TY - JOUR

T1 - Contingent valuation of health and mood impacts of PM2.5 in Beijing, China

AU - Yin, Hao

AU - Pizzol, Massimo

AU - Jacobsen, Jette Bredahl

AU - Xu, Linyu

PY - 2018

Y1 - 2018

N2 - Air pollution from PM 2. 5 affects many cities worldwide, causing both health impacts and mood depression. One of the obstacles to implementing environmental regulations for PM 2. 5 reduction is that there are limited studies of PM 2. 5 welfare loss and few investigations of mood depression caused by PM 2. 5. This article describes a survey study conducted in Beijing, China to estimate the welfare loss due to PM 2. 5. In total, 1709 participants completed either a face-to-face or online survey. A contingent valuation method was applied to elicit people's willingness to pay to avoid PM 2. 5 pollution and willingness to accept a compensation for such pollution. The payment/compensation was evaluated for two outcome variables: perceived health impacts and mood depression caused by PM 2. 5 pollution. This is one of few papers that explicitly studies the effects of PM 2. 5 on subjective well-being, and to the authors' knowledge, the first to estimate welfare loss from PM 2. 5 using a random forest model. Compared to the standard Turnbull, probit, and two-part models, the random forest model gave the best fit to the data, suggesting that this may be a useful tool for future studies too. The welfare loss due to health impacts and mood depression is CNY 1388.4/person/year and CNY 897.7/person/year respectively, indicating that the public attaches great importance to mood, feelings and happiness. The study provides scientific support to the development of economic policy instruments for PM 2. 5 control in China.

AB - Air pollution from PM 2. 5 affects many cities worldwide, causing both health impacts and mood depression. One of the obstacles to implementing environmental regulations for PM 2. 5 reduction is that there are limited studies of PM 2. 5 welfare loss and few investigations of mood depression caused by PM 2. 5. This article describes a survey study conducted in Beijing, China to estimate the welfare loss due to PM 2. 5. In total, 1709 participants completed either a face-to-face or online survey. A contingent valuation method was applied to elicit people's willingness to pay to avoid PM 2. 5 pollution and willingness to accept a compensation for such pollution. The payment/compensation was evaluated for two outcome variables: perceived health impacts and mood depression caused by PM 2. 5 pollution. This is one of few papers that explicitly studies the effects of PM 2. 5 on subjective well-being, and to the authors' knowledge, the first to estimate welfare loss from PM 2. 5 using a random forest model. Compared to the standard Turnbull, probit, and two-part models, the random forest model gave the best fit to the data, suggesting that this may be a useful tool for future studies too. The welfare loss due to health impacts and mood depression is CNY 1388.4/person/year and CNY 897.7/person/year respectively, indicating that the public attaches great importance to mood, feelings and happiness. The study provides scientific support to the development of economic policy instruments for PM 2. 5 control in China.

KW - PM2.5, welfare loss

KW - WTP/WTA

KW - Health impacts

KW - Mood impacts

KW - Random forest

KW - Air Pollution/statistics & numerical data

KW - Humans

KW - Affect

KW - Environmental Exposure/statistics & numerical data

KW - Beijing

KW - Air Pollutants/analysis

KW - Particulate Matter/analysis

KW - Perception

KW - Cities

KW - PM . , welfare loss

U2 - 10.1016/j.scitotenv.2018.02.275

DO - 10.1016/j.scitotenv.2018.02.275

M3 - Journal article

C2 - 29554748

VL - 630

SP - 1269

EP - 1282

JO - Science of the Total Environment

JF - Science of the Total Environment

SN - 0048-9697

ER -