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Theoretical and Applied Climatology

, Volume 134, Issue 1–2, pp 25–36 | Cite as

Important meteorological variables for statistical long-term air quality prediction in eastern China

  • Libo Zhang
  • Yongqiang Liu
  • Fengjun Zhao
Original Paper
  • 142 Downloads

Abstract

Weather is an important factor for air quality. While there have been increasing attentions to long-term (monthly and seasonal) air pollution such as regional hazes from land-clearing fires during El Niño, the weather-air quality relationships are much less understood at long-term than short-term (daily and weekly) scales. This study is aimed to fill this gap through analyzing correlations between meteorological variables and air quality at various timescales. A regional correlation scale was defined to measure the longest time with significant correlations at a substantial large number of sites. The air quality index (API) and five meteorological variables during 2001–2012 at 40 eastern China sites were used. The results indicate that the API is correlated to precipitation negatively and air temperature positively across eastern China, and to wind, relative humidity and air pressure with spatially varied signs. The major areas with significant correlations vary with meteorological variables. The correlations are significant not only at short-term but also at long-term scales, and the important variables are different between the two types of scales. The concurrent regional correlation scales reach seasonal at p < 0.05 and monthly at p < 0.001 for wind speed and monthly at p < 0.01 for air temperature and relative humidity. Precipitation, which was found to be the most important variable for short-term air quality conditions, and air pressure are not important for long-term air quality. The lagged correlations are much smaller in magnitude than the concurrent correlations and their regional correction scales are at long term only for wind speed and relative humidity. It is concluded that wind speed should be considered as a primary predictor for statistical prediction of long-term air quality in a large region over eastern China. Relative humidity and temperature are also useful predictors but at less significant levels.

Notes

Acknowledgements

The air pollution index (API) data were obtained from the Ministry of Environmental Protection of China. The meteorological data were obtained from the China Meteorological Science Data Sharing Service network. This study was supported by the China Natural Science Foundation under project 31670661 and the USDA Forest Service.

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Copyright information

© US Government (outside the USA) 2017

Authors and Affiliations

  1. 1.International Center for Ecology, Meteorology and Environment, College of Applied MeteorologyNanjing University of Information Science and TechnologyNanjingChina
  2. 2.Center for Forest Disturbance ScienceUSDA Forest ServiceAthensUSA
  3. 3.Research Institute of Forest Ecology, Environment and ProtectionChinese Academy of ForestryBeijingChina

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