title: A method to estimate spatiotemporal air quality in an urban traffic corridor.
abstract: Air quality exposure assessment using personal exposure sampling or direct measurement of spatiotemporal air pollutant concentrations has difficulty and limitations. Most statistical methods used for estimating spatiotemporal air quality do not account for the source characteristics (e.g. emissions). In this study, a prediction method, based on the lognormal probability distribution of hourly-average-spatial concentrations of carbon monoxide (CO) obtained by a CALINE4 model, has been developed and validated in an urban traffic corridor. The data on CO concentrations were collected at three locations and traffic and meteorology within the urban traffic corridor.(1) The method has been developed with the data of one location and validated at other two locations. The method estimated the CO concentrations reasonably well (correlation coefficient, r≥0.96). Later, the method has been applied to estimate the probability of occurrence [P(C≥Cstd] of the spatial CO concentrations in the corridor. The results have been promising and, therefore, may be useful to quantifying spatiotemporal air quality within an urban area.
authors: Department of Civil Engineering, Indian Institute of Technology Guwahati, Guwahati 781 039, India.
authors: Nongthombam Premananda
authors: NP
authors: Singh
authors: Department of Civil Engineering, Indian Institute of Technology Guwahati, Guwahati 781 039, India. Electronic address: sharadbg@iitg.ernet.in.
authors: Sharad
authors: S
authors: Gokhale
mesh_terms: D000393:Air Pollutants / Q000032:analysis*; D000397:Air Pollution / Q000706:statistics & numerical data*; D002947:Cities / Q000706:statistics & numerical data; D004784:Environmental Monitoring; D008962:Models, Theoretical; D001335:Vehicle Emissions / Q000032:analysis
chemical_list: D000393:Air Pollutants; D001335:Vehicle Emissions
keywords: CO; Concentration; Human exposure; Spatiotemporal; Traffic emission; Urban air quality