In JAMESK and YING, 2006, they estimated the economic value of preventing adverse health effects related to air pollution applying contingent valuation in three different locations in China. In their research, Values which have been estimated for three health points: cold, chronic bronchitis, and fatality. Alternative statistical models were conducted to find out their impact on estimated willingness to pay (WTP) and on the relationship between respondents' socio-parameters and their WTP. They found the results that average median WTP of interviewees' ranges between US$ 3 and US$ 6, the WTP to be away from chronic bronchitis ranges between US $500 and US$ 1,000, and the value per statistical life is at the range of US$ 4,000 and US$ 17,000. Estimated mean values are between two and thirteen times larger. Our estimates are between about 10 and 1,000 times smaller than estimates for the US and Taiwan using official exchange rates. The reason why estimates are quite small than US and Taiwan is surely because of the large income differences between China, the US, and Taiwan. However, there might be other factors existing, such as the level of health-care system, experience dealing with a market economy and different reactions to surveys that also count. Lastly it also showed that Indoor air quality, measured for a subset of respondents, has no consistent relationship with WTP.

In Willian, Edward and Tymon 1997, contingent valuation was applied to estimate a neighbourhood's willingness to pay for keeping a 5.5-acre parcel of undeveloped land in Boulder, Colorado, which can provide wildlife habitat. They have conducted an interval model to evaluate sample WTP as a function of distance, income and other socio-elements. The estimated model demonstrates that first collecting voluntary contributions can maximise the likelihood of raising enough funds, and then determine whether a specified tax should be charged for raising the additional revenues. This study indicates that contingent valuation is a very adaptable technique for both the official department and private community to decide whether to preserve the savage land.

In Yan and Yi-sheng 2009, they focus on the relationship between poor air quality and residents' willingness to pay for improving air quality in the city of Ji'nan, China. To address this topic trying to find willingness to pay for this improvement of air quality, a contingent valuation method (CVM) was employed. The 1500 respondents' WTP was then found through a number of face-to-face interviews by applying hypothetical, open-ended scenario questions. The result they got showed that 59.7% of respondents were willing to pay a positive amount and the mean WTP was 100 Chinese Yuan (CNY) per person, per year. In order to establish the relationship between those variables asked in questionnaire and WTP, they constructed both a Probit model and a stepwise regression model. The results from analysis are almost the same as they expected. It was found that annual household income, expenditure on the treatment of diseases and the number of workers in the family influenced WTP a lot. Also men showed the higher rate than women having positive WTP and more monetary amount as well. They also discussed the reason why individuals don't want to pay for this improvement and got the result that most respondents regard government should be responsible for improving the air quality. More than 40% of respondents had no incentive to pay for better air quality also demonstrates a relatively low environmental consciousness.

In X.J.WANG, W.ZHANG .etc. 2006, the aim of their research is to estimate residents' willingness to pay for improving air quality in the urban area of Beijing applying the Contingent Valuation Method (CVM). They got the result that the mean willingness to pay (WTP) for a 50% reduction of harmful substances in the air was 143CNY per household per year, indicating that the total WTP of the area where study was carried out was 336 million CNY per year. From the study we have learnt that the mean WTP amounted to 0.7% of household annual income. Four socio-economic variables were found to affect individuals' willingness to pay significantly. The analysis results indicate that WTP increases with income and education level, and decreases according to household population and age. The reason why they found willingness to pay was larger for residents in the urban districts than those in the suburban districts is also because of the different income level. The influence of household annual income on individual's willingness to pay demonstrates that households which have more spare money to dispose often take a more care about the environmental quality in order to be willing to pay more for this improvement. Although there are still some factors which can affect the accurate of individuals' willingness to pay, CVM is a practicable and adaptable tool both for policymakers to make any decisions about the environment. We can also summarize from this study that in each particular CV study, we should design the specific willingness to pay questions according to the different situation, so that we can obtain successful reliable estimates of values of environmental goods.

In Hong Wang and John Mullahy 2006, they chose 500 individuals to attend their research programme and held face-to-face household interview using a series of hypothetical, open-ended questions followed by bidding game questions in order to elicit the respondents' WTP for air pollution reduction and they also decided to use the two-part model for estimations. The results show that 96% of respondents were able to express their WTP. Their mean annual income of these interviewees is $490 and their WTP for saving one statistical life is $34,458. The saving on statistical life increases $240 per year according to age increase, $14,434 according to 100 Yuan monthly income increase and $1590 with 1 year education increase. Although this research indicated reasonable results, the figures should be examined with caution since the number of sample is relatively small which could raise a problem that respondents who were at home at the time of the interview might not be able to represent the individuals that were not at home at that time. In this study, they also discussed that the possibility of anchoring adjustment bias that has influence on the results of this study (Stalhammar, 1996; Boschetal., 1998). So the alternative CV methods, such as discrete-choice methods (Boschetal, 1998; Smith, 2000), might be able to reduce this bias in future studies. Last, they also announced that we should be aware that the difference between WTP got from CV method and actual mean WTP might be noticeable (Boardmanetal., 1996; Carlson, 2000).

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