Spatial and temporal analysis of Air Pollution Index and its timescale-dependent relationship with meteorological factors in Guangzhou, China, 2001-2011

Li Li, Jun Qian, Chun-Quan Ou, Ying-Xue Zhou, Cui Guo, Yuming Guo

Research output: Contribution to journalArticleResearchpeer-review

98 Citations (Scopus)

Abstract

There is an increasing interest in spatial and temporal variation of air pollution and its association with weather conditions. We presented the spatial and temporal variation of Air Pollution Index (API) and examined the associations between API and meteorological factors during 2001-2011 in Guangzhou, China. A Seasonal-Trend Decomposition Procedure Based on Loess (STL) was used to decompose API. Wavelet analyses were performed to examine the relationships between API and several meteorological factors. Air quality has improved since 2005. APIs were highly correlated among five monitoring stations, and there were substantial temporal variations. Timescale-dependent relationships were found between API and a variety of meteorological factors. Temperature, relative humidity, precipitation and wind speed were negatively correlated with API, while diurnal temperature range and atmospheric pressure were positively correlated with API in the annual cycle. Our findings should be taken into account when determining air quality forecasts and pollution control measures.

Original languageEnglish
Pages (from-to)75-81
Number of pages7
JournalEnvironmental Pollution
Volume190
DOIs
Publication statusPublished - Jul 2014
Externally publishedYes

Keywords

  • Air pollution
  • Meteorological factors
  • Seasonal-Trend Decomposition Procedure Based on Loess
  • Timescale-dependent relationship
  • Wavelet analysis

Cite this

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title = "Spatial and temporal analysis of Air Pollution Index and its timescale-dependent relationship with meteorological factors in Guangzhou, China, 2001-2011",
abstract = "There is an increasing interest in spatial and temporal variation of air pollution and its association with weather conditions. We presented the spatial and temporal variation of Air Pollution Index (API) and examined the associations between API and meteorological factors during 2001-2011 in Guangzhou, China. A Seasonal-Trend Decomposition Procedure Based on Loess (STL) was used to decompose API. Wavelet analyses were performed to examine the relationships between API and several meteorological factors. Air quality has improved since 2005. APIs were highly correlated among five monitoring stations, and there were substantial temporal variations. Timescale-dependent relationships were found between API and a variety of meteorological factors. Temperature, relative humidity, precipitation and wind speed were negatively correlated with API, while diurnal temperature range and atmospheric pressure were positively correlated with API in the annual cycle. Our findings should be taken into account when determining air quality forecasts and pollution control measures.",
keywords = "Air pollution, Meteorological factors, Seasonal-Trend Decomposition Procedure Based on Loess, Timescale-dependent relationship, Wavelet analysis",
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language = "English",
volume = "190",
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Spatial and temporal analysis of Air Pollution Index and its timescale-dependent relationship with meteorological factors in Guangzhou, China, 2001-2011. / Li, Li; Qian, Jun; Ou, Chun-Quan; Zhou, Ying-Xue; Guo, Cui; Guo, Yuming.

In: Environmental Pollution, Vol. 190, 07.2014, p. 75-81.

Research output: Contribution to journalArticleResearchpeer-review

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AU - Qian, Jun

AU - Ou, Chun-Quan

AU - Zhou, Ying-Xue

AU - Guo, Cui

AU - Guo, Yuming

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AB - There is an increasing interest in spatial and temporal variation of air pollution and its association with weather conditions. We presented the spatial and temporal variation of Air Pollution Index (API) and examined the associations between API and meteorological factors during 2001-2011 in Guangzhou, China. A Seasonal-Trend Decomposition Procedure Based on Loess (STL) was used to decompose API. Wavelet analyses were performed to examine the relationships between API and several meteorological factors. Air quality has improved since 2005. APIs were highly correlated among five monitoring stations, and there were substantial temporal variations. Timescale-dependent relationships were found between API and a variety of meteorological factors. Temperature, relative humidity, precipitation and wind speed were negatively correlated with API, while diurnal temperature range and atmospheric pressure were positively correlated with API in the annual cycle. Our findings should be taken into account when determining air quality forecasts and pollution control measures.

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