Carbon Emission of Regional Land Use and Its Decomposition Analysis: Case Study of Nanjing City, China

Through the matching relationship between land use types and carbon emission items, this paper estimated carbon emissions of different land use types in Nanjing City, China and analyzed the influencing factors of carbon emissions by Logarithmic Mean Divisia Index（LMDI） model. The main conclusions are as follows： 1） Total anthropogenic carbon emission of Nanjing increased from 1.22928 ×10^7 t in 2000 to 3.06939 × 10^7 t in 2009, in which the carbon emission of Inhabitation, mining ＆ manufacturing land accounted for 93% of the total. 2） The average land use carbon emission intensity of Nanjing in 2009 was 46.63 t/ha, in which carbon emission intensity of Inhabitation, mining ＆ manufacturing land was the highest（200.52 t/ha）, which was much higher than that of other land use types. 3） The average carbon source intensity in Nanjing was 16 times of the average carbon sink intensity（2.83 t/ha） in 2009, indicating that Nanjing was confronted with serious carbon deficit and huge carbon cycle pressure. 4） Land use area per unit GDP was an inhibitory factor for the increase of carbon emissions, while the other factors were all contributing factors. 5） Carbon emission effect evaluation should be introduced into land use activities to formulate low-carbon land use strategies in regional development.

Decomposition and decoupling effect of energy eco-footprint based on global net primary productivity in urban agglomerations

Net primary productivity(NPP)is an important breakthrough point of current research on ecological footprint improvement.The energy eco-footprint(EEF)of the Four-City Area in Central China(FCACC)was measured by constructing an EEF-NPP model.This work has made the following efforts:(1)Gini coefficient was employed to analyze the degree of matching between the EEF and economic growth,population,and energy consumption.(2)LMDI decomposition method was used to explore the impacts of multiple factors on the EEF in the FCACC.(3)Tapio decoupling model was applied to verify the decoupling relationships between the above influencing factors and the EEF.(4)LMDI decomposition formula was embedded into the decoupling model to analyze the impacts of technical and non-technical factors on the decoupling elasticity of the above.The main findings show that from 2010 to 2020:(1)the degree of matching of EEF-GDP,EEF-population,and EEF-energy consumption increased.(2)energy intensity and per capita GDP were the main factors that affected the EEF.(3)the decoupling states between total energy consumption,energy consumption structure,energy intensity,per capita GDP,and population size with the EEF were expansive negative decoupling,expansive negative decoupling,strong negative decoupling,weak decoupling,and expansive negative decoupling,respectively.(4)the impact of non-technical factors was greater than that of technical factors,and their impacts were always in opposite directions.

Assessment of depth of anesthesia using principal component analysis

A new approach to estimating level of uncon-sciousness based on Principal Component Analysis (PCA) is proposed. The Electroen-cephalogram (EEG) data was captured in both Intensive Care Unit (ICU) and operating room, using different anesthetic drugs. Assuming the central nervous system as a 20-tuple source, window length of 20 seconds is applied to EEG. The mentioned window is considered as 20 nonoverlapping mixed-signals (epoch). PCA algorithm is applied to these epochs, and larg-est remaining eigenvalue (LRE) and smallest remaining eigenvalue (SRE) were extracted. Correlation between extracted parameters (LRE and SRE) and depth of anesthesia (DOA) was measured using Prediction probability (PK). The results show the superiority of SRE than LRE in predicting DOA in the case of ICU and isoflurane, and the slight superiority of LRE than SRE in propofol induction. Finally, a mixture model containing both LRE and SRE could predict DOA as well as Relative Beta Ratio (RBR), which expresses the high capability of the proposed PCA based method in estimating DOA.

Strategic Measures to Reduce China's Carbon Emissions: Based on an Index Decomposition Analysis of Carbon Emissions in Eight Industries

This article uses the refined Laspeyres index decomposition method to examine the overall trends and characteristics of carbon emissions in eight Chinese industries for the period 1994-2008. The results show that every one percentage point increase in economic scale will result in an average increase of 15 Mt （million tonnes） in carbon emissions. However, different industries vary greatly in terms of marginal carbon emissions caused by economic growth. The economic structure＇s bias toward heavy industry fuels the increase of carbon emissions： every one percentage point rise in the share of manufacturing industry produces an average of 56 Mt carbon emissions. Technological progress helps reduce energy intensity and serves as a core driver in reducing carbon emissions, in that every one percentage point decrease in energy intensity will cause an average reduction of 33 Mt in carbon emissions. Our coal-dominated energy structure has resulted in a persistently high level of carbon emissions, suggesting that the reduction effect brought about by changes in energy structureis not significant. Nevertheless, lowering the density of overall carbon emissions is a positive signal, indicating that China is optimizing its energy structure. Only by promoting industrial restructuring, optimizing energy structure, encouraging energy-saving technologies and technological innovation, and reorienting industry can China achieve low-carbon development and control pollution.

基于IDA-DEA的乙烯工业能效评价方法研究及应用

为有效分析乙烯生产装置的能效状态,评价乙烯行业的能效水平,并寻找提高乙烯能效的改进方法,提出了一种基于IDA-DEA的乙烯行业能效评价方法。首先运用IDA分解方法获得影响能源消耗的活动、结构与强度3个能源绩效指标(EPI);然后使用基于投入-产出松弛变量的数据包络分析方法(DEA)对活动、结构与强度能源绩效指标进行分析,得到提高乙烯装置能效和产量的改进方向;最后,为提高乙烯装置生产提供操作指导。实验结果验证所提方法的可行性和有效性,为石化行业节能降耗提供了新思路。

基于IDA的高层框筒结构的抗震性能分析

进行结构抗震性能分析与评估是高层框筒结构抗震设计的关键内容。本文基于地面运动输入、IDA分析方法和性能指标三个方面,建立了基于IDA的高层框筒结构抗震性能分析方法,选取某高层框架核心筒结构,利用弹塑性分析软件(EPDA),基于IDA方法进行了高层框筒结构抗震性能分析。研究表明:(1)面积概率法可合理选取地面运动记录,IDA分析结果离散度较小;(2) IDA分析的地震动指标和结构损伤指标从二个维度表征了高层框筒结构抗震性能;(3)基于Hunt&fill的IDA分析方法,追踪了高层框筒结构从弹性、弹塑性破坏全过程的抗震行为,可从单条地面运动记录、多条地面运动记录和概率层面,对高层框筒结构的抗震性能做出全面评估与分析。

Decomposition analysis applied to energy and emissions:A literature review

Decomposition analysis has been widely used to assess the determinants of energy and CO_(2)emissions in academic research and policy studies.Both the methodology and application of decomposition analysis have been largely improved in the past decades.After more than 50 years’developments,decomposition studies have become increasingly sophisticated and diversified,and tend to converge internally and integrate with other analytical approaches externally.A good understanding of the literature and state of the art is critical to identify knowledge gaps and formulate future research agenda.To this end,this study presents a literature survey for decomposition analysis applied to energy and emission issues,with a focus on the period of 2016–2021.A review for three individual decomposition techniques is first conducted,followed by a synthesis of emerging trends and features for the decomposition analysis literature as a whole.The findings are expected to direct future research in decomposition analysis.

Revisiting the driving force underlying Chinese PM_(2.5)emissions:From the two perspectives of GVC and IDA

The depth and breadth of participation in the global value chain(GVC)significantly impacts a country's fine particulate contamination(PM_(2.5))emissions.First,based on the GVC accounting framework,the sources of PM_(2.5) emissions in China between 1990 and 2015 are identified and investigated considering production-side,consumption-side,and export-implied pollution.Then,index decomposition analysis(IDA)of emissions is conducted to further investigate the changes in and causes of air pollution in China.Throughout the analytical process,differences between the PM_(2.5) emissions in two time periods-one of rapid economic growth and another of the“new normal”economy-are compared.The results demonstrate that:China is embedded in high pollution links of GVCs;China transfers pollution to third-parties by importing intermediate products from resource-intensive countries in the global production system;extensive economic growth caused an increase in China's total PM_(2.5) emissions,but cleaner production technology can reduce the emissions intensity.Industrial restructuring under the“new normal”has increased China's short-term PM_(2.5) emissions intensity.These results suggest that China should optimize and upgrade its domestic economic structure and transform its export growth mode to deliver high added value and low pollution.Further,it should prioritize cooperation between the upstream and downstream value chain and accelerate the upgrading of its consumption structure in this new era.

中国城市PM_(2.5)污染暴露不平等及其驱动因素——基于Theil指数和LMDI分解

聚焦大气污染物PM_(2.5),对2015~2021年污染物浓度进行人口规模赋权,构建中国城市PM_(2.5)污染暴露水平指标,基于GINI系数和Theil指数测度污染暴露不平等,并按城市行政层级、省份进行差异分解;基于对数平均迪氏指数分解法(LMDI),分别对污染暴露水平、不平等程度进行驱动因素分解,探究其变化背后的社会经济因素.结果表明:中国城市PM_(2.5)污染暴露不平等总体温和,GINI系数保持在0.2以内且呈递减趋势.不同行政级别城市间未表现出污染暴露不平等,而省际差异对污染暴露不平等的贡献达68.4%;总体上能源的污染暴露乘数、政府绿色支出能耗强度是PM_(2.5)污染暴露水平的主要抑制因素,对污染暴露水平的驱动贡献超过60%.政府支出结构、支出规模、经济发展和人口因素对PM_(2.5)污染暴露起促增作用,但各因素在不同层级的城市间具有异质性;能源的污染暴露乘数、绿色支出能耗强度对不平等的动态抑制作用弱化,主要依靠能源绿色化的治污策略面临挑战.据此提出更好发挥政府作用,持续降低中国PM_(2.5)污染暴露水平,实现环境公共服务更加均等化的政策启示.

中国出口集装箱运价指数影响因素的实证研究

2020年,新型冠状病毒感染的流行,中国出口集装箱运价指数(CCFI)“疯涨”且不断创造历史新高。首先运用集合经验模态分解法将CCFI序列分解为若干分量,重构后得到高频部分、低频部分和趋势项,其次采用主成分分析法从选取的8个宏观影响因素中提取出两个公共因子,定义为国际贸易环境和中国出口形势,分别研究不同频率下的CCFI指数与影响因素之间的关系,探究病毒流行前后CCFI指数影响因素的变化。结果显示:CCFI的短期波动项在感染前不受宏观因素影响,感染流行后表现为正相关;病毒流行后CCFI的重大事件影响项与国际贸易环境由负相关变成正相关,与中国出口形势始终保持正相关;CCFI的长期趋势项与宏观因素在病毒流行前后均呈现正相关,且在病毒流行后正相关程度有所提高。

高强钢筋超高性能混凝土框架结构易损性分析

为了研究高强钢筋超高性能混凝土(ultra-high performance concrete, UHPC)结构的抗震能力,本文选取了8条地震动分别对普通钢筋混凝土框架结构(模型Frame-C)和高强钢筋UHPC框架结构(模型Frame-UHPC)进行了增量动力分析,分别以最大层间位移角和谱加速度为结构需求参数和地震动强度参数,拟合出概率地震需求模型,进而计算出2个模型的地震易损性曲线,得到了结构的风险预测和损伤评估结果。研究结果表明:规范性态点下,相较于模型Frame-C,模型Frame-UHPC达到最大中等破坏或严重破坏状态概率时所对应的地震动强度更大,表明模型Frame-UHPC在强震作用下具有更好的抗震能力;小震作用下,模型Frame-UHPC的易损性指数明显小于模型Frame-C,体现了高强钢筋UHPC结构的高强优势。当使用规范性态点时,2个模型在中震和大震作用下的易损性指数相差较小,模型Frame-UHPC不能充分发挥UHPC和高强钢筋的材料优势。通过对文献中配筋UHPC柱数据整理分析,给出了适用于模型Frame-UHPC的建议性态点。与规范性态点相比,建议性态点下模型Frame-UHPC达到极限状态的概率更低,易损性指数也明显减小,小震和中震所应对的易损性指数分别减小了19.5%和42.3%,模型Frame-UHPC在建议性态点下可以更好地发挥其材料优势。

江西省细分行业碳排放脱钩状态及影响因素分析

为响应经济与环境的协同发展,实现“双碳”发展目标,研究行业碳排放及脱钩情况具有一定现实意义。研究以2000研究行业年江西省各类数据为基础,采用Tapio脱钩模型判别各行业脱钩情况,结合LMDI模型深入研究影响各行业碳排放的驱动因素,厘清脱钩关系背后动因。结果表明:1)2000影响各行业年,江西省碳排增量10188.6×10^(4)t,能源消费结构中以化石能源为主,能源消费强度呈下降趋势。2)研究期内,经济增长对碳排放产生增量效应;人口增长对碳排放呈现先增后减现象;产业结构对碳排放的影响具有波动性且效力较大;能源强度和能源结构对碳排放整体呈现增量作用,各行业存在显著差异。3)研究期内江西省碳排放与经济增长的脱钩情况整体向好,第一产业、第二产业内整体呈现脱钩状态,而第三产业整体处于负脱钩状态。从多角度对江西省细分行业碳排放脱钩进行研究,以期为节能减排、实现产业转型提供参考建议。

“双碳”目标下中国工业碳排放驱动因素及其脱钩效应

通过对位于中国不同区域的辽宁省、湖北省、广东省、上海市、天津市和重庆市6个代表省市2010—2021年间的工业能源消费碳排放量进行计算,利用LMDI对数指数分解法和Tapio脱钩模型相结合的方式分析6省市经济增长与工业碳排放的脱钩动态及影响因素,并比较6省市的差异.研究发现,辽宁省与其他5省市的工业碳排放量及脱钩趋势存在差距,脱钩状态最好的是上海市和重庆市.总体来看,能源强度和产业结构因素是促进工业碳减排及脱钩的关键因素,经济增长则是最大的抑制因子,能源结构因子对于工业碳减排有很大潜力.因此,对于资源型高碳排地区的工业企业,提高能源利用效率、优化产业结构是主要的减碳及促进脱钩的方式;而非资源型经济发达地区工业企业应推动能源结构优化和经济增长方式转型.

1992-2008年我国工业废水排放变化效应

工业废水排放使我国水环境受到严重威胁,为剖析工业废水排放变化驱动机制,应用LMDI(对数平均迪氏指数)法将其分解为规模、结构和技术3种效应.结果表明:1992-2008年我国工业废水排放整体上呈先降后升的二次抛物线趋势.其中,1992-2002年工业废水减排498 583×104t,由工业规模效应、结构效应和技术效应产生的贡献值分别为1 829 988×104、206 807×104和-2 535 378×104t;2002-2008年工业废水排放增加了333 826×104t,相应地,3种效应的贡献值分别为1 470 045×104、-66 094×104、-1 070 126×104t.规模效应是造成工业废水排放增加的主要原因,技术效应是工业废水排放减少的关键因素,结构效应多表现为绝对值较小的负值,表明工业经济结构调整倾向于减小污染但贡献不大.规模效应的主要影响行业是化工原料及化学制品制造业,造纸及纸制品业和食品、烟草及饮料制造业,为减少这些部门的废水排放,可通过政策减缓经济规模的扩张趋势;结构效应的主要影响行业是电气、煤气及水的生产供应业,黑色金属冶炼及延压业和非金属矿物制造业,可通过鼓励重组促使产业结构升级,达到减排工业废水的目标;技术效应的主要影响行业是皮革、毛皮、羽绒及其制品业,为实现工业废水减排,应加大技术投入、提高生产水平.

国际贸易碳排放指数分解法研究综述

近年来,国际贸易领域碳排放影响因素的计量方法主要有描述性统计、回归分析法、情景分析法、结构分析法以及指数分解法(IDA)等几大类,而指数分解法凭借其自身优点成为当前学者研究的主流方法。文章从指数分解方法基本模型入手,在深入剖析Laspeyres指数分解法和Divisia指数分解法基础上,梳理了该方法在国际贸易碳排放中的实际应用,并对此法进行了评述。

1971—2011年辽宁寒潮时空分布特征

利用1971—2011年辽宁省58个常规观测站日最低气温资料,分析辽宁寒潮时空分布特征。结果表明:1971—2011年辽宁寒潮年平均发生频次空间分布存在两个大值中心,一个位于辽宁东北部地区,另一个位于辽西建平地区;11月大范围强寒潮出现最多。近41 a辽宁区域性寒潮呈不显著下降趋势,在20世纪70年代出现最多;区域性寒潮在10月中旬至翌年5月上旬均可出现,12月上旬至翌年2月下旬是区域性寒潮集中出现时段,出现最多的为1月;区域性寒潮出现次数存在20、13、8 a和4 a的变化周期。影响辽宁区域性寒潮的主要天气形势有小槽发展型、横槽型和低槽东移型。寒潮物理量预报指标主要有:寒潮前至少有一日升温过程;500 hPa冷中心温度≤-40℃;地面冷高压主体中心气压为1050 hPa以上,分裂小高压中心气压为1030 hPa以上;500 hPa和850 hPa急流普遍为24 m·s-1和12 m·s-1以上;850 hPa辽宁附近等温线密集程度≥5条/10纬度;风向与等温线夹角基本大于60°。

小波分析在信号预处理中的应用研究

从应用的角度简述了小波分析的基本理论和算法 ,论述了在小波分析下各尺度图对应不同频段的特性来提取或去除信号中的趋势项 ,利用有效信号和噪声在小波分析下的不同规律进行信噪分离 ,实验表明上述方法具有良好的效果。

基于LMDI方法的中国民航业碳排放因素的指数分解

2008年欧盟通过的将航空业纳入EU-ETS的提议草案,使得民航业的碳排放问题成为碳减排中的热点问题之一。中国民航业在CO2总排放量占比虽小但是增长迅速,而欧盟的这一政策如果付诸实施将给中国民航业带来一定的冲击。文章采用对数平均Divisia分解法建立中国民航业碳排放因素分解模型,定量分析了1985—2010年间民航业运输总收入、航线结构、单位运输收入周转量、能源强度、CO2排放系数等五个因素对民航业CO2排放量的影响。实证分析结果表明:民航业CO2排放量上升主要由运输总收入的增长引起,单位运输收入周转量和能源强度的下降则遏制了CO2排放量的上升。基于上述分析提出了中国民航业实现碳减排的应对策略和建议。

能源强度的指数分解分析研究综述

指数分解分析是一个研究能源强度变化及其作用机理的良好分析框架,围绕这一方法,综述了指数分解分析在方法论方面的研究现状及其在能源领域,尤其在能源强度方面的应用研究。将我国学者关于能源强度变化的研究结论划分为3类:技术进步决定论、阶段贡献变化论和分解层次影响论,并指出了指数分解分析在研究能源强度变化机理中的三大缺陷。最后,对未来的研究方向进行了展望。

高压交联聚乙烯电缆绝缘劣化试验分析

为掌握运行多年的交联聚乙烯(XLPE)电缆绝缘劣化状况及出现劣化的原因,采用热重法、红外光谱、机械强度试验分析了退运的14条110 kV和220 kV XLPE电缆绝缘。研究了电缆绝缘材料的热稳定性、物质成分及机械性能与电缆绝缘劣化的对应关系,并分析了14条退运电缆历史运行数据。结果表明,14条退运电缆中,有4条电缆绝缘出现了劣化,而这些电缆都经受过穿越故障电流或外部高温;起始分解温度、羰基指数、断裂能对表征XLPE电缆绝缘的劣化状况有很好的一致性,当绝缘出现劣化时,其起始分解温度降低、羰基指数升高、断裂能减小;交联电缆经受大的故障电流冲击或外部高温,都会加快绝缘的劣化。