Ecological citizenship and democracy: Communitarian versus agonistic perspectives

Grassroots environmental movements have recently started to question the focus on sustainable consumption as a main strategy to tackle climate change. They prefer to address individuals as citizens rather than as consumers, and focus on collective rather than individual change. Two prominent movements in this regard are Transition Towns and Climate Justice Action. While both movements criticise conventional approaches, they put forward entirely different strategies for what has to happen instead. Based on extensive qualitative research, this article analyses how these movements manifest themselves in Flanders (Belgium). The focus is on their different accounts of how and why collective practices have to be built, and the place they attribute to ‘the political’ in this. The analysis reveals the existence of two different forms of ecological citizenship: one communitarian, the other agonistic.     

整合消费与增加值视角的中国行业碳排放变动分解研究

在研究影响我国CO 2排放因素领域,基于投入产出技术的分解模型已成为主要的分析工具,现有研究多分别基于消费视角或收益视角展开分析。为全面评估各行业收益与消费对其上游、下游行业碳排放的综合影响,整合基于收益与基于消费两个视角,运用2012年与2015年我国投入产出表,构建两层嵌套式结构分解分析模型(SDA),比较分析消费规模效应、收益规模效应、行业流入、流出增加值变动效应、增加值结构变动效应等14个影响各行业碳排放变动的关键因素,并借助对消费者原则碳排放估算公式的重构,更准确地实现从增加值视角对各行业消费者原则碳排放变动的关键影响因素分析。研究发现:①研究期内,我国在总产出增长29.14%的同时碳排放量上升1.46%,各行业碳排放强度下降是主要的减排因素,其中建筑业减排贡献最大。②增排效应方面,影响从大到小依次为消费规模、收益规模、完全投入结构与完全消费结构四项效应,且前两个规模效应的影响是后两个结构效应的2倍以上,尤其建筑业消费规模效应、煤炭采选产品业收益规模效应增排较大。③消费规模扩大导致增排的原因并非行业本身生产规模扩大,而主要在于建筑业、服务业等行业规模扩张时吸收其他行业流入的增加值量增多。④收益规模扩大导致的增排效应方面,细分来说从大到小依次为劳动者报酬、生产税净额、固定资产折旧、营业盈余四项效应,且行业差异显著,如煤炭采选产品业的劳动者报酬效应,石油、炼焦产品和核燃料加工品业的生产税净额效应以及电力、热力生产和供应业的营业盈余效应增排贡献较大,而煤炭采选产品业的营业盈余效应、批发、零售业和住宿、餐饮业的生产税净额效应则减排贡献较大。     

Quantifying the rebound effects of residential solar panel adoption

Customers who adopt solar panels can reduce their energy bills and lower the effective average electricity prices they pay. When the price falls, a solar consumer might consume more electricity than before – a solar rebound effect. We provide the first empirical evidence of residential solar rebound effects in the U.S. We use household level hourly and daily electricity meter data as well as hourly solar panel electricity generation data from 277 solar homes and about 4000 non-solar homes from 2013 to 2017 in Phoenix Arizona. Using matching methods and a fixed effects panel regression approach, we find that when solar electricity generation increases by 1 kWh, solar homes increase their total electricity consumption by 0.18 kWh. This indicates that solar rebound effects are estimated at 18%. Building upon our theoretical framework, the increase in consumer surplus from solar panel adoption is estimated at $972/yr.     

Optimizing Messaging to Reduce Red Meat Consumption

Red meat production has a range of negative environmental impacts. We sought to characterize the motivations, environmental attitudes and demographics of red meat-eaters, and examine the effect of message framing in reducing future meat consumption. Canadian adult meat-eaters (593) completed a survey and were randomly assigned to one of six message treatments that presented information on the environmental impacts of meat production using frames representing social norms and/or place identity constructs. Taste and quality were the most important motivators for eating meat, while moral/ethical factors were the least. Forty-nine percent of respondents indicated they would reduce red meat intake after exposure to an information only message, while the social norms frame was more effective than others (χ2). Awareness of the environmental effects increased significantly after messaging for all 13 impacts. These findings should assist communicators with designing more effective messaging aimed at encouraging pro-environmental behaviours associated with meat consumption.     

Improving Pro-environmental Behaviours in Spain. The Role of Attitudes and Socio-demographic and Political Factors

Over the last 30 years, Spain has witnessed great economic growth. Nevertheless, in spite of an increasing degree of environmental concern, environmentally friendly attitudes and behaviours are still clearly below the European average. In this context, this paper analyses the impact of personal control and attitudes, and of certain socio-demographic, economic and political variables in the development of two environmentally friendly behaviours in Spain: consumption and purchase. The data were provided by a survey carried out in 2007 by the Centro de Investigaciones Sociológicas (Centre for Sociological Research) in Spain. The results show the importance of personal control, level of environmental information, political ideology, age and educational level variables to explaining the development of pro-environmental-related consumption behaviours. Personal attitudes, work situation, female gender and level of environmental information influence pro-environmental purchase behaviour in a positive way. Taking into account that personal attitudes are more determining of pro-environmental purchase than consumption behaviour, policy measures such as informal education, tax measures, social and individual norms and interpersonal and institutional trust are discussed to increase the development of pro-environmental behaviours in Spain.     

智能家电的低待机功耗研究

从智能家电待机工作状态入手,分析电器产品中参与待机工作的各部分电路原理,提出降低潜在功耗设计思路和计算方法,从家电设计研发阶段对待机功耗进行控制,同时对待机功耗精确测量方法关键点进行解读以控制低功耗测试不确定度,有助于低待机功耗设计和测量的标准化和规范化。     

An investigation on the fuel savings potential of hybrid hydraulic refuse collection vehicles

Refuse trucks play an important role in the waste collection process. Due to their typical driving cycle, these vehicles are characterized by large fuel consumption, which strongly affects the overall waste disposal costs. Hybrid hydraulic refuse vehicles offer an interesting alternative to conventional diesel trucks, because they are able to recuperate, store and reuse braking energy. However, the expected fuel savings can vary strongly depending on the driving cycle and the operational mode. Therefore, in order to assess the possible fuel savings, a typical driving cycle was measured in a conventional vehicle run by the waste authority of the City of Stuttgart, and a dynamical model of the considered vehicle was built up. Based on the measured driving cycle and the vehicle model including the hybrid powertrain components, simulations for both the conventional and the hybrid vehicle were performed. Fuel consumption results that indicate savings of about 20% are presented and analyzed in order to evaluate the benefit of hybrid hydraulic vehicles used for refuse collection.     

电力行业的节能减排与低碳经济

中国能源结构以煤为主,火电行业是碳排放量的主体,面对低碳经济的发展模式,电力行业势必将成为CO2减排的主力军。目前,火电行业通过"上大压小"政策,实现结构减排;通过提高电力工业的烟气脱硫,实现工程减排;通过扩大清洁能源的比例,减少煤炭消耗总量,实现总量减排。使用清洁能源是实现碳减排的有效途径。指出了电力行业"节能减排"的现状和措施,分析了电力行业在"低碳经济"中所面临的新形势,并对低碳电力技术的研究与运用进行了展望,阐述了通过利用清洁能源促进碳减排的迫切性和必要性。     

AAO工艺低氧条件下的运行及其模拟

利用厌氧-缺氧-好氧(AAO)工艺探讨了在好氧池低溶解氧(DO)浓度条件下的水质指标变化情况.结果表明,当好氧池DO浓度从2.00 mg·L~(-1)降低到1.00 mg·L~(-1)和0.50 mg·L~(-1)时,系统仍然具有良好的除磷脱氮效果,出水水质指标均满足我国《城镇污水处理厂污染物排放标准》(GB 18918-2002)中的一级A标准.在此基础上,基于Bio Win 4.1软件建立了AAO工艺的活性污泥模型,对模型参数进行了灵敏度分析,并利用动态模拟对模型参数中的聚磷菌吸收乙酸或丙酸的聚羟基烷酸(PHA)产率系数(YP/PHA,seq)、聚磷菌好氧氧化PHA的储磷率(YP/PHA,aerobic)、氨氧化菌的最大单位生长速率(μmax,A)和亚硝酸盐氧化菌的最大单位生长速率(μmax,N)进行了校验.此外,对系统的曝气能耗进行了模拟评估,结果表明,与好氧池DO浓度为2.00 mg·L~(-1)时相比,好氧池DO浓度为1.00 mg·L~(-1)和0.50 mg·L~(-1)时的空气流量可分别节省23.8%和38.1%,氧转移效率可分别提高7.2%和11.7%.     

Predicting vehicle fuel consumption patterns using floating vehicle data

The status of energy consumption and air pollution in China is serious. It is important to analyze and predict the different fuel consumption of various types of vehicles under different influence factors. In order to fully describe the relationship between fuel consumption and the impact factors, massive amounts of floating vehicle data were used. The fuel consumption pattern and congestion pattern based on large samples of historical floating vehicle data were explored, drivers'' information and vehicles'' parameters from different group classification were probed, and the average velocity and average fuel consumption in the temporal dimension and spatial dimension were analyzed respectively. The fuel consumption forecasting model was established by using a Back Propagation Neural Network. Part of the sample set was used to train the forecasting model and the remaining part of the sample set was used as input to the forecasting model.