Analysis of Synergistic Changes in PM2.5 and O3 Concentrations Based on Structural Equation Model Study DOI Creative Commons
Zhangwen Su, Liming Yang, Yimin Chen

et al.

Atmosphere, Journal Year: 2024, Volume and Issue: 15(11), P. 1374 - 1374

Published: Nov. 14, 2024

Given the increasing importance of effectively identifying synergistic changes between PM2.5 and O3 comprehensively analyzing their impact on air quality management in China, we employ Sen+Mann–Kendall (Sen+M-K) trend test this study to examine temporal spatial variation trends Yangtze River Delta (YRD), from 2003 2020. We identified regions where these pollutants exhibited established pathways potential drivers, using geographically weighted random forest algorithms structural equation modeling. The results revealed as follows: (1) Overall, concentrations show a decreasing trend, while exhibit an YRD. Analysis combined indicates that approximately 95% area displays opposing for O3, with only about 4% southern region showing both pollutants. (2) Drought average temperature are main drivers areas experiencing changes. Their effects alleviate aggregation reduce formation VOCs, indirectly reducing generation negative effect concentration may indicate existence nonlinear complex interaction drivers. NOx VOCs play important dual roles conversion pollutants, although overall is smaller than meteorological factors. They produce significant indirect through other human factors, further affecting O3. In without coordinated changes, factors remains unchanged, relationship two anthropogenic emission sources complex, different directions levels involved. This provides detailed insights into YRD offers scientific basis environmental authorities develop more comprehensive targeted strategies balancing control pollution.

Language: Английский

Impacts of land use transitions on ecosystem services: A research framework coupled with structure, function, and dynamics DOI
Xinhui Feng, Yan Li, Xize Wang

et al.

The Science of The Total Environment, Journal Year: 2023, Volume and Issue: 901, P. 166366 - 166366

Published: Aug. 18, 2023

Language: Английский

Citations

27
Impact of territorial spatial landscape pattern on PM2.5 and O3 concentrations in the Yangtze River delta urban agglomeration: Exploration and planning strategies DOI
Xin Chen, Fang Wei

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 452, P. 142172 - 142172

Published: April 10, 2024

Language: Английский

Citations

10
Identifying the spatiotemporal patterns and natural and socioeconomic influencing factors of PM2.5 and O3 pollution in China DOI Creative Commons
Dongsheng Zhan, Zi-Chen Wang,

Hongyang Xiang

et al.

PLoS ONE, Journal Year: 2025, Volume and Issue: 20(2), P. e0317691 - e0317691

Published: Feb. 13, 2025

To promote collaborative governance of PM 2.5 and O 3 pollution, understanding their spatiotemporal patterns determining factors is crucial to control air pollution in China. Using the ground-monitored data encompassing concentrations 2019 across 337 Chinese cities, this study explores concentrations, then employed Multi-scale Geographically Weighted Regression (MGWR) model examine socioeconomic natural affecting or concentrations. The results show that exhibit distinct monthly U-shaped inverted temporal fluctuation respectively. Spatially, both pollutants manifest spatial clustering characteristic a certain degree bivariate correlation. Elevated are predominantly concentrated on north central China, as well Xinjiang Autonomous Region, whereas higher distributed widely north, east, northwest MGWR outperforms traditional OLS global regression models, evidenced by its enhanced goodness-of-fit metrics. Specifically, R 2 values for models notably high, at 0.842 0.861, Socioeconomic found have multi-scale effects On average, positively correlations with population density, proportion added value secondary industry GDP, wind speed, relative humidity, atmospheric pressure, but negatively relationship per capita road urban greening, temperature, precipitation, sunshine duration. In contrast, also associated energy consumption, duration, correlated temperature. Our findings offer valuable insights inform development comprehensive management policies developing countries.

Language: Английский

Citations

1
Understanding the Dynamics of PM2.5 Concentration Levels in China: A Comprehensive Study of Spatio-Temporal Patterns, Driving Factors, and Implications for Environmental Sustainability DOI Open Access
Yuxin Miao, Chunmei Geng, Yuanyuan Ji

et al.

Sustainability, Journal Year: 2025, Volume and Issue: 17(4), P. 1742 - 1742

Published: Feb. 19, 2025

Over the past decade, China’s air quality has improved significantly. To further mitigate concentration levels of fine particulate matter (PM2.5), this study analyzed spatio-temporal evolution PM2.5 concentrations from 2012 to 2022. Furthermore, integrated generalized additive model (GAM) and GeoDetector investigate main driving factors explored complex response relationships between these concentrations. The results showed following: (1) annual average in China peaked 2013. reductions each city ranged 1.48 7.33 μg/m3. In year, were always consistently higher north east lowest northeast southwest China. (2) terms spatial distribution, North Plain, Middle Lower Yangtze River Sichuan Basin exhibited highest high aggregation characteristics. (3) analysis identified SO2, NO2, CO meteorological conditions as important influencing differentiation PM2.5. GAM that factors, such temperature, atmospheric pressure, wind speed, precipitation, generally had specific inflection points their effects on levels. relationship with gross domestic product population density followed an inverted U shape. under land use types cropland, barren, impervious, water than others. decreased significantly all types. Our work can be used a strong basis for providing insights crucial developing long-term pollution control strategies promoting environmental sustainability.

Language: Английский

Citations

0
Spatiotemporal distribution of PM2.5 concentrations in Shaanxi Province, China, and its responses to land use changes and meteorological factors DOI
Yu Zhao

Journal of Atmospheric and Solar-Terrestrial Physics, Journal Year: 2025, Volume and Issue: unknown, P. 106494 - 106494

Published: March 1, 2025

Language: Английский

Citations

0
Exploring PM2.5 and O3 disparities and synergies management through integrated natural and sociology-environmental drivers in the YRD DOI

Fanmei Zeng,

Chu Ren,

Weiqing Wang

et al.

Air Quality Atmosphere & Health, Journal Year: 2025, Volume and Issue: unknown

Published: April 21, 2025

Language: Английский

Citations

0
Multi-year (2015-2023) trend and key factors of bioaerosols in urban atmosphere: A case study in Xi’an DOI
Tantan Tan,

Gaoshan Zhang,

Chao Liu

et al.

Atmospheric Environment, Journal Year: 2025, Volume and Issue: unknown, P. 121258 - 121258

Published: April 1, 2025

Language: Английский

Citations

0
Spatiotemporal variations in the association between PM2.5 and ozone in the yangtze river economic belt: Impacts of meteorological and emissions factors DOI

Lei Wang,

Kai Qin,

Bingxue Zhao

et al.

Atmospheric Environment, Journal Year: 2024, Volume and Issue: 329, P. 120534 - 120534

Published: April 24, 2024

Language: Английский

Citations

3
Estimation of Near-Surface High Spatiotemporal Resolution Ozone Concentration in China Using Himawari-8 AOD DOI Creative Commons

Yixuan Wang,

Chongshui Gong, Li Dong

et al.

Remote Sensing, Journal Year: 2025, Volume and Issue: 17(3), P. 528 - 528

Published: Feb. 4, 2025

Near-surface ozone is a secondary pollutant, and its high concentrations pose significant risks to human plant health. Based on an Extra Tree (ET) model, this study estimated near-surface with the spatiotemporal resolution based Himawari-8 aerosol optical depth (AOD) data meteorological variables from 1 January 2016 31 December 2020. The SHapley Additive exPlanation (SHAP) method was employed evaluate contribution of AOD factors concentration. results indicate that (1) ET model achieves sample-based cross-validation R2 0.75–0.87 RMSE (μg/m3) 17.96–20.30. coefficient determination (R2) values in spring, summer, autumn, winter are 0.81, 0.80, 0.87, 0.75, respectively. (2) Higher temperature boundary layer heights were found positively contribute concentration, whereas higher relative humidity exerted negative influence. (3) From 11:00 15:00 (Beijing time, UTC+08:00), concentration increases gradually, highest occurring followed by spring. This has obtained spatial temporal data, offering valuable insights for development fine-scale pollution prevention control strategies.

Language: Английский

Citations

0
Contribution of ecological restoration projects to long-term changes in PM2.5 DOI Creative Commons

Yulu Yang,

Mingchang Shi, Baojian Liu

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 159, P. 111630 - 111630

Published: Jan. 27, 2024

Fine particulate matter (PM2.5) concentration, a crucial indicator reflecting changes in air quality, has frequently been used previous studies. However, the effects of large-scale ecological restoration (ER) projects on PM2.5 concentrations are often overlooked. Therefore, we net primary productivity (NPP) as an ER engineering benefits, ensemble empirical modal decomposition (EEMD) to reveal trend linear and nonlinear relationships driven by different types amounts projects, utilized Extreme Gradient Boosting (XGBoost) Shapley's Additive Interpretation (SHAP) values quantify impact each factor long-term concentrations. The results suggest that: (1) better describes change, with shift from increasing decreasing areas covering 74.15% China's area, especially four major zones; (2) concentration exhibits regional effects, L-L H-H aggregation account for larger proportion distributed low high concentrations, respectively. (3) year 1990 marks turning point 36.8% regions. Across regions emerge: dramatic increase before implementation, followed slowing growth initial stages project, ultimately gradual decrease. (4) While contribution decrease is lower than caused human activities climate plant newly main which project suppresses its growth. These findings highlight influence addition provide theoretical basis scientific technological support quantifying suppression pollution projects.

Language: Английский

Citations

3