组合灰色预测模型应用于山东省碳排放预测

根据山东省2000—2012年工业、建筑业和交通运输业能源消费数据测算得到碳排放量,基于GM(1,1)模型、Verhulst模型和SCGM(1,1)c模型建立组合灰色预测模型,运用预测有效度方法确定组合预测模型的权重系数。选用2000—2009年三大碳排放行业的实际值作为原始数据,利用各预测模型预测2010—2012年碳排放量。结果表明:组合灰色预测模型比单一预测模型具有更高的预测精度。利用组合模型预测山东省2013—2017年各行业碳排放量,为相关部门制定节能减排政策提供理论及方法借鉴。     

我国北方农村生活燃煤情况调查、排放估算及政策启示

北方重灰霾频发时段与集中燃煤在冬季高度重合,引发了对农村散煤严重污染的担忧,但缺乏有力的统计数据支持. 2014年9月,在河北保定开展了当地农村生活能源使用情况入村调查,共获得5个村庄中543户家庭的能源使用数据. 结果表明:①保定农村地区散煤、电、液化气的使用覆盖率均很高,分别达到97%、100%和94%,反映了当前农村居民的能源消费更倾向于商业购置;而木柴和秸杆的使用覆盖率则较低,分别为13%和11%,表明传统的依赖于木柴和秸杆的能源方式已发生了根本改变. ②目前煤炭在农村能源结构中仍居主导地位,占近80%(其中散煤占76%,蜂窝煤占2%),其次为电力(10%)、液化气(5%),秸杆和木柴的比例(小于5%)均较低. ③调查估算,保定农村地区在2013年冬季采暖季(2013年11月─2014年3月)散煤用量超过500×104 t,高于《中国能源统计年鉴(2013)》中河北全省2012年农村散煤的用量(467×104 t),表明现有能源统计体系有待进一步完善. ④保定农村地区散煤的烟粉尘(即PM)和SO₂排放量分别为5.4×104和11.2×104 t,均超过了《中国环境统计年报(2013)》中保定的工业废气和城镇生活领域相应的排放量(甚至超过2个领域排放量之和),表明农村散煤燃烧的排放问题确应引起特别关注.由于农村散煤燃烧排放高度较低,其单位排放对空气污染的贡献要远高于高架源排放,因此,建议国家和地方将农村能源结构调整置于当前能源结构调整计划的最优先领域,采取综合措施,消除农村散煤使用的污染排放,这可能是应对当前冬季灰霾问题的关键举措之一.      

产业结构调整对山东省碳排放的影响

在全球变暖的背景下,山东作为工业大省,碳排放总量居全国第一。因此,如何通过“转方式、调结构”以控制和减少碳排放是山东省日益紧迫的重大课题。论文采用LMDI分解方法定量分析了1994-2010 年山东省产业结构调整对碳排放的影响,并在此基础上结合LEAP模型预测2030 年之前的产业结构调整对山东碳排放的贡献。得出以下结论：①1994-2010 年产业结构效应为351.39×10⁴ t 标煤,对碳排放增长的贡献度为3.91%;②工业比重上升或下降1 个百分点所对应的CO₂排放量增加或减少78.6×10⁴～83.7×10⁴ t 标煤;③在基准情景和低碳情景下,到2030 年未来产业结构的调整对CO₂ 排放增长的贡献率分别约为-5.3%和-10.4%。这表明,与此前产业结构变动导致碳排放量增加的情形相反,未来产业结构的调整有助于减少碳排放。     

Duct-venting of dust explosions in a 20 L sphere at elevated static activation overpressures

Ducts are often recommended in the design of dust explosion venting in order to discharge materials to safe locations. However, the maximum reduced overpressure increases in a duct-vented vessel rather than in a simply vented vessel. This needs to be studied further for understanding the duct-venting mechanism. Numerous duct-vented dust explosion experiments were conducted, using a 20 L spherical chamber at elevated static activation overpressures, ranging from 1.8 bar to 6 bar. Duct diameters of 15 mm and 28 mm, and duct lengths of 0 m (simply venting), 1 m and 2 m, were selected. Explosion pressures both in the vessel and in the duct were recorded by pressure sensors, with a frequency of 5 kHz. Flame signals in the duct were also obtained by phototransistors. Results indicate that the secondary explosion occurring in the duct increases the maximum reduced overpressure in the vessel. The secondary explosion is greatly affected by the duct diameter and static activation overpressure, and hence influences the amplification of the maximum reduced overpressure. Larger static activation overpressure decreases the severity of the secondary explosion, and hence decreases the increment in the maximum reduced overpressure. The secondary pressure peak is more obvious as the pressure accumulation is easier in a duct with a smaller diameter. However, the increment of the maximum reduced overpressure is smaller because blockage effect, flame front distortion, and turbulent mixing due to secondary explosion are weaker in a narrow duct. The influence of duct length on the maximum reduced overpressure is small at elevated static activation overpressures, ranging from 1.8 bar to 6 bar at 15 mm and 28 mm duct diameters.     

Targeting for optimal grid-wide deployment of carbon capture and storage (CCS) technology

Carbon capture and storage (CCS) techniques are considered as one of the promising approaches to reduce carbon dioxide (CO₂) emissions from fossil fuel based power generation, which still accounts for a significant portion of greenhouse gas emissions in the world. CCS technology can be used to mitigate greenhouse gas emissions, with the additional advantage that it allows continuing use reliable and inexpensive fossil fuels. However, CCS retrofit entails major capital costs as well as a reduction of overall thermal efficiency and power output. Thus, it is essential for planning purposes to implement the minimal extent of CCS retrofit while meeting the specified carbon emission limits for the power sector. At the same time, it is necessary to plan for compensatory power generation capacity to offset energy losses resulting from CCS retrofit. In this paper, an algebraic targeting technique is presented for planning of grid-wide CCS retrofits in the power generation sector with compensatory power. The targeting technique is developed based on pinch analysis. In addition, the proposed methodologies are illustrated through case studies based on grid data in India and the Philippines. Sensitivity analysis is carried out to determine the suitable CCS technology and compensatory power source which satisfy emission limits.     

基于居民合理生活消费的人均碳排放计算

分析了我国居民消费直接与间接碳排放的变化及现状,并通过居民消费的微观角度,分析计算基于居民合理生活消费人均碳排放.试图通过居民消费的角度建立人均碳排放的核算方法,给出建议数据.根据国内当前主要消费环节的碳排放水平,对比国际先进水平和国内碳减排升级潜力,计算了满足居民正常小康生活水平条件下的人均碳排放,年人均排放约2203kg~2333kg碳.居民基本生活的碳排放主要集中在供暖制冷、住宅使用、污染治理和基础建设分摊等方面,而衣物与食品消耗、生活物质材料等方面的碳排放量所占比重相对较低.     

中国服务业能源消费CO2排放及其因素分解

基于IPCC温室气体排放清单指南中的CO₂排放因子与核算方法,估算了1995—2010年中国服务业能源消费与CO₂排放量,并对其总体变化趋势进行时间序列分析;以LMDI(对数平均迪氏指数)法辨识与分解3个时段(1995—2000年、2000—2005年和2005—2010年)中影响中国服务业CO₂排放量变动的关键因素及其对CO₂排放量的贡献值. 结果表明:1995—2010年中国服务业能源消费CO₂排放量增长态势明显,累计排放总量为853197.55×104t;服务业能源消费主要依赖于高碳化能源燃料,各年度油品和煤品分别占能源消费总量的67%~74%和5%~27%;LMDI分析结果显示,1995—2010年产业规模和人口效应引起CO₂排放增加量分别为133357.10×104和7691.25×104t,能源效率和能源结构引起CO₂排放减少量分别为59034.50×104和23898.60×104t. 提出CO₂减排对策:①以经济、政策和监管手段促进服务业节能减排;②依托科技创新提高能源综合利用效率,降低服务业CO₂排放量.      

广东货船水运的温室气体排放和低碳发展对策

作为我国港口大省和低碳试点省,广东需先行测算船舶水运的GHG(温室气体)排放量基线,以探究低碳水运对策. 通过文献调研收集适用数据和资料,基于引擎功率法,测算了广东抵港货船在2010年的GHG排放量. 结果表明:广东专属经济区海域内货船水运的GHG总排放量为2887×104t,不确定性在-36%~45%之间,其中在领海区域内的排放量为730×104t;远洋集装箱船是GHG最大排放源,占总排放量的43%;集装箱船、干散货船、油轮和其他货船的GHG排放量不确定性均介于-30%~50%之间,远洋货船的主引擎在正常航行模式下输出功率是最主要的不确定性源. 基于分析船舶水运的GHG排放特征,提出船舶减速、向远洋货船供应岸电和内河货船主引擎转用天然气共3项低碳节能措施,共可减排40%的GHG排放量.该研究结果不仅为广东低碳水运发展提供基础性的GHG排放数据,也可为其他港口地区提供估算水运业GHG排放量的技术方法参考和实践经验.      

Analysis of household energy consumption and related CO2 emissions in the disregarded villages of Lijiang City,China

Energy is one of the most important elements required for poverty alleviation and socioeconomic development, and it has a particularly strong impact on households in rural areas. An extensive survey on household energy consumption patterns that interrelates socioeconomic and demographic factors was conducted in the disregarded villages of Lijiang City by using the stratified random sampling technique for 120 households. This study focuses on household energy consumption and the related carbon dioxide (CO₂) emissions in the study area. Firewood, biogas, and electricity were identified as the main energy sources of the rural households. This study demonstrates that 100% of the households use firewood, 52% use biogas, and 95% use electricity as fuel types. On average, each household consumed 1752 kg of firewood, 280 m³ of biogas, and 392 kWh of electricity annually. All households generated an annual average amount of CO₂ emissions of 3851 kg, of which 85.08% come from firewood, 7.66% from biogas, and 7.26% from electricity. Family size, income, and educational level were found to be the major factors that influence CO₂ emissions. The results of this study may be useful in explaining the energy consumption characteristics in the rural areas of Lijiang City and are expected to be useful in policy formulation for energy consumption and environmental protection.     

灰色关联分析在中国农村家庭碳排放影响因素分析中的应用

农村家庭碳排放影响因素分析的研究对于合理发展农村经济,有效制定农村减排政策具有重要的指导意义.根据IPCC参考方法、生活碳排放研究方法和投入产出基本方法,计算了1995—2010年中国大陆31省区农村人均家庭碳排放量.通过因子分析方法,剔除农村人均家庭碳排放量不显著相关的影响因素,利用灰色关联分析方法对影响农村人均家庭碳排放量的显著相关影响因素进行评价,得出不同驱动因子对碳排放的关联度.结果表明,(1)从时间上看,1995至2010年,农村家庭碳排放呈现出逐渐上升趋势,1995年农村的人均家庭排放量为C 0.170 t?人-1,增加到2010年的0.504 t?人-1,同比增长196.90%.(2)从空间看,东部地区的农村家庭碳排放远远高于中部、东北和西部地区的农村家庭碳排放.(3)从地区差异看,位于东部地区的上海市农村人均家庭碳排放远远高于位于西部地区的内蒙古,1995年上海市农村人均家庭碳排放为C 0.454 t?人-1,而内蒙古为0.145 t?人-1;2010年上海市农村人均家庭碳排放为C 1.351 t?人-1,而内蒙古为0.498 t?人-1.(4)利用灰色关联分析,经济水平指标中的农林牧渔总产值与农村人均家庭碳排放的关联度为最大,为0.9824,因此对农村家庭碳排放的影响最大,而人口指标中的农村人口比例与农村人均家庭碳排放的关联度最小,为0.5702,因此对农村家庭碳排放的影响最小.