典型社区家庭消费碳排放特征与影响因素——以北京市为例

家庭消费碳排放是中国碳排放总量的重要组成部分,已成为碳排放增长的主要驱动力,从消费角度研究家庭碳排量特征及影响因素对家庭碳减排和低碳社区建设有重要意义。使用碳排放系数法和消费者生活方式法计算北京市5种典型社区家庭消费月均碳排量,通过最优尺度回归和多重比较分析对不同社区家庭碳排放影响因素进行探究。研究发现：北京市5种社区户均碳排放总量及构成差异显著,影响因素不一致。其中：（1）平房类社区家庭直接碳排量732.26 kgCO₂/月高于其他社区,燃煤取暖是平房社区家庭直接碳排放高的主要因素,单位社区、政策性住房社区和商品房社区家庭直接碳排量较低,约50.00 kgCO₂/月。家庭类型显著影响每个社区家庭直接碳排量,家庭积极参与节能环保活动有利于减少家庭直接碳排放;（2）商品房社区家庭间接碳排量最高,达3879.06 kgCO₂/月,平房类社区家庭最低,间接碳排量仅为商品房社区的1/3,间接碳排放是家庭生活消费碳排放的主体。食品和居住消费产生的间接碳排量较高,老龄化社区家庭医疗保健消费碳排量更高;（3）家庭类型和月总收入对所有社区家庭间接碳排量影响显著,但社区环保工作满意度、社区环境满意度、家庭节能环保活动参与度、耐用品使用年限等因素影响程度存在差异,胡同社区和平房类社区中受教育水平高的家庭产生的间接碳排量更高,需积极灌输环保理念。进一步分析了主要影响因素在不同水平下对应的家庭碳排量差异程度与变化规律,有助于社区管理者识别高碳排家庭,为社区低碳管理提供新思路。     

基于碳足迹的传统农业系统环境影响评价——以青田稻鱼共生系统为例

现代农业在带来粮食高产的同时也产生许多生态环境问题,这促使人们再次把目光转向传统农业系统。一些传统农业系统不仅具有突出的经济、社会和文化价值,还具有多种重要的生态功能,如温室气体减排。然而,已有研究缺乏对传统农业系统整个生命周期的固碳减排能力的测算及其环境影响的评价。为此,基于农户调研数据,运用生命周期评价法对青田稻鱼共生系统的碳足迹进行了测算,并与当地水稻单作系统进行比较。研究发现:(1)青田稻鱼共生系统和水稻单作系统碳足迹分别为6266.7 kgCO₂-eq/hm²和7520.0 kgCO₂-eq/hm²,单位产值碳足迹分别为0.12 kgCO₂-eq/元和0.21 kgCO₂-eq/元。与水稻单作系统相比,稻鱼共生系统排放的温室气体更少,环境影响更小,生态和经济效益更高。(2)农业生产过程中积累的CH₄是碳足迹的最主要来源,农业生产资料投入中的化肥是碳足迹的的第二大来源。农业生产资料投入中的饲料则是稻鱼共生系统碳足迹的另一重要来...     

基于能源代谢分析的南昌市能源消费碳排放综合生态效率研究

有关能源消费的代谢机理及生态效率研究是当前生态经济研究领域中的重点和难点,也是政府决策部门、相关行业及人群关注的热点。基于能源代谢分析理念,构建了基于相对变量的城市能源消费碳排放综合生态效率度量模型,对2000—2013年南昌市能源消费结构、碳排放量及其生态效率进行了测算与分析。结果表明:(1)南昌市在2000—2013年,能源消费量和碳排放量整体上呈"N"型曲线上升的一致性变化特征,主要经历了快速增长、短暂下降、恢复平稳增长3个阶段,且煤炭是南昌市能源消费和碳排放的主要来源,短时期内难以改变;(2)南昌市的能源消费效率和碳排放效率整体上在不断优化;(3)南昌市能源消费碳排放综合生态效率经历了较大的波动变化,整体上的生态效率分值并不高;仍需要加大节能减排力度,全面优化南昌市能源消费结构。     

中国农村居民生活氮素流动特征

人类生活消费是陆地生态系统氮素流动的主要驱动力。定量核算和评估农村居民生活消费氮产生(N_RUR)及其活性氮(Nr)排放特征,对农村氮的可持续管理和生态环境改善具有重要的指导意义。以中国为例(2000—2020年),建立了N_RUR的产生及其活性氮排放核算框架。结果表明：20年来N_RUR上升了36.7%,年均5.62 Tg/a,食物消费氮是最大的贡献源(43.2%),工业日用品和家庭生活燃料消费氮分别占31.5%和25.3%;Nr排放量占N_RUR的25.4%(年均1.43 Tg/a),其以年均1.3%速率下降;NH₃挥发是最大的Nr排放源(50.1%),其次为排入地表水的Nr(31.0%)、NO_x(15.8%)和N₂O(2.0%),排入地下水的Nr仅占1.1%。加大人类粪尿排泄物的处置能力,减少秸秆燃料的使用比例、优化农村居民生活能源消费结构对农村居民生活消费Nr减排至关重要。     

基于三维生态足迹模型的长江中游城市群平衡性分析与生态补偿研究

长江中游城市群是长江经济带的重要组成部分,明晰生态足迹平衡性对城市群区域间生态补偿以及长江中游城市群生态可持续发展具有重要意义。研究采用三维生态足迹模型和基尼系数,核算长江中游城市群各市生态足迹及生态承载力,并对其生态足迹空间平衡性进行分析;同时依据三维生态足迹相关理论,计算各市生态补偿金额。结果表明:(1)2000—2015年长江中游城市群整体生态足迹持续上升,由65.52 hm²/人增加至139.38 hm²/人,年增长率为7.52%,武汉城市圈和襄荆宜城市群对生态足迹增长的贡献最大;(2)生态承载力呈下降趋势,由11.25 hm²/人减小至10.73 hm²/人,从土地利用类型来看,耕地和林地是提供生态承载能力的最主要因素;(3)生态足迹的综合基尼系数处于0.425-0.488之间,整体上处于"集聚程度较大"的区间范围,空间分布显示出不平衡性;(4)2000—2015年长江中游城市群生态补偿支付区和补偿金额持续增加,各子城市群生态补偿差异大小关系为:环鄱阳湖城市群>环长株潭城市群>...     

城市住宅区碳源汇的空间分异规律、影响机制及管理对策——以关中地区为例

城市住宅区作为城市生态系统重要的组成单元,其碳源汇对城市生态系统碳循环和碳平衡产生重要影响.本文采取案例分析、文献查阅、问卷调查等多种方法,获取关中地区城市住宅区CO₂排放(碳源)与吸收(碳汇)数据,并分析其来源及空间分布情况.结果表明: 关中地区住宅区建材生产和改造更新过程CO₂排放量最大;且建材类的CO₂排放量远大于日常生活资料,仅有40%～52%碳排放发生在住宅区,其余发生在外围,呈现出碳源距离的空间波动性、成分的空间差异性以及圈层与分区分布.仅有9%～17%的碳排放可在住宅区内被吸收,外部空间被动承担大量碳汇功能,并显现为分层递变和空间分异.最后提出了碳源、碳汇空间管理技术和干预对策.
     

基于绿色GDP和生态足迹的江西省生态效率动态变化研究

生态效率是循环经济与可持续发展的有效测度,其测度方法一直是相关研究领域的热点和难点。鉴于绿色GDP能反映出剔除资源损耗和生态环境影响的国民经济净收益,生态足迹则更能全面地衡量经济发展中消耗的各种物质、能源以及带来的环境影响,基于WBCSD提出的生态效率定义及核算方法,创新性地从绿色GDP和生态足迹的视角改进生态效率度量模型,并以江西省为研究对象,对其2000—2015年间的生态效率变化轨迹及成因进行衡量与分析。结果表明:(1)2000—2015年江西省单位面积生态足迹的绿色GDP即生态效率总体呈上升趋势,15年来提升了4.57倍,与此同时,绿色GDP、生态足迹也呈上升趋势,但绿色GDP的增速明显高于生态足迹的增速;(2)江西省绿色GDP占总的GDP的比例处于不规则波动状态,平均为84.61%,其中自然资源损耗价值、环境退化损失价值和资源环境改善效益也呈不规则波动,三者皆呈现出先上升后下降的趋势,其中自然资源损耗对绿色GDP的影响较为显著;(3)江西省生态足迹不断增加,总生态足迹15年来增加了83.6%,年平均增长率为4.26%,从生态足迹构成来看,各土地利用类型生态足迹均呈波动上升趋势,其中牧草地足迹增长最为显著;(4)江西省生态足迹的主要类型是牧草地足迹、耕地足迹和化石能源用地足迹,其中牧草地足迹比重最大,并且保持波动上升趋势,其次是耕地和化石能源用地足迹,但两者比重均呈小幅下降趋势。从生态效率度量模型的创新性、适应性和生态效率的提高途径等方面进行了详细的探讨。     

生态效率视角下旅游业生态福利及驱动因素——以常州市为例

经济效益最大化与环境影响最小化是绿色旅游与可持续发展的内在诉求。本文立足于生态效率模型,创新性地提出旅游业生态福利指数,据此分析1995—2017年常州市旅游业生态福利变化趋势及驱动效应,旨在为评价旅游产业绿色可持续发展能力提供新视角。研究发现:(1)1995年来常州市生态足迹呈现先增长后下降趋势,但旅游业各部门生态足迹均不断增长,游客人均资源消耗约为本地居民人均资源消耗的2.81—9.37倍,面临艰巨的节能减排压力。(2)1995年来常州市本底生态效率与旅游生态效率逐年提升,分别增加了37033元/hm²和44226元/hm²;同等资源消耗下,旅游业平均每单位产出高14409元/hm²,但游客年均消耗的自然资源却为本地居民的5.78倍。(3)1995—2007年间常州市旅游生态福利升降波动频繁,2007年来呈以直线式地骤降,受规模效益影响,旅游业的绿色生态福利和高效性不断弱化,为全市的资源节约量下降了10.7倍。(4)迪氏对数指标分解法(Logarithmic Mean Disivia Index, LMDI)揭示规模...     

基于终端消费的云南省碳排放总量测算及驱动因素实证研究

在终端能源消费CO₂ 排放总量测算中, 二次能源(电力、热力)通常不被列入计算, 这种测算结果无法准确测算出CO₂ 排放总量, 更会影响减排相应措施的制定。根据生产和生活部门终端一次能源和二次能源消费量, 构建了17种(含电力、热力)能源的碳排放总量测算模型, 全面测算云南省2000-2014 年CO₂ 排放量。选取LMDI 1 分解法, 将CO₂ 排放量分解为生产部门5 类因素、生活部门6 类因素。结果表明: ①2000-2014 年, 云南省终端能源消费CO₂ 排放总量从5744.15 万吨增长到18952.46 万吨; 其中, 生产部门CO₂ 排放量约占总排放量91.2%, 为碳排放主要来源。②能源强度是生产与生活部门最主要的驱动因素, 其累计贡献度为–92.64%和–94.78%, 其次为生产部门的产业结构效应以及生产与生活部门的能源结构效应, 累计贡献度分别为–33.55%、–17.65%和–17.18%。③GDP 和人均收入分别以累计贡献度245.28%和194.54%成为生产与生活部门最大的碳排放增长驱动因素。     

气溶胶光学厚度与PM2.5浓度的时空分布特征及其关系——以京津冀大气污染传输通道城市群为例

城市人口和产业的聚集伴随化石能源消费的迅速增长,导致空气污染物排放量不断增加,对区域气候产生了不可逆的负面影响。以多源遥感数据为基础,对京津冀大气污染传输通道城市群(“2+26”城市群)2015—2019年气溶胶光学厚度(AOD)、PM_2.5浓度的时空分布格局进行分析,从月份、季节、年份三个时间维度定量分析其时空变化规律,并通过计算相关性系数来分析气溶胶光学厚度对PM_2.5浓度的影响。主要得出研究结论如下：(1)PM_2.5浓度整体呈现冬季>春季>秋季>夏季的趋势,并且表现出高度空间自相关性,2015—2019年间,PM_2.5浓度显著下降至40μg/m³以下;(2)AOD平均范围值在0—1之间,总体上呈现春夏季高,秋冬季低的分布特点,到2019年,春夏秋三季AOD浓度呈现明显降低,夏季下降趋势最为显著,AOD同样表现出高度空间自相关性;(3)AOD与PM_2.5浓度存在显著的正相关关系。从季节变化上看,相关性呈现出：秋季>夏季>冬...     

The Carbon Footprint of Bioinformatics

Bioinformatic research relies on large-scale computational infrastructures which have a nonzero carbon footprint but so far, no study has quantified the environmental costs of bioinformatic tools and commonly run analyses. In this work, we estimate the carbon footprint of bioinformatics (in kilograms of CO₂ equivalent units, kgCO₂e) using the freely available Green Algorithms calculator (www.green-algorithms.org, last accessed 2022). We assessed 1) bioinformatic approaches in genome-wide association studies (GWAS), RNA sequencing, genome assembly, metagenomics, phylogenetics, and molecular simulations, as well as 2) computation strategies, such as parallelization, CPU (central processing unit) versus GPU (graphics processing unit), cloud versus local computing infrastructure, and geography. In particular, we found that biobank-scale GWAS emitted substantial kgCO₂e and simple software upgrades could make it greener, for example, upgrading from BOLT-LMM v1 to v2.3 reduced carbon footprint by 73%. Moreover, switching from the average data center to a more efficient one can reduce carbon footprint by approximately 34%. Memory over-allocation can also be a substantial contributor to an algorithm’s greenhouse gas emissions. The use of faster processors or greater parallelization reduces running time but can lead to greater carbon footprint. Finally, we provide guidance on how researchers can reduce power consumption and minimize kgCO₂e. Overall, this work elucidates the carbon footprint of common analyses in bioinformatics and provides solutions which empower a move toward greener research.     

Carbon footprints of rice production in five typical rice districts in China

Five provinces located in the five main rice-growing regions in China were selected as study areas, which were Jiangsu, Heilongjiang, Sichuan, Guangdong and Hunan province respectively in the middle and lower reaches of the Yangtze River, northern, southwest, southern and central rice districts. Carbon footprints of rice production in these five provinces were calculated through the life cycle assessment method using governmental statistical data, industrial standards and relevant technical data separately. Material and energy consumptions were estimated, key stages of energy consumptions and carbon emissions were identified as well. Moreover, improving measurements had been suggested correspondingly. The results indicated that: the energy consumptions of rice production in these five provinces ranked as following (high to low): Guangdong, Heilongjiang, Hunan, Sichuan and Jiangsu. The carbon footprints of rice production were 2504.20 kg carbon dioxide equation per ton rice (kgCO₂-eq./t) (Guangdong province), 2326.47 kgCO₂-eq./t (Hunan province), 1889.97 kgCO₂-eq./t (Heilongjiang province), 1538.90 kgCO₂-eq./t (Sichuan province) and 1344.92 kgCO₂-eq./t (Jiangsu province) respectively. Reducing the quantities of urea and using the intermittent irrigation method could decrease energy consumption as well as carbon footprint.     

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。     

Greenhouse gas emissions from a Cu-contaminated soil remediated by in situ stabilization and phytomanaged by a mixed stand of poplar,willows, and false indigo-bush

Phytomanagement of trace element-contaminated soils can reduce soil toxicity and restore soil ecological functions, including the soil gas exchange with the atmosphere. We studied the emission rate of the greenhouse gases (GHGs) CO₂, CH₄, and N₂O; the potential CH₄ oxidation; denitrification enzyme activity (DEA), and glucose mineralization of a Cu-contaminated soil amended with dolomitic limestone and compost, alone or in combination, after a 2-year phytomanagement with a mixed stand of Populus nigra, Salix viminalis, S. caprea, and Amorpha fruticosa. Soil microbial biomass and microbial community composition after analysis of the phospholipid fatty acids (PLFA) profile were determined. Phytomanagement significantly reduced Cu availability and soil toxicity, increased soil microbial biomass and glucose mineralization capacity, changed the composition of soil microbial communities, and increased the CO₂ and N₂O emission rates and DEA. Despite such increases, microbial communities were evolving toward less GHG emission per unit of microbial biomass than in untreated soils. Overall, the aided phytostabilization option would allow methanotrophic populations to establish in the remediated soils due to decreased soil toxicity and increased nutrient availability.     

Scaling of photosynthetic production of aquatic macrophytes – a review

Most studies on photosynthetic production of aquatic macrophytes have been made on detached leaves and algal thalli. This may have given the false impression that production is often saturated by light and that inorganic carbon and nutrients are more important limiting factors. However, studies on the more relevant ecological scale of macrophyte communities lead to a completely different perception because community production is light limited due to intense self‐shading. Relatively high irradiances are needed for photosynthesis to balance respiratory costs and not even maximum irradiances at noon during summer saturate photosynthetic production. The fundamental importance of light is confirmed by the close coupling to community light absorptance of both maximum production in high‐light environments and efficiency of light use in low‐light environments. The upper boundaries of light‐limited and light‐saturated production are distinctly and linearly related to community absorptance. Moreover, higher diversity in the community has a positive and stabilizing influence on light absorptance and production because different species supplement each other temporally and spatially. Close predictions of actual production rates in macroalgal communities throughout the year are possible solely from determinations of incident and absorbed irradiance. Along with the increasing regulating role of light from leaves or thalli to entire communities the importance of temperature, inorganic carbon and other resources decreases. Thus, ten‐fold rise of CO₂ relative to atmospheric saturation does not enhance maximum production in dense communities of efficient HCO₃^?‐users and only doubles production of pure CO₂‐users. A challenge therefore exists establishing the importance of light for photosynthetic production of macrophytes from individuals to communities and re‐evaluating the postulated main importance of inorganic carbon and temperature in the scenarios of globally rising CO₂ and temperature.     

Impacts of long‐term elevated atmospheric CO2 concentrations on communities of arbuscular mycorrhizal fungi

The ecological impacts of long‐term elevated atmospheric CO₂ (eCO₂) levels on soil microbiota remain largely unknown. This is particularly true for the arbuscular mycorrhizal (AM) fungi, which form mutualistic associations with over two‐thirds of terrestrial plant species and are entirely dependent on their plant hosts for carbon. Here, we use high‐resolution amplicon sequencing (Illumina, HiSeq) to quantify the response of AM fungal communities to the longest running (>15 years) free‐air carbon dioxide enrichment (FACE) experiment in the Northern Hemisphere (GiFACE); providing the first evaluation of these responses from old‐growth (>100 years) semi‐natural grasslands subjected to a 20% increase in atmospheric CO₂. eCO₂ significantly increased AM fungal richness but had a less‐pronounced impact on the composition of their communities. However, while broader changes in community composition were not observed, more subtle responses of specific AM fungal taxa were with populations both increasing and decreasing in abundance in response to eCO₂. Most population‐level responses to eCO₂ were not consistent through time, with a significant interaction between sampling time and eCO₂ treatment being observed. This suggests that the temporal dynamics of AM fungal populations may be disturbed by anthropogenic stressors. As AM fungi are functionally differentiated, with different taxa providing different benefits to host plants, changes in population densities in response to eCO₂ may significantly impact terrestrial plant communities and their productivity. Thus, predictions regarding future terrestrial ecosystems must consider changes both aboveground and belowground, but avoid relying on broad‐scale community‐level responses of soil microbes observed on single occasions.     

丽江市家庭能耗碳排放特征及影响因素

现代社会中人类活动对碳排放的影响日益显著.家庭作为人类社会的基本单元,其消费活动产生的碳排放是全社会碳排放的重要组成部分.通过对丽江市农村和市区家庭生活用能的调查数据进行分析,发现农村家庭生活用能以木柴为主,沼气和电为辅;市区家庭的生活用能以电为主,其次是液化气和蜂窝煤.从碳排放构成来看,农村地区木柴消费为家庭能源碳排放的主要来源,占总碳排的83.6％;市区电力消费为家庭能源碳排放的主要来源,占总碳排的88.4％.农村地区家庭的碳排放远高于市区家庭,主要原因是木柴的碳排放因子(1.87 kg CO2/kg)远高于电能的边际排放因子(0.7134 kg CO2·kW-1·h-1).从各影响因素与家庭主要能源消费碳排放的回归结果来看,在农村地区,家庭规模、家庭收入、教育水平均对家庭木柴消费碳排放有显著的影响,但影响方向和程度有一定的差别;在市区,年龄结构、教育水平、家庭规模、住房面积均会不同程度增加家庭电能消费碳排放.建议政府在完善“家电下乡”政策、增加农村家庭收入、加强农村居民教育等方面加大投入力度,以减少丽江市整体的家庭能耗碳排放.     

Carbon budget of oligotrophic mire sites in the Southern Taiga of Western Siberia

The results of a long-term (1999–2007) investigation of vegetation productivity and carbon dioxide (CO₂) emission from the surface of an oligotrophic mire in southern taiga in Western Siberia are presented. The studied ecosystems include pine—shrub—sphagnum (PSS) community, a similar community with oppressed (low) tree stand (LPSS), and sedge—sphagnum fen (SSF). Net primary production for PSS, LPSS and SSF are equal to 552, 575, and 561 g m^?2 yr^?1. The mean respiration during the snow-free season determined by chamber method is 165.8, 105.6, 112.4 mgCO₂ m^?2 h^?1 for PSS, LPSS and SSF, respectively. Field measurements of NPP and CO₂ emission in combination with reference data on methane emission, winter CO₂ and CH₄ emissions and carbon export by river run–off were used to develop an overall carbon budget of the mire ecosystems. At present conditions the studied mire ecosystems are net sinks for atmospheric carbon and accumulate peat. Rates of the actual modern carbon accumulation are equal to 21, 112 and 102 g C m^?2 yr^?1 for PSS, LPSS and SSF communities.