Identifying Spatiotemporal Heterogeneity of PM<sub>2.5</sub> Concentrations and the Key Influencing Factors in the Middle and Lower Reaches of the Yellow River
Fine particulate matter (PM<sub>2.5</sub>) is a harmful air pollutant that seriously affects public health and sustainable urban development. Previous studies analyzed the spatial pattern and driving factors of PM<sub>2.5</sub> concentrations in different regions. However, th...
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MDPI AG
2022-05-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/14/11/2643 |
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| author | Hongbo Zhao Yaxin Liu Tianshun Gu Hui Zheng Zheye Wang Dongyang Yang |
| author_facet | Hongbo Zhao Yaxin Liu Tianshun Gu Hui Zheng Zheye Wang Dongyang Yang |
| author_sort | Hongbo Zhao |
| collection | DOAJ |
| description | Fine particulate matter (PM<sub>2.5</sub>) is a harmful air pollutant that seriously affects public health and sustainable urban development. Previous studies analyzed the spatial pattern and driving factors of PM<sub>2.5</sub> concentrations in different regions. However, the spatiotemporal heterogeneity of various influencing factors on PM<sub>2.5</sub> was ignored. This study applies the geographically and temporally weighted regression (GTWR) model and geographic information system (GIS) analysis methods to investigate the spatiotemporal heterogeneity of PM<sub>2.5</sub> concentrations and the influencing factors in the middle and lower reaches of the Yellow River from 2000 to 2017. The findings indicate that: (1) the annual average of PM<sub>2.5</sub> concentrations in the middle and lower reaches of the Yellow River show an overall trend of first rising and then decreasing from 2000 to 2017. In addition, there are significant differences in inter-province PM<sub>2.5</sub> pollution in the study area, the PM<sub>2.5</sub> concentrations of Tianjin City, Shandong Province, and Henan Province were far higher than the overall mean value of the study area. (2) PM<sub>2.5</sub> concentrations in western cities showed a declining trend, while it had a gradually rising trend in the middle and eastern cities of the study area. Meanwhile, the PM<sub>2.5</sub> pollution showed the characteristics of path dependence and region locking. (3) the PM<sub>2.5</sub> concentrations had significant spatial agglomeration characteristics from 2000 to 2017. The “High-High (H-H)” clusters were mainly concentrated in the southern Hebei Province and the northern Henan Province, and the “Low-Low (L-L)” clusters were concentrated in northwest marginal cities in the study area. (4) The influencing factors of PM<sub>2.5</sub> have significant spatiotemporal non-stationary characteristics, and there are obvious differences in the direction and intensity of socio-economic and natural factors. Overall, the variable of temperature is one of the most important natural conditions to play a positive impact on PM<sub>2.5</sub>, while elevation makes a strong negative impact on PM<sub>2.5</sub>. Car ownership and population density are the main socio-economic influencing factors which make a positive effect on PM<sub>2.5</sub>, while the variable of foreign direct investment (FDI) plays a strong negative effect on PM<sub>2.5</sub>. The results of this study are useful for understanding the spatiotemporal distribution characteristics of PM<sub>2.5</sub> concentrations and formulating policies to alleviate haze pollution by policymakers in the Yellow River Basin. |
| first_indexed | 2024-03-10T00:55:13Z |
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| language | English |
| last_indexed | 2024-03-10T00:55:13Z |
| publishDate | 2022-05-01 |
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| spelling | doaj.art-e10998460ce64c41987e57982dc262cc2023-11-23T14:45:03ZengMDPI AGRemote Sensing2072-42922022-05-011411264310.3390/rs14112643Identifying Spatiotemporal Heterogeneity of PM<sub>2.5</sub> Concentrations and the Key Influencing Factors in the Middle and Lower Reaches of the Yellow RiverHongbo Zhao0Yaxin Liu1Tianshun Gu2Hui Zheng3Zheye Wang4Dongyang Yang5Key Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization Jointly Built by Henan Province and Ministry of Education, Henan University, Kaifeng 475001, ChinaKey Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization Jointly Built by Henan Province and Ministry of Education, Henan University, Kaifeng 475001, ChinaKey Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization Jointly Built by Henan Province and Ministry of Education, Henan University, Kaifeng 475001, ChinaKey Laboratory of Geospatial Technology for Middle and Lower Yellow River Regions, Ministry of Education, College of Environment and Planning, Henan University, Kaifeng 475004, ChinaThe Kinder Institute for Urban Research, Rice University, 6100 Main St Kraft, Hall, 3rd Floor, Houston, TX 77005, USAKey Research Institute of Yellow River Civilization and Sustainable Development & Collaborative Innovation Center on Yellow River Civilization Jointly Built by Henan Province and Ministry of Education, Henan University, Kaifeng 475001, ChinaFine particulate matter (PM<sub>2.5</sub>) is a harmful air pollutant that seriously affects public health and sustainable urban development. Previous studies analyzed the spatial pattern and driving factors of PM<sub>2.5</sub> concentrations in different regions. However, the spatiotemporal heterogeneity of various influencing factors on PM<sub>2.5</sub> was ignored. This study applies the geographically and temporally weighted regression (GTWR) model and geographic information system (GIS) analysis methods to investigate the spatiotemporal heterogeneity of PM<sub>2.5</sub> concentrations and the influencing factors in the middle and lower reaches of the Yellow River from 2000 to 2017. The findings indicate that: (1) the annual average of PM<sub>2.5</sub> concentrations in the middle and lower reaches of the Yellow River show an overall trend of first rising and then decreasing from 2000 to 2017. In addition, there are significant differences in inter-province PM<sub>2.5</sub> pollution in the study area, the PM<sub>2.5</sub> concentrations of Tianjin City, Shandong Province, and Henan Province were far higher than the overall mean value of the study area. (2) PM<sub>2.5</sub> concentrations in western cities showed a declining trend, while it had a gradually rising trend in the middle and eastern cities of the study area. Meanwhile, the PM<sub>2.5</sub> pollution showed the characteristics of path dependence and region locking. (3) the PM<sub>2.5</sub> concentrations had significant spatial agglomeration characteristics from 2000 to 2017. The “High-High (H-H)” clusters were mainly concentrated in the southern Hebei Province and the northern Henan Province, and the “Low-Low (L-L)” clusters were concentrated in northwest marginal cities in the study area. (4) The influencing factors of PM<sub>2.5</sub> have significant spatiotemporal non-stationary characteristics, and there are obvious differences in the direction and intensity of socio-economic and natural factors. Overall, the variable of temperature is one of the most important natural conditions to play a positive impact on PM<sub>2.5</sub>, while elevation makes a strong negative impact on PM<sub>2.5</sub>. Car ownership and population density are the main socio-economic influencing factors which make a positive effect on PM<sub>2.5</sub>, while the variable of foreign direct investment (FDI) plays a strong negative effect on PM<sub>2.5</sub>. The results of this study are useful for understanding the spatiotemporal distribution characteristics of PM<sub>2.5</sub> concentrations and formulating policies to alleviate haze pollution by policymakers in the Yellow River Basin.https://www.mdpi.com/2072-4292/14/11/2643PM<sub>2.5</sub> concentrationsinfluencing factorspatiotemporal heterogeneityGTWR modelthe middle and lower reaches of the Yellow River |
| spellingShingle | Hongbo Zhao Yaxin Liu Tianshun Gu Hui Zheng Zheye Wang Dongyang Yang Identifying Spatiotemporal Heterogeneity of PM<sub>2.5</sub> Concentrations and the Key Influencing Factors in the Middle and Lower Reaches of the Yellow River Remote Sensing PM<sub>2.5</sub> concentrations influencing factor spatiotemporal heterogeneity GTWR model the middle and lower reaches of the Yellow River |
| title | Identifying Spatiotemporal Heterogeneity of PM<sub>2.5</sub> Concentrations and the Key Influencing Factors in the Middle and Lower Reaches of the Yellow River |
| title_full | Identifying Spatiotemporal Heterogeneity of PM<sub>2.5</sub> Concentrations and the Key Influencing Factors in the Middle and Lower Reaches of the Yellow River |
| title_fullStr | Identifying Spatiotemporal Heterogeneity of PM<sub>2.5</sub> Concentrations and the Key Influencing Factors in the Middle and Lower Reaches of the Yellow River |
| title_full_unstemmed | Identifying Spatiotemporal Heterogeneity of PM<sub>2.5</sub> Concentrations and the Key Influencing Factors in the Middle and Lower Reaches of the Yellow River |
| title_short | Identifying Spatiotemporal Heterogeneity of PM<sub>2.5</sub> Concentrations and the Key Influencing Factors in the Middle and Lower Reaches of the Yellow River |
| title_sort | identifying spatiotemporal heterogeneity of pm sub 2 5 sub concentrations and the key influencing factors in the middle and lower reaches of the yellow river |
| topic | PM<sub>2.5</sub> concentrations influencing factor spatiotemporal heterogeneity GTWR model the middle and lower reaches of the Yellow River |
| url | https://www.mdpi.com/2072-4292/14/11/2643 |
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