CO_2 Emission Induced by Urban Household Consumption in China

Household consumption is one of the important factors that induce COL emission. Based on input-output model, this article calculated the intensity of CO2 emission of different income groups and seven provinces in China, and then estimated total CO2 emission induced by urban household consumption from 1995 to 2004 in China based on statistic data of household living expenditure. The results show that CO2 emission per capita induced by household consumption had increased from 1583 to 2498 kg CO2 during 1995-2004. The ratio of consumption-induced CO2 emission to total CO2 emission had risen from 19% to 30% in the past decade. Indirect CO2 emission accounted for an important part of the consumption-induced emission, the ratio of indirect emission to consumption-induced emission had risen from 69% to 79% during the same period. A significant difference in consumption-induced CO2 emission across different income groups and different regions has been observed. COs emission per capita of higher income groups and developed regions increased faster than that of lower income groups and developing regions. Changing lifestyle has driven significant increase in CO2 emission. Especially, increases in private transport expenditure （for example, vehicle expenditure） and house building expenditure are key driving factors of growth in consumption-induced COL emission. There are big differences in the amount of CO2 emission induced by change in lifestyle across different income groups and provinces. It can be expected that lower income households and developing regions will increase consumption to improve their livings with income growth in the future, which may induce much more CO2 emission. A reasonable level of CO2 emission is necessary to satisfy human needs and to improve living standard, but a noticeable fact is that CO2 emission per capita induced by household consumption in developed areas of China had reached a quite high level. Adjustment in lifestyle towards a low-carbon society is in urgent need.     

经济快速发展地区土地利用结构的时空演变——以苏锡常地区为例

利用1996～2007年苏锡常地区土地利用变更数据,从土地利用变化幅度、动态度、变化强度、相对变化率及景观生态学角度,对区域土地利用结构的动态变化及区域差异进行分析。研究结果表明：近十多年来,由于区域经济快速发展,工业用地扩展迅猛,城镇加速蔓延,从而导致区内耕地面积锐减,居民点及工矿用地、交通用地所占比例则逐年上升,交通用地的变化幅度及动态度最大;各用地类型的变化强度在此期间呈一定波动,除牧草地外,交通用地历年的变化强度之和最大,其次为园地、居民点及工矿用地、水利设施用地、耕地、其他农用地、林地、未利用地;区域土地利用结构逐渐向均衡状态发展,用地结构的均质性逐渐增强,地区土地利用结构渐趋稳定;各市耕地、居民点及工矿用地、其他农用地的变化幅度及相对变化率差别不大,而园地、林地、牧草地、交通用地、水利设施用地及未利用地的变化幅度及相对变化率区域差异较大,且三市园地、牧草地及未利用地的变化方向不一致。     

Methanogenic activity of woody debris

The paper is devoted to the phenomenon of methanogenic activity of woody debris, i.e., methane production in the course of wood decomposition by fungi, which are not directly involved in methane synthesis but form an initial link in the trophic chain leading to methanogenic archaea. Expert evaluation of probable amounts of methane emission is made. The results show that woody debris is an important global source of this greenhouse gas.     

中国环境管理干部学院教师健康现状的动态分析

主要采用调查法、访问法等,对中国环境管理干部学院教师健康现状进行了调查研究,并根据教师每周参加体育活动情况,教师经常参加体育活动内容及地点,教师的闲暇时间与体育支出,学院教师体检等情况,建议我院教师注重身体健康,增强健身意识,建议学院为教职工的健康工作和生活创造健身条件和环境。     

基于状态监测的井喷风险动态安全评价

井喷是钻井作业引发的最严重事故之一.通过分析钻井作业过程各个环节,确定钻井过程的风险因素和指标因素,实时监测钻井作业各参数变化,利用模糊综合层次评价法计算出钻井过程井喷风险概率,实现井喷事故动态风险评价.给出了模糊综合评价法的具体步骤,基于该方法还开发了井喷动态安全评价软件,为钻井过程中钻井液参数和钻井工程参数的优选、调整提供理论依据,同时也为钻井过程的安全生产和管理提供了参考依据.     

中国碳排放强度的时空演进及跃迁机制

面对气候变化所带来的生存危机以及环境治理的复杂状况,对中国碳排放强度时空演进的动态监测与预警治理的研究是实现碳排放强度下降目标的关键。文章测算1997—2015年中国大陆30个省区碳排放强度的空间面板数据,采用探索性时空数据分析(ESTDA)方法对中国碳排放强度的空间相关性、集聚特征及其时空跃迁进行空间统计分析,借助分位数回归与时空跃迁嵌套模型,揭示在时间和空间推移的双重作用下中国各省区碳排放强度的时空跃迁机制。研究结果表明:(1)中国30个省区的碳排放强度在时空分布上并不是完全随机状态,各个省区碳排放强度之间具有显著的空间相关性特征,碳排放强度的变动趋势会受到其相临近省区碳排放强度的影响,省域间的碳排放强度在空间分布上呈现"集聚"与"分异"并存的时空演进特征。(2)中国碳排放强度空间集聚趋势增强,具有高度的凝固性和较低的流动性,10个高碳排放强度省区碳排放强度的稳定性将成为制约中国碳排放强度整体跃迁的重点省区,相关省区的跃迁性将成为驱动中国碳排放强度整体跃迁的关键省区。(3)各省区的碳排放强度空间集聚过程中存在时空跃迁的驱动模式和制约模式,分位数回归模型能够很好地解释各驱动因素对碳排放强度时空跃迁的驱动机制,不同响应阶段的驱动因素的分位数与碳排放强度时空跃迁类型之间具有很强的嵌套性。(4)根据各省区碳排放强度时空演进及其跃迁机制的分析结果,进一步提出加强对关键省区碳排放强度的有效监测与治理,加大碳排放的约束力度等差异化的碳减排调控措施。     

京津冀产业碳排放强度变化及驱动因素研究

为探讨京津冀地区温室气体排放强度变化的影响因素,采用对数平均迪式分解模型及归因分析(LMDI-Attribution)方法,基于1996—2014年数据从细分行业角度进行研究。针对温室气体排放强度作产业结构、能源强度和排放因子三因素LMDI乘法分解,对温室气体排放强度变化的影响效应作归因分析,量化4个行业对分解因素影响效应的贡献,得到以下主要结论:1996—2014年京津冀地区温室气体排放强度主要呈现下降趋势,累计下降23.05%。其中,能源强度是温室气体排放强度下降的主导因素,其影响效应为-61.18%,对这一影响效应贡献最大的是工业,并且四大经济部门均通过能源强度在不同程度上使得温室气体排放强度有所减小,可见"阶梯电价"、"千家企业节能项目"、"十大重点节能项目"等相关政策在工业发展中对提高能源效率的作用明显。产业结构使得温室气体排放强度增加23.53%,其主要贡献者是工业,说明"工业产品出口退税率调整"等一系列政策的效果不明显;然而农业则使得温室气体排放强度降低,贡献值为3.09%。碳排放因子在1996—2014年间对温室气体排放强度的影响为60.47%,是京津冀地区温室气体排放强度增加的主要因素,说明京津冀地区的能源结构不合理。工业对这一效应的贡献最大为55.97%。可见,工业在京津冀地区的温室气体减排工作中起到最为关键的作用。     

中国工业碳排放达峰的情景预测与减排潜力评估

实现2030年碳排放达峰不仅是中国为应对全球气候变化向国际社会做出的郑重承诺,也是中国未来经济结构转型与可持续发展的必然选择。基于中国实现2030年碳排放达到峰值的宏观目标为背景,本文以中国碳排放的主要行业工业为研究对象,首先运用拓展的STIRPAT模型对工业及其9个细分行业的碳排放达峰进行了情景预测,然后基于公平和效率的双重视角对工业细分行业的减排潜力进行评估。研究表明:(1)仅有低碳情景和抑制排放情景2可以实现中国碳排放2030年达峰,低碳情景是实现中国工业碳排放达峰的最佳发展模式,达峰时间最早(2030年),峰值最低(140.43亿t)。激进排放情景则是最差的发展模式,达峰时间最晚(2036年),峰值也最高(150.09亿t)。(2)工业内部各细分行业碳排放的最优达峰情景差别较大。建材和纺织制造业能够实现提前达峰,可以在这类行业率先实施达峰管理措施,使其带动其他行业陆续达峰。(3)最具减排潜力的行业是石油制造业,其次是电力行业,这些减排潜力较大的行业应该成为国家节能减排的重点对象。(4)基于工业各细分行业在减排公平性和效率性上的差异将工业9个细分行业分为四类。其中,石油、钢铁制造业和电力行业属于"高效高公平行业";化工、建材制造业属于"低效高公平行业";采掘业属于"高效不公平行业";纺织、轻工和机电制造业属于"低效不公平行业"。中国应针对不同类型的行业制定出相应的减排战略,将减排重点放在各行业最具潜力的方面。最后,文章对实现中国工业碳排放达峰管理提出了几点政策建议。     

Carbon dioxide emissions from cities in China based on high resolution emission gridded data

Based on the China high resolution emission gridded data (1 km spatial resolution), this article is aimed to create a Chinese city carbon dioxide (CO₂) emission data set using consolidated data sources as well as normalized and standardized data processing methods. Standard methods were used to calculate city CO₂ emissions, including scope 1 and scope 2. Cities with higher CO₂ emissions are mostly in north, northeast, and eastern coastal areas. Cities with lower CO₂ emissions are in the western region. Cites with higher CO₂ emissions are clustered in the Jing-Jin-Ji Region (such as Beijing, Tianjin, and Tangshan), and the Yangtze River Delta region (such as Shanghai and Suzhou). The city per capita CO₂ emission is larger in the north than the south. There are obvious aggregations of cities with high per capita CO₂ emission in the north. Four cities among the top 10 per capita emissions (Erdos, Wuhai, Shizuishan, and Yinchuan) cluster in the main coal production areas of northern China. This indicates the significant impact of coal resources endowment on city industry and CO₂ emissions. The majority (77%) of cities have annual CO₂ emissions below 50 million tons. The mean annual emission, among all cities, is 37 million tons. Emissions from service-based cities, which include the smallest number of cities, are the highest. Industrial cities are the largest category and the emission distribution from these cities is close to the normal distribution. Emissions and degree of dispersion, in the other cities (excluding industrial cities and service-based cities), are in the lowest level. Per capita CO₂ emissions in these cities are generally below 20 t/person (89%) with a mean value of 11 t/person. The distribution interval of per capita CO₂ emission within industrial cities is the largest among the three city categories. This indicates greater differences among per capita CO₂ emissions of industrial cities. The distribution interval of per capita CO₂ emission of other cities is the lowest, indicating smaller differences of per capita CO₂ emissions among this city category. Three policy suggestions are proposed: first, city CO₂ emission inventory data in China should be increased, especially for prefecture level cities. Second, city responsibility for emission reduction, and partitioning the national goal should be established, using a bottom-up approach based on specific CO₂ emission levels and potential for emission reductions in each city. Third, comparative and benchmarking research on city CO₂ emissions should be conducted, and a Top Runner system of city CO₂ emission reduction should be established.     

CO2 emission driving forces and corresponding mitigation strategies under low-carbon economy mode: evidence from China’s Beijing–Tianjin–Hebei region

On account of the background of China’s “new normal” characterized by slower economic growth, this paper analyses the low-carbon economy status quo in the Beijing–Tianjin–Hebei region and empirically investigates the relationship between carbon dioxide (CO₂) emissions and its various factors for China’s Beijing–Tianjin–Hebei region using panel data econometric technique. We find evidence of existence of Environmental Kuznets Curve. Results also show that economic scale, industrial structure, and urbanization rate are crucial factors to promote CO₂ emissions. However, technological progress, especially the domestic independent research and development, plays a key role in CO₂ emissions abatement. Next, we further analyze the correlation between each subregion and various factors according to Grey Relation Analysis. Thereby, our findings provide important implications for policymakers in air pollution control and CO₂ emissions reduction for this region.