Environmental Monitoring and Assessment

, Volume 120, Issue 1–3, pp 153–168 | Cite as

Air Quality Improvement Estimation and Assessment Using Contingent Valuation Method, A Case Study in Beijing

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Abstract

The aim of the paper is to estimate and assess residents' willingness to pay to improve air quality in the urban area of Beijing using the Contingent Valuation Method (CVM). The mean willingness to pay (WTP) for a 50% reduction of harmful substances in the air was 143 CNY per household per year, and the total WTP of the residents in the study area was 336 million CNY per year. As a proportion of household annual income, the mean WTP amounted to 0.7%. Four socio-economic variables were found to have significant impacts on residents' willingness to pay. The analysis results illustrated that WTP increases with income and education level, and decreases with household population and age. The willingness was larger for residents in the urban districts than those in the suburban districts. It was found that most of the protest bids lay on interviewees' incomplete perception of the values of environmental amenity. The influence of household income on people's willingness to pay illustrated in this study reflects a causal force of Beijing's transition to market economy that households created to have disposable income are more likely to care about environmental quality. The results of this study strike an optimistic note on the possibility of measuring the total economic value of environmental quality improvement by using the CVM in China. Suggestions on implication of the CVM for both academics and policy makers are provided in the paper.

Keywords

air quality contingent valuation method environmental valuation willingness to pay 
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Copyright information

© Springer Science+Business Media, Inc. 2006

Authors and Affiliations

  • X. J. Wang
    • 1
  • W. Zhang
    • 1
  • Y. Li
    • 1
  • K. Z. Yang
    • 1
  • M. Bai
    • 1
  1. 1.College of Environmental Sciences, MOE Laboratory of Earth Surface ProcessPeking UniversityBeijingP.R. China

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