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Abstract Cities are the major contributors to energy consumption and CO2 emissions, as well as being leading innovators and implementers of policy measures in climate change mitigation. Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is an agglomeration of cities put forward by China to strengthen international cooperation among “Belt and Road” countries and promote low-carbon, inclusive, coordinated and sustainable development. Few studies have discussed the emission characteristics of GBA cities. This study, for the first time, compiles emission inventories of 11 GBA cities and their surroundings based on IPCC territorial emission accounting approach, which are consistent and comparable with the national and provincial inventories. Results show that (a) total emissions increased from 426 Mt in 2000 to 610 Mt in 2016, while emissions of GBA cities increased rapidly by 6.9% over 2000–2011 and peaked in 2014 (334 Mt); (b) raw coal and diesel oil are the top two emitters by energy type, while energy production sector and tertiary industry are the top two largest sectors; (c) GBA cities take the lead in low-carbon development, emitted 4% of total national emissions and contributed 13% of national GDP with less than a third of national emission intensities and less than three-quarters of national per capita emissions; (d) Macao, Shenzhen and Hong Kong have the top three lowest emission intensity in the country; (e) most of GBA cities are experiencing the shift from an industrial economy to a service economy, while Hong Kong, Shenzhen, Foshan and Huizhou reached their peak emissions and Guangzhou, Dongguan and Jiangmen remained decreasing emission tendencies; (g) for those coal-dominate or energy-production cities (i.e. Zhuhai, Zhongshan, Zhaoqing, Maoming, Yangjiang, Shanwei, Shaoguan and Zhanjiang) in mid-term industrialization, total emissions experienced soaring increases. The emission inventories provide robust, self-consistent, transparent and comparable data support for identifying spatial–temporal emission characteristics, developing low-carbon policies, monitoring mitigation progress in GBA cities as well as further emissions-related studies at a city-level. The low-carbon roadmaps designed for GBA cities and their surroundings also provide a benchmark for other developing countries/cities to adapting changing climate and achieve sustainable development.

The UN Sustainable Development Goals (SDGs) and the Paris Agreement have ushered in a new era of policymaking to deliver on the formulated goals. Energy policies are key to ensuring universal access to affordable, reliable, sustainable, and modern energy (SDG7). Yet they can also have considerable impact on other goals. To successfully achieve multiple goals concurrently, policies need to balance different objectives and manage their interactions. Refining previously contemplated design principles, we identify three key principles - complementary, transparency and adaptability - as highly pertinent for multiple-objective energy policies based on a synthesis of seventeen coordinated policy case studies. First, policies should entail complementary measures and design provisions that specifically target non-energy objectives (complementarity). Second, policy impacts should be tracked comprehensively in both energy and non-energy domains to uncover diminishing returns and facilitate policy learning (transparency). Third, policies should be capable of adapting to changing objectives over time (adaptability). These principles are rarely considered in current policies, implying the need to mainstream them into the next generation of policymaking by pointing to best practices and new tools.

AbstractIn the wake of the Fukushima nuclear disaster, Japan largely moved away from nuclear power generation and turned back towards an energy sector dominated by fossil fuels. As a result, the pace towards reaching emission reduction targets has largely slowed down. This situation indicates that higher emissions will continue to be generated if there is no appropriate and efficient measurement implemented to bridge the energy demand gap. To contribute adequate mitigation policies, a detailed inventory of both CO2 emissions and socioeconomic factors, both at the national and regional level, should be issued. Thereby, this work contributes to a time-series emission with a record of 47 prefectures in Japan as well as their associated socioeconomic features. The compiled emission inventory is based on three major fossil fuels and 26 sectors with careful emission allocations for regional electricity generation. This dataset is uniformly formatted and can be expected to provide vital information to set regional reduction allowances and sectoral reduction priorities.

Recycling, renewables and a reinvigorated domestic energy market will allow China to lead the world in low-carbon development, say Zhu Liu and colleagues.

China committed itself to reduce the carbon intensity of its economy (the amount of CO2 emitted per unit of GDP) by 40-45% during 2005-2020. Yet, between 2002 and 2009, China experienced a 3% increase in carbon intensity, though trends differed greatly among its 30 provinces. Decomposition analysis shows that sectoral effciency gains in nearly all provinces were offset by movement towards a more carbon-intensive economic structure. Such a sectoral shift seemed to be heavily affected by the growing role of investments and capital accumulation in China's growth process which has favoured sectors with high carbon intensity. Panel data regressions show that changes in carbon intensity were smallest in sectors dominating the regional economy (so as not to endanger these large sectors, which are the mainstay of the provincial economy), whereas scale and convergence effects played a much smaller role.

The increasingly high frequency of heavy air pollution in most regions of China signals the urgent need for the transition to an environmentally friendly production performance by socioeconomic sectors for the sake of people's health and sustainable development. Focusing on CO2 and major air pollutants, this paper presents a comprehensive environmental efficiency index based on evaluating the environmental efficiency of major socioeconomic sectors, including agriculture, power, industry, residential and transportation, at the province level in China in 2010 based on a slack-based measure DEA model with non-separable bad output and weights determined by the coefficient of variation method. In terms of the environment, 5, 16, 6, 7 and 4 provinces operated along the production frontier for the agricultural, power, industrial, residential and transportation sectors, respectively, in China in 2010, whereas Shanxi, Heilongjiang, Ningxia, Hubei and Yunnan showed lowest efficiency correspondingly. The comprehensive environmental efficiency index varied from 0.3863 to 0.9261 for 30 provinces in China, with a nationwide average of 0.6383 in 2010; Shanghai ranked at the top, and Shanxi was last. Regional disparities in environmental efficiency were identified. A more detailed inefficiency decomposition and benchmarking analysis provided insight for understanding the source of comprehensive environmental inefficiency and, more specifically, the reduction potential for CO2 and air pollutants. Some specific research and policy implications were uncovered from this work.

As part of the Paris Agreement, China pledged to peak its CO2 emissions by 2030. In retrospect, the commitment may have been fulfilled as it was being made: China’s emissions peaked in 2013 at a level of 9.53 Gigatons of CO2, and declined in each year from 2014 to 2016. However, the prospect for maintenance of the continued reductions depend the relative contributions of different changes in China. Here we quantitatively evaluate the drivers of the peak and decline of China’s CO2 emissions between 2007 and 2016 using the latest available energy, economic, and industry data. We find that slowing economic growth in China has it easier to reduce emissions. Nevertheless, the decline is largely associated with changes in industrial structure and a decline in the share of coal used for energy. Decreasing energy intensity (energy per unit GDP) and emissions intensity (emissions per unit energy) also contributed to the decline. Based on an econometric (cumulative sum) test, we confirm that there is a clear structural break in China’s emission pattern from 2015. We conclude that the decline of Chinese emissions is structural and is likely to be sustained if the nascent industrial and energy system transitions continue.