Designing ambient particulate matter monitoring program for source apportionment study by receptor modeling |
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| Authors: | Nguyen Thi Kim Oanh Prapat Pongkiatkul Nabin Upadhyay Phillip P Hopke |
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| Institution: | 1. Key Laboratory for Semi-Arid Climate Change of Ministry of Education, College of Atmospheric Sciences, Lanzhou University, Lanzhou 730000, China;2. State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry (LAPC), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China;3. Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China;4. Jinan Ecological and Environment Monitoring Center of Shandong Province, Jinan 250000, China;5. Capital Normal University, Beijing 100048, China;1. Department for Environmental Health, National Institute for Public Health and the Environment (RIVM), P.O. Box, 2720 BA, Bilthoven, The Netherlands;2. Institute for Risk Assessment Sciences, Utrecht University, P.O. Box 80178, 3508 TD Utrecht, The Netherlands;3. Air Quality & Sustainable Nanotechnology, Institute of Energy and Environmental Technology (IUTA), Bliersheimer Straße 60, 47229 Duisburg, Germany;4. MRC-PHE Centre for Environment and Health, School of Biomedical Sciences, King''s College London, 150 Stamford Street, London SE1 9NH, United Kingdom;5. Division of Environmental Health & Risk Management, School of Geography, Earth & Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom;6. Department of Environmental Sciences, Center of Excellence in Environmental Studies, King Abdulaziz University, P.O. Box 80216, Jeddah 21589, Saudi Arabia;7. Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, P.O. Box 85500, 3508 GA Utrecht, The Netherlands |
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| Abstract: | Particulate matter (PM) receptor modeling requires specific intensive input data that is always a challenge to produce cost effectively. A well-designed monitoring program is important to collect such PM ambient data in urban areas with diverse and densely distributed sources. This paper presents a general framework for designing such a monitoring program while emphasizing appropriate quality assurance and quality control elements that are particularly applicable where limited resources are available. Topics for discussion include selection of monitoring sites, sampling and analytical techniques, and the uncertainty estimation for ambient concentration input data. The design framework is illustrated by a case study of a monitoring program for PM source apportionment in the Bangkok Metropolitan Region in which 24-h fine and coarse PM samples were collected using two collocated dichotomous samplers. Comparison between black carbon measurements by Smoke Stain reflectometry and Thermal Optical Transmittance method is highlighted. |
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