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Energy poverty, especially in rural areas, has become a central focus of scholarly and policy discussions. However, there is a significant gap in understanding the impact of religious beliefs on this phenomenon. This paper aims to fill this gap by utilizing household survey data from the China Labor-force Dynamics Survey (CLDS) spanning three waves (2012, 2014, and 2016) to examine the causal link between religious beliefs and energy poverty, covering clean energy accessibility and affordability among rural residents. Our analysis unveils a substantial positive influence of religious beliefs on the likelihood of experiencing energy poverty, especially concerning accessibility and affordability. This effect is notably pronounced among males, ethnic minorities, and low-income groups. Low income and education are recognized as pivotal mediating factors through which religious beliefs contribute to energy poverty. The findings of this study offer valuable insights for formulating strategies to mitigate energy poverty in rural China, with a particular emphasis on the role of religious beliefs. [ABSTRACT FROM AUTHOR]

Given that income disparity is expanding and diet‐related environmental footprints are increasing in urban China, this study aims to investigate the heterogeneity in these footprints across various income classes and examine the effect of income distribution on the total environmental footprints. Based on the quadratic almost ideal demand system model and taking into consideration the problems of endogeneity of food expenditure and zero expenditure, we estimate the income elasticities for 10 food categories across seven income classes and project the diet‐related environmental footprints under seven scenarios for various strategies of the income distribution. The results show that per capita diet‐related environmental footprints are greater for higher income classes than for lower income classes, as the former consume more animal‐based food. Compared with high‐income classes, income growth favouring low‐income classes results in a rather significant increase in diet‐related environmental footprints. With further economic growth, the lowest income group makes the greatest contribution to the increase in diet‐related environmental footprints. Thus, policymakers should promote a more sustainable diet on the road to alleviating income inequality to ensure sustainable environmental development. [ABSTRACT FROM AUTHOR]

The environmental impact of food consumption has been widely discussed, while it is still unclear whether carbon labels could play a role in persuading consumers to purchase food products with low greenhouse gas emissions (GHGE), especially in transitional economies where the demand for animal-based foods has shown a dramatic increase. This study extends the literature by examining consumers' willingness to pay (WTP) for carbon-neutral-labeled beef products in urban China and evaluating GHGE from consumers' food preferences for carbon-neutral-labeled beef products. We also project the potential GHGE reduction under various scenarios due to the changes in consumers' preferences for carbon-neutral-labeled beef products across different consumer segments. Based on a sample randomly collected in urban China, a choice experiment is conducted with the consideration of four attributes (price, carbon neutral label, feed methods, and origin) for beef products. The random parameter logit (RPL) and latent class model (LCM) are applied to measure consumers' WTPs and identify consumer segments, respectively. We find that consumers have a 28.92 CNY/500 g price premium for carbon-neutral-labeled beef, and a substitution effect is observed when both the carbon neutral label and the imported attribute (or grass-fed attribute) are present. In the projections based on the income distribution of consumer segments, we find that carbon-neutral-labeled beef leads to the greatest GHGE reduction (27.072%) when the population of the medium-income group increases. Therefore, promoting the implementation of carbon labels on agricultural products with high‑carbon footprints in transitional countries such as China, especially for beef products, would contribute to transforming agri-food systems to achieve the carbon neutrality goal. • Consumers have strong WTPs (28.92 CNY/500 g) for carbon-neutral-labeled beef. • There is a substitution effect when both the carbon neutral label and the imported attribute are present. • Consuming carbon-neutral-labeled beef leads to a 27.072% reduction in GHGE as the medium-income population rises. • Implementing carbon labels on agricultural products would help to reduce GHGE. [ABSTRACT FROM AUTHOR]

Increasing consumer demand has increased environmental pressure. Altering consumer behavior may be one strategy to achieve emission reduction targets. China's carbon labeling system is still in its infancy, and consumers' response to carbon labeling products is still uncertain. This study investigates consumers' willingness to pay (WTP) for carbon-labeled agricultural products (CAP) in different regions, the factors influencing them, and the strategies to implement carbon labeling. The results suggest that 77.60% of respondents are willing to pay more for CAP. The premium WTP for carbon-labeled milk, corn, bananas, tomatoes, and eggs is 25.66%, 31.96%, 24.08%, 23.62%, and 20.64%. Low-carbon awareness and the peer effect greatly and favorably impact people's reception of carbon labeling. Respondents' WTP for carbon labeling is considerably and favorably influenced by their acceptance of carbon labeling. We also put forward some suggestions on the promotion strategy of CAP from the perspective of government, enterprises, and consumers. • This study investigates consumers' WTP for carbon-labeled agricultural products (CAP). • 77.60% of respondents are willing to pay more for CAP. • People's reception of CLP is impacted by low-carbon awareness and peer effect. • Respondents' WTP for carbon labels is influenced by their acceptance of CAP. • We offer some advice on promoting CAP from multiple perspectives. [ABSTRACT FROM AUTHOR]

An emission inventory, involving both air pollutants (APs) and greenhouse gases (GHGs), is needed so that the questions of air pollution and climate change can be co-addressed, coordinated, and collaborated upon. In this study, an emission inventory, including both APs and CO 2 (representing GHGs), was developed for China 2019 using two special measures. First, the framework of air pollution source classification was used for the integrative inventory and then the CO 2 emissions for each sector/subsector/source in the GHG inventory were precisely arranged into the framework of APs by every possible means such as drawing on the constraints from the International Industrial Classification of All Economic Activities (ISIC), which enabled the sharing of common or intrinsically connected activity data for both APs and CO 2. Second, an attempt was made to deduce the activity data of various industrial processes through proper interpretation of the information carried in Pollutant Permits. The calculated emissions of APs and CO 2 were found to be comparable to the results of other studies. Additionally, the average per capita CO 2 and pollution equivalents (PEs) were 10.29 ± 6.75 tons and 11.72 ± 7.35 tons, respectively, over the provincial regions with per capita gross domestic product (GDP) lower than ￥70000 (about $10000). Whereas the average per capita CO 2 and PEs dropped to 6.10 ± 1.83 tons and 6.70 ± 2.09 tons, respectively, over the provincial regions with per capita GDP higher than ￥70000. This somewhat supports the philosophy of the Environmental Kuznets Curve (EKC) regarding the close connection between emission and development. Moreover, the two emission intensities (for APs and CO 2) were found to vary synchronously among the provinces, reflecting the inter-linked fates of the two emissions under the control measures oriented toward either APs or GHGs. [Display omitted] • An emission inventory integrating air pollutants and CO 2 are compiled. • GHG classification framework are used for the integrative inventory with additional constraints from ISIC. • Pollutant-Permit information is employed to derive activity data of industrial processes and links. • The EKC philosophy on emission/development relation is partly supported. [ABSTRACT FROM AUTHOR]