A panel study on the relationship between biofuels production and sustainable development

Biomass is one of the renewable energy sources on which policy makers are greatly dependent on since it is a flexible feedstock capable of conversion into electricity, transport liquid fuels and heat by chemical and biological processes on demand. Though numerous publications have examined the relationship of economic growth with renewable energy and other parameters, biomass energy has never been included in these studies. Then, this study examines the causal relationship within a multivariate panel cointegration/error correction framework which combines the cross-section and time series data while allowing for heterogeneity across different provinces. After employing panel data regression model ranging from 2003 through 2012 to examine the relationships of biofuels production with sustainable development in China, the paper concludes that the development of biofuel energy production integrated with the consideration of the improvement of income per capita, and the attraction of more capital investment, does make a significant contribution to economic growth. However, some negative side effects including the increase of greenhouse emissions and the decrease of marginal land still coexist with the economic development. Of course, the importance of these findings lies on their implications and their adoption on strategic policies.     

Suitable error evaluation criteria selection in the wind energy assessment via the K-means clustering algorithm

In this paper, wind energy potential of four locations in Xinjiang region is assessed. The Weibull distribution as well as the Logistic and the Lognormal distributions are applied to describe the distributions of the wind speed at different heights. In determining the parameters in the Weibull distribution, four intelligent parameter optimization approaches including the differential evolutionary, the particle swarm optimization, and two other approaches derived from these two algorithms and combined advantages of these two approaches are employed. Then the optimal distribution is chosen through the Chi-square error (CSE), the Kolmogorov–Smirnov test error (KSE), and the root mean square error (RMSE) criteria. However, it is found that the variation range of some criteria is quite large, thus these criteria are analyzed and evaluated both from the anomalous values and by the K-means clustering method. Anomaly observation results have shown that the CSE is the first one should be considered to be eliminated from the consequent optimal distribution function selection. This idea is further confirmed by the K-means clustering algorithm, by which the CSE is clustered into a different group with KSE and RMSE. Therefore, only the reserved two error evaluation criteria are utilized to evaluate the wind power potential.     

Modeling urban solar energy with high spatiotemporal resolution: A case study in Toronto,Canada

This research presents a method to determine the maximum potential for the capturing of solar radiation on the rooftop of buildings in an urban environment. This involves the modeling of solar energy potential and comparison to historical building energy demand profiles through the use of 3-D solar simulation software tools and geographic information systems (GIS). The objective is to accurately identify the amount of surface area that is suitable for solar photovoltaic (PV) installations and to estimate the hourly PV electricity generation potential of existing building rooftops in an urban environment. This study demonstrates a viable approach for modeling urban solar energy and offers valuable information for electricity distributors, policy makers, and urban energy planners to facilitate the substantial design of a green built environment. The developed methodology is comprised of three main sections: (1) determination of suitable rooftop area, (2) determination of the amount of incident solar radiation available per rooftop, and (3) estimation of hourly solar PV electricity generation potential. A case study was performed using this method for Ryerson University, located in Toronto, Canada. It was found that solar PV could supply up to 19% of the study area’s electricity demands during peak consumption hours. The potential benefits of solar PV was also estimated based upon hourly greenhouse gas emission intensity factors as well as Time-of-Use (TOU) savings through the Ontario Feed-in-Tariff (FIT) program, which allows for better representation of the positive impacts of solar technologies.     

The effect of industry activities on public support for ‘fracking’

Research suggests that previous, current, and prospective extractive industry activities influence perceptions of new development. Studies that have drawn this conclusion, however, have usually focused on specific projects in specific communities. Here, these factors are examined on an aggregate, national scale. Combining geospatial data on extractive industry activities and survey data from a nationally representative sample (N = 1061), the influence of extractive industry activities on support for fracking is studied. While limited evidence is found for the impact of proximity to oil and gas wells or production on support for fracking, employment levels in the natural resources and mining sector in the respondent’s county and residence in an area experiencing active oil and gas development significantly increase support for fracking. The results highlight the role of spatial and community factors in shaping support for energy development.     

Moving targets: Carbon pricing,energy markets,and social movements in Australia

Reporting on the origins and directions of social movement strategy on climate and energy issues in the last decade, the shifts in ‘climate movement’ practice are discussed using a neo-Polanyian account of the political economy of climate change combined with sociological analysis of the strategic decisions campaigners reported making. Since the mid-2000s, Australia’s climate movement has been engaged in three concurrent arenas of political contestation. The longest-standing arena of movement activity has been negotiations over climate policy. More recently, activists and communities are engaged in a struggle over the expansion of fossil fuels. A third contest has been waged over the present and future position of renewable energy technologies in Australia’s electricity market. In the wake of climate policy failure, energy campaigns have been deepened, and it seems that a broader energy justice agenda is being forged. New strategic dilemmas are visible in the field.     

家庭部门生活能源消费碳排放:测度与驱动因素研究

本文运用IPCC的二氧化碳排放量测算方法,在省际层面测度了我国家庭部门直接能源消费碳排放,并基于扩展的STIRPAT和Kaya模型,构建家庭部门直接能源消费碳排放影响因子动态面板数据模型,对我国2003-2012年分省面板数据样本及城乡子样本进行系统GMM估计。本文研究表明,第一,我国城乡家庭部门碳排放总量和人均碳排放在近十年都呈快速上升趋势,家庭部门碳排放的空间分布具有明显的地域差异特征,高碳排放地区主要集中在东、中部地区,西部地区的碳排放水平较低;第二,城乡家庭部门生活能源消费的上期碳排放量对本期碳排放产生重要的正向影响,这反映出我国家庭部门碳排放具有显著的惯性特征和路径依赖性,是一种动态自适应机制;人口规模、居民消费水平、能源消费结构、碳排放强度、能源消费强度和城镇化因素,都对我国居民能源消费碳排放总量及人均碳排放具有显著的影响,城乡之间的家庭能源消费碳排放驱动因素存在差异。本文研究得到如下启示及政策含义:家庭部门碳减排将是一个有步骤、分区域的渐进过程,我国碳减排政策应当兼顾消费升级和碳排放的双重目标,努力构建分层次碳减排的适应性预期机制。具体而言,一方面应着眼于引导和激励居民低碳消费,缓解人口规模增加、消费水平提升和城镇化对家庭部门碳减排的压力;另一方面要通过能源价格改革、财政政策和环境规制政策等优化我国能源消费结构,不断降低煤炭消费比重,提高清洁能源的消费。同时,通过技术创新、设备改造等科技手段提高煤炭利用效率,降低碳排放强度,这些政策将更有利于城镇家庭部门碳减排。     

城镇化与工业化对能源强度影响的实证研究——基于截面相关和异质性回归系数的非平衡面板数据模型

城镇化、工业化对中国能源强度的影响如何?如何在快速推进城镇化、工业化进程的同时确保节能减排目标的实现?论文以能源强度指标代替传统的能源消费指标来反映能源综合利用效率,并应用考虑截面相关性和异质性回归系数的非平衡面板数据模型,使用共同相关效应组均值(CCEMG)估计方法对中国1978-2014年城镇化、工业化与能源强度之间的关系进行分析。研究结果表明:人均实际GDP增长1%,能源强度将会降低0.412%,工业化水平增长1%,能源强度将会上升0.630%,而由于生产消费等经济活动的增加、高度集中化以及规模经济的综合作用,使得城镇化对能源强度的影响并不确定。联系研究结论,本文提出政策建议:我国应加快产业结构升级,转变经济增长方式;构建绿色制造体系,推进"五化"协同发展;推进绿色、循环、低碳发展的新型城镇化建设,提高城镇化质量,提升我国整体的能源效率,确保节能减排目标的实现,推动经济全面、协调、可持续发展。     

Rebound effect and its decomposition – an analysis based on energy types in China

Rebound effect derived from energy efficiency improvement has been widely invested. However, most of studies focus on the rebound effect of the energy composite level and neither distinguish nor compare different energy types. We compare the differences in energy saving and energy rebound between primary and secondary energy sources, and further decompose the rebound effect into production rebound part and final demand component. To do so, we add a module for rebound into a comparative state China-CGE model. We design and test two simulation scenarios using the model. In Scenario 1, all production sectors’ energy efficiency of using primary energy increases by 5%. In Scenario 2, all production sectors’ energy efficiency of using secondary energy increases by 5%. The results show that Scenario 2 leads to more GDP growth and more energy saving. Our scenarios show rebound effects range between 9.6% and 27.9%, and in general are higher when energy efficiency of using primary energy sources is improved. Our decomposition analysis shows that improving energy efficiency in production sectors would stimulates energy use of final demand. Indeed, the consumption side has significant contribution to rebound in secondary energy use, especially in crude oil and gas. This study reveals that improving efficiency of using secondary energy is better than improving that of primary energy, both in terms of economic impact and energy rebound. And complementary policies that prevent energy services prices from falling too much can be adopted to reduce rebound. Controlling residential energy use could also be effective in reducing rebound, this has particular implication to economies in which residential energy consumption are far from saturation.     

Global trends and development of energy services industry in China

Energy service is an effective way to promote energy conservation by market mechanisms, including energy saving services, energy procurement, supply of many varieties of energy, supply of renewable energy technologies, energy-related consulting services, risk management, etc. China is a major energy consumer but energy is in short supply, and the efficiency of energy use is low. China’s energy service industry has expanded rapidly, in terms of both the number of new Energy Service Companies entering the market and amount of capital invested in Energy Performance Contracting projects, but the energy service sector in China is still at an early stage of development. Developed countries began early in developing the energy service sector and their energy service market is mature, and the experience of developed countries shows that energy services play a significant role in advancing energy saving and emission reduction. Under the new situation, China needs combine energy services experience of developed countries, and take following measures to accelerate China’s energy services rapid and healthy development, including the long-term aspects of policy planning, energy-saving core technology, finance and capital investment, public sector reductions, personnel training, and so on.     

The influence of Chinese population policy change on resources and the environment

Universal two-child policy has been implemented since the end of 2015 in China. This policy is anticipated to bring a significant increase in the total population, with profound influences on the resources and environment in the future. This paper analyzes the changing dynamics of urban and rural population, and forecasts urban and rural population from 2016 to 2030 at national and provincial scale using a double log linear regression model. Drawing upon the results of these two predictions, the impact of the population policy change on Chinese resources consumption and environmental pollution are predicted quantitatively. Given the future total population maintains current levels on resources consumption and environmental emission, the additional demand of resources and environment demand for the new population is forecasted and compared against the capacity on supply side. The findings are as follows: after implementing the universal two-child policy, China’s grain, energy consumption, domestic water demand, and pollutant emissions are projected to increase at different rates across provinces. To meet the needs arising from future population growth, food and energy self-sufficiency rate will be significantly reduced in the future, while relying more on imports. Stability of the water supply needs to be improved, especially in Beijing, Henan, Jiangsu, Qinghai, and Sichuan where the gap in future domestic water demand is comparatively larger. Environmental protection and associated governing capability are in urgent need of upgrade not least due to the increasing pressure of pollution.