基于生命周期评价的上海市水稻生产的碳足迹

碳足迹是指由企业、组织或个人引起的碳排放的集合。参照PAS2050规范并结合生命周期评价方法对上海市水稻生产进行了碳足迹评估。结果表明:(1)目前上海市水稻生产的碳排放为11.8114 t CO2e/hm2,折合每吨水稻生产周期的碳足迹为1.2321 t CO2e;(2)稻田温室气体排放是水稻生产最主要的碳排放源,每吨水稻生产的总排放量为0.9507 t CO2e,占水稻生产全部碳排放的77.1%,其中甲烷(CH4)又是最主要的温室气体,对稻田温室气体碳排放的贡献率高达96.6%;(3)化学肥料的施用是第二大碳排放源,每吨水稻生产的总排放量为0.2044 t CO2e,占水稻生产总碳排放的16.5%,其中N最高,排放量为0.1159 t CO2e。因此,上海低碳水稻生产的关键在降低稻田甲烷的排放,另外可通过提高氮肥利用效率,减少氮肥施用等方法减少种植过程中碳排放。     

北京市居民食物消费碳足迹

碳足迹作为一种评价碳排放影响的全新测度方法,已被用来衡量人类活动对大气环境和气候变化的影响。食物是人类的首要消费品,其消费的碳足迹反应维持一个区域人口的基本食物需求的碳排放以及对气候变化的影响。在碳足迹理论和模型的基础上,根据北京市食物的供应和消费现状情况,利用生命周期法(Life cycle analysis LCA),计算和分析了北京市居民食物消费的碳足迹。得到北京市居民食消费碳足迹为476.8×104t,约占北京市总碳足迹的6%,人均碳足迹为310.0kgCO2/人,占北京市家庭消费碳排放的23.3%,只占北京市能源消费人均碳排放量的5.96%,反映了居民食物消费对全球气候变化造成的影响有限。食物消费碳足迹最大的为粮食,其次为瓜果蔬菜豆类,总共占到65%以上,而在食物生命周期过程中,食物的再加工炊事过程碳排放最大,超过50%,合理减少食物加工炊事过程中碳排放将是减少食物消费碳排放的重要途径之一。其次为化肥农药施用,占到23.23%,减少食物生产过程中化肥农药使用,提高化肥农药的使用效率,或者进行生态农业尽量不使用化肥农药,北京市每年可减少135.1×104t CO2排放,人均87.84kgCO2/人,是有效的减排途径之一。     

甘南高原不同生计方式农户的碳足迹分析

二氧化碳增加导致的全球气候变暖已成为当前人类社会面临的最严峻挑战,减少碳排放迫在眉睫。以地处青藏高原东缘的甘南高原为研究区,基于农户调查数据,采用生命周期评价法估算了甘南高原不同生计方式农户的生活直接能源消费碳足迹和间接能源消费碳足迹,并运用最小二乘法分析了影响农户碳足迹的关键因素。结果发现:(1)甘南高原农户年人均碳足迹达2.67 t CO2,其中,生活直接能源消费碳足迹比例达76.53%,间接能源消费碳足迹比例仅占23.47%;(2)随着非农化水平的提高,甘南高原农户的碳足迹依次下降,其中,纯农户人均碳足迹达4.32 t,兼业户与非农户分别为2.37 t和1.07 t;(3)随着农户家庭规模的增大、收入水平的提高、距县城距离的增加和消费水平的提高,农户碳足迹不断增加;随着劳动力受教育程度的提高、恩格尔系数的增加和非农化程度的提高,农户碳足迹不断减少。     

城市餐饮业食物浪费碳足迹——以北京市为例

食物浪费及其造成的环境影响已成为全球广泛关注的热点。无论从生命周期还是碳足迹的视角来看,食物浪费意味着生产、运输、加工与储存这些被浪费掉的食物过程中所投入的各种资源的浪费以及不必要的温室气体排放。以北京市餐饮食物浪费问题为切入点,在通过问卷调查和称重方法对餐饮食物浪费状况进行调查的基础上,将整个食物生命周期各供应链环节相应的温室气体排放纳入考量,估算了北京市餐饮食物浪费的碳排放量。研究结果表明:北京市餐饮食物浪费总量为39.86×10~4t/a。其中,蔬菜类浪费量最高,约占浪费总量的43.16%,其次为肉类和主食类,分别占食物浪费总量的20.59%和16.66%。北京市餐饮食物浪费所产生的总碳足迹为192.51×10~4—208.52×10~4t CO_2eq。其中,农业生产阶段的碳排放量最大为99.34×10~4t CO2eq,占食物浪费总碳足迹的47.64%。其次是消费阶段的碳足迹77.96×10~4t CO_2eq,占食物浪费总碳足迹的37.39%,再次是餐厨垃圾处理阶段的碳足迹28.54×104tCO2eq,占食物浪费总碳足迹的13.68%。这些不同供应链环节的碳排放比例,为透视食物浪费所带来的环境影响提供了新的认知,也为遏制食物浪费提供了科学的理论依据。     

旅游风景区旅游交通系统碳足迹评估——以南岳衡山为例

随着全国各地旅游业的蓬勃发展,旅游风景区内碳排放总量不断攀升,严重影响了旅游业的可持续发展。选择南岳衡山旅游风景区为典型案例区,运用生命周期评价理论,构建了南岳风景区旅游交通系统碳足迹计算模型。结果表明:①从总量来看,不同类型交通方式的碳足迹情况相差甚远。公路旅游交通对旅游景区的环境威胁最大,碳足迹总量是索道旅游交通的2.6倍,人行道旅游交通的46.1倍;②从阶段构成来看,公路和索道旅游交通系统运营使用阶段碳足迹占整个生命周期的大部分,所占比率分别为79%和96%.而人行道旅游交通系统中建造施工和运营后期阶段能源消耗比较大;③从来源构成来看,在使用期内公路旅游交通的碳足迹比重最大,约占碳足迹总量的71%,其次是索道旅游交通占27%,人行道旅游交通仅占2%。研究结果有利于实现旅游风景区低碳旅游发展目标,为旅游风景区节能减排提供理论支撑。     

基于土地利用变化的四川省碳排放与碳足迹效应及时空格局

土地利用变化的碳排放与碳足迹研究对了解人类活动对生态环境的扰动程度及其机理、制定有效的碳排放政策具有重要意义。采用1990—2010年四川省能源消费数据和土地利用数据,通过构建碳排放模型、碳足迹及其压力指数模型,对研究区20年来土地利用的碳排放及碳足迹进行了定量分析。结果表明:(1)土地利用变化的碳排放和能源消费碳的足迹呈显著增加趋势。碳排放增加5407.839×10~4t,增长率达143%;能源消费的碳足迹增加1566.622×10~4hm~2,四川全省的生态赤字达1563.598×10~4hm~2。(2)建设用地和林地分别为四川省最大的碳源与碳汇。20年间建设用地的碳排放增加5407.072×10~4t,增长率达126.27%,占碳排放总量的88%以上;林地的碳汇减少10.351×10~4t,但仍占四川省碳汇的96%以上。(3)土地利用碳排放、碳足迹和生态赤字存在明显区域差异。成都平原区碳排放、碳足迹压力最大,生态赤字严重,西部高山高原区和盆周山区碳排放、碳足迹最小,未出现生态赤字;成都、德阳、资阳和内江等地的碳排放、碳足迹压力最大,生态赤字最严重,甘孜、阿坝等地的碳排放、碳足迹最小,未出现生态赤字。(4)土地利用结构与碳排放、碳足迹存在一定的相互关系,趋高的碳源、碳汇比导致土地利用的碳源效应远大于碳汇效应。因此,四川省减排的重点应该在保持或增加现有的林地的同时,主要以降低建设用地的碳排放、碳足迹为主。     

农田生态系统碳足迹时空变化——以河南省为例

农田生态系统是陆地生态系统的重要组成部分,起着碳源和碳汇的双重作用,对维持整个生态系统碳平衡具有重要意义.本文基于ArcGIS 10.1、SPSS 20.0、Sigmaplot 12.5等分析平台,以农田生态系统为研究对象,构建农田生态系统碳足迹模型,分析2005—2014年河南省农田生态系统碳排放、碳吸收和碳足迹及三者之间的关系.结果表明: 2005—2014年,研究区碳排放年平均增长率为2.7%,其中因化肥施用引起的碳排放量占总碳排放量的比例最高,占66.2%,且化肥的使用强度为890.38 kg·hm^-2,远高于发达国家公认的安全警戒线225 kg·hm^-2.河南省农田生态系统的碳总储量整体呈逐年上升趋势,其中,小麦的碳吸收比例最高,占总吸收量的60%,水稻的碳吸收增速最快,为7.9%.河南省农田生态系统存在碳生态盈余,且农田生态系统碳足迹总体呈现不断增加趋势,农田生态系统碳足迹占同期生产性土地面积(耕地)的平均比例为5.7%.研究区碳排放、碳吸收、碳足迹的空间变化较为一致,均呈现东南多、西北少的空间分布规律,且地区差异及变化幅度差异较大是三者的最主要外部特征.     

全球电力碳足迹及其当量因子测算

电力碳足迹旨在测度发电过程中所引起的生命周期CO2排放水平.本研究从地球碳循环的角度入手,在综合大量研究数据的基础上,针对不同电力来源的碳排放特征,结合地表覆被的碳吸收能力,分类测算了全球平均电力碳足迹当量(即单位电力消费量所产生的生命周期碳足迹),并实证分析了2000-2008年全球电力碳足迹的构成及变化.结果表明:煤炭类火电(以下简称煤电)、石油类火电、天然气类火电、水电和核电的全球平均碳足迹当量分别为131.3×10-6、95.8×10-6、56.6×10-6、38.8×10-6、1.9×10-6 hm2·(kW·h)-1,火电特别是煤电的环境影响显著大于水电和核电;2000-2008年,全球电力碳足迹由730.7×106 hm2增至1101.8×106 hm2,其中火电占比由60.0％增至68.1％,煤炭取代石油成为火电碳足迹的主要构成部分,而水电和核电占比则分别降至30.7％、1.3％;全球电力结构总体趋于劣化,平均碳排放系数由265.8×10-3kg·(kW· h)-1增至315.4×10-3 kg·(kW·h)-1,火电特别是煤电在很大程度上决定着电力碳排放的强度与规模.     

区域旅游交通碳排放测度模型及实证分析

交通是旅游业发展的基础,旅游交通的碳排放是旅游业碳排放的主体部分。合理配置区域旅游交通是旅游业可持续发展的重要保障。从区域的角度出发,构建区域旅游交通碳排放测算模型,并以南京市和黄山市为例进行分析。研究发现:(1)区域经济和旅游发展水平是影响旅游交通碳排放的重要因素,且经济发展水平和旅游发展水平对旅游交通碳排放"贡献"的大小和方向不同;(2)区域旅游交通碳排放主要在区外,区内比例较小。2008至2012年,南京市旅游交通碳排放中区外部分所占比例平均达到89.13%,黄山市平均达到90.21%,两城市区外与区内部分之比均约为9∶1;(3)区域旅游交通碳排放结构中,民航所占比重最大,其次是公路和铁路,区域交通结构的优化有利于旅游交通碳排放的减少;(4)区域各类交通方式中,外部交通的碳排放中旅游业的贡献较大,而城市内部交通的碳排放中旅游业的贡献较小。     

我国农村居民生活能源碳排放的时空特征分析

随着生活质量的提高,我国农村居民生活能源消费呈现大幅增长的趋势,成为碳排放增长的新源泉。估算了我国30个省区2001—2013年的农村居民生活能源碳排放,采用碳基尼系数、Arc GIS技术分析了中国省级尺度农村居民生活能源碳排放的时空特征,并利用STIRPAT模型辨明了农村居民生活能源碳排放的主要影响因素。结果表明:(1)2001—2013年农村居民直接生活能源碳排放量和间接生活能源碳排放量分别增长了7.65%、9.16%。(2)东部、中部、西部地区的碳基尼系数呈下降趋势,说明各区域农村居民人均生活能源碳排放量的区域差异总体均呈缩小趋势。(3)2001—2013年间,处于我国农村居民人均直接生活能源碳排放高水平地区的空间格局分布相对较为稳定,而对于人均间接生活能源碳排放来说,处于低水平地区的空间格局分布较为稳定。(4)农村人口规模、农民人均纯收入、农村居民生活消费支出、青壮年人口比重对农村居民生活能源碳排放量具有促进作用,而农村居民能源消费结构对其具有减缓作用,且北方农村居民生活能源碳排放量明显高于南方。(5)从环境Kuznets曲线假说出发,经济发展是促使我国农村居民生活能源碳排放Kuznets曲线存在拐点的重要因素。     

Data for the Carbon Footprinting of Rendering Operations

This article presents a tool and data for calculation of the carbon footprint of rendering operations in North America, quantifying Scope 1 (direct) and Scope 2 (indirect) greenhouse gas emissions. Scope 3 (life cycle) emissions are not included. According to the sample data, in one year an average‐size rendering plant in North America processes 100,000 tonnes (t) of meat by‐products, fallen animals, and restaurant grease and produces 40,000 t of marketable fats and proteins. A plant of this size emits directly about 20,000 t of carbon dioxide (CO₂), mostly by burning fuels to operate cookers that destroy pathogens, drive off moisture, and separate the fat and protein. Another 4,000 t of CO₂ is emitted by utility companies to provide electricity for the rendering process. These direct and indirect emissions are equivalent to about 30% of the CO₂ that would be released if all of the carbon in the rendered raw material were decomposed into CO₂.     

能源活动CO2排放不同核算方法比较和减排策略选择

能源活动CO₂排放是温室气体排放的最重要部分,这部分CO₂排放量的核算是温室气体清单编制和减排方案制定的关键和基础。采用直接法、电热终端法和隐含终端法核算了2009年中国能源消费的CO₂排放量,对不同核算法的CO₂排放部门分布、部门排放强度进行了比较,明确不同核算方法的差异和适用范围。采用电热终端法的核算结果定量分析了各产业部门和工业行业的经济增长和排放强度变化对中国能源活动CO₂排放增长的影响。结果表明,中国2009年隐含终端CO₂排放量为65.6亿t,略高于直接和电热终端CO₂排放量62.2亿t。3种核算方法的CO₂排放部门分布和排放强度有明显的差异:电、热力生产与供应业的直接排放占比为45.2%,而电热终端CO₂排放仅占4.5%;制造业的直接法、电热终端法和隐含终端法核算的CO₂排放占比分别为35.3% 、61.1%和65.5%,是终端能源消费CO₂排放最主要的部门;制造业、电热力生产与供应业和交通运输业的电热终端CO₂排放强度分别为2.166、1.72和1.622 t CO₂/万元GDP,是排放强度较高的部门。在产业部门中,制造业的色金属冶炼及压延加工业、非金属矿物制品业等5个行业以9.8%的经济增长贡献,排放了52.4%的CO₂,是产业结构调整、技术和工程减排的重点;服务业以7.2%的CO₂排放,贡献了38.4%的经济增长,应作为中国低碳经济优先发展的产业。     

Environmental footprinting of hospitals: Organizational life cycle assessment of a Canadian hospital

Healthcare is a critical and complex service sector with direct and indirect greenhouse gas (GHG) emissions amounting to 5%–10% of the national total in developed economies like Canada and the United States. Along with a growing, albeit sporadic, set of life cycle assessment (LCA) (and “carbon footprinting”) studies of specific medical products and procedures, there is growing interest in “environmental footprinting” of hospitals. In this article, we advance this rapidly evolving area through a comprehensive organizational LCA of a 40-bed hospital in British Columbia, Canada, in its 2019 fiscal year. Our results indicate that the total environmental footprint of the hospital includes, among other things, global warming potential of 3500–5000 t CO₂ eq. (with 95% confidence). “Hotspots” in this footprint are attributable to energy and water use (and wastewater released), releases of anesthetic gases (which are potent GHGs), and the upstream production of the thousands of materials, chemicals, pharmaceuticals, and other products used in the hospital. The generalizability and comparability of these results are limited by inconsistencies across the few environmental footprinting studies of hospitals conducted to date. Nonetheless, our novel methodological approach, in which we compiled new LCA data for 200 goods and services used in healthcare—strategically selected to statistically represent the 2927 unique products in the hospital's “supply-chains”—has broad applicability in healthcare and beyond.     

Carbon footprint and embodied energy assessment of a civil works program in a residential estate of Western Australia

Purpose

With building construction and demolition waste accounting for 50 % of land fill space, the diversion of reusable materials is essential for Perth”s environment. The reuse and recovery of embodied energy-intensive construction materials during civil engineering works programs can offer significant energy savings and assist in the mitigation of the carbon footprint.

Methods

A streamlined life cycle assessment, with limited focus, was carried out to determine the carbon footprint and embodied energy associated with a 100-m section of road base. A life cycle inventory of inputs (energy and materials) for all processes that occurred during the development of a 100-m road section was developed. Information regarding the energy and materials used for road construction work was obtained from the Perth-based firm, Cossill and Webley, Consulting Engineers. These inputs were inserted into Simapro LCA software to calculate the associated greenhouse gas emissions and embodied energy required for the construction and maintenance of a 100-m road section using. Two approaches were employed; a traditional approach that predominantly employed virgin materials, and a recycling approach.

Results and discussion

The GHG emissions and embodied energy associated with the construction of a 100-m road section using virgin materials are 180 tonnes of CO₂-e and 10.7 terajoules (TJ), respectively. The substitution of crushed rock with recycled brick road base does not appear to reduce the carbon footprint in the pre-construction stage (i.e. from mining to material construction, plus transportation of materials to the construction site). However, this replacement could potentially offer environmental benefits by reducing quarrying activities, which would not only conserve native bushland but also reduce the loss of biodiversity along with reducing the space and cost requirements associated with landfill. In terms of carbon footprint, it appears that GHG emissions are reduced significantly when using recycled asphalt, as opposed to other materials. About 22 to 30 % of greenhouse gas (GHG) emissions can be avoided by replacing 50 to 100 % of virgin asphalt with Reclaimed Asphalt Pavement (RAP) during the maintenance period.

Conclusions

The use of recycled building and road construction materials such as asphalt, concrete, and limestone can potentially reduce the embodied energy and greenhouse gas emissions associated with road construction. The recycling approach that uses 100 % reused crushed rock base and recycled concrete rubble, and 15 % RAP during the maintenance period could reduce the total carbon footprint by approximately 6 %. This large carbon saving in pavement construction is made possible by increasing the percentage of RAP in the wearing course.     

Does Size Matter? Scaling of CO2 Emissions and U.S. Urban Areas

Urban areas consume more than 66% of the world’s energy and generate more than 70% of global greenhouse gas emissions. With the world’s population expected to reach 10 billion by 2100, nearly 90% of whom will live in urban areas, a critical question for planetary sustainability is how the size of cities affects energy use and carbon dioxide (CO₂) emissions. Are larger cities more energy and emissions efficient than smaller ones? Do larger cities exhibit gains from economies of scale with regard to emissions? Here we examine the relationship between city size and CO₂ emissions for U.S. metropolitan areas using a production accounting allocation of emissions. We find that for the time period of 1999–2008, CO₂ emissions scale proportionally with urban population size. Contrary to theoretical expectations, larger cities are not more emissions efficient than smaller ones.     

Carbon footprint of science: More than flying

Previous efforts to evaluate the climate change impact of researchers have focused mainly on transport related impact of conference attendance, and infrastructure. Because these represent only a part of the activities involved in the science making process this short note presents the carbon footprint of a complete science making process of one specific case. Apart from presenting the total footprint, we evaluate the relative contribution of the different scientific activities, and quantify mitigating possibilities. The case PhD project had a carbon footprint of 21.5 t CO₂-eq (2.69 t CO₂-eq per peer-reviewed paper, 0.3 t CO₂-eq per citation and 5.4 t CO₂-eq per h-index unit at graduation) of which general mobility represents 75%. Conference attendance was responsible for 35% of the carbon footprint, whereas infrastructure related emissions showed to contribute 20% of the total impact. Videoconferencing could have reduced the climate change impact on this case PhD with up to 44%. Other emission reduction initiatives, such as using green electricity, reduction of energy consumption, and promoting commuting by bicycle, could have triggered a reduction of 14% in this case study. This note fits in the movement of academics and universities willing to be green. The study confirms that researchers’ mobility is the biggest contributor to his or her carbon footprint, but is not limited to conference attendance, showing the importance of considering all activities in the science making process.     

我国典型城市化石能源消费CO2排放及其影响因素比较研究

城市是化石能源消费和CO_2排放的主要区域。分析典型城市化石能源消费CO_2排放特征,明确不同城市CO_2排放动态及主要影响因素的差异,是开展城市减排行动的重要科学依据。采用IPCC推荐方法及中国的排放参数核算11个典型城市2006—2015年间化石能源消费产生的CO_2排放量。根据各城市经济发展和CO_2排放特征将之分为四类:经济高度发达城市(北京、上海、广州)、高碳排放城市(重庆、乌鲁木齐、唐山)、低排放低增长城市(哈尔滨、呼和浩特和大庆)和低排放高增长城市(贵阳、合肥),并运用对数平均迪氏指数法(Logarithmic Mean Divisia Index,即LMDI分解法)对比分析了四类城市CO_2排放量的影响因素。结果表明:(1)研究期内大部分城市CO_2排放总量有所增加,仅北京和广州呈下降趋势,工业部门CO_2排放在城市排放总量及其变化中占据主导地位;四类城市的人均CO_2排放量表现出与排放总量相似的变化趋势;CO_2排放强度整体上表现为经济高度发达城市(均值为0.88 t CO_2/万元)低排放低增长城市(均值为2.82 t CO_2/万元)低排放高增长城市(均值为3.05 t CO_2/万元)高碳排放城市(均值为6.62 t CO_2/万元)。(2)在城市CO_2排放的影响因素中,经济发展和人口规模均是4类城市CO_2排放增长的促进因素,但经济发展效应的累积贡献值大于人口规模效应;能源强度降低是4类城市CO_2排放最主要的抑制因素,且经济高度发达和高碳排放城市的抑制作用强于其他两类城市;对第三产业GDP年平均增速高于第二产业的6个城市来说,产业结构是CO_2排放的抑制因素;能源结构的变化仅对煤炭消费比重较低且降幅较大的北京和广州的CO_2排放是抑制作用,累积贡献值分别为-21.73Mt和-0.03Mt,而对其他城市,特别是高碳排放城市的CO_2排放具有明显的促进作用。     

庐山风景区碳源、碳汇的测度及均衡

旅游目的地系统碳源、碳汇的计算与分析,不仅是旅游业节能减排政策制定的重要依据,也是旅游与环境相互关系研究的一个新的科学命题.以庐山风景区为例,计算并分析了2010年的碳源及碳汇.结果表明:(1)2010年庐山风景区包括本地居民和旅游者的总碳排放为108 697 t.其中,本地居民占碳排放总量的19.52％,旅游者占碳排放总量的80.48％.在旅游者碳排放中,旅游交通碳排放占50.24％,旅游住宿碳排放占38.04％,旅游食物消费碳排放占10.65％,旅游活动碳排放仅占1.07％;(2)2010年庐山风景区内陆地生态系统碳吸收为9447 t;(3)从碳源、碳汇均衡角度看,庐山陆地生态系统的固碳量吸收了区内碳排放的23.47％.但由于旅游者的区际流动和旅游业的产业关联性强,陆地生态系统的碳吸收仅占区内和区外碳排放总量的8.69％,旅游业使庐山成为一个显著的碳源.