Exploring preference and willingness for rural water pollution control: A choice experiment approach incorporating extended theory of planned behaviour.

Rural water pollution control (RWPC) is a crucial issue for developing countries, particularly because of its importance for improving ecosystems, promoting sustainable development, and ultimately contributing to the health and well-being of individuals. This study adopted a choice experiment (CE) to explore farmers' preference and willingness for RWPC and to investigate whether socioeconomic and psychosocial factors can explain differences in farmers' preferences and values governing RWPC. The theory of planned behaviour (TPB) and some additional constructs (risk perception, knowledge, moral norms, and subjective norms) were included in an empirical test that predicts stated choices. The Wei River basin, one of the most water-polluted areas in China, was used as the location for our study. From June to July 2022, we collected the questionnaire responses of 427 farmers who live and work in this area. The results suggested that farmers have significant heterogeneity in their preference for RWPC attributes, but the majority highly value improving water quality through water pollution treatment. The inclusion of TPB and additional constructs in our test explained the behaviour of farmers. Those with high scores tended to already perform RWPC and have a willingness to continue to do so. According to the results of a latent class (LC) model, the average willingness to pay (WTP) per farmer for rural water pollution treatment was 254.69 Chinese yuan (CNY) per year. Excluding biodiversity, the average WTP was 241.55 CNY per year. This study provides a new path for developing countries to promote RWPC and improve local rural environments and the well-being of rural residents.

Innovation-driven development and urban carbon emission reduction: a quasi-natural experiment in China.

Constructing a quasi-natural experiment based on China's National Independent Innovation Demonstration Zone (NIDZ) pilot, this study applies the time-varying difference-in-differences (DID) model to estimate the impact of innovation-driven development on urban carbon emission reduction. We use panel data on 285 cities which covers 95.96% of Chinese cities during the period of 2003 to 2017. Compared with non-pilot cities, our results indicate that total carbon dioxide emissions and emission intensity of pilot cities decreased by 4.8% and 5.8%, respectively. The results suggest that the construction of NIDZs can significantly promote urban carbon emission reductions. Moreover, our mechanism tests indicate that this pilot policy can encourage technological innovation and optimize industrial structure, which in turn suppresses urban carbon dioxide emissions. Additionally, further analysis shows that the policy effect increases over years and is stronger in urban areas with higher levels of human capital, government finance, and information infrastructure. This study enriches the relevant research on carbon emission reduction.