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

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 Guangz...

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Veröffentlicht in:Environmental pollution (1987) 2014-07, Vol.190, p.75-81
Hauptverfasser: Li, Li, Qian, Jun, Ou, Chun-Quan, Zhou, Ying-Xue, Guo, Cui, Guo, Yuming
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container_start_page 75
container_title Environmental pollution (1987)
container_volume 190
creator Li, Li
Qian, Jun
Ou, Chun-Quan
Zhou, Ying-Xue
Guo, Cui
Guo, Yuming
description 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. [Display omitted] •Air pollution is still serious in Guangzhou, China.•Air Pollution Index was associated with a variety of meteorological parameters.•The temporal relationships were timescale-dependent.•The findings should be taken into account in air quality forecasts and pollution control. Spatial and temporal variation of API and its timescale-dependent relationship with meteorological factors in Guangzhou were demonstrated.
doi_str_mv 10.1016/j.envpol.2014.03.020
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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. [Display omitted] •Air pollution is still serious in Guangzhou, China.•Air Pollution Index was associated with a variety of meteorological parameters.•The temporal relationships were timescale-dependent.•The findings should be taken into account in air quality forecasts and pollution control. 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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. [Display omitted] •Air pollution is still serious in Guangzhou, China.•Air Pollution Index was associated with a variety of meteorological parameters.•The temporal relationships were timescale-dependent.•The findings should be taken into account in air quality forecasts and pollution control. 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[Display omitted] •Air pollution is still serious in Guangzhou, China.•Air Pollution Index was associated with a variety of meteorological parameters.•The temporal relationships were timescale-dependent.•The findings should be taken into account in air quality forecasts and pollution control. Spatial and temporal variation of API and its timescale-dependent relationship with meteorological factors in Guangzhou were demonstrated.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><pmid>24732883</pmid><doi>10.1016/j.envpol.2014.03.020</doi><tpages>7</tpages><orcidid>https://orcid.org/0000-0002-8002-2909</orcidid></addata></record>
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ispartof Environmental pollution (1987), 2014-07, Vol.190, p.75-81
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source MEDLINE; Elsevier ScienceDirect Journals
subjects Air Pollutants - analysis
Air pollution
Air Pollution - statistics & numerical data
Analysis methods
Applied sciences
Atmospheric pollution
China
Climate
Environmental Monitoring - methods
Exact sciences and technology
Meteorological Concepts
Meteorological factors
Pollution
Seasonal-Trend Decomposition Procedure Based on Loess
Seasons
Spatio-Temporal Analysis
Temperature
Timescale-dependent relationship
Wavelet analysis
Weather
Wind
title Spatial and temporal analysis of Air Pollution Index and its timescale-dependent relationship with meteorological factors in Guangzhou, China, 2001–2011
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