from prefrail back to robust. No significant subgroup differences were observed across age, gender, Hukou, education, and social participation. CCAA has been associated with a reduction in frailty deterioration in robust and prefrail populations.

Interplay of Climate Change and Air Pollution- Projection of the under-5 mortality attributable to ambient particulate matter (PM2.5) in South Asia

Ambient fine particulate matter (PM2.5) pollution is a leading health risk factor for children under- 5 years, especially in developing countries. South Asia is a PM2.5 hotspot, where climate change, a potential factor affecting PM2.5 pollution, adds a major challenge. However, limited evidence is available on under-5 mortality attributable to PM2.5 under different climate change scenarios. This study aimed to project under-5 mortality attributable to long-term exposure to ambient PM2.5 under seven air pollution and climate change mitigation scenarios in South Asia. We used a concentration-risk function obtained from a previous review to project under-5 mortality attributable to ambient PM2.5. With a theoretical minimum risk exposure level of 2.4 μg/m3, this risk function was linked to gridded annual PM2.5 concentrations from atmospheric modeling to project under-5 mortality from 2010 to 2049 under different climate change mitigation scenarios. The scenarios were developed from the Aim/Endues global model based on end-of-pipe (removing the emission of air pollutants at the source, EoP) and 2 °C target measures. Our results showed that, in 2010–2014, about 306.8 thousand under-5 deaths attributable to PM2.5 occurred in South Asia under the Reference (business as usual) scenario. The number of deaths was projected to increase in 2045–2049 by 36.6% under the same scenario and 7.7% under the scenario where EoP measures would be partially implemented by developing countries (EoPmid), and was projected to decrease under other scenarios, with the most significant decrease (81.2%) under the scenario where EoP measures would be fully enhanced by all countries along with the measures to achieve 2 °C target (EoPmaxCCSBLD) across South Asia. Country-specific projections of under-5 mortality varied by country. The current emission control strategy would not be sufficient to reduce the number of deaths in South Asia. Robust climate change mitigation and air pollution control policy implementation is required.

Research on the spatial and temporal patterns of ozone concentration and population health effects in the Central Plains Urban Agglomeration from 2017 to 2020.

Fine particulate matter (PM2.5) and near-surface ozone (O3) are the main atmospheric pollutants in China. Long-term exposure to high ozone concentrations adversely affects human health. It is of great significance to systematically analyze the spatiotemporal evolution mechanism and health effects of ozone pollution. Based on the ozone data of 91 monitoring stations in the Central Plains Urban Agglomeration from 2017 to 2020, the research used Kriging method and spatial autocorrelation analysis to investigate the spatiotemporal variations of ozone concentration. Additionally, the study assessed the health effects of ozone on the population using the population exposure risk model and exposure-response relationship model. The results indicated that: (1) The number of premature deaths caused by ozone pollution in the warm season were 37,053 at 95% confidence interval (95% CI: 28,190-45,930) in 2017, 37,685 (95% CI: 28,669-46,713) in 2018, and 37,655 (95% CI: 28,647-46,676) in 2019. (2) The ozone concentration of the Central Plains urban agglomeration showed a decreasing trend throughout the year and during the warm season from 2017 to 2020, there are two peaks monthly, one is June, and the other is September. (3) In the warm season, the high-risk areas of population exposure to ozone in the Central Plains Urban Agglomeration were mainly concentrated in urban areas. In general, the population exposure risk of the south is lower than that of the north. The number of premature deaths attributed to ozone concentration during the warm season has decreased, but some southern cities such as Xinyang and Zhumadian have also seen an increase in premature deaths. China has achieved significant results in air pollution control, but in areas with high ozone concentrations and high population density, the health burden caused by air pollution remains heavy, and stricter air pollution control policies need to be implemented.

Adaptive Governance or Status Quo? Unpacking the City of Jakarta's Approach to the Air Pollution Control Program

In recent years, Jakarta has experienced an increase in air pollution which has the potential to have a significant impact on Jakarta residents not only in terms of health, but socio-cultural and productivity. This encourages the need for effective governance strategies to overcome air pollution problems. This study seeks to critically analyze the approach used by the city of Jakarta in dealing with air pollution to find out whether the city of Jakarta's air pollution control policy has led to innovative, flexible and adaptive governance, or is still more inclined towards maintaining the status quo. Based on qualitative data, including in-depth interviews, policy analysis, and consultation with stakeholders, this research examines Jakarta's policy mechanisms, community participation pathways, and inter-agency coordination in controlling air quality and dealing with pollution. The research results show a lack of alignment between progressive policy frameworks and implementation challenges, thus underscoring the need for a more adaptive and dynamic approach. The approach adopted in Jakarta appears to be dominated by a top-down, government-led model, where policies and decisions are primarily formulated and implemented with minimal participation from non-governmental institutions. Such models, while ensuring efficient decision making, may exclude valuable insights of other stakeholders and hinder innovative and context-specific solutions. Additionally, these rigid structures appear to lack the flexibility and responsiveness that are hallmarks of adaptive governance, potentially reducing cities' ability to effectively address air pollution challenges. This research underscores the need for a more inclusive and adaptive governance framework in managing air pollution in Jakarta.

UNRAVELING COMORBIDITY PREVALENCE AND PM2.5 EXPOSURE AMONG MIDDLE-AGED AND ELDERLY: A SPATIAL-TEMPORAL ANALYSIS

Abstract Objective This study describes regional differences and dynamic changes in the prevalence of comorbidities among middle-aged and elderly people with chronic diseases (PCMC) in China from 2011-2018, and explores distribution patterns and the relationship between PM2.5 and PCMC, aiming to provide data support for regional prevention and control measures for chronic disease comorbidities in China. Methods This study utilized CHARLS follow-up data for ≥45-year-old individuals from 2011, 2013, 2015, and 2018 as research subjects. Missing values were filled using the random forest machine learning method. PCMC spatial clustering investigated using spatial autocorrelation methods. The relationship between macro factors and PCMC was examined using Geographically and Temporally Weighted Regression, Ordinary Linear Regression, and Geographically Weighted Regression. Results PCMC in China showing a decreasing trend. Hotspots of PCMC appeared mainly in western and northern provinces, while cold spots were in southeastern coastal provinces. PM2.5 content was a risk factor for PCMC, the range of influence expanded from the southeastern coastal areas to inland areas, and the magnitude of influence decreased from the southeastern coastal areas to inland areas. Conclusion PM2.5 content, as a risk factor, should be given special attention, taking into account regional factors. In the future, policy-makers should develop stricter air pollution control policies based on different regional economic, demographic, and geographic factors, while promoting public education, increasing public transportation, and urban green coverage.

Structural equation modeling of the combined effect of urban population, gross regional product and area on air pollution in selected Chinese cities

Expansion of urban scale, including the growth of population, gross regional product and city area, have led to an increase in the city's air pollution. Previous research has often emphasized the adverse effect of urban scale on air pollution levels through the expansion of residents' activities. However, the expansion of urban scale can also induce the green technological innovation and change in the industry structure via the effect of agglomeration, thus leading to reduction of air pollution to some extent. Association mechanisms between urban scale and air pollution are complex and poorly understood. In this context, this study aims to identify the combined effects of urban scale on air pollution through residents' activities, industry structure and technique impact in 292 selected Chinese cities from 2015 to 2020, using the structural equation modeling. Results suggested that the expansion of urban scale had a positive impact on air pollution levels through residents' activities (average impact coefficient: 0.509). But urban scale promoted the impact of green technological innovation and optimization in the industry structure, causing a decrease in air pollution levels. The average impact coefficients of urban scale on air pollution levels through technique impact and industry structure were −0.202 and −0.018, respectively. Furthermore, the multiple-group analysis found that with the growth of urban population, there was an increase in the association strength of urban scale on air pollution via technique impact, while there was a great deal of difference for the industry structure. Findings from this study can contribute to a more comprehensive understanding of the impact of urban scale on air pollution, which will provide a theoretical basis for air pollution prevention and control policies.

Is air pollution joint prevention and control effective in China-evidence from "Air Pollution Prevention and Control Action Plan".

This paper examined the effect of air pollution joint prevention and control on pollution emissions in China. Specifically, based on the panel data of 290 cities from 2007 to 2021, taking the implementation of the "Air Pollution Prevention and Control Action Plan" as a natural experiment, the difference-in-difference-in-difference (DDD) model was used to explore the effect of air pollution joint prevention and control on haze pollution. Results show that air pollution joint prevention has a significant impact on pollutant emissions either as a whole or as a single pollutant. In terms of individual urban agglomeration, whether the Yangtze River Delta or the Pearl River Delta urban agglomerations, the air pollution joint prevention and control policy has a significant impact not only on the overall reduction of pollutant emissions but also on the reduction of single PM2.5 or industrial sulfur dioxide emissions alone. Environmental regulations have also achieved the effect of haze control in general and have a significant impact on the reduction of PM2.5 or industrial sulfur dioxide emissions. Environmental regulations also significantly reduced PM2.5 emissions in these three urban agglomerations. These findings provide a scientific basis and essential reference for understanding the implementation effect of regional joint prevention and control policies comprehensively and objectively.

Comprehensive Evaluation of Spatial Distribution and Temporal Trend of NO2, SO2 and AOD Using Satellite Observations over South and East Asia from 2011 to 2021

The past decade has witnessed remarkable economic development, marked by rapid industrialization and urbanization across Asian regions. This surge in economic activity has led to significant emissions, resulting in alarming levels of air pollution. Our study comprehensively assessed the spatial and temporal trends of key pollutants, namely nitrogen dioxide (NO2), sulfur dioxide (SO2), and aerosol (using aerosol optical depth (AOD) at 550 nm as an indicator), from 2011 to 2021. The data sources utilized include OMI onboard the Aura satellite for NO2 and SO2, as well as MODIS onboard Terra and Aqua satellites for AOD. The results from spatial and temporal trend analyses of the three parameters show that there is a clear declining trend over China and Republic of Korea (e.g., NO2 is declining with an overall rate of −7.8 × 1012 molecules/cm2/year over China) due to the strict implementation of air pollution control policies. However, it is essential to note that both countries still grapple with substantial pollution levels, with proportions exceeding 0.5, indicating that air quality is improving but has not yet reached a safe threshold. In contrast, South Asian regions, including Bangladesh, Pakistan, and India, are experiencing an increasing trend (e.g., NO2 is increasing with an overall rate of 1.2 × 1012 molecules/cm2/year in Bangladesh), primarily due to the lack of rigorous air pollution control policies. The average emissions of NO2 and SO2 were remarkably higher in winter than in summer. Notably, the identified hotspots are statistically significant and predominantly coincide with densely populated areas, such as the North China Plain (NCP). Furthermore, this study underscores the pivotal role of sector-wise emissions in air quality monitoring and improvement. Different cities are primarily influenced by emissions from specific sectors, emphasizing the need for targeted pollution control measures. The findings presented in this research contribute valuable insights to the air quality monitoring and improvement efforts in East and South Asian regions.

Traceability of atmospheric ammonia in a suburban area of the Beijing-Tianjin-Hebei region

Ammonia (NH3) is one of the most important sources that have been linked to the formation of PM2.5. Therefore, it is important to study the source contributions to atmospheric NH3 for air pollution control. Here we used 15N natural abundance (expressed by δ15N) values to quantify the source contributions to atmospheric NH3 in the Beijing-Tianjin-Hebei (BTH) region, which suffers from the country's worst air pollution. Results showed that from 2017 to 2019, the annual mean δ15N-NH3 value at the livestock site (−27.5 ± 6.0 ‰) was lower than at cropland (−20.7 ± 6.0 ‰) and rural residential sites (−22.1 ± 7.4 ‰), while their concentrations were the opposite. Seasonal mean δ15N-NH3 values were the highest in winter and lowest in summer, whereas monthly mean δ15N-NH3 values were the highest in January and lowest in June. The isotope mixing model results showed that agricultural sources account for 64.5 ± 13.5 % of year-round total NH3 emissions, while industrial and other sources contributed 27.4 and 8.1 %, respectively. However, the contribution of industrial sources was higher than that of agricultural sources in January. Our results indicated that the contribution of agricultural sources has decreased after the implementation of air pollution control policies in this region suggesting that NH3 abatement from agricultural sources is effective. However, further refinement of agricultural emission abatement measures will be required, accompanied by a greater focus on controlling winter non-agricultural sources.