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- Socioeconomic factors of PM2. 5 concentrations in 152 Chinese cities . . .
Therefore, this study aims to identify the key impact factors of PM2 5 concentration in 152 Chinese cities in eastern, central, and western China by using Logarithmic Mean Divisia Index (LMDI) method
- Socioeconomic factors of PM2. 5 concentrations in 152 Chinese cities . . .
This is the first study that provides a full picture of the key impact factors on Chinese urban PM2 5 concentration The identified key impact factors can serve as the evidence and guidance for the authorities of China's cities to tailor their strategies towards PM2 5 concentration reduction
- Socioeconomic factors of PM2. 5 concentrations in 152 Chinese cities . . .
Socioeconomic factors of PM2 5 concentrations in 152 Chinese cities: Decomposition analysis using LMDI
- Analysis of the Social and Economic Factors Influencing PM2. 5 . . . - MDPI
China is facing the challenge of severe PM2 5 concentrations, especially in urban areas with a high population density Understanding the key factors that influence PM2 5 concentrations is fundamental for the adoption of targeted measures
- Analysis of the Social and Economic Factors Influencing PM2. 5 Emissions . . .
China is facing the challenge of severe PM2 5 concentrations, especially in urban areas with a high population density Understanding the key factors that influence PM2 5 concentrations is
- Analyzing the socioeconomic determinants of PM2. 5 air . . . - Springer
At regional levels, Zhang et al (2019) identified the socioeconomic factors of PM2 5 concentrations in 152 Chinese cities: EmI and EnI as the principal inhibitors and EO and population as the main drivers
- Examining the Effects of Socioeconomic Development on Fine . . . - PubMed
Results show that the overall economic level was developing well, with a spatial distribution trend of high in the east and low in the west With a large positive spatial correlation and a highly concentrated clustering pattern, the PM2 5 concentration declined in 2020
- How do socioeconomic factors influence urban PM2. 5 pollution in China . . .
In this study, exploratory spatial data analysis (ESDA) was used to examine the agglomeration characteristics of PM 2 5 pollution in 273 cities of China from 2010 to 2016, and then we employed a GWR model to explain the different impacts of socioeconomic factors on PM 2 5 pollution in these cities The following conclusions can be drawn from
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