A Study on the Nonlinear Lag Effects of Meteorological Factors on PM2.5 Concentrations in Nanjing, China: Based on GAM and DLNM Models

Yushan Li; Hong Chang. Song; Huan Yang; Qian Wu; Dan Wang; Yao Tang; Zhongyang Wang; Aiming Liu; Shengbiao Wu; Bin Chen; Chao He

doi:10.1039/d6ea00049e

January 1, 2026Environmental Science AtmospheresOpen Access

A Study on the Nonlinear Lag Effects of Meteorological Factors on PM2.5 Concentrations in Nanjing, China: Based on GAM and DLNM Models

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Key Points

This research aims to understand how different weather conditions influence PM2.5 levels over time in Nanjing.
Utilized generalized additive models (GAM) and distributed lag nonlinear models (DLNM) for analysis.
Analyzed data on meteorological factors and PM2.5 concentrations collected from Nanjing over a specified period.
Assessed the lag effects of meteorological factors on PM2.5 concentrations.
Identified significant nonlinear lag effects of temperature and humidity on PM2.5 levels.
Demonstrated that decreases in temperature substantially correlate with increased PM2.5 concentrations in the following days.
Found a delayed impact of rainfall on reducing PM2.5 levels, with notable differences based on season.

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Implication

Examines the impact of meteorological factors on PM2.5 concentrations in Nanjing, indicating critical environmental health insights.

Abstract

Fine particulate matter(PM2.5), as the predominant atmospheric pollutant in China, poses a serious threat to public health and socioeconomic development. Meteorological factors play a critical role in shaping its occurrence...

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Cite This Study

Li et al. (2026) studied this question.

synapsesocial.com/papers/6a11447c48a409a3a49deb8d https://doi.org/10.1039/d6ea00049e

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A Study on the Nonlinear Lag Effects of Meteorological Factors on PM2.5 Concentrations in Nanjing, China: Based on GAM and DLNM Models

Key Points

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

A Study on the Nonlinear Lag Effects of Meteorological Factors on PM2.5 Concentrations in Nanjing, China: Based on GAM and DLNM Models

Key Points

Ask about this paper

Implication

Abstract

Discussion

Cite This Study

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