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Particulate matter with an aerodynamic diameter of less than 1 μm (PM 1.0 ) can be extremely hazardous to human health, so it is imperative to accurately estimate the spatial and temporal distribution of PM 1.0 and analyze the impact of related policies on it. In this study, a stacking generalization model was trained based on aerosol optical depth (AOD) data from satellite observations, combined with related data affecting aerosol concentration such as meteorological data and geographic data. Using this model, the PM 1.0 concentration distribution in China during 2016-2019 was estimated, and verified by comparison with ground-based stations. The coefficient of determination (R 2 ) of the model is 0.94, and the root-mean-square error (RMSE) is 8.49 μg/m 3 , mean absolute error (MAE) is 4.10 μg/m 3 , proving that the model has a very high performance. Based on the model, this study analyzed the PM 1.0 concentration changes during the heating period (November and December) in the regions where the "coal-to-gas" policy was implemented in China, and found that the proposed "coal-to-gas" policy did reduce the PM 1.0 concentration in the implemented regions. However, the lack of natural gas due to the unreasonable deployment of the policy in the early stage caused the increase of PM 1.0 concentration. This study can provide a reference for the next step of urban air pollution policy development., Competing Interests: Declaration of competing interest Dear editors, all the authors (Tianqi Shi, Yanran Peng, Xin Ma, Ge Han, Zhipeng Pei, Siwei Li, Huiqin Mao, Xingying Zhang, Wei Gong) declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Volatile organic compounds (VOCs) significantly contribute to ozone pollution formation, and many VOCs are known to be harmful to human health. Plastic has become an indispensable material in various industries and daily use scenarios, yet the VOC emissions and associated health risks in the plastic manufacturing industry have received limited attention. In this study, we conducted sampling in three typical plastic manufacturing factories to analyze the emission characteristics of VOCs, ozone formation potential (OFP), and health risks for workers. Isopropanol was detected at relatively high concentrations in all three factories, with concentrations in organized emissions reaching 322.3 μg/m 3 , 344.8 μg/m 3 , and 22.6 μg/m 3 , respectively. Alkanes are the most emitted category of VOCs in plastic factories. However, alkenes and oxygenated volatile organic compounds (OVOCs) exhibit higher OFP. In organized emissions of different types of VOCs in the three factories, alkenes and OVOCs contributed 22.8%, 67%, and 37.8% to the OFP, respectively, highlighting the necessity of controlling them. The hazard index (HI) for all three factories was less than 1, indicating a low non-carcinogenic toxic risk; however, there is still a possibility of non-cancerous health risks in two of the factories, and a potential lifetime cancer risk in all of the three factories. For workers with job tenures exceeding 5 years, there may be potential health risks, hence wearing masks with protective capabilities is necessary. This study provides evidence for reducing VOC emissions and improving management measures to ensure the health protection of workers in the plastic manufacturing industry., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Black carbon (BC) significantly affects climate, environmental quality, and human health. This study utilised Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), which can compensate for the shortcomings of ground BC monitoring in spatial-temporal distribution to study the pollution characteristics of BC and potential pollution sources in a typical industrial city (Xinxiang) with serious air pollution in northern China. The results showed that average daily ground observation and MERRA-2 concentration of BC of 7.33 μg m -3 and 9.52 μg m -3 . The mean BC concentration derived from MERRA-2 reanalysis data was higher than ground measurement due to resolution limitations and pollution from the northern regions. The reliability of the MERRA-2 data was confirmed through correlation analysis. Consideration of the spatial distribution of BC from MERRA-2 and incorporating the potential source contribution function (PSCF), concentration-weighted trajectory (CWT), and emission inventory, other possible source areas and primary sources of BC in Xinxiang were investigated. The results indicated that implementing transportation and residential emission control measures in Henan Province and its surrounding provinces, such as Hebei Province, will effectively decrease the BC level in Xinxiang City. A passively smoked cigarettes model was used to evaluate the risk of BC exposure. The percentage of lung function decrement (PLFD) was the highest in school-age children, while the impact on lung cancer (LC) health risk was comparatively lower. Notably, the BC health risk in Xinxiang was lower than in most cities across Asia., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Spatial misallocation of resource elements impedes the coordination in regional co-benefit in carbon emission and pollution reduction. Guided by scope economy principles, this study aims to quantifies co-benefits and explores spatial variation patterns to facilitate mutual synergy. The findings offer valuable insights for identifying optimal focus points and shaping targeted collaborative policies. Based on the multi-source provincial panel data spanning 2000 to 2021, this paper quantitatively assesses the co-benefit through the lens of marginal abatement cost. Then, the Dagum Gini coefficient was employed to investigate the disparities at the spatial level. Additionally, geographical detector is introduced to analyze the source of disparities at the factor level. Results indicate: (1) Under joint reduction, the marginal abatement cost reduces by 57.86% and 79.97% respectively, with an overall 68.77% increase in co-benefit fluctuation. (2) Provinces with low co-benefit significantly decreased after 2007, while provinces with high co-benefit concentrated in the northwest, southwest, and east. (3) Overall disparities decreased, east-central regions hold the lowest spatial disparities in co-benefit and east-west hold the most; intragroup differences and supervariable density primarily contributes to the disparity. (4) FDI significantly influence the co-benefit over the past two decades, with spatial disparities influenced by both endogenous and exogenous factors across development stages., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Polycyclic aromatic hydrocarbons (PAHs) are of significant public concern because of their toxicity and long-range transport potential. Extensive studies have been conducted to explore the source-receptor relationships of PAHs via atmospheric transport. However, the transfer of trade-driven regional and global PAHs is poorly understood. This study estimated the virtual PAHs emission transfer embodied in global trade from 2004 to 2014 and simulated the impact of international trade on global contamination and associated human inhalation exposure risk of PAHs. Results show that trade-driven PAHs flowed primarily from developed to less-developed regions, particularly in those regions with intensive heavy industries and transportation. As the result, international trade resulted in an increasing risk of lung cancer induced by exposure to PAHs (27.8% in China, 14.7% in India, and 11.3% in Southeast Asia). In contrast, we found decreasing risks of PAHs-induced lung cancer in Western Europe (63.2%) and the United States (45.9%) in 2004. Our findings indicate that final demand and emission intensity are the key driving factors contributing to rising and falling consumption-based PAHs emissions and related health risk respectively. The results could provide a useful reference for global collaboration in the reduction of PAHs pollution and related health risks., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Artificial intelligence (AI) technology represents a disruptive innovation that has garnered significant interest among researchers for its potential applications in ecological and environmental management. While many studies have investigated the impact of AI on carbon emissions, relatively few have delved into its relationship with air pollution. This study sets out to explore the causal mechanisms and constraints linking AI technologies and air pollution, using provincial panel data collected from 2007 to 2020 in China. Furthermore, this study examines the distinct pathways through which AI technology can ameliorate air pollution and reduce carbon emissions. The findings reveal the following key insights: (1) AI technologies have the capacity to significantly reduce air pollution, particularly in terms of PM 2.5 and SO 2 levels. (2) AI technologies contribute to enhanced air quality by facilitating adjustments in energy structures, improving energy efficiency, and strengthening digital infrastructure. Nonetheless, it is important to note that adjusting the energy structure remains the most practical approach for reducing carbon emissions. (3) The efficacy of AI in controlling air pollution is influenced by geographical location, economic development level, level of information technology development, resource dependence, and public attention. In conclusion, this study proposes novel policy recommendations to offer fresh perspectives to countries interested in leveraging AI for the advancement of ecological and environmental governance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Volatile organic compounds (VOCs) are the precursors of forming ozone (O 3 ) and fine particulate matter (PM 2.5 ). Accurate estimates of biogenic VOC (BVOC) emissions is essential for understanding the formation mechanism of O 3 and PM 2.5 pollution and precise reduction on anthropogenic emissions and thereby mitigating O 3 and PM 2.5 pollution. To gain comprehensive knowledge of BVOC emissions and improve the accuracy of their estimation, this study reviewed localized national, regional, and municipal emission estimations in China. From their comparisons, BVOC emission characteristics and deficiencies in the inventory compilation methodology were also investigated. The estimated BVOC emissions in China ranged between 10 and 58.9 Tg yr -1 and 10.9-18.9 Tg C yr -1 , with diverse contributions for different BVOC categories. The simulated historical and future BVOC emissions exhibited an increasing trend. The uncertainty of the BVOC estimates was mainly from the applications of incomplete emission models, less localized accurate emission factors, deficient vegetation cover information, and low-resolution meteorological data in the inventory compilation. The regional and municipal BVOC emission inventories mainly focused on the Beijing-Tianjin-Hebei, Pearl River Delta, Sichuan Basin, and Yangtze River Delta regions, as well as the cities therein. For the same area, different studies reported diverse BVOC emissions by a maximum of two orders of magnitude. There is usually a lack of basic data with more detailed investigations and higher precision for estimation of BVOC emissions. By summarizing the measurements on terrestrial and marine BVOC emission fluxes, they are mainly focused on the Guangdong, Zhejiang and Jiangxi provinces, and Yellow Sea, East China Sea, and South China Sea, respectively. Expanding the temporal and spatial scales of observations is encouraged to enhance our understanding on the emissions and improve the emission estimates., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

To determine the priority control sources, an approach was proposed to evaluate the source-specific contribution to health risks from inhaling PM 2.5 -bound heavy metals (PBHMs). A total of 482 daily PM 2.5 samples were collected from urban and suburban areas of Beijing, China, between 2018 and 2019. In addition to the PMF-PSCF model, a Pb isotopic IsoSource model was built for more reliable source apportionment. By using the comprehensive indicator of disability-adjusted life years (DALYs), carcinogenic and noncarcinogenic health risks could be compared on a unified scale. The study found that the annual average concentrations of the total PBHMs were significantly higher in suburban areas than in urban areas, with significantly higher concentrations during the heating season than during the nonheating season. Comprehensive dust accounted for the largest contribution to the concentration of PBHMs, while coal combustion contributed the most to the DALYs associated with PBHMs. These results suggest that prioritizing the control of coal combustion could effectively reduce the disease burden associated with PBHMs, leading to notable public health benefits., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

As surface ozone (O 3 ) gains increasing attention, there is an urgent need for high temporal resolution and accurate O 3 monitoring. By taking advantage of the progress in artificial intelligence, deep learning models have been applied to satellite based O 3 retrieval. However, the underlying physical mechanisms that influence surface O 3 into model construction have rarely been considered. To overcome this issue, we considered the physical mechanisms influencing surface O 3 and used them to select relevant variable features for developing a novel deep learning model. We used a wide and deep model architecture to account for linear and non-linear relationships between the variables and surface O 3 . Using the developed model, we performed hourly inversions of surface O 3 retrieval over China from 2017 to 2019 (9:00-17:00, local time). The validation results based on sample-based (site-based) methods yielded an R 2 of 0.94 (0.86) and an RMSE of 12.79 (19.13) μg/m 3 , indicating the accuracy of the models. The average surface O 3 concentrations in China in 2017, 2018, and 2019 were 82, 78, and 87 μg/m 3 , respectively. There was a diurnal pattern in surface O 3 in China, with levels rising significantly from 55 μg/m 3 at 9:00 a.m. to 96 μg/m 3 at 15:00. Between 15:00 and 16:00, the O 3 concentration remained stable at 95 μg/m 3 and decreased slightly thereafter (16:00-17:00). The results of this study contribute to a deeper understanding of the physical mechanisms of ozone and facilitate further studies on ozone monitoring, thereby enhancing our understanding of the spatiotemporal characteristics of ozone., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Cities occupy a central position in addressing climate change and promoting sustainable regional development. Synergistic control of urban gas emissions at the city level is one of the main issues typically explored. The confounding effect and the interactions between the urban indicators of population and area have been ignored in previous studies. In this study, we examined the spatial distribution characteristics and synergy between greenhouse gases (CO 2 ) and air pollutants (SO 2 and NO X ) using spatial population and gas emission data. By upgrading the city clustering algorithm (CCA), we established a method for defining active areas of gas emissions (spatial element-coupled clustering, SECC) and identified active areas of gas emissions in China. In this study, we created a research framework that can simultaneously consider the effects of population and area, as well as the possible interactions between these indicators in active areas. The superlinear scaling relationship between the above three gases was revealed at the active zone level, and the existence of synergy between the emission patterns of the three gases was confirmed. Via further model application, we measured the synergistic efficiency of the three gases. It was found that for every 1% increase in SO 2 and NO X in an active zone, CO 2 increases by 0.86%. In this study, we explored a new perspective and approach to explain the synergy between greenhouse gases and air pollutants. This is essential to promote national competition among cities to achieve synergistic control of CO 2 and local air pollutants., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The potential cause-effect relationship between synoptic meteorological conditions and levels of criteria air pollutants, including CO, NO 2 , O 3 , PM 10 , PM 2.5 and SO 2 , in Bahia Blanca, Argentina, was assessed for the period of 2018-2019. Daily back-trajectories and global meteorological data fields were employed to characterize the primary transport paths of air masses reaching the study site, and to identify the synoptic meteorological patterns responsible for these atmospheric circulations. Time series of surface-level meteorological parameters and midday mixing layer height were collected to examine the impact of the synoptic meteorological patterns on local meteorology. Furthermore, the NAAPS global aerosol model was utilized to identify days when contributions from long-range transport processes, such as dust and/or biomass burning smoke, impacted air quality. By applying this methodology, it was determined that the air masses coming from the N, NW and W regions significantly contributed to increased mean concentrations of coarse particles in this area through long-range transport events involving dust and smoke. Indeed, the high average levels of PM 10 recorded in 2018-2019 (annual mean values of 47 and 52 μg/m 3 , respectively) represent the main air quality concern in Bahía Blanca. Moreover, PM 10 , PM 2.5 and NO 2 emissions should be reduced in order to meet recommended air quality guidelines. On the other hand, the results from this study suggest that the sources and meteorological processes leading to the increase in the concentrations of CO and SO 2 have a local-regional origin, although these air pollutants did not reach high values probably as a consequence of the strong wind speed registered in this region during any synoptic meteorological pattern., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

In megacities, vehicle emissions face urgent challenges related to air pollution and CO 2 control. To achieve the refinement of vehicle control policies for the co-control of air pollutants and CO 2 , this study established a vehicle emission inventory with high spatial and temporal resolution based on the hourly traffic flow in Shanghai and analyzed the spatial and temporal distribution characteristics of the real-time vehicle emissions. Meanwhile, a policy evaluation framework was constructed by combining pollutant emission predictions with quantitative co-control effect assessments. The results indicated that spatio-temporal variations in different air pollutants and CO 2 could mainly be attributed to primary contributing vehicle types. The pollutants (CO 2 , CO and VOCs) primarily contributed by private cars exhibited a bimodal pattern in 24-h time series and their spatial distribution was concentrated in the urban city center. The spatial distribution of NOx and PM primarily contributed by heavy trucks was still obvious on non-urban center areas. Furthermore, the results of synergistic effect analysis revealed that the alternative energy replacement scenario demonstrated the most significant potential for the co-control. Based on temporal-spatial and co-benefit analysis, the precise control policy of vehicle emissions can be established through time-, region-, and model-control. This study provides references and research methods for the formulation of the vehicle refinement control policies in worldwide megacities., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The effects of volatile organic compounds on urban air quality and the ozone have been widely acknowledged, and the contributions of relevant biogenic sources are currently receiving rising attentions. However, inventories of biogenic volatile organic compounds (BVOCs) are in fact limited for the environmental management of megacities. In this study, we provided an estimation of BVOC emissions and their spatial characteristics in a typical urbanized area, Shenzhen megacity, China, based on an in-depth vegetation investigation and using remote sensing data. The total BVOC emission in Shenzhen in 2019 was estimated to be 3.84 × 10 9  g C, of which isoprene contributed to about 24.4%, monoterpenes about 44.4%, sesquiterpenes about 1.9%, and other VOCs (OVOCs) about 29.3%. Metropolitan BVOC emissions exhibited a seasonal pattern with a peak in July and a decline in January. They were mainly derived from the less built-up areas (88.9% of BVOC emissions). Estimated BVOCs comprised around 5.2% of the total municipal VOC emissions in 2019. This percentage may increase as more green spaces emerge and anthropogenic emissions decrease in built-up areas. Furthermore, synergistic effects existed between BVOC emissions and relevant vegetation-based ecosystem services (e.g., air purification, carbon fixation). Greening during urban sprawl should be based on a trade-off between BVOC emissions and ecosystem benefits of urban green spaces. The results suggested that urban greening in Shenzhen, and like other cities as well, need to account for BVOC contributions to ozone. Meanwhile, greening cites should adopt proactive environmental management by using plant species with low BVOC emissions to maintain urban ecosystem services while avoid further degradation to ozone pollution., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

A profound green transformation of China's heavy industrial aggregation regions is required to conquer severe air pollution, and fulfill carbon peak pledge. Here, to clarify the coordinated mechanism and an optimal roadmap for the reduction of CO 2 and gaseous pollutants, we integrated input-output modelling, system dynamics, and multi-objective programming to construct a CO 2 and gaseous pollutants synergistic reduction model initially; investigated incentive approaches from 2020 to 2035; Hebei, with the largest steel production in China, was adopted as a demonstrative region. Results revealed that intensive dual control of efficiency and structure in energy and industry can accelerate achieving carbon peak in 2029. In optimal case, CO 2 emission intensity can reach a 75.2% reduction compared to 2020, and gaseous pollutants continue decline simultaneously (SO 2 and NOx can drop by 63% and 48%); and the synergistic reduction level is expected to improve. Thus, vigorously develop decoupling between economy-air pollution-carbon reduction in Hebei. As opposed to efficiency improvement, structural adjustments were demonstrated to be more effective than short-term efficiency improvements. In addition, the estimated development potential of traditional heavy industries such as steel and petrochemicals is limited, whereas the equipment manufacturing industry, closely linked to traditional industries, is expected to continue its development. Furthermore, although in the electrification process, coal consumption is still needed because of its indispensable role in the production process of heavy industries. The results can facilitate policy-making for heavy industrial aggregation areas' green transformation in shaping policies and actions with clear objectives, effective measures, and sound coordination., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Elevated nitrogen (N) deposition due to intensified emissions of NH 3 and NO x is a global problem with profound consequences on living organisms and the environment. Although N emission rates are currently considered to be high in East Asia, reports on the current N deposition level and composition are still limited, especially in northeastern China, where official N deposition monitoring sites are unavailable. This limits our understanding of the spatio-temporal N deposition patterns and their influencing factors at regional to continental scales. Here, we used data collected mostly during 2019 at 38 sites, comprising 7 sites in northeastern China and 31 EANET (Acid Deposition Monitoring Network in East Asia) sites in middle and east Russia, Mongolia, central and southern China, South Korea and Japan to explore the spatial-seasonal variations and drivers of ammonium and nitrate deposition across the Northeast Asia. Total bulk inorganic N (TIN) deposition was 3.7-24.5 kg N ha -1 yr -1 and NH 4 + -N ratio in the TIN was 0.8-2.8 in northeastern China. The bulk/wet TIN deposition averaged 7.5 kg N ha 3 - -N ratio in the TIN was 0.8-2.8 in northeastern China. The bulk/wet TIN deposition averaged 7.5 kg N ha -1 yr -1 -N = 1.4) over the Northeast Asia region, with the highest rates being observed in northeastern China (11.6), as well as central and southern China (10.7), followed by east Russia, South Korea and Japan (5.6), and the lowest in middle Russia and Mongolia (1.5). This regional bulk/wet TIN deposition level is about twice of the wet TIN deposition level in Europe and the United States. The TIN deposition in summer and spring was 45-467% higher than in autumn and winter. Out of the ten land uses considered, only agricultural and urban land uses significantly positively correlated with NH 4 + -N/NO 3 - -N = 1.4) over the Northeast Asia region, with the highest rates being observed in northeastern China (11.6), as well as central and southern China (10.7), followed by east Russia, South Korea and Japan (5.6), and the lowest in middle Russia and Mongolia (1.5). This regional bulk/wet TIN deposition level is about twice of the wet TIN deposition level in Europe and the United States. The TIN deposition in summer and spring was 45-467% higher than in autumn and winter. Out of the ten land uses considered, only agricultural and urban land uses significantly positively correlated with NH 4 + -N and NO 3 - -N deposition rates across all monitored sites. This study suggests that the ongoing agricultural and urban expansions are likely to enhance N deposition and its associated effects across global ecosystems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Although considerable health effects are gained from air quality improvement action plans implemented in China recently, they may have been amplified or offset due to the complexity and uncertainty of the changing demographic factors. In this study, we developed a framework for analyzing the effects of demographic factors on environmental health effects, focusing on three aspects: population scale, age structure, and spatial distribution. We quantified the above three effects by investigating how the health endpoint changed by the three demographic factors, based on a strategy of counterfactual and step-by-step relaxing hypothesis. We found that the increasing population scale and population aging caused 44,279 to 292,442 premature deaths, which offset the health effect of air quality improvement efforts for China. The change in population spatial distribution, in general, has little impact on the health effects of air quality improvement. Furthermore, the three effects are distributed unevenly across regions, especially the spatial distribution effect. Considering the widespread effect of demographic factors, PM 2.5 concentration should be further reduced, and the aged population and mega-cities should be targeted for managing air quality in a cost-effective manner., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Evidence from the past has previously established that the air information disclosure program has an impact on people's air pollution perception. However, the influence of the concrete information communicated has always been overlooked. In this study, we examine the impact of the announced air pollution level information on public pollution perception. We collect air-related Weibo posts from June 1, 2019, to May 31, 2021, in China, and apply a regression discontinuity (RD) design to quantify the impact. According to our research, when a higher pollution level is announced, people's pollution perception expressed online rises by 3.5%-3.7%, which is approximately equivalent to the response to a more than 100 Air Quality Index (AQI) increase. The episode-based analyses reveal that the impact of pollution level information would fade away along with the persistence or the frequency of the announced pollution episode, which shows a phenomenon of information fatigue. The heterogeneity analyses reveal that the impact of pollution level is significant only when the original pollution level is "Good" or "Lightly Polluted", leading to an increase of pollution perception by 2.8% and 4.8%, respectively. We also find that men, highly-educated, and urban residents are more responsive to the pollution level information. Our study illustrates a detailed picture of how people's perception responds to the announced pollution level information under the AQI standards, and can provide guidance for policymakers when developing the AQI standards to maximize the welfare of the air information., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Indoor air quality (IAQ) of urban public transportation stations (UPTS) has adverse health impacts on the station employees and commuters. However, there is a lack of comprehensively evaluations of IAQ in waiting rooms of UPTS. Therefore, it is crucial to select appropriate air quality indexes (including fuzzy synthetic index (B), comprehensive index (P), I 1 index, and indoor air quality index (IAQI)) to assess air quality and potential health risks. Our study is a subsample of the CPPEHS 2019 study, which included 224 UPTS in 126 cities of China. We found that P index showed an excellent air quality rate of 95.96% in the railway stations and 83.19% in the inter-city bus stations. The P index was correlated with UPTS usage years, useable area, and per passenger useable area. Furthermore, waiting rooms in UPTS with good (OR = 1.9187, 95% CI: 1.1204, 3.2859) and bad (OR = 2.0854, 95% CI: 1.2182, 3.5698) air quality evaluated by P index had a higher risk of rhinitis compared to those with excellent air quality. Similarly, UPTS with good (OR = 2.2202, 95% CI: 1.3427, 3.6711), bad (OR = 1.7897, 95% CI: 1.0807, 2.9637), and serious (OR = 1.7478, 95% CI: 1.0098, 3.0250) air quality evaluated by P index were associated with a higher risk of pharyngitis. These findings suggested that P index is the optimal index for assessing air quality in UPTS, while IAQI may exaggerate indoor air pollution and the B index may underestimate it. Overall, this study aims to identify and evaluate the more suitable air quality index (P) in nationwide UPTS, providing valuable insights for control of IAQ and guiding the air quality management and standards., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

China's Coal Ban policy is one of the world's most extensive and ambitious programs designed to mitigate air pollution. However, the effects of this policy on the environment and the economy remain unknown. This study examines the impacts of the Coal Ban policy, which has been implemented in 28 cities in Beijing and its adjacent provinces, on air quality and economic growth. Based on a panel dataset spanning 138 cities between 2010 and 2019, the policy was found to have reduced atmospheric particulate matter with a diameter less than or equal to 2.5 μm (PM 2.5 ) by 4.74 μg/m 3 in the 28 cities, but have also reduced per capita gross domestic product (GDP) by 5.8%. Further, the policy has also produced spatial spillover effects. In cities near the 28 cities, the policy has reduced PM 2.5 by 4.40 μg/m 3 and per capita GDP by 0.9%. Robustness tests corroborated the reliability of the conclusions. These findings underscore the importance of fostering a harmonious relationship between efforts to mitigate air pollution and the pursuit of economic growth objectives., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Since especially the 12th Five-Year Plan (2011-2015), China has made great efforts to reverse the increasing trend of NO x emissions through end-of-pipe measures. With the Ozone Monitoring Instrument (OMI) level 2 swath product of tropospheric NO 2, this study explores the temporal-spatial patterns of NO x concentrations over China's coal-fired power plants from 2005 to 2020 and investigates the evolution of its control strategy. The nationwide deployment of flue-gas denitration facilities was a critical measure to mitigate NO x emissions from coal-fired power plants, while this study externally assesses the implementation gap of their operation. Our results illustrate that, besides the impacts of economic cycles, China's control strategy experienced a dramatic transformation from an ad hoc campaign style for meeting short-term temporary targets to more sustainable, technology- and governance-centered institutional arrangements for ensuring long-term fundamental solutions. Furthermore, the satellite-based assessment may provide not only ex post evaluation, but also in-time and independent data for more effective and efficient environmental compliance monitoring., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Real Drive Emission (RDE) test with Portable Emission Measurement System (PEMS) is a widely adopted way to assess vehicle emission compliance. However, the current NOx emissions calculation method stipulated in the China VI emission standard easily ignores the NOx emissions during cold start and low-power operation. To study the effect of cold start and low-power operation on the calculation of NOx emissions in the PEMS test, in this study, a China VI Heavy-Duty Vehicle (HDV) for urban use was used to conduct PEMS tests under various vehicle payload conditions. The data analysis results show that the increase in vehicle payload is beneficial to reducing the specific NOx emissions and passing the NOx emission compliance test because the increased payload improves the NOx conversion efficiency of the SCR system. Cold start duration has no obvious relationship with vehicle payload, accounting for only about 4∼6% in each test, but contributing more than 30% of NOx emissions. Due to the effect of the power threshold and the 90th cumulative percentile, the cold start data has little influence on the result of the NOx emissions assessment and the maximum variation of the NOx emissions result in this study is an 8% rise. For the HDV for urban use, the variation of the power threshold resulting from vehicle payload is small, no more than 2% in this study. The presence of the power threshold makes almost only the low-power operation in the second half of urban driving have an impact on the NOx emissions calculation, which may make more than 50% of NOx emissions in the PEMS test be neglected. The impact of the low-power operation on NOx emissions calculation result will be significantly enhanced if all windows are considered in the Moving Average Window (MAW) method. In the meantime, the degree of variation is closely related to the NOx emissions level during the first half of urban driving. The maximum deterioration of NOx emission assessment result can be more than 90% in this study., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Transboundary air pollution poses a significant challenge in China, and collaborative governance presents a promising approach to tackle this problem. However, such approach is rarely implemented due to the influence of inter-regional trade dynamics. To address this issue, a comprehensive, responsibility-based fair compensation mechanism was established in the present study. The aim of the mechanism is to bridge the existing gap through the integrated utilization of air pollutant emission inventories, multi-regional input-output analysis, emission responsibility allocation, and an ecological compensation model. In 2017, approximately 50% of China's air pollutant emissions were embedded in inter-provincial trade, primarily originating from wealthier provinces and directed towards less-developed regions with higher pollution intensity. There exists a significant imbalance between the inter-provincial transfers of air pollution and economic benefits, owing to which Inner Mongolia and Liaoning have suffered from serious environmental inequity brought about by trade. The allocation of responsibility for trade-related emissions between producers and consumers is determined by the economic surplus they gain from trade. Such approach results in an intermediate outcome that falls between production-based and consumption-based emissions for the majority of provinces. The scheme highlights the import-related share of responsibility for economically developed provinces and the export-related share for less-developed, pollution-intensive provinces, which can primarily be attributed due to their differences in value chain specialization. The inter-provincial compensation volumes for trade-related emissions are determined based on the economically equitable emission responsibility sharing scheme. More developed provinces, characterized by industrial structures focused on low-pollution, high-value-added products, primarily function as compensation providers. In contrast, less-developed provinces with higher pollution intensity seek compensation from these more affluent regions. The present findings can offer a quantitative basis for the ecological compensation and collaborative control mechanism of trade-driven transboundary air pollution in China., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Quantity-based and concentration-based limits are two common environmental permitting approaches utilized by government worldwide in environmental management. While existing literature is still unambiguous about roles played by quantity-based versus concentration-based limits in environmental management, it becomes evident that relying exclusively on concentration-based or quantity-based limits to control plant emissions may not necessarily result in improved environmental quality. This paper leverages a unique opportunity arising from a recent reform in China's Pollutant Emission Permit System (PEPS) initiated in 2016 to analyze how the introduction of quantity-based limits in addition to concentration-based limits through the PEPS reform impact emissions at the plant level. Utilizing a unique plant-level continuous emission monitoring system data collected from Shaanxi Province (located in western China), the paper finds a significant reduction in air pollutant emissions as a result of the PEPS reform (nitrogen oxides (NOx) by 39%, sulfur dioxide (SO 2 ) by 15% and particulate matter (PM) by 13%). The heterogeneity analyses show emission reductions in plants differ across those with varying quantity limits specified in their permits, distinct emission ratios and diverse ownership structures. Furthermore, plants that fall under the classified management system with more stringent regulations imposed, especially those operating in high-pollution sectors, situated within industrial parks, or classified as large-sized plants, attain higher pollutant quantity limits. Findings of the paper carry important implications for effective environmental management, particularly within developing countries, and shed some light on carbon emission reduction policies in China., Competing Interests: Declaration of competing interest This work is supported by the National Natural Science Foundation of China (Grant no. 71773135), Fundamental Research Funds for the Central Universities, and the Research Funds of Renmin University of China (Grant no. 21XNH057) and the Fund for Building World-class Universities (disciplines) of Renmin University of China (Grant no. KYGJA2022004). Authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

In recent years, China has achieved numerous economic miracles but it has also been plagued by severe air pollution. The frequent hazy weather has severely restricted China's sustainable development. To investigate the nonlinear threshold effect of socio-economic factors on urban haze in China, this study constructs a spatial econometric Smooth Transition Autoregressive Regression (STAR) model based on the STIRPAT theory by using the remote sensing inversion PM 2.5 data of 223 prefecture-level and above cities in China mainland during 2004-2016. In this study, the ARAR-STAR model is estimated by quasi-maximum likelihood estimation, and the accuracy of parameter estimation is verified by Monte Carlo simulation, which proves that the ARAR-STAR model constructed in this study is robust. It is concluded that: there is a complex spatial nonlinear relationship between socio-economic factors such as economic development level, population density, advanced industrial structure, energy consumption, opening-up, and haze pollution. The effect of socio-economic factors on haze emission reduction under the spatial influence has complex heterogeneity with the smooth transition between high and low regimes with economic development. The ARAR-STAR model constructed in this paper, which has both individual fixed effects and time fixed effects, expands the form of existing spatial panel nonlinear models and enriches and implements the application of spatial panel smooth transfer threshold models in the environmental field. Not only can it provide policy recommendations for China to achieve "coordinated efficiency in pollution reduction and carbon reduction" as soon as possible, but it also contributes to China's plan to address global climate change and promote global sustainable development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

The location and layout of enterprises have an important impact on local air quality. However, a few studies on exploring of the optimal layout of gas-related enterprises from the perspective of optimizing the layout of air pollution sources. This study developed a method for the evaluation of air pollution source layout based on air pollutant emission inventory data, atmospheric self-purification capacity data, and satellite remote sensing air quality data. Taking Shaanxi Province as an example, the Moran's I index and GIS spatial analysis techniques were used to evaluate the layout of air pollution sources, analyze the spatial variation characteristics of air pollution sources, and propose specific countermeasures to optimize the layout of air pollution sources. Results showed that northern Shaanxi and Guanzhong Plain are the most unsuitable for the distribution of NO x and CO sources, accounting for 13.78% and 21.77% of the total area, respectively. The most suitable area for the distribution of NO x is southern Shaanxi, accounting for 65.77% of the total area, mainly concentrated in Hanzhong and Ankang regions. The most suitable area for the distribution of CO is southern Shaanxi, accounting for 40.97% of the total area, mainly concentrated in Hanzhong and Shangluo regions. The findings of this study could supplement and improve the evaluation of the layout of industrial enterprises in China from technical and methodological aspects, and provide new insight for local governments to adjust and optimize the layout of air pollution sources., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Rainwater hydrochemistry is an important indicator for tracing anthropogenic input on air quality. As the fastest economically developing city in the northwestern China and the Chinese Loess Plateau, rainwater chemistry, sources of dissolved solutes, and the influence of loess dust on rainwater chemistry in Xi'an city is unclear. Inorganic ions, δD and δ 18 O of two years' rainwater samples were measured to decipher the above issues. Rainwater samples were weakly alkaline (pH = 7.2) with the mean total dissolved solids (TDS) values of 43 mg/L. NH 4 + and Ca 2+ dominated in the cations and SO 4 2- and NO 3 - dominated in the anions. The wet deposition of sulfur (S) and nitrogen (N) was 70.9 ± 67 mg·(m 2 ·month) -1 and 244.8 ± 270.9 mg·(m 2 ·month) -1 , respectively. The meteoric water line in Xi'an was δD = 7.29δ 18 O+3.72 (R 2 , and the neutralization ability in Xi'an city is higher than the southern China cities. Correlation analysis (CA), positive matrix factorization (PMF), and the backward air masses trajectory model identified high NH 18 O, and d-excess analysis indicated the influence of evaporation on the dissolved solutes in rainwater, especially in the dry season. Rainwater acidity in the Xi'an city was mainly neutralized by Ca 2+ and NH 4 + , and the neutralization ability in Xi'an city is higher than the southern China cities. Correlation analysis (CA), positive matrix factorization (PMF), and the backward air masses trajectory model identified high NH 4 + and Ca 2+ in rainwater were mainly originated from local agricultural activities and loess dust, while NO 3 - and SO 4 2- were associated with local coal combustion and vehicle exhaust sources. High inputs of dusts and coal combustion in spring and winter resulted in elevated values of pH and major ions in Xi'an. Due to the air pollution control policy, air quality in Xi'an is getting better in recent years. Our study highlights the influence of anthropogenic activities and loess dusts on the rainwater hydrochemistry in Xi'an and provides important dataset for air pollution control for other cities in semi-arid and arid regions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Radiocarbon ( 14 C), stable carbon isotope ( 13 C), and levoglucosan in PM 2.5 were measured in two northern Chinese cities during haze events and nonhaze periods in January 2019, to ascertain the sources and their differences in carbonaceous aerosols between the two periods. The contribution of primary vehicle emissions (17.8 ± 3.7%) to total carbon in Beijing during that haze event was higher than that of primary coal combustion (7.3 ± 4.2%), and it increased significantly (7.1%) compared to the nonhaze period. The contribution of primary vehicle emissions (4.1 ± 2.8%) was close to that of primary coal combustion (4.3 ± 3.3%) during the haze event in Xi'an, and the contribution of primary vehicle emissions decreased by 5.8% compared to the nonhaze period. Primary biomass burning contributed 21.1 ± 10.5% during the haze event in Beijing and 40.9 ± 6.6% in Xi'an (with an increase of 3.3% compared with the nonhaze period). The contribution of secondary fossil fuel sources to total secondary organic carbon increased by 29.2% during the haze event in Beijing and by 18.4% in Xi'an compared to the nonhaze period. These results indicate that specific management measures for air pollution need to be strengthened in different Chinese cities in the future, that is, controlling vehicle emissions in Beijing and restricting the use of coal and biomass fuels in winter in Xi'an., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Due to variations in economic scale, economic structure, and technological advancement across different Chinese provinces and cities, the cost of air pollution reduction differs significantly. Therefore, the total reduction cost can be decreased by capitalizing on these regional discrepancies in reduction cost to carry out cooperative emission reduction. In this paper, taking NO x reduction in North China as an example, a regional cooperative reduction game (CRG) model was constructed to minimize the total cost of emission reduction while achieving future emission reduction targets. The fair allocation of benefits from cooperation plays a crucial role in motivating regions to participate into the cooperation. A comprehensive mechanism of benefits allocation was proposed to achieve fair transferred compensation. The mechanism combines the consumption responsibility principle based on input-output theory and the Shapley value method based on game theory. Compared to the cost before the optimized collaboration, the CRG model will save 20.36% and 13.71% of the total reduction cost in North China, respectively, under the target of 17.68% NO x reduction by 2025 and 66.44% NO x reduction by 2035 relative to 2020. This method can be employed in other regions to achieve targets for air pollution reduction at minimum cost, and to motivate inter-regional cooperation with this practical and fair way of transferred compensation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Long-term exposure to ambient ozone (O 3 ) poses a severe public health threat in China. However, the drivers of premature mortality caused by O 3 pollution are still poorly constrained, despite being prerequisites for addressing the threat. Here, we demonstrate the contributions of historical and future changes in peak-season O 3 , population size, age structure, and baseline mortality to China's O 3 -related mortality using decomposition analysis. From 2013 to 2021, O 3 -related mortality decreased dramatically from 78.8 (40.8-124.6) to 68.7 (36.0-107.2) thousand, especially in densely populated areas with high pollution. Variations in peak-season O 3 , population size, age structure, and baseline mortality led to changes in O 3 -related mortality of +27.3 (14.8-41.3), +2.6 (1.4-4.1), +22.3 (11.5-35.2), and -40.3 (20.9-63.7) thousand, respectively. The influence of peak-season O 3 on O 3 -related mortality shifted from positive during 2013-2019 (+8.4% per year) to negative during 2019-2021 (-8.8% per year), which highly regulated the interannual trend of mortality. From 2021 to 2035, O 3 -related mortality is expected to increase by 31% in the current context of peak-season O 3 levels, primarily caused by increased aging. Even reducing peak-season O 3 to the WHO interim target 1 (IT-1) would only reduce O 3 -related mortality by 3.9%, while a more rigorous standard (IT-2) would prevent 83.7% of mortality. These findings suggest that improving ambient O 3 can lead to significant health benefits, but substantial mitigation strategies are merited given the future trend of population aging., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Volatile organic compounds (VOC) contributing to smog formation, have been an important indicator of atmospheric governance during China's "14th Five-Year Plan". VOC would be possibly incorporated into the scope of environmental protection tax, but previous studies have seldom explored impacts of VOC control policies at national and regional levels. Here, we design a national uniform VOC control policy, as well as two regionally differentiated policies based on regional disparities in PM 2.5 concentrations and energy intensity by using a cross-scale dynamic computable general equilibrium (CGE) model. Our analysis is to assess the impacts of these policies on VOC, CO 2 , sulfur dioxide (SO 2 ), nitrogen oxides (NO X ), and PM 2.5 emissions, air quality and environmental equity, and to estimate health benefits, policy costs and net benefits. We find that national and regionally differentiated VOC control policies generally lead to VOC emission reductions and generate co-benefits on emission reductions in CO 2 , SO 2 , NO X and PM 2.5 at national and provincial levels. However, regional emission leakage exists due to differences in the provincial costs of VOC mitigation. The regionally differentiated VOC pricing policies are found to be more effective to enhance environmental equity than the uniform policy. In particular, the regionally differentiated VOC control policy based on provincial energy efficiency is found to be superior to other policies in terms of improve air quality. Furthermore, the human health benefits associated with VOC pricing policies would partially offset policy costs at both the national and regional levels. Our results suggest that policymakers would pay attention to developing regions with low energy efficiency which have the great emission reduction potential. Advanced producing technology and further end-of-pipe control measures to reduce non-combustion PM 2.5 emissions are needed. VOC policy designed based on provincial energy efficiency provides great insights for environmental policy making to accomplish 2035 goal of building a Beautiful China., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

PM 2.5 is one of the primary air pollutants that affect air quality and threat human health in the port areas. To prevent and control air pollution, it is essential to understand the spatiotemporal distributions of PM 2.5 concentrations and their key drivers in ports. 19 coastal ports of China are selected to examine the spatiotemporal distributions of PM 2.5 concentrations during 2013-2020. The annual average PM 2.5 concentration decreases from 61.03 μg/m 3 to 30.17 μg/m 3 , with an average decrease rate of 51.57%. Significant spatial autocorrelation exists among PM 2.5 concentrations of ports. The result of the geographically and temporally weighted regression (GTWR) model shows significant spatiotemporal heterogeneity in the effects of meteorological and socioeconomic factors on PM 2.5 concentrations. The effects of boundary layer height on PM 2.5 concentrations are found to be negative in most ports, with a stronger effect found in the Pearl River Delta, Yangtze River Delta and some ports of the Bohai Rim Area. The total precipitation shows negative effects on PM 2.5 concentrations, with the strongest effect found in ports of the Southeast Coast. The effects of surface pressure on PM 2.5 concentrations are positive, with stronger effects found in Beibu Gulf Port and Zhanjiang Port. The effects of wind speed on PM 2.5 concentrations generally increase from south to north. Cargo throughput shows strong and positive effects on PM 2.5 concentrations in ports of Bohai Rim Area; the positive effects found in Beibu Gulf Port increased from 2013 to 2018 and decreased since 2019. The positive effects of GDP and nighttime light on PM 2.5 concentrations gradually decrease and turn negative from south to north. Understandings obtained from this study can potentially support the prevention and control of air pollution in China's coastal ports., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Clarifying the driving forces of O 3 and fine particulate matter (PM 2.5 ) co-pollution is important to perform their synergistic control. This work investigated the co-pollution of O 3 and PM 2.5 in Hainan Province using an observation-based model and explainable machine learning. The O 3 and PM 2.5 pollution that occurs in winter is affected by the wintertime East Asian Monsoon. The O 3 formation shifts from a NO x -limited regime with a low O 3 production rate (P O3 ) in the non-pollution season to a transition regime with a high P O3 in the pollution season due to an increase in NO x concentrations. Increased O 3 and atmospheric oxidation capacity promote the conversion from gas-phase precursors to aerosols. Meanwhile, the high concentration of particulate nitrate favors HONO formation via photolysis, in turn facilitating O 3 production. Machine learning reveals that NO x promotes O 3 and PM 2.5 co-pollution during the pollution period. The P O3 shows an upward trend at the observation site from 2018 to 2022 due to the inappropriate reduction of volatile organic compounds (VOCs) and NO x in the upwind areas. Our results suggest that a deep reduction of NO x should benefit both O 3 and PM 2.5 pollution control in Hainan and bring new insights into improving air quality in other regions of China in the future., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

As China's largest energy infrastructure, thermal power plant consumed approximately half of China's coal over the past decade and threatened air quality, human health and socioeconomic development. Thus, a series of control policies have been implemented to alleviate those impacts in China. Particularly, China has witnessed unprecedented declines in air pollutant emissions from thermal power plants since the ultra-low emissions (ULE) standards were implemented. In contrast, the effect of the ULE policy on air quality, health and cost benefits remains poorly understood. Therefore, this study estimates the improved air quality and associated health and economic benefits under the ULE standards in the thermal power sector by using a measure-specific approach, combining a bottom-up emission inventory, an atmospheric model, a health assessment model and a cost analysis model. The results show that all the control measures lead to reduced air pollution, and renovating pre-existing units (RPU) is the most effective. Compared to without implementing the ULE policy, the population-weighted average PM 2.5 and O 3 concentrations decreased by 1.50 μg/m 3 and 0.87 ppm, and 67,831 premature deaths could be avoided nationally. Furthermore, the results also show the net economic benefits of combining health benefits and costs due to control measures are 109.92 billion Yuan (in 2015 value) in China. The comprehensive results reveal that the health benefits outweigh the direct policy. Based on these empirical findings and the specific circumstances of China, we suggest that RPU should be further promoted to the entire of China, and if necessary, establish a long-term compensation mechanism for inter-provincial interests and institute and enforce comprehensive policies that carefully consider the health impacts of policies. This study provides strong arguments for China's policy-making and considering tightening emission standards for thermal power plants worldwide., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Long-term trends in particulate-bound polycyclic aromatic hydrocarbon (PAH) concentrations in air in Zhengzhou (a severely polluted city in central China) between 2010 and 2018 were studied to assess the effectiveness of an air pollution prevention and control action plan (APPCAP) implemented in 2013. The PM 2.5 , sum of 16 PAHs (Σ16 PAHs), benzo[a]pyrene (BaP), and BaP toxic equivalent concentrations were high before 2013 but 41%, 77%, 77%, and 78% lower, respectively, after the APPCAP. The maximum daily Σ16 PAHs concentration between 2014 and 2018 was 338 ng/m 3 , 65% lower than the maximum of 961 ng/m 3 between 2010 and 2013. The ratio between the Σ16 PAHs concentrations in winter and summer decreased over time and was 8.0 in 2011 and 1.5 in 2017. The most abundant PAH was benzo[b]fluoranthene, for which the 9-year mean concentration was 14 ± 21 ng/m 3 (15% of the Σ16 PAHs concentration). The mean benzo[b]fluoranthene concentration decreased from 28 ± 27 ng/m 3 before to 5 ± 4 ng/m 3 after the APPCAP (an 83% decrease). The mean daily BaP concentrations were 0.1-62.8 ng/m 3 , and >56% exceeded the daily standard limit of 2.5 ng/m 3 for air. The BaP concentration decreased from 10 ± 8 ng/m 3 before to 2 ± 2 ng/m 3 after the APPCAP (a 77% decrease). Diagnostic ratios and positive matrix factorization model results indicated that coal combustion and vehicle exhausts were important sources of PAHs throughout the study period, contributing >70% of the Σ16 PAHs concentrations. The APPCAP increased the relative contribution of vehicle exhausts from 29% to 35% but decreased the Σ16 PAHs concentration attributed to vehicle exhausts from 48 to 12 ng/m 3 . The PAH concentration attributed to vehicle exhausts decreased by 79% even though vehicle numbers strongly increased, indicating that pollution caused by vehicles was controlled well. The relative contribution of coal combustion remained stable but the PAH concentration attributed to coal combustion decreased from 68 ng/m 3 before to 13 ng/m 3 after the APPCAP. Vehicles made dominant contributions to the incremental lifetime cancer risk (ILCRs) before and after the APPCAP even though the APPCAP decreased the ILCRs by 78%. Coal combustion was the dominant source of PAHs but contributed only 12-15% of the ILCRs. The APPCAP decreased PAH emissions and changed the contributions of different sources of PAHs, and thus strongly affected the overall toxicity of PAHs to humans., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Air sampling campaigns were conducted at 100 survey sites across Japan from April 2014 to February 2020, and a comprehensive database of atmospheric particles was obtained. In this study, the characteristics of PM 2.5 and 26 metals were investigated in depth. Spatially, the concentration of PM 2.5 gradually increased from the northeast to the southwest of Japan. The pollution in Kitakyushu City was the most serious, reaching 19.8 μg m -3 . As an important particle component, metals did not show obviously spatial variation in Japan, with a sum concentration of 0.4 μg m -3 . Anthropogenic metals only accounted for about 8% of the total metals, but they could pose a serious threat to public health. For children, the non-carcinogenic risk and carcinogenic risk due to exposure to anthropogenic metals could not be neglected in Japan; the corresponding HI and CR values at 100 survey sites ranged from 2.7 to 15.0 and 4.1 × 10 -5 to 3.4 × 10 -4 , respectively. Adults faced lower health risks than children, with HI values ranging from 0.2 to 2.0 and CR values ranging from 2.0 × 10 -5 to 1.6 × 10 -4 . The integrated health risk assessment results showed that the coastal region of the Seto Inland Sea and the north Tohoku Region were the most heavily polluted areas of Japan; in this study, 20 survey sites were finally determined to be high-risk sites, among which pollution control for Niihama City, Kitakyushu City, Hachinohe City, and Shimonoseki City were of first priority. With further combination with a positive matrix factorization model, it can be known that these four cities mainly had five to seven metal sources, and their heavy pollution was mainly caused by ship emissions, industrial emissions, biomass burning, and coal combustion. Overall, our study comprehensively revealed the regional patterns of PM 2.5 -bound metal pollution across Japan, which can help in making cost-effective risk management policies with limited national/local budgets., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper, (Copyright © 2023 Elsevier Ltd. All rights reserved.)

China is presently confronted with the intricate challenge of simultaneously mitigating air pollution and decelerating the pace of climate change. An integrated perspective to investigate the synergetic control of CO 2 and air pollutant emissions is in an urgent need. Using data for 284 Chinese cities from 2009 to 2017, we introduced an indicator called coupling and coordination degree of CO 2 and air pollutant emissions control (CCD) and found an upward and spatial agglomeration trend of CCD distribution during the research period. Then, this study posed a specific focus on the impact of China's Air Pollution Prevention and Control Action Plan (APPCAP). The DID model revealed that implementation of the APPCAP resulted in a 4.0% increase in CCD for cities with special emission limits, attributed to industrial structural adjustments and the promotion of technology innovation. Furthermore, we also identified positive spillover effects of the APPCAP on neighboring control group cities situated within 350 km of the treatment group cities, providing an explanation for the spatial agglomeration trend observed in CCD distribution. These findings hold significant implications for the synergetic control in China and underscored the potential benefits of industrial structural adjustments and technology innovation in mitigating environmental pollution., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The pollution control effect of seasonal environmental regulation policies in developing countries still lacks empirical evidence. In 2017, China implemented its first Atmospheric Environmental Policy in Autumn and Winter (AEPAW) to coordinate efforts among cities in reducing air pollutant emissions. Taking the daily panel data of 174 cities in northern China from July 2017 to July 2020 as samples, this paper empirically examines the pollution control effect of the AEPAW using a difference-in-differences model, a difference-in-difference-in-differences model, and a regression discontinuity design. The results show that the AEPAW significantly improves air quality in autumn and winter, with the air quality index decreasing by 5.6% on average by reducing PM 2.5 , PM 10 , SO 2 , and O 3 emissions. However, the AEPAW only creates a short-term "policy-induced blue sky", and there exists a phenomenon of "retaliatory pollution" after the AEPAW ends. Besides, the pollution control effect of the AEPAW is moderated by the heterogeneity of the national "Two Sessions" and the Central Environmental Protection Inspection. The implementation of the AEPAW also has a significant spillover effect on air pollution control in surrounding areas. The net benefit from the AEPAW is estimated to be approximately US$ 670 million per year. These findings not only have practical significance for strengthening the comprehensive control of air pollution in China, but also give some important references for other developing countries., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Phasing out thermal power plants is vital to combatting climate change. Less attention has been given to provincial-level thermal power plants, which are implementers of the policy of phasing out backward production capacity. To improve energy efficiency and reduce negative environmental impacts, this study proposes a bottom-up cost-optimal model to explore technology-oriented low-carbon development pathways for China's provincial-level thermal power plants. Taking 16 types of thermal power technologies into consideration, this study investigates the impacts of power demand, policy implementation, and technology maturity on energy consumption, pollutant emissions, and carbon emissions of power plants. The results show that an enhanced policy combined with a reduced thermal power demand would peak carbon emissions of the power industry at approximately 4.1 GtCO 2 in 2023. Meanwhile, most of the inefficient coal-fired power technologies should be eliminated by 2030. Carbon capture and storage technology should be gradually promoted in Xinjiang, Inner Mongolia, Ningxia, and Jilin after 2025. Energy-saving upgrades on 600 MW and 1000 MW ultra-supercritical technologies should be emphatically carried out in Anhui, Guangdong, and Zhejiang. By 2050, all thermal power will come from ultra-supercritical and other advanced technologies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Monitoring long-term variations in fine particulate matter (PM 2.5 ) is essential for environmental management and epidemiological studies. While satellite-based statistical/machine-learning methods can be used for estimating high-resolution ground-level PM 2.5 concentration data, their applications have been hindered by limited accuracy in daily estimates during years without PM 2.5 measurements and massive missing values due to satellite retrieval data. To address these issues, we developed a new spatiotemporal high-resolution PM 2.5 hindcast modeling framework to generate the full-coverage, daily, 1-km PM 2.5 data for China for the period 2000-2020 with improved accuracy. Our modeling framework incorporated information on changes in observation variables between periods with and without monitoring data and filled gaps in PM 2.5 estimates induced by satellite data using imputed high-resolution aerosol data. Compared to previous hindcast studies, our method achieved superior overall cross-validation (CV) R 2 and root-mean-square error (RMSE) of 0.90 and 12.94 μg/m 3 and significantly improved the model performance in years without PM 2.5 measurements, raising the leave-one-year-out CV R 2 [RMSE] to 0.83 [12.10 μg/m 3 ] at a monthly scale (0.65 [23.29 μg/m 3 ] at a daily scale). Our long-term PM 2.5 estimates show a sharp decline in PM 2.5 exposure in recent years, but the national exposure level in 2020 still exceeded the first annual interim target of the 2021 World Health Organization air quality guidelines. The proposed hindcast framework represents a new strategy to improve air quality hindcast modeling and can be applied to other regions with limited air quality monitoring periods. These high-quality estimates can support both long- and short-term scientific research and environmental management of PM 2.5 in China., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Border pollution is usually a difficult problem in environmental governance. Based on the data at the county level in China from 2005 to 2019, this study takes the 12th Five-Year Plan (FYP) for atmospheric pollution as a policy shock, and uses the difference-in-differences (DID) method to explore the impact of regional joint prevention and control (JPC) of atmospheric pollution policy on air pollution of the border regions. Empirical results show that: (1) After implementing the JPC of atmospheric pollution policy, the PM 2.5 concentration in the border regions is reduced by 3.5%. (2) The mechanism analysis shows that there is a spillover effect in the governing behaviors of local governments. In the border areas under low economic growth pressure and high environmental protection pressure, the reduction effect of the JPC of atmospheric pollution policy is more significant on the PM 2.5 concentration of the border regions. The research conclusions have new insights into the role and effect of macro-regional environmental JPC policy and border pollution control, and provide practical guidance for social green governance., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Countries around the world are increasingly turning towards developing digital economies to find better strategies for tackling the environmental pollution associated with economic growth while also pursuing high-quality economic conditions. This study aims to probe the link between coordinated regional digital economy development (RDEC) and air quality. A province-level RDEC indicator based on city-level data is developed, and air pollution is gauged by annual average PM 2.5 concentrations. Furthermore, a spatial simultaneous equation model is employed to examine the causality further. The empirical results indicate that a bilateral causal relationship exists: RDEC improves air quality, and better air quality also facilitates RDEC. This relationship is influenced by spatial spillover effects. Specifically, air quality and RDEC of an area have a negative influence on the RDEC of neighboring regions, while they have a positive impact on neighboring areas' air quality. Further analysis suggests that green total factor productivity, advanced industrial structure, and regional entrepreneurship level can indirectly affect the contribution of RDEC to air quality. Additionally, the impact of air quality on RDEC may be realized through the increase in labor productivity, lower external environmental costs of regional economic development, and enhanced regional foreign economic exchange., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

PM 2.5 has been a hot concern in the recent decade. Many studies have focused on metropolises or those areas with poor air quality, but the PM 2.5 of more widespread areas is less considered. Considering the challenges of rapid economic growth and environmental problems against a developing region, we took Guiyang as a study case to assess the spatiotemporal variations and mechanism of PM2.5 pollution in an urban area from 2000 to 2020 in an extended sense. Based on PM 2.5 concentration data from 14 monitoring points in Guiyang, spatiotemporal variations and formation mechanism were assessed using wavelet, moving maximal information coefficients, and spatial correlation analysis. The urban Nighttime light data was selected to evaluate the impacts of socioeconomic factors on PM2.5 concentration using spatial correlation analysis. Further, wavelet and statistical analysis were adopted to analyze multi-dimensional temporal variations of PM 2.5 hourly concentration and the relationship with pressure, temperature, vapor pressure, relative humidity, wind, and visibility. The PM 2.5 hourly concentration was obtained from the monitoring points in downtown Guiyang according to data continuity and availability. PM 2.5 had different temporal variations at daily, monthly, seasonal, and annual levels, and interannual variation was the most obvious. The temperature was the main factor leading to the interannual temporal variation of PM 2.5 . Wind and pressure were more significant for the responses of a shorter period variation with -0.76 and -0.80 of the minimum of correlation coefficient, respectively. Meanwhile, human activities significantly influenced spatiotemporal variations of PM 2.5 . A spatial correlation analysis between PM2.5 and the related influencing factors from 2000 to 2018 was implemented based on a geographic information system. Besides, the landcovers within a buffer zone with a radius of 1 km on 14 monitoring points were visually interpreted to analyze the relationship between PM 2.5 and landcovers. Moreover, multivariate wavelet coherence analysis revealed the PM2.5 interaction among monitoring points. The PM 2.5 concentration in Guiyang dropped from 49 μg/m 3 in 2012 to about 27 μg/m 3 in 2018, and the air quality greatly improved. As in most cities, Guiyang has a significant PM 2.5 pollution island effect, with traffic and building land density contributing to higher PM 2.5 concentrations. There were some typical nonlinear spatiotemporal variations between PM 2.5 and its influencing factors, and these variations varied with the selected scale., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

China is one of the world's most highly-pollutant countries, and over the last few years has experienced severe and persistent haze pollution. Exploring the effects of air pollution on household energy expenditure will provide a more comprehensive and accurate understanding of the economic effects of environmental pollution. It is an important question but remains unanswered because of an estimation endogeneity. Household non-clean energy consumption would increase air pollution. A major challenge in estimates is how to accurately and cleanly identify the unwatched effect of air pollution given the endogeneity. Using the global satellite monitoring data and unique micro-household survey data, we try to construct an instrumental variable to identify the net effect of air pollution on Chinese household energy expenditure. We find that the increase in air pollution has a significantly positive effect on household energy expenditure. The results remain robust after a series of pivotal checks. Our findings highlight that stay-home-avoidance behaviors as a potential mechanism behind the energy-associated effects of air pollution on household energy expenditure. The well-educated, high-income, and urban households in southern China are more likely to engage in stay-home-avoidance behaviors. These findings can provide some useful policy enlightenments for the government in terms of environmental regulation and promotion of household clean energy., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Previous research has implicated PM 2.5 as a potential environmental risk factor for CKD, but little is known about the associations between its components and CKD. We conducted a nationwide cross-sectional study using the updated air pollution data in the nationwide population (N = 2,938,653). Using generalized additive models, we assessed the association between long-term exposure to PM 2.5 and its components (i.e., black carbon [BC], organic matter [OM], nitrate [NO 3 - ], ammonium [NH 4 ]), and CKD prevalence. The air pollution data was estimated using high-resolution and high-quality spatiotemporal datasets of ground-level air pollutants in China. Besides, we adopted a novel quantile-based g-computation approach to assess the effect of a mixture of PM + ], sulfate [SO 4 2- ]), and CKD prevalence. The air pollution data was estimated using high-resolution and high-quality spatiotemporal datasets of ground-level air pollutants in China. Besides, we adopted a novel quantile-based g-computation approach to assess the effect of a mixture of PM 2.5 constituents on CKD prevalence. The average concentration of PM 2.5 was 78.67 ± 22.5 μg/m 3 , which far exceeded WHO AQG. In the fully adjusted generalized additive model, at a 10 km × 10 km spatial resolution, the ORs per IQR increase in previous 1-year average PM 2.5 exposures was 1.380 (95%CI: 1.345-1.415), for NH 4 + was 1.094 (95%CI: 1.062-1.126), for BC was 1.604 (95%CI: 1.563-1.646), for NO 3 - was 1.094 (95%CI: 1.060-1.130), for SO 4 2- was 1.239 (95%CI: 1.208-1.272), and for the OM was 1.387 (95%CI: 1.354-1.421), respectively. Subgroup analysis showed females, younger, and healthier were more vulnerable to this effect. In the further exploration of the joint effect of PM 2.5 compositions (OR 1.234 [95%CI 1.222-1.246]) per quartile increase in all 5 PM 2.5 components, we found that PM 2.5 SO 4 2- contributed the most. These findings provide important evidence for the positive relationship between long-term exposure to PM 2.5 and its chemical constituents and CKD prevalence in a Chinese health check-up population, and identified PM 2.5 SO 4 2- has the highest contribution to this relationship. This study provides clinical and public health guidance for reducing specific air particle exposure for those at risk of CKD., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

Polycyclic aromatic hydrocarbons (PAHs) are common air pollutants worldwide, associated with industrial processes. In the general population, both modeling and field studies revealed a positive correlation between air PAH concentrations and urinary PAH metabolite levels. Many countries lack population urinary data that correspond to local PAH air concentrations. Thus, we proposed a scoring-based approximate approach to investigating that correlation in selected countries, hypothesizing that PAH air concentrations in selected regions could represent the national air quality influenced by industrial emission and further correlate to PAH internal exposure in the general population. This research compiled 85 peer-reviewed journal articles and 9 official monitoring datasets/reports covering 34 countries, 16 of which with both atmospheric PAH data and human biomonitoring data. For the air pollution score (AirS), Egypt had the highest AirS at 0.94 and Pakistan was at the bottom of the score ranking at -1.95, as well as the median in the UK (AirS: 0.50). For the population exposure score (ExpS), China gained the top ExpS at 0.44 and Spain was with the lowest ExpS of -1.52, with the median value in Italy (ExpS: 0.43). Through the correlation analysis, atmospheric PAHs and their corresponding urinary metabolites provided a positive relationship to a diverse extent, indicating that the related urinary metabolites could reflect the population's exposure to specific atmospheric PAHs. The findings also revealed that in the 16 selected countries, AirS indexes were positively correlated with ExpS indexes, implying that higher PAH levels in the air may lead to elevated metabolite urinary levels in general populations. Furthermore, lowering PAH air concentrations could reduce population internal PAH exposure, implying that strict PAH air regulation or emission would reduce health risks for general populations. Notably, this study was an ideal theoretical research based on proposed assumptions to some extent. Further research should focus on understanding exposure pathways, protecting vulnerable populations, and improving the PAH database to optimize PAH pollution control., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Source contributions and regional transport of maximum daily average 8-h (MDA8) O 3 during a high O 3 month (June 2019) in Henan province in central China are explored using a source-oriented Community Multiscale Air Quality (CMAQ) model. The monthly average MDA8 O 3 exceeds ∼70 ppb in more than half of the areas and shows a clear spatial gradient, with lower O 3 concentrations in the southwest and higher in the northeast. Significant contributions of anthropogenic emissions to monthly average MDA8 O 3 concentrations of more than 20 ppb are predicted in the provincial capital Zhengzhou, mostly due to emissions from the transportation sector (∼50%) and in the areas in the north and northeast regions where industrial and power generation-related emissions are high. Biogenic emissions in the region only contribute to approximately 1-3 ppb of monthly average MDA8 O 3 . In industrial areas north of the province, their contributions reach 5-7 ppb. Two CMAQ-based O 3 -NO x -VOCs sensitivity assessments (the local O 3 sensitivity ratios based on the direct decoupled method and the production ratio of H 2 O 2 to HNO 3 ) and the satellite HCHO to NO 2 column density ratio consistently show that most of the areas in Henan are in NO x -limited regime. In contrast, the high O 3 concentration areas in the north and at the city centers are in the VOC-limited or transition regimes. The results from this study suggest that although reducing NO x emissions to reduce O 3 pollution in the region is desired in most areas, VOC reductions must be applied to urban and industrial regions. Source apportionment simulations with and without Henan anthropogenic emissions show that the benefit of local anthropogenic NO x reduction might be lower than expected from the source apportionment results because the contributions of Henan background O 3 increase in response to the reduced local anthropogenic emissions due to less NO titration. Thus, collaborative O 3 controls in neighboring provinces are needed to reduce O 3 pollution problems in Henan effectively., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

To support the achievement of the Paris Agreement's 1.5 °C global warming threshold, China aims to peak CO 2 emissions before 2030 and achieve carbon neutrality before 2060. However, the specific carbon neutrality pathway remains to be designed. By applying a refined Chinese version of Global Change Analysis Model, this study examines implications of four illustrative carbon neutrality scenarios for aligning China's energy system with below 1.5 °C by 2100. The results feature a trade-off between China's ambition to transform its energy system toward mid-century and its reliance on carbon dioxide removal (CDR) after carbon neutrality. From a full time perspective until 2100, accelerating carbon neutrality could help China's energy system align with below 1.5 °C. Compared to a 2060 carbon neutrality scenario, a 2050 carbon neutrality scenario reduces China's total mitigation costs between 2021 and 2100 by 1.04% of GDP, reduces reliance on CDR by 36%, and provides some additional co-benefits, such as reduced air pollutants. However, special attention needs to be paid to the fact that accelerating carbon neutrality poses greater challenges and costs to China in overcoming development inertia and restructuring its energy system over the next 30-40 years. Compared to a 2060 carbon neutrality scenario, a 2050 scenario increases China's mitigation costs by a factor of 1.13 between 2021 and 2050. This study suggests through quantitative evidence that China could accelerate emissions reductions and energy system transformation to achieve carbon neutrality, based on its national circumstances and capabilities and international support., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

In China, along with the rapid development of economy, air pollution has become a hot issue of public concern, particularly in many cities. The distortion in the labor factor market can cause air pollution, but the underlying mechanism is not yet clear. To investigate this question, this article examines the effect of labor market distortion on air pollution focusing on SO 2 emissions based on data of China's 283 cities during 2003-2015. The main objectives are to examine the direct and spillover effects of labor market distortion on air pollution using panel fixed-effects models, including the spatial Durbin model and the mediated-effects model. Results show that labor market distortion directly aggravates air pollution in cities. Mechanism analysis suggests that labor market distortion incurs air pollution through mechanisms of suppressing technological progress, hindering the upgrading of industrial structure, and reducing the efficiency of energy use. Divided the cities by their locations into those in eastern, central, and western regions, we find that such unfavorable effects are more prominent in eastern and western regions of the country. These findings highlight the impetus of mitigating the distorted labor market to ameliorate air quality and promote sustainable development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Synergetic control of environmental pollution and carbon emissions (SCEPCE) is essential to green development. The emergence of the digital economy has become a significant component in regional economic growth. Investigating the digital driving mode for SCEPCE in developing countries is crucial. This paper empirically analyzes the effect of establishing big data comprehensive experimental areas (BDCEAs) on air pollutants and carbon emissions using panel data of prefecture-level cities from 2009 to 2020 and the time-varying difference-in-differences method. The research found that (1) BDCEA inhibits pollution and carbon emissions, and the policy effect is sustainable. (2) The synergistic effect is significant, particularly in small and medium-sized cities and old industrial-base cities. The benefit of reducing pollution is only significant in the east. The effect of reducing CO 2 emissions is only significant in the west. (3) The pollution reduction effect of digital economic development has the characteristics of an increasing marginal effect, and the marginal effect of its carbon reduction effect is not apparent. (4) The technological innovation and energy efficiency improvement effects are effective mechanisms. This paper enriches the studies on the factors influencing SCEPCE, which will help to realize SCEPCE and the harmonious coexistence of humans and nature in developing countries. However, policy incentives and green development strategies must be fine-tuned to achieve global SCEPCE., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)