国外CO2地质储存现状与展望

温室气体CO2的大量排放给全球气候和环境带来的巨大影响,受到了世界各国的关注。实现CO2的深度减排是人类可持续发展的必由之路。CO2地质储存是缓解碳排放行之有效的方法之一。本文通过以下几方面论述了国外CO2地质储存的现状以及对未来的展望：1）CO2捕集机理,2）CO2地质储存,3）CO2地质储存项目现状与未来预测,4）CO2地质储存场地储量评估,5）CO2地质储存监测技术,6）CO2地质储存模拟工具,7）CO2地质存储经费等。     

国外 CO2地质储存现状与展望

温室气体CO2的大量排放给全球气候和环境带来的巨大影响,受到了世界各国的关注.实现CO2的深度减排是人类可持续发展的必由之路.CO2地质储存是缓解碳排放行之有效的方法之一.本文通过以下几方面论述了国外CO2地质储存的现状以及对未来的展望:1)CO2捕集机理,2)CO2地质储存,3)CO2地质储存项目现状与未来预测,4) CO2地质储存场地储量评估,5)CO2地质储存监测技术,6)CO2地质储存模拟工具,7)CO2地质存储经费等.     

广西壮族自治区碳排放时空规律及达峰预测

广西壮族自治区是国家重要的工业原料供应地,但工业化进程缓慢致使碳排放增长显著,为了积极响应国家减排号召,探究广西历史及未来碳排放规律,以期尽早实现碳达峰目标。由于县级碳排放数据可获取性方面的限制,研究以2003—2017年广西县级碳排放数据,进行广西碳排放量、碳排放强度及碳排放压力的时空变化分析,划分广西不同地域碳排放类型和碳排放情景,并利用可扩展的随机性环境影响模型（STIRPAT）对2022—2035年间广西各地域碳排放类型进行了不同情景下碳排放达峰预测。（1）2003—2017年间,广西碳排放总量、碳排放压力增幅明显,碳排放强度明显降低。碳排放总量变异系数总体趋势平稳,呈高强度变异。（2）依据碳排放总量、强度、压力分级组合,碳排放可分为高总量-高强度-高压力型等6种地域类型,根据广西碳排放影响因素的现状及未来发展趋势划分基准情景、节能情景等7种情景。（3）广西全域达峰预测结果显示,4种节能发展情景均能在2030年前完成达峰目标。不同地域类型达峰预测结果显示高总量-高强度-低压力型与高总量-低强度-低压力型采用节能情景可以实现达峰目标。高总量-高强度-高压力型和高总量-低强度-高压...     

基于能源需求理论的全球CO2排放趋势分析

能源消费是影响CO2排放的最主要因素, 本文以能源消费基本规律为基础, 按照人均累积CO2排放、人均CO2排放以及CO2排放强度三个重要指标, 系统分析了英国、美国、法国、日本、中国等典型国家CO2排放的历史轨迹, 全面预测了未来20年全球及中国CO2排放量。结果表明: 2030年中国CO2排放总量将为124亿吨, 人均排放约为8.5吨, CO2排放强度为356吨/百万美元, 与处于相同发展程度的美国(1994年)相比, 人均排放指标和排放强度指标均不到其一半水平。2020年和2030年, 中国的CO2排放强度与2007年比将分别降低46%和60%, 将为减缓温室气体排放做出突出贡献。     

海洋直接注入CO2封存技术方法综述

人类活动造成的CO2排放是全球气候变暖面临的主要挑战之一。CO2封存有望成为全世界减少碳排放份额最大的单项技术。海洋碳捕获、利用和封存（OCCUS）可以在较短时间内提供最大的碳封存能力,与其他地质封存方法相比更加安全有效。而且,多相态形式的CO2（气态、液态、固态和水合物）可以在海洋纵深尺度上实现直接注入。海洋碳封存是一项发展潜力巨大、优势明显的新兴碳封存技术,是实现大规模碳减排的重要措施之一,具有广阔的应用前景。因此,笔者等系统地阐述了海洋CO2直接注入、封存（OCS）的基本原理、技术现状、监测与评估,以及环境方面的影响,并对高效CO2注入技术,CO2泄漏的检测、防范与补救技术,以及海洋碳封存的生态后效等方面进行了展望。     

基于土地利用变化的河西内陆河流域碳排放时空特征北大核心CSCD

土地利用变化是引起碳排放增加的重要原因之一。探索区域土地利用变化引起的碳排放量和碳排放效率问题,对于把握各土地利用类型的碳排放特征、制定土地利用减排策略具有重要意义。本研究以集中国生态系统重要性与脆弱性于一体的典型区域的河西内陆河流域为研究区,利用1985—2020年的土地利用现状遥感数据,通过土地利用动态变化模型、排放系数法深入分析了河西内陆河流域的土地利用变化及其引起的碳排放量和碳排放效率的时空变化特征。结果显示:(1)1985—2020年绿洲规模呈持续扩张趋势,与1985年相比,2020年的绿洲面积相对增加了13.17%;建设用地以单向转入为主,其余土地利用类型之间的双向转变频繁。(2)各土地利用类型的净碳排放量总体呈增加趋势,2020年净碳排放量(113.17×104t)相对1985年(48.57×104t)增加了1.33倍,净碳排放量与绿洲面积显著正相关,耕地和建设用地扩张引起的碳排放量是净碳排放量增加的主要原因。碳排放弹性系数整体呈增加趋势,由1990年的-1.83增至2020年的205.91。(3)1985—2020年的耕地和建设用地碳排放强度、绿洲碳排放强度均呈增加趋势,分别由1985年的32.17 t·km-2和5.09 t·km-2增至2020年的60.74 t·km-2和10.48 t·km-2,但绿洲碳排放强度增加速率小于耕地和建设用地,同期的绿洲碳吸收强度普遍呈递减趋势。(4)工业城市嘉峪关市、金昌市的多年平均绿洲碳排放强度最大,以灌溉农业为主的行政单元相对较低,以畜牧业为主的祁连县最低。本研究通过定量分析河西内陆河流域土地利用的碳排放量及其变化,有助于宏观把握河西内陆河流域土地利用的碳排放特征,对于寻找解决土地利用的减排方案、加强土地管理和推动土地利用的低碳发展模式提供了科学认识基础和决策参考。     

东营凹陷高青-平南断裂带幔源流体活动特征及其成藏效应

东营凹陷高青-平南断裂带为幔源流体运移的主要通道,该幔源流体主要为岩浆(岩)和CO2气体。高青-平南断裂带幔源流体活动方式和活动强度存在着时间和空间上的差异,该断裂带在古近纪-新近纪至少经历了四期富CO2幔源流体活动。高青-平南断裂带富CO2幔源流体对油气成藏的影响主要表现在：①直接形成无机CO2气藏;②通过能量——热的作用和物质,即CO2的加入,影响水-岩相互作用的强度和方向,从而改善油气储集层的物性;③在一定程度上提高源岩的排烃效率,增加油气的运移速率。     

汶川地震相关的断裂带含碳气体排放量估算

断裂带是地下气体向上运移的有利通道,地震活动会加剧地下气体沿断裂带向上运移,释放到大气中。本文利用卫星高光谱遥感技术,初步估算了汶川地震伴随的大范围含碳气体(CH_4、CO和CO_2)的排放变化总量。结果显示,龙门山断裂带长期不断地向大气中排放大量的含碳气体,汶川地震的发生导致在短时间里龙门山断裂带向大气中至少多排放了4740t CO、8549t CH_4和87.15 Mt CO_2。地震活动造成的断裂带含碳气体排放不可忽视,是地质碳排放的重要组成部分,对大气环境效应有重要影响。     

中国区域碳排放研究

通过比较不同机构和学者对中国区域碳排放的测算结果, 指出现有测算结果间存在巨大差异的具体原因, 按照更加科学准确的方法重新测算了中国各省及中部、东部、西部等主要区域的能源和水泥的碳排放量, 以此为基础, 通过对比分析, 对1990至2008年间不同区域碳排放总量、人均排放量、碳排放强度等重要指标的差异进行了系统分析。研究表明: 中国的区域碳排放格局是东部地区排放总量和累计排放量最大, 但西部地区排放总量及占全国的份额有逐步增加的趋势; 着重指出西部地区作为中国下一轮经济发展最重要的增长点, 其目前的人均碳排放量和碳排放强度均高于相同发展阶段的其他地区, 如不尽快转变其发展模式, 则会使未来的节能减排形势异常严峻, 中国的低碳经济之路仍旧任重而道远。     

民航飞行CO2排放及其对气候变化影响研究综述

碳排放是国际社会共同关注的热点,从碳减排到碳中和,已成为全球共同的目标。CO₂是航空飞行排放中最丰富的气体,尽管在人类活动碳排放总量中占比不大,但其影响会成数倍增加,因此,全球性应对气候变化的共同行动使得航空运输业必须重视CO₂排放。随着我国民航业快速发展,航空燃油消耗所产生的碳排放也在不断增长,这就给我国实现碳减排目标徒增压力,所以,民航飞行碳排放的气候变化效应问题就显得十分重要,且具有很强的科学性。国内外特别是国际上就这一课题进行了较多研究,形成了较丰富的成果。通过对相关主要成果的深入研阅和凝练,从碳排放测算、碳排放对气候变化的影响等方面评述了目前较为主流的航空飞行碳排放及其气候变化效应的研究进展和工作动态,并提出了未来的探索方向。通过对航空飞行排放影响的另一个角度的梳理总结,有助于未来更加全面地认识气候变化问题,以期为相关部门学者和科技工作者开展我国科学全面的减排对策研究提供参考。     

Changes in carbon intensity of China’s energy-intensive industries: a combined decomposition and attribution analysis

There has been growing interest among researchers in factors influencing carbon emissions of energy-intensive industries in China due to the important roles they play. Such studies mainly focused on evaluating carbon emissions and identifying the contributing factors separately for each energy-intensive industry. Regarding energy-intensive industries as a whole and investigating the contribution of each industry to changes in carbon intensity have not yet been sufficiently addressed and quantified. In order to deeply understand this issue, this study employed the LMDI decomposition analysis to study driving forces (e.g., emission coefficient, energy intensity, and industrial structure) of carbon intensity of energy-intensive industries. Then, attribution analysis was further used to study the contribution of each energy-intensive industry to the percent change in carbon intensity through each impact factor. The results showed that the carbon intensity of energy-intensive industries dropped by 31.83% from 1996 to 2014. The energy intensity effect was largely responsible for this decrease, of which, five industries were the contributors except for the fuel-processing industry. The industrial structure effect also contributed to the decrease, and non-metallic industry and fuel-processing industry played important roles. However, the emission coefficient effect showed a slight impact on increasing carbon intensity, which principally due to chemical industry and power generation industry. The findings suggested that the adaptability and sensitivity of different energy-intensive industries to the implemented policies were various. Based on the results, differentiated and feasible policies related to energy intensity, industrial structure, and energy structure for energy-intensive industries were provided to further mitigate carbon intensity.     

The impact of economic growth,industrial structure and urbanization on carbon emission intensity in China

China’s macroeconomic policy framework has been determined to ensure steady growth, adjust the industrial structure and advance the socioeconomic reforms in recent years. And urbanization is supposed to be one of the most important socioeconomic reform directions. Meanwhile, China also committed to reduce carbon emissions intensity by 2020, then it should be noted that what kind of impact of these policy orientations on carbon emission intensity. Therefore, based on the historical data from 1978 to 2011, this paper quantitatively studies the impact of China’s economic growth, industrial structure and urbanization on carbon emission intensity. The results indicate that, first, there is long-term cointegrating relationship between carbon emission intensity and other factors. And the increase in the share of tertiary industry [i.e., the ratio of tertiary industry value added to gross domestic product (GDP)] and economic growth (here we use the real GDP per capita) play significant roles in curbing carbon emission intensity, while the promotion of population urbanization (i.e., the share of population living in the urban regions of total population) may lead to carbon emission intensity growth. Second, there exists significant one-way causality running from the urbanization rate and economic growth to carbon emission intensity, respectively. Third, among the three drivers, economic growth proves the main influencing factor of carbon emission intensity changes during the sample period.     

产业转移背景下区域工业碳排放时空格局演变——以泛长三角为例

产业转移背景下区域能源消费、碳排放格局时空格局变化是近期研究者关注的热点。以处于产业转移期的泛长三角地区为例,以工业能源消费为对象,分析了1990,1995,2000,2005和2010年5个年份碳排放的空间格局和演变规律,探索了产业转移对碳排放格局演变的影响。结果表明,1990年以来工业碳排放稳步增长,高值区集中于长三角核心区;碳排放增长的区域差异较大,热点区域由长三角核心区向外围区转移;碳排放格局发生变化,排放重心呈现先东南向、后西北向移动的态势;工业重心和碳排放重心空间分离,但移动过程类似。研究认为,产业转移所引起的各地区工业产值、产品结构和碳排放强度的变化,与碳排放格局变化具有较大关联性,是影响区域碳排放格局变化的重要因素。     

The impact of inter-industry R&D technology spillover on carbon emission in China

Based on input–output table to measure inter-industry R&D technology spillover, this paper introduces inter-industry R&D technology spillover into panel econometric model for carbon dioxide (CO₂) emissions factor analysis. Using the panel data of 34 industrial sectors in China from 2005 to 2014, the results reveal that there is an inverted “U-shaped” nonlinear relationship between R&D technology spillover (intensity) and carbon emission; it is estimated that R&D technology spillover can reduce carbon emission currently; the indirect impact of R&D technology spillovers or spillovers intensity through R&D intensity on carbon emissions is also beneficial to carbon emission reduction; at last, this study suggests that industrial sectors should improve R&D intensity and strengthen technical exchanges and cooperation with other related sectors for the purpose of R&D technology spillover increase and CO₂ emissions reduction.     

基于STIRPAT模型的甘肃省交通碳排放测算及影响因素分析

依据IPCC清单指南的数据, 采用"自上而下"的碳排放计算方法, 对2000-2013年甘肃省交通碳排放进行测算, 对交通碳排放总量、人均量、交通能源碳排放结构及碳排放强度进行动态分析. 基于STIRPAT模型, 运用岭回归统计方法对甘肃省交通碳排放影响因素进行定量分析. 结果表明: 甘肃省交通碳排放总量和人均碳排放量都呈逐年上升的趋势; 煤炭、汽油、柴油、电力四种能源消费的碳排放量占交通碳排放量的绝大部分; 交通碳排放强度呈下降趋势; 城镇化水平、客运周转量、货运周转量、人均GDP每增长1%, 导致交通碳排放分别增长0.221%、0.137%、0.174%和0.125%. 建设低碳交通体系将成为甘肃省交通部门减碳的有效途径.     

Club convergence and spatial distribution dynamics of carbon intensity in China’s construction industry

Climate change caused by carbon emissions continuously threatens sustainable development. Due to China’s immense territory, there are remarkable regional differences in carbon emissions. The construction industry, which has strong internal industrial differences, further leads to carbon emission disparity in China. Policymakers should consider spatial effects and attempt to eliminate carbon emission inequality to promote the sustainable development of the construction industry and realize emission reduction targets. Based on the classic Markov chain and spatial Markov chain, this paper investigates the club convergence and spatial distribution dynamics of China’s carbon intensity in the construction industry from 2005 to 2014. The results show that the provincial carbon intensity in the construction industry is characterized by “convergence clubs” during the research period, and very low-level and very high-level convergence clubs have strong stability. Moreover, the carbon intensity class transitions of provinces tend to be consistent with that of their neighbors. Furthermore, the transition of carbon intensity types is highly influenced by their regional backgrounds. The provinces with high carbon emissions have a negative influence on their neighbors, whereas the provinces with low carbon emissions have a positive influence. These analyses provide a spatial interpretation to the “club convergence” of carbon intensity.     

Using decomposition analysis to evaluate the performance of China’s 30 provinces in CO2 emission reductions over 2005–2009

This paper aims to evaluate the carbon dioxide (CO₂) emissions reduction performance of 30 mainland provinces in China over 2005?C2009. First, the log-mean Divisia index (LMDI) technique is used to decompose the changes in CO₂ emissions at the provincial level into 4 effects that are carbon intensity effect, energy mix effect, energy intensity effect and gross domestic product (GDP) effect. Next, two indicators, decoupling index and rescaled decoupling index, are implemented to evaluate the performance of 30 provinces in CO₂ emission reduction from 2005 to 2009. The decomposition result shows that the GDP growth is mainly responsible for the CO₂ emissions increase, while the energy intensity effect is the key factor for the decrease in CO₂ emissions in each province. Moreover, according to the evaluation, the performance of each province in what concerns the CO₂ emission reduction varies significantly. Most provinces in China made significant efforts in emissions reduction during 2005?C2009, while some provinces only made weak efforts or even no efforts in decoupling progress.     

重庆市不同功能区建设用地碳排放的库兹涅茨曲线特征分析

文章对重庆市五大功能区1998-2013年的土地利用变更数据调查和能源消耗数据进行分析,运用库兹涅茨曲线模型研究了重庆市五大功能区16年间建设用地扩张与碳排放效应之间的内在关系。结果表明:（1）重庆市建设用地扩张与碳排放强度之间的回归模型关系呈倒U型库兹涅茨曲线关系,且拐点即将到来;（2）都市功能核心区、都市功能拓展区建设用地与碳排放强度之间的关系呈倒U型库兹涅茨曲线关系;（3）城市发展新区建设用地与碳排放强度之间的关系呈一次线性关系,显示出区域产业结构调整和土地利用集约水平的初级特征;（4）渝东北生态涵养区建设用地与碳排放强度之间呈正U型二次曲线关系,土地集约利用水平亟待提高。