Evaluating the effects of air pollution control policies in China using a difference-in-differences approach

Revealing the impacts of the built environment factors on pedestrian-weighted air pollutant concentration using automated and interpretable machine learning

Urban air pollution poses significant health risks, especially to pedestrians due to their proximity to pollutants and lack of physical protection. Understanding the influence of built environment factors is essential to mitigate this pollution and safeguard pedestrian health. However, most existing literature focus primarily on pollutant sources and dispersion dynamics, paying less attention to the factors that affect the extent of pedestrian exposure to pollutants. Additionally, while machine learning has gained traction in urban studies, challenges remain in model optimization and interpretability, leading to limited transparency and reduced clarity in environment strategy development. To address these gaps, this study proposes a methodological framework to measure pedestrian-weighted air pollutant concentrations (PWAPC) and analyze the complex effects of the built environment. The objectives include (1) integrating air pollution and pedestrian volume data to quantify PWAPC levels, and (2) employing automated machine learning (AutoML) and interpretable machine learning (IML) to model PWAPC and evaluate key built environment impacts. A case study on PM2.5 concentrations in Central London demonstrates the efficiency of AutoML in algorithm selection and hyperparameter optimization. Using IML, critical factors such as points of interest (POIs), traffic infrastructure, diversion ratios, betweenness centrality, street canyon effects, and urban greenness are identified. The analysis also reveals non-linear relationships between these factors and PWAPC. This study provides actionable insights for urban planning and environmental management.

China's Healthy City Pilot Policy Improves Physical and Mental Health Outcomes for Middle-Aged and Older Adults: A Quasi-Natural Experiment Based on CHARLS

BACKGROUND

Rapid urbanization in China has raised significant public health concerns, particularly regarding residents' physical and mental well-being. Effective interventions are urgently needed to address these issues.

OBJECTIVE

This study evaluates the impact of China's Healthy City Pilot Policy (HCPP), introduced in 2016, on improving residents' health outcomes and examines demographic differences and mechanisms driving these effects.

METHODS

Using data from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2020, a difference-in-differences (DID) approach was employed, along with propensity score matching (PSM-DID), placebo tests, and sensitivity analyses for robust results.

RESULTS

The HCPP significantly enhanced residents' health in pilot cities, leading to better self-rated health, lower medical expenses, higher life satisfaction, and reduced depression. These benefits were most pronounced among the elderly, women, less-educated individuals, and residents of rural and central-western regions. Key mechanisms included increased physical exercise, social activities, and improved air quality.

CONCLUSION

The HCPP positively impacts urban health, especially for vulnerable groups, highlighting the urgent need to integrate health considerations into urban planning and providing valuable insights for future policy development.

Winter-spring droughts exacerbated PM2.5-O3 compound pollution? Evidence from China

With the impact of global climate change, drought events are becoming more frequent, making it critically important to quantitatively evaluate the effects of these events on air pollution. This study uses the augmented synthetic control method and the mediation effect model to quantitatively evaluate the impact effect of the winter-spring drought of 2023 on PM2.5-O3 compound pollution and its driving factors with Chinese prefecture-level city data. This study indicates that: firstly, compared to non-drought periods, both the monthly averaged and diurnal variations pattern of PM2.5 and O3 significantly increased during drought periods. Secondly, the winter-spring drought of 2023 led to an average increase of 101.05 μg/m3(28.14 %) for PM2.5 and 153.74 μg/m3(13.32 %) for O3 in Yunnan Province, while the average increases in Guizhou Province were 25.71 μg/m3(11.59 %) and 23.95 μg/m3(4.09 %), respectively. Thirdly, the increase in temperature and the decrease in precipitation and relative humidity during the winter-spring drought were among the main driving factors for the increased risk of "double-high" PM2.5-O3 compound pollution. The article expands the research on the impact of abnormal weather events on atmospheric compound pollution, providing new insights for preventing compound pollution events in the context of abnormal weather.

Policy, innovation, market or behavior driven effects: Energy green transition and environmental management in Chinese heterogeneous cities

Energy green transition (EGT) is currently one of the main measures for countries around the world to address the contradiction between economic growth and increasingly deteriorating environmental and climate issues. Cities are the center of energy consumption. The key to EGT lies in urban energy green transition. Therefore, the focus of this study is on the driving mechanism of urban EGT. Firstly, the spatial-temporal characteristic of EGT in Chinese heterogeneous cities is analyzed by using methods such as gravity model. Secondly, the possible paths includes policy driven, innovation driven, market driven, and behavior driven for urban EGT are discussed through theoretical analysis. Finally, combined with panel data of 236 Chinese cities in 2007-2022, this study empirically analyzes the complex driving mechanism of urban EGT. Results show that: (1) The EGT in Chinese cities is continuing. From the perspective of urban heterogeneous, EGT in 1-tier and 2-tier cities is significantly faster than that in 3-, 4-, and 5-tier cities. The EGT speed in eastern cities is the fastest, while that in northeastern cities is the slowest. The difficulty of EGT in energy resource-based cities is actually the greatest. From the perspective of spatial features, the spatial center of EGT in Chinese cities generally shows a changing trend from northwest to southeast. (2) Policy driven, innovation driven, market driven, and behavior driven constitute the complex driving mechanism of urban EGT, and policy driven is the primary driving force for this round of EGT. (3) Positive effect of economic development level and education level improvement on EGT in Chinese cities is significant while resource endowment and population agglomeration level exhibit significant inhibitory effects. (4) There are significant differences in the core driving force for EGT in heterogeneous cities. Both policy driven effect and market driven effect have the highest impact in 1- and 2-tier cities. Innovation driven effect, market driven effect, and behavior driven effect are only significant in eastern and central cities. In energy resource-based cities, innovation driven effect of green innovation is not significant. This study can assist government departments better in formulating relevant policies to support energy transition, promote technological innovation, design market mechanisms, and guide energy consumption behavior.

Effects of seasonal management programs on PM2.5 in Seoul and Beijing using DN-PMF: Collaborative efforts from the Korea-China joint research

South Korea and China have implemented increasingly stringent mitigation measures to reduce the health risks from PM2.5 exposure, jointly conducting a ground-based air quality observation study in Northeast Asia. Dispersion normalized positive matrix factorization (DN-PMF) was used to identify PM2.5 sources in Seoul and Beijing and assess the effectiveness of the seasonal management programs (SMPs) through a comparative study. Samples were collected during three periods: January-December 2019, September 2020-May 2021, and July 2021-March 2022. In Seoul, ten sources were resolved (Secondary nitrate: 8.67 μg/m3, 34 %, Secondary sulfate: 5.67 μg/m3, 22 %, Motor vehicle: 1.83 μg/m3, 7.2 %, Biomass burning: 2.30 μg/m3, 9.1 %, Residual oil combustion: 1.66 μg/m3, 6.5 %, Industry: 2.15 μg/m3, 8.5 %, Incinerator: 1.39 μg/m3, 5.5 %, Coal combustion: 0.363 μg/m3, 1.4 %, Road dust/soil: 0.941 μg/m3, 3.7 %, Aged sea salt: 0.356 μg/m3, 1.4 %). The SMP significantly decreased PM2.5 mass concentrations and source contributions of motor vehicle, residual oil combustion, industry, coal combustion, and biomass burning sources (p-value < 0.05). For Seoul, the reduction effects of the SMPs were evident even considering the influence of the natural meteorological variations and the responses to COVID-19. In Beijing, nine sources were resolved (Secondary nitrate: 12.6 μg/m3, 28 %, Sulfate: 8.27 μg/m3, 18 %, Motor vehicle: 3.77 μg/m3, 8.4 %, Biomass burning: 2.70 μg/m3, 6.0 %, Incinerator: 4.50 μg/m3, 10 %, Coal combustion: 3.52 μg/m3, 7.8 %, Industry: 5.01 μg/m3, 11 %, Road dust/soil: 2.92 μg/m3, 6.5 %, Aged sea salt: 1.63 μg/m3, 3.6 %). Significant reductions in PM2.5 mass concentrations and source contributions of industry, coal combustion, and incinerator (p-value < 0.05) were observed, attributed to the SMP and additional measures enforced before the 2022 Beijing Winter Olympics. Unlike comparing PM2.5 mass concentration variations using conventional methods, investigation of the source contribution variations of PM2.5 by using DN-PMF can provide a deeper understanding of the effectiveness of the air quality management policies.

Classification and Prediction of Food Safety Policy Tools in China Based on Machine Learning

Governments use policy interventions to mitigate food safety risks. Despite its crucial role, empirical studies evaluating the effectiveness of China's food safety policy tools are scarce. Drawing on a dataset encompassing 11,236 food safety policy texts from 2005 to 2021 and the incidence of problematic food products in the Eastern, Central, and Western regions of China, this study employs Latent Dirichlet Allocation (LDA) and eXtreme Gradient Boosting (XGBoost) models to facilitate the classification of policy tools and forecast the effectiveness of policy combinations. The study reveals that (1) local governments have gradually become an important supplementary maker of food safety policies, and have issued an increasing number of policy tools year by year. (2) Mandatory policy tools are predominant in number and have the highest legal hierarchy and authority levels, followed successively by guiding policy and voluntary policy tools. (3) Mandatory policy tools demonstrated the most effective intervention results, followed successively by guiding policy and voluntary policy tools. (4) The forecast analysis reveals that combinations of policies within high-growth frameworks and those driven by mandatory regulations emerge as the most effective. Therefore, the balance of policy tools in terms of type, effectiveness, and quantity, as well as their applicability in different situations, should all be taken into account.

Can low-carbon cities pilot policy promote enterprise sustainable development? Quasi-experimental evidence from China

With the predicament of sustainable improvement in traditional cities, the low-carbon city pilot policy (LCCPP), as a novel development mode, provides thinking for resolving the tensions of green development, resource conservation and environmental protection among firms. Using Chinese A-share listed companies panel data during 2007-2019, this study adopts the difference-in-differences model to explore the impact of LCCPP on firm green innovation. Based on theoretical analysis, LCCPP-driven environmental rules have the impact of encouraging business green innovation. The relationship between LCCPP and green innovation is strengthened by external media attention and organizational redundancy resources. The mechanism study shows that the incentive effect of LCCPP on firm green innovation is mainly due to the improvement of enterprises' green total factor productivity and financial stability. In addition, the heterogeneity analysis shows that the LCCPP has significantly positive effects in promoting green innovation in high-carbon industries and state-owned enterprises. This research contributes to the understanding of city-level low-carbon policies as a driving force for corporate green innovation, offering practical implications for policymakers and businesses striving for sustainability.

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.

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.

Assessing the policy benefits of constructing "Zero-waste Cities" in China: From the perspective of hazardous waste lifecycle management

Based on China's quasi-natural experiment of constructing "Zero-waste Cities", this study assessed its policy benefits on hazardous waste lifecycle management. Utilizing the theory of difference-in-differences analysis, the study quantifies the net benefits of the policy in 10 pilot cities using an average treatment effect formula, and the results indicate a reduction of 162,900 tons/year in waste generation, an increase of 2.3 % in utilization and disposal rate, and a decrease of 28,200 tons/year in end-of-pipe storage. By constructing a regression model and employing robustness tests such as changing control variables, substituting the explained variable, re-matching control groups, and random assignment of pilot sites, the study confirms that the significant policy benefits primarily lie in source reduction, with a reduction intensity of approximately 1.73 tons/100 million yuan of industrial GDP. Additionally, by applying the mixed-effects model and mediation-analysis model, the study finds that the policy benefit of source reduction exhibits a lag effect, and during the pilot period, the main approach to achieving the benefit was through enhancing cleaner production in companies rather than adjusting industrial structures in cites.

Can environmental information disclosure spur corporate green innovation?

How can the disclosure of environmental information (EID) stimulate corporate green innovation (CGI)? This research challenges the prevailing assumption that environmental regulations impact CGI by influencing corporate compliance costs. Instead, it offers a fresh theoretical framework to explain how EID affects CGI. This study combines signal theory and resource dependence theory to develop a moderated mediation model, illustrating how EID reduces information asymmetry and alleviates corporate financial constraints (CFC). To test these hypotheses, this study utilized data from A-share listed companies spanning the period 2004 to 2017. This study considered the year 2009 as a crucial point of analysis, marking the period before and after the implementation of China's first EID policy in 2008. This study employed a Difference-in-Differences (DID) model. The results reveal that EID has a positive impact on CGI by mitigating CFC, with non-state-owned enterprises (non-SOEs) exhibiting a more pronounced mediating effect. These findings remain robust even when the parallel trend assumption was tested to eliminate interference from other factors. This study unveils the mechanism through which voluntary environmental regulation, represented by EID, influences CGI by mitigating information asymmetry and alleviating CFC. These results deviate from the predictions of compliance cost theory and Porter's hypothesis regarding the impact of traditional environmental regulations on CGI, providing a fresh perspective on the role of voluntary environmental regulation in driving CGI.

The synergistic reduction effect of PM2.5 and CO2: evidence from national key ecological functional areas in China

China faces the dual pressure of haze pollution control and carbon emission reduction. The goals of national key ecological functional areas (NKEFAs) are to improve ecological quality and enhance ecological supply. In this paper, a time-varying difference-in-differences model is used to assess the impact of NKEFAs on PM2.5 and CO2 by the panel data of prefecture-level cities of China and then investigate the synergistic reduction effect. This quasi-natural experiment reveals that NKEFAs can effectively reduce both PM2.5 and CO2 and then achieve the synergistic emission reduction effect. Land use pattern optimization and productivity enhancement are identified as key drivers for promoting this synergistic effect. This effect is observed in NKEFAs of water conservation and soil conservation types, as well as in the northern region, middle and lower reaches of the Yangtze River, and southeast coastal areas of the southern region. This study provides valuable theoretical references and empirical insights for realizing a synergistic status of environmental improvement and low-carbon transformation.

Managing urban development could halve nitrogen pollution in China

Halving nitrogen pollution is crucial for achieving Sustainable Development Goals (SDGs). However, how to reduce nitrogen pollution from multiple sources remains challenging. Here we show that reactive nitrogen (Nr) pollution could be roughly halved by managed urban development in China by 2050, with NH3, NOx and N2O atmospheric emissions declining by 44%, 30% and 33%, respectively, and Nr to water bodies by 53%. While rural-urban migration increases point-source nitrogen emissions in metropolitan areas, it promotes large-scale farming, reducing rural sewage and agricultural non-point-source pollution, potentially improving national air and water quality. An investment of approximately US$ 61 billion in waste treatment, land consolidation, and livestock relocation yields an overall benefit of US$ 245 billion. This underscores the feasibility and cost-effectiveness of halving Nr pollution through urbanization, contributing significantly to SDG1 (No poverty), SDG2 (Zero hunger), SDG6 (Clean water), SDG12 (Responsible consumption and production), SDG14 (Climate Action), and so on.

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.

Measuring the urban-rural and spatiotemporal heterogeneity of the drivers of PM2.5-attributed health burdens in China from 2008 to 2021 using high-resolution dataset

Urbanization has been considered a driver of PM2.5 pollution and the attributed health burden. This study systematically measured the spatiotemporal and urban-rural heterogeneity of PM2.5-attributed health burden drivers, including income, population, baseline mortality rate, and PM2.5 level. The results reveal the significantly positive contribution of disposable income and the periodical and urban-rural differentiation of population contribution to PM2.5-attributed health burden. The difference in driver performance due to socioeconomic development and urbanization stages might be an important determinant for different or even opposite results of previous studies. Policymaking for mitigating PM2.5-attributed health risk could incorporate the re-assessment and driver determination for PM2.5-attributed health burden into the construction and development plan from the overall urbanization perspective. The urbanization-perspective driver decomposition could be synergized with the flow analysis, equality evaluation, and policy benefit estimation to achieve further direction-determining and quantitative assessment of the urban-rural PM2.5 health risk management strategies.

Iron and Steel Industry Emissions: A Global Analysis of Trends and Drivers

The iron and steel industry (ISI) is important for socio-economic progress but emits greenhouse gases and air pollutants detrimental to climate and human health. Understanding its historical emission trends and drivers is crucial for future warming and pollution interventions. Here, we offer an exhaustive analysis of global ISI emissions over the past 60 years, forecasting up to 2050. We evaluate emissions of carbon dioxide and conventional and unconventional air pollutants, including heavy metals and polychlorinated dibenzodioxins and dibenzofurans. Based on this newly established inventory, we dissect the determinants of past emission trends and future trajectories. Results show varied trends for different pollutants. Specifically, PM2.5 emissions decreased consistently during the period 1970 to 2000, attributed to adoption of advanced production technologies. Conversely, NOx and SO2 began declining recently due to stringent controls in major contributors such as China, a trend expected to persist. Currently, end-of-pipe abatement technologies are key to PM2.5 reduction, whereas process modifications are central to CO2 mitigation. Projections suggest that by 2050, developing nations (excluding China) will contribute 52-54% of global ISI PM2.5 emissions, a rise from 29% in 2019. Long-term emission curtailment will necessitate the innovation and widespread adoption of new production and abatement technologies in emerging economies worldwide.

Spatial and temporal coupling characteristics of industrial structure optimization and air quality in Chinese cities and multi-scale driver analysis

This paper takes the panel data of 283 prefecture-level cities in China from 2011 to 2020 as the research sample, measures the comprehensive index of industrial structure optimization and air quality by using GRA-TOPSIS comprehensive evaluation method, explores the spatial and temporal divergence characteristics of industrial structure optimization and air quality and the spatial and temporal evolution pattern of coupled and coordinated development by using ArcGIS spatial analysis and coupled coordination degree model, and analyzes the driving factors of coupled coordination degree of industrial structure optimization and air quality by combining multi-scale geographically weighted regression model. The study found the following: (1) The overall level of China's urban industrial structure is low, and shows an obvious eastern > central > western decreasing trend; urban air quality has a strong spatial clustering and spatial locking effect. (2) During the study period, the coupling coordination degree of industrial structure optimization and air quality showed an inverted "W" shape fluctuation from 2011 to 2020. The coupling degree and coupling coordination degree in 2020 were both higher than that in 2011, and most cities were in the run-in stage and moderate coordination stage. (3) There is a consistency in the temporal evolution trend and spatial evolution pattern of industrial structure optimization and air quality coupling degree and coupling coordination degree. (4) The driving factors are ranked according to the scale of action: public transportation intensity > population density > government intervention > GDP per capita > industrialization level. At present, China is in a critical period of promoting high-quality development by ecological civilization, and it is recommended to optimize regional industrial structure, improve urban air quality, and promote coordinated urban development.

Resource Allocation Efficiency of Urban Medical and Health Financial Expenditure Under the Background of Employees' Health

Introduction

The study proposes a method based on difference-in-differences (DID) to improve the resource allocation efficiency of medical and health financial expenditure to better guarantee the health level of enterprise employees. The DEA method is utilized to measure the comprehensive technology, pure technology, and scale as the resource allocation efficiency values of urban medical and health financial expenditure.

Methods

The proposed method includes the use of DEA to measure the resource allocation efficiency values of urban medical and health financial expenditure. The benchmark regression model and DID model are used to analyze the impact effect, robustness, and parallel trend of the policy.

Results

The study shows that the proposed method effectively evaluates and analyzes the impact of medical comprehensive reform on the resource allocation efficiency of urban medical and health financial expenditure. The comprehensive medical reform can improve the comprehensive efficiency and scale efficiency of urban medical and health financial expenditure, leading to improved resource allocation efficiency of urban employees' medical and health financial expenditure. The results also indicate a significant positive effect on the time trend, which can have a long-term impact and effectiveness.

Discussion

The proposed method can provide useful insights into the resource allocation efficiency of medical and health financial expenditure, which can help improve the health level of enterprise employees. The study suggests that comprehensive medical reform can be an effective way to improve resource allocation efficiency and guarantee the health of employees in urban areas. Further research can be conducted to evaluate the impact of medical reform on other aspects of health care, such as quality and accessibility.

Impact of the COVID-19 lockdown on typical ambient air pollutants: Cyclical response to anthropogenic emission reduction

Preliminary studies have confirmed that ambient air pollutant concentrations are significantly influenced by the COVID-19 lockdown measures, but little attention focus on the long term impacts of human countermeasures in cities all over the world during the period. Still, fewer have addressed their other essential properties, especially the cyclical response to concentration reduction. This paper aims to fill the gaps with combined methods of abrupt change test and wavelet analysis, research areas were made of five cities, Wuhan, Changchun, Shanghai, Shenzhen and Chengdu, in China. Abrupt changes in contaminant concentrations commonly occurred in the year prior to the outbreak. The lockdown has almost no effect on the short cycle below 30 d (days) for both pollutants, and a negligible impact on the cycle above 30 d. PM2.5 (fine particulate matter) has a stable short-cycle nature, which is greatly influenced by anthropogenic emissions. The analysis revealed that the sensitivity of PM2.5 to climate is increased along with the concentrations of PM2.5 were decreasing by the times when above the threshold (30-50 μg m-3), and which could lead to PM2.5 advancement relative to the ozone phase over a period of 60 d after the epidemic. These results suggest that the epidemic may have had an impact earlier than when it was known. And significant reductions in anthropogenic emissions have little impact on the cyclic nature of pollutants, but may alter the inter-pollutant phase differences during the study period.

Factors affecting recent PM2.5 concentrations in China and South Korea from 2016 to 2020

This study used observational data and a chemical transport model to investigate the contributions of several factors to the recent change in air quality in China and South Korea from 2016 to 2020. We focused on observational data analysis, which could reflect the annual trend of emission reduction and adjust existing emission amounts to apply it into a chemical transport model. The observation data showed that the particulate matter (PM_2.5) concentrations during winter 2020 decreased by -23.4 % (-14.68 μg/m³) and - 19.5 % (-5.73 μg/m³) in China and South Korea respectively, compared with that during winter 2016. Meteorological changes, the existing national plan for a long-term emission reduction target, and unexpected events (i.e., Coronavirus disease 2019 (COVID-19) in China and South Korea and the newly introduced special winter countermeasures in South Korea from 2020) are considered major factors that may affect the recent change in air quality. The impact of different meteorological conditions on PM_2.5 concentrations was assessed by conducting model simulations by fixing the emission amounts; the results indicated changes of +7.6 % (+4.77 μg/m³) and + 9.7 % (+2.87 μg/m³) in China and South Korea, respectively, during winter 2020 compared to that during winter 2016. Due to the existing and pre-defined long-term emission control policies implemented in both countries, PM_2.5 concentration significantly decreased from winter 2016-2020 in China (-26.0 %; -16.32 μg/m³) and South Korea (-9.1 %; -2.69 μg/m³). The unexpected COVID-19 outbreak caused the PM_2.5 concentrations in China to decrease during winter 2020 by another -5.0 % (-3.13 μg/m³). In South Korea, the winter season special reduction policy, which was introduced and implemented in winter 2020, and the COVID-19 pandemic may have contributed to -19.5 % (-5.92 μg/m³) decrease in PM_2.5 concentrations.

Co-benefits of the National Key Ecological Function Areas in China for carbon sequestration and environmental quality

Introduction

The National Key Ecological Functional Areas (NKEFAs) are location-oriented ecological engineering of China, which rely on the main functional area planning. The co-benefits of ecological product supply and ecological environment improvement of NKEFAs has not been fully assessed in the literature.

Methods

NKEFAs is considered a quasi-natural experiment, and the time-varying difference-in-differences (DID) model is used to assess the impact of NKEFAs on carbon sequestration (CS) and environmental quality (EQ) based on the panel data of 330 cities in China from 2001 to 2019. Then, we explore whether the co-benefits of ecological product supply and eco-environment protection can be achieved.

Results and discussion

NKEFAs can enhance CS and EQ and thus achieve co-benefits for both. NKEFAs can achieve the co-benefits of CS and EQ through territory spatial allocation and labor force aggregation, but industrial structure upgrading only positively mediates the impact of NKEFAs on CS. The co-benefits of CS and EQ are heterogeneous across functional area types, geospatial locations, and quantiles, while only CS at windbreak-sand fixation area, northwestern region, and low quantile regions is enhanced. This study makes a theoretical and methodological contribution to the existing literature on the policy effect assessment of ecological engineering. It also provides a comprehensive framework for evaluating the ecological effects of relevant policies in other countries by integrating the co-benefits of ecological products and eco-environment, analyzing regional heterogeneity, and exploring the underlying mechanisms.

Impacts of industrial agglomeration on industrial pollutant emissions: Evidence found in the Lanzhou-Xining urban agglomeration in western China

Industrial agglomeration does not only promote economic and social prosperity of urban agglomeration, but also increases industrial pollution, which poses a health risk to the general public. The Lanzhou-Xining urban agglomeration in western China is characterized by industrial agglomeration and serious industrial pollution. Based on the county panel data of the Lanzhou-Xining urban agglomeration in western China from 2010 to 2018, a research of the impacts of industrial agglomeration on industrial pollutant emissions was conducted by using spatial analysis technology and spatial econometric analysis. The results indicate that industrial agglomeration is an important factor leading to an increase in industrial pollutant emissions. In addition, population density, economic level, and industrial structure are also important factors that lead to the increase in industrial pollutant emissions. However, technological level has led to the reduction in industrial pollutant emissions. Furthermore, industrial pollutant emissions are not only affected by the industrial agglomeration, population density, economic level, industrial structure, and technological level of the county but also by those same factors in the surrounding counties, owing to the spatial spillover effect. Joint development of green industries and control of industrial pollutant emissions is an inevitable result for the Lanzhou-Xining urban agglomeration in western China.