Our inventories cataloged GHG emissions by eight urban sectors: residential and institutional buildings; commercial buildings; industrial buildings (energy use); industrial process and fugitive emissions; on-road transportation (e.g., cars, buses); railways, aviation, and waterway; waste disposal (wastewater treatment, landfills); and other (agriculture, mining). Both territorial emissions within urban geographical boundaries and those related to imported electricity were included in these inventories. When emission data of some cities are available at different data sources, the inventory data from C40 Cities were selected to maximize data consistency and avoid mismatches of statistical calibers. Because of the scarcity of emission data at sector scale, some cities may have missing data for certain sectors (for example, waste-related emission data was not available for Amsterdam and other emission (agriculture, mining) data was not available for Los Angeles).

We selected the 42 out of the 167 cities that had GHG emission inventories for at least 2 years to analyze the progresses of GHG emission reduction in cities. The basic information and study periods of these cities are shown in Table A1. If cities had inventories for more than 2 years, we prioritized the use of data within the same source. Additionally, we tend to maximize the timespan by using the first year and last year data that were available to facilitate a more meaningful comparison. If an urban region only had 2 years of inventories with different data sources, we first determine whether their emission boundaries are consistent by comparing their urban land areas in respective data sources. If they are consistent, we confirm the GHG emission data of the city is comparable and could be selected.

Our survey showed that 113 out of the 167 cities have set clear and traceable carbon reduction targets. The target information was extracted on the basis of the following aspects: general city information (name, location, and boundaries), target details (reduction target types and magnitude, baseline year, and the latest update date), and supporting data (i.e., population). The near-term (2020s), mid-term (2030s), and long-term (2040s−2050) climate targets were identified for each city. They are further classified by absolute emission reduction targets, intensity targets, and baseline scenario targets to discuss their climate relevance and appropriateness from a global perspective.

The total and per capita GHG emissions of the 167 cities are mapped in Figure 1. As shown in Figure 1a, the total GHG emissions ranged between 3.5 kt CO₂-eq and 199.7 Mt CO₂-eq. The top 25 (15%) of the 167 cities accounted for 52% of the total GHG emissions, which are mainly from Asian and European countries [such as China (Handan, Shanghai, and Suzhou) and Japan (Tokyo), Russia (Moscow) and Turkey (Istanbul)]. As suggested by Moran et al. (2018), concerted actions implemented by a small number of local governments could have remarkable impacts on global emissions reduction. In general, both developed and developing countries have cities with high total GHG emissions, and some cities in developed countries still generated a great deal of emissions (such as cities in Japan, the USA, Korea, Germany, and Singapore) in the study period. This could raise equity concerns, since major cities have generated the biggest share of GHG emissions, but the consequences of climate change (such as extreme weathers, wide fires, and biodiversity loss) are borne by the whole world, and the poorer regions are possibly more vulnerable to these consequences (Morgan and Waskow, 2014).

The divide of per capita GHG emissions among cities were also huge (ranging from 0.15–34.95 t CO₂-eq/capita) (Figure 1b). Cities in the USA, Europe, and Australia had a notably higher per capita GHG emissions than those in most developing areas. For the former cities, efforts for decreasing per capita GHG emissions should be further enhanced. Though China is still a developing country, several Chinese cities (such as Yinchuan, Urumqi, and Dalian) had the per capita GHG emissions (34.95, 30.99, and 24.30 t CO₂-eq/capita, respectively) approaching those of developed countries, which is partially attributed to their rapid urbanization, industrialization, and relatively high reliance on coal energy. Another major reason is that many high-carbon production chains were outsourced from developed nations to Chinese cities, thus increasing the export-related emission of the latter.

The sector-level emissions of cities around 2012 (108 cities in total) were shown in Figure 2. Stationary energy is one of the largest contributors to GHG emissions of cities, which includes emissions from the fuel combustion and electricity use in residential and institutional buildings, commercial buildings, and industrial buildings in the study. Nearly half of the 108 cities had stationary energy emissions that represented more than 70% of their total GHG emissions, and more than 80% of the cities had stationary energy emissions that represented over 50% of total emissions; therefore, most of these cities can achieve significant GHG reduction progress only if this portion of energy emissions can be well-controlled. Stationary energy emissions are typically prominent in Chinese cities (especially from industrial buildings). Among them, Shanghai, Suzhou, Dalian, Handan, and Tianjin had the largest stationary energy emissions, largely because of their big manufacturing or service sectors. In comparison, some South American and Asian cities had a relatively small proportion of stationary energy emissions. For example, Belo Horizonte in Brazil had 25% of GHG emissions from stationary energy, while the proportions for Amman and Manila of Asia were 24 and 22%, respectively, which was due to the relatively more developed agricultural and farming industries in these regions. Emission of stationary energy in European and North American cities contributes 60–80% (e.g., 74% in New York City, Chicago, Torino, and 60% in Stockholm). Consumers in richer cities tend to buy more and carbon-intensive products manufactured in Chinese cities or other upstream regions, which would greatly increase the energy demand and GHG emissions within those areas. Therefore, plateauing or reducing the consumption for consumers worldwide should be considered as an important supplementary strategy for mitigating GHG emissions that related to international trade.

Transportation also plays an important role in the total GHG emissions in most cities. In about one-third of the cities, more than 30% of total GHG emissions were from on-road transportation. In comparison, the emissions from railways, aviation, and waterways (<15% of total GHG emissions) were much lower. The variation of emissions in the transportation sector may due to a range of factors such as economic development, urban forms, traffic structures, and types of vehicle fuel (Chester and Cano, 2016; Li et al., 2019a). The average GHG emissions of on-road transportation in developed regions was about two times of that in the developing regions. In cities of developed nations, the higher level of urbanization arouses more traffic activities and vehicle fleets that result in larger transport emissions; and transportation sector has a higher proportion in total economy-wide emission. As for the cities in developing areas, although the emission from transportation could also be considerable given the reliance on fossil fuels, it generally has a lower proportion in total emission.

Waste disposal and industrial process and fugitive emissions were smaller sources of GHG emissions by comparison. Although many studies recognized that waste is a minor contributor to the emissions in most of cities (Kennedy et al., 2009, 2014), it should be noted that technology advance in waste treatment and emission capture and reuse need further development toward carbon-neutral waste disposal and recycling systems (Dong et al., 2018).

Figure 3 reveals the annual change of total GHG emissions, and Figure 4 shows the annual change of per capita GHG emissions over the study period in 42 cities that had reliable emission data for at least 2 years (detailed information is shown in Table A1). Figure 3 shows that 30 cities reduced their annual GHG emissions, many of which are in America and Europe. Seattle (North America), Oslo (Europe), Bogotá (South America), and Houston (North America) are the top four cities with the largest per capita emission reduction (Bogotá is also the second largest city in terms of total reduction). European cities were heading for achieving their climate mitigation targets from a territorial perspective. From 2008 to 2016, the EU Emissions Trading System regulated ~50% of EU GHG emissions and reduced more than one billion tons of CO₂ from 2008 to 2016 (Bayer and Aklin, 2020). Furthermore, the total GHG emissions and emissions from the power sector have been largely reduced in the USA in recent decades due to the changes from the use of coal to natural gas (Feng et al., 2015) and the transformation toward a cleaner and renewable energy system (Aslani and Wong, 2014; Ahn et al., 2021), where the climate actions have already significantly promoted GHG emission reduction. It should be noted that cities in the developed countries (e.g., American and European cities) had moved a certain amount of high-carbon industries to developing areas (mostly in Asian and Latin American cities) in the past few decades. The transfer of industrial activities across cities would possibly lead to an ineffective GHG emission reduction. The decrease of the local emissions in the developed cities may end up transferring the GHG emission to cities in the developing regions. Therefore, it has been acknowledged appropriate city boundaries and accounting methods for carbon inventory should be developed and applied to identify the climate responsibility for cities (Chen et al., 2020a,b).

The GHG emissions continued to increase in several cities over the research period. Venice, Rio de Janeiro, Curitiba, and Johannesburg were the top four cities with the largest annual increases in per capita GHG emission, while Rio de Janeiro and Curitiba were also among cities with the largest annual total GHG emissions. Most of them are the cities in developing countries. Compared with the cities in developed areas, their industrial development mainly relies on industries with low technology and high energy consumption. For example, as the second largest industrial base of Brazil, Rio de Janeiro is under a fast development of chemical industry and mining industry. Some of these high-carbon industries are transferred from cities in developed countries (Cai et al., 2018). These cities have a great potential of emission reduction by making more aggressive climate mitigation plans that are anchored upon local sustainable development goals (Octaviano et al., 2016; Busch et al., 2019; Roe et al., 2019).

Of the 167 analyzed cities, 113 already set traceable targets for GHG emission reduction, which included absolute emission reduction targets for 68 cities, intensity targets for 40 cities, and baseline scenario targets for 8 cities. For some cities, more than one kind of target exists. Most of these cities set targets on GHG emissions (CO₂-eq) and some of them only referred to CO₂ emissions. The cities showed great variance from 1990 to 2015, the emission targets ranged from 15 to 100% reduction. Here, we classified these targets into near-term (2020s), mid-term (2030s), and long-term (2040s−2050) goals of emission reduction (Figure 5).

Absolute emission reduction targets (Figure 5A) were most widely reported in cities of developed nations. In general, these absolute targets are easier to trace over time and one can readily compare the near-term, mid-term, and long-term goals of the same city or between different cities. The commitments were concentrated in developed areas like Europe and North America. For instance, Toronto had announced to cut its GHG emissions by 80% of 1990 levels by 2050, with the near-term target of 30% reduction by 2020 and mid-term target of 65% target by 2030. European cities like Milan, Bologna, Warsaw had committed to achieve 20% of GHG emission reduction compared to 2005 levels by 2020, in alignment with the overall targets of the EU. There are cities that strive for even more ambitious goals (e.g., Porto adopted the goal of 45% reduction in community-wide GHG emissions compared to 2004 level by 2020 and Manchester has committed to be net-zero carbon by 2038). In comparison, cities tend to propose their climate targets through reduction of intensity (Figure 5B) or a simulated business-as-usual scenario (Figure 5C) if they are at the stage of rapid economic growth and accelerated industrialization (C40 Cities ARUP, 2014). For example, many Chinese cities have proposed clear intensity targets, following the national targets. The city-level goals were to reduce per unit GDP CO₂ emissions by 12–25% by 2020 compared with 2015 according to the “13th Five-Year-Plan,” although the latest 14th Five-Year-Plan for 2020–2025 set a national target of 18% reduction in carbon intensity. The targets for the cities with more developed economy and higher urbanization rate are more ambitious (e.g., 25% of carbon intensity declined for Hangzhou and 23% for Guangzhou and Shenzhen), while the goals are generally more conservative for cities that are still at a fast-developing stage (e.g., the intensity targets for Urumqi and Haikou were 12 and 14%, respectively). Absolute targets are developed for Chinese cities in the “14th Five-Year-Plan,” and some cities (e.g., Guangzhou, Shenzhen, Suzhou, Jinan, and Qingdao) have pledged to achieve carbon peak before 2025. These targets are consistent with China's commitments to mid-term goals (60–65% reduction in CO₂ emissions per unit of GDP by 2030 compared with 2005). The Chinese government had promised that the carbon intensity would be reduced by 40–45% during the periods of 2005–2020. In fact, by the end of 2019, China had reduced its carbon intensity by ~48.1% compared with 2005, which already exceeded their commitment.

More than 30 countries have announced their commitments of carbon neutrality and almost 100 countries that have net-zero-emission targets under discussion (Net Zero Tracker, 2021), which may inspire other regions to strengthen their own climate goals. An increasing number of cities have also proposed carbon neutrality targets. In total, 40 (24%) of the 167 cities in this study have set carbon neutrality (or net-zero-carbon, climate neutrality) goal, which may account for over 80% of their current GHG reduction. Most European cities strive to achieve carbon neutrality by 2050 (36 cities; i.e., 90%) to synchronize with the EU's goal as a whole; and four European cities even set these goals by 2020s−2030s. Similarly, most American cities have set targets to reduce GHG emissions by 80% by 2050. Copenhagen (Denmark) aims to be the first carbon-neutral capital in 2025. However, there is still a gap between the current climate policies in cities and the global climate goal. Studies have shown that 60% of EU Covenant of Mayors' cities are able to meet their 2020 carbon reduction targets (Hsu et al., 2020), which is 20% of CO₂ reduction between 1990 and 2020 (Kona et al., 2018); however, overall, they must double their efforts to comply with the Paris Agreement of net-zero emissions around 2050 (Salvia et al., 2021). To address this gap, megacities in China have proposed carbon peak and carbon neutrality targets ahead of the nation. As the most populated urban agglomerations and the frontier of low-carbon economic transition in mainland China, Guangdong-Hong Kong-Macao Greater Bay Area (consists of nine cities in Guangdong Province, Hong Kong. and Macao) is expected to peak their emissions by 2025 and become carbon neutrality by 2050, which is 5 years and a decade ahead of the national goals, respectively.

Stationary energy and on-road transportation are the most significant contributors to GHG emissions of global cities. Among all the stationary energy users, residential, and institutional buildings play important roles in emission of global cities. Measures such as promoting energy audits on building energy use (Kontokosta et al., 2020), adjusting building structures (Li et al., 2019b), and controlling and decreasing unnecessary construction activities (Zhang et al., 2019) should be considered when striving for the net-zero emission of buildings.

Cities with large size of populations, fast-developing transportation infrastructures, and a high level of travel demand tend to have larger shares of transportation-related emissions. For example, on-road transportation accounted for 44 and 42% of total GHG emissions in Bangkok and Seoul, respectively. These results are consistent with previous studies, which suggested that the GHG emission of transportation is closely relevant to the size of population and economy (Lakshmanan and Han, 1997; Timilsina and Shrestha, 2009; Ehrlich, 2017; Liang et al., 2017). Population growth during urbanization increases travel activities and vehicle fleets, although the growing population density could end up with lower transport emission per capita. To effectively control the transportation emissions, policy makers can use various policy tools. For example, in South Korea's cities, the governors proposed that the public sectors should buy green cars and there should be rewards and subsidies for using public buses and taxis (CSTNET, 2021). Moreover, fossil fuels for transport should be replaced by cleaner energy (e.g., hydrogen, and biofuels) (Axsen et al., 2020), and a higher leverl of electrification in both public and private transportation should promoted (Safarzyńska and van den Bergh, 2018; Xylia et al., 2019). In addition, the on-road emission is significantly higher than those from other types of traffic (e.g., railway, aviation, and shipping) from a global perspective. The on-road emission standards should be improved and updated to minimize the impact of existing gasoline-based and diesel-based vehicles (Jacobsen and Benthem, 2013; Thiel et al., 2016). Besides, a green traffic mode should be also formed in communities. People travel with bicycle and public transportation should be encouraged through incentive economic measures (e.g., a carbon currency system that rewards low-carbon transport choices). The rail transit should be also invested to appropriately relieve the travel pressure of ground transportation in cities of high population density.

Additionally, waste management and recycling for disposal should not be ignored. As shown in our results, for some developed cities such as Lima and Geneva, the contribution of waste disposal to total emission were relatively high. Their total GHG emissions were lower than most cities but their waste disposal proportions reached 44.5 and 18.5%, respectively. Strengthening the reuse of waste as new products in a low-carbon way is highly important (such as the reuse of biomass for energy generation) (Tripathi et al., 2019). Properly managing the solid waste can help realize the maximization of resource utilization and the “zero emission” of waste, which are significant for building a circular economy.

To trace the effectiveness of carbon reduction policies in urban areas, it is necessary to compile accurate and time-series emission inventories through a consistent methodology. Currently, despite many efforts exist in establishing carbon accounts of individual cities, high-quality dynamic GHG emission database of cities is still lacking at a global scale. Most cities do not have comparable time-series GHG emission inventories at a detailed sector level. Some American and EU cities developed relatively comprehensive GHG inventories, while other cities only had emission data for a few discrete years or did not report emission from some sectors. Several GHG emission databases have been developed in developing nations such as China. Carbon Emission Accounts and Datasets (CEAD) (https://www.ceads.net.cn/) reports GHG emission accounts and dataset for Chinese provincial regions and cities in different years. Moreover, the China High Resolution Emission Gridded Database (CHRED) (http://www.cityghg.com/) has established a GHG database for China, including a high-resolution CO₂ emissions dataset for Chinese cities (Cai et al., 2017). The global society and world organizations should help the cities in developing cities set up traceable GHG emission data and foster better collaboration of database development among major cities. It is necessary to build transparent and available carbon data disclosure systems so that the carbon mitigation processes can be consistently tracked. Also, the consumption-based and infrastructure-based carbon accounts have been increasingly adopted in determining climate impact and mitigation responsibilities of cities (Chen and Chen, 2017; Ramaswami et al., 2021). Development of global databases that support the consumption-based and infrastructure-based accounting should be also in the agenda. Improving the reporting scheme and data quality of GHG emission would be better for the evaluation of carbon mitigation processes. This places higher demands on basic data collection, both in terms of data volume and the level of accuracy.

Although many countries have announced ambitious climate commitments, climate targets seem less clear and available for many cities. In our study, only around 60% of cities have traceable climate targets (e.g., absolute emission reduction targets), which is insufficient. Cities in most developed countries have set clear long-term climate goals such as carbon neutrality by 2050. In comparison, a large number of cities in developing regions prefer intensity targets and baseline scenario targets that are usually short-term or mid-term based, which is not entirely compatible with the global climate goals. At certain stage, carbon intensity is a useful indicator showing the decarbonization of economy and provides better flexibilities for cities of fast economic growth and increase in emission. But in the long run, switching from intensity targets to absolute targets in cities is essential to achieve the global carbon neutrality by 2050. In fact, some Chinese cities have already presented their timetables for carbon peak and carbon neutrality in their 14th Five-Year Plans. For example, Guangzhou and Shenzhen aim to peak their GHG emission first in 2020, while other cities (such as Zhuhai and Huizhou) aim for around 2025, and finally achieve overall carbon neutrality by 2050. Beijing, Shanghai, cities in Jiangsu Province have also committed to achieve carbon peak no later than the national goal.

In addition, specific targets that are decomposed into various sectors (e.g., specific targets for energy consumption, transportation, and waste) are needed to mitigate the emission gaps. For example, Copenhagen plans to achieve 20% reduction in heat consumption in 2025 compared with 2010 and net-zero carbon emissions in public transport by 2025 (CPH, 2012). A wide cooperation among governments, business communities, research institutions, and social organizations are required to provide synergistic technological solutions toward achieving emission mitigation targets for sectors. The climate targets for different sectors and industries should be designed with a timely and easily-traceable way, and facilitate a transparent sector-level comparison among cities (Levin and Fransen, 2019).