Associations Between Simulated Future Changes in Climate, Air Quality, and Human Health

Is Pollution the Primary Driver of Infectious Syndemics?

Syndemics, the adverse interaction of two or more coterminous diseases or other negative health conditions, have probably existed since human settlement, plant and animal domestication, urbanization, and the growth of social inequality beginning about 10-12,000 years ago. These dramatic changes in human social evolution significantly increased opportunities for the spread of zoonotic infectious diseases in denser human communities with increased sanitation challenges. In light of a growing body of research that indicates that anthropogenic air pollution causes numerous threats to health and is taking a far greater toll on human life and wellbeing than had been reported, this paper proposes the possibility that air pollution is now the primary driver of infectious disease syndemics. In support of this assertion, this paper reviews the growth and health impacts of air pollution, the relationship of air pollution to the development and spread of infectious diseases, and reported cases of air pollution-driven infectious disease syndemics, and presents public health recommendations for leveraging the biosocial insight of syndemic theory in responding to infectious disease.

China's carbon-neutral policies will reduce short-term PM2.5-associated excess incidence of cardiovascular diseases

China's carbon-neutral target could have benefits for ambient fine particulate matter (PM2.5)-associated mortality. Although previous studies have researched such benefits, the potential impact on cardiovascular disease incidence burden is yet to be investigated thoroughly. Here, we first estimate the association between short-term PM2.5 exposure and the incidence of stroke and coronary heart disease (CHD) via a case-crossover study before projecting future changes in short-term PM2.5-associated excess incidence across China from 2025 to 2060 under three different emission scenarios. We find that, compared to the 2015-2020 baseline, average PM2.5 concentrations nationwide in 2060 under SSP119 (an approximation of a carbon-neutral scenario) are projected to decrease by 81.07%. The short-term PM2.5-related excess incidence of stroke and CHD is projected to be reduced to 3,352 cases (95% confidence interval: 939, 5,738)-compared with 34,485 cases under a medium-emissions scenario (SSP245)-and is expected to be accompanied by a 95% reduction in the related economic burden. China's carbon-neutral policies are likely to bring health benefits for cardiovascular disease by reducing short-term PM2.5-related incidence burden.

Ozone-related acute excess mortality projected to increase in the absence of climate and air quality controls consistent with the Paris Agreement

Short-term exposure to ground-level ozone in cities is associated with increased mortality and is expected to worsen with climate and emission changes. However, no study has yet comprehensively assessed future ozone-related acute mortality across diverse geographic areas, various climate scenarios, and using CMIP6 multi-model ensembles, limiting our knowledge on future changes in global ozone-related acute mortality and our ability to design targeted health policies. Here, we combine CMIP6 simulations and epidemiological data from 406 cities in 20 countries or regions. We find that ozone-related deaths in 406 cities will increase by 45 to 6,200 deaths/year between 2010 and 2014 and between 2050 and 2054, with attributable fractions increasing in all climate scenarios (from 0.17% to 0.22% total deaths), except the single scenario consistent with the Paris Climate Agreement (declines from 0.17% to 0.15% total deaths). These findings stress the need for more stringent air quality regulations, as current standards in many countries are inadequate.

Attribution of fine particulate matter and ozone health impacts in Canada to domestic and US emission sources

Exposure to ambient air pollution is associated with a wide range of adverse health effects such as respiratory symptoms, cardiovascular events, and premature mortality. Canada and the United States (US) have worked collaboratively for decades to address transboundary air pollution and its impacts across their shared border. To inform transboundary air quality considerations, we conducted modelling to attribute health impacts from ambient PM2.5 and O3 exposure in Canada to Canadian and US emission sources. We employed emissions, chemical transport, and health impacts modelling for 2015, 2025, and 2035 using a brute-force modelling approach whereby anthropogenic domestic and US emissions were reduced separately by 20 % or 100 %, and the resulting changes in health impacts were estimated across Canada. We find that transboundary PM2.5 and O3 related health impacts vary widely by region, with >80 % of impacts occurring in Central Canada, and most health impacts occurring within 200-300 km of the Canada-US border. The relative contribution of US sources to O3 in Canada is larger than for PM2.5, yet we find that the health impacts from transboundary PM2.5 exceeded those from transboundary O3. Nationally, we estimate that roughly one in five PM2.5 deaths in Canada is attributable to US sources (2000 deaths in 2015) and more than one in two O3 deaths are attributable to US sources (roughly 800 to 1200 deaths in 2015). We project health impacts from domestic and US sources to increase from 2025 to 2035 in Canada. Our results suggest that there are substantial benefits to be gained by domestic and international strategies to reduce PM2.5 in the Canada-US transboundary region.

The Social Cost of Ozone-Related Mortality Impacts From Methane Emissions

Atmospheric methane directly affects surface temperatures and indirectly affects ozone, impacting human welfare, the economy, and environment. The social cost of methane (SC-CH4) metric estimates the costs associated with an additional marginal metric ton of emissions. Current SC-CH4 estimates do not consider the indirect impacts associated with ozone production from changes in methane. We use global model simulations and a new BenMAP webtool to estimate respiratory-related deaths associated with increases in ozone from a pulse of methane emissions in 2020. By using an approach consistent with the current SC-CH4 framework, we monetize and discount annual damages back to present day values. We estimate that the methane-ozone mechanism is attributable to 760 (95% CI: 330-1200) respiratory-related deaths per million metric tons of methane globally, for a global net present damage of $1800/mT (95% CI: $760-$2800/Mt CH4; 2% Ramsey discount rate); this would double the current SC-CH4 if included. These physical impacts are consistent with recent studies, but comparing direct costs is challenging. Economic damages are sensitive to uncertainties in the exposure and health risks associated with tropospheric ozone, assumptions about future projections of NOx emissions, socioeconomic conditions, and mortality rates, monetization parameters, and other factors. Our estimates are highly sensitive to uncertainties in ozone health risks. We also develop a reduced form model to test sensitivities to other parameters. The reduced form tool runs with a user-supplied emissions pulse, as well as socioeconomic and precursor projections, enabling future integration of the methane-ozone mechanism into the SC-CH4 modeling framework.

Air Pollution and Arrhythmias

Air pollution is commonly defined as the contamination of the air we breathe by any chemical, physical, or biological agent that is potentially threatening to human and ecosystem health. The common pollutants known to be disease-causing are particulate matter, ground-level ozone, sulphur dioxide, nitrogen dioxide, and carbon monoxide. Although the association between increasing concentrations of these pollutants and cardiovascular disease is now accepted, the association of air pollution and arrhythmias is less well established. In this review we provide an in-depth discussion of the association of acute and chronic air pollution exposure and arrhythmia incidence, morbidity, and mortality, and the purported pathophysiological mechanisms. Increases in concentrations of air pollutants have multiple proarrhythmic mechanisms including systemic inflammation (via increases in reactive oxygen species, tumour necrosis factor, and direct effects from translocated particulate matter), structural remodelling (via an increased risk of atherosclerosis and myocardial infarction or by affecting the cell-to-cell coupling and gap junction function), and mitochondrial and autonomic dysfunction. Furthermore, we describe the associations of air pollution and arrhythmias. There is a strong correlation of acute and chronic air pollutant exposure and the incidence of atrial fibrillation. Acute increases in air pollution increase the risk of emergency room visits and hospital admissions for atrial fibrillation and the risk of stroke and mortality in patients with atrial fibrillation. Similarly, there is a strong correlation of increases of air pollutants and the risk of ventricular arrhythmias, out-of-hospital cardiac arrest, and sudden cardiac death.

Association Between Exposure to Ozone (O3) and the Short-Term Effect on Tuberculosis Outpatient Visits: A Time-Series Study in 16 Cities of Anhui Province, China

Introduction

Evidence has shown that air pollutant exposure plays a vital role in the progression of tuberculosis (TB). The aim of this research was to assess the short-term effects of ozone (O₃) exposure and TB outpatient visits in 16 prefecture-level cities of Anhui, China, 2015-2020.

Methods

Distributed lag nonlinear model (DLNM), Poisson generalized linear regression model and random effects model were applied in this study. The effects of different age and gender on TB were investigated by stratified analysis, and then we performed sensitivity analyses to verify the stability of the results.

Results

A total of 186,623 active TB cases were registered from January 1, 2015 to December 31,2020 in Anhui. The average concentration of ozone is 92.77 ± 42.95 μg/m³. The maximum lag-specific and cumulative relative risk (RR) of TB outpatient visits was 1.0240 (95% CI: 1.0170-1.0310, lag 28 days) for each 10 µg/m³ increase in O₃ in the single-pollutant model. Estimation for 16 prefecture-level cities indicated that the strong association between O₃ and the risk of TB outpatient visits was in tongling (RR = 1.0555, 95% CI: 1.0089-1.1042), Suzhou (RR = 1.0475, 95% CI: 1.0268-1.0687), wuhu (RR = 1.0358, 95% CI: 1.0023-1.0704). Stratified analysis showed that the health effects of ozone exposure remained significant in male and older adults, and there was no significant association between exposure to ozone in children and adolescents and the risk of tuberculosis.

Discussion

We found that ozone exposure increases the risk of TB infection in outpatient patients, with males and the elderly being more susceptible, and it is necessary for government departments to develop targeted publicity and prevention measures in response to the local air quality conditions.

Estimating future PM2.5-attributed acute myocardial infarction incident cases under climate mitigation and population change scenarios in Shandong Province, China

BACKGROUND

The effects of fine particulate matter (PM2.5) on acute myocardial infarction (AMI) have been widely recognized. However, no studies have comprehensively evaluated future PM2.5-attributed AMI burdens under different climate mitigation and population change scenarios. We aimed to quantify the PM2.5-AMI association and estimate the future change in PM2.5-attributed AMI incident cases under six integrated scenarios in 2030 and 2060 in Shandong Province, China.

METHODS

Daily AMI incident cases and air pollutant data were collected from 136 districts/counties in Shandong Province from 2017 - 2019. A two-stage analysis with a distributed lag nonlinear model was conducted to quantify the baseline PM2.5-AMI association. The future change in PM2.5-attributed AMI incident cases was estimated by combining the fitted PM2.5-AMI association with the projected daily PM2.5 concentrations under six integrated scenarios. We further analyzed the factors driving changes in PM2.5-related AMI incidence using a decomposition method.

RESULTS

Each 10 μg/m3 increase in PM2.5 exposure at lag05 was related to an excess risk of 1.3 % (95 % confidence intervals: 0.9 %, 1.7 %) for AMI incidence from 2017 - 2019 in Shandong Province. The estimated total PM2.5-attributed AMI incident cases would increase by 10.9-125.9 % and 6.4-244.6 % under Scenarios 1 - 3 in 2030 and 2060, whereas they would decrease by 0.9-5.2 % and 33.0-46.2 % under Scenarios 5 - 6 in 2030 and 2060, respectively. Furthermore, the percentage increases in PM2.5-attributed female cases (2030: -0.3 % to 135.1 %; 2060: -33.2 % to 321.5 %) and aging cases (2030: 15.2-171.8 %; 2060: -21.5 % to 394.2 %) would wholly exceed those in male cases (2030: -1.8 % to 133.2 %; 2060: -41.1 % to 264.3 %) and non-aging cases (2030: -41.0 % to 45.7 %; 2060: -89.5 % to -17.0 %) under six scenarios in 2030 and 2060. Population aging is the main driver of increased PM2.5-related AMI incidence under Scenarios 1 - 3 in 2030 and 2060, while improved air quality can offset these negative effects of population aging under the implementation of the carbon neutrality and 1.5 °C targets.

CONCLUSION

The combination of ambitious climate policies (i.e., 1.5 °C warming limits and carbon neutrality targets) with stringent clean air policies is necessary to reduce the health impacts of air pollution in Shandong Province, China, regardless of population aging.

Child-focused climate change and health content in medical schools and pediatric residencies

Anthropogenic climate change-driven primarily by the combustion of fossil fuels that form greenhouse gases-has numerous consequences that impact health, including extreme weather events of accelerating frequency and intensity (e.g., wildfires, thunderstorms, droughts, and heat waves), mental health sequelae of displacement from these events, and the increase in aeroallergens and other pollutants. Children are especially vulnerable to climate-related exposures given that they are still developing, encounter higher exposures compared to adults, and are at risk of losing many healthy future years of life. In order to better meet the needs of generations of children born into a world affected by climate change, medical trainees must develop their knowledge of the relationships between climate change and children's health-with a focus on applying that information in clinical practice. This review provides an overview of salient climate change and children's health topics that medical school and pediatric residency training curricula should cover. In addition, it highlights the strengths and limitations of existing medical school and residency climate change and pediatric health curricula. IMPACT: Provides insight into the current climate change and pediatric health curricular opportunities for medical trainees in North America at both the medical school and residency levels. Condenses climate change and pediatric health material relevant to trainees to help readers optimize curricula at their institutions.

Identifying a suitable model for predicting hourly pollutant concentrations by using low-cost microstation data and machine learning

Accurately predicting the concentration of PM_2.5 (fine particles with a diameter of 2.5 μm or less) is essential for health risk assessment and formulation of air pollution control strategies. At present, there is also a large amount of air pollution data. How to efficiently mine its hidden features to obtain the future concentration of pollutants is very important for the prevention and control of air pollution. Therefore we build a pollutant prediction model based on Lightweight Gradient Boosting Model (LightGBM) shallow machine learning and Long Short-Term Memory (LSTM) neural network. Firstly, the PM_2.5 pollutant concentration data of 34 air quality stations in Beijing and the data of 18 weather stations were matched in time and space to obtain an input data set. Subsequently, the input data set was cleaned and preprocessed, and the training set was obtained by methods such as input feature extraction, input factor normalization, and data outlier processing. The hourly PM_2.5 concentration value prediction was achieved in accordance with experiments conducted with the hourly PM_2.5 data of Beijing from January 1, 2018 to October 1, 2020. Ultimately, the optimal hourly series prediction results were obtained after model comparisons. Through the comparison of these two models, it is found that the RMSE predicted by LSTM model for each pollutant is nearly 50% lower than that of LightGBM, and is more consistent with the fitting curve between the actual observations. The exploration of the input step size of LSTM model found that the accuracy of 3-h input data was higher than that of 12-h input data. It can be used for the management and decision-making of environmental protection departments and the formulation of preventive measures for emergency pollution incidents.

Global Health Impacts for Economic Models of Climate Change: A Systematic Review and Meta-Analysis

Rationale: Avoiding excess health damages attributable to climate change is a primary motivator for policy interventions to reduce greenhouse gas emissions. However, the health benefits of climate mitigation, as included in the policy assessment process, have been estimated without much input from health experts. Objectives: In accordance with recommendations from the National Academies in a 2017 report on approaches to update the social cost of greenhouse gases (SC-GHG), an expert panel of 26 health researchers and climate economists gathered for a virtual technical workshop in May 2021 to conduct a systematic review and meta-analysis and recommend improvements to the estimation of health impacts in economic-climate models. Methods: Regionally resolved effect estimates of unit increases in temperature on net all-cause mortality risk were generated through random-effects pooling of studies identified through a systematic review. Results: Effect estimates and associated uncertainties varied by global region, but net increases in mortality risk associated with increased average annual temperatures (ranging from 0.1% to 1.1% per 1°C) were estimated for all global regions. Key recommendations for the development and utilization of health damage modules were provided by the expert panel and included the following: not relying on individual methodologies in estimating health damages; incorporating a broader range of cause-specific mortality impacts; improving the climate parameters available in economic models; accounting for socioeconomic trajectories and adaptation factors when estimating health damages; and carefully considering how air pollution impacts should be incorporated in economic-climate models. Conclusions: This work provides an example of how subject-matter experts can work alongside climate economists in making continued improvements to SC-GHG estimates.

Health and Clinical Impacts of Air Pollution and Linkages with Climate Change

Air Pollution Impacts and Climate Change LinksAs part of the NEJM Group series on climate change, Keswani and colleagues review the linkages between climate change and air pollution and suggest strategies that clinicians may use to mitigate the adverse health impacts of air pollution.

Global climate change and human health: Pathways and possible solutions

Global warming has been changing the planet's climate pattern, leading to increasing frequency, intensity and duration of extreme weather events and natural disasters. These climate-changing events affect various health outcomes adversely through complicated pathways. This paper reviews the main signs of climate change so far, e.g., suboptimal ambient temperature, sea-level rise and other conditions, and depicts the interactive pathways between different climate-changing events such as suboptimal temperature, wildfires, and floods with a broad range of health outcomes. Meanwhile, the modifying effect of socioeconomic, demographic and environmental factors on the pathways is summarised, such that the youth, elderly, females, poor and those living in coastal regions are particularly susceptible to climate change. Although Earth as a whole is expected to suffer from climate change, this review article discusses some potential benefits for certain regions, e.g., a more liveable environment and sufficient food supply. Finally, we summarise certain mitigation and adaptation strategies against climate change and how these strategies may benefit human health in other ways. This review article provides a comprehensive and concise introduction of the pathways between climate change and human health and possible solutions, which may map directions for future research.

Flexible Bayesian Ensemble Machine Learning Framework for Predicting Local Ozone Concentrations

3D-grid-based chemical transport models, such as the Community Multiscale Air Quality (CMAQ) modeling system, have been widely used for predicting concentrations of ambient air pollutants. However, typical horizontal resolutions of nationwide CMAQ simulations (12 × 12 km2) cannot capture local-scale gradients for accurately assessing human exposures and environmental justice disparities. In this study, a Bayesian ensemble machine learning (BEML) framework, which integrates 13 learning algorithms, was developed for downscaling CMAQ estimates of ozone daily maximum 8 h averages to the census tract level, across the contiguous US, and was demonstrated for 2011. Three-stage hyperparameter tuning and targeted validations were designed to ensure the ensemble model's ability to interpolate, extrapolate, and capture concentration peaks. The Shapley value metric from coalitional game theory was applied to interpret the drivers of subgrid gradients. The flexibility (transferability) of the 2011-trained BEML model was further tested by evaluating its ability to estimate fine-scale concentrations for other years (2012-2017) without retraining. To demonstrate the feasibility of using the BEML approach to strictly "data-limited" situations, the model was applied to downscale CMAQ outputs for a future-year scenario-based simulation that considers effects of variations in meteorology associated with climate change.

The Role of Temperature in Modifying the Risk of Ozone-Attributable Mortality under Future Changes in Climate: A Proof-of-Concept Analysis

Air pollution risk assessments typically estimate ozone-attributable mortality counts using concentration-response (C-R) parameters from epidemiologic studies that treat temperature as a potential confounder. However, some recent epidemiologic studies have indicated that temperature can modify the relationship between short-term ozone exposure and mortality, which has potentially important implications when considering the impacts of climate change on public health. This proof-of-concept analysis quantifies counts of temperature-modified ozone-attributable mortality using temperature-stratified C-R parameters from a multicity study in which the pooled ozone-mortality effect coefficients change in concert with daily temperature. Meteorology downscaled from two global climate models is used with a photochemical transport model to simulate ozone concentrations over the 21st century using two emission inventories: one holding air pollutant emissions constant at 2011 levels and another accounting for reduced emissions through the year 2040. The late century climate models project increased summer season temperatures, which in turn yields larger total counts of ozone-attributable deaths in analyses using temperature-stratified C-R parameters compared to the traditional temperature confounder approach. This analysis reveals substantial heterogeneity in the magnitude and distribution of the temperature-stratified ozone-attributable mortality results, which is a function of regional variability in both the C-R relationship and the model-predicted temperature and ozone.

Modeling future asthma attributable to fine particulate matter (PM2.5) in a changing climate: a health impact assessment

Exposure to fine particulate matter (PM_2.5) is associated with asthma development as well as asthma exacerbation in children. PM_2.5 can be directly emitted or can form in the atmosphere from pollutant precursors. PM_2.5 emitted and formed in the atmosphere is influenced by meteorology; future changes in climate may alter the concentration and distribution of PM_2.5. Our aim is to estimate the future burden of climate change and PM_2.5 on new and exacerbated cases of childhood asthma. Projected concentrations of PM_2.5 are based on the Geophysical Fluid Dynamics Laboratory Coupled Model version 3 climate model, the Representative Concentration Pathway 8.5 greenhouse gas scenario, and two air pollution emissions datasets: a 2011 emissions dataset and a 2040 emissions dataset that reflects substantial reductions in emissions of PM_2.5 as compared to the 2011 inventory. We estimate additional PM_2.5-attributable asthma as well as PM_2.5-attributable albuterol inhaler use for four future years (2030, 2050, 2075, and 2095) relative to the year 2000. Exacerbations, regardless of the trigger, are counted as attributable to PM_2.5 if the incident disease is attributable to PM_2.5. We project 38 thousand (95% CI 36, 39 thousand) additional PM_2.5-attributable incident childhood asthma cases and 29 million (95% CI 27, 31 million) additional PM_2.5-attributable albuterol inhaler uses per year in 2030, increasing to 200 thousand (95% CI 190, 210 thousand) additional incident cases and 160 million (95% CI 150, 160 million) inhaler uses per year by 2095 relative to 2000 under the 2011 emissions dataset. These additional PM_2.5-attributable incident asthma cases and albuterol inhaler use would cost billions of additional U.S. dollars per year by the late century. These outcomes could be mitigated by reducing air pollution emissions.

Air quality and health-related impacts of traditional and alternate jet fuels from airport aircraft operations in the U.S

Aviation emissions from landing and takeoff operations (LTO) can degrade local and regional air quality leading to adverse health outcomes in populations near airports and downwind. In this study we aim to quantify the air quality and health-related impacts from commercial LTO emissions in the continental U.S. for two recent years' inventories, 2011 and 2016. We quantify the LTO-attributable PM_2.5, O₃, and NO₂ concentrations and health outcomes for mortality and multiple morbidity health endpoints. We also quantify the impacts from two scenarios representing a nation-wide implementation of 5% or 50% blends of sustainable alternative jet fuels. We estimate 80 (68-93) and 88 (75-100) PM_2.5-attributable and 610 (310-920) and 1,100 (570-1,700) NO₂-attributable premature mortalities in 2011 and 2016, respectively. We estimate a net decrease of 28 (14-56) and 54 (27-110) in O₃-attributable premature mortalities across the U.S. in 2011 and 2016, respectively due to the large O₃ titration effects near the airports. We also find that the asthma exacerbations due to NO₂ exposures from LTO emissions increase from 100,000 (2,500-200,000) in 2011 to 170,000 (4,400-340,000) in 2016. Implementing a 5% or 50% blend of sustainable alternative jet fuel in 2016 results in a 1% or 18% reduction, respectively in PM_2.5-attributable premature mortalities. Monetizing the value of avoided total premature mortalities, we find that a 50%-blended sustainable alternative jet fuel results in a 19% decrease in PM_2.5 damages per ton of fuel burned and a 2% decrease in total damages per ton of fuel burned as compared to damages from traditional jet fuel. We also quantify health impacts by state and find California to be the most impacted by LTO emissions. We find that LTO-attributable PM_2.5 and NO₂ premature mortalities increase by 10% and 80%, respectively from 2011 to 2016 and that NO₂-attributable premature mortalities are responsible for 91% of total LTO-attributable premature mortalities in both 2011 and 2016. And since we find LTO-attributable NO₂ to be unaffected by the implementation of sustainable alternative jet fuels, additional approaches focused on NO_X reductions in the combustor are needed to mitigate the air quality-related health impacts from LTO emissions.

Regional temperature-ozone relationships across the U.S. under multiple climate and emissions scenarios

The potential effects of 21st century climate change on ozone (O₃) concentrations in the United States are investigated using global climate simulations to drive higher-resolution regional meteorological and chemical transport models. Community Earth System Model (CESM) and Coupled Model version 3 (CM3) simulations of the Representative Concentration Pathway 8.5 scenario are dynamically downscaled using the Weather Research and Forecasting model, and the resulting meteorological fields are used to drive the Community Multiscale Air Quality model. Air quality is modeled for five 11-year periods using both a 2011 air pollutant emission inventory and a future projection accounting for full implementation of promulgated regulatory controls. Across the U.S., CESM projects daily maximum temperatures during summer to increase 1-4°C by 2050 and 2-7°C by 2095, while CM3 projects warming of 2-7°C by 2050 and 4-11°C by 2095. The meteorological changes have geographically varying impacts on O₃ concentrations. Using the 2011 emissions dataset, O₃ increases 1-5 ppb in the central Great Plains and Midwest by 2050 and more than 10 ppb by 2095, but it remains unchanged or even decreases in the Gulf Coast, Maine, and parts of the Southwest. Using the projected emissions, modeled increases are attenuated while decreases are amplified, indicating that planned air pollution control measures ameliorate the ozone climate penalty. The relationships between changes in maximum temperature and changes in O₃ concentrations are examined spatially and quantified to explore the potential for developing an efficient approach for estimating air quality impacts of other future climate scenarios.Implications: The effects of climate change on ozone air quality in the United States are investigated using two global climate model simulations of a high warming scenario for five decadal periods in the 21st century. Warming summer temperatures simulated under both models lead to higher ozone concentrations in some regions, with the magnitude of the change increasing with temperature over the century. The magnitude and spatial extent of the increases are attenuated under a future emissions projection that accounts for regulatory controls. Regional linear regression relationships are developed as a first step toward development of a reduced form model for efficient estimation of the health impacts attributable to changes in air quality resulting from a climate change scenario.

Health Impacts of Climate Change as Contained in Economic Models Estimating the Social Cost of Carbon Dioxide

The health impacts of climate change are substantial and represent a primary motivating factor to mitigate climate change. However, the health impacts in economic models that estimate the social cost of carbon dioxide (SC-CO2) have generally been made in isolation from health experts and have never been rigorously evaluated. Version 3.10 of the Framework for Uncertainty, Negotiation and Distribution (FUND) model was used to estimate the health-based portion of current SC-CO2 estimates across low-, middle-, and high-income regions. In addition to the base model, three additional experiments assessed the sensitivity of these estimates to changes in the socio-economic assumptions in the model. Economic impacts from adverse health outcomes represent ∼8.7% of current SC-CO2 estimates. The majority of these health impacts (74%) were attributable to diarrhea mortality (from both low- and high-income regions) followed by diarrhea morbidity (12%) and malaria mortality (11%); no other health impact makes a meaningful contribution to SC-CO2 estimates in current economic models. The results of the socio-economic experiments show that the health-based portion of SC-CO2 estimates are highly sensitive to assumptions regarding income elasticity of health effects, income growth, and use of equity weights. Improving the health-based portion of SC-CO2 estimates could have substantial impacts on magnitude of the SC-CO2. Incorporating additional health impacts not previously included in estimates of SC-CO2 will be a critical component of model updates. This effort will be most successful through coordination between economists and health researchers and should focus on updating the form and function of concentration-response functions.

A temperature binning approach for multi-sector climate impact analysis

Characterizing the future risks of climate change is a key goal of climate impacts analysis. Temperature binning provides a framework for analyzing sector-specific impacts by degree of warming as an alternative or complement to traditional scenario-based approaches in order to improve communication of results, comparability between studies, and flexibility to facilitate scenario analysis. In this study, we estimate damages for nine climate impact sectors within the contiguous United States (US) using downscaled climate projections from six global climate models, at integer degrees of US national warming. Each sector is analyzed based on socioeconomic conditions for both the beginning and the end of the century. The potential for adaptive measures to decrease damages is also demonstrated for select sectors; differences in damages across adaptation response scenarios within some sectors can be as much as an order of magnitude. Estimated national damages from these sectors based on a reactive adaptation assumption and 2010 socioeconomic conditions range from $600 million annually per degree of national warming for winter recreation to $8 billion annually per degree of national warming for labor impacts. Results are also estimated per degree of global temperature change and for 2090 socioeconomic conditions.

Estimating PM2.5-related premature mortality and morbidity associated with future wildfire emissions in the western US

Wildfire activity in the western United States (US) has been increasing, a trend that has been correlated with changing patterns of temperature and precipitation associated with climate change. Health effects associated with exposure to wildfire smoke and fine particulate matter (PM_2.5) include short- and long-term premature mortality, hospital admissions, emergency department visits, and other respiratory and cardiovascular incidents. We estimate PM_2.5 exposure and health impacts for the entire continental US from current and future western US wildfire activity projected for a range of future climate scenarios through the 21st century. We use a simulation approach to estimate wildfire activity, area burned, fine particulate emissions, air quality concentrations, health effects, and economic valuation of health effects, using established and novel methodologies. We find that climatic factors increase wildfire pollutant emissions by an average of 0.40% per year over the 2006-2100 period under Representative Concentration Pathway (RCP) 4.5 (lower emissions scenarios) and 0.71% per year for RCP8.5. As a consequence, spatially weighted wildfire PM_2.5 concentrations more than double for some climate model projections by the end of the 21st century. PM_2.5 exposure changes, combined with population projections, result in a wildfire PM2.5-related premature mortality excess burden in the 2090 RCP8.5 scenario that is roughly 3.5 times larger than in the baseline period. The combined effect of increased wildfire activity, population growth, and increase in the valuation of avoided risk of premature mortality over time results in a large increase in total economic impact of wildfire-related PM_2.5 mortality and morbidity in the continental US, from roughly $7 billion per year in the baseline period to roughly $36 billion per year in 2090 for RCP4.5, and $43 billion per year in RCP8.5. The climate effect alone accounts for a roughly 60% increase in wildfire PM2.5-related premature mortality in the RCP8.5 scenario, relative to baseline conditions.