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

Highlights: • The perceived welfare loss caused by PM_2.5 in Beijing are CNY 2286.1/person/year. • Both health and mood impacts are investigated via contingent valuation. • "Willingness to pay" (WTP) and "willingness to accept" (WTA) formats are applied. • Both face-to-face and web-based survey modes are used. • WTP/WTA estimates from different models, including Random Forest, are compared. Air pollution from PM₂.₅ affects many cities worldwide, causing both health impacts and mood depression. One of the obstacles to implementing environmental regulations for PM₂.₅ reduction is that there are limited studies of PM₂.₅ welfare loss and few investigations of mood depression caused by PM₂.₅. This article describes a survey study conducted in Beijing, China to estimate the welfare loss due to PM₂.₅. 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 PM₂.₅ 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 PM₂.₅ pollution. This is one of few papers that explicitly studies the effects of PM₂.₅ on subjective well-being, and to the authors' knowledge, the first to estimate welfare loss from PM₂.₅ 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 PM₂.₅ control in China.