New-Type Urbanization on pollution and carbon reduction impact mechanism and co-benefits analysis.

How to simultaneously reduce environmental pollution and CO2 emissions is a challenging issue for various countries, particularly in China. Unlike traditional urbanization process that inevitably deteriorates environment, China initiated a New-Type Urbanization (NTU) strategy in 2014 following four principles: people-centeredness, optimal layout, ecological civilization, and cultural inheritance. Previous studies conduct research on NTU's influencing pollution and carbon reduction (PCR), respectively, while ignoring synergistic governance. The research objectives of this study are to investigate the potential mechanisms of NTU's influencing PCR and co-benefits for PCR. By leveraging 30 provincial-level data from China spanning 2005 to 2019, we comprehensively construct an index and assess NTU from six domains: population, economic, environmental, spatial, equitable, and social urbanizations and combine a coupling coordination model with a 2-way fixed effects model for empirical analysis. Our findings demonstrate that (1) NTU tends to significantly suppress pollution and carbon emissions, and this finding is reliable after several robustness tests and solving endogeneity with relief degree of land surface as an instrumental variable (IV). (2) The reducing effects seem to be achieved by promoting talent agglomeration, facilitating economic agglomeration and strengthening environmental regulations. (3) NTU tends to have both current and time-lag effects on pollution and carbon reduction, and their co-benefits are mainly influenced by the time-lag effect. Accordingly, policy recommendations are recommended: governments need to plan urbanization rationally, including strengthening public infrastructure and social welfare, pursuing the strategy of introducing talents, planning land and resource use rationally and efficiently, and strengthening environmental regulations. In addition, a mechanism should be developed to reduce pollution and carbon in an integrated manner for the long term. Our study broadens the horizons for international scholars engaged in sustainable urbanization research, enriching the array of research methodologies.

Synergistic effect of energy and industrial structures on carbon emissions in China.

Energy structure and industrial structure are two crucial economic factors affecting carbon emissions. However, current research often examines them separately, neglecting the potential additional synergistic effect between them. Leveraging the coupling concept from physics, we objectively quantify these synergistic effect and investigate influencing factors on CO2 intensity from a novel perspective of the synergy by combining a coupling coordination model with econometric model of generalized method of moments (GMM) with a panel dataset from China spanning 2007 to 2019. Our estimates indicate that (1) synergy of energy and industrial structures significantly reduces carbon intensity, which is stable after a series of robust check. (2) the reduced effect of synergy can be enlarged by enhancing environmental regulation and green innovation. (3) the inhibiting effect of synergy is significant, mainly occurs in regions with abundant energy resource endowments. Correspondingly, we recommend several policy implications for China and other developing countries.

China's experience in developing green finance to reduce carbon emissions: from spatial econometric model evidence.

The objective of this study is to attempt to assess the effect of green finance in reducing carbon emissions in China, analyze the transformative role of policy impact in the development of green finance markets, and investigate the impact mechanisms of how green finance affects carbon dioxide emissions. Our time frame from 2007 to 2018 is selected for the empirical study by integrating the availability of data due to the scarcity of relevant statistics in the early days of green finance. Location of this study is in China where 30 provinces are included, excluding Tibet due to severe data shortage. As for methodology, we construct a green finance evaluation index system containing five indicators by entropy weight method, choose dynamic spatial Durbin model (DSDM) for empirical research, and perform mechanism analysis of restructuring industry and greening technology as intermediary channel. Our findings demonstrate that green finance in China does significantly reduce carbon emissions, and its spatial spillover effect and long-term effect are also verified. Furthermore, green finance tends to reduce CO2 emissions through restructuring industry and greening technology. Correspondingly, policy implications are recommended. First, improving green financial market and strengthening information disclosure of green financial market are crucial to facilitate green finance development. Local governments formulate carbon emission reduction strategies focusing on space by joint conference or coordination mechanism like river head system. Lastly, a mechanism should be developed to strengthen the transformation of industrial structure and to promote greening technology.

Understanding Fishermen's Willingness and Preferences for Eco-compensation of Lake Conservation Projects: A Case Study From Nansi Lake Nature Reserve, China.

Lake regions face a tradeoff between water environmental conservation and social development. Although lake conservation projects along with eco-compensation policies are considered the solutions to this problem, it is often controversial and unsustainable. Therefore, it is essential to understand the key stakeholders' willingness to participate in lake conservation projects under the different compensation schemes. In this work, we conducted a choice experiment to estimate fishermen's willingness and preference for the returning fishponds to lake (RFTL) project in the Nansi Lake Nature Reserve (NLNR). Socioeconomic, perception and spatial factors are employed to analyze the preference heterogeneity of fishermen. We employed conditional logit, mixed logit and latent class models to estimates the parameters of factor variables considering the heterogeneous preferences and choice randomness across respondents. The results indicate that on average, fishermen are unwilling to change the status quo and are most concerned about the subsidy amount and contract duration in compensation contracts. However, there is obvious spatial heterogeneity in fishermen's choice preference, mainly manifested in their habitation distance to a town and fishpond location in different zones of the NLNR. Specifically, perceptions of supply and demand for water yield and water quality services significantly influence fishermen's choice, but they have opposite effects. Moreover, we estimated marginal willingness to accept (MWTA) of attributes in compensation contract and measured compensating surplus (CS) to compare different eco-compensation policy scenarios. Our results contribute to designing targeted payment policies, and promote the effective implementation of lake conservation projects and regional sustainable development.

The impact of FDI on environmental pollution in China: evidence from spatial panel data.

With the rapid development of the economy, China's environmental problems remain prominent, and ecological environmental protection has far to go. Many factors work together to affect environmental pollution. In this study, based on the spatial correlation of environmental situation between adjacent regions, spatial autoregressive models are constructed to examine the impacts of foreign direct investment (FDI) on environmental pollution in China. We find an inverted U-shaped relationship between FDI and environmental situation. The study further investigates the mediating effect of economic scale, technology, and industrial structure between FDI and environmental situation. The results show that regions with a larger economic scale and better industrial structure experience a greater FDI impact on environmental situation, but technological level does not serve as a moderator in this study. Our findings have important implications for environmental pollution control and provide important insights for China into a new stage of high-quality development.

Do economic development and population agglomeration inevitably aggravate haze pollution in China? New evidence from spatial econometric analysis.

With sustained economic development, China's ecological environment is becoming increasingly fragile and the problem of haze pollution is becoming increasingly prominent, which has affected the normal life of human beings and the stable development of society. In this paper, 287 cities' panel data from 1998 to 2016 are used, PM2.5 is used to represent haze pollution, and the spatial Durbin model is used to explore the role of the economy and population agglomeration on smog pollution. The empirical results show that (1) haze pollution has obvious spatial spillover. From the perspective of China as a whole, the relationship between the economy and smog pollution is an inverted U shape. (2) China is divided into three economic regions, i.e., the east, the middle, and the west. In the east and middle regions, it is found that economic development also shows an inverted U-shaped relationship with haze pollution. (3) Regardless of the country or the three major economic regions, population agglomeration is the primary factor that aggravates haze pollution; the progress of technology and the optimization of the industrial structure can improve haze pollution. (4) Through further analysis of the indirect effects of haze in China, it is found that there is a significant spatial spillover effect. According to the results of this research, policy suggestions are put forward.