Author(s)

Huanzheng Zhu ¹, Jiaqiang Xie ¹, Chenglong Chao ¹, Zhengxun Fang ¹

Affiliation(s)

¹ School of Mechanical and Electronic Engineering, Shandong Jianzhu University, Jinan, 250101, China

Corresponding Author

Huanzheng Zhu

ABSTRACT

With the advancement of urbanization and industrialization, energy consumption has increased, resulting in a surge in the discharge of harmful pollutants, and the problem of air pollution has become increasingly serious. The aim of this study is to provide decision support for improving air quality. By analyzing the data of AQI and six kinds of pollutants in Nanjing from 2018 to 2023, the current situation of air quality in Nanjing was explored, and the air quality level was evaluated from multiple perspectives. The factors affecting air quality were also discussed, and the correlation between pollutants, meteorological factors and economic factors and AQI was analyzed by using multiple linear regression, random forest and grey correlation analysis. The study found that the Air quality Index (AQI) in Nanjing was high in spring and winter and low in autumn and summer, and the air quality grade gradually improved from 2018 to 2022. According to the model regression, the key meteorological factors affecting the air quality of Nanjing are temperature and precipitation, and the important economic factors are the proportion of the secondary industry in GDP, the green coverage rate of built-up areas and the population density.

KEYWORDS

Air Quality Index, Random Forest, Multiple Linear Regression, Grey Correlation

CITE THIS PAPER

Huanzheng Zhu, Jiaqiang Xie, Chenglong Chao, Zhengxun Fang, Analysis of influencing factors of air quality in Nanjing based on linear regression algorithm. Environment, Resource and Ecology Journal (2025) Vol. 9: 63-73. DOI: http://dx.doi.org/10.23977/erej.2025.090108.

REFERENCES

[1] Cheng Hanxi, Zhu Hongxia, Wang Jing, et al. Impact of air pollution control on air quality in Beijing-Tianjin-Hebei region [J]. Environmental Impact Assessment, 2019, 46(06):78-85. 
[2] Huang Yu, Liu Jinfu, You Tiange, et al. Air quality detection in Fujian Province based on multivariate statistics [J]. Regional Governance, 2019, (42):45-47.
[3] Li Jiacheng, Liang Longyue. Air quality prediction and Influencing factor identification based on Machine learning method [J]. Computer Technology and Development, 2019, 34(01):164-170. 
[4] Ren J H. Evaluation method and application of meteorological factors on atmospheric pollutant concentration [D]. Chinese Academy of Environmental Sciences, 2024. 
[5] Huang Qiaolong, Cai Xuexiong. Digital economy development and air quality improvement: An analysis based on innovation-driven perspective [J]. Journal of Enterprise Economics, 2018, 43(07):91-101.

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