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Highlights: [•] We study determinants of employee electricity saving habit in organization. [•] The model was tested using survey data collected from office workers in China. [•] Enjoyment, image, personal norm and perceived harm positively influence habit. [•] Anticipated extrinsic benefit and perceived threat didn’t have significant effect. [ABSTRACT FROM AUTHOR]

Hydrogen blending into natural gas is a feasible approach to realize the low-carbon energy structure. The impact of the hydrogen blending ratio on the leakage characteristics of buried gas pipelines determines the safety of pipeline operations. In this study, we investigated the influence of the hydrogen blending ratio on the soil temperature field after the buried gas pipeline leak and the detection range of fiber optic sensors through a field test and numerical simulation. A critical flow model based on the Peng-Robinson (PR) equation and a soil diffusion model based on simplified throttling were established for the microleakage and diffusion stages of the buried pipeline. Furthermore, the soil temperature variation after the buried pipeline leak and the prediction model of cooling capacity caused by gas leakage were obtained. In addition, the leakage experiments were performed to evaluate the impact of hydrogen blending ratio, pipeline operation pressure, and leak direction, as well as to achieve the soil temperature field distribution near the leak point. The following conclusions can be drawn: (1) Soil temperature decreases as the hydrogen blending ratio increases; (2) The detection range of the fiber optic sensors increases as the hydrogen blending ratio increases, ensuring the applicability of the existing fiber optic detection system for detecting hydrogen blending pipeline leaks. The findings provide a valuable research topic for hydrogen pipeline leak detection. • An experiment on the leakage of hydrogen - doped natural gas from buried pipeline is carried out. • A flow model based on PR equation of state is established for leakage prediction. • Calculation method of cooling capacity caused by gas injection based on soil temperature distribution. • The distribution of soil temperature and temperature change rate near the leakage. [ABSTRACT FROM AUTHOR]

Abstract: In order to further study the realization of carbon intensity target, find the key influencing factors of CO2 emissions, and explore the path of developing low-carbon economy, this paper empirically studied the influences of urbanization level, economic level, industry proportion, tertiary industry proportion, energy intensity and R&D output on CO2 emissions in Beijing using improved STIRPAT (stochastic impacts by regression on population, affluence and technology) model. The model is examined using partial least square regression. Results show that urbanization level, economic level and industry proportion positively influence the CO2 emissions, while tertiary industry proportion, energy intensity and R&D output negatively do. Urbanization level is the main driving factor of CO2 emissions, and tertiary industry proportion is the main inhibiting factor. In addition, along with the growth of per capita GDP, the increase of CO2 emissions does not follow the Environmental Kuznets Curve model. Based on these empirical findings and the specific circumstances of Beijing, we provide some policy recommendations on how to reduce carbon intensity. Beijing should pay more attention to tertiary industry and residential energy consumption for carbon emission reduction. It is necessary to establish a comprehensive evaluation index of social development. Investing more capital on carbon emission reduction science and technology, and promoting R&D output is also an efficient way to reduce CO2 emissions. [Copyright &y& Elsevier]

Abstract: Tiered electricity price (TEP) reform is a planning policy for household electricity conservation in China. Based on TEP, several price hierarchies are provided, and additional payment will be charged if the electricity consumptions exceed the upper bound of each hierarchy. Yet, the optimal level of each price tier and the institutions for implementing TEP need further research, which are set on the basis of considering residents’ affordability and willingness to pay. Therefore, this paper aims at exploring determinants of public willingness to accept TEP and finding out the acceptable range of premium. A questionnaire survey in four urban cities of China is conducted to collect data, and an ordinary regression model is adopted in our analysis to identify the drivers and barriers to general public’s acceptance of TEP. The results show that middle income earners are the groups that are mostly opposed to TEP. Rather than just focusing on economic factors, public environmental awareness should be highlighted during the implementation of TEP, because cost is not a statistically significant determinant in this study. Moreover, the public acceptable rate of premium of TEP in the urban cities, according to our research results, may be below .05RMB/kWh. [Copyright &y& Elsevier]