title: High-resolution satellite-based analysis of ground-level PM2.5 for the city of Montreal.
abstract: Satellite remote sensing offers the opportunity to determine the spatial distribution of aerosol properties and could fill the gap of ground-level observations. Various algorithms have recently been developed in order to retrieve the aerosol optical depth (AOD) at continental scales. However, they are, to some extent, subject to coarse spatial resolutions which are not appropriate for intraurban scales as usually needed in health studies. This paper presents an improved AOD retrieval algorithm for satellite instrument MODIS at 1-km resolution for intraurban scales. The MODIS-retrieved AODs are used to derive the ground-level PM2.5 concentrations using the aerosol vertical profiles and local scale factors obtained from the GEOS-Chem model simulation. The developed method has been applied to retrieve the AODs and to evaluate the ground-level PM2.5 over the city of Montreal, Canada for 2009 on daily, monthly and annual scales. The daily and monthly results are compared with the monitoring values with correlations R(2) ranging from 0.86 to 0.93. Especially, the annual mean PM2.5 concentrations are in good agreement with the measurement values at all monitoring stations (r=0.96, slope=1.0132 ± 0.0025, intercept=0.5739 ± 0.0013). This illustrates that the developed AOD retrieval algorithm can be used to retrieve AODs at a higher spatial resolution than previous studies to further derive the regional full coverage PM2.5 results at finer spatial and temporal scales. The study results are useful in health risk assessment across this region.
authors.affiliation: Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Quebec H3G 1M8, Canada.
authors.forename: Baozhen
authors.initials: B
authors.lastname: Wang
authors.affiliation: Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Quebec H3G 1M8, Canada. Electronic address: zhichen@alcor.concordia.ca.
authors.forename: Zhi
authors.initials: Z
authors.lastname: Chen
mesh_terms: D000336:Aerosols / Q000032:analysis; D000393:Air Pollutants / Q000032:analysis*; D000397:Air Pollution / Q000706:statistics & numerical data; D000465:Algorithms; D002947:Cities / Q000706:statistics & numerical data; D004784:Environmental Monitoring / Q000379:methods*; D052638:Particulate Matter / Q000032:analysis*; D011792:Quebec; D063809:Satellite Imagery
chemical_list: D000336:Aerosols; D000393:Air Pollutants; D052638:Particulate Matter
keywords: Aerosol optical depth; GEOS-Chem; MODIS; PM(2.5); Satellite data retrieval