Assessing synergies and trade-offs of diverging Paris-compliant mitigation strategies with long-term SDG objectives.

The Sustainable Development Goals (SDGs) and the Paris Agreement are the two transformative agendas, which set the benchmarks for nations to address urgent social, economic and environmental challenges. Aside from setting long-term goals, the pathways followed by nations will involve a series of synergies and trade-offs both between and within these agendas. Since it will not be possible to optimise across the 17 SDGs while simultaneously transitioning to low-carbon societies, it will be necessary to implement policies to address the most critical aspects of the agendas and understand the implications for the other dimensions. Here, we rely on a modelling exercise to analyse the long-term implications of a variety of Paris-compliant mitigation strategies suggested in the recent scientific literature on multiple dimensions of the SDG Agenda. The strategies included rely on technological solutions such as renewable energy deployment or carbon capture and storage, nature-based solutions such as afforestation and behavioural changes in the demand side. Results for a selection of energy-environment SDGs suggest that some mitigation pathways could have negative implications on food and water prices, forest cover and increase pressure on water resources depending on the strategy followed, while renewable energy shares, household energy costs, ambient air pollution and yield impacts could be improved simultaneously while reducing greenhouse gas emissions. Overall, results indicate that promoting changes in the demand side could be beneficial to limit potential trade-offs.

Local mortality impacts due to future air pollution under climate change scenarios.

The health impacts of global climate change mitigation will affect local populations differently. However, most co-benefits analyses have been done at a global level, with relatively few studies providing local level results. We aimed to quantify the local health impacts due to fine particles (PM2.5) under the governance arrangements embedded in the Shared Socioeconomic Pathways (SSPs1-5) under two greenhouse gas concentration scenarios (Representative Concentration Pathways (RCPs) 2.6 and 8.5) in local populations of Mozambique, India, and Spain. We simulated the SSP-RCP scenarios using the Global Change Analysis Model, which was linked to the TM5-FASST model to estimate PM2.5 levels. PM2.5 levels were calibrated with local measurements. We used comparative risk assessment methods to estimate attributable premature deaths due to PM2.5 linking local population and mortality data with PM2.5-mortality relationships from the literature, and incorporating population projections under the SSPs. PM2.5 attributable burdens in 2050 differed across SSP-RCP scenarios, and sensitivity of results across scenarios varied across populations. Future attributable mortality burden of PM2.5 was highly sensitive to assumptions about how populations will change according to SSP. SSPs reflecting high challenges for adaptation (SSPs 3 and 4) consistently resulted in the highest PM2.5 attributable burdens mid-century. Our analysis of local PM2.5 attributable premature deaths under SSP-RCP scenarios in three local populations highlights the importance of both socioeconomic development and climate policy in reducing the health burden from air pollution. Sensitivity of future PM2.5 mortality burden to SSPs was particularly evident in low- and middle- income country settings due either to high air pollution levels or dynamic populations.

Dynamic Linking of Upstream Energy and Freight Demands for Bio and Fossil Energy Pathways in the Global Change Analysis Model.

Comprehensive study of the environmental impacts associated with demand for an energy resource or carrier in any one sector requires a full consideration of the direct and indirect impacts on the rest of the regional and global energy system. Biofuels are especially complex since they have feedbacks to both the energy system and to regional and global crop markets. In this study, we present a strategy for dynamically including the upstream energy and transportation links to the Global Change Analysis Model. We incorporate the following inter-sectoral linkages: energy inputs to crop production, energy inputs to fossil resource production, and freight transport requirements of energy and agricultural commodities. We assess the implications of explicitly including these links by measuring the global impacts of increased corn ethanol demand in the United States with and without these links included. Although the net global impact of the upstream links on energy and emissions are relatively modest in the scenarios analyzed, the inclusion of these links illustrates interesting trade-offs in energy and transportation demand among fossil fuel and agriculture sectors. We find that the increment in agricultural energy driven by the additional biofuel production associated with the corn ethanol shock is higher than the decrease of energy associated with the displaced fossil fuel consumption. However, this effect is compensated by the reduction in freight transportation requirements of energy. These sectoral interactions suggest that this level of modeling detail could be important in evaluating future analytical questions.

Guidelines for Modeling and Reporting Health Effects of Climate Change Mitigation Actions.

BACKGROUND: Modeling suggests that climate change mitigation actions can have substantial human health benefits that accrue quickly and locally. Documenting the benefits can help drive more ambitious and health-protective climate change mitigation actions; however, documenting the adverse health effects can help to avoid them. Estimating the health effects of mitigation (HEM) actions can help policy makers prioritize investments based not only on mitigation potential but also on expected health benefits. To date, however, the wide range of incompatible approaches taken to developing and reporting HEM estimates has limited their comparability and usefulness to policymakers. OBJECTIVE: The objective of this effort was to generate guidance for modeling studies on scoping, estimating, and reporting population health effects from climate change mitigation actions. METHODS: An expert panel of HEM researchers was recruited to participate in developing guidance for conducting HEM studies. The primary literature and a synthesis of HEM studies were provided to the panel. Panel members then participated in a modified Delphi exercise to identify areas of consensus regarding HEM estimation. Finally, the panel met to review and discuss consensus findings, resolve remaining differences, and generate guidance regarding conducting HEM studies. RESULTS: The panel generated a checklist of recommendations regarding stakeholder engagement: HEM modeling, including model structure, scope and scale, demographics, time horizons, counterfactuals, health response functions, and metrics; parameterization and reporting; approaches to uncertainty and sensitivity analysis; accounting for policy uptake; and discounting. DISCUSSION: This checklist provides guidance for conducting and reporting HEM estimates to make them more comparable and useful for policymakers. Harmonization of HEM estimates has the potential to lead to advances in and improved synthesis of policy-relevant research that can inform evidence-based decision making and practice. https://doi.org/10.1289/EHP6745.

Health co-benefits and mitigation costs as per the Paris Agreement under different technological pathways for energy supply.

This study assesses the reductions in air pollution emissions and subsequent beneficial health effects from different global mitigation pathways consistent with the 2 °C stabilization objective of the Paris Agreement. We use an integrated modelling framework, demonstrating the need for models with an appropriate level of technology detail for an accurate co-benefit assessment. The framework combines an integrated assessment model (GCAM) with an air quality model (TM5-FASST) to obtain estimates of premature mortality and then assesses their economic cost. The results show that significant co-benefits can be found for a range of technological options, such as introducing a limitation on bioenergy, carbon capture and storage (CCS) or nuclear power. Cumulative premature mortality may be reduced by 17-23% by 2020-2050 compared to the baseline, depending on the scenarios. However, the ratio of health co-benefits to mitigation costs varies substantially, ranging from 1.45 when a bioenergy limitation is set to 2.19 when all technologies are available. As for regional disaggregation, some regions, such as India and China, obtain far greater co-benefits than others.

Health co-benefits from air pollution and mitigation costs of the Paris Agreement: a modelling study.

BACKGROUND: Although the co-benefits from addressing problems related to both climate change and air pollution have been recognised, there is not much evidence comparing the mitigation costs and economic benefits of air pollution reduction for alternative approaches to meeting greenhouse gas targets. We analysed the extent to which health co-benefits would compensate the mitigation cost of achieving the targets of the Paris climate agreement (2°C and 1·5°C) under different scenarios in which the emissions abatement effort is shared between countries in accordance with three established equity criteria. METHODS: Our study had three stages. First, we used an integrated assessment model, the Global Change Assessment Model (GCAM), to investigate the emission (greenhouse gases and air pollutants) pathways and abatement costs of a set of scenarios with varying temperature objectives (nationally determined contributions, 2°C, or 1·5°C) and approaches to the distribution of climate change methods (capability, constant emission ratios, and equal per capita). The resulting emissions pathways were transferred to an air quality model (TM5-FASST) to estimate the concentrations of particulate matter and ozone in the atmosphere and the resulting associated premature deaths and morbidity. We then applied a monetary value to these health impacts by use of a term called the value of statistical life and compared these values with those of the mitigation costs calculated from GCAM, both globally and regionally. Our analysis looked forward to 2050 in accordance with the socioeconomic narrative Shared Socioeconomic Pathways 2. FINDINGS: The health co-benefits substantially outweighed the policy cost of achieving the target for all of the scenarios that we analysed. In some of the mitigation strategies, the median co-benefits were double the median costs at a global level. The ratio of health co-benefit to mitigation cost ranged from 1·4 to 2·45, depending on the scenario. At the regional level, the costs of reducing greenhouse gas emissions could be compensated with the health co-benefits alone for China and India, whereas the proportion the co-benefits covered varied but could be substantial in the European Union (7-84%) and USA (10-41%), respectively. Finally, we found that the extra effort of trying to pursue the 1·5°C target instead of the 2°C target would generate a substantial net benefit in India (US$3·28-8·4 trillion) and China ($0·27-2·31 trillion), although this positive result was not seen in the other regions. INTERPRETATION: Substantial health gains can be achieved from taking action to prevent climate change, independent of any future reductions in damages due to climate change. Some countries, such as China and India, could justify stringent mitigation efforts just by including health co-benefits in the analysis. Our results also suggest that the statement in the Paris Agreement to pursue efforts to limit temperature increase to 1·5°C could make economic sense in some scenarios and countries if health co-benefits are taken into account. FUNDING: European Union's Horizon 2020 research and innovation programme.