基于行业增长的省级可再生能源规划目标分解

为了有效的把国家可再生能源规划分阶段的落实到各个省市,做好二者之间衔接工作,研究考虑了我国在从发展中国家过渡到中等发达国家时所需要考虑的如何平衡公平与效率之阀关系的问题,结合中国可再生能源发展实际特征,提出一种基于行业增长曲线的可再生能源阶段目标分解模型.模型首先求解出中国不同的可再生能源行业的增长曲线.然后给出可再生能源发展阶段目标函数.结合区域发展规划,给出了各省的阶段目标,为了验证该模型的正确性,以风电、水电和太阳发电为代表能源,结合国家可再生能源整体规划和资源需求分布状况,分阶段提出了各省域的可再生能源发展目标.目标分解参照两个原则(1)可分解原则.国家总量目标可以根据一定的标准在不同地区、部门和行业进行分解,由全社会共同完成发展目标.(2)公平性和区域差异的原则.考虑资源禀赋和社会经济发展水平差距,各地总量目标有所区别.研究对于可再生能源规划的整体实施和监管具有一定的借鉴意义.     

基于二次能源省际调配的中国分省CO2排放量计算

节能减排目标任务的制定需要依据科学合理的CO2排放量测算。现有的IPCC提供的CO2排放量计算方法仅考虑一次能源燃料所产生的CO2,未考虑到二次能源省际调配的情况,不能真实反映各省CO2排放情况。本研究提出了考虑二次能源省际调配情况下CO2排放量的计算方法,并以2009年的数据为例,对各省能源消费CO2排放量进行了计算。考虑二次能源省际调配后,传统的能源大省如内蒙古、山西的CO2排放总量下降,东部沿海省份的CO2排放总量上升。中西部地区的CO2排放强度仍显著高于东部地区。中西部地区存在能源利用效率低、能源加工技术设备落后的情况,导致了西部地区的CO2排放强度偏高。建议中央在实施西部大开发"十二五"规划时,应当加强对中西部地区能源加工行业的投资,改善能源加工技术,改良加工设备,提高能源加工效率,降低CO2排放强度。建议由能源调入省向能源调出省份实施补偿。该部分补偿资金用于调出省的能源产业升级改造,以顺利实现节能减排的目标。     

中国西部能源及矿业开发与环境保护协调发展研究

中国西部地区自然环境脆弱且恶劣,但能源及矿产资源分布相对集中,能源及矿业开发已经成为其经济社会发展的支柱产业.本文力图从西部能源及矿业开发与环境保护协调发展、促进资源开发与生态保护的视角,综合辨析出西部地区能源及矿业开发引发的地质环境及生态环境恶化问题,主要包括土壤污染与土地破坏、水资源污染与短缺、矿区大气污染、噪声污染以及采矿诱发的各类地质灾害和生态环境破坏等.文章认为:西部地区矿产资源和能源开发等人为因素引发的地质环境及生态环境恶化问题日益突出,增强西部地区可持续发展能力,确保资源开发与环境保护的协调发展是西部地区提高能源资源保障能力的现实选择,也是转变发展方式、建设“两型”社会的必然要求.为此,本文对西部地区能矿资源开发与环境保护的协调发展提出了相关建议,主要包括:大力推行绿色发展,极开发绿色新能源;加强资源管理与污染控制,建立、健全矿产资源开发环境保护相关法律法规和体系,健全生态补偿机制;通过市场准入制度设立绿色门槛,继续整合小矿山;加强西部资源型城市与沿海地区的区域融合,减少资源开发的负外部性,破除“资源诅咒”;借鉴国际上“责任矿产开发倡议”,提高能源及矿产资源开发利益相关者的参与能力;统筹协调资源税费、地方发展基金,明确资源税的调节作用,健全利益分配机制,设立绿色发展基金;加强能矿资源开发全过程的第三方独立监管,在能源及矿产资源开发过程中实行有效透明的监管等.     

Key factors that influence households’ tree planting behaviour

Despite a decrease in indigenous forests and a growing demand for tree products in developing countries, tree planting activities are not considerably expanding in Tanzania. In this paper, we analyse factors that influence households’ tree planting behaviour, as well as the number of trees planted. Coast and Morogoro regions in the east of Tanzania were selected as the case, and data was gathered from 202 households in 11 villages in these regions where tree planting programmes have been or still are active. A Heckman model is used to analyse the factors that drive tree planting behaviour. Results indicate that households get wood energy from forest reserves (57%), in addition to their own planted trees (9.1%). Emperical findings show that the most important factors have significantly positive effects on households’ tree planting behaviour, as well as the extent to which it was implemented. These factors include households’ land sizes, households’ awareness of tree planting programmes, tree planting for wood energy, and the age of the head of the household. The right/freedom to harvest and transport tree products, households’ attitudes towards tree planting, and family size have significantly negative effects on households’ tree planting behaviour. This paper is perhaps the first comprehensive study to analyse the factors that influence households’ tree planting behaviour in Tanzania, and it uncovers results that are useful, even for other developing countries with similar conditions.     

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.     

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.     

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.     

基于LCA的废旧资源循环利用节能减排效果评估模式与方法研究——以吉林省某钢铁企业为例

促进废旧资源循环利用是加快推进我国生态文明建设,完成节能减排目标的必然选择。本文基于生命周期评价模式,从微观企业层面入手,构建产品全生命周期基准流程,引入能量输入与环境输出参数,建立废旧资源循环利用节能减排效果量化核算模型,评估再生产品的节能减排经济成效,并以吉林省某钢铁企业为例,评估"废钢-电炉"短流程和"铁矿石-高炉-转炉"长流程的能源、环境、成本差异,辨识影响废钢再循环节能减排效果的主要因素和重要环节。结果显示,再生钢铁全生命周期与原生钢铁全生命周期相比,节能588.48kgce/t,节能率为84%;主要污染物中SO2减排率最高,达92%;CO2总减排1 180.92 kg/t,减排率为67%;总成本却高出198元/t。其中,炼铁工序的节能量和减碳量最大,烧结工序SO2、NOx和烟(粉)尘减排量最大,焦化工序COD和氨氮减排量最大,回收、加工处理、炼钢环节节能量和减碳量以及SO2、NOx和烟(粉)尘减排量均为负。成本方面,再生钢铁生产成本高于原生钢铁308元/t,虽然再生钢铁由于污染减排可节省56元/t的排污费并获取54元/t的碳交易收益,但都不足以扭转电炉炼钢费用较高的现状。因此,国家应在电炉炼钢方面给予钢企及相关企业适当的财税扶持政策,在电价方面给予钢企一定的优惠或补贴,并完善废钢回收加工体系等,以促进废钢循环利用。基于LCA的废旧资源循环利用节能减排效果评估可以实现对产品生命周期全过程的资源、环境、成本的优化管理。