Ozone Pollution in Chinese Cities: Spatiotemporal Variations and Their Relationships with Meteorological and Other Pollution Factors (2016–2020)
With the acceleration of urbanization, ozone (O<sub>3</sub>) pollution has become increasingly serious in many Chinese cities. This study analyzes the temporal and spatial characteristics of O<sub>3</sub> based on monitoring and meteorological data for 366 cities and national...
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MDPI AG
2022-06-01
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| Series: | Atmosphere |
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| Online Access: | https://www.mdpi.com/2073-4433/13/6/908 |
| _version_ | 1797490125135937536 |
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| author | Qiang Ge Xusheng Zhang Kun Cai Yang Liu |
| author_facet | Qiang Ge Xusheng Zhang Kun Cai Yang Liu |
| author_sort | Qiang Ge |
| collection | DOAJ |
| description | With the acceleration of urbanization, ozone (O<sub>3</sub>) pollution has become increasingly serious in many Chinese cities. This study analyzes the temporal and spatial characteristics of O<sub>3</sub> based on monitoring and meteorological data for 366 cities and national weather stations throughout China from 2016 to 2020. Least squares linear regression and Spearman’s correlation coefficient were computed to investigate the relationships of O<sub>3</sub> with various pollution factors and meteorological conditions. Global Moran’s I and the Getis–Ord index <inline-formula><math display="inline"><semantics><mrow><msubsup><mi mathvariant="normal">G</mi><mi mathvariant="normal">i</mi><mo>*</mo></msubsup></mrow></semantics></math></inline-formula> were adopted to reveal the spatial agglomeration of O<sub>3</sub> pollution in Chinese cities and characterize the temporal and spatial characteristics of hot and cold spots. The results show that the national proportion of cities with an annual concentration exceeding 160 μg·m<sup>−3</sup> increased from 21.6% in 2016 to 50.9% in 2018 but dropped to 21.5% in 2020; these cities are concentrated mainly in Central China (CC) and East China (EC). Throughout most of China, the highest seasonal O<sub>3</sub> concentrations occur in summer, while the highest values in South China (SC) and Southwest China (SWC) occur in autumn and spring, respectively. The highest monthly O<sub>3</sub> concentration reached 200 μg·m<sup>−3</sup> in North China (NC) in June, while the lowest value was 60 μg·m<sup>−3</sup> in Northeast China (NEC) in December. O<sub>3</sub> is positively correlated with the ground surface temperature (GST) and sunshine duration (SSD) and negatively correlated with pressure (PRS) and relative humidity (RHU). Wind speed (WIN) and precipitation (PRE) were positively correlated in all regions except SC. O<sub>3</sub> concentrations are significantly differentiated in space: O<sub>3</sub> pollution is high in CC and EC and relatively low in the western and northeastern regions. The concentration of O<sub>3</sub> exhibits obvious agglomeration characteristics, with hot spots being concentrated mainly in NC, CC and EC. |
| first_indexed | 2024-03-10T00:26:29Z |
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| id | doaj.art-3d364ef125c34354895753cc0d20de0f |
| institution | Directory Open Access Journal |
| issn | 2073-4433 |
| language | English |
| last_indexed | 2024-03-10T00:26:29Z |
| publishDate | 2022-06-01 |
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| spelling | doaj.art-3d364ef125c34354895753cc0d20de0f2023-11-23T15:32:34ZengMDPI AGAtmosphere2073-44332022-06-0113690810.3390/atmos13060908Ozone Pollution in Chinese Cities: Spatiotemporal Variations and Their Relationships with Meteorological and Other Pollution Factors (2016–2020)Qiang Ge0Xusheng Zhang1Kun Cai2Yang Liu3School of Computer and Information Engineering, Henan University, Kaifeng 475004, ChinaSchool of Computer and Information Engineering, Henan University, Kaifeng 475004, ChinaSchool of Computer and Information Engineering, Henan University, Kaifeng 475004, ChinaSchool of Computer and Information Engineering, Henan University, Kaifeng 475004, ChinaWith the acceleration of urbanization, ozone (O<sub>3</sub>) pollution has become increasingly serious in many Chinese cities. This study analyzes the temporal and spatial characteristics of O<sub>3</sub> based on monitoring and meteorological data for 366 cities and national weather stations throughout China from 2016 to 2020. Least squares linear regression and Spearman’s correlation coefficient were computed to investigate the relationships of O<sub>3</sub> with various pollution factors and meteorological conditions. Global Moran’s I and the Getis–Ord index <inline-formula><math display="inline"><semantics><mrow><msubsup><mi mathvariant="normal">G</mi><mi mathvariant="normal">i</mi><mo>*</mo></msubsup></mrow></semantics></math></inline-formula> were adopted to reveal the spatial agglomeration of O<sub>3</sub> pollution in Chinese cities and characterize the temporal and spatial characteristics of hot and cold spots. The results show that the national proportion of cities with an annual concentration exceeding 160 μg·m<sup>−3</sup> increased from 21.6% in 2016 to 50.9% in 2018 but dropped to 21.5% in 2020; these cities are concentrated mainly in Central China (CC) and East China (EC). Throughout most of China, the highest seasonal O<sub>3</sub> concentrations occur in summer, while the highest values in South China (SC) and Southwest China (SWC) occur in autumn and spring, respectively. The highest monthly O<sub>3</sub> concentration reached 200 μg·m<sup>−3</sup> in North China (NC) in June, while the lowest value was 60 μg·m<sup>−3</sup> in Northeast China (NEC) in December. O<sub>3</sub> is positively correlated with the ground surface temperature (GST) and sunshine duration (SSD) and negatively correlated with pressure (PRS) and relative humidity (RHU). Wind speed (WIN) and precipitation (PRE) were positively correlated in all regions except SC. O<sub>3</sub> concentrations are significantly differentiated in space: O<sub>3</sub> pollution is high in CC and EC and relatively low in the western and northeastern regions. The concentration of O<sub>3</sub> exhibits obvious agglomeration characteristics, with hot spots being concentrated mainly in NC, CC and EC.https://www.mdpi.com/2073-4433/13/6/908ozonetemporal and spatial characteristicsinfluencing factorsagglomeration characteristicsChinese cities |
| spellingShingle | Qiang Ge Xusheng Zhang Kun Cai Yang Liu Ozone Pollution in Chinese Cities: Spatiotemporal Variations and Their Relationships with Meteorological and Other Pollution Factors (2016–2020) Atmosphere ozone temporal and spatial characteristics influencing factors agglomeration characteristics Chinese cities |
| title | Ozone Pollution in Chinese Cities: Spatiotemporal Variations and Their Relationships with Meteorological and Other Pollution Factors (2016–2020) |
| title_full | Ozone Pollution in Chinese Cities: Spatiotemporal Variations and Their Relationships with Meteorological and Other Pollution Factors (2016–2020) |
| title_fullStr | Ozone Pollution in Chinese Cities: Spatiotemporal Variations and Their Relationships with Meteorological and Other Pollution Factors (2016–2020) |
| title_full_unstemmed | Ozone Pollution in Chinese Cities: Spatiotemporal Variations and Their Relationships with Meteorological and Other Pollution Factors (2016–2020) |
| title_short | Ozone Pollution in Chinese Cities: Spatiotemporal Variations and Their Relationships with Meteorological and Other Pollution Factors (2016–2020) |
| title_sort | ozone pollution in chinese cities spatiotemporal variations and their relationships with meteorological and other pollution factors 2016 2020 |
| topic | ozone temporal and spatial characteristics influencing factors agglomeration characteristics Chinese cities |
| url | https://www.mdpi.com/2073-4433/13/6/908 |
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