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 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.

[1]  Rob J Hyndman,et al.  Quantifying the influence of local meteorology on air quality using generalized additive models , 2011 .

[2]  Jaranit Kaewkungwal,et al.  Temporal patterns and forecast of dengue infection in Northeastern Thailand. , 2008, The Southeast Asian journal of tropical medicine and public health.

[3]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[4]  Lucien Hoffmann,et al.  Air pollution characteristics associated with mesoscale atmospheric patterns in northwest continental Europe , 2010 .

[5]  Christer Johansson,et al.  Spatial & temporal variations of PM10 and particle number concentrations in urban air , 2007, Environmental monitoring and assessment.

[6]  Andrew C. Comrie,et al.  Meteorologically adjusted urban air quality trends in the Southwestern United States , 2005 .

[7]  S. Hering,et al.  Mixing characteristics and water content of submicron aerosols measured in Los Angeles and at the grand canyon , 1993 .

[8]  Shuxiao Wang,et al.  Characteristics and health impacts of particulate matter pollution in China (2001–2011) , 2013 .

[9]  C. Chan,et al.  Air pollution in mega cities in China , 2008 .

[10]  M. Chaloupka.  Historical trends, seasonality and spatial synchrony in green sea turtle egg production , 2001 .

[11]  Vinod Thomas,et al.  The Quality of Growth: Fiscal Policies for Better Results , 2008 .

[12]  H. Elminir.  Relative influence of air pollutants and weather conditions on solar radiation – Part 1: Relationship of air pollutants with weather conditions , 2007 .

[13]  H. Ozcan.  Long Term Variations of the Atmospheric Air Pollutants in Istanbul City , 2012, International journal of environmental research and public health.

[14]  Seasonal Variations of PM10 and TSP in Residential and Industrial Sites in an Urban Area of Kolkata, India , 2006, Environmental monitoring and assessment.

[15]  Jiming Hao,et al.  Assessment of air quality benefits from national air pollution control policies in China. Part I: Background, emission scenarios and evaluation of meteorological predictions , 2010 .

[16]  N. Martiny,et al.  Seasonality of meningitis in Africa and climate forcing: aerosols stand out , 2013, Journal of The Royal Society Interface.

[17]  Irma J. Terpenning,et al.  STL : A Seasonal-Trend Decomposition Procedure Based on Loess , 1990 .

[18]  H. Puxbaum,et al.  Seasonal variation of SO2, HNO3, NH3 and selected aerosol components at Sonnblick (3106 m a.s.l.) , 1998 .

[19]  Bert Brunekreef,et al.  Spatial variation in nitrogen dioxide in three European areas. , 2004, The Science of the total environment.

[20]  Mohd Talib Latif,et al.  An assessment of influence of meteorological factors on PM10 and NO2 at selected stations in Malaysia , 2012 .

[21]  S. Zoras,et al.  Particulate Matter Over A Seven Year Period in Urban and Rural Areas Within, Proximal and Far from Mining and Power Station Operations in Greece , 2006, Environmental monitoring and assessment.

[22]  Ryan Hafen,et al.  Syndromic surveillance: STL for modeling, visualizing, and monitoring disease counts , 2009, BMC Medical Informatics Decis. Mak..

[23]  L. Morawska,et al.  Spatial variation of airborne pollutant concentrations in Brisbane, Australia and its potential impact on population exposure assessment , 2002 .

[24]  Y. Wang,et al.  Characteristics and recent trends of sulfur dioxide at urban, rural, and background sites in north China: effectiveness of control measures. , 2012, Journal of environmental sciences.

[25]  Fitz-Simons.  Guideline for reporting of daily air quality: Air Quality Index (AQI) , 1999 .

[26]  Z. Yuan,et al.  Science–policy interplay: Air quality management in the Pearl River Delta region and Hong Kong , 2013 .

[27]  A. Hedley,et al.  Effect of air pollution on daily mortality in Hong Kong. , 2001, Environmental health perspectives.

[28]  C. Torrence,et al.  A Practical Guide to Wavelet Analysis. , 1998 .

[29]  Ari B. Friedman,et al.  Spatial and temporal patterns of particulate matter sources and pollution in four communities in Accra, Ghana. , 2012, The Science of the total environment.

[30]  Rebecca Smith,et al.  Automated ventricular systems segmentation in brain CT images by combining low-level segmentation and high-level template matching , 2009, BMC Medical Informatics Decis. Mak..

[31]  Gerik Scheuermann,et al.  Visual Exploration of Climate Variability Changes Using Wavelet Analysis , 2009, IEEE Transactions on Visualization and Computer Graphics.

[32]  M. Tayanç,et al.  An assessment of spatial and temporal variation of sulfur dioxide levels over Istanbul, Turkey. , 2000, Environmental pollution.

[33]  Aslak Grinsted,et al.  Nonlinear Processes in Geophysics Application of the Cross Wavelet Transform and Wavelet Coherence to Geophysical Time Series , 2022 .

[34]  Alexis K.H. Lau,et al.  A study of control policy in the Pearl River Delta region by using the particulate matter source apportionment method , 2013 .

[35]  P. Marazioti,et al.  STATISTICAL ANALYSIS OF INHALABLE ( PM 10 ) AND FINE PARTICLES ( PM 2 . 5 ) CONCENTRATIONS IN URBAN REGION OF PATRAS , GREECE , 2008 .