Assessment of energy supply vulnerability between China and USA

USA and China are the two largest energy-consuming countries, and energy supply vulnerability is a prior topic on energy policy. Then, we develop energy supply vulnerability assessment index including the sustainability, the stability, the reliability, and the diversification indicators to assess and compare the change of energy supply vulnerability between China and USA based on the data in 2001–2010. We found that the fluctuations of energy supply vulnerability in China are more than those of USA. In 2001–2006, the index of China’s energy supply vulnerability presented a quick uptrend, but it presented a slow downtrend in 2007–2010 due to the uncertainty of some indicators; energy supply vulnerability of USA presented smaller change from 2000 to 2008 because of the stable and comprehensive energy supply system, but in 2009 and 2010, it became obviously less than those in other years due to the decline of energy consumption per capita. Additionally, Chinese energy supply also faces higher maritime transportation and geopolitical vulnerability than that of USA. The comparisons of the change of energy supply vulnerability between China and USA show that it is important to develop comprehensive energy supply system to reduce the uncertainty of main effect indicators, such as the control of energy consumption growth, and the diversification of energy supply and import.

     

Indirect carbon emissions from household consumption between China and the USA: based on an input–output model

Based on an input–output model, this paper calculates carbon emissions from household energy consumption in 2002, 2005, 2007, and 2010 between China and the USA. By a comparative analysis of the two countries, the results indicate the following: (1) In terms of the total household indirect carbon emissions, the USA has always been at a higher level than China. However, in recent years, China has presented a rapidly rising trend. In contrast, the USA appears to be experiencing a downward trend. (2) Indirect carbon emissions from USA household consumption mainly focus on Residence; Education, Culture, and Recreation; and Transport and Communications. By comparison, residence accounts for 50 % of China’s household indirect carbon emissions, and seven other sectors are much less than the USA (3) Although the number of China’s household facilities is growing rapidly, the carbon emissions remain at a relatively steady level. (4) In terms of the absolute value of the indirect carbon emissions from housing, the USA maintains a steady 400 million ton, while China increased from 150 to 500 million ton over 2002–2010.

     

Study on temporal and spatial evolution of China’s oil supply and consumption

To begin with, energy flow chart is used to analyze the status of China’s oil supply and consumption. Moreover, the temporal and spatial evolution of the oil production and oil products consumption in China is studied based on the gravity model. Finally, the decoupling index combined with the log mean Divisia index method is used to explore the contribution of the factors which influence terminal oil product consumption in China over the period 1991–2010. This paper draws the following results: (1) China’s net oil import dependency soared from 7.5 % in 1993 to 58.63 % in 2010. (2) The center of gravity for crude oil production and oil products consumption is an overall movement toward the southwest. (3) The economic activity effect is the critical factor in the growth of oil products consumption in China. However, industrial energy intensity effect plays the dominant role in decreasing oil products consumption. (4) The value of the decoupling index represented a re-coupling effect in 1996–1997 and 2003–2004. The other time interval showed weak decoupling effect.     

基于DPRISM概念框架的生态环境脆弱性评价—以岷江上游为例

针对目前生态环境脆弱性评价中存在的评价指标选取片面性、脆弱性动态变化研究薄弱的问题,基于DPRISM概念框架选取22个指标构建评价指标体系,定量研究岷江上游2000年-2014年生态环境脆弱性动态变化过程。结合岷江上游生态环境特点,建立基于驱动力-压力-状态-影响-响应-管理(DPSIRM)概念框架的生态环境脆弱性评价模型,利用多源数据,包括气象数据,遥感数据,基本地理数据,社会经济数据,计算出EVI(Ecological Vulnerability Index)值,并利用生态环境脆弱性综合指数及其变化率分析研究区生态环境脆弱性时空变化规律。结果表明:①2000年-2014年间研究区生态环境脆弱性呈西部向东部逐渐递减的空间分布特点;②三个时间段内脆弱性均以微度、轻度、中度为主,面积比例分别为:84.15%、84.42%、87.13%;③三个时间段内,研究区生态环境脆弱性综合指数变化率R均小于0,表明研究区生态环境脆弱性值在逐年减小;④14年间,岷江上游生态环境脆弱性呈逐步改善趋势,但该趋势不明显,还需长期坚持生态治理政策。     

Identifying urban–rural differences in social vulnerability to natural hazards: a case study of China

Identifying and analyzing the urban–rural differences of social vulnerability to natural hazards is imperative to ensure that urbanization develops in a way that lessens the impacts of disasters and generate building resilient livelihoods in China. Using data from the 2000 and 2010 population censuses, this study conducted an assessment of the social vulnerability index (SVI) by applying the projection pursuit cluster model. The temporal and spatial changes of social vulnerability in urban and rural areas were then examined during China’s rapid urbanization period. An index of urban–rural differences in social vulnerability (SVI_D) was derived, and the global and local Moran’s I of the SVI_D were calculated to assess the spatial variation and association between the urban and rural SVI. In order to fully determine the impacts of urbanization in relation to social vulnerability, a spatial autoregressive model and Bivariate Moran’s I between urbanization and SVI were both calculated. The urban and rural SVI both displayed a steadily decreasing trend from 2000 to 2010, although the urban SVI was always larger than the rural SVI in the same year. In 17.5% of the prefectures, the rural SVI was larger than the urban SVI in 2000, but was smaller than the urban SVI in 2010. About 12.6% of the urban areas in the prefectures became less vulnerable than rural areas over the study period, while in more than 51.73% of the prefectures the urban–rural SVI gap decreased over the same period. The SVI_D values in all prefectures had a significantly positive spatial autocorrelation and spatial clusters were apparent. Over time, social vulnerability to natural hazards at the prefecture-level displayed a gathering–scattering pattern across China. Though a regional variation of social vulnerability developed during China’s rapid urbanization, the overall trend was for a steady reduction in social vulnerability in both urban and rural areas.

     

The role of disaggregated renewable energy consumption on income and load capacity factor: A novel inclusive sustainable growth approach

Stimulating renewable energy consumption is a major focus of the Sustainable Development Goals in combating climate change and global warming. The International Energy Agency estimates that renewable energy consumption should be doubled to achieve the COP21 targets. In this context, the question is whether renewable energy types promote the improvement of ecological quality and economic growth. Most studies have investigated the influence of renewable energy on ecological pollution using carbon dioxide emissions or ecological footprint indicators, which only represent the pollution caused by human consumption patterns, and these indicators neglect the supply side. Motivated by this point, this study uses the LCF (Load Capacity Factor) as an environmental indicator and examines the causality relationship among different types of renewable energy, income, and environmental quality in the USA, while also incorporating employment and capital stock into the analysis. Through using the Fourier causality test with the wavelet-decomposed series, the study explores for the validity of the renewable energy-based growth hypothesis and answers to the question of whether there is a causal effect of renewable energy types on environmental quality. The results demonstrate that there is a bidirectional causality between total renewable energy, wood, biomass, and economic growth as well as between these renewable energy types and the LCF.     

Exposure,vulnerability, and adaptation of major maize-growing areas to extreme temperature

Driven by increasing demand for food and industrial consumption, world’s maize supply is under stress. Besides, the extreme temperature events are now exposing more threat to maize yield with ongoing climate change. Thus, a comprehensive analysis on maize exposure (exposure is defined as the cultivated area which is exposed to extreme temperature stress), vulnerability (here it means how much yield losses with each temperature increase/decrease at a national scale), and adaptation to extreme temperature is essential to better understand the effects on global maize production, especially in major production countries. It was found that warming trends during the growing season have extensively dominated the main maize-growing areas across the globe. And along with this mean temperature trend was the increasing heat stress and decreasing cold stress among most regions. Moreover, from 1981 to 2011, maize yield losses caused by heat stress in China, India, and the USA were 1.13, 0.64 and 1.12% per decade, respectively, while Mexico has been experiencing a reduction of yield loss due to decreased cold stress of 0.53% per decade. Furthermore, during the period of 2021–2051, the extreme heat stress would increase substantially, while the low temperature was estimated to drop slightly during the growing seasons. Such pattern had also been found over the key reproductive stage of maize. Accordingly, through the sensitivity test of two adaption measures, improved high-temperature-tolerant varieties and changing maize calendar earlier could both mitigate extreme meteorological stress on maize, while the former method would be the most effective way to do so. Our study could provide a paradigm for other crops and other countries in the world to analyze their exposure and vulnerability to the temperature stress and make corresponding adaptation measures.

     

Characterizing the spatial distribution of typical natural disaster vulnerability in China from 2010 to 2017

Natural disaster vulnerability can intuitively reflect the susceptibility of an area to environmental changes. Better understanding the spatial distribution of natural disaster vulnerability is a critical process for taking effective adaptation and management. Although significant achievements have been made in disaster vulnerability, few studies are known about natural disaster vulnerability at the national scale, especially from the typical natural disaster events in China. In this study, with normalizing selected indicators and calculating vulnerability index, we analyzed the spatial distribution of natural disasters vulnerability during 2010–2017 using the geospatial techniques. The results showed that natural disaster vulnerability has certain spatial differences, but different natural disaster can occur in the same area during the study period. Drought disaster can occur in all regions of China, especially in Inner Mongolia. Flood disaster is mainly concentrated in the middle and lower reaches of the Yangtze River and the Yellow River Basin. The wind and storm disaster is chiefly in the northern regions in China. The freezing disaster is widely distributed in China. Furthermore, the regions with low vulnerability were primarily distributed in the eastern coastal region, indicating that the rapid development of economy and technology can resist or mitigate natural disaster to a certain extent. This study offers a solution to study natural disasters and provides scientific basis for disaster prevention and mitigation actions.

     

Strategies for addressing climate change on the industrial level: affecting factors to CO<Subscript>2</Subscript> emissions of energy-intensive industries in China

This paper explores China’s strategies for addressing climate change on the industrial level. Focusing on six energy-intensive industries, this paper applies gray relational analysis theory to the affecting factors to CO₂ emissions of each industry after calculating each industry’s CO₂ emissions during 2001–2010. Further research based on GM(1, 1) model is conducted to forecast the trend of the factors, the energy consumption and each industry’s CO₂ emissions during the 12th Five-Year Plan period. As a breakthrough in previous conclusions, energy consumption structure was divided into the respective proportion of coal, oil, natural gas and electricity in the primary energy consumption, with which industrial output and energy intensity are combined to analyze each of their impacts on the energy-intensive industries. It turns out that all the factors’ impacts on emissions of the six major energy-intensive industries are significant, despite their differentiated extents. It is worth noting that, contrary to previous findings, industrial output is not the leading affecting factor to CO₂ emissions of the energy-intensive industries compared with the proportion of coal and electricity in the primary energy consumption. The GM(1, 1) forecast results of energy consumption and CO₂ emissions by the end of 2015 show that coal and electricity will remain a large proportion in primary energy consumption. This research may shed some light on China’s adjustment of energy structure under the pressure of addressing climate change and hence provide decision support for the acceleration of renewable energy utilization in the industrial departments.     

基于集对分析法的喀斯特地区水资源安全动态变化及原因分析——以贵州省为例

根据中国西南喀斯特地区特殊的水文水资源特点,从水资源赋存、供水状况、用水状况、水资源利用效率、水资源管理等五个方面构建了水资源安全评价指标体系,选择SPA（集对分析法）对贵州省2001-2015年水资源安全状况进行了动态评价。结果表明:贵州省2001-2007年水资源处于临界安全状态,2008-2015年水资源整体处于安全和较安全等级（除2009干旱年份外）。从影响水资源安全的5大要素类的变化看,水资源赋存受自然环境因素影响显著,H2值较不稳定;供水状况因受水利工程建设的影响,2001-2015年H2值由0.53上升到0.90;用水状况因生产用水和生态环境用水的提高,H3值由2001年的0.87下降为2015年0.20;水资源利用效率因万元GDP用水量以及农田亩均灌溉用水量的显著下降,H2值由2001年的0.26增加到2015年的0.88,向安全和较安全等级转变明显;水资源管理受生活污水处理率、森林覆盖率显著提高的影响,H2值由2001年的0.09增加到2015年的0.58,由原先的极不安全等级提升到临界安全等级,但在某些方面,如万元GDP污染物减排率等仍有较大的提升空间;供水状况、水资源利用效率、水资源管理这几个方面均表明人类行为对水资源安全影响显著。      

Methodology for the assessment and classification of regional vulnerability to natural hazards in China: the application of a DEA model

This paper presents a new method for quantifying vulnerability to natural hazards in China. As an important area of vulnerability research, quantitative assessment of vulnerability has raised much focus in academia. Presently, scholars have proposed a variety of methods for quantitative assessment, which usually create an index of overall vulnerability from a suite of indicators, based on the understanding of the cause or mechanism of vulnerability. However, due to the complex nature of vulnerability, this approach caused some arguments on the indicator selection and the weight set for subindices. A data envelopment analysis?Cbased model for the assessment of the regional vulnerability to natural disasters is presented here to improve upon the traditional methods, and a new approach for the classification of vulnerability is proposed. The vulnerability to natural hazards in China??s mainland is illustrated as a case study. The result shows that the overall level of vulnerability to natural hazards in mainland China is high. The geographic pattern shows that vulnerability is highest in western China, followed by diminishing vulnerability in central China, and lowest vulnerability levels in eastern China. There is a negative correlation between the level of vulnerability and the level of regional economic development.     

Investigation of ionospheric TEC precursors related to the M7.8 Nepal and M8.3 Chile earthquakes in 2015 based on spectral and statistical analysis

The assessment of social vulnerability is a requirement for understanding the risk of natural hazards. This paper calculates the social vulnerability index of geological disasters in China with the super-efficiency DEA (data envelopment analysis) model, carries out global and local autocorrelation tests for social vulnerability to geological disasters in each province in China and identifies the characteristics of its spatial distribution pattern. The results show the following. (1) China’s social vulnerability to geological disasters is relatively high and has obvious differences. It represents the pattern of a significant increase by degrees in social vulnerability to geological disasters from east to west and a significantly negative correlation relationship between the vulnerability level and the economic level. (2) Based on the comparative analysis of the mean values of the indexes and the social vulnerability index of geological disasters, it is found that the social vulnerability index of geological disasters in China is directly related to the regional exposure degree and reaction and recovery ability, among which the reaction and recovery ability has great effects on the social vulnerability index. (3) Most of the regions in China are in a high–high clustering area or a low–low clustering area; that is to say, the regions with similar social vulnerability to geological disasters represent the pattern of clustering.     

我国县域单元地质灾害风险评估

文中地质灾害包括崩塌、滑坡、泥石流、地面塌陷四类突发性地质灾害。采用地质灾害危险性与承灾体易损性分项测算,定性综合评估的方式实现我国县域单元地质灾害风险评估。将承灾体易损性分为人口安全易损性与资产易损性,用因灾死亡人口比与因灾直接经济损失比表征。基于以历史数据分析指导未来预测的思想,以国土资源部2001—2015年地质灾害灾情数据为样本,提出了人口安全易损性与资产易损性的分级标准。对我国2869个县域单元进行地质灾害风险评价,结果表明共有216个地质灾害高风险单元、643个中风险单元和2010个低风险单元。地质灾害高风险区集中分布于乌蒙山区、四川盆地周边山区以及云南西部和西藏东南部。     

Assessment of provincial social vulnerability to natural disasters in China

Assessment of social vulnerability has been recognized as a critical step to understand natural hazard risks and to enhance effective response capabilities. Although significant achievements have been made in social vulnerability researches, little is know about the comprehensive profile of regional social vulnerability in China. In this study, the social vulnerability to natural hazards was firstly divided into socioeconomic and built environmental vulnerability. Then, using factor analysis, we identified the dominant factors that influence the provincial social vulnerability in China to natural hazards based on the socioeconomic and built environmental variables in 2000 and 2010 and explored the spatial patterns of social vulnerability. The results indicated that the provincial social vulnerability in China showed significant regional differences. The social vulnerability in the southeastern and eastern regions of China was greater than its northern and central parts over the past decade. Economic status, rural (proportion of agricultural population and percentage of workers employed in primary industries), urbanization, and age structure (children) were the dominant driving forces of variations in provincial socioeconomic vulnerability in two studied years, while lifelines and housing age could explain most of changes in built environmental vulnerability in 2000 and 2010. There were no statistically significant correlations between social vulnerability and disaster losses (p > 0.05), indicating the impact of disasters was also related to the intensity of hazards and exposure. Disaster relief funds allocated to each province of China depended more on its disaster severity than the regional integrated social vulnerability over the past decade. These findings would provide a scientific base for the policy making and implementation of disaster prevention and mitigation in China.     

The impact of acid rain on China’s socioeconomic vulnerability

Acid rain has been a great threat to socioeconomic sustainable development of China; therefore, we develop an indicator system based on the sensitivity and adaptive capacity perspectives and employ the TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) approach to investigate the impact of acid rain on socioeconomic vulnerability of China. Some empirical findings are obtained. First, there is significant provincial difference of socioeconomic vulnerability caused by acid rain in China. Specifically, Tibet, Qinghai, and Shanghai are the top three provinces with the largest vulnerability but Inner Mongolia, Xinjiang, and Jilin are bottom of the rankings. Second, adaptive capacity indicators overall appear more important than sensitivity indicators to measure the vulnerability of acid rain, and the most important indicators are population density and output value of agriculture, forestry, animal husbandry, and fishery while GDP per capita ranks the last. Third, upgrading energy structure and reducing outdated capacity in China prove to be effective means to mitigate vulnerability of acid rain, which has been validated in Guizhou and Hunan provinces. Finally, great attention should be attached to the population increase so as to curb the acid rain vulnerability, especially in Beijing and Tianjin. These results present a basis for future acid rain prevention planning and economic development in China.     

Stress of urban energy consumption on air environment

With rapid urbanization and heavy industrialization as well as the rapid increase of cars in China, the effect of energy consumption on urban air environment is increasingly becoming serious, and has become a hot topic for both scholars and decision-makers. This paper explores the effect mechanism and regulation of urban energy consumption on the air environment, and summarizes the framework of the stress effect relationship and the evolutionary process. In accordance with the effect relationship of the internal factors between the two, analytic approaches studying the stress effect of urban energy consumption on air environment are proposed, including the analysis of air environment effects caused by urban energy consumption structure change, and the analysis of air environment effects caused by urban energy economic efficiency change, as well as a decomposition analysis of air pollutant emission caused by urban energy consumption. Applying the above-mentioned approaches into a case study on Beijing City, this paper analyzes the effect relationship among urban energy consumption structure improvement, energy economic efficiency increase and air quality change since the period when Beijing City officially proposed to bid for the 2008 Olympic Games in 1998. In addition, it further analyzes the effect and contribution of urban industrial activity level, industrial economic structure, industrial energy intensity, and industrial energy structure as well as emission coefficients on the change in industrial SO₂ emission, which can provide valuable information to the government for making comprehensive environmental policies, with the use of the logarithmic mean Divisia index (LMDI) method. It is shown that under the precondition that the industrial economy maintain a continuous and rapid increase, improvements in energy intensity and a decline in emission coefficients are the main means for reducing Beijing’s industrial SO₂ emissions.     

The total-factor energy productivity growth of China’s construction industry: evidence from the regional level

This study uses the total-factor energy productivity change index (TFEPCH) to investigate the changes in energy productivity of construction industry for 30 provincial regions in China from 2006 to 2015, adopting the improved Luenberger productivity index combined with the directional distance function. In addition to traditional economic output indicator, this study introduces building floor space under construction as a physical output indicator for energy productivity evaluation. The TFEPCH was decomposed into energy technical efficiency change and energy technical progress shift. Results indicate that, first, energy productivity of China’s construction industry decreased by 7.1% annually during 2006–2015. Energy technical regress, rather than energy technical efficiency, contributed most to the overall decline in energy productivity of China’s construction industry. Second, energy productivity in the central region of China decreased dramatically, by a cumulative sum of approximately 77.1%, since 2006, while energy productivity in the eastern and western regions decreased by over 54.3 and 65.3%, respectively. Only two of the 30 provinces considered—Hebei and Shandong—improved their energy productivity during 2006–2015. The findings presented here provide a basis for decision-making and references for administrative departments to set differentiated energy efficiency goals and develop relevant measures. Additionally, the findings are highly significant for energy and resource allocation of Chinese construction industry in different regions.     

京津冀主要大城市经济发展中城市化与大气环境质量的关系

京津冀城市群在快速城市化进程中,"高耗能、高污染、高排放"的粗放型经济发展模式带来了一系列大气污染问题,亟需协调经济发展与大气环境质量之间的关系.本文基于2004—2017年北京市、天津市、石家庄市的大气环境质量与城市化各指标数据,运用熵值法多维度研究了城市化进程中大气环境质量的演化规律.选取城市空气主要污染物SO2、...     

水资源资产价格模糊数学综合评价指标体系构建——以黑河中游张掖市为例

针对水资源本身的模糊性和不确定性,基于模糊数学综合评价模型,从水量、水质、人口、社会经济和生态环境5个方面选取18个评价指标,结合AHP法与熵权法确定指标权重,对张掖市2010-2014年的水资源价格进行动态评价,水价计算模糊数学模型由水资源价值评价和水资源价格计算两部分组成.结果表明：采用水资源价值模糊综合指数对水资源价值进行测算,5 a间张掖市水资源模糊综合指数介于水资源价值指数的“中等”与“偏低”之间,说明张掖市水资源价值属于中等偏低;在2010-2014年5 a间水资源价格呈明显上升趋势,核算期初的2010年为2.12元·m^-3,证实了张掖市目前水资源价格偏低,水资源资产价格存在较大的上升空间,而核算期末的2014年最高达4.96元·m^-3.基于熵权与AHP相结合确定权重的水资源价格模糊数学综合评价模型,评价结果更客观合理,为下一步水资产负债表编制中水资产与负债价值核算提供数据支持.