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Dergiler / Atmospheric Pollution Research / 2020 / Cilt: 11 - Sayı: 3

Spatiotemporal variation of PM2.5 concentrations and its relationship to urbanization in the Yangtze river delta region, China

Dongyang YANG
Yulong CHEN
Changhong MIAO
Dexin LIU
Sayfa
491–498
DOI
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Thesefindings and the policy suggestions can contribute to effective policymaking aimed at abating PM2.5 pollutionfrom the perspective of urbanization development.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:Having experienced a rapid urbanization and socioeconomic development, China is now facing a serious PM2.5pollution issue.
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Temel Bulgular & Veri:Based on the PM2.5 concentration data during 2000–2016 in the Yangtze River Delta region, thestudy analyzed the spatiotemporal variation of PM2.5 concentrations.
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Sonuç & Katkı:Thesefindings and the policy suggestions can contribute to effective policymaking aimed at abating PM2.5 pollutionfrom the perspective of urbanization development.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:2000–2016 Verileri
⚙️Değişkenler:Alan Parametreleri

Özet

Having experienced a rapid urbanization and socioeconomic development, China is now facing a serious PM2.5pollution issue. Based on the PM2.5 concentration data during 2000–2016 in the Yangtze River Delta region, thestudy analyzed the spatiotemporal variation of PM2.5 concentrations. The study also examined the correlationbetween PM2.5 concentrations and urbanization by using the correlation analysis as well as bivariate local indicators of spatial association analysis. Furthermore, we constructed the Environmental Kuznets Curve (EKC)model to investigate their evolution relationship. The results showed that PM2.5 concentrations generally increased during 2000–2016. In most cities of the northeast of this region, PM2.5 concentrations were high; but theincreased trend were relatively slow. There was a positive correlation between urbanization and PM2.5 concentrations. However, there was a negative correlation between urbanization and the variation trend of PM2.5concentrations. There was a relationship of “high-high” aggregation between urbanization and PM2.5 concentrations in cities of southern Jiangsu province; and a relationship of “low-low” aggregation in cities ofsouthern Zhejiang province. PM2.5 concentrations had a pattern of inversed-U shape with urbanization. Thesefindings and the policy suggestions can contribute to effective policymaking aimed at abating PM2.5 pollutionfrom the perspective of urbanization development.

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Bu Makaleye Atıf Yap

YANG, D., CHEN, Y., MIAO, C., LIU, D. (2020). Spatiotemporal variation of PM2.5 concentrations and its relationship to urbanization in the Yangtze river delta region, China. Atmospheric Pollution Research, Cilt: 11 - Sayı: 3, 491–498. https://ajindex.com/articles/351435

Kaynakça (8)

  1. Anselin, L., Syabri, I., Smirnov, O., 2002. Visualizing multivariate spatial correlation with dynamically linked windows. New Tools Spat. Data Anal. Proc. Spec. Meet. 1–20.
  2. Bekhet, H.A., Othman, N.S., 2017. Impact of urbanization growth on Malaysia CO2 emissions: evidence from the dynamic relationship. J. Clean. Prod. 154, 374–388. https://doi.org/10.1016/j.jclepro.2017.03.174.
  3. Chen, M., Liu, W., Lu, D., Chen, H., Ye, C., 2018. Progress of China's new-type urbanization construction since 2014: a preliminary assessment. Cities. https://doi.org/10. 1016/j.cities.2018.02.012. Chen, M., Ye, C., Zhou, Y., 2014. Comments on Mulligan's Revisiting the urbanization curve. Cities 41, S54–S56. https://doi.org/10.1016/j.cities.2013.10.006.
  4. Gao, B., Huang, Q., He, C., Ma, Q., 2015. Dynamics of urbanization levels in China from 1992 to 2012: perspective from DMSP/OLS nighttime light data. Remote Sens. 7, 1721–1735. https://doi.org/10.3390/rs70201721.
  5. Gurjar, B.R., Ravindra, K., Nagpure, A.S., 2016. Air pollution trends over Indian megacities and their local-to-global implications. Atmos. Environ. 142, 475–495. https:// doi.org/10.1016/j.atmosenv.2016.06.030. Han, L., Zhou, W., Li, W., 2018. Growing urbanization and the impact on fine particulate matter (PM2.5) dynamics. Sustainability 1696. https://doi.org/10.3390/su10051696.
  6. Han, L., Zhou, W., Li, W., 2015. City as a major source area of fine particulate PM2.5 in China. Environ. Pollut. 206, 183–187. https://doi.org/10.1016/j.envpol.2015.06. 038. Han, L., Zhou, W., Li, W., Li, L., 2014. Impact of urbanization level on urban air quality: a case of fine particles (PM2.5) in Chinese cities. Environ. Pollut. 194, 163–170. https:// doi.org/10.1016/j.envpol.2014.07.022. Han, L., Zhou, W., Pickett, S.T.A., Li, W., Li, L., 2016. An optimum city size? the scaling relationship for urban population and fine particulate (PM2.5) concentration. Environ. Pollut. 208, 96–101. https://doi.org/10.1016/j.envpol.2015.08.039.
  7. He, C., Pan, F., Chen, T., 2016. Research progress of industrial geography in China. J. Geogr. Sci. 26, 1057–1066. https://doi.org/10.1007/s11442-016-1315-y.
  8. Ji, X., Yao, Y., Long, X., 2018. What causes PM2.5 pollution? Cross-economy empirical analysis from socioeconomic perspective. Energy Policy 119, 458–472. https://doi. org/10.1016/j.enpol.2018.04.040. Li, G., Fang, C., Wang, S., Sun, S., 2016. The effect of economic growth, urbanization, and industrialization on fine particulate matter (PM2.5) concentrations in C