Author
Listed:
- Shaowei Zhang
(School of Human Settlements, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)
- Chen Li
(School of Human Settlements, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)
- Shennian Zhang
(School of Architecture, Xi’an University of Architecture and Technology, Xi’an 710055, China)
- Ling Song
(School of Human Settlements, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)
- Chenming Zhang
(School of Human Settlements, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)
- Pu Jia
(School of Human Settlements, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)
Abstract
Rapid urbanization and climate change have intensified the interconnected challenges of surface heating, air pollution, and declining ecosystem functions, with important implications for regional sustainability. Taking Henan Province, China, as the study area, this study selected 2013, 2018, and 2023 as representative years and used land surface temperature (LST), fine particulate matter (PM2.5), ozone (O3), and net primary productivity (NPP) to characterize the thermal environment, air pollution, and carbon sequestration capacity. Pearson correlation analysis, multiple linear regression, and XGBoost-SHAP were integrated to examine bivariate associations, independent linear associations, factor importance, nonlinear responses, and potential threshold characteristics associated with natural, ecological, and anthropogenic factors. The results showed marked spatial differences in the four environmental variables. The multiple linear regression models explained 57.4–69.0% of the variation in LST, 23.8–72.0% in O3, 81.0–84.8% in PM2.5, and 57.4–62.5% in NPP. Natural factors generally showed relatively large and temporally stable standardized coefficients. Precipitation and potential evapotranspiration were positively associated with LST, whereas elevation and precipitation were negatively associated with PM2.5 and O3. NDVI showed an environmentally favorable pattern, being negatively associated with LST, PM2.5, and O3 but positively associated with NPP. Anthropogenic variables generally exhibited smaller and less temporally stable coefficients. The XGBoost models demonstrated good predictive performance, particularly for PM2.5, with R 2 values of 0.945, 0.920, and 0.905 in 2013, 2018, and 2023, respectively. SHAP analysis identified DEM, PRE, PET, and NDVI as the main contributors to model predictions and revealed nonlinear responses and potential threshold characteristics. These findings indicate that coordinated management of vegetation cover, hydrothermal conditions, and urban development can support heat mitigation, air pollution control, ecosystem productivity, and more sustainable, climate-resilient, and low-carbon development in rapidly urbanizing regions.
Suggested Citation
Shaowei Zhang & Chen Li & Shennian Zhang & Ling Song & Chenming Zhang & Pu Jia, 2026.
"Integrated Driving Mechanisms of the Thermal Environment, Air Pollution, and Carbon Sequestration Capacity in Henan Province, China,"
Sustainability, MDPI, vol. 18(13), pages 1-33, July.
Handle:
RePEc:gam:jsusta:v:18:y:2026:i:13:p:6708-:d:1982196
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