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The carbon peaking and carbon neutrality strategy have become China's national strategy. Given the significant regional differences in China, the Chinese government has proposed "one policy for one province" guiding principle for carbon emission reduction. This study takes Tianjin as a representative of "a province-level city with high degree of industrialization and prominent emerging industries", and Gansu Province a representative of "a province with a low degree of industrialization but the potential for green energy". Using the integrated modeling frameworkthis study conducts a comparative analysis of the hidden flows generated by inter-provincial inward and outward transfers and extracts a feasible model for carbon neutrality transformation. The study also focuses on carbon emission, GDP changes, carbon hidden flow change in trade and carbon emission reduction path. By comparing the results, this study identifies the mechanism of the industrial spillover effect and carbon emission spillover effect between the two regions. Then it concludes the "cross-regional transfer mode of high-carbon industries" of industrial carbon neutral transformation: more carbon emission allowances are allocated to developing regions represented by Gansu Province, implement regionally differentiated carbon emission reduction constraint policies, and achieve industrial spatial transfer through more inter-provincial transfer. The paper found that in implementing a regionally differentiated carbon emission reduction constraint policy (DE scenario), the transfer of high-carbon industries can achieve the "superposition effect" through inter-provincial transfer. Accordingly, three carbon policy mechanisms for cross-regional transfer of high-carbon industries are summarized. [Display omitted] [ABSTRACT FROM AUTHOR]

In order to deal with the rapid growth in residential electricity consumption, residential peak-valley pricing (PVP) policies have been implemented in 12 provinces in China. However, being inappropriate, the residential PVP policies have delivered no significant results. The challenge to China's PVP policy research lies in obtaining high-resolution electricity consumption data and modeling residents' behavior. By simulating household electricity load profiles, an electricity price policy response model and a residential PVP policy optimization model, are constructed and applied in this paper to simulate the effect of the current residential PVP policy and optimize the policy. The results show that the peak-shaving capability (represented by the reduction in peak load) of the PVP policy in 11 provinces is less than 3%, while the PVP policy in Gansu Province has increased household electricity bills by about 5.7%. In addition, the optimized PVP can reduce household electricity bills by 3% and reduce peak electricity consumption by about 9%. The 12 provinces should adopt the 3-phase division method and optimize the electricity price in the peak and valley (i.e. off-peak) periods respectively. This paper promotes the research on China's residential PVP policy and provides an effective reference for the design of the PVP policy. • An electricity demand model based on household characteristic is presented. • The peak-shaving effect of the current PVP policy in 11 provinces is less than 3%. • Optimized PVP can significantly reduce peak power usage and increase benefits. • The PVP policy needs to be optimized from the price and time period division. [ABSTRACT FROM AUTHOR]

In order to deal with the rapid growth in residential electricity consumption, residential peak-valley pricing (PVP) policies have been implemented in 12 provinces in China. However, being inappropriate, the residential PVP policies have delivered no significant results. The challenge to China's PVP policy research lies in obtaining high-resolution electricity consumption data and modeling residents' behavior. By simulating household electricity load profiles, an electricity price policy response model and a residential PVP policy optimization model, are constructed and applied in this paper to simulate the effect of the current residential PVP policy and optimize the policy. The results show that the peak-shaving capability (represented by the reduction in peak load) of the PVP policy in 11 provinces is less than 3%, while the PVP policy in Gansu Province has increased household electricity bills by about 5.7%. In addition, the optimized PVP can reduce household electricity bills by 3% and reduce peak electricity consumption by about 9%. The 12 provinces should adopt the 3-phase division method and optimize the electricity price in the peak and valley (i.e. off-peak) periods respectively. This paper promotes the research on China's residential PVP policy and provides an effective reference for the design of the PVP policy. • An electricity demand model based on household characteristic is presented. • The peak-shaving effect of the current PVP policy in 11 provinces is less than 3%. • Optimized PVP can significantly reduce peak power usage and increase benefits. • The PVP policy needs to be optimized from the price and time period division. [ABSTRACT FROM AUTHOR]

This paper developed a multi-objective fuzzy programming method for simultaneously optimizing the use of water and land resources for irrigation under uncertainty. The developed model was then applied to a case study in Wuwei, Gansu Province, China. In this study, administrative, economic and ecological benefits were regarded as the planning objectives. Moreover, the variations of irrigation water demand with rainfall, soil moisture content and evapotranspiration were considered in the developed model. Optimal irrigation plans were obtained under different possibility levels of fuzzy parameters. The obtained results could be helpful for decision makers to make decisions on the optimal use of irrigation water and land resources under uncertainty and multiple objectives. [ABSTRACT FROM AUTHOR]

New Energy Vehicles (NEVs) exert great potential in reducing carbon emissions, improving air quality and reducing the dependence on petroleum products, and are also essential in realizing the social transformation toward a low-carbon society. Since public are the principal users and stakeholders of NEVs, it's vital to understand their acceptance of NEVs and discuss the influencing factors of public acceptance, so as to promote the development of NEVs. Based on the survey data of Gansu Province, this paper analyzes the public perception and acceptance of NEVs in underdeveloped regions, and explores main factors affecting their acceptance by adopting Structural Equation Model. The results show that the public acceptance of NEVs is relatively higher, with only 51.99% residents are willing to accept NEVs. And there are differences of public acceptance of NEVs among different groups. The acceptance of females, young and less educated public are relatively higher, decreases with aging and increases with education attainment. Perceived risk and perceived cost are significantly negative correlated with public acceptance of NEVs, while subjective norm and the quality of NEVs positively correlated with public acceptance. In addition, support policy is significantly positively correlated with perceived cost while perceived cost is positively corelated with perceived risk. Finally, this paper proposes countermeasures and suggestions on improving the public acceptance of NEVs in underdeveloped regions. • We conducted the NEVs acceptance of 1356 residents in Chinese underdeveloped regions. • 51.99% of the public in underdeveloped regions of China were willing to accept NEVs. • Perceived risk, perceived cost, and NEVs' quality are the key influencing factors. • Support policy, knowledge have significant indirect impact on acceptance of NEVs. • Enhancing subsidies and supporting facilities were effective ways. [ABSTRACT FROM AUTHOR]