National CO2 Emissions Research Articles

Identification of on-road vehicle CO2 emission pattern in China: A study based on a high-resolution emission inventory

As the country with the largest anthropogenic CO2 emission, China is greatly influential on fighting with climate change. However, CO2 emitted from on-road vehicles in China is a barrier to its carbon neutral due to the inevitable increase trend of vehicle quantity. Thus, to meet the requirement of refined policy-making for vehicular CO2 abatement, we calculated the CO2 emissions from 37 vehicular types and 3 fuel categories across 339 cities in China through the bottom-up method, and developed a national vehicular CO2 emission inventory in a high spatial resolution (1 km × 1 km). Additionally, machine learnings were conducted to the inventory for the emission pattern identification. It was found that the total vehicular CO2 emission in 2019 was 1090 million tons, and 77.1% of CO2 was emitted by vehicles of light-duty gasoline vehicle (LDGV) and heavy-duty diesel truck (HDDT). In addition, for the grids accompanying CO2 emissions, 75% of vehicular CO2 emissions were contributed by 15% of grids (hot grids). Furthermore, results of machine learning showed that LDGVs mainly distributed in economically advanced regions of which vehicular structures were relatively simple, while HDDTs were widely applied on the national scale. Based on the results above, two measures were proposed: (1) Electric cars have to be strongly promoted in hot grids for the LDGV replacement. (2) Long-distance freight tool replacements are urgently required in the national wide. Our study provided a studying base for further investigations on decarbonization and a new insight of China's vehicular CO2 emission controls.

The who, why and where of Norway’s [formula omitted] emissions from tourist travel

We present CO2 emissions from Norway’s tourist travel by the available transport modes, i.e., aviation, maritime (ferries and cruises) and land-based transport (road and railways). Our study includes detailed information on both domestic and international tourist travel within, from and to Norway. We have coupled statistics from several large surveys with detailed emission data to allow us to separate the purpose of the travel (holiday or business).Total transport CO2 emissions for tourists in 2018 were estimated to be 8 530 kt, equivalent to 19% of the reported Norwegian national CO2 emissions. Of these emissions, international tourists visiting Norway were responsible for 3 273 kt CO2, whereas travel by Norwegians accounted for 4 875 kt CO2, most of which occur outside Norway’s reporting obligations. Aviation and maritime transport were found to be the largest emission sources, responsible for 71% and 21% of total CO2 emissions, respectively. The reduction due to the COVID-19 pandemic was approximately 60% in 2020, and was sustained throughout the year.Our study shows that officially reported emissions, as limited to the countries territory, are not suitable for accurate evaluation of transport CO2 emissions related to tourism. A consumer or tourist-based calculation gives a marked redistribution of emission responsibility. Our results indicate that emissions from Norwegian residents travelling abroad are 1 602 kt higher than those from tourists coming to Norway. This is driven by frequent trips to popular tourist destinations such as Spain, Thailand, Turkey and Greece. Globally consumer based calculations would shift the responsibility of emissions by tourists to the large wealthy nations, with the most international tourists. The understanding of emission distributed by population group or market support in addition the developing of marketing strategies to attract low emission tourist markets and create awareness among the nations with higher shares of international tourist.

Using system dynamics to analyse key factors influencing China's energy-related CO2 emissions and emission reduction scenarios

Considering the complexity and dynamicity of national energy-related CO2 emissions, it is necessary to analyse the influencing factors and evaluate the possible impact of relevant emission reduction policies before formulating them. Based on the system dynamics (SD) method, this study proposed a research framework and established a multi-level SD model to comprehensively analyse national energy-related carbon emissions, considering the relationship between factors of society, economic, energy and carbon emissions. The method was applied to the case of China. Firstly, it simulated China's historical emissions and predicted future baseline from 2005 to 2050. Then, based on the sensitivity analysis, the key influencing factors were discerned. Finally, by setting scenarios and introducing causal chains, the model was used to test the effectiveness of different emission reduction measures. The results show that GDP, energy structure and industrial structure have significant impact on energy-related CO2 emissions. The impact of the population is limited, while that of industrial energy intensity varies in different periods. Without carbon constraints, China's CO2 emissions will peak by 2043 with the value of 15.2 Gt/year. Enhancing technological innovation in energy efficiency improvement and non-fossil energy is a better choice to reduce carbon emissions at current stage. An integrated measure combining technological innovation, infrastructure construction, resident behaviour improvement and adjustment of industrial structure can effectively advance the carbon peak to 2028, and reduce carbon intensity by 94% by 2050 compared to 2005, which will achieve China's national determined contribution goals. Such information will be important for China's future energy low-carbon transition and will provide suggestions for policy-making.

Contributions of economic growth, terrestrial sinks, and atmospheric transport to the increasing atmospheric CO2 concentrations over the Korean Peninsula

BackgroundUnderstanding a carbon budget from a national perspective is essential for establishing effective plans to reduce atmospheric CO2 growth. The national characteristics of carbon budgets are reflected in atmospheric CO2 variations; however, separating regional influences on atmospheric signals is challenging owing to atmospheric CO2 transport. Therefore, in this study, we examined the characteristics of atmospheric CO2 variations over South and North Korea during 2000–2016 and unveiled the causes of their regional differences in the increasing rate of atmospheric CO2 concentrations by utilizing atmospheric transport modeling.ResultsThe atmospheric CO2 concentration in South Korea is rising by 2.32 ppm year− 1, which is more than the globally-averaged increase rate of 2.05 ppm year− 1. Atmospheric transport modeling indicates that the increase in domestic fossil energy supply to support manufacturing export-led economic growth leads to an increase of 0.12 ppm year− 1 in atmospheric CO2 in South Korea. Although enhancements of terrestrial carbon uptake estimated from both inverse modeling and process-based models have decreased atmospheric CO2 by up to 0.02 ppm year− 1, this decrease is insufficient to offset anthropogenic CO2 increases. Meanwhile, atmospheric CO2 in North Korea is also increasing by 2.23 ppm year− 1, despite a decrease in national CO2 emissions close to carbon neutrality. The great increases estimated in both South Korea and North Korea are associated with changes in atmospheric transport, including increasing emitted and transported CO2 from China, which have increased the national atmospheric CO2 concentrations by 2.23 ppm year− 1 and 2.27 ppm year− 1, respectively.ConclusionsThis study discovered that economic activity is the determinant of regional differences in increasing atmospheric CO2 in the Korea Peninsula. However, from a global perspective, changes in transported CO2 are a major driver of rising atmospheric CO2 over this region, yielding an increase rate higher than the global mean value. Our findings suggest that accurately separating the contributions of atmospheric transport and regional sources to the increasing atmospheric CO2 concentrations is important for developing effective strategies to achieve carbon neutrality at the national level.

CO2 emission accounts of Russia\u2019s constituent entities 2005\u20132019

Constituent entities which make up Russia have wide-ranging powers and are considered as important policymakers and implementers of climate change mitigation. Formulation of CO2 emission inventories for Russia’s constituent entities is the priority step in achieving emission reduction. Russia is the world’s largest exporter of oil and gas combined and the fourth biggest CO2 emitter, so it’s efforts in mitigating CO2 emissions are globally significant in curbing climate change. However, the existing emission inventories only present national CO2 emissions; the subnational emission details are missing. In addition, the emission factors are not country-specific and energy activity data by fossil energy types and sectors are not sufficiently detailed. In this study, the CO2 emission inventories of Russia and its 82 constituent entities from 2005 to 2019 are constructed. The emission inventories include energy-related emissions with 89 socio-economic sectors and 17 energy types and process-related emissions. The uniformly formatted emission inventories can be a reference for in-depth analysis of emission characteristics and emission-related studies of Russia.

Optimal planning of a rooftop PV system using GIS-based reinforcement learning

This study aimed to develop a geographic information system (GIS)-based reinforcement learning (RL) model for optimal planning of a rooftop PV system, considering the uncertainty of future scenarios throughout the life cycle of buildings. To that end, GIS was used to establish the spatial data for the rooftop PV installation, and an RL model was developed to maximize the economic profit of the rooftop PV installation in various locations and future scenarios. The developed model was applied to residential buildings in Nonhyeon district, South Korea to evaluate their economic profitability and to compare the model with the existing planning methods. With the use of the developed GIS-based RL model, the rooftop PV system became economically feasible, achieving average economic profit of 539,197 USD over all scenarios for all target buildings which was higher than that of the existing models by 4.4% and 4.3%. Furthermore, the developed model outperformed the existing models especially in volatile scenarios with lower solar radiation. Therefore, the use of the proposed GIS-based RL model can optimize the economic feasibility of rooftop PV systems for buildings, which will benefit building owners and community-level energy business owners. In conclusion, the developed model can promote the adoption of rooftop PV systems, which have 91.8% lower global warming potential than the Korean mixed grid, without additional subsidies to achieve Korea’s national CO2 emission reduction plan.

Carbon emissions and removals from forests: new estimates, 1990–2020

Abstract. National, regional and global CO2 emissions and removals from forests were estimated for the period 1990–2020 using as input the country reports of the Global Forest Resources Assessment 2020. The new Food and Agriculture Organization of the United Nations (FAO) estimates, based on a simple carbon stock change approach, update published information on net emissions and removals from forests in relation to (a) net forest conversion and (b) forest land. Results show a significant reduction in global emissions from net forest conversion over the study period, from a mean of 4.3 in 1991–2000 to 2.9 Gt CO2 yr−1 in 2016–2020. At the same time, forest land was a significant carbon sink globally but decreased in strength over the study period, from −3.5 to −2.6 Gt CO2 yr−1. Combining net forest conversion with forest land, our estimates indicated that globally forests were a small net source of CO2 to the atmosphere on average during 1990–2020, with mean net emissions of 0.4 Gt CO2 yr−1. The exception was the brief period 2011–2015, when forest land removals counterbalanced emissions from net forest conversion, resulting in a global net sink of −0.7 Gt CO2 yr−1. Importantly, the new estimates allow for the first time in the literature the characterization of forest emissions and removals for the decade just concluded, 2011–2020, showing that in this period the net contribution of forests to the atmosphere was very small, i.e., a sink of less than −0.2 Gt CO2 yr−1 – an estimate not yet reported in the literature. This near-zero balance was nonetheless the result of large global fluxes of opposite sign, namely net forest conversion emissions of 3.1 Gt CO2 yr−1 counterbalanced by net removals on forest land of −3.3 Gt CO2 yr−1. Finally, we compared our estimates with data independently reported by countries to the United Nations Framework on Climate Change, indicating close agreement between FAO and country emissions and removals estimates. Data from this study are openly available via the Zenodo portal (Tubiello, 2020), with DOI https://doi.org/10.5281/zenodo.3941973, as well as in the FAOSTAT (Food and Agriculture Organization Corporate Statistical Database) emissions database (FAO, 2021a).

CDIAC-FF: global and national CO<sub>2</sub> emissions from fossil fuel combustion and cement manufacture: 1751–2017

Abstract. Global- and national-scale inventories of carbon dioxide (CO2) emissions are important tools as countries grapple with the need to reduce emissions to minimize the magnitude of changes in the global climate system. The longest time series dataset on global and national CO2 emissions, with consistency over all countries and all years since 1751, has long been the dataset generated by the Carbon Dioxide Information and Analysis Center (CDIAC), formerly housed at Oak Ridge National Laboratory. The CDIAC dataset estimates emissions from fossil fuel combustion and cement manufacture, by fuel type, using the United Nations energy statistics and global cement production data from the United States Geological Survey. Recently, the maintenance of the CDIAC dataset was transferred to Appalachian State University, and the dataset is now identified as CDIAC-FF. This paper describes the annual update of the time series of emissions with estimates through 2017; there is typically a 2- to 3-year time lag in the processing of the two primary datasets used for the estimation of CO2 emissions. We provide details on two changes to the approach to calculating CO2 emissions that have been implemented in the transition from CDIAC to CDIAC-FF: refinement in the treatment of changes in stocks at the global level and changes in the procedure to calculate CO2 emissions from cement manufacture. We compare CDIAC-FF's estimates of CO2 emissions with other global and national datasets and illustrate the trends in emissions (1990–2015) using a decomposition analysis of the Kaya identity. The decompositions for the top 10 emitting countries show that, although similarities exist, countries have unique factors driving their patterns of emissions, suggesting the need for diverse strategies to mitigate carbon emissions to meditate anthropogenic climate change. The data for this particular version of CDIAC-FF are available at https://doi.org/10.5281/zenodo.4281271 (Gilfillan et al., 2020a).

Do spatial spillovers matter? Estimating the impact of tourism development on CO2 emissions.

Most of the extant literature on the environmental impact of tourism has ignored the possible spatial interaction effects across countries. This study thus aims to re-investigate the impact of tourism development on CO2 emissions by taking spatial dependence into account. To that end, the spatial econometric techniques, which can address the issue of potential spatial dependence among countries, are adopted. Using a panel data of 95 countries over 2000-2014, the results confirm that there exists a significant spatial dependence among national CO2 emissions. Besides, the results provide confirmation that tourism development exerts a significant enhancing influence on CO2 emissions. Interestingly, we find that the promoting effect of tourism development on CO2 emissions primarily comes from the spillover effect rather than the direct effect, after considering spatial dependence. Finally, in light of the research findings, some policy implications are put forward to improve environmental quality.

Decoupling of economic growth from CO2 emissions in Yangtze River Economic Belt cities

Cities play significant roles in mitigating global climate change and formulating low carbon roadmaps. As the first regional strategy that prioritizes green development, the Yangtze River Economic Belt (YREB) is an economic circle along the Yangtze River, stringing up 11 provinces and municipalities from west to east of China. The huge regional heterogeneity in terms of economic development, size, and structure in YREB cities need differentiated emission reduction strategies and low-carbon development pathways. This study compiled the CO2 emission inventories of 85 cities in the YREB for the first time and explored the decoupling of economic growth from CO2 emissions at the city level. The results show that CO2 emissions of YREB cities increased at an annual average rate of 5.1% from 2005 to 2017, and 85 YREB cities emitted 44% of national total CO2 emissions and contributed 41% of national GDP in 2017. 61% of cities dominated by high-tech and service industry achieved decoupling between economic development and emissions before 2009 and are moving forward to a stronger decoupling state. 25% of cities achieved decoupling after 2009 and these post-decoupling cities took the heavy industry and light industry as their leading industries. Resource-based cities with slow economic development and high CO2 emissions changed from decoupling to negative decoupling or coupling. The proposed differentiated low-carbon development pathways for YREB cities could provide references for cities at different stages to achieve decoupling of GDP from CO2 emissions and emission reduction goals.

Energy-Water-Carbon Nexus Optimization for the Path of Achieving Carbon Emission Peak in China Considering Multiple Uncertainties: A Case Study in Inner Mongolia

The Chinese government has launched a guideline for carbon emissions up to the peak (CEUP) in the 2030 target. The electric power sector has to make its own contributions to the national CO2 emissions mitigation target. In this study, a patron–client interactive optimized (PCIO) model is proposed to investigate the regional energy–water–carbon nexus optimization under the policy background of the CEUP target. Inner Mongolia, the largest energy base in China, which is also facing the prominent contradiction including the energy production and serious environmental problems, is chosen as a case study. Multiple uncertainties, including the fuel price uncertainty and output of the wind and solar power, are considered to make the optimization process more realistic. Results show that coal-fired power will gradually be substituted by the gas, wind, and solar power in Inner Mongolia to reach the CEUP target. The CO2 capture and storage technology and air-cooling systems will play important roles, especially under the strict water policy scenario. However, the achievement of the CEUP and water-saving target will be at the expense of high system costs. The PCIO model makes it possible for the decision-maker to make flexible strategies to balance the CEUP target and saving system costs. The results have demonstrated the validity of the PCIO model in addressing the hierarchical programming problems.

Induction mechanism and optimization of tradable green certificates and carbon emission trading acting on electricity market in China

China has promised that CO2 emissions per GDP in 2030 would decrease by 60% to 65% than that in 2005, and proposed the goal of achieving carbon neutral by 2060. In order to fulfill these goals, Carbon Emissions Trading (CET) and Tradable Green Certificates (TGC) have been implemented in the power industry during the ‘13th five-year’ period. We firstly simulate the combined effects of TGC and CET on the electricity market from 2020 to 2026. Further, we build a policy synergy model to explore the optimization relationship between TGC and CET systems. The results show that, the power supply structure can be optimized under TGC and CET systems. The growth rate of CO2 emissions from the power industry will slow down, accelerating peaking CO2 emissions of the power industry. The national CO2 emissions reduction goal (1.185–1.037 tons /RMB 10,000 yuan by 2030) is expected to be achieved. There may be policy redundancy between TGC and CET systems. It is determined by how to set renewable energy objective and CET quota objective. Under multiple policy objectives, the key is to obtain the policy synergy intervals for staged optimization. Finally, we propose some suggestions on the improvement of TGC and CET mechanisms, and combined implementation and optimization of multiple emission reduction policies.

Alien plant introductions and greenhouse gas emissions: Insights from Gunnera tinctoria invasions

Plant invasions represent a major global change in land/vegetation cover with the potential to significantly modify greenhouse gas (GHG) emissions. To get a better understanding of the impacts of terrestrial invasive plants on soil GHG emissions we report, firstly, on experiments conducted on invasive populations of the N-fixing herbaceous species Gunnera tinctoria in Ireland, and secondly, compare our results with published information based on a systematic review of the literature. For G. tinctoria populations, there was a >50% reduction in soil CO2 emissions, mainly due to a reduction in autotrophic respiration, but with little impact on annual N2O or CH4 budgets. One year after the removal of G. tinctoria, soil GHG emissions returned to values comparable to uninvaded areas and this was associated with the reestablishment of the vegetation and an increased root biomass per unit area. If G. tinctoria covered 10% of abandoned agricultural land in Ireland, this could be associated with a reduction of approximately 8% (or 4.988 Mt CO2eq y−1) of the country's national CO2 emissions. Comparisons of these results with literature values were difficult because of the often low and limited sampling effort of previous investigations, a failure to assess all three major GHGs and because of marked seasonal variations. We found 46 studies that documented results for 16 species. From the studies that measured soil respiration, it was enhanced in only 45% of cases, questioning the assumption that invasive plants always increase soil CO2 emissions. In 25 cases that analysed methane, CH4 emissions increased in 76% of them, but all of these were conducted in wetlands. In only two cases were N-fixing species associated with enhanced N2O emissions. Our results argue for more detailed and comprehensive assessments of the effect of plant invasions on GHG emissions and their global impact.

Assessment of International Trade-Related Transport CO2 Emissions—A Logistics Responsibility Perspective

International supply chains generate substantial amounts of CO2 emissions. However, established methodologies for national freight transport emission assessments do not consider such international perspectives sufficiently. This research aims to show how logistic responsibility may be used in ex post transport CO2 emission assessments, for macrologistic or supply chain levels. We propose an original approach to estimate and allocate CO2 emissions generated by international freight transport between trade countries. The proposed method relies on the applied Incoterms® rules in sales contracts. A new indicator, the index of responsibility for transport emissions (RTE-index), is introduced to allocate bilateral trade-related transport CO2 emissions. This is the first time that the Incoterms® clauses are used for macrologistic assessments of international trade-related transport CO2 emissions. Our approach is exemplified using bilateral trade-related transport flows between Serbia and other European countries. The introduced RTE-index is expected to help visualise average national trade-related transport CO2 emission responsibilities; increase awareness regarding environmental considerations among trade parties, logistics companies, and national organisations; and provide new perspectives for environmental transport policy actions.

Environmental implications of changes in China's inter-provincial trade structure

Interprovincial trade structure keeps changing during the development of domestic market economy in China. As the internal circulation and environmental protection become the theme of China's future development, a shift towards more environment-friendly interprovincial trade structure should be advocated to achieve sustainable economic and environmental development. Previous studies rarely paid attention to the comprehensive influences of interprovincial trade structure change on multiple environmental impacts. Here, we constructed an analytical framework to quantify the influences of trade structure change on national and provincial CO2 emissions, land use and water consumption during 1997–2012 based on the multi-regional input-output analysis. The results showed that inter-provincial trade structure change contributed to the decline in national average carbon intensity and water use intensity, resulting in an overall decrease of CO2 emissions and water use by 313.6 million tons and 2.9 billion m3. However, interprovincial trade structure change made some water-scarce provinces (e.g., Xinjiang, Ningxia, Shaanxi, Jiangsu) undertake water-intensive industries, further exacerbating the uneven distribution of water resources in China. On the contrary, interprovincial trade structure change led to the increase of national average land use intensity, which increased 6.3 million hectares of land use. We suggested that the environment costs of carbon emissions should be further embodied into the commodity prices through carbon tax or carbon market, facilitating the development of low-carbon interprovincial trade structure. Besides, water-intensive industries should be transferred to water-abundant provinces by adjusting the water price in water-scarce provinces. The trade-offs between land and water resources should be made for these eastern regions that took more and more land-intensive industries, as they had high land use efficiency but scarce water resources.

Quantitative analysis of automobile sector in Indonesian automotive roadmap for achieving national oil and CO2 emission reduction targets by 2030

The dominance of private vehicles in the Indonesian transport modal mix has led to an enormous energy demand from oil and transport-related externalities. In 2018, to increase the sustainability of the automotive industry, the Indonesian government established an industrial roadmap with strong links to the national energy policy and CO2 emission reduction targets. The present manuscript proposes a model that could enable a quantitative projection of oil demand, CO2 emissions and assess the impact of proposed policy initiatives under the Activity, Mode Share, Intensity, and Fuel Choice (ASIF) framework.The results showed that improvements in vehicle fuel economy and the adoption of alternative fuels―such as bioethanol, biodiesel, and electricity―could reduce oil and CO2 emissions by up to 30.8% and 33.2%, respectively, as compared to the business as usual (BAU) case by 2030. The most significant contribution was derived by adopting policies related to biofuel blending: bioethanol (E−10) and biodiesel (B-50) reduced oil emissions by up to 5.44% and 10.30%, respectively. The electrified vehicle policy and improvements related to the new vehicle fuel economy contributed a combined 10.38% reduction. Meanwhile, the mandatory use of CNG made a contribution of only 0.98%. The end-of-life vehicle (ELV) retirement policy was also evaluated, with the results showing that it could contribute up to 3.49%. The findings suggest that the roadmap should be restructured to include a specific biofuel blend ratio mandate and new vehicle fuel economy targets. Additionally, a step-by-step implementation timeline needs to be established to enable a sufficient transition period during which the industry sector can adjust.

Gridded fossil CO2 emissions and related O2 combustion consistent with national inventories 1959\u20132018

Quantification of CO2 fluxes at the Earth’s surface is required to evaluate the causes and drivers of observed increases in atmospheric CO2 concentrations. Atmospheric inversion models disaggregate observed variations in atmospheric CO2 concentration to variability in CO2 emissions and sinks. They require prior constraints fossil CO2 emissions. Here we describe GCP-GridFED (version 2019.1), a gridded fossil emissions dataset that is consistent with the national CO2 emissions reported by the Global Carbon Project (GCP). GCP-GridFEDv2019.1 provides monthly fossil CO2 emissions estimates for the period 1959–2018 at a spatial resolution of 0.1°. Estimates are provided separately for oil, coal and natural gas, for mixed international bunker fuels, and for the calcination of limestone during cement production. GCP-GridFED also includes gridded estimates of O2 uptake based on oxidative ratios for oil, coal and natural gas. It will be updated annually and made available for atmospheric inversions contributing to GCP global carbon budget assessments, thus aligning the prior constraints on top-down fossil CO2 emissions with the bottom-up estimates compiled by the GCP.

Optimisation of retrofit wall insulation: An Irish case study

Ireland has one of the highest rates of emissions per capita in the world and its residential sector is responsible for approximately 10% of total national CO2 emissions. Therefore, reducing the CO2 emissions in this sector will play a decisive role in achieving EU targets of reducing emissions by 40% by 2030. To better inform decisions regarding retrofit of the existing building stock, this study proposes Optimum Insulation Thicknesses (OIT) for typical walls in 25 regions in Ireland. The calculation of OIT includes annual heat energy expenditure, CO2 emissions, and material payback period. The approach taken is based on Heating Degree Day (HDD) and life cycle cost analysis methods for different combinations of insulation material, heat energy type, and Irish wall configuration. Results indicate that OIT increases with increased HDD and varies up to 30% from lower to higher HDD regions in Ireland. The type of wall materials, configuration, insulation type, and heat energy type all have a significant impact on annual cost saving potential (up to 170 €/m2) and carbon emission (up to 50 kg/m2). The Analysis of Variance (ANOVA) technique is used to compare the significant mean difference between combinations under OIT and cost savings.

Drivers of global and national CO2 emissions changes 2000–2017

ABSTRACT Understanding the drivers of CO2 emissions changes is useful in supporting future mitigation. This study applies a log-mean divisia index decomposition to assess four drivers of CO2 emissions changes – population, income, energy intensity and carbon intensity – in 138 countries worldwide over the period 2000–2017. At the global level, income and population are the main drivers of increased emissions over time, with contributions of 116% and 60% to global CO2 emissions changes, respectively. Energy intensity is the key mitigation driver, with a contribution of −80%. Although carbon intensity increased CO2 emissions overall over the period 2000–2017 with a contribution of 4%, it has started to reduce emissions in recent years. China, the United States of America, the European Union, India and Russia are the five regions responsible for most changes in global emissions. The five regions together contribute −73% of the energy intensity effect, and China’s income contribution is 83% in relation to the total of 116%. At the national level, in 2017, CO2 emissions returned to below 2000 levels in 62% of Annex I (developed) countries but increased in 88% of non-Annex I (mostly developing) countries. Among the 35 countries realizing CO2 emissions reductions, 24 were driven primarily by energy intensity, six by carbon intensity, three by economic recession, and one by population decrease. Among the 103 countries with increasing CO2 emissions, 63 were driven primarily by income, 26 by population, nine by carbon intensity increase, and five by energy intensity increase. Our analysis emphasizes the necessity of considering differences in national development stages when formulating climate change mitigation policies. Key policy insights Over the period 2000–2017, at the global and national levels, CO2 emissions increases were driven mainly by economic development and population growth, and mitigation was driven mainly by energy intensity improvement. Improving energy intensity and carbon intensity is the key to mitigating CO2 emissions. Carbon intensity is expected to play an increasing role in the future. In over one-third of Annex I countries, CO2 emissions increased from 2000 to 2017. To meet the Paris Agreement goals, Annex I countries will need to enhance mitigation ambition by further tapping the mitigation potentials of energy and carbon intensity. In accordance with national circumstances, development needs and international support, non-Annex I countries should achieve low-carbon economic and energy transitions and peak CO2 emissions as early as possible.

Co-benefits of subnationally differentiated carbon pricing policies in China: Alleviation of heavy PM2.5 pollution and improvement in environmental equity

Carbon policies differentiated according to regional disparities have been recognized and recommended. However, the air quality co-benefits of differentiated policies remain unclear. Here we combine a multi-regional dynamic computable general equilibrium (CGE) model and an extend response surface model (ERSM) to investigate the impact of nationally uniform and subnationally differentiated carbon pricing policies on fine particulate matter (PM2.5) concentrations in China. All policies examined lead to the same accumulated national CO2 emissions (2020–2050), with the 2030 emissions attaining China's national abatement target. We find that, when subnational policies differentiated according to provincial PM2.5 concentrations are implemented, the higher-than-average carbon price over more polluted provinces results in twice as much reduction in CO2 and air pollutant emissions in 2050 as the national policy. As a result, the subnational policies cause larger PM2.5 concentration reductions in these provinces (9%–18%) than the national policy (7%–11%). Also, the subnational policies eliminate high PM2.5 exposure of over 45 μg/m3 which 12% people suffer from under the national policy. The subnational policies substantially reduce regional disparity in PM2.5 pollution and hence improve environmental equity. The results suggest that subnationally differentiated carbon policies are a promising instrument to mitigate severe pollution and promote environmental equity.