Mapping risk scenarios of environmental impact assessment accidents in construction projects
With the improvement of environmental protection requirements, risk analysis is significant for environmental impact assessment accidents (EIAA) of construction projects. Currently, many risk variables can cause EIAA, and risk probabilities of EIAA are various in different risk scenarios. Therefore,...
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Veröffentlicht in: | Environmental impact assessment review 2023-09, Vol.102, p.107190, Article 107190 |
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Sprache: | eng |
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Zusammenfassung: | With the improvement of environmental protection requirements, risk analysis is significant for environmental impact assessment accidents (EIAA) of construction projects. Currently, many risk variables can cause EIAA, and risk probabilities of EIAA are various in different risk scenarios. Therefore, the aim of the study is to explore various risk scenarios with different risk probabilities of EIAA. According to the results of risk variables, which were studied by Grounded Theory (GT), the risk scenarios with high risk probabilities of EIAA are proposed by Bayesian Network (BN) in this study. This study finds that 1) 21 risk variables contained 5 categories involve invalid data, fuzzy evaluation scope, unreasonable evaluation model, unreasonable evaluation conclusion, incomplete assessment report. 2) critical risk variables causing EIAA contain lacking of personnel signature in EIA report, unreasonable project site selection, unreasonable evaluation grade of pollution source. 3) there are 4 risk scenarios with high risk probabilities of EIAA, and their risk probabilities are 90.3%, 90.3%, 89.6%, 89.6%, respectively. These findings offer a good reference for the environmental impact assessment of construction projects.
•EIAA contains 21 risk variables.•unreasonable evaluation grade of pollution source is critical.•there are four risk scenarios with higher risk probabilities of EIAA.•four risk scenarios' probabilities 90.3%, 90.3%, 89.6%, 89.6%, respectively. |
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ISSN: | 0195-9255 1873-6432 |
DOI: | 10.1016/j.eiar.2023.107190 |