Is environmental regulation conducive to the reduction of residents’ health costs? – evidence from the Chinese Family Panel Survey DOI Creative Commons
Zhihua Xu,

H He,

Ying Qin

и другие.

Ecological Processes, Год журнала: 2024, Номер 13(1)

Опубликована: Авг. 21, 2024

Abstract Background In response to environmental degradation and the associated health challenges, Chinese government has implemented a comprehensive array of protection measures. Given enhancement objective measures considerable costs involved in implementation process, evaluating whether regulation is beneficial reducing population great significance for enhancing governance efficiency social welfare. The data from Family Panel Survey (CFPS) applied examine effect on reduction residents’ microscopic perspective. Results results indicate that 1% increase total investment governance, will decrease by 0.189%. examination causal pathway suggests implementing can diminish through improving air quality status. Concurrently, there exist significant heterogeneities role costs. more pronounced young, males, individuals with better self-perceived health. Furthermore, outcome exhibits greater efficacy urban areas compared rural areas. Lastly, market-incentive effective than command-controlled regulation. Conclusions Enhancing intensity contributes decreasing findings provide policy reference achieving tangible enhancements individuals' life quality.

Язык: Английский

Explainable ensemble machine learning revealing the effect of meteorology and sources on ozone formation in megacity Hangzhou, China DOI
Lei Zhang, Lili Wang, Dan Ji

и другие.

The Science of The Total Environment, Год журнала: 2024, Номер 922, С. 171295 - 171295

Опубликована: Фев. 27, 2024

Язык: Английский

Процитировано

23

Causal-Inference Machine Learning Reveals the Drivers of China’s 2022 Ozone Rebound DOI Creative Commons
Lin Wang, Baihua Chen,

Jingyi Ouyang

и другие.

Environmental Science and Ecotechnology, Год журнала: 2025, Номер 24, С. 100524 - 100524

Опубликована: Янв. 11, 2025

Ground-level ozone concentrations rebounded significantly across China in 2022, challenging air quality management and public health. Identifying the drivers of this rebound is crucial for designing effective mitigation strategies. Commonly used methods, such as chemical transport models machine learning, provide valuable insights but face limitations-chemical are computationally intensive, while learning often fails to address confounding factors or establish causality. Here we show that elevated temperatures increased solar radiation, primary meteorological drivers, collectively account 57 % total increase, based on an integrated analysis ground-based monitoring data, satellite observations, reanalysis information using explainable causal inference techniques. Compared year 2021, 90 stations reported increase Formaldehyde Nitrogen ratio, implying a growing sensitivity formation nitrogen oxide levels. These findings highlight significant role changes rebound, urging adoption targeted strategies under climate warming, particularly through varied regional consider existing anthropogenic emission levels prospective biogenic volatile organic compounds. This identification relationships pollution dynamics can support data-driven accurate decision-making.

Язык: Английский

Процитировано

2

Two-decade surface ozone (O3) pollution in China: Enhanced fine-scale estimations and environmental health implications DOI
Zeyu Yang, Zhanqing Li,

Fan Cheng

и другие.

Remote Sensing of Environment, Год журнала: 2024, Номер 317, С. 114459 - 114459

Опубликована: Ноя. 21, 2024

Язык: Английский

Процитировано

8

Evaluating urban and nonurban PM 2.5 variability under clean air actions in China during 2010–2022 based on a new high-quality dataset DOI Creative Commons
Boya Liu, Lili Wang, Lei Zhang

и другие.

International Journal of Digital Earth, Год журнала: 2024, Номер 17(1)

Опубликована: Фев. 2, 2024

The air quality in China has changed due to the implementation of clean actions since 2013. Evaluating spatial pattern PM2.5 and effectiveness reducing anthropogenic emissions urban nonurban areas is crucial. Therefore, Long-term Air Pollutant dataset for (CLAP_PM2.5) was generated from 2010 2022 with a daily 0.1° resolution using random forest model integrating multiple data sources, including extensive in-situ measurements, visibility, satellite retrievals, surface upper-level meteorological other ancillary data. CLAP_PM2.5 more reliable accurate than public datasets. Analysis reveals decrease positive urban-nonurban differences higher decreasing rates most city clusters eastern China. Furthermore, separating emission contributions variability by normalization approach indicates that contribution gradually unfavorable reduction during 2013–2017 favorable decline enhancement 2018–2022, regions, areas. Overall, deweathered concentrations highlights China's significant achievements terms comprehensive actions.

Язык: Английский

Процитировано

7

Anthropogenically and meteorologically modulated summertime ozone trends and their health implications since China's clean air actions DOI

Dan Yan,

Zhipeng Jin,

Yiting Zhou

и другие.

Environmental Pollution, Год журнала: 2023, Номер 343, С. 123234 - 123234

Опубликована: Дек. 26, 2023

Язык: Английский

Процитировано

14

Evidence for Coordinated Control of PM2.5 and O3: Long-Term Observational Study in a Typical City of Central Plains Urban Agglomeration DOI Creative Commons

Chenhui Jia,

Guangxuan Yan,

Xijun Yu

и другие.

Toxics, Год журнала: 2025, Номер 13(5), С. 330 - 330

Опубликована: Апрель 23, 2025

Fine particulate matter (PM2.5) and Ozone (O3) pollution have emerged as the primary environmental challenges in China recent years. Following implementation of Air Pollution Prevention Control Action Plan, a substantial decline PM2.5 concentrations was observed, while O3 exhibited an increasing trend across country. Here, we investigated long-term from 2015 to 2022 Xinxiang City, typical city within Central Plains urban agglomeration. Our findings indicate that hourly average increased by 3.41 μg m-3 yr-1, with characterized two distinct phases (Phase I, 2015-2018; Phase II, 2019-2022). Interestingly, rate concentration I (7.89 m-3) notably higher than II (2.89 m-3). The Random Forest (RF) model employed identify key factors influencing during phases. significant dropping could be responsible for increase. In reductions nitrogen dioxide (NO2) unfavorable meteorological conditions were major drivers continued increase O3. Observation-Based Model (OBM) developed further explore role formation. results suggest can influence chemical sensitivity regime through heterogeneous reactions changes photolysis rates. addition, relatively high City years underscores its Future efforts should focus on joint control improve air quality

Язык: Английский

Процитировано

0

Evaluating the effects of meteorology and emission changes on ozone in different regions over China based on machine learning DOI
Boya Liu, Yuanyuan Li, Lili Wang

и другие.

Atmospheric Pollution Research, Год журнала: 2024, Номер unknown, С. 102354 - 102354

Опубликована: Ноя. 1, 2024

Язык: Английский

Процитировано

2

Machine Learning Integrated PMF Model Reveals Influencing Factors of Ozone Pollution in a Coal Chemical Industry City at the Jiangsu-Shandong-Henan-Anhui Boundary DOI
Chaolong Wang, Xiaofei Qin, Yisheng Zhang

и другие.

Atmospheric Environment, Год журнала: 2024, Номер 342, С. 120916 - 120916

Опубликована: Ноя. 2, 2024

Язык: Английский

Процитировано

2

Elucidating Contributions of Meteorology and Emissions to O3 Variations in Coastal City of China during 2019-2022: insights from VOCs Sources DOI

Keran Zhang,

Qiaoling Chen,

Youwei Hong

и другие.

Environmental Pollution, Год журнала: 2024, Номер unknown, С. 125491 - 125491

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

2

The influence of dry deposition on surface ozone simulations under different planetary boundary layer schemes over eastern China DOI
Danyang Li, Zehui Liu, Mi Zhou

и другие.

Atmospheric Environment, Год журнала: 2024, Номер 327, С. 120514 - 120514

Опубликована: Апрель 7, 2024

Язык: Английский

Процитировано

1