Impact of the Three Gorges Dam on the spatial and temporal variation of groundwater level in Jianghan Plain using STL algorithm

Huang, Peng; Zhou, Aiguo; Ma, Chuanming; Guo, Jing; Wang, Yijie; Fan, Wei; Li, Wei

doi:10.1007/s12665-023-11110-y

Cited by 1 publication

(1 citation statement)

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“…Air pollution in China has a U-shaped distribution in terms of time, with major pollutants varying with the seasons; spatially, it has spatial clustering characteristics, with higher levels in northern China and Xinjiang, which are more vulnerable to being influenced by natural factors [18]. Scholars [19,20] analyzed the temporal variation and seasonal spatial distribution characteristics of SO 2 concentrations in the Fenwei Plain using column concentration data monitored by the Ozone Monitoring Instrument (OMI) and found that Fenwei Plain has higher levels of SO 2 and NO 2 in autumn and winter and in the flatter topography of the river valley plains. While studying the spatial and temporal distribution of air pollution in the Fenwei Plain, Hao et al [21] proposed the characteristics of the correlation between pollution concentrations and air temperature, rainfall, and air pressure.…”

Section: Introductionmentioning

confidence: 99%

Analysis of air pollution in Fenwei Plain in China based on functional spatial autoregressive combined model

Tang

Shi

2023

PLoS ONE

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The Fenwei Plain is listed as one of the most serious air pollution regions in China, along with Beijing-Tianjin-Hebei and Yangtze River Delta regions. This paper proposed a functional data analysis method to study the environmental pollution problem in the Fenwei Plain of China. Functional spatial autoregressive combined (FSAC) model with spatial autocorrelation of both the response variable and error term is developed. The model takes the SO2 concentration of Fenwei Plain as the dependent variable and the dew point temperature as the independent variable and realizes the maximum likelihood estimation using functional principal component analysis to obtain the asymptotic properties of parameter estimation and the confidence interval of the slope function. According to the findings of the empirical analysis of the Fenwei Plain, the SO2 concentration has significant seasonal characteristics and has decreased year over year for three years in a row. Winter is the season with the highest concentration on the Fenwei Plain, followed by spring and autumn, while summer is the season with the lowest concentration. Winter also has a high spatial autocorrelation. The FSAC model is more effective at fitting the concentration and dew point temperature of the Fenwei Plain in China because its mean square error (MSE) is significantly lower than that of the other models. As a result, this paper can more thoroughly study the pollution problem on the Fenwei Plain and offer guidance for prevention and control.

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Section: Introductionmentioning

confidence: 99%