Considerations on air pollution monitoring network design in the light of spatio-temporal variations of data |
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| Institution: | 1. Department of Land Management and Systems, Lincoln University, New Zealand;2. Living Earth, Christchurch, New Zealand;3. School of Physical & Chemical Sciences, University of Canterbury, New Zealand;4. Department of Soil and Physical Sciences, Lincoln University, New Zealand;1. University of Salento, Dipartimento di Scienze e Tecnologie Biologiche ed Ambientali, S.P. 6 Lecce-Monteroni, 73100 Lecce, Italy;2. RESEAUX S.r.l., Strada Prov.le per Monteroni 6, 73100 Lecce, Italy;3. University of Notre Dame, Environmental Fluid Dynamics Laboratories, Department of Civil & Environmental Engineering and Earth Sciences, Notre Dame, IN 46556, USA;1. European Commission, Joint Research Centre (JRC), Via Enrico Fermi 2749, 21027, Ispra, VA, Italy;2. Institute for Medical Research and Occupational Health, Ksaverska cesta 2, Zagreb, Croatia;3. Institut national de l''Environnement Industriel et des Risques (INERIS), Parc technologique Alata, BP 2, F-60550, Verneuil-en-Halatte, France;4. Laboratoire Central de Surveillance de la Qualité de l’Air (LCSQA), Parc technologique Alata, BP 2, F-60550, Verneuil-en-Halatte, France;5. NILU – Norwegian Institute for Air Research, PO Box 100, 2027, Kjeller, Norway;6. Flemish Institute for Technological Research (VITO), Boeretang 200, 2400, Mol, Belgium;7. Flanders Environment Agency, Dokter De Moorstraat 24-26, 9300, Aalst, Belgium;8. Liberaintentio Srl, Malnate, 21046, Italy;1. University of Chengdu Technology, Chengdu, 610059, China;2. Department of Environmental Geosciences, Faculty of Environmental Sciences, Czech University of Life Sciences Prague, Kamýcká 129, 165 00, Prague, Suchdol, Czech Republic;3. Applied Nuclear Techniques in Geosciences Key Laboratory of Sichuan Province, Chengdu, 610059, China |
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| Abstract: | Spatial and temporal variations of air pollution data obtained from ambient air monitoring stations are studied. Spatial correlation fields and spatial distributions of long-term averages are subject to yearly and seasonal changes for NO2 and SO2 concentrations. Many previous works for monitoring network design did not pay much attention to these changes. Fundamental policies for a rational network design are proposed: (1) optimality should be pursued within the accuracy limits ensured by the model fields, (2) network designs should be based on features of the air pollution fields, especially yearly and seasonal fluctuations evaluated from actual monitoring data, and (3) some redundancy is necessary in a network to examine whether or not the required accuracy representing the air pollution field is attained. |
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