Energy efficiency evaluation, changing trends and determinants of energy productivity growth across South Asian countries: SBM-DEA and Malmquist approach.

Energy efficiency is widely regarded as the most efficient means of supplying additional energy to meet the rising demand. However, extensive energy consumption causes greenhouse emissions, environmental destruction, and a decrease in energy efficiency (EE). This study investigates the role of energy efficiency and productivity growth in the ecological improvement of South Asia. Moreover, it evaluates the determinants (efficiency change or technology change) of energy productivity change across different SA (South Asian) countries. To estimate the energy efficiency and productivity change, we employed SBM-DEA and Malmquist Productivity Index methods with three inputs (capital stock, labor, and energy consumption), a single desirable output (gross domestic product) and a single undesirable output (CO2 emissions) on the well-extended dataset (2001-2019) for 6 South Asian countries. Furthermore, to check the impact of energy policy (2010) over the study period, the statistical significance of the change in mean scores for energy efficiency and productivity over two time periods (2001-2010 and 2011-2019) and six countries was examined using the Mann-Whitney U and Kruskal-Wallis tests. Results reveal that the average EE score of all 6 SA countries for the study period is 0.7278. This score shows that SA countries still have the potential of 27.22% to improve their energy efficiency to minimize the inputs to get the optimum output level with the least emissions. The primary determinant of energy productivity growth is technological change instead of efficiency. The average energy efficiency level is significantly different for two time periods, 2001-2010 and 2011-2019. Results conclude that energy efficiency and productivity in SA declined over the period, and potential causes are an inefficiency in the energy conversion process, extensive utilization of inputs, and less output growth.

Research on hot rolling scheduling problem based on Two-phase Pareto algorithm.

Under the background of excess capacity and energy saving in iron and steel enterprises, the hot rolling batch scheduling problem based on energy saving is a multi-objective and multi constraint optimization problem. In this paper, a hybrid multi-objective prize-collecting vehicle routing problem (Hybrid Price Collect Vehicle Routing Problem, HPCVRP) model is established to ensure minimum energy consumption, meet process rules, and maximize resource utilization. A two-phase Pareto search algorithm (2PPLS) is designed to solve this model. The improved MOEA/D with a penalty based boundary intersection distance (PBI) algorithm (MOEA/D-PBI) is introduced to decompose the HPCVRP in the first phase. In the second phase, the multi-objective ant colony system (MOACS) and Pareto local search (PLS) algorithm is used to generate approximate Pareto-optimal solutions. The final solution is then selected according to the actual demand and preference. In the simulation experiment, the 2PPLS is compared with five other algorithms, which shows the superiority of 2PPLS. Finally, the experiment was carried out on actual slab data from a steel plant in Shanghai. The results show that the model and algorithm can effectively reduce the energy consumption in the process of hot rolling batch scheduling.

The Influence of Information Intervention Cognition on College Students' Energy-Saving Behavior Intentions.

Based on the theory of planned behavior, this research examines the influence of different types of information on the behavioral intentions of college students in the context of perceived behavioral control (perceived self-efficacy and perceptual control) as mediating variables. The results showed that: (1) Different types of information intervention factors have different effects on perceptual self-efficacy and perceptual control; the influence degree of economic cost has the strongest effect, followed by group pressure, while the influence degree of publicity and education has the weakest effect. However, policy intervention has no statistically significant effect on both of them (perceived self-efficacy and perceptual control). (2) Two variables, perceived self-efficacy and perceptual control, serve as mediators between information intervention factors and energy-saving behavior intention. (3) Individual characteristic factors have significant moderating effects on each path in the model of information intervention-perceived behavior control-intention. Finally, suggestions are made on how to encourage college students to more effectively save energy.

Incorporating Injury Prevention Into Energy Weatherization Programs.

Clients receiving weatherization/energy services with an added injury prevention home assessment with modifications/repairs experienced a decline in falls and thus fall-related costs. Interventions in 35 homes were associated with significant reductions in falls from baseline to 6 months postintervention (from 94% to 9%; P < .001) and falls with calls for assistance (from 23% to 3%; P < .02). The decline in falls with calls for assistance in the intervention group was significant when adjusted for a comparison group effect (P = .07). At a median cost of $2058 per home, the addition of an injury prevention component led by an occupational therapist offers the potential to avoid expensive fall-related medical costs (lift assistance, hospital transport and admission, long-term care). Integration of injury prevention into weatherization work, which targets lower-income seniors with high energy use, offers potential to reduce costly hospitalizations and poor health outcomes.

Does regional energy consumption disparities assist to control environmental degradation in OBOR: an entropy approach.

China launched the One Belt & One Road (OBOR) initiative to minimize the energy resource shortage. The China's nearby countries are rich in energy resources especially Middle East and North Africa (MENA) and Asian countries which make them ideal locations to cooperate with China in terms of energy resources, as 42.8% of world energy consumption belongs to OBOR countries. The present study elaborates the spatial distribution pattern of energy consumption disparities and its impact on environment. To do this, an entropy approach is utilized to compute the energy consumption inequalities in OBOR and its regions. The spatial and Pareto analysis show that MENA, East, and Southeast Asian economies have the highest degree of energy consumption inequalities, while European and Central Asian economies show the lowest energy consumption inequalities in OBOR region. The long-run estimates indicate that energy consumption inequalities enhance the CO2 emission in OBOR and its region except South and Southeast Asia. Financial development also has a significantly positive impact on CO2 emission in all models for OBOR and its regions except East Asia. Based on findings, the spatial distribution analysis is applicable to maintain balance in regional energy consumption inequality within OBOR and its regions.

Empirical Study on Households' Energy-Conservation Behavior of Jiangsu Province in China: The Role of Policies and Behavior Results.

With the improvement of living quality and the increase of energy consumption of residents, their energy conservation behavior (ECB) plays an increasingly important role in energy conservation and emission reduction. As a kind of environmental behavior, ECB of residents is a complicated process. In this paper, ECB is divided into four types, considering habit adjustment, quality threshold, efficiency investment, and interpersonal facilitation. A comprehensive conceptual framework is built, adding perception about energy conservation results (PER) and contextual factors from a new perspective. Based on a survey in Jiangsu province of China, this paper examines the impact of intention on behavior under the moderation of contextual factors, as well as the effect of perception of energy-conservation results on intention and ECB by means of multivariate statistical analysis. The results show that the intention of energy conservation is the determinant of behavior, but it does not well transform into behavior, especially into quality threshold and interpersonal facilitation behavior. Different contextual factors have positive effects on the relationship of intention and different behavior. However, modulating effects of contextual factors as amplifiers do not function effectively due to their low rating scores. PER has a positive impact on intention but not on all types of ECB. Finally, this paper presents important implications for policy makers to optimize energy conservation policy.

Sustainability Evaluation.

The long-term substitution of fossil resources can only be achieved through a bio-based economy, with biorefineries and bio-based products playing a major role. However, it is important to assess the implications of the transition to a bio-based economy. Life cycle-based sustainability assessment is probably the most suitable approach to quantify impacts and to identify trade-offs at multiple levels. The extended utilisation of biomass can cause land use change and affect food security of the most vulnerable people throughout the world. Although this is mainly a political issue and governments should be responsible, the responsibility is shifted to companies producing biofuels and other bio-based products. Organic wastes and lignocellulosic biomass are considered to be the preferred feedstock for the production of bio-based products. However, it is unlikely that a bio-based economy can rely only on organic wastes and lignocellulosic biomass.It is crucial to identify potential problems related to socio-economic and environmental issues. Currently there are many approaches to the sustainability of bio-based products, both quantitative and qualitative. However, results of different calculation methods are not necessarily comparable and can cause confusion among decision-makers, stakeholders and the public.Hence, a harmonised, globally agreed approach would be the best solution to secure sustainable biomass/biofuels/bio-based chemicals production and trade, and to avoid indirect effects (e.g. indirect land use change). However, there is still a long way to go.Generally, the selection of suitable indicators that serve the purpose of sustainability assessment is very context-specific. Therefore, it is recommended to use a flexible and modular approach that can be adapted to various purposes. A conceptual model for the selection of sustainability indicators is provided that facilitates identifying suitable sustainability indicators based on relevance and significance in a given context.

Urban energy environment efficiency in China: Based on dynamic meta-frontier slack-based measures.

Rapid economic growth in China has resulted in a significant increase in particulate matter (PM2.5) and sulfur dioxide (SO2), the reduction of which has become a primary government focus. However, as the energy consumption and air pollutant emissions in Chinese cities have very significant regional characteristics, individual governance measures are necessary. This study used 2013 to 2016 energy consumption data from 31 Chinese cities to evaluate the dynamic efficiency of the urban environments. Labor, fixed assets, and energy consumption were taken as the inputs, gross domestic product (GDP) was taken as the output, and particulate matter (PM2.5) and sulfur dioxide (SO2) were taken as the carry-over variable indicators. Using a meta-frontier dynamic DEA model, the 31 cities were classified into high-income and upper-middle-income cities, the overall 2013-2016 energy consumption and air pollutant efficiency scores were analyzed, and improvements and changes were recommended to increase the efficiencies. Large differences were found in the energy consumption and air pollution emissions efficiency scores and the needed improvements, with the hig-income cities performing better overall than the upper-middle-income cities. While there have been some significant improvements in SO2 emissions, PM2.5 improvements have been far slower. Therefore, in most cities, more control measures are needed to control PM2.5 emissions. However, in addition to improving PM2.5 in the upper-middle-income cities, SO2treatments are also needed. Implications: There are big differences in the expectation of improvement of the two pollutants in all cities. In many Western cities, the expectation of PM2.5 improvement in the past years has not been reduced, but has been expanding. This shows that the central government has unified the air pollution control policies and the existing air pollution control measures formulated and implemented by the local governments.

The impact on air quality of energy saving measures in the major cities signatories of the Covenant of Mayors initiative.

This study is a first attempt to evaluate how the major efforts made by several European cities in the frame of the Covenant of Mayors (CoM) initiative can impact the air pollution levels in the participating cities. CoM is by no mean one of the major cities initiatives aimed at mitigating climate change, supporting local authorities in the implementation of their climate action plans. Energy savings measures reported in the CoM cities' action plans have been analysed from the air quality perspective in order to find quantitative relations in the way local authorities deal with mitigation and how these practices are expected to have consequences on the air quality at urban level and finally positively impacting the citizens' health. In the paper, the air quality 2713 energy saving measures proposed by 146 cities located in 23 countries in the frame of the CoM are selected and their co-benefits for air quality and public health estimated by means of SHERPA, a fast modelling tool that mimics the behaviour of a full physically-based Chemical Transport Model. Besides evaluating the overall benefits of this subset of mitigation measures for the air quality, the study also investigates the relevance of some factors such as the implementation sector, the city size and the pollution levels in achieving the highest possible co-benefits. The results presented refer to the special field covered by the study, i.e. energy saving measures and are not automatically referable to other types of measures. Nevertheless, they clearly show how climate mitigation and air quality policies are deeply interconnected at the urban level.

Decoupling effect and forecasting of economic growth and energy structure under the peak constraint of carbon emissions in China.

The decoupling effect between economic growth and energy structure was quantitatively analyzed from 1999 to 2014 across China. The results showed it existed weak decoupling effects in most regions. Based on the analysis of the influence of energy structure on carbon intensity, using scenario simulation methods and Markov chain modeling, the carbon intensity was predicted for China in 2020. The impact of energy structure adjustment on the carbon intensity to meet China's carbon target by 18 possible scenarios are calculated. Furthermore, the peak value of carbon emissions was also calculated in 2030. The results showed that the carbon intensity predicted for China in 2020 can be achieved regardless of whether the energy structure was adjusted or not when energy saving and carbon reduction policies maintained with economic growth at 6-7%. Moreover, given fixed energy structure growth, for each 1% of economic growth, the carbon intensity will decrease by about 3.5%. Given fixed economic growth, the decrease of energy intensity will be greater if the control of energy consumption is stronger. The effect of energy structure adjustment on the decreasing of carbon intensity will be 4% higher under constraints than without constraints. On average, the contribution of energy structure adjustment to achieving the carbon intensity target was calculated as 4% higher than that with constraints. In addition, given relatively fixed economic growth at 6-7%, the peak value of carbon emission in 2030 was calculated as 13.209 billion tons with constraints and 14.38 billion tons without constraints.

Spatial econometric analysis of factors influencing regional energy efficiency in China.

Increased environmental pollution and energy consumption caused by the country's rapid development has raised considerable public concern, and has become the focus of the government and public. This study employs the super-efficiency slack-based model-data envelopment analysis (SBM-DEA) to measure the total factor energy efficiency of 30 provinces in China. The estimation model for the spatial interaction intensity of regional total factor energy efficiency is based on Wilson's maximum entropy model. The model is used to analyze the factors that affect the potential value of total factor energy efficiency using spatial dynamic panel data for 30 provinces during 2000-2014. The study found that there are differences and spatial correlations of energy efficiency among provinces and regions in China. The energy efficiency in the eastern, central, and western regions fluctuated significantly, and was mainly because of significant energy efficiency impacts on influences of industrial structure, energy intensity, and technological progress. This research is of great significance to China's energy efficiency and regional coordinated development.

Evaluating the efficiency of nuclear energy policies: an empirical examination for 26 countries.

The decarbonization of the global economy is an urgent concern. As a potential solution, it can be important to understand the efficiency of nuclear energy policies. For this purpose, the paper analyzes whether there is a unit root in nuclear energy consumption in 26 countries and it uses the unit root tests with two endogenous (unknown) structural breaks. The paper finds that nuclear energy consumption is stationary around a level and the time trend in 25 of 26 countries and nuclear energy consumption contains a unit root only in France. The paper also discusses the potential implications of the findings.

Green Collar Workers: An Emerging Workforce in the Environmental Sector.

OBJECTIVE: We describe the socio-demographic, occupational, and health characteristics of "green collar" workers, a vital and emerging workforce in energy-efficiency and sustainability. METHODS: We linked data from the 2004 to 2012 National Health Interview Surveys (NHIS) and US Occupational Information Network (O*NET). Descriptive and logistic regression analyses were conducted using green collar worker status as the outcome (n = 143,346). RESULTS: Green collar workers are more likely than non-green workers to be men, age 25 to 64 years, obese, and with less than or equal to high school (HS) education. They are less likely to be racial/ethnic minorities and employed in small companies or government jobs. CONCLUSIONS: Green collar workers have a distinct socio-demographic and occupational profile, and this workforce deserves active surveillance to protect its workers' safety. The NHIS-O*NET linkage represents a valuable resource to further identify the unique exposures and characteristics of this occupational sector.

Energy consumption and CO2 emissions in Iran, 2025.

Climate change and global warming as the key human societies' threats are essentially associated with energy consumption and CO2 emissions. A system dynamic model was developed in this study to model the energy consumption and CO2 emission trends for Iran over 2000-2025. Energy policy factors are considered in analyzing the impact of different energy consumption factors on environmental quality. The simulation results show that the total energy consumption is predicted to reach 2150 by 2025, while that value in 2010 is 1910, which increased by 4.3% yearly. Accordingly, the total CO2 emissions in 2025 will reach 985million tonnes, which shows about 5% increase yearly. Furthermore, we constructed policy scenarios based on energy intensity reduction. The analysis show that CO2 emissions will decrease by 12.14% in 2025 compared to 2010 in the scenario of 5% energy intensity reduction, and 17.8% in the 10% energy intensity reduction scenario. The results obtained in this study provide substantial awareness regarding Irans future energy and CO2 emission outlines.

Analysis of energy-related CO2 emissions and driving factors in five major energy consumption sectors in China.

Continual growth of energy-related CO2 emissions in China has received great attention, both domestically and internationally. In this paper, we evaluated the CO2 emissions in five major energy consumption sectors which were evaluated from 1991 to 2012. In order to analyze the driving factors of CO2 emission change in different sectors, the Kaya identity was extended by adding several variables based on specific industrial characteristics and a decomposition analysis model was established according to the LMDI method. The results demonstrated that economic factor was the leading force explaining emission increase in each sector while energy intensity and sector contribution were major contributors to emission mitigation. Meanwhile, CO2 emission intensity had no significant influence on CO2 emission in the short term, and energy consumption structure had a small but growing negative impact on the increase of CO2 emissions. In addition, the future CO2 emissions of industry from 2013 to 2020 under three scenarios were estimated, and the reduction potential of CO2 emissions in industry are 335 Mt in 2020 under lower-emission scenario while the CO2 emission difference between higher-emission scenario and lower-emission scenario is nearly 725 Mt. This paper can offer complementary perspectives on determinants of energy-related CO2 emission change in different sectors and help to formulate mitigation strategies for CO2 emissions.

A framework for energy use indicators and their reporting in life cycle assessment.

Energy use is a common impact category in life cycle assessment (LCA). Many different energy use indicators are used in LCA studies, accounting for energy use in different ways. Often, however, the choice behind which energy use indicator is applied is poorly described and motivated. To contribute to a more purposeful selection of energy use indicators and to ensure consistent and transparent reporting of energy use in LCA, a general framework for energy use indicator construction and reporting in LCA studies will be presented in this article. The framework differentiates between 1) renewable and nonrenewable energies, 2) primary and secondary energies, and 3) energy intended for energy purposes versus energy intended for material purposes. This framework is described both graphically and mathematically. Furthermore, the framework is illustrated through application to a number of energy use indicators that are frequently used in LCA studies: cumulative energy demand (CED), nonrenewable cumulative energy demand (NRCED), fossil energy use (FEU), primary fossil energy use (PFEU), and secondary energy use (SEU). To illustrate how the application of different energy use indicators may lead to different results, cradle-to-gate energy use of the bionanomaterial cellulose nanofibrils (CNF) is assessed using 5 different indicators and showing a factor of 3 differences between the highest and lowest results. The relevance of different energy use indicators to different actors and contexts will be discussed, and further developments of the framework are then suggested. Integr Environ Assess Manag 2016;12:429-436. © 2015 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of SETAC.