The effects of missing data on the calculation of precipitation-weighted-mean concentrations in wet deposition |
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| Institution: | 1. European Commission, Joint Research Centre (JRC), Directorate for Energy, Transport and Climate, Air and Climate Unit, Via E. Fermi 2749, I-21027, Ispra, VA, Italy;2. NILU Norwegian Institute for Air Research, Instituttveien 18, 2027 Kjeller, Norway;3. Earth Sciences Department, Barcelona Supercomputing Center, Barcelona, 08034, Spain;4. VITO, Flemish Institute for Technological Research, Boeretang 200, 2400 Mol, Belgium;5. IVU Umwelt GmbH, 79110 Freiburg, Germany;6. ENEA, National Agency for New Technologies, Energy and Sustainable Economic Development, Laboratory of Atmospheric Pollution, Bologna-Ispra-Pisa-Roma, Italy;7. Slovenian Environment Agency, Ljubljana, Slovenia;8. FMI, Finnish Meteorological Institute, Helsinki, Finland;9. HSY, Helsinki Region Environmental Services, Helsinki, Finland;10. Environment and Health Administration, City of Stockholm, Sweden;11. ARPAE Emilia Romagna, Bologna, Italy;12. Irish Environmental Protection Agency, Ireland;13. Institute of Environmental Protection - National Research Institute, Poland;14. Minister for Environment, Croatia;15. Meteorological and Hydrological Service, Croatia;p. Institute for Environmental Research and Sustainable Development, National Observatory of Athens, Lofos Koufou, 152 36 Penteli, Greece;q. Warsaw University of Technology, Poland;r. Institute of Geophysics, Polish Academy of Sciences, Poland;s. “Climate, Energy and Air” Directorate, Sofia Municipality, USA;t. Universität für Chemische Technologie und Metallurgie, Sofia, USA;u. Ex European Commission, Joint Research Centre, Ispra, Italy;1. School of Criminal Justice, University of Lausanne, Switzerland;2. Department of Economics, University Ca’ Foscari of Venice, Italy;3. Formation Continue UNIL-EPFL, University of Lausanne, Switzerland;4. Department of Architecture and Arts, University IUAV of Venice, Italy |
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| Abstract: | Uncertainties in the calculation of monthly, seasonal and annual precipitation-weighted-mean concentrations due to missing data are addressed. An algorithm is presented to estimate the effects of missing samples through the use of a simulation technique. Quantitative estimates of uncertainty due to missing data are given for monthly, seasonal and annual precipitation-weighted-mean sulphate and nitrate concentrations at six monitoring sites where daily precipitation samples were taken. It is found that the expected value of the precipitation-weighted-mean concentration estimator is biased if the percentage of missing samples (% MN), and the percentage (% MP) of the precipitation amount associated with the missing samples, are different. The absolute value of the bias becomes larger as the difference increases. The standard deviation of the estimator increases with increasing values of % MP. For a given value of % MP, its a minimum when % MN is equal to % MP, and increases with increasing differences between % MN and % MP. These results indicate that % MN of about 10%, which is not uncommon in precipitation networks data, gives an uncertainty of about 10, 5 and 2 % for monthly, seasonal and annual averaging periods, respectively. Procedures to estimate confidence intervals for the true values from observed precipitation-weighted-mean concentrations are presented. |
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