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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/nhess-2017-341
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/nhess-2017-341
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  05 Feb 2018

05 Feb 2018

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This preprint has been withdrawn by the authors.

An inversion of fine particulate matter (PM2.5) mass concentrations based on the air quality index (AQI) during dust prone periods in Hotan oasis, Sinkiang

Ju Chunyan1,2,*, Zhang Zili3,*, Zhou Xu4,*, and He Qing2 Ju Chunyan et al.
  • 1School of Management, Xinjiang Agricultural University, Urumqi, China
  • 2Institute of Desert Meteorology, China Meteorological Administration, Urumqi, China
  • 3Zhejiang Environment Monitoring Centre, Hangzhou, China
  • 4Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, China
  • *These authors contributed equally to this work.

Abstract. Ambient air pollution has been implicated as a major environmental problem in Urban development process. The objective of this publication is to analyse deeply the correlation coefficient of PM2.5 and AOD and aerosol optical depth (AOD). Surface PM2.5 observation data and AOD were investigated from March to June in 2015 and 2016. Hourly PM2.5 data are sampled from air quality monitoring stations in Hotan oasis. The AOD data are derived from Terra and Aqua at 10 km resolution. The satellite passed the area at about 13:30 AM and 15:30 PM,respectively.By using the matched PM2.5 and AOD data,the spatial and temporal distribution characteristics are discussed, and the correlation coefficient of PM2.5 versus AOD are estimated. The results show that PM2.5 mass concentration and AOD vary greatly in different pollution weather. This phenomenon may be associated with data collection time, and other meteorological factors. Regression analysis based on typical air pollution show subsection fitting effect is relatively good choice, and regression is relatively well in Hazardous and serious pollution weather. Fitting analysis is good for PM2.5 in different level of air pollution, and sources and pollutants transmission have difference.

This preprint has been withdrawn.

Ju Chunyan et al.

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Ju Chunyan et al.

Ju Chunyan et al.

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Short summary
The objective of this publication is to analyse deeply the correlation coefficient of PM2.5 and AOD and aerosol optical depth (AOD). By using the matched Surface PM2.5 observation and AOD data from March to June in 2015 and 2016, the spatial and temporal distribution characteristics are discussed, and the correlation coefficient of PM2.5 versus AOD are estimated. The results show that PM2.5 mass concentration and AOD vary greatly in different pollution weather.
The objective of this publication is to analyse deeply the correlation coefficient of PM2.5 and...
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