中国能源消费碳排放的空间计量分析(英文)

Based on energy consumption data of each region in China from 1997 to 2009 and using ArcGIS9.3 and GeoDA9.5 as technical support,this paper made a preliminary study on the changing trend of spatial pattern at regional level of carbon emissions from energy con-sumption,spatial autocorrelation analysis of carbon emissions,spatial regression analysis between carbon emissions and their influencing factors.The analyzed results are shown as follows.(1) Carbon emissions from energy consumption increased more than 148% from 1997 to 2009 but the spatial pattern of high and low emission regions did not change greatly.(2) The global spatial autocorrelation of carbon emissions from energy consumption in-creased from 1997 to 2009,the spatial autocorrelation analysis showed that there exists a "polarization" phenomenon,the centre of "High-High" agglomeration did not change greatly but expanded currently,the centre of "Low-Low" agglomeration also did not change greatly but narrowed currently.(3) The spatial regression analysis showed that carbon emissions from energy consumption has a close relationship with GDP and population,R-squared rate of the spatial regression between carbon emissions and GDP is higher than that between carbon emissions and population.The contribution of population to carbon emissions in-creased but the contribution of GDP decreased from 1997 to 2009.The carbon emissions spillover effect was aggravated from 1997 to 2009 due to both the increase of GDP and population,so GDP and population were the two main factors which had strengthened the spatial autocorrelation of carbon emissions.     

基于IO-SDA模型的新疆能源消费碳排放影响机理分析（英文）

Analysis of carbon emission mechanism based on regional perspectives is an important research method capable of achieving energy savings and emission reductions.Xinjiang,an important Chinese energy production base,is currently going through a period of strategic opportunities for rapid development.Ensuring stable socio-economic development while achieving energy savings and meeting emission reductions targets,is the key issue currently facing the region.This paper is based on the input-output theory,and conducts a structural decomposition analysis on the factors affecting energy-related carbon emissions in Xinjiang from 1997 to 2007;this analysis employs a hybrid input-output analysis framework of "energy- economy- carbon emissions".(1) Xinjiang's carbon emissions from energy consumption increased from 20.70 million tons in 1997 to 40.34 million tons in 2007;carbon emissions growth was mainly concentrated in the production and processing of energy resources,the mining of mineral resources,and the processing industry.(2) The analysis of the direct effects of the influencing factors on carbon emissions showed that the change in per capita GDP,the final demand structure,the population scale,and the production structure were the important factors causing an increase in carbon emissions,while the decrease in carbon emission intensity during this period was the important influencing factor in stopping the growth of carbon emissions.This showed that while the sizes of Xinjiang's economy and population were growing,the economic structure had not been effectively optimized and the production technology had not been efficiently improved,resulting in a rapid growth of carbon emissions from energy consumption.(3) The analysis of the indirect effects of the influencing factors of carbon emission showed that the inter-provincial export,fixed capital formation,and the consumption by urban residents had significant influence on the changes in carbon emissions from energy consumption in Xinjiang.(4) The growth of investments in fixed assets of carbon intensive industry sectors,in addition to the growth of inter-provincial exports of energy resource products,makes the transfer effect of inter-provincial "embodied carbon" very significant.     

中国城市能源消费碳排放的区域差异、空间溢出效应及影响因素分析（英文）

Data show that carbon emissions are increasing due to human energy consumption associated with economic development. As a result, a great deal of attention has been focused on efforts to reduce this growth in carbon emissions as well as to formulate policies to address and mitigate climate change. Although the majority of previous studies have explored the driving forces underlying Chinese carbon emissions, few have been carried out at the city-level because of the limited availability of relevant energy consumption statistics. Here, we utilize spatial autocorrelation, Markov-chain transitional matrices, a dynamic panel model, and system generalized distance estimation(Sys-GMM) to empirically evaluate the key determinants of carbon emissions at the city-level based on Chinese remote sensing data collected between 1992 and 2013. We also use these data to discuss observed spatial spillover effects taking into account spatiotemporal lag and a range of different geographical and economic weighting matrices. The results of this study suggest that regional discrepancies in city-level carbon emissions have decreased over time, which are consistent with a marked spatial spillover effect, and a ‘club' agglomeration of high-emissions. The evolution of these patterns also shows obvious path dependence, while the results of panel data analysis reveal the presence of a significant U-shaped relationship between carbon emissions and per capita GDP. Data also show that per capita carbon emissions have increased in concert with economic growth in most cities, and that a high-proportion of secondary industry and extensive investment growth have also exerted significant positive effects on city-level carbon emissions across China. In contrast, rapid population agglomeration, improvements in technology, increasing trade openness, and the accessibility and density of roads have all played a role in inhibiting carbon emissions. Thus, in order to reduce emissions, the Chinese government should legislate to inhibit the effects of factors that promote the release of carbon while at the same time acting to encourage those that mitigate this process. On the basis of the analysis presented in this study, we argue that optimizing industrial structures, streamlining extensive investment, increasing the level of technology, and improving road accessibility are all effective approaches to increase energy savings and reduce carbon emissions across China.     

城市能源消费碳排放特征及其机理分析 ——以广州市为例

采用表观能源消费数据进行分能源品种和分行业类型的碳排放总量核算,利用基于IDA理论和Kaya恒等式的LMDI模型对碳排放总量变化进行多要素的分解分析,在解析人口规模效应、经济产出效应、能源强度效应对碳排放影响机理的同时,进一步纳入人口结构性因素、产业结构性因素和能源结构性因素对碳排放的影响。以广州市为例,对其2003—2013年产业活动和居民消费2个部门碳排放的主要驱动因素进行时间序列分析,并定量研究各个影响因子在2003—2005、2005—2010和2010—2013年3个不同发展阶段的作用机理,主要研究结论如下：1）广州市能源消费及其碳排放前期以煤炭为主,近年来以石油为主,同时外购电力对广州市的能源消费结构优化影响显著。2）各影响因子对广州市碳排放总量变化的作用机理与影响机制在3个发展阶段各不相同,不同发展阶段的发展措施和政策背景对于各个影响因子的碳排放效应影响显著。3）总体分析,经济产出效应和人口规模效应是产业部门碳排放增长的最主要贡献因子;工业能源消费强度效应、工业能源消费结构效应和经济结构效应是遏制产业部门碳排放增长的最主要贡献因子。城镇居民收入效应是居民消费碳排放增长的最主要贡献因子,城镇居民能源消费强度效应是遏制居民消费碳排放增长的最主要贡献因子。     

中国产业结构升级、全要素能源效率与碳排放（英文）

基于2000-2018年全国30个省份（港澳台、西藏除外）的面板数据,利用面板回归模型和中介效应模型分析了产业结构升级、全要素能源效率及碳排放之间的关系和影响机制。研究发现：产业结构高级化在不同区域对碳排放均呈现显著的抑制作用,不同区域的抑制强度呈现“西部>中部>东部”的规律;产业结构合理化在不同区域对碳排放的抑制作用差异较大,在中西部地区表现为显著的抑制作用,但在东部地区抑制作用不显著;各区域全要素能源效率的提升对碳排放的抑制作用均较为显著,抑制强度呈现“西部>东部>中部”的规律。进一步通过中介检验发现,不同区域的全要素能源效率在产业结构升级与碳排放的作用中具有部分和完全中介效应,能够促进和加强产业结构升级对碳排放的抑制作用。因此,研究认为产业结构升级和提升全要素能源效率是促进碳减排的有效手段,但单独依赖产业结构升级的碳减排效果并不理想,需与提升全要素能源效率相结合才会对碳减排起到有效的促进作用。     

中国能源消费碳排放强度及其影响因素的空间计量(英文)

The sustainable development has been seriously challenged by global climate change due to carbon emissions. As a developing country, China promised to reduce 40%–45% below the level of the year 2005 on its carbon intensity by 2020. The realization of this target depends on not only the substantive transition of society and economy at the national scale, but also the action and share of energy saving and emissions reduction at the provincial scale. Based on the method provided by the IPCC, this paper examines the spatiotemporal dynamics and dominating factors of China's carbon intensity from energy consumption in 1997–2010. The aim is to provide scientific basis for policy making on energy conservation and carbon emission reduction in China. The results are shown as follows. Firstly, China's carbon emissions increased from 4.16 Gt to 11.29 Gt from 1997 to 2010, with an annual growth rate of 7.15%, which was much lower than that of GDP(11.72%). Secondly, the trend of Moran's I indicated that China's carbon intensity has a growing spatial agglomeration at the provincial scale. The provinces with either high or low values appeared to be path-dependent or space-locked to some extent. Third, according to spatial panel econometric model, energy intensity, energy structure, industrial structure and urbanization rate were the dominating factors shaping the spatiotemporal patterns of China's carbon intensity from energy consumption. Therefore, in order to realize the targets of energy conservation and emission reduction, China should improve the efficiency of energy utilization, optimize energy and industrial structure, choose the low-carbon urbanization approach and implement regional cooperation strategy of energy conservation and emissions reduction.     

中国在气候变化下碳排放、能源消费与低碳经济领域的研究进展综述（英文）

Accompanying the rapid growth of China's population and economy, energy consumption and carbon emission increased significantly from 1978 to 2012. China is now the largest energy consumer and CO2 emitter of the world, leading to much interest in researches on the nexus between energy consumption, carbon emissions and low-carbon economy. This article presents the domestic Chinese studies on this hotpot issue, and we obtain the following findings. First, most research fields involve geography, ecology and resource economics, and research contents contained some analysis of current situation, factors decomposition, predictive analysis and the introduction of methods and models. Second, there exists an inverted "U-shaped" curve connection between carbon emission, energy consumption and economic development. Energy consumption in China will be in a low-speed growth after 2035 and it is expected to peak between 6.19–12.13 billion TCE in 2050. China's carbon emissions are expected to peak in 2035, or during 2020 to 2045, and the optimal range of carbon emissions is between 2.4–3.3 PgC/year(1 PgC=1 billion tons C) in 2050. Third, future research should be focused on global carbon trading, regional carbon flows, reforming the current energy structure, reducing energy consumption and innovating the low-carbon economic theory, as well as establishing a comprehensive theoretical system of energy consumption, carbon emissions and low-carbon economy.     

环境规制、FDI与能源消费碳排放峰值预测——以西北五省为例

基于STIRPAT模型,运用情景分析法对西北地区2017—2030年能源消费碳排放进行预测,在高、中、低三种环境规制强度下设定出9种发展模式,以分析环境规制与FDI对能源碳排放峰值的影响。研究表明：（1） 在初始发展情境下,西北地区2030年碳排放总量为70 273.07×10⁴ t,无法实现碳排放达峰目标。（2） 低环境规制背景下,高、高中、高低三种发展模式2030年能源消费碳排放额为73 550.53×10⁴ t、64 881.98×10⁴ t、56 296.96×10⁴ t。（3） 中、高环境规制下,中低、低两种发展模式分别于2025年、2020年达到碳排放峰值,峰值额度为53 447.15×10⁴ t、51 022.68×10⁴ t。能源碳排放强度为0.86 t·（10⁴元）^-1、0.68 t·（10⁴元）^-1,相比较2005年碳排放强度下降48.38%、60.14%。9种发展模式中,仅中低、低两种发展模式能够如期实现碳排放峰值任务,表明严格的环境规制政策能够有效减缓西北地区能源消费碳排放,为促进西北地区碳排放峰值目标如期实现,针对西北地区碳减排工作提出了相应对策建议。     

石油资源流动框架构建——以中国为例（英文）

石油作为现代工业社会的血液和全球性重要的战略资源,被广泛用于交通运输、化工、医药、制造等各行各业。加强石油资源流动研究,有助于理解石油在产业内部以及其他产业之间的流动过程。石油资源流动分析框架及测算方法研究是开展石油供需研究的基础与前提,同时也是石油产品二氧化碳排放评估研究的基础。鉴于此,本文构建了石油资源流动分析框架,把石油资源产业流动过程划分为4阶段,3种流,3种库和2个过程,归纳总结了石油资源流动测算分析方法。以中国为例开展实证研究,研究结果显示:(1)过去二十年中国石油生产、消费和出口量迅猛增长,快速正价的需求和有限的供应能力导致中国石油进口来源呈现多元化,从而实现国家层面上的石油安全;(2)终端消费掉多数石油产品,应该特别关注石油炼制过程中的损失情况;(3)除去原油,不同部门之间的石油产品流入量已经发展了巨大变化,在交通运输和生活消费部门呈现明显的上升趋势,而工业消费量呈现下降趋势。(4)石油资源流动的CO2排放而言,从1993年的4.56亿t上升到2013年的15.17亿t;与此同时,二氧化碳排放的前三名从工业、运输业(包括运输业、仓储和邮政业)、火力发电业转变为交通运输、工业和生活消费。此外,石油资源产业流动需进一步加强系统边界、数据库和针对非能源消费的石油资源流动模型研究等。     

矿区风场CFD数值模拟研究——以中国内蒙古乌海市新星煤矿为例（英文）

在中国西北干旱区,大量煤矿开采导致植被退化,强风发生概率增大。风场特征直接影响着沙尘的输运过程。为获取矿区风场特征,本文以内蒙古乌海新星煤矿为例,采用RANS湍流模型,利用开源软件OpenFOAM进行了CFD数值模拟。基于矿区多个观测点的风场实测结果,对数值模拟结果进行了验证,并讨论了西风、西北风和东风三个风向下矿区平均风速和湍动能的分布规律。结果表明：矿区东西两侧凸起的高山或丘陵对矿区平均风速分布影响较大;当风从西或东方向来袭时,由于尾流效应的影响,高地下游平均风速相对较小;而湍流动能则表现出较大的数值。对于西北风向,山或丘陵的尾流效应不太明显;同样,在低洼矿坑附近,平均风速减小,湍流动能增大。本研究可为矿区风沙防治及风沙建设提供理论依据。     

县域尺度下能源产区能源消费碳排放强度空间分异——以陕西省榆林市为例

以能源产区陕西省榆林市的12个区县为研究单元,在Geo Da和Arc GIS等软件的支持下,结合趋势分析和空间统计方法,分析2005—2010年榆林县域尺度下的能源消费碳排放强度的空间格局特征与空间分异机制。榆林各区县能源消费碳排放强度水平差异明显,总体差异呈扩大趋势,两极分化加剧。县域碳排放强度南北走向上表现出逐渐减小趋势,东西走向上具有微弱的"U"型变化态势。总体上,东北部区县碳排放强度高于西南部。各区县碳排放强度具有正的空间关联分布特征,且处于低水平非均衡空间分布状态,空间依赖性明显。结合相关性分析,榆林区县碳排放强度具有极化区、扩散区、塌陷区和传染区4个特征。"热点"主要分布在东北部三县,"冷点"主要分布于南部六县。能源资源分布不均、经济总量以及产业结构差异是造成榆林碳排放强度空间分布不均的主要原因。     

中国不同区域能源消费碳足迹的时空变化(英文)

Study on regional carbon emission is one of the hot topics under the background of global climate change and low-carbon economic development, and also help to establish different low-carbon strategies for different regions. On the basis of energy consumption and land use data of different regions in China from 1999 to 2008, this paper established carbon emission and carbon footprint models based on total energy consumption, and calculated the amount of carbon emissions and carbon footprint in different regions of China from 1999 to 2008. The author also analyzed carbon emission density and per unit area carbon footprint for each region. Finally, advices for decreasing carbon footprint were put forward. The main conclusions are as follows: (1) Carbon emissions from total energy consumption increased 129% from 1999 to 2008 in China, but its spatial distribution pattern among different regions just slightly changed, the sorting of carbon emission amount was: Eastern China > Northern China > Central and Southern China > Southwest China > Northwest China. (2) The sorting of carbon emission density was: Eastern China > Northeast China > Central and Southern China > Northern China > Southwest China > Northwest China from 1999 to 2003, but from 2004 Central and Southern China began to have higher carbon emission density than Northeast China, the order of other regions did not change. (3) Carbon footprint increased significantly since the rapid increasing of carbon emissions and less increasing area of pro-ductive land in different regions of China from 1999 to 2008. Northern China had the largest carbon footprint, and Northwest China, Eastern China, Northern China, Central and Southern China followed in turn, while Southwest China presented the lowest area of carbon footprint and the highest percentage of carbon absorption. (4) Mainly influenced by regional land area, Northern China presented the highest per unit area carbon footprint and followed by Eastern China, and Northeast China; Central and Southern China, and Northwest China had a similar medium per unit area carbon footprint; Southwest China always had the lowest per unit area carbon footprint. (5) China faced great ecological pressure brought by carbon emission. Some measures should be taken both from reducing carbon emission and increasing carbon absorption.     

省尺度森林植被碳储量空间分布模拟不确定性分析——以江西省为例（英文）

Forest vegetation carbon patterns are significant for evaluating carbon emission and accumulation. Many methods were used to simulate patterns of forest vegetation carbon stock in previous studies, however, uncertainty apparently existed between results of different methods, even estimates of same method in different studies. Three previous methods, including Atmosphere-vegetation interaction model 2(AVIM2), Kriging, Satellite-data Based Approach(SBA), and a new method, High Accuracy Surface Modeling(HASM), were used to simulate forest vegetation carbon stock patterns in Jiangxi Province in China. Cross-validation was used to evaluate methods. The uncertainty and applicability of the four methods on provincial scale were analyzed and discussed. The results showed that HASM had the highest accuracy, which improved by 50.66%, 33.37% and 28.58%, compared with AVIM2, Kriging and SBA, respectively. Uncertainty of simulation of forest biomass carbon stock was mainly derived from modeling error, sampling error and statistical error of forest area. Total forest carbon stock, carbon density and forest area of Jiangxi were 288.62 Tg, 3.06 kg/m~2 and 94.32×109 m~2 simulated by HASM, respectively.     

基于结构分解法的北京能源碳排放增量分析(英文)

确保减碳的首要任务是定量测度化石能源消费碳排放的增量影响因素及其大小。为分析北京市1997-2007年的碳排放增量,本文构建了一个扩展的(调入、进口)竞争型经济—能源—碳排放投入产出模型,从整体特征、不同产业、工业行业3个方面,对1997-2007年北京能源消费的碳排放增量进行了结构分解。分析发现:经济规模增长要素(消费、投资、调出和出口等)是拉动碳排放增长的主导因素,能源强度变动效应却是碳减排的决定性因素;在规模扩张因素中,消费和调出超过投资和出口,是碳排放增长的主要贡献者;2002以来新一轮"高碳"特征的工业化导致CO2排量呈急增之势;产业结构调整、三产比重最大使得服务业成为碳排放增长的最大部门,但工业排放的增长却后来居上;碳增排的重点行业是高能耗业,而碳减排的却是能源工业;两时段各效应在不同产业、不同工业行业的影响方向和大小不一。     

甘肃省能源消费碳足迹变化及影响因素分析(英文)

能源消费是人类活动影响全球气候变化的主要行为之一,对能源消费导致的碳足迹进行研究具有重要意义。本文首先应用能源消费碳足迹的相关概念和方法,计算得到了甘肃省1990年-2009年的总碳足迹、各能源消费类型的碳足迹、碳足迹产值和碳足迹生态压力;然后利用STIRPAT模型进行岭回归函数拟合,探讨了经济增长与碳足迹之间的定量关系,并验证了环境库兹涅茨曲线的存在性;最后通过脱钩指数分析进一步研究了经济增长与碳足迹之间的动态变化关系。结果表明:碳足迹从1990年的每人0.091 ha上升为2009年的每人0.191 ha,呈现波动上升的趋势。各能源消费类型的碳足迹构成中,煤和石油占据了绝对地位,其中又以煤所占比重最大,石油次之,天然气所起的作用甚微。碳足迹产值由1990年的1.18万元ha-1增加为2009年的2.51万元ha-1,碳足迹生态压力也从1990年的0.10上升至2009年的0.24。人口和人均GDP是驱动碳足迹增长的主要因素,且回归分析和脱钩指数分析都表明经济增长与碳足迹之间存在环境库兹涅茨曲线。     

农村宅基地功能转型分析——以江西省鄱阳县为例（英文）

农村宅基地是农村土地系统中极其重要的组成部分,是农村衰落、农村空心化等各种问题表征的重要载体。农村地区发生巨大变化的同时,农村宅基地也发生着深刻的转型。本研究在总结国内外对于农村宅基地多功能分类的基础上,根据实地调查问卷,从宅基地功能提升的角度划分并界定了宅基地的人口承载功能、资产以及居住功能。通过协调转型度模型对农村宅基地的功能及协调转型度进行了分析。结果表明:(1)2000–2017年鄱阳县农村宅基地功能转型度在整体上有了明显提升。(2)北部山地丘陵区及环鄱阳湖区主要分布着协调转型度的高值区,近县城的平原区主要分布着协调转型度的低值区。(3)区位条件与资源禀赋较好的区域,人口、资本等要素非农化的支撑条件也比较好,相应的非农化趋势也更为明显。应根据不同区域农村宅基地转型的差异化情况提出针对性的发展建议。     

城市碳足迹与碳循环压力分析——以南京市为例（英文）

Urban carbon footprint reflects the impact and pressure of human activities on urban environment.Based on city level,this paper estimated carbon emissions and carbon footprint of Nanjing city,analyzed urban carbon footprint intensity and carbon cycle pressure and discussed the influencing factors of carbon footprint through LMDI decomposition model.The main conclusions are as follows:(1) The total carbon emissions of Nanjing increased rapidly since 2000,in which the carbon emission from the use of fossil energy was the largest.Meanwhile,carbon sinks of Nanjing presented a declining trend since 2000,which caused the decrease of carbon compensation rate and the increase of urban carbon cycle pressure.(2) The total carbon footprint of Nanjing increased rapidly since 2000,and the carbon deficit was more than ten times of total land areas of Nanjing in 2009,which means Nanjing confronted high carbon cycle pressure.(3) Generally,carbon footprint intensity of Nanjing was on decrease and the carbon footprint productivity was on increase.This indicated that energy utilization rate and carbon efficiency of Nanjing was improved since 2000,and the policy for energy conservation and emission reduction taken by Nanjing's government received better effects.(4) Economic development,population and industrial structure are promoting factors for the increase of carbon footprint of Nanjing,while the industrial carbon footprint intensity was inhibitory factor.(5) Several countermeasures should be taken to decrease urban carbon footprint and alleviate carbon cycle pressure,such as:improvement of the energy efficiency,industrial structure reconstruction,afforestation and environmental protection and land use control.Generally,transition to low-carbon economy is essential for Chinese cities to realize sustainable development in the future.     

中国碳排放对国际贸易影响的经验分析(英文)

International trade is an important impact factor to the carbon emissions of a country.As the rapid development of Chinese foreign trade since its entry into the WTO in 2002,the effects of international trade on carbon emissions of China are more and more significant.Using the recent available input-output tables of China and energy consumption data,this study estimated the effects of Chinese foreign trade on carbon emissions and the changes of the effects by analyzing the emissions embodied in trade between 2002 and 2007.The re-sults showed a more and more significant exporting behavior of embodied carbon emissions in Chinese international trade.From 2002 to 2007,the proportion of net exported emissions and domestic exported emissions in domestic emissions increased from 18.32% to 29.79% and from 23.97% to 34.76%,respectively.In addition,about 22.10% and 32.29% of the total imported emissions were generated in processing trade in 2002 and 2007,respectively,which were imported and later exported emissions.Although,most of the sectors showed a growth trend in imported and exported emissions,sectors of electrical machinery and communication electronic equipment,chemical industry,and textile were still the biggest emission exporters,the net exported emissions of which were also the largest.For China and other developing countries,technology improvement may be the most favorable and acceptable ways to re-duce carbon emissions at present stage.In the future negotiations on emissions reduction,it would be more fair and reasonable to include the carbon emissions embodied in international trade when accounting the total emissions of an economy.     

城市气候承载力定量化评价——以上海市为例（英文）

为了开展气候风险管理,近期学者们提出了气候承载力的概念。本文在分析气候承载力的概念内涵及其影响因子的基础上,从当前气候天然容量,城市气候压力和城市协调发展潜力3个方面构建城市气候承载力综合评价指标体系。以上海市为例,采用构建的城市气候承载力评价方法分析上海市2004-2013年气候承载力变化特点,并利用主成分因子分析法确定气候承载力的主要影响因子。分析结果如下:(1)当前气候天然容量指数表明上海市的气候条件劣于基准年,在研究期间呈波动状态;(2)城市气候压力和城市协调发展能力呈稳步增长状态,但协调发展能力的增长速度低于城市气候压力的增长速度;(3)总体来说,研究期间上海市气候承载力远低于基准年,且气候承载力值因受气候条件变化影响较大而处于较大波动状态;(4)基于主成分因子分析方法确定城市人口密度、人均GDP、单位生产总值能耗、工业总产值、环境保护投资、科技经费支出以及人均绿地面积为主要影响因子。结果表明,该气候承载力评价方法是可行的,它可以描述某一城市气候承载力在时域上的变化,也可以对区域气候承载力开发利用过程中存在的问题进行甄别,并可作为气候预警响应的依据,为我国建立气候安全管理机制提供技术参考。