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• Digitalization become a new driving force to improve energy-saving and emission reduction performance (EEP). • The relationship between digitalization and EEP has spatial and temporal heterogeneity. • There is a synergy between digitalization and industrialization. • Some constructive policy suggestions are proposed from the perspective of digital development. In the digital era, enterprises actively use digital technology to enable resource conservation and pollution reduction, which has important practical significance. However, the existing research has not fully clarified the link between digitalization and energy-saving and emission reduction. This paper measures the digital development level and energy-saving and emission reduction performance (EEP) of 271 Chinese cities from 2003 to 2019 and empirically explores the impact of digitalization on EEP. The empirical results are: (1) digitalization can significantly improve EEP in Chinese cities, and become a new driving force to save energy and reduce emissions in the new era. After solving the endogeneity problems and replacing the explained variables, the conclusion remains robust. (2) The relationship between digitalization and EEP has significant spatiotemporal heterogeneity. Digitalization helps to promote EEP in China's eastern cities, but it has not shown a positive effect in western cities. The positive effect of digitalization began to emerge after 2011. (3) There is a synergy between digitalization and industrialization, which enables cities to save energy and reduce emissions. This study helps clarify the relationship between digitalization and EEP, which provides important insights into how digitalization can empower cities' energy-saving and emission reduction. [ABSTRACT FROM AUTHOR]

This paper explores how green fiscal expenditure affects G reen T otal F actor E nergy E fficiency (GTFEE) from both non-spatial and spatial perspectives based on selected panel data of 254 cities in China. The results of the non-spatial panel model indicate that green fiscal expenditure has a significant positive impact on GTFEE. A comparative study of different econometric models shows that the main parts of the results are largely consistent, which indicates that the conclusions are robust. The spatial autocorrelation findings indicate a statistically significant presence of positive spatial spillover effects in the GTFEE of Chinese cities. Spatial Durbin Model (SDM) and Dynamic Spatial Durbin Model (DSDM) indicate that green fiscal expenditure has a similarly significant positive effect on GTFEE, which will increase over time. This paper considers different spatial weight matrices and changing measures to measure GTFEE, and the conclusions remain robust. Furthermore, industrial structure upgrading, and digital economy are vital in strengthening the relationship between local governments' green fiscal expenditure and GTFEE. According to heterogeneity analysis, green fiscal expenditure has a more significant effect on the GTFEE in mature resource-based cities and non-resource-based cities. • Influence factors of green total factor energy efficiency (GTFEE) is explored. • Green fiscal expenditure (GFE) has a significant positive impact on GTFEE. • Significant positive spatial spillover effects exist in the GTFEE of Chinese cities. • Industrial structure upgrading and digital economy are vital for GFE and GTFEE. [ABSTRACT FROM AUTHOR]

This paper examines the dynamic behaviour of energy intensity across Chinese cities. It employs a dynamic distribution approach which takes economic size into consideration. The results support the existence of convergence in terms of energy intensity among Chinese cities during the sample period. However, bimodality is the dominant characteristic in the long-term distribution using the full sample. The results also show that the distribution dynamics of energy intensity differ greatly among city groups in terms of geographical location, environmental policy, and population size. Weighting by economic size does not change the convergence trend of energy intensity, but has a significant influence on the long-term distribution. Neglecting economic size may overstate the energy reduction performance in Chinese cities. Furthermore, the results also suggest that geographical location, income level, and city population size have a significant impact on the spatial distribution dynamics of energy intensity. However, the formation of convergence clubs is complicated and thus requires further investigation. [ABSTRACT FROM AUTHOR]

• LNG point supply has the advantages of safety, economy, and environmental protection. • Incomplete construction regulations are the challenges of LNG point supply method. • LNG supply chain optimization model aims to minimize economic & environmental costs. • This paper employs the actual data of towns in the optimization model for research. • The sensitivity of construction cost is relatively high. Liquefied natural gas (LNG) point supply is one of the most flexible and convenient methods advocated by China for distributing energy to end-users such as towns and villages where it is difficult or uneconomical to construct gas pipelines. This study sorts out the advantages and challenges and designs the optimization model for LNG point supply in China based on a mixed-integer linear programming (MILP) model. In this model, the goal of optimization is to minimize economic and environmental costs in the construction and operation stages. By optimizing location-allocation, gas storage capacity, vaporization capacity, equipment selection, and pipeline distribution, the model meets the fluctuating seasonal demand for natural gas. This model design uses the actual construction and operation-related parameters of the vaporization station and pipeline, and applies the model to four different types of towns. Through sensitivity analysis, this study finds that the sensitivity of construction cost is relatively high. [ABSTRACT FROM AUTHOR]

This paper attempts to explore carbon tax pilot in Yangtze River Delta (YRD) urban agglomerations based on a novel energy-saving and emission-reduction (ESER) system with carbon tax constraints, which has not yet been discussed in present literature. A novel carbon tax attractor is achieved through the discussion of the dynamic behavior of the new system. Based on the genetic algorithm-back propagation neural network, the quantitative coefficients of the actual system are identified. The scenario analysis results show that, under the same tax rate and constraint conditions, the ESER system in YRD urban agglomerations is superior to the average case in China, in which the impacts on economic growth are almost the same. The former’s energy intensity is lower and the shock resistance is stronger. It is found that economic property of YRD urban agglomerations is the main cause for the ESER system of YRD urban agglomerations being superior. In the current YRD urban agglomerations’ ESER system, energy intensity cannot be adjusted to an ideal level by commercialization management and government control; however, it is under effective control of carbon tax incentives. Therefore, strengthening the economic property of YRD urban agglomerations and effective utilization of carbon tax incentives could perfectly control energy intensity, without obvious potential negative impact on economic growth. [ABSTRACT FROM AUTHOR]

Along with rapid development of economy, urbanization and industrialization in China, the transportation sector especially road transport accounts for the quickest growth of energy consumption and greenhouse gas (GHG) emissions across the country. This paper selects four representative cities (Beijing, Shanghai, Guangzhou, and Chongqing) in the north, east, south, and west of China as targets of case study. It predicts future motor vehicle population in various cities using the Gompertz Model, and predicts and analyzes fuel consumption and GHG emissions of different types of motor vehicles in the case cities by 2035. The results indicate that besides gasoline and diesel, in the future uses of various types of vehicle fuels will follow different patterns among these four cities due to diverse resources endowment, economic strength, technology levels and geographical features. Based on predicted vehicle population and fuel consumption, it is found that from 2013 to 2035, GHG emissions from tank to wheel (TTW) and well to wheel (WTW) in all cities will continuously increase yet at different rates. If there is no interference from new policies, around 2020 Chongqing is expected to replace Beijing as the city with the highest volume of GHG emissions of vehicles among four case study cities. Therefore, the four cities especially Chongqing need urgently to develop or adjust low-carbon policies in road transportation sector, in order to achieve China’s future greenhouse gas reduction targets. Some policy implications to reduce GHG emissions of the road transportation sectors of the case cities are suggested based on the analysis results. [ABSTRACT FROM AUTHOR]

China’s commitment to the UNFCCC to peak its emissions by 2030, or sooner, signaled a long anticipated shift in China’s model of development with far reaching consequences. Cities in China, and particularly the residential sector in cities, will be charged with making significant reductions in emissions growth even as rates of urbanization continue to climb. Focusing on Beijing and Shanghai, this paper carries out a measures-based economic analysis of low carbon investment opportunities in the residential sector. Results find significant opportunity: between 2015 and 2030, BAU levels of CO 2 emissions could be reduced by 10.2% in Beijing and 6.8% in Shanghai with the adoption of economically attractive low carbon measures. While these headline results underline the case for low carbon investment in the residential sectors of these megacities in China, a closer analysis provides insights for understanding the economics of decarbonisation in cities more generally. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents a model to quantify the impact of electric power outages on GDP by using Cobb–Douglas production function to develop an economic relationship between the reliability of the electric power supply system and the cost of electric energy unserved. Our findings show that average costs for providing a stable power supply are much lower than disruption costs, which is supported by recurring to the data available of Shanghai. Estimated by using Shanghai’s macroeconomic data of 1990–2006, this relationship indicates that the impact of electricity service disruption on Shanghai’s GDP is about 48.18×108 CNY in 2006, matching an alternative “back-of-envelope” estimate of 50.91×108 CNY. The estimated costs per kWh unserved are 1.81–10.26 CNY in 1990–2006, mirroring the increasing importance of electricity in the period’s economic development. These results demonstrate the usefulness of our approach for quantifying the reliability benefits of investments in electricity infrastructure. [Copyright &y& Elsevier]

• The role of grid-connected parking lots (GPL) on the power reliability is studied. • GPLs are viewed as virtual energy storage units and statistically modeled. • The evaluation is conducted from a physical-social system perspective. • Fuzzy logic approach is used to model individuals' participation of Vehicle-to-Grid. • The influential factors for the capacity value of GPLs are analyzed. This paper presents a study to investigate the potential role of public plug-in electric vehicle grid-connected parking lot (GPL) in improving the sustainability of power supply as virtual energy storage in the urban grid. For this, a comprehensive evaluation framework is proposed which introduces an extension of the generation-oriented concept of capacity value to GPL, with the aim of assessing their contribution to adequacy of supply for different settings. In order to capture the volatility in the available energy from GPL, a compound parametric model is developed from the perspective of physical-social system. Comparing with peer studies, our proposed approach has prominent advantages: (a) it accounts the effects from both technical and human factors associated with the GPL operations; (b) it considers the uncertainty of vehicle users' preference for using GPL and its potential dynamics with the externalities. Hence, it can provide a more comprehensive and realistic representation of the operating characteristics of the GPL. A general framework based on the sequential Monte-Carlo simulation method is developed to derive the corresponding capacity value indices. The effectiveness of the proposed method is validated through implementation on both a standard test case and a real distribution system in China. The obtained results suggest that the capacity value of GPLs could vary significantly, dependent on both the operational characteristics of facilities and the charging pattern of electric vehicles. Additionally, the uncertainties in drivers' behaviors can have a noticeable impact on the reliability benefits of GPL program. [ABSTRACT FROM AUTHOR]