•11% of Chinese cities achieved strong decoupling of GDP from CO2 from 2005 to 2015•65.6% of the cities achieved weak decoupling•A city-level inverted-U relationship (or EKC) between CO2 and GDP is weakly confirmed•Decline in emission intensity via efficiency gains is vital to achieving decoupling Cities contribute to over 80% of global gross domestic product (GDP) and account for at least 75% of global CO2 emissions. As such, they are well placed to lead climate change mitigation efforts. Decoupling economic growth from emissions is key to low-carbon development, particularly in fast-growing countries, such as China. In this work, we estimated CO2 emissions for 294 Chinese cities and examined the extent to which economic development is decoupled from emissions. Results show that 11% of the cities have negative emission growth between 2005 and 2015, whereas their economy continued to grow (i.e., strong decoupling). A total of 65.6% of cities exhibit slower growth of emissions than economic growth (i.e., weak decoupling). We find that decline in emission intensity via improvement in production and energy use efficiency is the most important driver that leads to a decoupled economy. Other developing economies could learn from China's experience in emission-GDP decoupling to design their own low-carbon development pathways. Cities, contributing more than 75% of global carbon emissions, are at the heart of climate change mitigation. Given cities' heterogeneity, they need specific low-carbon roadmaps instead of one-size-fits-all approaches. Here, we present the most detailed and up-to-date accounts of CO2 emissions for 294 cities in China and examine the extent to which their economic growth was decoupled from emissions. Results show that from 2005 to 2015, only 11% of cities exhibited strong decoupling, whereas 65.6% showed weak decoupling, and 23.4% showed no decoupling. We attribute the economic-emission decoupling in cities to several socioeconomic factors (i.e., structure and size of the economy, emission intensity, and population size) and find that the decline in emission intensity via improvement in production and carbon efficiency (e.g., decarbonizing the energy mix via building a renewable energy system) is the most important one. The experience and status quo of carbon emissions and emission-GDP (gross domestic product) decoupling in Chinese cities may have implications for other developing economies to design low-carbon development pathways. Cities, contributing more than 75% of global carbon emissions, are at the heart of climate change mitigation. Given cities' heterogeneity, they need specific low-carbon roadmaps instead of one-size-fits-all approaches. Here, we present the most detailed and up-to-date accounts of CO2 emissions for 294 cities in China and examine the extent to which their economic growth was decoupled from emissions. Results show that from 2005 to 2015, only 11% of cities exhibited strong decoupling, whereas 65.6% showed weak decoupling, and 23.4% showed no decoupling. We attribute the economic-emission decoupling in cities to several socioeconomic factors (i.e., structure and size of the economy, emission intensity, and population size) and find that the decline in emission intensity via improvement in production and carbon efficiency (e.g., decarbonizing the energy mix via building a renewable energy system) is the most important one. The experience and status quo of carbon emissions and emission-GDP (gross domestic product) decoupling in Chinese cities may have implications for other developing economies to design low-carbon development pathways. With the accelerating climate emergency, decision makers need specific sub-national information on sources of carbon emissions, reduction potentials, and effectiveness of mitigation measures. Cities are emissions and development hotspots given that urban economic activity accounts for 80% of global gross domestic product (GDP), 60%–80% of energy consumption, and 75% of carbon emissions.1C40 CitiesA global opportunity for cities to lead.https://www.c40.org/why_citiesGoogle Scholar, 2World BankUrban development.https://www.worldbank.org/en/topic/urbandevelopment/overviewDate: 2019Google Scholar, 3UN Environment ProgrammeCities and climate change.https://www.unenvironment.org/explore-topics/resource-efficiency/what-we-do/cities/cities-and-climate-changeGoogle Scholar Most global population growth in the next couple of decades is estimated to take place in urban areas in developing countries.4Neiderud C.-J. How urbanization affects the epidemiology of emerging infectious diseases.Infect. Ecol. Epidemiol. 2015; 5: 27060Crossref PubMed Scopus (253) Google Scholar Given higher per capita emissions of urban populations due to higher income and urban lifestyles,5Feng K. Hubacek K. Carbon implications of China’s urbanization.Energ. Ecol. Environ. 2016; 1: 39-44Crossref Scopus (49) Google Scholar,6Yu B. Wei Y.-M. Kei G. Matsuoka Y. Future scenarios for energy consumption and carbon emissions due to demographic transitions in Chinese households.Nat. Energy. 2018; 3: 109-118Crossref Scopus (52) Google Scholar achieving low-carbon development in cities is of great significance to global climate change mitigation. A city's emission growth is usually closely coupled with its GDP;7Guan D. Meng J. Reiner D.M. Shan Y. Mi Z. Zhang N. Shao S. Liu Z. Zhang Q. Davis S.J. Structural decline in China's CO2 emissions through transitions in industry and energy systems.Nat. Geosci. 2018; 11: 551-555Crossref Scopus (215) Google Scholar however, some cities have shown a decoupling of GDP from emission growth (i.e., GDP growing faster than emissions).8Wang Q. Zhao M. Li R. Decoupling sectoral economic output from carbon emissions on city level: a comparative study of Beijing and Shanghai, China.J. Clean. Prod. 2019; 209: 126-133Crossref Scopus (65) Google Scholar At this moment, such decoupling is only examined in high-income cities in China, such as Beijing, Shanghai, Chongqing, and Guangzhou, as a result of data limitations.9Yu Y. Zhou L. Zhou W. Ren H. Kharrazi A. Ma T. Zhu B. Decoupling environmental pressure from economic growth on city level: the case study of Chongqing in China.Ecol. Indicat. 2017; 75: 27-35Crossref Scopus (67) Google Scholar,10Wang Q. Jiang R. Li R. Decoupling analysis of economic growth from water use in City: a case study of Beijing, Shanghai, and Guangzhou of China.Sustain. Cities Soc. 2018; 41: 86-94Crossref Scopus (49) Google Scholar Given that China is the largest emitter and one of the fastest growing countries in the world with numerous cities and huge regional heterogeneity in terms of economic development, size, and structure, the patterns of decoupling should be studied with as many cities as possible. Previous studies on the decoupling of emissions and economic growth in Chinese cities encountered several challenges and mainly focused on the accounting of emissions. First, most studies adopted a top-down approach that downscales national or provincial emissions to the city level by using socioeconomic indexes.11Shan Y. Guan D. Liu J. Mi Z. Liu Z. Liu J. Schroeder H. Cai B. Chen Y. Shao S. Methodology and applications of city level CO2 emission accounts in China.J. Clean. Prod. 2017; 161: 1215-1225Crossref Scopus (231) Google Scholar,12Moran D. Kanemoto K. Jiborn M. Wood R. Többen J. Seto K.C. Carbon footprints of 13,000 cities.Environ. Res. Lett. 2018; 13: 064041Crossref Scopus (149) Google Scholar The top-down approach assumes that cities have characteristics similar to those of their larger administrative unit at which data are available, assuming similar economic structure, energy mix, lifestyles, or climatic conditions.13Dhakal S. Urban energy use and carbon emissions from cities in China and policy implications.Energy Policy. 2009; 37: 4208-4219Crossref Scopus (588) Google Scholar These are strong assumptions potentially leading to inaccurate estimates of emissions. Second, most studies only calculated urban emissions for a particular time point rather than for a longer time span,14Ramaswami A. Tong K. Fang A. Lal R.M. Nagpure A.S. Li Y. Yu H. Jiang D. Russell A.G. Shi L. Urban cross-sector actions for carbon mitigation with local health co-benefits in China.Nat. Clim. Change. 2017; 7: 736Crossref Scopus (67) Google Scholar which makes it difficult to observe changes and understand underlying mechanisms. Third, existing accounts of emissions of cities use different methods, system boundaries, and data sources, making them incomparable with each other.15Creutzig F. Baiocchi G. Bierkandt R. Pichler P.-P. Seto K.C. Global typology of urban energy use and potentials for an urbanization mitigation wedge.Proc. Natl. Acad. Sci. U S A. 2015; 112: 6283-6288Crossref PubMed Scopus (270) Google Scholar This study overcomes these challenges by compiling an extensive emission dataset for 294 Chinese prefecture-level cities for the years 2005, 2010, and 2015. These cities covered 54.9% of China's territory and 94.4% of the population, and their GDP and emissions accounted for 99.4%16National Bureau of Statistics National data.https://data.stats.gov.cn/Date: 2020Google Scholar and 95.4%17European CommissionCO2 emissions of countries. Joint Research Centre/PBL Netherlands Environmental Assessment Agency, 2019https://edgar.jrc.ec.europa.eu/Google Scholar of the national values in 2015, respectively. We estimated the emissions by using a bottom-up approach that aggregates the emissions of all enterprises and industrial factories to the corresponding city. We calculated both scope 1 emissions from fossil fuel combustion and industrial processes and scope 2 emissions from net imports of electricity (see experimental procedures). We then examined the extent of decoupling of economic growth and CO2 emissions in each city with the Tapio decoupling index (DI)18Tapio P. Towards a theory of decoupling: degrees of decoupling in the EU and the case of road traffic in Finland between 1970 and 2001.Transport Pol. 2005; 12: 137-151Crossref Scopus (769) Google Scholar and compared the decoupling degree of cities with their economic development stage and structure. We then investigated and compared the drivers of emission change and the degree of decoupling for cities. Finally, we simulated four scenarios of different declines in emission intensity to show the potential decoupling of economic development and CO2 emissions in Chinese cities. Our study provides baselines and quantitative evidence for the reduction of emissions in Chinese cities with the degree of decoupling over time. Given that Chinese cities are at different phases of industrialization and urbanization from the east to the west of China, what Chinese cities are experiencing is informative for efforts to reduce emissions in other developing and transition economies and is thus of significance to global emission reduction. Scope 1 emissions of cities, shown in Figure 1, increased by 41.7% from 6,248 million metric tons (mt) in 2005 to 8,855 mt in 2010 and then by another 16.5% to 10,315 mt in 2015. Per capita emissions show similar trends. Average per capita emissions of 294 cities increased by 35.2% from 5.3 metric tons (t) in 2005 to 7.1 t in 2010 and by another 11.9% to 8.0 t in 2015. Despite the rapid growth of scope 1 emissions, emission intensities (emissions per unit of GDP) of cities show a downward trend over the same time period from 3.2 t per 1,000 yuan on average in 2005 to 2.5 in 2010 and then a further decline to 1.8 in 2015. The average emission intensity in 2015 was 44.2% lower than the 2005 level, indicating that China has fulfilled its commitments to the Paris Agreement of reducing its emission intensity by 40%–45% of the 2005 level by 2020 cahead of schedule, and before even signing the agreement. The decline in emission intensity implies that cities' GDP was growing faster than their emissions. The total GDP of cities was 19,410 billion yuan in 2005, 36,114 in 2010 (+86% from 2005, at a 2005 constant price level), and 57,390 in 2015 (+59% from 2010, in 2005 at a constant price level). City GDP grew twice as fast as emissions between 2005 and 2010 and 3.5 times as fast from 2010 to 2015. In terms of emission structure, secondary sectors (such as manufacturing, energy production and supply, and construction) were the most important source of scope 1 emissions by contributing from 78.3% (in 2015) to 83.3% (in 2010) of total emissions. There was an increasing trend of emissions in the tertiary sector (1.0% in 2005, 0.9% in 2010, and 2.8% in 2015) and transport (5.7% in 2005, 6.0% in 2010, and 7.3% in 2015), indicating an expansion of the service sectors and inter-city travel in China. Scope 2 emissions from imported electricity for cities are shown in Figure 2. A total of 188 cities were net importers of electricity in 2015 (shown in red), and the remaining 152 cities were net exporters (shown in blue). Total scope 2 emissions in net-importing cities almost doubled from 397 mt in 2005 to 779 mt in 2010 and further increased to 1,085 mt in 2015, which accounted for 13.5% in 2005, 13.2% in 2010, and 15.2% in 2015 of the cities' combined scope 1 and scope 2 emissions. Cities and their emissions show considerable regional heterogeneity, including differences in the degree of urbanization and size and structure of the economy.19Shan Y. Guan D. Hubacek K. Zheng B. Davis S.J. Jia L. Liu J. Liu Z. Fromer N. Mi Z. et al.City-level climate change mitigation in China.Sci. Adv. 2018; 4: eaaq0390Crossref PubMed Scopus (152) Google Scholar,20Feng K. Siu Y.L. Guan D. Hubacek K. Analyzing drivers of regional carbon dioxide emissions for China. A structural decomposition analysis.J. Ind. Ecol. 2012; 16: 600-611Crossref Scopus (181) Google Scholar Generally, richer cities have higher per capita emissions. The Spearman correlation coefficient between per capita GDP and per capita emissions was 0.584 at a significance level of 99%. The top 10% cities in terms of per capita GDP contributed 32.9% of the national GDP and emitted 18.8% of China's territorial emissions in 2015, while the bottom 10% cities contributed only 4.1% of the GDP and 4.3% of emissions. Average per capita emissions and emission intensity of the capital region (Beijing, Tianjin, Hebei, and Shandong) were 10.1 and 0.2 t per 1,000 yuan in 2015, and those of the Yangtze river delta (Shanghai, Jiangsu, and Zhejiang) were 9.6 and 1.2 t, respectively. Regions with an energy-intensive economic structure also had high emissions, such as Shanxi-Shaanxi-Inner Mongolia (16.6 t per capita and 0.42 t per 1,000 yuan in 2015). Shanxi-Shaanxi-Inner Mongolia contributed 68.9% (or 2.4 billion t) of China's total coal production in 2018,21Chinapower.comProvincial coal production in 2018.http://www.chinapower.com.cn/bigdataenterprise/20190218/1266172.htmlDate: 2019Google Scholar and coal mining was the largest part of its cities' industrial output (e.g., 80.8% of Yangquan city's GDP in 2015). Despite the fact that China has weakly decoupled its economic growth from carbon emissions at the national level (China’s DI was 0.55, indicating weak decoupling between 2005 and 2015), decoupling analysis at the city level is still lacking and may provide more important information on how the development of cities contributed to national decoupling trends. We calculated the DIs for each city over the period of 2005–2015.18Tapio P. Towards a theory of decoupling: degrees of decoupling in the EU and the case of road traffic in Finland between 1970 and 2001.Transport Pol. 2005; 12: 137-151Crossref Scopus (769) Google Scholar Cities are grouped into four categories with different degrees of decoupling: strong decoupling (DI < 0), weak decoupling (0 < DI < 0.8), coupling (0.8 < DI < 1.2), and negative decoupling (DI > 1.2) (see also Table S1 and the experimental procedures). We included 282 cities in the decoupling analysis dependent on the availability of consistent emissions and economic data for the period from 2005 to 2015. Figure 3A shows that a number of cities have strongly or weakly decoupled their economic growth from emissions from 2005 to 2015, accounting for 11.0% or 65.6% of all cities in China, respectively. If we separate the period of 2005–2015 into two (as shown in Figures 3B and 3C), we find that more cities achieved decoupling of economic growth and carbon emissions during 2010–2015 than during 2005–2010. Between 2005 and 2010, 46 (or 16.3%) cities had strongly decoupled, and the number increased to 79 (or 28.0%) between 2010 and 2015. The number of cities that showed a tight link between economic and emission growth decreased from 33 (or 11.7%) between 2005 and 2010 to 31 (or 11.0%) between 2010 and 2015, and the number of negatively decoupled cities declined from 68 (or 24.1%) to 51 (or 18.1%). Cities' DI values had a weak negative correlation with their per capita GDP in 2015 (with a correlation coefficient of −0.109 at a significance level of 10%) but a positive correlation with their per capita emissions (with a correlation coefficient of 0.117 at a significance level of 5%) and emission intensity (with a correlation coefficient of 0.214 at a significance level of 1%), indicating that cities with a higher degree of decoupling tend to have higher per capita GDP but lower per capita emissions and emission intensity. For example, the average per capita GDP of strongly decoupled cities in 2015 was 52,200 yuan, whereas the average per capita GDP of weakly decoupled, coupled, and negatively decoupled cities was 47,2000, 40,200, and 24,300 yuan, respectively. Meanwhile, the average per capita CO2 of strongly decoupled, weakly decoupled, coupled, and negatively decoupled cities was 6.0, 7.7, 10.1, and 8.4 t, respectively. Thus, rich cities tend to be more likely to achieve decoupling of economic growth and emissions. This finding is in line with the environmental Kuznets curve (EKC) hypothesis that assumes that per capita emissions of an economy will first increase and then decrease with increasing growth of per capita GDP.22Stern D.I. Common M.S. Barbier E.B. Economic growth and environmental degradation: the environmental Kuznets curve and sustainable development.World Dev. 1996; 24: 1151-1160Crossref Scopus (945) Google Scholar, 23Dinda S. Environmental Kuznets curve hypothesis: a survey.Ecol. Econ. 2004; 49: 431-455Crossref Scopus (1930) Google Scholar, 24Wang H. Lu X. Deng Y. Sun Y. Nielsen C.P. Liu Y. Zhu G. Bu M. Bi J. McElroy M.B. China’s CO2 peak before 2030 implied from characteristics and growth of cities.Nat. Sustain. 2019; 2: 748-754Crossref Scopus (106) Google Scholar Our empirical result weakly confirms such an “inverted-U curve” relationship for Chinese cities, as shown in Figure 4 (see the experimental procedures for more details). There is little correlation between cities' degree of decoupling and their economic structure. We grouped the cities into five categories characterized by their dominating economic sector (i.e., industry with the largest share of GDP): energy production, heavy manufacturing, light manufacturing, high-tech manufacturing, and service sectors.19Shan Y. Guan D. Hubacek K. Zheng B. Davis S.J. Jia L. Liu J. Liu Z. Fromer N. Mi Z. et al.City-level climate change mitigation in China.Sci. Adv. 2018; 4: eaaq0390Crossref PubMed Scopus (152) Google Scholar A statistical test of group means (t test results displayed in Table S2) indicates that, apart from cities dominated by the service economy (which have a relatively higher extent of decoupling), there is no significant difference in the average degree of decoupling of cities dominated by energy production, heavy manufacturing, light manufacturing, and high-tech industry, respectively. The message is that cities could achieve decoupled economic growth from emissions with any economic structure, even for cities dominated by the extraction of highly polluting natural resources. Thus, it is not necessary for every city to pursue service-oriented structural transformation. Moreover, there is the real danger that mitigation based on outsourcing of polluting industries (potentially to places with less-efficient technologies and less-stringent environmental policies) can lead to a backfire effect with overall increasing emissions at the national level.25Fang D. Chen B. Hubacek K. Ni R. Chen L. Feng K. Lin J. Clean air for some: unintended spillover effects of regional air pollution policies.Sci. Adv. 2019; 5: eaav4707Crossref PubMed Scopus (86) Google Scholar We decompose each city's CO2 emissions into four factors (economic structure, emission intensity, per capita GDP, and population) to quantify the effects of economic restructuring, improvement of carbon efficiency (i.e., productivity and energy mix), economic growth, and population growth on a city's emissions as well as its extent of decoupling. Figure 5 shows the average contributing effects of the drivers in four city categories. Detailed results of each city are presented in Tables S3–S8. While decline in emission intensity (improvement in production and energy use efficiency) was shown to be the most important driver for carbon emission reduction, it should be pointed out that economic growth could lead to increased emissions and counteract decoupling efforts. That is, between 2005 and 2015, for cities that experienced strong decoupling, the reduction in emissions led by efficiency improvement could still surpass the emission surge due to economic growth. However, for weakly decoupling cities, the increase in carbon efficiency only offset 76.2% of emission growth in the presence of economic growth. Economic restructuring toward less energy-intensive manufacturing could reduce emissions and DI, but its reduction effect was far smaller than improvement in efficiency. For example, the share of manufacturing in strongly decoupled cities declined from 2010 to 2015 and thus decreased emissions by 26.2% and DI by 0.20. Furthermore, the effects of economic restructuring relied heavily on the development stage of cities. For example, the share of manufacturing in negatively decoupled cities kept increasing from 2005 to 2015, leading to increases in cities' emissions and DI. One of the possible reasons could be that strongly decoupled and high-income cities substantially developed their service sectors and outsourced their manufacturing sectors to less-developed regions. As a result, less-developed cities were still developing their manufacturing sectors and their emissions and economic growth were still coupled, or even negatively decoupled. Therefore, the effectiveness of emission reduction via economic restructuring and relocation is limited from a national perspective. Different contributions of drivers have been found in cities with similar economic structure. We take Jincheng in Shanxi and Shuangyashan in Heilongjiang as examples because both of them have coal mining as their dominating industry. The emission intensity of Jincheng decreased from 5.6 t per 1,000 yuan in 2010 to 2.6 t in 2015, having a negative effect (−1.29) on the city's DI, offsetting the increase from economic growth (0.65). As a result, Jincheng's total emissions decreased from 32 mt in 2010 to 22 mt in 2015, while its GDP kept growing from 56.7 to 85.3 billion yuan over the same period. Jincheng’s DI value from 2010 to 2015 was −0.62 (strongly decoupled). Meanwhile, the effect of a decline in emission intensity on DI (−0.18) in Shuangyashan was not sufficient to offset the increase from economic growth (1.23) over the period of 2010–2015. As a result, Shuangyashan's DI from 2010 to 2015 was 0.81 (coupling), and its emissions increased by 9.8% while its GDP increased by 11.9%. Therefore, we suggest that reducing cities' emission intensity to achieve decoupling of economic growth and emissions is an effective and feasible way to realize a low-carbon development. Our scenarios show that an additional 3.2%, 6.7%, 9.6%, and 11.3% of cities could have achieved strong decoupling over the period of 2005–2015, if their emission intensities in 2015 decreased by 5%, 10%, 15%, and 20%, respectively. Meanwhile, the number of coupled cities and negatively decoupled cities will decrease from 29 (or 10.3%) to 16 (or 5.7%) and from 37 (13.1%) to 23 (8.2%) under the strongest scenario, respectively (as shown in Figure 6 and Table S9). This study presents internally consistent CO2 emission inventories for 294 Chinese cities for the years 2005, 2010, and 2015. We include scope 1 emissions from fossil fuel consumption and industrial processes and scope 2 emissions from imported electricity consumption. Our accounts show that, while total emissions and per capita emissions increased in most of the cities, their growth significantly slowed down after 2010. We weakly confirm an inverted-U curve relationship (or EKC) between emissions and GDP (i.e., per capita emissions first increase then decrease with the growth of per capita GDP). A total of 84% of the cities experienced a decrease in emission intensity, which fulfilled the country's conservative commitment to the Paris Agreement by reducing emission intensity ahead of schedule. Analysis of the decoupling of emissions and GDP shows that 11.0% (or 31) of the cities have achieved strongly decoupled economic growth from emissions from 2005 to 2015, exhibiting an absolute decline in emissions along with an increase in GDP. Almost two-thirds (or 65.6% and 185) of cities have achieved weak decoupling with emission growth being smaller than their GDP growth. Although there was slow emission growth or even an emission decline in decoupled cities, they kept adding CO2 to the atmospheric and increasing CO2 concentration. Ultimately, we need to keep reducing emissions and reach net zero CO2 emissions globally around 2050 to meet the goal of 1.5°C warming.26Rogelj J. Shindell D. Jiang K. Fifita S. Forster P. Ginzburg V. Handa C. Kheshgi H. Kobayashi S. Kriegler E. et al.Mitigation pathways compatible with 1.5°C in the context of sustainable development..in: Masson-Delmotte V. Zha P. Pörtner H.-O. Roberts D. Skea J. Shukla P.R. Pirani A. Moufouma-Okia W. Péan C. Pidcock R. Global Warming of 1.5°C. Intergovernmental Panel on Climate Change, 2018: 93-174Google Scholar Our analysis finds that economic transformation toward service sectors and less energy-intensive manufacturing has limited effects on emission reduction. Cities could achieve decoupled economic growth from emissions with any economic structure, even in highly polluting resource-dominated cities or low-income cities. Thus, it is not necessary for every city to pursue service-oriented structural transformation. Meanwhile, emission intensity reduction via improvement in production and energy use efficiency has been identified as the most important driver and is even able to offset the increase in emissions from economic growth in strongly decoupled cities. Our scenarios show that up to 243 (or 86.2%) of cities could have achieved strong or weak decoupling from 2005 to 2015, if their emission intensity by 2015 had declined by 20%, ceteris paribus. One effective approach to reduce emission intensity is to build a renewable energy-based system. In the past decade, the supply of renewable energy has quickly increased in China. Total consumption of hydropower and wind power and the non-renewable but low-carbon intensive nuclear power quickly increased from 107 mt of standard coal equivalent (or 7.3% of total energy consumption) in 2000 to 744 mt (or 15.3% of total energy consumption) in 2019. Meanwhile, the consumption of coal peaked in 2013 at 2,810 mt, and the proportion of coal consumption to total consumption of energy decreased substantially from 70.2% in 2011 to 27.7% in 2019, although coal still dominates electricity supply. Such a quick replacement of coal with other forms of energy, including renewables, has led to a peak of China's overall emissions in 2013.7Guan D. Meng J. Reiner D.M. Shan Y. Mi Z. Zhang N. Shao S. Liu Z. Zhang Q. Davis S.J. Structural decline in China's CO2 emissions through transitions in industry and energy systems.Nat. Geosci. 2018; 11: 551-555Crossref Scopus (215) Google Scholar For an example at the local level, Shenzhen has taken great efforts to develop its renewable energy system. Shenzhen is one of the first low-carbon pilot cities for low-carbon development in China and has successfully replaced most of its coal power infrastructure with cleaner energy systems (such as natural gas, solar power, wind power, nuclear power, and biomass energy).27Zhou Y. Shan Y. Liu G. Guan D. Emissions and low-carbon development in Guangdong-Hong Kong-Macao Greater Bay Area cities and their surroundings.Appl. Energy. 2018; 228: 1683-1692Crossref Scopus (76) Google Scholar Benefiting from a series of initiatives, Shenzhen has achieved a strong decoupling of economic growth and emissions between 2010 and 2015, and its overall emission intensity in 2015 was 0.2 t per 1,000 yuan, which is ranked as the fourth lowest in China. Given the abundance and the low price of coal, many developing countries, including China, still use coal as their primary energy resource. In this regard, so-called “clean” coal technologies are seen as a potential solution to reducing carbon emissions,28Chang S. Zhuo J. Meng S. Qin S. Yao Q. Clean coal technologies in China: current status and future perspectives.Engineering. 2016; 2: 447-459Crossref Scopus (136) Google Scholar and the government needs to invest more in such technologies and promote their applications to high-coal-consuming industries.29Tang X. Snowden S. McLellan B.C. Höök M. Clean coal use in China: challenges and policy implications.Energy Policy. 2015; 87: 517-523Crossref Scopus (62) Google Scholar Carbon capture and storage (CCS) could be an effective approach to mitigate carbon emissions, bu