• Energy Research
• 11. Sustainability close
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Abstract This paper analyzes the effect of clean energy use on total-factor efficiencies under the simultaneous consideration of economic output, energy conservation, and emission reduction. The empirical findings on 87 countries during 2004–2010 show that clean energy consumption significantly increases the total-factor emissions reduction efficiency (TFCE), slightly improves the total-factor economic output efficiency (TFYE), and significantly decreases the total-factor energy efficiency (TFEE), with the influence coefficients respectively 0.00292, 0.00029, and −0.00213. On balance, the comprehensive effect of clean energy consumption on total-factor technical efficiency (TFTE) is 0.00028. European countries have higher comprehensive efficiency in economic growth, energy conservation, and emissions reduction. International cooperation is needed to facilitate technology transfer and reduce the gap in efficiency.

Urban heat islands (UHIs) are an important issue in urban sustainability, and the standardized calculation of surface urban heat island (SUHI) intensity has been a common concern of researchers in the past. In this study, we used the administrative borders (AB) method and an optimized simplified urban-extent (OSUE) algorithm to calculate the surface urban heat island intensity from 2001 to 2017 for 36 major cities in mainland China by using Moderate Resolution Imaging Spectroradiometer (MODIS) images. The spatiotemporal differences between these two methods were analyzed from the perspectives of the regional and national patterns and the daily, monthly, and annual trends. Regardless of the spatial or temporal scale, the calculation results of these two methods showed extremely similar patterns, especially for the daytime. However, when the calculated SUHI intensities were investigated through a regression analysis with multiple driving factors, we found that, although natural conditions were the main drivers for both methods, the anthropogenic factors obtained from statistical data (population and gross domestic product) were more correlated with the SUHI intensity from the AB method. This trend was probably caused by the spatial extent of the statistical data, which aligned more closely with the rural extent in the AB method. This study not only explores the standardization of the calculation of urban heat intensity but also provides insights into the relationship between urban development and the SUHI.

With the rapid development of urban rail transit, the energy consumption of trains is increasing dramatically. The shortage of electrical energy is becoming more and more serious. In this paper, a novel method is proposed to better use regenerative braking energy for energy saving. A ‘time slot and energy grid’ model is set up to analyze the utilization of regenerative energy among trains. Based on this model, an energy efficient strategy that integrates train dispatch with train control is designed. The running time of trains in sections, the dwell time of trains at stations and the headway can be adjusted to find the global optimal solution for energy saving. The operational data of Beijing Changping subway line and Beijing Yizhuang subway line are used in simulation to illustrate the effectiveness of the proposed method in different scenarios. Simulation results show that our approach can significantly improve the utilization of regenerative braking energy and minimize the energy consumption in different scenarios when compared with the existing method.

Abstract Accurate rooftop solar energy potential characterization is critically important for promoting the wide penetration of renewable energy in high-density cities. However, it has been a long-standing challenge due to the complex building shading effects and diversified rooftop availabilities. To overcome the challenge, this study proposed a novel 3D-geographic information system (GIS) and deep learning integrated approach, in which a 3D-GIS-based solar irradiance analyzer was developed to predict dynamic rooftop solar irradiance by taking shading effects of surrounding buildings into account. A deep learning framework was developed to identify the rooftop availabilities. Experimental validations have shown their high accuracies. As a case study, a real urban region of Hong Kong was used. The results showed that the annual solar energy potential of the entire building group was reduced by 35.7% due to the shading effect and the reduced rooftop availability. The reductions of individual buildings varied from 13.4% to 74.5%. In spite of the substantial reductions of the annual solar energy, the shading effect could only slightly reduce the peak solar power. In fact, the annual solar energy reduction could be five times higher than the peak solar power reduction. Further analysis showed that simple addition of the respective solar energy potential reductions, caused by the shading effect and the rooftop availability, tends to highly overestimate the total reduction by up to 26%. For this reason, their impacts cannot be considered separately but as joint effects. The integrated approach provides a viable means to accurately characterize rooftop solar energy potential in urban regions, which can help facilitate solar energy applications in high-density cities.

Management of natural resources is pivotal for sustained economic growth—the increasing ecological footprints causing biocapacity deficit threaten the resource conversation agenda. The study identified the potential causes and consequences of natural resource depletion in a broad cross-section of 138 countries. Ecological footprints, international migrant stocks, industrial value-added, and population growth influenced natural resource capital across countries. The results show that ecological footprints, industrial value-added, and population growth are the detrimental factors of resource capital. In contrast, continued economic growth is helpful to conserve natural resources for future generations. The rise and fall in the natural resource degradation are evident in the wake of international migrants’ stocks to support an inverted U-shaped relationship between them. The Granger causality inferences confirmed the one-way linkages, running from international migrant stocks, economic growth, and population growth to natural resource degradation. It verifies migrants-led, affluence-led, and population-led resource degradation. Ecological footprints Granger causes industrial value-added across countries. The forecasting estimates suggested that economic growth would likely to influenced greater in magnitude to resource degradation by its innovation shocks of 4.791%, followed by international migrant stocks, population growth, ecological footprints, and industrial value added by their innovation shocks of 4.709%, 1.829%, 1.247%, and 0.700%, respectively. The study concludes that international migrant stocks should manage smartly, causing more resource degradation via a channel of increasing biocapacity deficit across countries.

Were the large investments in energy and transportation infrastructure effective in fostering economic growth? Or did economic growth trigger these infrastructure developments? To answer these questions, we develop a simple model of production capacity constraints and use China’s Western Development Strategy (WDS) as an example to investigate how the relationships among energy investment, transportation infrastructure expansion and economic growth differ in the pre- and post-WDS periods. Our Granger causality analysis uses a panel data sample for China’s 30 provinces in the Western and non-Western regions for the period of 1991-2012. We find Granger causality only in the post-WDS period from transportation infrastructure expansion to economic growth and from economic growth to energy investment. These results suggest energy and transportation capacity constraints in the post-WDS period but not the pre-WDS period. Their policy implication is that China should continue its energy and transportation infrastructure investments with improved coordination.

China's rapid industrialization has induced water and energy shortage issue. Since water and energy resources are inextricably connected, the synergetic conservation of these two resources is conducive to China's sustainable development. In this paper, using a heterogeneous stochastic frontier model, we estimate the output and substitution elasticities of water and energy in China's industrial sector at the provincial level during the period of 2004-2014, in order to explore how to achieve synergetic conservation of water and energy resources by identifying the water-energy nexus. The results show that in China's industrial sector, the overall technical efficiency measured by the ratio of actual output to the ideal output in production frontier experienced a slight decline during the research period. The output elasticity (i.e., the changes in output caused by per unit change in a certain input) of water remains positive, while that of energy is negative in most years, indicating that water input increase contributes to industrial output growth, rather than energy input. Water and energy show a complementary relationship in most years, suggesting that a decrease in water input can reduce energy input. Therefore, to achieve the synergetic conservation of water and energy, the government should actively advance water-saving and energy-saving technologies by taking account of the differentiated production characteristics of different provincial-level industrial sector. In particular, when water and energy are complementary, the technological progress for saving either energy or water will be conducive to the synergetic conservation of these two resources.

Abstract Chinese food is characterized by frying and steaming, which generates a large amount of cooking oil fumes. The air quality inside a Chinese residential kitchen looks not satisfying, and the ventilation system is usually poorly designed. An excellent air distribution system is an effective way to maintain the good indoor air quality in the kitchen where high-concentration contaminants are released. This study explores a new way of make-up air based on a push–pull ventilation system in the kitchen. The performance of ventilation systems with mechanical and natural supply methods, as well as the combined effect with door seam, is evaluated experimentally and numerically. Results indicated the significance of the air distribution system on kitchen ventilation performance. The experiment results show that when an air curtain with velocity 0.6 m/s (38.1% of exhaust rate) is used in the MD (mechanical air slot, downside door seam) system, the average temperature in the occupied zone and iF (intake fraction) of the occupant could be maintained at lower values compared to that in the other three systems. Numerical results show that the average temperature and CO2 concentration in the occupied zone with the MD system are 8.0–15.8% and 33.3–60.9% lower than that for other three systems, respectively. Moreover, the MD system has the largest ratio (94.7%) of 0–200 s MAA (mean air age) area and the highest ACE (air change efficiency) (39.5%) among the four studied systems. Therefore, the MD system could be used to create a more effective airflow distribution and a good environment in the kitchen.