The potential effects of climate change on air quality across the conterminous U.S. at 2030 under three Representative Concentration Pathways

Impact of climate change on paediatric respiratory health: pollutants and aeroallergens

Paediatric populations are particularly vulnerable to respiratory diseases caused and exacerbated by aeroallergens, pollutants and infectious agents. Worsening climate change is expected to increase the prevalence of pollutants and aeroallergens while amplifying disease severity and causing disproportionate effects in under-resourced areas. The purpose of this narrative review is to summarise the role of anthropogenic climate change in the literature examining the future impact of aeroallergens, pollutants and infectious agents on paediatric respiratory diseases with a focus on equitable disease mitigation. The aeroallergens selected for discussion include pollen, dust mites and mould as these are prevalent triggers of paediatric asthma worldwide. Human rhinovirus and respiratory syncytial virus are key viruses interacting with climate change and pollution and are primary causal agents of viral respiratory disease. Within this review, we present the propensity for aeroallergens, climate change and pollution to synergistically exacerbate paediatric respiratory disease and outline measures that can ameliorate the expected increase in morbidity and severity of disease through a health equity lens. We support shifting from fossil fuels to renewable energy worldwide, across sectors, as a primary means of reducing increases in morbidity.

Rapid Estimation of Climate-Air Quality Interactions in Integrated Assessment Using a Response Surface Model

Air quality and climate change are substantial and linked sustainability challenges, and there is a need for improved tools to assess the implications of addressing these challenges together. Due to the high computational cost of accurately assessing these challenges, integrated assessment models (IAMs) used in policy development often use global- or regional-scale marginal response factors to calculate air quality impacts of climate scenarios. We bridge the gap between IAMs and high-fidelity simulation by developing a computationally efficient approach to quantify how combined climate and air quality interventions affect air quality outcomes, including capturing spatial heterogeneity and complex atmospheric chemistry. We fit individual response surfaces to high-fidelity model simulation output for 1525 locations worldwide under a variety of perturbation scenarios. Our approach captures known differences in atmospheric chemical regimes and can be straightforwardly implemented in IAMs, enabling researchers to rapidly estimate how air quality in different locations and related equity-based metrics will respond to large-scale changes in emission policy. We find that the sensitivity of air quality to climate change and air pollutant emission reductions differs in sign and magnitude by region, suggesting that calculations of "co-benefits" of climate policy that do not account for the existence of simultaneous air quality interventions can lead to inaccurate conclusions. Although reductions in global mean temperature are effective in improving air quality in many locations and sometimes yield compounding benefits, we show that the air quality impact of climate policy depends on air quality precursor emission stringency. Our approach can be extended to include results from higher-resolution modeling and also to incorporate other interventions toward sustainable development that interact with climate action and have spatially distributed equity dimensions.

Evidence of air pollution-related ocular signs and altered inflammatory cytokine profile of the ocular surface in Beijing

We evaluated how different degrees of air pollution affect the ocular surface of a cohort of human subjects in Beijing by correlating in-patient test outcomes with tear cytokines. A cross-sectional study involving 221 volunteers was carried out in different districts of Beijing. Air pollution indices were recorded for 7 d (including the visit day). The indices recorded were the air quality index (AQI), which is a dimensionless measure that quantitatively describes the state of air quality, concentrations of particulate matter smaller than 2.5 μm (PM2.5) and 10 μm (PM10), sulfur dioxide (SO₂), ozone (O₃), and nitrogen dioxide (NO₂). The Ocular Symptom Disease Index (OSDI) questionnaire provided. Subsequently, subjects underwent slit-lamp examination, which included meibomian gland examination, conjunctival congestion score, conjunctivochalasis grade, tear meniscus height (TMH), tear breakup time (TBUT), corneal fluorescein staining (CFS), Schirmer I test, and conjunctival impression cytology. The concentrations of vascular endothelial growth factor (VEGF), interleukins (IL)-1β, IL-6 and IL-8 in tears were measured by microsphere-based immunoassay analysis. According to the value of the AQI, participants are divided into a slightly polluted (SP) group (n = 103) which the AQI value is less than or equal to 100 and a heavily polluted (HP) group (n = 118) whose AQI value is more than 100. Air pollution is related to ocular discomfort based on tear cytokine concentrations. PM2.5, PM10 and NO₂ were positively correlated with OSDI, MG expressibility, meibum score, meiboscore, conjunctival congestion score, Schirmer I test value, TMH, goblet-cell density, concentrations of IL-6, and VEGF were negatively correlated with TBUT. PM2.5 and PM10 appear to be the major risk factors to the ocular surface, with NO₂ being another important risk factor based on this study. The symptoms and signs of eye discomfort in the SP group were significantly less severe than those in the HP group, and tear cytokine concentrations (IL-6 and VEGF) were lower. Air pollution degrees were significantly correlated with tear cytokine concentrations, indicating an alteration of cytokine balance at the ocular surface under different degrees of air pollution.

Modeling past and future spatiotemporal distributions of airborne allergenic pollen across the contiguous United States

Exposures to airborne allergenic pollen have been increasing under the influence of changing climate. A modeling system incorporating pollen emissions and atmospheric transport and fate processes has been developed and applied to simulate spatiotemporal distributions of two major aeroallergens, oak and ragweed pollens, across the contiguous United States (CONUS) for both historical (year 2004) and future (year 2047) conditions. The transport and fate of pollen presented here is simulated using our adapted version of the Community Multiscale Air Quality (CMAQ) model. Model performance was evaluated using observed pollen counts at monitor stations across the CONUS for 2004. Our analysis shows that there is encouraging consistency between observed seasonal mean concentrations and corresponding simulated seasonal mean concentrations (oak: Pearson = 0.35, ragweed: Pearson = 0.40), and that the model was able to capture the statistical patterns of observed pollen concentration distributions in 2004 for most of the pollen monitoring stations. Simulation of pollen levels for a future year (2047) considered conditions corresponding to the RCP8.5 scenario. Modeling results show substantial regional variability both in the magnitude and directionality of changes in pollen metrics. Ragweed pollen season is estimated to start earlier and last longer for all nine climate regions of the CONUS, with increasing average pollen concentrations in most regions. The timing and magnitude of oak pollen season vary across the nine climate regions, with the largest increases in pollen concentrations expected in the Northeast region.

Climate change and air pollution: Translating their interplay into present and future mortality risk for Rome and Milan municipalities

Heat and cold temperatures associated with exposure to poor air quality lead to increased mortality. Using a generalized linear model with Poisson regression for overdispersion, this study quantifies the natural-caused mortality burden attributable to heat/cold temperatures and PM₁₀ and O₃ air pollutants in Rome and Milan, the two most populated Italian cities. We calculate local-specific mortality relative risks (RRs) for the period 2004-2015 considering the overall population and the most vulnerable age category (≥85 years). Combining a regional climate model with a chemistry-transport model under future climate and air pollution scenarios (RCP2.6 and RCP8.5), we then project mortality to 2050. Results show that for historical mortality the burden is much larger for cold than for warm temperatures. RR peaks during wintertime in Milan and summertime in Rome, highlighting the relevance of accounting for the effects of air pollution besides that of climate, in particular PM₁₀ for Milan and O₃ for Rome. Overall, Milan reports higher RRs while, in both cities, the elderly appear more susceptible to heat/cold and air pollution events than the average population. Two counterbalancing effects shape mortality in the future: an increase associated with higher and more frequent warmer daily temperatures - especially in the case of climate inaction - and a decrease due to declining cold-mortality burden. The outcomes highlight the urgent need to adopt more stringent and integrated climate and air quality policies to reduce the temperature and air pollution combined effects on health.

Projections of future wildfires impacts on air pollutants and air toxics in a changing climate over the western United States

Wildfires emit smoke particles and gaseous pollutants that greatly aggravate air quality and cause adverse health impacts in the western US (WUS). This study evaluates how wildfire impacts on air pollutants and air toxics evolve from the present climate to the future climate under a high anthropogenic emission scenario at regional and city scales. Through employing multiple climate and chemical transport models, small changes in domain-averaged air pollutant concentrations by wildfires are simulated over WUS. However, such changes significantly increase future city-scale pollutant concentrations by up to 53 ppb for benzene, 158 ppb for formaldehyde, 655 μg/m³ for fine particulate matter (PM_2.5), and 102 ppb for ozone, whereas that for the present climate are 104 ppb for benzene, 332 ppb for formaldehyde, 1,378 μg/m³ for PM_2.5, and 140 ppb for ozone. Despite wildfires induce smaller changes in the future, the wildfire contribution ratios can increase by more than tenfold compared to the present climate, indicating wildfires become a more critical contributor to future air pollution in WUS. In addition, additional 6 exceedance days/year for formaldehyde and additional 3 exceedance days/year for ozone suggest increasing health impacts by wildfires in the future.

Resolving and Predicting Neighborhood Vulnerability to Urban Heat and Air Pollution: Insights From a Pilot Project of Community Science

Urban heat and air pollution, two environmental threats to urban residents, are studied via a community science project in Los Angeles, CA, USA. The data collected, for the first time, by community members, reveal the significance of both the large spatiotemporal variations of and the covariations between 2 m air temperature (2mT) and ozone (O₃) concentration within the (4 km) neighborhood scale. This neighborhood variation was not exhibited in either daily satellite observations or operational model predictions, which makes the assessment of community health risks a challenge. Overall, the 2mT is much better predicted than O₃ by the weather and research forecast model with atmospheric chemistry (WRF-Chem). For O₃, diurnal variation is better predicted by WRF-Chem than spatial variation (i.e., underestimated by 50%). However, both WRF-chem and the surface observation show the overall consistency in describing statistically significant covariations between O₃ and 2mT. In contrast, satellite-based land surface temperature at 1 km resolution is insufficient to capture air temperature variations at the neighborhood scale. Community engagement is augmented with interactive maps and apps that show the predictions in near real time and reveals the potential of green canopy to reduce air temperature and ozone; but different tree types and sizes may lead to different impacts on air temperature, which is not resolved by the WRF-Chem. These findings highlight the need for community science engagement to reveal otherwise impossible insights for models, observations, and real-time dissemination to understand, predict, and ultimately mitigate, urban neighborhood vulnerability to heat and air pollution.

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.

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.

Projecting changes in extreme rainfall from three tropical cyclones using the design-rainfall approach

In the past quarter-century, Eastern North Carolina (ENC) experienced several devastating tropical cyclones that led to widespread flooding and damage. Historical climate records reflect an increasing trend in the frequency and intensity of extreme rainfall events across the eastern U.S., which is projected to continue to increase throughout the twenty-first century. Potential changes to extreme rainfall across ENC are explored and quantified for 2025-2100 for three tropical cyclones using an approach based on relative changes in future extreme rainfall frequencies (return periods) from dynamically downscaled projections. Maximum rainfall intensities at '2100' could increase locally by 168%, with widespread regional increases in total rainfall up to 44%. Although these magnitudes exceed the consensus in the literature, the values here are comparable to the most extreme rainfall events observed in the U.S. during the early twenty-first century, which suggests that the intensity of projected future events is already a present-day reality.

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.

SPATIAL DISTRIBUTED LAG DATA FUSION FOR ESTIMATING AMBIENT AIR POLLUTION

We introduce spatial (DLfuse) and spatiotemporal (DLfuseST) distributed lag data fusion methods for predicting point-level ambient air pollution concentrations, using, as input, gridded average pollution estimates from a deterministic numerical air quality model. The methods incorporate predictive information from grid cells surrounding the prediction location of interest and are shown to collapse to existing downscaling approaches when this information adds no benefit. The spatial lagged parameters are allowed to vary spatially/spatiotemporally to accommodate the setting where surrounding geographic information is useful in one area/time but not in another. We apply the new methods to predict ambient concentrations of eight-hour maximum ozone and 24-hour average PM2.5 at unobserved spatial locations and times, and compare the predictions with those from several state-of-the-art data fusion approaches. Results show that DLfuse and DLfuseST often provide improved model fit and predictive accuracy when the lagged information is shown to be beneficial. Code to apply the methods is available in the R package DLfuse.

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

IMPORTANCE

Future changes in climate are likely to adversely affect human health by affecting concentrations of particulate matter sized less than 2.5 μm (PM2.5) and ozone (O3) in many areas. However, the degree to which these outcomes may be mitigated by reducing air pollutant emissions is not well understood.

OBJECTIVE

To model the associations between future changes in climate, air quality, and human health for 2 climate models and under 2 air pollutant emission scenarios.

DESIGN, SETTING, AND PARTICIPANTS

This modeling study simulated meteorological conditions over the coterminous continental US during a 1995 to 2005 baseline and over the 21st century (2025-2100) by dynamically downscaling representations of a high warming scenario from the Community Earth System Model (CESM) and the Coupled Model version 3 (CM3) global climate models. Using a chemical transport model, PM2.5 and O3 concentrations were simulated under a 2011 air pollutant emission data set and a 2040 projection. The changes in PM2.5 and O3-attributable deaths associated with climate change among the US census-projected population were estimated for 2030, 2050, 2075, and 2095 for each of 2 emission inventories and climate models. Data were analyzed from June 2018 to June 2020.

MAIN OUTCOMES AND MEASURES

The main outcomes were simulated change in summer season means of the maximum daily 8-hour mean O3, annual mean PM2.5, population-weighted exposure, and the number of avoided or incurred deaths associated with these pollutants. Results are reported for 2030, 2050, 2075, and 2095, compared with 2000, for 2 climate models and 2 air pollutant emissions data sets.

RESULTS

The projected increased maximum daily temperatures through 2095 were up to 7.6 °C for the CESM model and 11.8 °C for the CM3 model. Under each climate model scenario by 2095, compared with 2000, an estimated additional 21 000 (95% CI, 14 000-28 000) PM2.5-attributable deaths and 4100 (95% CI, 2200-6000) O3-attributable deaths were projected to occur. These projections decreased to an estimated 15 000 (95% CI, 10 000-20 000) PM2.5-attributable deaths and 640 (95% CI, 340-940) O3-attributable deaths when simulated using a future emission inventory that accounted for reduced anthropogenic emissions.

CONCLUSIONS AND RELEVANCE

These findings suggest that reducing future air pollutant emissions could also reduce the climate-driven increase in deaths associated with air pollution by hundreds to thousands.

Ozone-related asthma emergency department visits in the US in a warming climate

Ozone exposure is associated with higher risk of asthma-related emergency department visits. The meteorological conditions that govern ozone concentration are projected to be more favorable to ozone formation over much of the United States due to continued climate change, even as emissions of anthropogenic ozone precursors are expected to decrease by 2050. Our goal is to quantify the health benefits of a climate change mitigation scenario versus a "business-as-usual" scenario, defined by the United Nations Intergovernmental Panel on Climate Change Representative Concentration Pathways (RCPs) 4.5 and 8.5, respectively, using the health impact analytical program Benefits Mapping and Analysis Program - Community Edition (BenMAP - CE) to project the number of asthma ED visits in 2045-2055. We project an annual average of 3100 averted ozone-related asthma ED visits during the 2045-2055 period under RCP4.5 versus RCP8.5, with all other factors held constant, which translates to USD $1.7 million in averted costs annually. We identify counties with tens to hundreds of avoided ozone-related asthma ED visits under RCP4.5 versus RCP8.5. Overall, we project a heterogeneous distribution of ozone-related asthma ED visits at different spatial resolutions, specifically national, regional, and county levels, and a substantial net health and economic benefit of climate change mitigation.

Projections of Atmospheric Nitrogen Deposition to the Chesapeake Bay Watershed

Atmospheric deposition is among the largest pathways of nitrogen loading to the Chesapeake Bay Watershed (CBW). The interplay between future climate and emission changes in and around the CBW will likely shift the future nutrient deposition abundance and chemical regime (e.g., oxidized vs. reduced nitrogen). In this work, a Representative Concentration Pathway (RCP) from the Community Earth System Model is dynamically downscaled using the Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) model coupled to the agro-economic Environmental Policy Integrated Climate (EPIC) model. The relative impacts of emission and climate changes on atmospheric nutrient deposition are explored for a recent historical period and a period centered on 2050. The projected regional emissions in CMAQ reflect current federal and state regulations, which use baseline and projected emission years 2011 and 2040, respectively. The historical simulations of 2-m temperature and precipitation have cool and dry biases, and temperature and precipitation are projected to both increase. Ammonium wet deposition agrees well with observations, but nitrate wet deposition is underpredicted. Climate and deposition changes increase simulated future ammonium fertilizer application. In the CBW at 2050, these changes (along with widespread decreases in anthropogenic nitrogen oxide and sulfur oxide emissions, and relatively constant NH3 emissions) decrease total nitrogen deposition by 21%, decrease annual average oxidized nitrogen deposition by 44%, and increase reduced nitrogen deposition by 10%. These results emphasize the importance of decreased anthropogenic emissions on the control of future nitrogen loading to the Chesapeake Bay in a changing climate.

Development of a semi-mechanistic allergenic pollen emission model

Modeling pollen emission processes is crucial for studying the spatiotemporal distributions of airborne allergenic pollen. A semi-mechanistic emission model was developed based on mass balance of pollen grain fluxes in the surroundings of allergenic plants. The emission model considers direct emission and resuspension and accounts for influences of temperature, wind velocity, and relative humidity. Modules of this emission model have been developed and parameterized with multiple years of pollen count observations to provide pollen season onset and duration, hourly flowering likelihood, and vegetation coverage for oak and ragweed, as two examples. The simulated spatiotemporal pattern of pollen emissions generally follows the corresponding pattern of area coverage of allergenic plants and diurnal pattern of hourly flowering likelihood. It is found that oak pollen emissions start from the Southern part of the Contiguous United States (CONUS) in March and then shift gradually toward the Northern CONUS, with a maximum emission flux of 5.8 × 10⁶ pollen/(m² h). On the other hand, ragweed pollen emissions start from the Northern CONUS in August and then shift gradually toward the Southern CONUS. The mean ragweed emission flux during August to September can increase up to 2.4 × 10⁶ pollen/(m² h). This emission model is robust with respect to the input parameters for oak and ragweed. Qualitative evaluations of the model performance indicated that the simulated pollen emission is strongly correlated with the plant coverages and observed pollen counts. This model could also be applied to other pollen species given the relevant parameters.