Suchergebnisse

The coronavirus pandemic has severely affected our daily lives, with direct consequences on passenger transport. This in turn has strongly impacted the energy demand of the transport sector and associated CO 2 emissions. We analyse near real-time passenger mobility and related emission trends in Europe between 21 January and 21 September 2020. We compiled a dataset of country-, sector- and lockdown- specific values, representing daily activity changes in private, public, and active passenger transport. In the aggregate, surface passenger transport emissions fell by 11.2% corresponding to 40.3 MtCO 2 in Europe. This decline was predominantly due to the reduction of private passenger transport in five European countries (France, Germany, Italy, Spain, and the UK). During the first lockdown in April 2020, CO 2 emissions from surface passenger transport declined by 50% in Europe, resulting in a 7.1% reduction in total CO 2 emissions. After April 2020, private passenger travel recovered rapidly, while public passenger flows remained low. Solely prompted by the private sector, a rebound in total emissions and surface passenger transport emissions of 1.5% and 10.7%, respectively, was estimated at the end of the study period. The resulting situation of increased private and decreased public passenger transport is in contradiction to major climate goals, and without reversing these trends, emission reductions, as stated in the European Green Deal are unlikely to be achieved. Our study provides an analysis based on a detailed and timely set of data of surface passenger transport and points to options to grasp the momentum for innovative changes in passenger mobility.

China has the largest number of industrial parks in the world. These parks are not only crucial for the country to accelerate industrialization but also to achieve its climate change targets. Constructing CO2 emission inventories for industrial parks is the first step in analysing the park's emission patterns and designing low-carbon policies. However, most of the previous emission accounts for industrial parks adopted various scopes and methodologies, making them incomparable with each other. This study develops a self-consistent methodology and framework for China's industrial parks based on enterprise-level data. We consider both Scope 1 and 2 emissions and construct the inventories by 19 energy types and 39 industrial sectors, which are consistent with the existing national, provincial, and city-level emission inventories. Such sectoral-based emission inventories will be not only able to provide data support for the design of emission/energy control policies, but also help the central/local governments evaluate a park's emission reduction performance. Finally, an empirical study is applied to four industrial parks to verify the method. In addition, we review the eco-industrial park programmes in Japan and South Korea, as well as their emissions accounting framework. We find that most of the Japanese industrial parks provide Scope 1, 2 and 3 emissions, while for South Korea, parks mostly focus on Scope 1 emissions. The discussion of Japan and South Korea's eco-industrial parks have referential significance for the construction China's low-carbon parks.

China has the largest number of industrial parks in the world. These parks are not only crucial for the country to accelerate industrialization but also to achieve its climate change targets. Constructing CO 2 emission inventories for industrial parks is the first step in analysing the park's emission patterns and designing low-carbon policies. However, most of the previous emission accounts for industrial parks adopted various scopes and methodologies, making them incomparable with each other. This study develops a self-consistent methodology and framework for China's industrial parks based on enterprise-level data. We consider both Scope 1 and 2 emissions and construct the inventories by 19 energy types and 39 industrial sectors, which are consistent with the existing national, provincial, and city-level emission inventories. Such sectoral-based emission inventories will be not only able to provide data support for the design of emission/energy control policies, but also help the central/local governments evaluate a park's emission reduction performance. Finally, an empirical study is applied to four industrial parks to verify the method. In addition, we review the eco-industrial park programmes in Japan and South Korea, as well as their emissions accounting framework. We find that most of the Japanese industrial parks provide Scope 1, 2 and 3 emissions, while for South Korea, parks mostly focus on Scope 1 emissions. The discussion of Japan and South Korea's eco-industrial parks have referential significance for the construction China's low-carbon parks.

The COVID-19 pandemic has created significant challenges for energy transition. Concerns about the overwhelming emphasis on economic recovery at the cost of energy transition progress have been raised worldwide. More voices are calling for "green" recovery scheme, which recovers the economy while not compromising on the environment. However, limited academic attention has been paid to comprehensively investigating the implications of COVID-19 for global energy transition. This study thus provides a comprehensive analysis of the dynamics between energy transition and COVID-19 around the world and proposes a low-carbon energy transition roadmap in the post-pandemic era. Using energy data from the International Energy Agency (IEA), we first summarized and reviewed the progress of energy transition prior to COVID-19. Building on prior progress, we identified the challenges for energy transition during the pandemic from the perspectives of government support, fossil fuel divestment, renewable energy production capacity, global supply chain, and energy poverty. However, the pandemic also generates opportunities for global energy transition. We hence also identified potential opportunities for energy transition presented by the pandemic from the perspectives of price competitiveness, policy implementation efficiency, and renewable energy strengths. We further provided an in-depth discussion on the impact of current worldwide economic recovery stimulus on energy transition. Based on the identified challenges and opportunities, we proposed the post-pandemic energy transition roadmap in terms of broadening green financing instruments, strengthening international cooperation, and enhancing green recovery plans. Our study sheds light on a global low-carbon energy transition framework and has practical implications for green recovery schemes in post-pandemic times.

In an effort to address climate change, in 2013 China launched the world's largest government-driven carbon emission reduction programme, the National Low Carbon Industrial Parks Pilot Programme (LCIPPP). This paper analyses this newly developed pilot program. To deepen our understanding of the causes and the impact of industrial park CO2 emissions, we use the STIRPAT (Stochastic Impacts by Regression on Population, Affluence and Technology) model and data from 20 pilot industrial parks involved in the LCIPPP for the period 2012–2016. This study quantitatively evaluates the effect of CO2 emissions on output, energy structure, energy intensity, industrial structure, R&D intensity, and population change in different regions and nationally through an elasticity coefficient method. The results confirm that an increase in output and energy intensity is a dominant contributor to the growth of CO2 emissions whereas an increase of the share of tertiary industry and R&D intensity has significant effects on reducing CO2 emissions. The elasticity of energy intensity and renewable energy consumption on CO2 emissions in the eastern region of China is the highest, indicating that using renewable energy to reduce CO2 emissions for the industrial parks is more effective in the eastern region as compared to the central and western regions of the country. The elasticity of population is significantly negative in both the central and western areas while it is positive in eastern part of China, thereby illustrating that promoting labour intensive industries will be an effective way to reduce CO2 emissions for the industrial parks in China's central and western regions. Our study reveals that differentiated low carbon development pathways should be adopted. Concrete policy implications for reducing CO2 emissions are also provided.

The ten countries that joined the European Union (EU) in 2004 (Cyprus, Czechia, Estonia, Hungary, Lithuania, Latvia, Malta, Poland, Slovakia, and Slovenia) have experienced faster economic growth and slower declines in energy consumption than traditional EU members. As designing of low-carbon policies requires accurate CO 2 emission accounting, this study describes the evolving trajectories of CO 2 emissions from 2005 to 2017 of 2004 EU accession members by providing detailed emission inventories by 28 types of energy and 47 socioeconomic sectors. We further quantify the contributions of four socioeconomic drivers (i.e., economic growth, energy structure, carbon intensity, and energy intensity) to the emission changes. The results show that the total CO 2 emissions of the ten countries decreased by 7.50% from 2010 (506.81 Mt) to 2016 (468.78 Mt), which is lower than the average decline rate of other EU members (10.52%). Although the effect of economic growth contributed the most to emission increase (15.44%), it is completely offset by the decline in carbon intensity (-18.82%). We also discuss potential roadmaps towards carbon neutrality by designing 33 scenarios based on the European Union Low-Carbon Development Map 2050. We find that carbon neutrality cannot be achieved unless the share of renewable energy sources reaches 60% and more than half of existing coal and gas power plants are upgraded to Carbon Capture Storage (CCS) technology. These changes require the implementation of both short-term and long-term strategies.

For decades, resource-based cities in China have significantly contributed to China's socio-economic development. The heavy resource dependence of resource-based cities inevitably leads to a series of environmental problems. Mitigating environmental impacts in an unthinking manner might be disruptive for economic development. Improving eco-efficiency has been a crucial solution for protecting the environment while mitigating its negative economic impact. However, the method commonly used to evaluate the eco-efficiency – that is, the black-box data envelopment analysis (DEA) – cannot examine the inefficiencies of the internal structure, and as a result, the underlying management defects are unclear. To open the black box, this study presents a two-stage network DEA framework incorporating government and industrial sectors and measures the eco-efficiency of 84 resource-based cities during the post-financial crisis period (2007–2015). The results indicate that the average eco-efficiency of China's resource-based cities shows a promising increase, and there is a positive relationship between governance efficiency and production efficiency. The decreasing trend of governance efficiency in the Central, Western, and Northeast regions after 2014 shows the low quality of the government sector in the usage of fiscal income. Proactive disclosure of how the government sector conducts public business and spends taxpayers' money should be made to increase transparency, attract more entrepreneurial resources to carry out production activities, and further improve sustainability. The two-stage network DEA framework helps obtain more insights into the internal management defects of the government and industrial sectors and enhance their cooperation to improve the eco-efficiency precisely.

To put the brakes on global climate change, China, the world's top emitter, has established ambitious CO 2 emissions reduction targets. Industry-level emissions analysis can help policymakers determine better ways to achieve mitigation targets. This study is the first to target the total-factor carbon emission performance (TCPI) of secondary and service industries. We first compile industry-level CO 2 emission inventories of 25 Yangtze River Delta cities during 2007–2016. The TCPI of secondary and service industries is then estimated by the non-radial directional distance function. We then compare the TCPI of the two industries across levels, dynamics, and inequalities using a global metafrontier approach. The results show the TCPI of the service industry (0.563 in 2016) was significantly higher than that of secondary industry (0.256 in 2016), suggesting that the service industry was more carbon-friendly. The TCPI gap between the secondary and service industries narrowed over the study period. The TCPI of secondary industry showed a promising increase during 2007–2016 with an annual growth rate of 2.30%, reflecting the positive effects of the government's reforms and environmental regulations. By contrast, the service industry saw a downward trend in TCPI, decreasing by 1.68% annually, primarily because it is a newcomer to low-carbon development. TCPI inequality in secondary industry was much larger than in the service industry, suggesting that significant heterogeneity exists in secondary industry. Therefore, policymakers should implement targeted mitigation policies for secondary industry, and place decarbonising the service industry on the agenda to reverse its decreasing TCPI.

AbstractEmerging countries are at the frontier of climate change actions, and carbon emissions accounting provides a quantifiable measure of the environmental impact of economic activities, which allows for comparisons of emissions across different entities. However, currently there is no study covering detailed emissions inventories for emerging countries in Central Asian. This paper compiles detailed and accurate carbon emissions inventories in several Central Asian countries (i.e., Kazakhstan, Kyrgyzstan, Pakistan, Palestine, Tajikistan, and Uzbekistan) during the period 2010–2020. Using the IPCC administrative territorial approach, we for the first time compile their emissions inventories in 47 economic sectors and five energy categories. Moreover, we also investigate decoupling status based on Tapio decoupling model and examine emissions driving factors based on the index decomposition analysis method. The primary results illustrate that carbon emissions in Central Asian countries are increasing with huge differences. Decoupling results highlight that most of the sample countries still need more effort to decouple the economy and emissions except that Pakistan achieves an ideal strong decoupling state. The results of the decomposition indicate that the economy and population both raise emissions, while energy intensity and carbon intensity are negative drivers in some countries. We propose practical policy implications for decarbonization and energy transition roadmap in Central Asian countries.