Evaluating the regional risks to food availability and access from land-based climate policies in an integrated assessment model.

Mitigating greenhouse gas emissions is necessary to reduce the overall negative climate change impacts on crop yields and agricultural production. However, certain mitigation measures may generate unintended consequences to food availability and food access due to both land use competition and economic burden of mitigation. Integrated assessment models (IAM) are generally used to evaluate these policies; however, currently these models may not capture the importance of income and food prices for hunger and overall economic wellbeing. Here, we implement a measure of food security that captures the nutritional and economic aspects as the total expenditures on staple foods divided by income and weighted by total caloric consumption in an IAM, the global change analysis model (GCAM4.0). We then project consumer prices and our measure of food security along the shared socioeconomic pathways. Sustained economic growth underpins increases in caloric consumption and lowering expenditures on staple foods. Strict conservation policies affect food accessibility in a larger number of developing countries, whereas the negative effects of pricing terrestrial emissions are more concentrated on the poor in Sub-Saharan Africa, by substantially replacing their cropland with forests and affecting the production of key staples. Supplementary Information: The online version contains supplementary material available at 10.1007/s10669-022-09860-4.

Decision-first modeling should guide decision making for emerging risks.

An emerging risk is characterized by scant published data, rapidly changing information, and an absence of existing models that can be directly used for prediction. Analysis may be further complicated by quickly evolving decision-maker priorities and the potential need to make decisions quickly as new information comes available. To provide a forum to discuss these challenges, a virtual conference, "Decision Making for Emerging Risks," was held on June 22-23, 2021, sponsored jointly by the Decision Analysis Society of the Institute for Operations Research and the Management Sciences and the Decision Analysis and Risk specialty group in the Society for Risk Analysis. Speakers reflected on the work to support decision-makers related to the COVID-19 pandemic as well as experiences in emerging risks across domains from cybersecurity, infrastructure, transportation, energy, food safety, national security, and climate change. Here, we distill the key findings to propose a set of best practice principles for a "decision-first" approach for emerging risks. These discussions underscore the importance of scoping the decision context and the shared responsibility for the development and implementation of the analysis between the analyst and the decision-maker when the context can evolve rapidly. Emerging risks may also favor simpler analytical approaches that increase transparency, ease of explanation, and ability to conduct new analyses quickly. Continued dialogue by the decision and risk analysis communities on the use and development of models for emerging risks will enhance the credibility and usefulness of these approaches.

Climate mitigation policies and the potential pathways to conflict: Outlining a research agenda.

Climate policies will need to incentivize transformative societal changes if they are to achieve emission reductions consistent with 1.5°C temperature targets. To contribute to efforts for aligning climate policy with broader societal goals, specifically those related to sustainable development, we identify the effects of climate mitigation policy on aspects of socioeconomic development that are known determinants of conflict and evaluate the plausibility and importance of potential pathways to armed conflict and political violence. Conditional on preexisting societal tensions and socioeconomic vulnerabilities, we isolate effects on economic performance, income and livelihood, food and energy prices, and land tenure as most likely to increase conflict risks. Climate policy designs may be critical to moderate these risks as different designs can promote more favorable societal outcomes such as equity and inclusion. Coupling research with careful monitoring and evaluation of the intermediate societal effects at early stages of policy implementation will be a critical part of learning and moderating potential conflict risks. Importantly, better characterizing the future conflict risks under climate policy allows for a more comprehensive comparison to the conflict risk if mitigation is not implemented and graver climate damages are experienced. This article is categorized under:The Carbon Economy and Climate Mitigation > Benefits of Mitigation.

Government effectiveness and institutions as determinants of tropical cyclone mortality.

Strong institutions as well as economic development are generally understood to play critical roles in protecting societies from the adverse impacts of natural hazards, such as tropical cyclones. The independent effect of institutions on reducing these risks, however, has not been confirmed empirically in previous global studies. As a storm's path and intensity influence the severity of the damages and may be spatially correlated with human vulnerabilities, failing to accurately capture physical exposure in an econometric analysis may result in imprecise and biased estimates of the influence of the independent variables. Here, we develop an approach to control for physical exposure by spatially interacting meteorological and socioeconomic data for over 1,000 tropical cyclone disasters from 1979 to 2016. We find evidence that higher levels of national government effectiveness are associated with lower tropical cyclone mortality, even when controlling for average income and other socioeconomic conditions. Within countries, deaths are higher when strong winds are concentrated over areas of the country with elevated infant mortality rates, an indicator of institutional effectiveness through public service delivery. These results suggest that policies and programs to enhance institutional capacity and governance can support risk reduction from extreme weather events.

Usable Science for Managing the Risks of Sea-Level Rise.

Sea-level rise sits at the frontier of usable climate climate change research, because it involves natural and human systems with long lags, irreversible losses, and deep uncertainty. For example, many of the measures to adapt to sea-level rise involve infrastructure and land-use decisions, which can have multigenerational lifetimes and will further influence responses in both natural and human systems. Thus, sea-level science has increasingly grappled with the implications of (1) deep uncertainty in future climate system projections, particularly of human emissions and ice sheet dynamics; (2) the overlay of slow trends and high-frequency variability (e.g., tides and storms) that give rise to many of the most relevant impacts; (3) the effects of changing sea level on the physical exposure and vulnerability of ecological and socioeconomic systems; and (4) the challenges of engaging stakeholder communities with the scientific process in a way that genuinely increases the utility of the science for adaptation decision making. Much fundamental climate system research remains to be done, but many of the most critical issues sit at the intersection of natural sciences, social sciences, engineering, decision science, and political economy. Addressing these issues demands a better understanding of the coupled interactions of mean and extreme sea levels, coastal geomorphology, economics, and migration; decision-first approaches that identify and focus research upon those scientific uncertainties most relevant to concrete adaptation choices; and a political economy that allows usable science to become used science.

Evaluation of environmental health benefits of China's building energy conservation policies: an integrated assessment on national and provincial levels.

This article evaluates the effect of energy conservation policies and carbon mitigation efforts on reducing health damage in China's building sector, which has been long ignored. The study bases on both national and provincial levels. To evaluate the health damage effect, we use domestic data by region to ensure the reliability of the evaluation. Results show that in the co-control scenario, the GDP loss saved from health benefit in 2020, 2030, and 2050 is 0.13 %, 0.16 %, and 0.23 %, respectively, compared to reference scenario. At a provincial level, extra health benefit of 16, 16, 33, 25, and 23 RMB/person can be observed for Beijing, Heilongjiang, Guangdong, Henan, and Qinghai owing to energy conservation, even with the strictest end-of-pipe control measures. The results confirm the significant effect of energy conservation efforts on reducing the health damage in China's building sector at both national and provincial levels.

Bridging Research and Policy on Climate Change and Conflict.

PURPOSE OF REVIEW: This special issue on "Bridging Research and Policy on Climate Change and Conflict" brings together the results of a 2018 workshop organized by the Peace Research Institute, Oslo (PRIO) and the Wilson Center with six papers that address different aspects of the translation of the research on climate change and conflict to policy and practice. Here, we provide an overview of the workshop and papers to highlight key opportunities and challenges to linking the climate-conflict scholarship with pressing issues in diplomacy, development, and security. RECENT FINDINGS: Multiple methods, especially comparative case studies, should be applied to elucidate the more complex mechanisms of the climate-conflict link. This approach may also enhance engagement with the policymakers who draw on examples and narratives. There is also a need for both predictive models that capture contextual factors and policy interactions as well as decision-support tools, such as integrated assessment models, that can be used to test the implications of different theories and models in the literature. SUMMARY: Scholars should engage the policy community to formulate research questions that are more policy relevant, such as the effectiveness of interventions. There is also the need for models and frameworks that help practitioners synthesize the academic results. Practitioners are encouraged to leverage the comparative advantages of academic researchers in new policy and projects to inform data collection and future analysis of effectiveness.

An Expert Elicitation of the Proliferation Resistance of Using Small Modular Reactors (SMR) for the Expansion of Civilian Nuclear Systems.

To facilitate the use of nuclear energy globally, small modular reactors (SMRs) may represent a viable alternative or complement to large reactor designs. One potential benefit is that SMRs could allow for more proliferation resistant designs, manufacturing arrangements, and fuel-cycle practices at widespread deployment. However, there is limited work evaluating the proliferation resistance of SMRs, and existing proliferation assessment approaches are not well suited for these novel arrangements. Here, we conduct an expert elicitation of the relative proliferation resistance of scenarios for future nuclear energy deployment driven by Generation III+ light-water reactors, fast reactors, or SMRs. Specifically, we construct the scenarios to investigate relevant technical and institutional features that are postulated to enhance the proliferation resistance of SMRs. The experts do not consistently judge the scenario with SMRs to have greater overall proliferation resistance than scenarios that rely on conventional nuclear energy generation options. Further, the experts disagreed on whether incorporating a long-lifetime sealed core into an SMR design would strengthen or weaken proliferation resistance. However, regardless of the type of reactor, the experts judged that proliferation resistance would be enhanced by improving international safeguards and operating several multinational fuel-cycle facilities rather than supporting many more national facilities.

Characterizing the Long-Term PM2.5 Concentration-Response Function: Comparing the Strengths and Weaknesses of Research Synthesis Approaches.

The magnitude, shape, and degree of certainty in the association between long-term population exposure to ambient fine particulate matter (PM2.5 ) and the risk of premature death is one of the most intensely studied issues in environmental health. For regulatory risk analysis, this relationship is described quantitatively by a concentration-response (C-R) function that relates exposure to ambient concentrations with the risk of premature mortality. Four data synthesis techniques develop the basis for, and derive, this function: systematic review, expert judgment elicitation, quantitative meta-analysis, and integrated exposure-response (IER) assessment. As part of an academic workshop aiming to guide the use of research synthesis approaches, we developed criteria with which to evaluate and select among the approaches for their ability to inform policy choices. These criteria include the quality and extent of scientific support for the method, its transparency and verifiability, its suitability to the policy problem, and the time and resources required for its application. We find that these research methods are both complementary and interdependent. A systematic review of the multidisciplinary evidence is a starting point for all methods, providing the broad conceptual basis for the nature, plausibility, and strength of the associations between PM exposure and adverse health effects. Further, for a data-rich application like PM2.5 and premature mortality, all three quantitative approaches can produce estimates that are suitable for regulatory and benefit analysis. However, when fewer data are available, more resource-intensive approaches such as expert elicitation may be more important for understanding what scientists know, where they agree or disagree, and what they believe to be the most important areas of uncertainty. Whether implicitly or explicitly, all require considerable judgment by scientists. Finding ways for all these methods to acknowledge, appropriately elicit, and examine the implications of that judgment would be an important step forward for research synthesis.

Using backup generators for meeting peak electricity demand: a sensitivity analysis on emission controls, location, and health endpoints.

Generators installed for backup power during blackouts could help satisfy peak electricity demand; however, many are diesel generators with nonnegligible air emissions that may damage air quality and human health. The full (private and social) cost of using diesel generators with and without emission control retrofits for fine particulate matter (PM2.5) and nitrogen oxides (NOx) were compared with a new natural gas turbine peaking plant. Lower private costs were found for the backup generators because the capital costs are mostly ascribed to reliability. To estimate the social costs from air quality, the changes in ambient concentrations of ozone (O3) and PM2.5 were modeled using the Particulate Matter Comprehensive Air Quality Model with extensions (PMCAMx) chemical transport model. These air quality changes were translated to their equivalent human health effects using concentration-response functions and then into dollars using estimates of "willingness-to-pay" to avoid ill health. As a case study, 1000 MW of backup generation operating for 12 hr/day for 6 days in each of four eastern U.S. cities (Atlanta, Chicago, Dallas, and New York) was modeled. In all cities, modeled PM2.5 concentrations increased (up to 5 microg/m3) due mainly to primary emissions. Smaller increases and decreases were observed for secondary PM2.5 with more variation between cities. Increases in NOx, emissions resulted in significant nitrate formation (up to 1 microg/m3) in Atlanta and Chicago. The NOx emissions also caused O3 decreases in the urban centers and increases in the surrounding areas. For PM2.5, a social cost of approximately $2/kWh was calculated for uncontrolled diesel generators in highly populated cities but was under 10 cent/kWh with PM2.5 and NOx controls. On a full cost basis, it was found that properly controlled diesel generators are cost-effective for meeting peak electricity demand. The authors recommend NOx and PM2.5 controls.

The costs, air quality, and human health effects of meeting peak electricity demand with installed backup generators.

Existing generators installed for backup during blackouts could be operated during periods of peak electricity demand, increasing grid reliability and supporting electricity delivery. Many generators, however, have non-negligible air emissions and may potentially damage air quality and harm human health. To evaluate using these generators, we compare the levelized private and social (health) costs of diesel internal combustion engines (ICE) with and without diesel particulate filters (DPF), natural gas ICEs, and microturbines to a new peaking plant in New York, NY. To estimate the social cost, first we calculate the upper range emissions for each generator option from producing 36,000 megawatt-hours (MWh) of electricity over 3 days. We then convert the emissions into ambient concentrations with a 3-D chemical transport model, PMCAMx, and Gaussian dispersion plumes. Using a Monte Carlo approach to incorporate the uncertainties, we calculate the health endpoints using concentration-response functions and multiply the response by its economic value. While uncontrolled diesel ICEs would harm air quality and health, a generator with a DPF has a social cost, comparable to natural gas options. We conclude on a full cost basis that backup generators, including controlled diesel ICEs, are a cost-effective method of meeting peak demand.