Influence of the large grid size used in a multimedia mass balance model (POPsME) on the exposure assessment of polychlorinated dibenzo-p-dioxins and dibenzofurans
| Autor: | Kyung-Min Kim, Gyutak Cho, Seung-Pil Choi, Gilho Jang, Jee Yoon Lee, Dong Soo Lee, Dong Won Kim, Yoon Kwan Kim, Sujin Kim, Yunah Lee |
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| Rok vydání: | 2007 |
| Předmět: |
Pollution
Geologic Sediments Polychlorinated Dibenzodioxins Grid size media_common.quotation_subject Magnitude (mathematics) computer.software_genre Risk Assessment Soil Environmental monitoring Environmental Chemistry Exposure assessment media_common Benzofurans Multimedia Geography Air Water General Chemistry Environmental exposure Environmental Exposure Models Theoretical Polychlorinated Dibenzo-p-dioxins computer Order of magnitude Environmental Monitoring |
| Zdroj: | Environmental sciencetechnology. 41(15) |
| ISSN: | 0013-936X |
| Popis: | A multimedia mass balance model (MMM), POPsME, was evaluated for its performance to assess the fate and transport of 2,3,7,8-substituted PCDD/Fs in Seoul and a neighboring area (150 km x 150 km) in Korea. As part of the evaluation, the effects of the grid size with the homogeneous mixing assumption were estimated on the sign and magnitude of the prediction bias. The prediction compared with the monitoring data generally within 1 order of magnitude. In the presence of a concentration gradient within individual cells of 30 km x 30 km,the prediction bias for air and soil tended to increase with the distance from the sources. It was observed that the ratio of the predicted to the measured values could vary more than 4 times with the location of the monitoring site. Use of the large grid size in POPsME (and perhaps other MMMs) resulted in overpredictions for a major portion of the model domain at the cost of underprediction for limited areas nearthe sources. Beyond the source areas, a substantial contribution of the total prediction bias originated from the congeners with a large atmospheric loss rate and small TEF value. On a TEQ basis, therefore, the magnitude of the overpredictions could be significantly reduced as compared to that of the underprediction for the source areas. |
| Databáze: | OpenAIRE |
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