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- W4317936464 abstract "Many heavy industrial cities in the world are suffered from serious air pollution problems from stationary emission sources and the spatial patterns between the sources and the receptors is an important environmental issue. Some existed studies adopted numerical models, machine learning or deep learning to characterize the spatial patterns and impacts of air pollution sources in urban areas. Due to the complexity of the air circulation system and consideration of several factors, the relationship between stationary emission sources and ambient air quality is hard to estimate; as a result, limited studies discussed and gave quantitative evidence. This study aimed to quantify and verify the relative impacts from stationary emission sources to each ambient air quality station via applying time-series Granger causality. The study is conducted in Kaohsiung, the largest industrial metropolitan area in Taiwan. The results from the analysis on the role of transboundary pollutants show that the estimated relative impact does not significantly increase during transboundary-dominating seasons winter and spring in the study area. We found that the spatial characteristics of the estimated relative impacts in seasonal and diurnal variation are strongly related to the geographical factors and wind field, respectively. The major stationary emission source is attributed to the category “Smelting and Refining of Iron and Steel”. Moreover, the emission amount of different industrial categories is highly consistent with the estimated relative impacts. This method could efficiently reveal the spatial relationship between stationary emission sources and ambient air quality with limited data; hence, the results could provide as suggestions to local residents, administrations of government and non-government organizations for policy planning. Nevertheless, this concept could be utilized even in low-infrastructure cities, regions or countries for monitoring or realizing how stationary emission sources affect to ambient air quality." @default.
- W4317936464 created "2023-01-25" @default.
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- W4317936464 date "2023-01-01" @default.
- W4317936464 modified "2023-09-23" @default.
- W4317936464 title "A Novel Evaluation of Air Pollution Impact from Stationary Emission Sources to Ambient Air Quality via Time-Series Granger Causality" @default.
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- W4317936464 doi "https://doi.org/10.1007/978-981-19-8765-6_2" @default.
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