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Journal of Zhejiang University SCIENCE A 2010 Vol.11 No.5 P.370-381

10.1631/jzus.A0900333


Quantitative evaluation of air pollution in transport strategic environmental assessment: a case study based on uncertainty analysis and graphic information system technology


Author(s):  Hong-tao Bai, Hui-zhi Wang, He Xu, Tan Zhu

Affiliation(s):  Research Center for Strategic Environmental Assessment, Nankai University, Tianjin 300071, China

Corresponding email(s):   seacenter@nankai.edu.cn

Key Words:  Air pollution, Transport strategic environmental assessment (SEA), Quantitative evaluation, Uncertainty


Hong-tao Bai, Hui-zhi Wang, He Xu, Tan Zhu. Quantitative evaluation of air pollution in transport strategic environmental assessment: a case study based on uncertainty analysis and graphic information system technology[J]. Journal of Zhejiang University Science A, 2010, 11(9): 370-381.

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%A He Xu
%A Tan Zhu
%J Journal of Zhejiang University SCIENCE A
%V 11
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T1 - Quantitative evaluation of air pollution in transport strategic environmental assessment: a case study based on uncertainty analysis and graphic information system technology
A1 - Hong-tao Bai
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A1 - He Xu
A1 - Tan Zhu
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%@ 1673-565X
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PB - Zhejiang University Press & Springer
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Abstract: 
Although the impact of road transport on urban air quality has achieved a high profile in China, still greater attention is required as it has not yet been considered fully even in relation to the road network linking cities and urban areas. Strategic environmental assessment (SEA) is a systematic and comprehensive process for evaluating the environmental impacts of a policy, plan or program in publicly accountable decision-making. air pollution has been recognized as a significant issue in most transport SEA practices. The Strategic Environmental Assessment of the Hubei Road Network Plan (2002–2020) (HRNP) was introduced as one of the World Bank’s pilot SEA projects. An effective framework was developed to investigate the functional relationship between the road network and its potential air pollutant emissions. In this study, two indicators were identified: emission intensity/inventory of pollutants and the spatial distribution of the most polluted areas. Because strategic actions are inherently nebulous and data quality is often disappointing, three alternative scenarios were employed to address uncertainties and data/scale issues. Calculations were made using emission models and results were analyzed with the help of statistical tools and the geographic information system (GIS). The results from the project implementation and the feedback from the World Bank have both shown that the proposed framework is effective in the transport SEA process.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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