In June 2015, China announced its post-2020 reduction targets, its central element being the intention to peak CO2 emissions by 2030 or earlier. China has implemented several policies to reduce its ...greenhouse gas (GHG) emissions. This study provides emission projections for China up to 2030 given current policies and a selected set of enhanced policies, and compares the results with projected CO2 emission trajectories that are consistent with the announced target for 2030. The projections are based on existing scenarios and energy system and land use model calculations. We project that the 2030 CO2 emission level consistent with a peak in CO2 emissions by 2030 ranges from 11.3 to 11.8 GtCO2. The corresponding total GHG emission level ranges from 13.5 to 14.0 GtCO2e in 2030. Current policies are likely not to be sufficient to achieve the 2030 targets, as our projected total GHG emission level under current policies ranges from 14.7 to 15.4 GtCO2e by 2030. However, an illustrative set of enhancement policy measures, all of which are related to national priorities, leads to projected GHG emission levels from 13.1 to 13.7 GtCO2e by 2030 – and thus below the levels necessary for peaking CO2 emissions before 2030.
•China has announced its intention to peak CO2 emissions by 2030 or earlier.•The peak in greenhouse gas emissions would reach 35–40% above 2010 levels.•Current policies are likely not to be sufficient to meet the announced 2030 target.•The expected emission levels reach about 50% above 2010 levels.•Our selected enhancement policy measures lead to peaking CO2 emissions before 2030.
The bottom-up approach of the Nationally Determined Contributions (NDCs) in the Paris Agreement has led countries to self-determine their greenhouse gas (GHG) emission reduction targets. The planned ...‘ratcheting-up’ process, which aims to ensure that the NDCs comply with the overall goal of limiting global average temperature increase to well below 2 °C or even 1.5 °C, will most likely include some evaluation of ‘fairness’ of these reduction targets. In the literature, fairness has been discussed around equity principles, for which many different effort-sharing approaches have been proposed. In this research, we analysed how country-level emission targets and carbon budgets can be derived based on such criteria. We apply novel methods directly based on the global carbon budget, and, for comparison, more commonly used methods using GHG mitigation pathways. For both, we studied the following approaches: equal cumulative per capita emissions, contraction and convergence, grandfathering, greenhouse development rights and ability to pay. As the results critically depend on parameter settings, we used the wide authorship from a range of countries included in this paper to determine default settings and sensitivity analyses. Results show that effort-sharing approaches that (i) calculate required reduction targets in carbon budgets (relative to baseline budgets) and/or (ii) take into account historical emissions when determining carbon budgets can lead to (large) negative remaining carbon budgets for developed countries. This is the case for the equal cumulative per capita approach and especially the greenhouse development rights approach. Furthermore, for developed countries, all effort-sharing approaches except grandfathering lead to more stringent budgets than cost-optimal budgets, indicating that cost-optimal approaches do not lead to outcomes that can be regarded as fair according to most effort-sharing approaches.
Afforestation is considered a cost‐effective and readily available climate change mitigation option. In recent studies afforestation is presented as a major solution to limit climate change. However, ...estimates of afforestation potential vary widely. Moreover, the risks in global mitigation policy and the negative trade‐offs with food security are often not considered. Here we present a new approach to assess the economic potential of afforestation with the IMAGE 3.0 integrated assessment model framework. In addition, we discuss the role of afforestation in mitigation pathways and the effects of afforestation on the food system under increasingly ambitious climate targets. We show that afforestation has a mitigation potential of 4.9 GtCO2/year at 200 US$/tCO2 in 2050 leading to large‐scale application in an SSP2 scenario aiming for 2°C (410 GtCO2 cumulative up to 2100). Afforestation reduces the overall costs of mitigation policy. However, it may lead to lower mitigation ambition and lock‐in situations in other sectors. Moreover, it bears risks to implementation and permanence as the negative emissions are increasingly located in regions with high investment risks and weak governance, for example in Sub‐Saharan Africa. Afforestation also requires large amounts of land (up to 1,100 Mha) leading to large reductions in agricultural land. The increased competition for land could lead to higher food prices and an increased population at risk of hunger. Our results confirm that afforestation has substantial potential for mitigation. At the same time, we highlight that major risks and trade‐offs are involved. Pathways aiming to limit climate change to 2°C or even 1.5°C need to minimize these risks and trade‐offs in order to achieve mitigation sustainably.
Afforestation is often presented as a key climate change mitigation option, but potential risks and trade‐offs are generally disregarded. In this study we show afforestation has large potential for mitigation, which could reduce overall costs. However, we also show there could be major risks regarding implementation and permanence as well as large trade‐offs with food security. Pathways aiming to limit climate change to 2°C or even 1.5°C need to minimize these risks and trade‐offs in order to achieve mitigation sustainably.
By 15 December 2015, 187 countries had submitted their Intended Nationally Determined Contributions (INDCs) summarising their climate actions after 2020 in the context of the Paris Agreement. We used ...a unified framework to assess the mitigation components of INDCs covering 105 countries (representing approximately 91 % of global greenhouse gas emissions in 2012) with a special focus on the G20 economies. We estimated the required reduction effort by comparing the greenhouse gas emission targets implied by the INDCs with the projected levels resulting from current mitigation policies. The resulting projected global reduction effort amounts to approximately 4–6 GtCO
2
eq by 2030, of which the G20 economies are responsible for the largest share, in particular Brazil, China, the EU, and the United States. Despite these reductions, the global and G20 emission level is still projected to be higher in 2030 than it was in 2010. We compared the ambition levels of individual INDCs by analysing various indicators. Our analysis shows, for instance, that INDCs imply that greenhouse gas emissions of Brazil, Indonesia, Mexico, and South Korea peak before 2025, and of China, India and South Africa by 2030 or later.
•Downscaling PBs to the national level increases their policy relevance.•We use allocation approaches from the climate change literature on effort sharing.•Diverging equity considerations play out ...differently for countries and PBs.•Environmental footprints of EU, US, China & India are mostly higher than scaled PBs.•Methodology and results can inform national target setting for global SDG ambitions.
The planetary boundaries (PBs) framework proposes global quantitative precautionary limits for human perturbation of nine critical Earth system processes. Together they define a global safe operating space for human development. Translating the global limits to the national level increases their policy relevance. Such translation essentially divides up the global safe operating space. What is considered fair distribution is a political decision and there is no globally agreed principle that can be applied. Here, we analyse the distributional consequences of alternative perspectives on distributive fairness. We scale the global limits of selected PBs to resource budgets for the EU, US, China and India, using three allocation approaches from the climate change literature. Furthermore, we compare the allocated budgets to 2010 environmental footprints of the four economies, to assess their performance with respect to the selected PBs. The allocation approaches are based on (1) current shares of global environmental pressure (‘grandfathering’); (2) ‘equal per capita’ shares, and (3) ‘ability to pay’ to reduce environmental pressure. The results show that the four economies are not living within the global safe operating space. Their 2010 environmental footprints are larger than the allocated budgets for all approaches and parameterisations analysed for the PBs for climate change and biogeochemical flows, and, except for India, also for the PB for biosphere integrity. Grandfathering was found to be most favourable for the EU and US for all PBs, and ability to pay as least favourable. For climate change and biogeochemical flows, ability to pay even resulted in negative resource budgets for the two economies. In contrast, for China and India, equal per capita allocation and ability to pay were most favourable. Results were sensitive to the parameterisation. Accounting for future population growth in the equal per capita approach benefits India, with lower budgets for the EU, US and China, while accounting for future economic growth in ability to pay benefits the EU and US, with lower budgets for China and India. Our results underline the need for all four economies to act, while hinting at diverging preferences for specific allocation approaches. The methodology and results may help countries to define policy targets in line with global ambitions, such as those defined by the Sustainable Development Goals (SDGs), accounting for differences in countries’ circumstances and capacities. Further attention is required for PB-specific allocation approaches and integration of biophysical and socioeconomic considerations in the allocation.
Nearly 900 million people in Sub-Saharan Africa rely on traditional biomass for cooking, with negative impacts on health, biodiversity and the climate. In this study, we use the IMAGE ...modellingframework to construct two sets of scenarios for promoting clean cooking solutions. In the first set, specific policy options to promote clean cooking are evaluated, while in the second the SDG target to achieve universal access to modern cooking energy by 2030 is imposed. The study adds knowledge to understanding the impact of individual policy options on access to clean cooking solutions, and provides insight into synergies and trade-offs of achieving the SDG targets on human health, biodiversity and climate change. The results show that, in the absence of coordinated actions, enabling policies and scaled-up finance, the number of people in Sub-Saharan Africa relying on traditional biomass cookstoves could amount to 660–820 million by 2030. Subsidies on specific clean cooking technologies or fuels could increase their use substantially, but could hinder the uptake of alternative clean cooking fuels or technologies. Meeting the SDG target has considerable social, environmental and economic benefits, and could even lead to lower total fuel expenditures. However, investments in cookstoves need to be quadrupled relative to baseline.
•Baseline trends leave a billion people without access to modern cooking fuels.•Phasing-out traditional biomass may lead to lower total cost of cooking.•Clean cooking solutions could save the lives of 100 thousand children in 2030.•Harvesting biomass for cooking increases the risk of local forest degradation.•Halting the use of traditional biomass cuts emissions from cooking by at least half.
Determining international climate mitigation response strategies is a complex task. Integrated Assessment Models support this process by analysing the interplay of the most relevant factors, ...including socio-economic developments, climate system uncertainty, damage estimates, mitigation costs and discount rates. Here, we develop a meta-model that disentangles the uncertainties of these factors using full literature ranges. This model allows comparing insights of the cost-minimising and cost-benefit modelling communities. Typically, mitigation scenarios focus on minimum-cost pathways achieving the Paris Agreement without accounting for damages; our analysis shows doing so could double the initial carbon price. In a full cost-benefit setting, we show that the optimal temperature target does not exceed 2.5 °C when considering medium damages and low discount rates, even with high mitigation costs. With low mitigation costs, optimal temperature change drops to 1.5 °C or less. The most important factor determining the optimal temperature is the damage function, accounting for 50% of the uncertainty.
Measures that aim to reduce greenhouse gas emissions also have impacts on achieving other Sustainable Development Goals (SDGs). Given the enormous challenge of achieving the goals of the Paris ...Agreement and the SDGs, insight into these impacts provides information on how to improve the feasibility of climate change mitigation measures by maximizing the co-benefits and managing the risks of possible trade-offs across SDGs. In this paper, we explore the impact of 20 promising climate mitigation measures on achieving the other SDGs for 11 world regions. Using the IMAGE modelling framework, the paper explores the GHG emission reduction potential of these measures aggregated by the sector under three scenarios. Based on peer-reviewed articles, the impact of the measures on other SDGs is assessed for the top three sectors with the highest GHG reduction potential in each region. We conclude that the number of synergies between the selected climate change mitigation measures and other SDGs dwarf the number of trade-offs in all regions. The magnitude of these synergies and trade-offs, however, varies by regional and socio-economic context. In high- and middle-income regions, the mitigation measures show few trade-offs that are generally associated with technology choices that could aggravate inequality and impact biodiversity. In low-income regions, some measures, especially land-use related ones, could interfere with efforts to reduce poverty, end hunger and improve well-being, if not complemented by additional policies that aim to protect the poor from increasing food and energy prices.
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