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Abstract Climate mitigation is reported to benefit biodiversity globally. However, the impacts of mitigation measures based on large-scale land-use modifications can be concentrated in the regions where they are introduced, resulting in regional mismatches between mitigation efforts and biodiversity benefits. Here, we evaluated the impacts of large-scale deployment of bioenergy with carbon capture and storage and afforestation to attain the climate stabilization target stated by the Paris Agreement on global and regional biodiversity by using an integrated model framework. Our results highlight that climate mitigation efforts can benefit global biodiversity regardless of large-scale implementation of land-based mitigation measures. However, the negative impacts of mitigation measures on biodiversity are concentrated in regions with a higher contribution to land-use change and carbon sequestration. The results imply the need to consider the unequal regional distribution of benefits from climate mitigation, as well as mitigation options that avoid regional biodiversity loss by minimizing land-use change.

Abstract Afforestation is a major carbon dioxide removal technology but can negatively affect food and land systems. Here, we used an integrated assessment model to quantitatively demonstrate how the selection of forest type to use in afforestation could increase global carbon sequestration without compromising global food and land sustainability. Our findings indicate that if a carbon-intensive forest type is selected, afforestation would increase carbon sequestration by 25% compared to the level assuming the native forest type. At the same time, if implemented inappropriately at a large scale, afforestation would worsen the economy, food, and land systems due to decreased land efficiency in carbon removal compared to bioenergy with carbon capture and storage, leading to increased land expansion for carbon removal, higher food prices, and increased risk of hunger. These results suggest the need to implement carbon-intensive forest types with complementary measures to reduce the adverse impacts on food and land sustainability.

Abstract Climate change mitigation generally require rapid decarbonization in the power sector, including phase-out of fossil fuel-fired generators. Given recent technological developments, co-firing of hydrogen or ammonia, could help decarbonize fossil-based generators, but little is known about how its effects would play out globally. Here, we explore this topic using an energy system model. The results indicate that hydrogen co-firing occurs solely in stringent mitigation like 1.5 °C scenarios, where around half of existing coal and gas power capacity can be retrofitted for hydrogen co-firing, reducing stranded capacity, mainly in the Organization for Economic Co-operation and Development (OECD) countries and Asia. However, electricity supply from co-firing generators is limited to about 1% of total electricity generation, because hydrogen co-firing is mainly used as a backup option to balance the variable renewable energies. The incremental fuel cost of hydrogen results in lower capacity factor of hydrogen co-fired generators, whereas low-carbon hydrogen contributes to reducing emission cost associated with carbon pricing. While hydrogen co-firing may play a role in balancing intermittency of variable renewable energies, it will not seriously delay the phase-out of fossil-based generators.

We study Japan’s net-zero emissions target by 2050 in a multi-model framework, focusing on residual emissions and carbon dioxide removal (CDR). Four energy-economic and integrated assessment models show similar but stronger strategies for the net-zero target, compared to the previous, low-carbon policy target (80% emissions reduction). Results indicate that around 90% (inter-model median) of the current emissions are reduced through abatement, including improved energy efficiency and cleaner electricity and fuels. Models deploy new options such as CDR based on carbon capture and storage (CCS) (bioenergy with CCS and direct air carbon dioxide capture and storage) and hydrogen to achieve net zero. The scale of CCS-based CDR deployment reaches an inter-model median of 132Mt-CO _2 /yr. The median hydrogen share of final energy in 2050 increases from 0.79% to 6.9% between the low-carbon and net-zero scenarios. The CDR sensitivity analysis reveals that limiting the use of CDR significantly increases the mitigation costs for net zero. Achieving Japan’s net-zero goal will require exploring methods to reduce residual emissions, including demand-side solutions, and accelerating responsible CDR policies.

Fire emits hazardous air pollutants, the most dominant of which is fine particulate matter of diameter ⩽2.5 μ m (PM _2.5 ). PM _2.5 is a great concern due to its adverse effects on public health. Previous studies have examined the health burden from fire-related PM _2.5 for the historical period; however, future global mortality associated with fire-PM _2.5 , particularly under the coexisting impacts of climate and socioeconomic changes, is yet to be projected. Here, we estimated the mortality associated to fire-PM _2.5 (fire-PM _2.5 mortality) for the present period (2010s) and then projected the mortality for the 2050s and 2090s under 10 scenarios created by combining two Representative Concentration Pathways (RCP2.6 or 6.0) with five Shared Socioeconomic Pathways (SSP1–5). We used the Li-Park fire model in combination with a chemical transport model and health risk assessment to calculate fire-PM _2.5 mortality. For the present period, the estimated fire-PM _2.5 mortality was 135 180 (105 403–163 738), which is 1.7 deaths per 100 000 population globally. When countries were grouped by income, the fire-PM _2.5 mortality rate was the highest in the high-income country group and lowest in the lowest-income country group. For the 2050s and 2090s, the fire-PM _2.5 mortality rate was projected to decrease under most scenarios because of decreases in fire emissions and baseline mortality rate. However, a scenario of high population growth and low technical development (SSP3) together with severe global warming (RCP6.0) would lead to an increase in the fire-PM _2.5 mortality rate in the 2090s, particularly in the highest-income countries, due to increased fire under drier and warmer weather conditions. Stratification of countries by gross domestic product indicated the need for adaptation efforts in the highest-income countries to avoid future increases of mortality associated with fire-PM _2.5 .

Comprehensive policy measures are needed to close the emissions gap between Nationally Determined Contributions and emissions goals of the Paris Agreement. Here the authors present a Bridge scenario that may aid in closing the emissions gap by 2030.

What will be the aggregated cost of climate change in achieving the Paris Agreement, including mitigation, adaptation, and residual impacts? Several studies estimated the aggregated cost but did not always consider the critical issues. Some do not address non-market values such as biodiversity and human health, and most do not address differentiating discount rates. In this study, we estimate the aggregated cost of climate change using an integrated assessment model linked with detailed-process-based climate impact models and different discount rates for market and non-market values. The analysis reveals that a climate policy with minimal aggregated cost is sensitive to socioeconomic scenarios and the way discount rates are applied. The results elucidate that a lower discount rate to non-market value—that is, a higher estimate of future value—makes the aggregated cost of achieving the Paris Agreement economically reasonable.

To evaluate the effectiveness of current national policies in achieving global temperature targets is important but a systematic multi-model evaluation is still lacking. Here the authors identified a reduction of 3.5 GtCO2 eq of current national policies relative to a baseline scenario without climate policies by 2030 due to the increasing low carbon share of final energy and the improving final energy intensity.

Greenhouse gas mitigation can involve land-use changes that alter the habitat available for wildlife. Here, Ohashi et al. perform an integrated assessment showing that climate mitigation can be beneficial for global biodiversity but may entail local biodiversity losses where land-based mitigation is implemented.

Computable General Equilibrium models can hardly decouple economic growth and energy consumption while energy system models can hardly predict macroeconomic implications of energy system changes. Here the authors investigated the macroeconomic implications of consistently dealing with energy systems and the stability of further power generation and show that GDP losses were significantly lower than those in the conventional economic model by more than 50% in 2050, while industry and service sector energy consumption are the main factors causing these differences.

Abstract Bioenergy plays an important role in low greenhouse gas stabilization scenarios. Among various possible sources of bioenergy, dedicated bio‐crops could contribute to most of the potential. However, large scale bio‐crop deployment raises sustainability concerns. Policies to alleviate the pressure of bio‐crops on the terrestrial environment can affect bioenergy potential and production costs. Here, we estimated the maximum bioenergy potential under environmental protection policies (biodiversity and soil protection) and societal transformation measures from demand and supply side (demand‐side policy includes sustainable diet; supply‐side policy includes advanced technology and trade openness for food) by using an integrated assessment modelling framework, which consists of a general equilibrium model (Asian‐Pacific Integrated Model/Computable General Equilibrium) and a spatial land use allocation model (Asian‐Pacific Integrated Model/Platform for Land‐Use and Environmental Model). We found that the global advanced bioenergy potential under no policy was 245 EJ/year and that 192 EJ/year could be produced under US$5/GJ. These figures were 149 EJ/year and 110 EJ/year, respectively, under a full environmental policy. Biodiversity protection has a greater impact than soil protection due to its larger coverage and stronger implementation. Societal transformation measures effectively increase them to 186 EJ/year and 143 EJ/year, respectively, even under full environmental policies. These results imply that the large‐scale bioenergy deployment possibly needed for the climate target to limit the global mean temperature increase well below 2°C compared to the preindustrial level might face a trade‐off with environmental protection targets and that possible mitigation pathways in harmony with other environmental issues need to be explored.

There lacks model comparison of global land use change projections. Here the authors explored how different long-term drivers determine land use and food availability projections and they showed that the key determinants population growth and improvements in agricultural efficiency.

The Paris Agreement has confirmed that the ultimate climate policy goal is to hold the increase in the global average temperature to well below 2 °C above pre-industrial levels and to pursue efforts to limit the increase to 1.5 °C. Moving the goal from 2 °C to 1.5 °C calls for much more concerted effort, and presents greater challenges and costs. This study uses an Asia-Pacific Integrated Model/Computable General Equilibrium (AIM/CGE) to evaluate the role of socioeconomic factors (e.g. technological cost and energy demand assumptions) in changing mitigation costs and achieving the 1.5 °C and 2 °C goals, and to identify the channels through which socioeconomic factors affect mitigation costs. Four families of socioeconomic factors were examined, namely low-carbon energy-supply technologies, end-use energy-efficiency improvements, lifestyle changes and biomass-technology promotion (technology cost reduction and social acceptance promotion). The results show that technological improvement in low-carbon energy-supply technologies is the most important factor in reducing mitigation costs. Moreover, under the constraints of the 1.5 °C goal, the relative effectiveness of other socioeconomic factors, such as energy efficiency improvement, lifestyle changes and biomass-related technology promotion, becomes more important in decreasing mitigation cost in the 1.5 °C scenarios than in the 2 °C scenarios.

Climate change mitigation efforts to reduce greenhouse gas (GHG) emissions have associated costs, but there are also potential benefits from improved air quality, such as public health improvements and the associated cost savings. A multidisciplinary modeling approach can better assess the co-benefits from climate mitigation for human health and provide a justifiable basis for establishment of adequate climate change mitigation policies and public health actions. An integrated research framework was adopted by combining a computable general equilibrium model, an air quality model, and a health impact assessment model, to explore the long-term economic impacts of climate change mitigation in South Korea through 2050. Mitigation costs were further compared with health-related economic benefits under different socioeconomic and climate change mitigation scenarios. Achieving ambitious targets (i.e., stabilization of the radiative forcing level at 3.4 W/m2) would cost 1.3–8.5 billion USD in 2050, depending on varying carbon prices from different integrated assessment models. By contrast, achieving these same targets would reduce costs by 23 billion USD from the valuation of avoided premature mortality, 0.14 billion USD from health expenditures, and 0.38 billion USD from reduced lost work hours, demonstrating that health benefits alone noticeably offset the costs of cutting GHG emissions in South Korea. Keywords: Climate mitigation, Air pollution, Health impact assessment, Co-benefit analysis, CGE, IMED Model

Abstract Although biophysical yield responses to local warming have been studied, we know little about how crop yield growth—a function of climate and technology—responds to global temperature and socioeconomic changes. Here, we present the yield growth of major crops under warming conditions from preindustrial levels as simulated by a global gridded crop model. The results revealed that global mean yields of maize and soybean will stagnate with warming even when agronomic adjustments are considered. This trend is consistent across socioeconomic assumptions. Low-income countries located at low latitudes will benefit from intensive mitigation and from associated limited warming trends (1.8 °C), thus preventing maize, soybean and wheat yield stagnation. Rice yields in these countries can improve under more aggressive warming trends. The yield growth of maize and soybean crops in high-income countries located at mid and high latitudes will stagnate, whereas that of rice and wheat will not. Our findings underpin the importance of ambitious climate mitigation targets for sustaining yield growth worldwide.

Near-term climate forcers (NTCFs), including aerosols and chemically reactive gases such as tropospheric ozone and methane, offer a potential way to mitigate climate change and improve air quality—so called ‘win-win’ mitigation policies. Prior studies support improved air quality under NTCF mitigation, but with conflicting climate impacts that range from a significant reduction in the rate of global warming to only a modest impact. Here, we use state-of-the-art chemistry-climate model simulations conducted as part of the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP) to quantify the 21st-century impact of NTCF reductions, using a realistic future emission scenario with a consistent air quality policy. Non-methane NTCF (NMNTCF; aerosols and ozone precursors) mitigation improves air quality, but leads to significant increases in global mean precipitation of 1.3% by mid-century and 1.4% by end-of-the-century, and corresponding surface warming of 0.23 and 0.21 K. NTCF (all-NTCF; including methane) mitigation further improves air quality, with larger reductions of up to 45% for ozone pollution, while offsetting half of the wetting by mid-century (0.7% increase) and all the wetting by end-of-the-century (non-significant 0.1% increase) and leading to surface cooling of −0.15 K by mid-century and −0.50 K by end-of-the-century. This suggests that methane mitigation offsets warming induced from reductions in NMNTCFs, while also leading to net improvements in air quality.

Low-carbon pathways consistent with the 2 °C and 1.5 °C long-term climate goals defined in the Paris Agreement are likely to induce substantial co-benefits for air pollution and associated health impacts. In this analysis, using five global integrated assessment models, we quantify the emission reductions in key air pollutants resulting from the decarbonization of energy systems and the resulting changes in premature mortality attributed to the exposure to ambient concentrations of fine particulate matter. The emission reductions differ by sectors. Sulfur emissions are mainly reduced from power plants and industry, cuts in nitrogen oxides are dominated by the transport sector, and the largest abatement of primary fine particles is achieved in the residential sector. The analysis also shows that health benefits are the largest when policies addressing climate change mitigation and stringent air pollution controls are coordinated. We decompose the key factors that determine the extent of health co-benefits, focusing on Asia: changes in emissions, urbanization rates, population growth and ageing. Demographic processes, particularly due to ageing population, counteract in many regions the mortality reductions realized through lower emissions.

Integrated assessment models (IAMs) form a prime tool in informing about climate mitigation strategies. Diagnostic indicators that allow comparison across these models can help describe and explain differences in model projections. This increases transparency and comparability. Earlier, the IAM community has developed an approach to diagnose models (Kriegler (2015 Technol. Forecast. Soc. Change 90 45–61)). Here we build on this, by proposing a selected set of well-defined indicators as a community standard, to systematically and routinely assess IAM behaviour, similar to metrics used for other modeling communities such as climate models. These indicators are the relative abatement index, emission reduction type index, inertia timescale, fossil fuel reduction, transformation index and cost per abatement value. We apply the approach to 17 IAMs, assessing both older as well as their latest versions, as applied in the IPCC 6th Assessment Report. The study shows that the approach can be easily applied and used to indentify key differences between models and model versions. Moreover, we demonstrate that this comparison helps to link model behavior to model characteristics and assumptions. We show that together, the set of six indicators can provide useful indication of the main traits of the model and can roughly indicate the general model behavior. The results also show that there is often a considerable spread across the models. Interestingly, the diagnostic values often change for different model versions, but there does not seem to be a distinct trend.

A carbon tax is one of the measures used to reduce GHG emissions, as it provides a strong political instrument for reaching the goal, stated in the Paris Agreement, of limiting the global mean temperature increase to well below 2 °C. While one aspect of a carbon tax is its ability to change income distribution, no quantitative assessment has been made within the context of global poverty. Here, we explore future poverty scenarios and show the extent to which carbon tax revenue, obtained to limit global warming to well below 2 °C, has the potential to help eradicate poverty. In order to better understand the relationship between poverty and climate change mitigation policy, we developed a novel modelling framework that includes a module representing poverty indicators in the conventional integrated assessment model. We found that the poverty gap, which is a measure of the shortfall in income relative to the poverty line, is 84 billion US dollars (USD) and that the carbon tax revenue potential for the above-mentioned 2 °C consistent climate change mitigation would be 1600 billion USD in 2030. Many low-income countries cannot fill the poverty gap using only their own domestic revenue; however, this shortfall could be met by using a portion of the revenue in high-income countries. Our results demonstrate that climate change mitigation can have a great potential in synergy effects for resolving poverty and illustrates the importance of international cooperation.

Actions tackling with climate change can cause co-benefits and trade-offs with Sustainable Development Goals (SDGs) concerned with air pollution, water scarcity, food security, land use, and sustainable energy. Such interactions can be greatly influenced by socioeconomic conditions. The impacts of socioeconomic conditions on multiple SDGs have not been evaluated separately from climate policies. This paper employs a Representative Concentration Pathways–Shared Socio-economic Pathways (RCP-SSP) framework and the Asia-Pacific Integrated Model/computable general equilibrium (AIM/CGE) integrated assessment model to identify the global multi-sectoral consequences of socioeconomic conditions through 2050 under future SSP scenarios. Results show that changes of socioeconomic conditions consistent with the SSP1 pathway could always improve SDG indicators, with or without climate policies. In many respects, socioeconomic conditions are more important than climate policies in achieving SDGs, particularly SDGs concerned with food security and energy affordability, as well as in simultaneously achieving multiple SDGs. We conclude that the advantages of a joint effort to implement climate policies and promulgate socioeconomic changes should be recognized by policy makers.

Electrification is widely considered an attractive solution for reducing the oil dependency and environmental impact of road transportation. Many countries have been establishing increasingly stringent and ambitious targets in support of transport electrification. We conducted scenario simulations to depict the role of transport electrification in climate change mitigation and how the transport sector would interact with the energy-supply sector. The results showed that transport electrification without the replacement of fossil-fuel power plants leads to the unfortunate result of increasing emissions instead of achieving a low-carbon transition. While transport electrification alone would not contribute to climate change mitigation, it is interesting to note that switching to electrified road transport under the sustainable shared socioeconomic pathways permitted an optimistic outlook for a low-carbon transition, even in the absence of a decarbonized power sector. Another interesting finding was that the stringent penetration of electric vehicles can reduce the mitigation cost generated by the 2 °C climate stabilization target, implying a positive impact for transport policies on the economic system. With technological innovations such as electrified road transport, climate change mitigation does not have to occur at the expense of economic growth. Because a transport electrification policy closely interacts with energy and economic systems, transport planners, economists, and energy policymakers need to work together to propose policy schemes that consider a cross-sectoral balance for a green sustainable future.

Cost-effective achievement of the Paris Agreement’s long-term goals requires the unanimous phase-out of coal power generation by mid-century. However, continued investments in coal power plants will make this transition difficult. India is one of the major countries with significant under construction and planned increase in coal power capacity. To ascertain the likelihood and consequences of the continued expansion of coal power for India’s future mitigation options, we use harmonised scenario results from national and global models along with projections from various government reports. Both these approaches estimate that coal capacity is expected to increase until 2030, along with rapid developments in wind and solar power. However, coal capacity stranding of the order of 133–237 GW needs to occur after 2030 if India were to pursue an ambitious climate policy in line with a well-below 2 °C target. Earlier policy strengthening starting after 2020 can reduce stranded assets (14–159 GW) but brings with it political economy and renewable expansion challenges. We conclude that a policy limiting coal plants to those under construction combined with higher solar targets could be politically feasible, prevent significant stranded capacity, and allow higher mitigation ambition in the future.

Synergies and trade-offs exist between climate mitigation actions and target indicators of the Sustainable Development Goals (SDGs). Some studies have assessed such relationships, but the degree of such interaction remains poorly understood. Here, we show the SDG implications associated with CO _2 emissions reductions. We developed ‘marginal SDG-emissions-reduction values (MSVs)’, which represent the marginal impacts on SDG indicators caused by a unit CO _2 emissions reduction. This metric is applicable to national assessments and was applied to Asia. We found clear relationships between CO _2 emissions reduction rates and many SDG targets. For instance, 1% reduction of CO _2 can avoid 0.57% of air pollution-related premature deaths (SDG3), whereas the mean species richness (SDG15) is decreased by 0.026% with the same reduction (not including climate change impacts). Our findings are useful for assessing the SDG implications associated with CO _2 emissions reduction targets, which will help inform national climate policies.

International efforts to avoid dangerous climate change aim for large and rapid reductions of fossil fuel CO _2 emissions worldwide, including nearly complete decarbonization of the electric power sector. However, achieving such rapid reductions may depend on early retirement of coal- and natural gas-fired power plants. Here, we analyze future fossil fuel electricity demand in 171 energy-emissions scenarios from Integrated Assessment Models (IAMs), evaluating the implicit retirements and/or reduced operation of generating infrastructure. Although IAMs calculate retirements endogenously, the structure and methods of each model differ; we use a standard approach to infer retirements in outputs from all six major IAMs and—unlike the IAMs themselves—we begin with the age distribution and region-specific operating capacities of the existing power fleet. We find that coal-fired power plants in scenarios consistent with international climate targets (i.e. keeping global warming well-below 2 °C or 1.5 °C) retire one to three decades earlier than historically has been the case. If plants are built to meet projected fossil electricity demand and instead allowed to operate at the level and over the lifetimes they have historically, the roughly 200 Gt CO _2 of additional emissions this century would be incompatible with keeping global warming well-below 2 °C. Thus, ambitious climate mitigation scenarios entail drastic, and perhaps un-appreciated, changes in the operating and/or retirement schedules of power infrastructure.

Increasing human demands for water, energy, food and materials, are expected to accentuate resource supply challenges over the coming decades. Experience suggests that long-term strategies for a single sector could yield both trade-offs and synergies for other sectors. Thus, long-term transition pathways for linked resource systems should be informed using nexus approaches. Global integrated assessment models can represent the synergies and trade-offs inherent in the exploitation of water, energy and land (WEL) resources, including the impacts of international trade and climate policies. In this study, we review the current state-of-the-science in global integrated assessment modeling with an emphasis on how models have incorporated integrated WEL solutions. A large-scale assessment of the relevant literature was performed using online databases and structured keyword search queries. The results point to the following main opportunities for future research and model development: (1) improving the temporal and spatial resolution of economic models for the energy and water sectors; (2) balancing energy and land requirements across sectors; (3) integrated representation of the role of distribution infrastructure in alleviating resource challenges; (4) modeling of solution impacts on downstream environmental quality; (5) improved representation of the implementation challenges stemming from regional financial and institutional capacity; (6) enabling dynamic multi-sectoral vulnerability and adaptation needs assessment; and (7) the development of fully-coupled assessment frameworks based on consistent, scalable, and regionally-transferable platforms. Improved database management and computational power are needed to address many of these modeling challenges at a global-scale.

In climate change research, future scenarios of greenhouse gas and air pollutant emissions generated by integrated assessment models (IAMs) are used in climate models (CMs) and earth system models to analyze future interactions and feedback between human activities and climate. However, the spatial resolutions of IAMs and CMs differ. IAMs usually disaggregate the world into 10-30 aggregated regions, whereas CMs require a grid-based spatial resolution. Therefore, downscaling emissions data from IAMs into a finer scale is necessary to input the emissions into CMs. In this study, we examined whether differences in downscaling methods significantly affect climate variables such as temperature and precipitation. We tested two downscaling methods using the same regionally aggregated sulfur emissions scenario obtained from the Asian-Pacific Integrated Model/Computable General Equilibrium (AIM/CGE) model. The downscaled emissions were fed into the Model for Interdisciplinary Research on Climate (MIROC). One of the methods assumed a strong convergence of national emissions intensity (e.g., emissions per gross domestic product), while the other was based on inertia (i.e., the base-year remained unchanged). The emissions intensities in the downscaled spatial emissions generated from the two methods markedly differed, whereas the emissions densities (emissions per area) were similar. We investigated whether the climate change projections of temperature and precipitation would significantly differ between the two methods by applying a field significance test, and found little evidence of a significant difference between the two methods. Moreover, there was no clear evidence of a difference between the climate simulations based on these two downscaling methods.

Clarifying characteristics of hazards and risks of climate change at 2 °C and 1.5 °C global warming is important for understanding the implications of the Paris Agreement. We perform and analyze large ensembles of 2 °C and 1.5 °C warming simulations. In the 2 °C runs, we find substantial increases in extreme hot days, heavy rainfalls, high streamflow and labor capacity reduction related to heat stress. For example, about half of the world’s population is projected to experience a present day 1-in-10 year hot day event every other year at 2 °C warming. The regions with relatively large increases of these four hazard indicators coincide with countries characterized by small CO _2 emissions, low-income and high vulnerability. Limiting global warming to 1.5 °C, compared to 2 °C, is projected to lower increases in the four hazard indicators especially in those regions.

The Paris Agreement set long-term global climate goals to pursue stabilization of the global mean temperature increase at below 2 °C (the so-called 2 °C goal). Individual countries submitted their own short-term targets, mostly for the year 2030. Meanwhile, the UN’s sustainable development goals (SDGs) were designed to help set multiple societal goals with respect to socioeconomic development, the environment, and other issues. Climate policies can lead to intended or unintended consequences in various sectors, but these types of side effects rarely have been studied in China, where climate policies will play an important role in global greenhouse gas emissions and sustainable development is a major goal. This study identified the extent to which climate policies in line with the 2 °C goal could have multi-sectoral consequences in China. Carbon constraints in China in the 2Deg scenario are set to align with the global 2 °C target based on the emissions per capita convergence principle. Carbon policies for NDC pledges as well as policies in China regarding renewables, air pollution control, and land management were also simulated. The results show that energy security and air quality have co-benefits related to climate policies, whereas food security and land resources experienced negative side effects (trade-offs). Near-term climate actions were shown to help reduce these trade-offs in the mid-term. A policy package that included food and land subsidies also helped achieve climate targets while avoiding the adverse side effects caused by the mitigation policies. The findings should help policymakers in China develop win–win policies that do not negatively affect some sectors, which could potentially enhance their ability to take climate actions to realize the global 2 °C goal within the context of sustainable development.

Currently, thermal power is the largest source of power in the world. Although the impacts of climate change on cooling water sufficiency in thermal power plants have been extensively assessed globally and regionally, their economic consequences have seldom been evaluated. In this study, the Asia-Pacific Integrated Model Computable General Equilibrium model (AIM/CGE) was used to evaluate the economic consequences of projected future cooling water insufficiency on a global basis, which was simulated using the H08 global hydrological model. This approach enabled us to investigate how the physical impacts of climate change on thermal power generation influence economic activities in regions and industrial sectors. To account for the uncertainty of climate change projections, five global climate models and two representative concentration pathways (RCPs 2.6 and 8.5) were used. The ensemble-mean results showed that the global gross domestic product (GDP) loss in 2070–2095 due to cooling water insufficiency in the thermal power sector was −0.21% (−0.12%) in RCP8.5 (RCP2.6). Among the five regions, the largest GDP loss of −0.57% (−0.27%) was observed in the Middle East and Africa. Medium-scale losses of −0.18% (−0.12%) and −0.14% (−0.12%) were found in OECD90 (the member countries of the Organization for Economic Co-operation and Development as of 1990) and Eastern Europe and the Former Soviet Union, respectively. The smallest losses of −0.05% (−0.06%) and −0.09% (−0.08%) were found in Latin America and Asia, respectively. The economic impact of cooling water insufficiency was non-negligible and should be considered as one of the threats induced by climate change.

The goal of limiting global temperature rise to “well below” 2 °C has been reaffirmed in the Paris Agreement on climate change at the 21st Conference of the Parties (COP21). Almost all countries submitted their decarbonization targets in their Intended Nationally Determined Contributions (INDC) to the United Nations Framework Convention on Climate Change (UNFCCC) and India did as well. India’s nationally determined contribution (NDC) aims to reduce greenhouse gas (GHG) emissions intensity of national GDP in 2030 by 33–35% compared to 2005. This paper analyzes how India’s NDC commitments compare with emission trajectories consistent with well below 2 °C and 1.5 °C global temperature stabilization goals. A top-down computable general equilibrium model is used for the analysis. Our analysis shows that there are significant emission gaps between NDC and global climate stabilization targets in 2030. The energy system requires significant changes, mostly relying on renewable energy and carbon capture and storage (CCS) technology. The mitigation costs would increase if India delays its abatement efforts and is locked into NDC pathways till 2030. India’s GHG emissions would peak 10 years earlier under 1.5 °C global temperature stabilization compared to the 2 °C goal. The results imply that India would need financial and technological support from developed countries to achieve emissions reductions aligned with the global long-term goal.

Thermoelectric power plants in inland regions use primarily riverine water for cooling. The future availability of riverine water will be affected by climatic change. Power generation is expected to grow throughout the 21st century, accompanied by growth in cooling water demand. We estimated cooling water sufficiency globally under the Shared Socioeconomic Pathway 2 scenario with and without climate mitigation throughout the 21st century (2006–2099) at a spatial resolution of 0.5° × 0.5°. We used the Asia-Pacific Integrated Model Computable General Equilibrium Model (AIM/CGE) to project future thermoelectric cooling-water requirements in 17 global regions with no hydrological constraint on water availability, and the H08 global hydrological model to assess whether consumptive water requirements could be met under particular spatiotemporal and hydrological constraints. The results show that cooling water sufficiency will decrease by 7.9% and 11.4% in 2040–2069 (11.3% and 18.6% in 2070–2099) with and without climate mitigation, respectively. A distinct difference was found between with and without climate mitigation in the Middle East and Africa. The predicted insufficiency was attributable primarily to changes in river flow regimes, particularly a general decrease in low flow levels, and to increased water requirements for thermoelectric power generation and other sectors. The results imply that the growing water demand projected by AIM/CGE will not be fulfilled sustainably in many parts of the world, hence considerable additional efforts of reducing water consumption will be required to secure electric power supply. This confirms the importance of coupling integrated assessment models and global hydrological models for consistent water-energy nexus analyses.

Energy demand associated with space heating and cooling is expected to be affected by climate change. There are several global projections of space heating and cooling use that take into consideration climate change, but a comprehensive uncertainty of socioeconomic and climate conditions, including a 1.5 °C global mean temperature change, has never been assessed. This paper shows the economic impact of changes in energy demand for space heating and cooling under multiple socioeconomic and climatic conditions. We use three shared socioeconomic pathways as socioeconomic conditions. For climate conditions, we use two representative concentration pathways that correspond to 4.0 °C and 2.0 °C scenarios, and a 1.5 °C scenario driven from the 2.0 °C scenario with assumption in conjunction with five general circulation models. We find that the economic impacts of climate change are largely affected by socioeconomic assumptions, and global GDP change rates range from +0.21% to −2.01% in 2100 under the 4.0 °C scenario, depending on the socioeconomic condition. Sensitivity analysis that differentiates the thresholds of heating and cooling degree days clarifies that the threshold is a strong factor that generates these differences. Meanwhile, the impact of the 1.5 °C is small regardless of socioeconomic assumptions (−0.02% to −0.06%). The economic loss caused by differences in socioeconomic assumption under the 1.5 °C scenario is much smaller than that under the 2 °C scenario, which implies that stringent climate mitigation can work as a risk hedge to socioeconomic development diversity.

The Paris Agreement is a milestone in international climate policy as it establishes a global mitigation framework towards 2030 and sets the ground for a potential 1.5 °C climate stabilization. To provide useful insights for the 2018 UNFCCC Talanoa facilitative dialogue, we use eight state-of-the-art climate-energy-economy models to assess the effectiveness of the Intended Nationally Determined Contributions (INDCs) in meeting high probability 1.5 and 2 °C stabilization goals. We estimate that the implementation of conditional INDCs in 2030 leaves an emissions gap from least cost 2 °C and 1.5 °C pathways for year 2030 equal to 15.6 (9.0–20.3) and 24.6 (18.5–29.0) GtCO _2 eq respectively. The immediate transition to a more efficient and low-carbon energy system is key to achieving the Paris goals. The decarbonization of the power supply sector delivers half of total CO _2 emission reductions in all scenarios, primarily through high penetration of renewables and energy efficiency improvements. In combination with an increased electrification of final energy demand, low-carbon power supply is the main short-term abatement option. We find that the global macroeconomic cost of mitigation efforts does not reduce the 2020–2030 annual GDP growth rates in any model more than 0.1 percentage points in the INDC or 0.3 and 0.5 in the 2 °C and 1.5 °C scenarios respectively even without accounting for potential co-benefits and avoided climate damages. Accordingly, the median GDP reductions across all models in 2030 are 0.4%, 1.2% and 3.3% of reference GDP for each respective scenario. Costs go up with increasing mitigation efforts but a fragmented action, as implied by the INDCs, results in higher costs per unit of abated emissions. On a regional level, the cost distribution is different across scenarios while fossil fuel exporters see the highest GDP reductions in all INDC, 2 °C and 1.5 °C scenarios.

The transport sector contributes around a quarter of global CO _2 emissions; thus, low-carbon transport policies are required to achieve the 2 °C and 1.5 °C targets. In this paper, representative transport policy scenarios are structured with the aim of achieving a better understanding of the interaction between the transport sector and the macroeconomy. To accomplish this, the Asia–Pacific Integrated Model/Transport (AIM/Transport) model, coupled with a computable general equilibrium model (AIM/CGE), is used to simulate the potential for different transport policy interventions to reduce emissions and cost over the period 2005–2100. The results show that deep decarbonization in the transport sector can be achieved by implementing transport policies such as energy efficiency improvements, vehicle technology innovations particularly the deployment of electric vehicles, public transport developments, and increasing the car occupancy rate. Technological transformations such as vehicle technological innovations and energy efficiency improvements provide the most significant reduction potential. The key finding is that low-carbon transport policies can reduce the carbon price, gross domestic product loss rate, and welfare loss rate generated by climate mitigation policies to limit global warming to 2 °C and 1.5 °C. Interestingly, the contribution of transport policies is more effective for stringent climate change targets in the 1.5 °C scenario, which implies that the stronger the mitigation intensity, the more transport specific policy is required. The transport sector requires attention to achieve the goal of stringent climate change mitigation.

Climate change mitigation to limit warming to 1.5 °C or well below 2 °C, as suggested by the Paris Agreement, can rely on large-scale deployment of land-related measures (e.g. afforestation, or bioenergy production). This can increase food prices, and hence raises food security concerns. Here we show how an inclusive policy design can avoid these adverse side-effects. Food-security support through international aid, bioenergy tax, or domestic reallocation of income can shield impoverished and vulnerable people from the additional risk of hunger that would be caused by the economic effects of policies narrowly focussing on climate objectives only. In the absence of such support, 35% more people might be at risk of hunger by 2050 (i.e. 84 million additional people) in a 2 °C-consistent scenario. The additional global welfare changes due to inclusive climate policies are small (

Seawater desalination is a promising approach to satisfying water demand in coastal countries suffering from water scarcity. To clarify its potential future global scale, we perform a detailed investigation of the economic feasibility of desalination development for different countries using a feasibility index (Fi) that reflects a comparison between the price of water and the cost of production. We consider both past and future time periods. For historical validation, Fi is first evaluated for nine major desalination countries; its variation is in good agreement with the actual historical development of desalination in these countries on both spatial and temporal scales. We then simulate the period of 2015–2050 for a Shared Socioeconomic Pathway (SSP2) and two climate scenarios. Our projected results suggest that desalination will become more feasible for countries undergoing continued development by 2050. The corresponding total global desalination population will increase by 3.2-fold in 2050 compared to the present (from 551.6 × 106 in 2015 to 1768 × 106). The major spread of seawater desalination to more countries and its availability to larger populations is mainly attributed to the diminishing production costs and increasing water prices in these countries under the given socioeconomic/climate scenarios.

The exposure of workers to hot environments is expected to increase as a result of climate change. In order to prevent heat-related illness, it is recommended that workers take breaks during working hours. However, this would lead to reductions in worktime and labor productivity. In this study, we estimate the economic cost of heat-related illness prevention through worker breaks associated with climate change under a wide range of climatic and socioeconomic conditions. We calculate the worktime reduction based on the recommendation of work/rest ratio and the estimated future wet bulb glove temperature, which is an index of heat stresses. Corresponding GDP losses (cost of heat-related illness prevention through worker breaks) are estimated using a computable general equilibrium model throughout this century. Under the highest emission scenario, GDP losses in 2100 will range from 2.6 to 4.0% compared to the current climate conditions. On the other hand, GDP losses will be less than 0.5% if the 2.0 °C goal is achieved. The benefit of climate-change mitigation for avoiding worktime loss is comparable to the cost of mitigation (cost of the greenhouse gas emission reduction) under the 2.0 °C goal. The relationship between the cost of heat-related illness prevention through worker breaks and global average temperature rise is approximately linear, and the difference in economic loss between the 1.5 °C goal and the 2.0 °C goal is expected to be approximately 0.3% of global GDP in 2100. Although climate mitigation and socioeconomic development can limit the vulnerable regions and sectors, particularly in developing countries, outdoor work is still expected to be affected. The effectiveness of some adaptation measures such as additional installation of air conditioning devices or shifting the time of day for working are also suggested. In order to reduce the economic impacts, adaptation measures should also be implemented as well as pursing ambitious climate change mitigation targets.

This study analyzed the role of low-carbon energy technologies in reducing the greenhouse gas emissions of Indonesia’s energy sector by 2030. The aim of this study was to provide insights into the Indonesian government’s approach to developing a strategy and plan for mitigating emissions and achieving Indonesia’s emission reduction targets by 2030, as pledged in the country’s Intended Nationally Determined Contribution. The Asia-Pacific Integrated Model/Computable General Equilibrium (AIM/CGE) model was used to quantify three scenarios that had the same socioeconomic assumptions: baseline, countermeasure (CM)1, and CM2, which had a higher emission reduction target than that of CM1. Results of the study showed that an Indonesian low-carbon energy system could be achieved with two pillars, namely, energy efficiency measures and deployment of less carbon-intensive energy systems (i.e., the use of renewable energy in the power and transport sectors, and the use of natural gas in the power sector and in transport). Emission reductions would also be satisfied through the electrification of end-user consumption where the electricity supply becomes decarbonized by deploying renewables for power generation. Under CM1, Indonesia could achieve a 15.5% emission reduction target (compared to the baseline scenario). This reduction could be achieved using efficiency measures that reduce final energy demand by 4%; This would require the deployment of geothermal power plants at a rate six times greater than the baseline scenario and four times the use of hydropower than that used in the baseline scenario. Greater carbon reductions (CM2; i.e., a 27% reduction) could be achieved with similar measures to CM1 but with more intensive penetration. Final energy demand would need to be cut by 13%, deployment of geothermal power plants would need to be seven times greater than at baseline, and hydropower use would need to be five times greater than the baseline case. Carbon prices under CM1 and CM2 were US$16 and US$63 (2005)/tCO2, respectively. The mitigation scenarios for 2030 both had a small positive effect on gross domestic product (GDP) compared to the baseline scenario (0.6% and 0.3% for CM1 and CM2, respectively). This is mainly due to the combination of two assumptions. The first is that there would be a great increase in coal-fired power in the baseline scenario. The other assumption is that there is low productivity in coal-related industries. Eventually, when factors such as capital and labor shift from coal-related industries to other low-carbon-emitting sectors in the CM cases are put in place, the total productivity of the economy would offset low-carbon investment.

This study contributes to the realization of intended nationally determined contributions (INDCs) by analyzing their implications for the energy production system and the economy, and determines the role of renewable energies (RE) in reducing the challenge of committing to the INDCs. The Asia-Pacific Integrated Model/Computable General Equilibrium (AIM/CGE) model was used to assess seven scenarios having the same socioeconomic development but different shares of RE in power generation. By comparing different relative reductions caused by the emission constraints vis-a-vis the business-as-usual (BaU) scenario, the mitigation costs can be estimated. Results show that the economic impact could be reduced by around 55% in terms of welfare loss (from 6.0% to 2.7%) and by around 36% in terms of gross domestic product (GDP) loss (from 3.4% to 2.1%) through the incorporation of high levels of renewable energy. Furthermore, the additional double deployment of wind and SPV to 5.4% and 12.0%, respectively, which currently comprise 43.1% of the renewable energies used in electricity generation, could reduce the GDP loss from 2.1% to 1.9% and reduce the welfare loss from 2.7% to 1.5% in order to achieve a 25.0% GHG emissions reduction. These losses are less than those in the pricing-only scenario (2.1% and 2.3%, respectively).

Under the Paris Agreement, parties set and implement their own emissions targets as nationally determined contributions (NDCs) to tackle climate change. International carbon emissions trading is expected to reduce global mitigation costs. Here, we show the benefit of emissions trading under both NDCs and a more ambitious reduction scenario consistent with the 2 °C goal. The results show that the global welfare loss, which was measured based on estimated household consumption change in 2030, decreased by 75% (from 0.47% to 0.16%), as a consequence of achieving NDCs through emissions trading. Furthermore, achieving the 2 °C targets without emissions trading led to a global welfare loss of 1.4%–3.4%, depending on the burden-sharing scheme used, whereas emissions trading reduced the loss to around 1.5% (from 1.4% to 1.7%). These results indicate that emissions trading is a valuable option for the international system, enabling NDCs and more ambitious targets to be achieved in a cost-effective manner.

Each country’s Intended Nationally Determined Contribution (INDC) pledges an emission target for 2025 or 2030. Here, we evaluated the INDC inter-generational and inter-regional equity by comparing scenarios with INDC emissions target in 2030 and with an immediate emission reduction associated with a global uniform carbon price using Asian-Pacific Integrated Model/Computable General Equilibrium. Both scenarios eventually achieve 2 °C target. The results showed that, as compared with an immediate emission reduction scenario, the inter-generational equity status is not favorable for INDC scenario and the future generation suffers more from delayed mitigation. Moreover, this conclusion was robust to the wide range of inequality aversion parameter that determines discount rate. On the other hand, the INDC scenario has better inter-regional equity in the early part of the century than does the immediate emission reduction scenario in which we assume a global carbon price during the period up to 2030. However, inter-regional equity worsens later in the century. The additional emissions reduction to the INDC in 2030 would improve both inter- and inter-regional equity as compared to the current INDC. We also suggest that countries should commit to more emissions reductions in the follow-up INDC communications and that continuous consideration for low-income countries is needed for global climate change cooperation after 2030.

We present a model comparison study that combines multiple integrated assessment models with a reduced-form global air quality model to assess the potential co-benefits of global climate mitigation policies in relation to the World Health Organization (WHO) goals on air quality and health. We include in our assessment, a range of alternative assumptions on the implementation of current and planned pollution control policies. The resulting air pollution emission ranges significantly extend those in the Representative Concentration Pathways. Climate mitigation policies complement current efforts on air pollution control through technology and fuel transformations in the energy system. A combination of stringent policies on air pollution control and climate change mitigation results in 40% of the global population exposed to PM levels below the WHO air quality guideline; with the largest improvements estimated for India, China, and Middle East. Our results stress the importance of integrated multisector policy approaches to achieve the Sustainable Development Goals.

Shared socioeconomic pathways (SSPs) are being developed internationally for cross-sectoral assessments of climate change impacts, adaptation, and mitigation. These are five scenarios that include both qualitative and quantitative information for mitigation and adaptation challenges to climate change. In this study, we quantified scenarios for the risk of hunger in the 21st century using SSPs, and clarified elements that influence future hunger risk. There were two primary findings: (1) risk of hunger in the 21st-century greatly differed among five SSPs; and (2) population growth, improvement in the equality of food distribution within a country, and increases in food consumption mainly driven by income growth greatly influenced future hunger risk and were important elements in its long-term assessment.

This study assessed the health burden attributable to childhood underweight through 2050 focusing on disability-adjusted life years (DALYs), by considering the latest scenarios for climate change studies (representative concentration pathways and shared socioeconomic pathways (SSPs)) and conducting sensitivity analysis. A regression model for estimating DALYs attributable to childhood underweight (DAtU) was developed using the relationship between DAtU and childhood stunting. We combined a global computable general equilibrium model, a crop model, and two regression models to assess the future health burden. We found that (i) world total DAtU decreases from 2005 by 28 ∼ 63% in 2050 depending on the socioeconomic scenarios. Per capita DAtU also decreases in all regions under either scenario in 2050, but the decreases vary significantly by regions and scenarios. (ii) The impact of climate change is relatively small in the framework of this study but, on the other hand, socioeconomic conditions have a great impact on the future health burden. (iii) Parameter uncertainty of the regression models is the second largest factor on uncertainty of the result following the changes in socioeconomic condition, and uncertainty derived from the difference in global circulation models is the smallest in the framework of this study.