Study on Dynamic Transformation,Application and Comparison of Aviation Carbon Emission Environmental Damage Assessment Methods

The contradiction between the rapid development of aviation market and supply of airspace resources has increased the environmental damages of aviation carbon emission. The conversion and application of environmental damage assessment method of aviation carbon emission were summarized, and the characteristics of the assessment methods for air and ground transportation were compared. We found out the followings: \mathrm{①} The evaluation method has been transformed from static assessment to dynamic evaluation, and focused on four key problems, average and total carbon emissions, airspace resource utilization, LTO stage emission, and reduction practice; \mathrm{②} Airport terminal area as well as LTO are becoming the focus in the study of aviation carbon emission assessment method, while the former is the main area and the latter is the main stage of aviation carbon emission. The practice of emission reduction is mainly reflected in the optimization of emission reduction measures in economic field; \mathrm{③} Based on the situation and total assessment methods, environmental damage assessment and comparative advantage of aviation carbon emission and ground transportation carbon emission are reflected in the distance by using distance factor and energy consumption; \mathrm{④} Improving the smoothness of airspace resource traffic network, optimizing flight schedule structure and airspace resource allocation are more conducive to promoting aviation emission reduction.     

Using LMDI method to analyze the influencing factors of carbon emissions in China’s petrochemical industries

China’s petrochemical industries are playing an important role in China’s economic development. However, the industries consume large amounts of energy and have become primary sources of carbon emission. In this paper, the change in carbon emissions from China’s petrochemical industries between 2000 and 2010 was quantitatively analyzed with the Log-Mean Divisia Index method, which was decomposed into economic output effect, industrial structural effect and technical effect. The results show that economic output effect is the most important factor driving carbon emission growth in China’s petrochemical industries; industrial structural effect has certain decrement effect on carbon emissions; adjustment of industrial structure by developing low-carbon emission industrial sectors may be a better choice for reducing carbon emissions; and the impact of technical effect varies considerably without showing any clear decrement effect trend over the period of year 2000–2010. The biggest challenge is how to make use of these factors to balance the relationship between economic development and carbon emissions. This study will promote a more comprehensive understanding of the inter-relationships of economic development, industrial structural shift, technical effect and carbon emissions in China’s petrochemical industries and is helpful for exploration of relevant strategies to reduce carbon emissions.     

Using LMDI method to analyze the influencing factors of carbon emissions in China’s petrochemical industries

China’s petrochemical industries are playing an important role in China’s economic development. However, the industries consume large amounts of energy and have become primary sources of carbon emission. In this paper, the change in carbon emissions from China’s petrochemical industries between 2000 and 2010 was quantitatively analyzed with the Log-Mean Divisia Index method, which was decomposed into economic output effect, industrial structural effect and technical effect. The results show that economic output effect is the most important factor driving carbon emission growth in China’s petrochemical industries; industrial structural effect has certain decrement effect on carbon emissions; adjustment of industrial structure by developing low-carbon emission industrial sectors may be a better choice for reducing carbon emissions; and the impact of technical effect varies considerably without showing any clear decrement effect trend over the period of year 2000–2010. The biggest challenge is how to make use of these factors to balance the relationship between economic development and carbon emissions. This study will promote a more comprehensive understanding of the inter-relationships of economic development, industrial structural shift, technical effect and carbon emissions in China’s petrochemical industries and is helpful for exploration of relevant strategies to reduce carbon emissions.

     

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.     

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。     

Black carbon and organic carbon emissions from wildfires in Mexico

In Mexico, approximately 7650 wildfires occur annually, affecting 263 115 hectares of land. In addition to their impact on land degradation, wildfires cause deforestation, damage to ecosystems and promote land use change; apart from being the source of emissions of toxic substances to the environment (i.e., hydrogen cyanide, black carbon and organic carbon). Black carbon is a short-lived greenhouse pollutant that also promotes snow and ice melting and decreased rainfall; it has an estimated global warming potential close to 5000.¹ We present an estimate of the black carbon and organic carbon emissions from wildfires in Mexico from 2000 to 2012 using selected emission factors from the literature and activity data from local agencies. The results show average emissions of 5955 Mg/yr for black carbon and 62 085 Mg/yr for organic carbon. Black carbon emissions are estimated to be 14 888 Gg CO₂ equivalent (CO₂ eq) per year on average. With proper management of wildfires, such emissions can be mitigated. Moreover, improved air quality, conservation of ecosystems, improvement of visibility and maintenance of land use are a subset of the related co-benefits. Mitigating forest organic carbon emissions, which are ten times higher than black carbon emissions, would also prevent the morbidity and mortality impacts of toxic organic compounds in the environment.     

Assessing the technology impact for industry carbon density reduction in China based on C3IAM-Tice

Thermal power, steel, cement, and coal chemical industries account 62.6% energy consumption and 84.6% carbon emissions of China simultaneously in 2015. This research use C³IAM-Tice model to analyze the impact of advanced technologies ratio increasing quantitatively. The model can explore the balance of emission reduction and economy efficiency of energy use, finally got the technology structure optimization for these four industries. The paper uses the historical energy consumption and CO₂ emission, combing with the low-carbon developing goal objection, to create the database for these four energy- and carbon-intensive industries. As the result, the scenario-4, which is the most advanced technology-oriented strategy, shows 282 Mt CO₂ emission reductions for the 2020 Goal. In this scenario, 26.19%, 47.43%, 65.39%, and 28.98% of the CO₂ emissions per unit of added value in thermal power industry, steel industry, cement industry, and coal chemical industry could be reduced comparing with data in 2005. Although the advanced technology-oriented strategy shows the positive impact, we need to consider the cost of elimination of existed technology. On the other hand, the paper notices the future technology, with new energy alternative, low-carbon economy development, and industry restructure together, which are important factors for the low-carbon development of China.

     

煤矿区碳排放的确认和低碳绿色发展途径研究

开展煤矿区碳排放的系统评价和减排路径的综合分析,是落实我国碳达峰与碳中和愿景的具体行动。针对煤矿区碳排放源边界不清、核算模型缺乏及碳中和背景下发展方向等问题开展分析。通过文献查阅、资料收集等方法,厘清煤矿区碳排放源边界,并建立碳排放量核算模型,明确煤矿区低碳绿色发展方向。结果表明:煤矿区碳排放(CH₄和CO₂)来源可划分为自然排放和人为排放两大类,并细分为5种类型,针对不同碳排放源提出相应的数学模型;同时煤矿区要加大节能和低碳技术的投入,提高综合资源的利用程度和瓦斯的监测力度,加强绿色矿山修复和建设,积极参与碳市场和碳排放权交易及培育适应市场的管理模式等一系列措施,逐步实现低碳、绿色产业体系;此外,煤矿相关单位应高瞻远瞩,深入分析并发挥政府的低碳环保政策的作用,与相关高校加强合作,在我国碳减排目标下,大力推动煤制氢技术的发展,突破CO₂-ECBM和CCUS关键技术中的运输、封存选址、安全稳定性评价、成本降低等瓶颈问题,以期在双碳背景下碳减排过程中实现经济、环保双重效益。      

Low-carbon development in the least developed region: a case study of Guangyuan, Sichuan province, southwest China

The Wenchuan earthquake in 2008 has resulted in 50% of Guangyuan city facing recovery from different extents of damages. The massive reconstruction provides a good opportunity for Guangyuan city to response to the National Council??s call for tackling climate change by developing a harmonised and low-carbon economy. However, there are many arguments about the definition of ??low carbon?? and the framework that low-carbon development should follow. Low-carbon development in an economically least developed region such as Guangyuan would provide evidence and contribute to the discussion. The paper employs CO₂ emissions as an environmental indicator in scenario analysis to investigate Guangyuan??s future carbon performance in following the national call of reducing 40% of carbon intensity by 2020 and an alternative low-carbon development path. The results have demonstrated that a ??win?Cwin?? solution can be reached??keeping rapid economic growth while reducing CO₂ emissions, however, only by addressing the ??correct?? determining factors. Technology improvements and production structure changes have been identified as the key determining factors to affect both carbon intensity and CO₂ emissions in the future. The two factors are also interdependent. Governmental policies should give appropriate guideline to address both factors but with strong emphasis on production structure decarbonisation in order to avoid the mistake of ??polluting first and deal with the pollution later?? during the emission-intensive industrialisation processes that many western countries and China??s coastal regions have followed.     

论煤地质学与碳中和

煤基碳排放构成了中国碳排放总量中最重要的部分,做好煤基碳减排和煤炭高效洁净低碳化利用是实现"碳中和"国家目标的重要途径,碳中和背景下的煤地质学发展值得关注.系统评述与碳中和相关的煤地质学研究领域,分析煤地质学在碳中和研究与工程实践中的作用和应用前景,探讨碳中和背景下煤地质学的重要发展方向.取得以下认识:推进清洁煤地质研...     

基于社会网络分析方法的二氧化碳地质封存风险传染特征研究

二氧化碳(CO₂)地质封存技术作为深度减排不可或缺的必要手段,对保护生态环境、推动全球中长期应对气候变化的国际合作以及推进社会绿色、循环、低碳发展具有重要意义。文章总结了二氧化碳地质封存项目全生命周期中可能出现的46个风险因素,运用社会网络分析方法构建风险网络关系模型,对二氧化碳地质封存项目风险因素间的传递作用关系进行了研究。通过风险网络整体与局部参数分析确定风险传递过程中的关键起始节点、关键致险节点、关键传递节点等关键因素,识别出三条潜在风险传递链：(1)地质灾害风险→CO₂供应、注入或运输意外中断风险→预期外的建设或操作成本变化风险;(2)操作人员知识不足或无相应资质风险→人为泄漏风险→项目对环境的破坏风险→公众参与风险→预期外的建设或操作成本变化风险;(3)部门协调不当风险→人才招聘和管理风险→操作人员知识不足或无相应资质风险→预期外的建设或操作成本变化风险。研究旨在为二氧化碳地质封存项目风险研究提供理论创新与技术参考,进而促进CO₂捕集、利用与封存项目的健康发展。     

Provincial variation of carbon emissions from bituminous coal: influence of inertinite and other factors

We observe a 1.3 kg C/net GJ variation of carbon emissions due to inertinite abundance in some commercially available bituminous coal. An additional 0.9 kg C/net GJ variation of carbon emissions is expected due to the extent of coalification through the bituminous rank stages. Each percentage of sulfur in bituminous coal reduces carbon emissions by about 0.08 kg C/net GJ. Other factors, such as mineral content, liptinite abundance and individual macerals, also influence carbon emissions, but their quantitative effect is less certain.The large range of carbon emissions within the bituminous rank class suggests that rank-specific carbon emission factors are provincial rather than global. Although carbon emission factors that better account for this provincial variation might be calculated, we show that the data used for this calculation may vary according to the methods used to sample and analyze coal. Provincial variation of carbon emissions and the use of different coal sampling and analytical methods complicate the verification of national greenhouse gas inventories.     

A Review of the Scientific Assessment and Research on Household Carbon Emission

Household consumption represents an important proportion of all energy consumption,and it is an important source of CO₂ emission. But household consumption and carbon emissions are often overlooked in climate change policies and measures. Through literature review, the research status of household consumption and carbon emissions were reviewed. On this basis, the main aspects and directions of the research are summarized and the main research of household carbon emissions should focus on three aspects in the future: ①The impact of income, consumption levels and other factors on household carbon emission; ②The relationship between direct and indirect carbon emissions of household carbon emission; ③The structure and source of household carbon emission. In future research, there are four issues which need in-depth study: ①Index and models study of household carbon emissions;②Impact of demographic change on household carbon emissions; ③The path of how to achieve sustainable and green urban lifestyle;④The relevant policy research of household carbon emissions.     

Modeling and prediction of ventilation methane emissions of U.S. longwall mines using supervised artificial neural networks

Methane emissions from a longwall ventilation system are an important indicator of how much methane a particular mine is producing and how much air should be provided to keep the methane levels under statutory limits. Knowing the amount of ventilation methane emission is also important for environmental considerations and for identifying opportunities to capture and utilize the methane for energy production.Prediction of methane emissions before mining is difficult since it depends on a number of geological, geographical, and operational factors. This study proposes a principle component analysis (PCA) and artificial neural network (ANN)-based approach to predict the ventilation methane emission rates of U.S. longwall mines.Ventilation emission data obtained from 63 longwall mines in 10 states for the years between 1985 and 2005 were combined with corresponding coalbed properties, geographical information, and longwall operation parameters. The compiled database resulted in 17 parameters that potentially impacted emissions. PCA was used to determine those variables that most influenced ventilation emissions and were considered for further predictive modeling using ANN. Different combinations of variables in the data set and network structures were used for network training and testing to achieve minimum mean square errors and high correlations between measurements and predictions. The resultant ANN model using nine main input variables was superior to multilinear and second-order non-linear models for predicting the new data. The ANN model predicted methane emissions with high accuracy. It is concluded that the model can be used as a predictive tool since it includes those factors that influence longwall ventilation emission rates.     

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。     

丝绸之路经济带节点城市人文驱动因素对环境的影响

“一带一路”上升为国家战略,推进丝绸之路经济带建设使中国西北地区由过去发展的腹地转变为开放的前沿。通过引入STIRPAT模型,研究分析了丝绸之路经济带节点城市人文驱动因素对环境的影响,设定了三种情景分析节点城市未来低碳发展情况。结果表明：人文驱动因素对碳排放的影响程度较大,模型拟合优度达到95.2%,能源消耗强度（T）、富裕程度（A）和人口数量（P）的弹性系数分别为0.511、0.285和0.222,基准情景下二氧化碳排放总量呈现稳步上升态势,政策情景和低碳情景下碳排放存在“拐点”,预计碳排放峰值将在2025-2033年间出现,低碳情景峰值比政策情景提前8 a到达,峰值总量减少40.79×10⁴ t。最后针对分析结果就丝绸之路经济带节点城市人文驱动因素对环境的影响提出了相关建议,即控制人口数量、优化产业结构、强化污染治理。     

青藏高原土壤碳排放研究进展

青藏高原土壤碳排放研究是评估国家区域碳排放量和预测气候变化所可能导致影响的关键. 首先对青藏高原土壤碳排放的关键性影响因子进行探讨, 并分析了土壤碳排放的时空分布格局变化. 目前青藏高原土壤碳排放研究主要是针对高寒草甸及高寒草地生态系统, 较少涉及高寒荒漠, 研究区域较为分散; 土壤碳排放受到气候环境因素、生物因素及人为因素等多重因素的影响, 其中温度、土壤湿度、土壤区系生物、人为因素及多年冻土退化是最关键的影响因素; 土壤碳排放具有明显的时空变异性, 空间变异性在生物群丛、景观、区域和生物群系四个尺度体现, 时间变异性在日、季、年上体现. 总体而言, 青藏高原土壤碳排放的研究较少, 尤其关于大尺度、长时间序列的研究以及土壤碳排放的机理等方面的研究十分缺乏, 有待于后续加强研究.     

Driving forces of indirect carbon emissions from household consumption in China: an input–output decomposition analysis

Human activities have become a major source of Earth’s climate change, which brings the rise of surface air temperature and subsurface ocean temperature. Therefore, promoting sustainable consumption and production patterns is imperative to minimize the use of natural resources and reduce emissions of pollutants. This study uses Economic Input–Output Life-Cycle Assessment method and structural decomposition model to identify the driving forces that influence the changes in carbon emissions from China’s residential consumption in the context of sustainable consumption. The findings of the study are as follows: (1) indirect carbon emissions from Chinese household consumption increase rapidly over time; (2) the largest carbon dioxide emitting sector turns from agriculture sector in 1992 into service sector in 2007; (3) the consumption level and the emission intensity are the main drivers that influence the change in indirect carbon emissions; and (4) the factor of consumption level presents positive effect on the emissions, while the emission intensity effect plays a negative role. Besides, the factors of urbanization, production structure, population size and consumption structure also promote the rapid increase in carbon emissions.     

Driving forces of indirect carbon emissions from household consumption in China: an input–output decomposition analysis

Human activities have become a major source of Earth’s climate change, which brings the rise of surface air temperature and subsurface ocean temperature. Therefore, promoting sustainable consumption and production patterns is imperative to minimize the use of natural resources and reduce emissions of pollutants. This study uses Economic Input–Output Life-Cycle Assessment method and structural decomposition model to identify the driving forces that influence the changes in carbon emissions from China’s residential consumption in the context of sustainable consumption. The findings of the study are as follows: (1) indirect carbon emissions from Chinese household consumption increase rapidly over time; (2) the largest carbon dioxide emitting sector turns from agriculture sector in 1992 into service sector in 2007; (3) the consumption level and the emission intensity are the main drivers that influence the change in indirect carbon emissions; and (4) the factor of consumption level presents positive effect on the emissions, while the emission intensity effect plays a negative role. Besides, the factors of urbanization, production structure, population size and consumption structure also promote the rapid increase in carbon emissions.