China, the world’s largest greenhouse gas emitter in 2022, aims to achieve carbon neutrality by 2060. The power sector will play a major role in this decarbonization process due to its current reliance on coal. Prior studies have quantified air quality co-benefits from decarbonization or investigated pathways to eliminate greenhouse gas emissions from the power sector. However, few have jointly assessed the potential impacts of accelerating decarbonization on electric power systems and public health. Additionally, most analyses have treated air quality improvements as co-benefits of decarbonization, rather than a target during decarbonization. Here, we explore future energy technology pathways in China under accelerated decarbonization scenarios with a power system planning model that integrates carbon, pollutant, and health impacts. We integrate the health effects of power plant emissions into the power system decision-making process, quantifying the public health impacts of decarbonization under each scenario. We find that compared with a reference decarbonization pathway, a stricter cap (20% lower emissions than the reference pathway in each period) on carbon emissions would yield significant co-benefits to public health, leading to a 22% reduction in power sector health impacts. Although extra capital investment is required to achieve this low emission target, the value of climate and health benefits would exceed the additional costs, leading to $824 billion net benefits from 2021 to 2050. Another accelerated decarbonization pathway that achieves zero emissions five years earlier than the reference case would result in lower net benefits due to higher capital costs during earlier decarbonization periods. Treating air pollution impacts as a target in decarbonization can further mitigate both CO2emissions and negative health effects. Alternative low-cost solutions also show that small variations in system costs can result in significantly different future energy portfolios, suggesting that diverse decarbonization pathways are viable.
We estimate the climate value of offshore wind energy with a highly flexible, forward-looking method that estimates the value in a consistent manner under a range of policies, including carbon caps and taxes. Backward looking methods measure the damages avoided due to emissions reductions attributed to renewable energy under an existing policy structure. Under a carbon cap, however, the climate value of offshore wind energy comes entirely from reducing the cost of meeting the cap. Our method for estimating the prospective climate value compares both
- NSF-PAR ID:
- 10360470
- Publisher / Repository:
- IOP Publishing
- Date Published:
- Journal Name:
- Environmental Research Letters
- Volume:
- 15
- Issue:
- 5
- ISSN:
- 1748-9326
- Page Range / eLocation ID:
- Article No. 054003
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Sea level rise (SLR) may impose substantial economic costs to coastal communities worldwide, but characterizing its global impact remains challenging because SLR costs depend heavily on natural characteristics and human investments at each location – including topography, the spatial distribution of assets, and local adaptation decisions. To date, several impact models have been developed to estimate the global costs of SLR. Yet, the limited availability of open-source and modular platforms that easily ingest up-to-date socioeconomic and physical data sources restricts the ability of existing systems to incorporate new insights transparently. In this paper, we present a modular, open-source platform designed to address this need, providing end-to-end transparency from global input data to a scalable least-cost optimization framework that estimates adaptation and net SLR costs for nearly 10 000 global coastline segments and administrative regions. Our approach accounts both for uncertainty in the magnitude of global mean sea level (g.m.s.l.) rise and spatial variability in local relative sea level rise. Using this platform, we evaluate costs across 230 possible socioeconomic and SLR trajectories in the 21st century. According to the latest Intergovernmental Panel on Climate Change Assessment Report (AR6), g.m.s.l. is likely to rise during the 21st century by 0.40–0.69 m if late-century warming reaches 2 ∘C and by 0.58–0.91 m with 4 ∘C of warming (Fox-Kemper et al., 2021). With no forward-looking adaptation, we estimate that annual costs of sea level rise associated with a 2 ∘C scenario will likely fall between USD 1.2 and 4.0 trillion (0.1 % and 1.2 % of GDP, respectively) by 2100, depending on socioeconomic and sea level rise trajectories. Cost-effective, proactive adaptation would provide substantial benefits, lowering these values to between USD 110 and USD 530 billion (0.02 and 0.06 %) under an optimal adaptation scenario. For the likely SLR trajectories associated with 4 ∘C warming, these costs range from USD 3.1 to 6.9 trillion (0.3 % and 2.0 %) with no forward-looking adaptation and USD 200 billion to USD 750 billion (0.04 % to 0.09 %) under optimal adaptation. The Intergovernmental Panel on Climate Change (IPCC) notes that deeply uncertain physical processes like marine ice cliff instability could drive substantially higher global sea level rise, potentially approaching 2.0 m by 2100 in very high emission scenarios. Accordingly, we also model the impacts of 1.5 and 2.0 m g.m.s.l. rises by 2100; the associated annual cost estimates range from USD 11.2 to 30.6 trillion (1.2 % and 7.6 %) under no forward-looking adaptation and USD 420 billion to 1.5 trillion (0.08 % to 0.20 %) under optimal adaptation. Our modeling platform used to generate these estimates is publicly available in an effort to spur research collaboration and support decision-making, with segment-level physical and socioeconomic input characteristics provided at https://doi.org/10.5281/zenodo.7693868 (Bolliger et al., 2023a) and model results at https://doi.org/10.5281/zenodo.7693869 (Bolliger et al., 2023b).more » « less
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Abstract Growing global food demands place major strains on water resources, including quality impairments and increased water scarcity. Drawing on the largely separate bodies of literature on externalities and technological innovation, this article develops a dynamic framework to explore the long‐term impacts of alternative policy approaches to the agricultural impacts on water resources. Environmental policies, which focus on correcting environmental externalities, lead to an overall gain because costs to farmers are more than offset by reduced environmental damages. Technology policies, which direct public investments into agricultural eco‐innovations, lead to benefits for farmers as well as the environment. Joint implementation of both types of policies leads to the largest overall gain. In principle, a technology policy alone could have greater environmental benefits than an environmental policy alone. This outcome is most likely in cases where the productivity effect of new technology is large and the cost of research is low.
Recommendations for research managers As an alternative to traditional environmental policy, investments in research can provide win–win solutions that benefit the environment and agricultural producers.
Conceivably, eco‐innovations could lead to environmental conditions that are better than those achieved by environmental policy alone.
Adding research investments to existing environmental policy would lead to further improvements in environmental quality while also benefitting farmers.
Unlike environmental policies that are perceived to impose costs on agriculture, technology policies impart benefits to farmers and are less likely to face political opposition from industry.
Technology policies are likely to be the most effective when eco‐innovation leads to technologies that meaningfully reduce environmental impacts and also raise farm productivity.
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Abstract The combined impacts of climate change and ecological degradation are expected to worsen inequality within society. These dynamics are exemplified by increases in flood risk globally. In general, low‐income and socially vulnerable populations disproportionately bear the cost of flood damages. Climate change is expected to increase the number of people exposed to fluvial flood risk and cause greater property damages. Floodplain restoration has the potential to mitigate these impacts, but the distribution of future risks among different types of property owners under these altered conditions is often unknown.
Here, we develop a simple probabilistic approach for estimating flood risk to property owners under floodplain restoration and climate change scenarios for a range of flood recurrence intervals. We apply this approach in the Vermont, USA portion of the Lake Champlain Basin.
Over a 100‐year time horizon, we estimate that the value of property damages caused by flood inundation is approximately $2.13 billion under the baseline scenario. Climate change is expected to increase damages to $5.29 billion, a 148% increase; however, floodplain restoration has the potential to reduce these impacts by approximately 20%.
For all scenarios, a larger proportion of lower‐value properties, specifically mobile homes, face greater flood risk compared to higher‐value properties. Climate change is expected to cost higher‐value properties and commercial properties more than other types of properties, but these same groups are also expected to benefit most from floodplain restoration.
In general, these results raise concern that those least able to prepare for and recover from flood damages are also the people who face the greatest threats. In response, public policy interventions must consider not only where flood risk is most severe, but also the vulnerability of people exposed to such risk.
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