Effects of Air Pollutants from Wildfires on Downwind Ecosystems: Observations, Knowledge Gaps, and Questions for Assessing Risk.

Wildfires have increased in frequency and area burned, trends expected to continue with climate change. Among other effects, fires release pollutants into the atmosphere, representing a risk to human health and downwind terrestrial and aquatic ecosystems. While human health risks are well studied, the ecological impacts to downwind ecosystems are not, and this gap may present a constraint on developing an adequate assessment of the ecological risks associated with downwind wildfire exposure. Here, we first screened the scientific literature to assess general knowledge about pathways and end points of a conceptual model linking wildfire generated pollutants and other materials to downwind ecosystems. We found a substantial body of literature on the composition of wildfire derived pollution and materials in the atmosphere and subsequent transport, yet little observational or experimental work on their effects on downwind ecological end points. This dearth of information raises many questions related to adequately assessing the ecological risk of downwind exposure, especially given increasing wildfire trends. To guide future research, we pose eight questions within the well-established US EPA ecological risk assessment paradigm that if answered would greatly improve ecological risk assessment and, ultimately, management strategies needed to reduce potential wildfire impacts.

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.

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.

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

Exposure to fine particulate matter (PM2.5) is associated with asthma development as well as asthma exacerbation in children. PM2.5 can be directly emitted or can form in the atmosphere from pollutant precursors. PM2.5 emitted and formed in the atmosphere is influenced by meteorology; future changes in climate may alter the concentration and distribution of PM2.5. Our aim is to estimate the future burden of climate change and PM2.5 on new and exacerbated cases of childhood asthma. Projected concentrations of PM2.5 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 PM2.5 as compared to the 2011 inventory. We estimate additional PM2.5-attributable asthma as well as PM2.5-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 PM2.5 if the incident disease is attributable to PM2.5. We project 38 thousand (95% CI 36, 39 thousand) additional PM2.5-attributable incident childhood asthma cases and 29 million (95% CI 27, 31 million) additional PM2.5-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 PM2.5-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.

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.

Evaluating long-term emission impacts of large-scale electric vehicle deployment in the US using a human-Earth systems model.

While large-scale adoption of electric vehicles (EVs) globally would reduce carbon dioxide (CO2) and traditional air pollutant emissions from the transportation sector, emissions from the electric sector, refineries, and potentially other sources would change in response. Here, a multi-sector human-Earth systems model is used to evaluate the net long-term emission implications of large-scale EV adoption in the US over widely differing pathways of the evolution of the electric sector. Our results indicate that high EV adoption would decrease net CO2 emissions through 2050, even for a scenario where all electric sector capacity additions through 2050 are fossil fuel technologies. Greater net CO2 reductions would be realized for scenarios that emphasize renewables or decarbonization of electricity production. Net air pollutant emission changes in 2050 are relatively small compared to expected overall decreases from recent levels to 2050. States participating in the Regional Greenhouse Gas Initiative experience greater CO2 and air pollutant reductions on a percentage basis. These results suggest that coordinated, multi-sector planning can greatly enhance the climate and environmental benefits of EVs. Additional factors are identified that influence the net emission impacts of EVs, including the retirement of coal capacity, refinery operations under reduced gasoline demands, and price-induced fuel switching in residential heating and in the industrial sector.

The Community Multiscale Air Quality (CMAQ) model versions 5.3 and 5.3.1: system updates and evaluation.

The Community Multiscale Air Quality (CMAQ) model version 5.3 (CMAQ53), released to the public in August 2019 and followed by version 5.3.1 (CMAQ531) in December 2019, contains numerous science updates, enhanced functionality, and improved computation efficiency relative to the previous version of the model, 5.2.1 (CMAQ521). Major science advances in the new model include a new aerosol module (AERO7) with significant updates to secondary organic aerosol (SOA) chemistry, updated chlorine chemistry, updated detailed bromine and iodine chemistry, updated simple halogen chemistry, the addition of dimethyl sulfide (DMS) chemistry in the CB6r3 chemical mechanism, updated M3Dry bidirectional deposition model, and the new Surface Tiled Aerosol and Gaseous Exchange (STAGE) bidirectional deposition model. In addition, support for the Weather Research and Forecasting (WRF) model's hybrid vertical coordinate (HVC) was added to CMAQ53 and the Meteorology-Chemistry Interface Processor (MCIP) version 5.0 (MCIP50). Enhanced functionality in CMAQ53 includes the new Detailed Emissions Scaling, Isolation and Diagnostic (DESID) system for scaling incoming emissions to CMAQ and reading multiple gridded input emission files. Evaluation of CMAQ531 was performed by comparing monthly and seasonal mean daily 8 h average (MDA8) O3 and daily PM2.5 values from several CMAQ531 simulations to a similarly configured CMAQ521 simulation encompassing 2016. For MDA8 O3, CMAQ531 has higher O3 in the winter versus CMAQ521, due primarily to reduced dry deposition to snow, which strongly reduces wintertime O3 bias (2-4 ppbv monthly average). MDA8 O3 is lower with CMAQ531 throughout the rest of the year, particularly in spring, due in part to reduced O3 from the lateral boundary conditions (BCs), which generally increases MDA8 O3 bias in spring and fall ( 0.5 µg m-3). For daily 24 h average PM2.5, CMAQ531 has lower concentrations on average in spring and fall, higher concentrations in summer, and similar concentrations in winter to CMAQ521, which slightly increases bias in spring and fall and reduces bias in summer. Comparisons were also performed to isolate updates to several specific aspects of the modeling system, namely the lateral BCs, meteorology model version, and the deposition model used. Transitioning from a hemispheric CMAQ (HCMAQ) version 5.2.1 simulation to a HCMAQ version 5.3 simulation to provide lateral BCs contributes to higher O3 mixing ratios in the regional CMAQ simulation in higher latitudes during winter (due to the decreased O3 dry deposition to snow in CMAQ53) and lower O3 mixing ratios in middle and lower latitudes year-round (due to reduced O3 over the ocean with CMAQ53). Transitioning from WRF version 3.8 to WRF version 4.1.1 with the HVC resulted in consistently higher (1.0-1.5 ppbv) MDA8 O3 mixing ratios and higher PM2.5 concentrations (0.1-0.25 µg m-3) throughout the year. Finally, comparisons of the M3Dry and STAGE deposition models showed that MDA8 O3 is generally higher with M3Dry outside of summer, while PM2.5 is consistently higher with STAGE due to differences in the assumptions of particle deposition velocities to non-vegetated surfaces and land use with short vegetation (e.g., grasslands) between the two models. For ambient NH3, STAGE has slightly higher concentrations and smaller bias in the winter, spring, and fall, while M3Dry has higher concentrations and smaller bias but larger error and lower correlation in the summer.

The Detailed Emissions Scaling, Isolation, and Diagnostic (DESID) module in the Community Multiscale Air Quality (CMAQ) modeling system version 5.3.2.

Air quality modeling for research and regulatory applications often involves executing many emissions sensitivity cases to quantify impacts of hypothetical scenarios, estimate source contributions, or quantify uncertainties. Despite the prevalence of this task, conventional approaches for perturbing emissions in chemical transport models like the Community Multiscale Air Quality (CMAQ) model require extensive offline creation and finalization of alternative emissions input files. This workflow is often time-consuming, error-prone, inconsistent among model users, difficult to document, and dependent on increased hard disk resources. The Detailed Emissions Scaling, Isolation, and Diagnostic (DESID) module, a component of CMAQv5.3 and beyond, addresses these limitations by performing these modifications online during the air quality simulation. Further, the model contains an Emission Control Interface which allows users to prescribe both simple and highly complex emissions scaling operations with control over individual or multiple chemical species, emissions sources, and spatial areas of interest. DESID further enhances the transparency of its operations with extensive error-checking and optional gridded output of processed emission fields. These new features are of high value to many air quality applications including routine perturbation studies, atmospheric chemistry research, and coupling with external models (e.g., energy system models, reduced-form models).

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.

The contribution of wildland fire emissions to deposition in the U S: implications for tree growth and survival in the Northwest.

Ecosystems require access to key nutrients like nitrogen (N) and sulfur (S) to sustain growth and healthy function. However, excessive deposition can also damage ecosystems through nutrient imbalances, leading to changes in productivity and shifts in ecosystem structure. While wildland fires are a known source of atmospheric N and S, little has been done to examine the implications of wildland fire deposition for vulnerable ecosystems. We combine wildland fire emission estimates, atmospheric chemistry modeling, and forest inventory data to (a) quantify the contribution of wildland fire emissions to N and S deposition across the U S, and (b) assess the subsequent impacts on tree growth and survival rates in areas where impacts are likely meaningful based on the relative contribution of fire to total deposition. We estimate that wildland fires contributed 0.2 kg N ha-1 yr-1 and 0.04 kg S ha-1 yr-1 on average across the U S during 2008-2012, with maxima up to 1.4 kg N ha-1 yr-1 and 0.6 kg S ha-1 yr-1 in the Northwest representing over ~30% of total deposition in some areas. Based on these fluxes, exceedances of S critical loads as a result of wildland fires are minimal, but exceedances for N may affect the survival and growth rates of 16 tree species across 4.2 million hectares, with the most concentrated impacts occurring in Oregon, northern California, and Idaho. Understanding the broader environmental impacts of wildland fires in the U S will inform future decision making related to both fire management and ecosystem services conservation.

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.

Air pollution control strategies directly limiting national health damages in the US.

Exposure to fine particulate matter (PM2.5) from fuel combustion significantly contributes to global and US mortality. Traditional control strategies typically reduce emissions for specific air pollutants and sectors to maintain pollutant concentrations below standards. Here we directly set national PM2.5 mortality cost reduction targets within a global human-earth system model with US state-level energy systems, in scenarios to 2050, to identify endogenously the control actions, sectors, and locations that most cost-effectively reduce PM2.5 mortality. We show that substantial health benefits can be cost-effectively achieved by electrifying sources with high primary PM2.5 emission intensities, including industrial coal, building biomass, and industrial liquids. More stringent PM2.5 reduction targets expedite the phaseout of high emission intensity sources, leading to larger declines in major pollutant emissions, but very limited co-benefits in reducing CO2 emissions. Control strategies limiting health damages achieve the greatest emission reductions in the East North Central and Middle Atlantic states.

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.

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.

Projected Changes in Maternal Heat Exposure During Early Pregnancy and the Associated Congenital Heart Defect Burden in the United States.

Background More intense and longer-lasting heat events are expected in the United States as a consequence of climate change. This study aimed to project the potential changes in maternal heat exposure during early pregnancy (3-8 weeks post conception) and the associated burden of congenital heart defects ( CHD s) in the future. Methods and Results This study expanded on a prior nationwide case-control study that evaluated the association between CHD s and maternal heat exposure during early pregnancy in summer and spring. We defined multiple indicators of heat exposure, and applied published odds ratios obtained for the matching season of the baseline (1995-2005) into the projection period (2025-2035) to estimate potential changes in CHD burden throughout the United States. Increases in maternal heat exposure were projected across the United States and to be larger in the summer. The Midwest will potentially have the highest increase in summer maternal exposure to excessively hot days (3.42; 95% CI, 2.99-3.88 per pregnancy), heat event frequency (0.52; 95% CI, 0.44-0.60) and heat event duration (1.73; 95% CI, 1.49-1.97). We also found large increases in specific CHD subtypes during spring, including a 34.0% (95% CI, 4.9%-70.8%) increase in conotruncal CHD in the South and a 38.6% (95% CI , 9.9%-75.1%) increase in atrial septal defect in the Northeast. Conclusions Projected increases in maternal heat exposure could result in an increased CHD burden in certain seasons and regions of the United States.

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.

State-level drivers of future fine particulate matter mortality in the United States.

Future fine particulate matter (PM2.5) concentrations and resulting health impacts will be largely determined by factors such as energy use, fuel choices, emission controls, state and national policies, and demographcs. In this study, a human-earth system model is used to estimate PM2.5 mortality costs (PMMC) due to air pollutant emissions from each US state over the period 2015 to 2050, considering current major air quality and energy regulations. Contributions of various socioeconomic and energy factors to PMMC are quantified using the Logarithmic Mean Divisia Index. National PMMC are estimated to decrease 25% from 2015 to 2050, driven by decreases in energy intensity and PMMC per unit consumption of electric sector coal and transportation liquids. These factors together contribute 68% of the decrease, primarily from technology improvements and air quality regulations. States with greater population and economic growth, but with fewer clean energy resources, are more likely to face significant challenges in reducing future PMMC from their emissions. In contrast, states with larger projected decreases in PMMC have smaller increases in population and per capita GDP, and greater decreases in electric sector coal share and PMMC per unit fuel consumption.

Southeast Atmosphere Studies: learning from model-observation syntheses.

Concentrations of atmospheric trace species in the United States have changed dramatically over the past several decades in response to pollution control strategies, shifts in domestic energy policy and economics, and economic development (and resulting emission changes) elsewhere in the world. Reliable projections of the future atmosphere require models to not only accurately describe current atmospheric concentrations, but to do so by representing chemical, physical and biological processes with conceptual and quantitative fidelity. Only through incorporation of the processes controlling emissions and chemical mechanisms that represent the key transformations among reactive molecules can models reliably project the impacts of future policy, energy and climate scenarios. Efforts to properly identify and implement the fundamental and controlling mechanisms in atmospheric models benefit from intensive observation periods, during which collocated measurements of diverse, speciated chemicals in both the gas and condensed phases are obtained. The Southeast Atmosphere Studies (SAS, including SENEX, SOAS, NOMADSS and SEAC4RS) conducted during the summer of 2013 provided an unprecedented opportunity for the atmospheric modeling community to come together to evaluate, diagnose and improve the representation of fundamental climate and air quality processes in models of varying temporal and spatial scales. This paper is aimed at discussing progress in evaluating, diagnosing and improving air quality and climate modeling using comparisons to SAS observations as a guide to thinking about improvements to mechanisms and parameterizations in models. The effort focused primarily on model representation of fundamental atmospheric processes that are essential to the formation of ozone, secondary organic aerosol (SOA) and other trace species in the troposphere, with the ultimate goal of understanding the radiative impacts of these species in the southeast and elsewhere. Here we address questions surrounding four key themes: gas-phase chemistry, aerosol chemistry, regional climate and chemistry interactions, and natural and anthropogenic emissions. We expect this review to serve as a guidance for future modeling efforts.

Estimating environmental co-benefits of U.S. low-carbon pathways using an integrated assessment model with state-level resolution.

There are many technological pathways that can lead to reduced carbon dioxide emissions. However, these pathways can have substantially different impacts on other environmental endpoints, such as air quality and energy-related water demand. This study uses an integrated assessment model with state-level resolution of the energy system to compare environmental impacts of alternative low-carbon pathways for the United States. One set of pathways emphasizes nuclear energy and carbon capture and storage, while another set emphasizes renewable energy, including wind, solar, geothermal power, and bioenergy. These are compared with pathways in which all technologies are available. Air pollutant emissions, mortality costs attributable to particulate matter smaller than 2.5 µm in diameter, and energy-related water demands are evaluated for 50% and 80% carbon dioxide reduction targets in 2050. The renewable low-carbon pathways require less water withdrawal and consumption than the nuclear and carbon capture pathways. However, the renewable low-carbon pathways modeled in this study produce higher particulate matter-related mortality costs due to greater use of biomass in residential heating. Environmental co-benefits differ among states because of factors such as existing technology stock, resource availability, and environmental and energy policies.

Atmospheric deposition and exceedances of critical loads from 1800-2025 for the conterminous United States.

Atmospheric deposition of nitrogen (N) and sulfur (S) has increased dramatically over pre-industrial levels, with many potential impacts on terrestrial and aquatic ecosystems. Quantitative thresholds, termed "critical loads" (CLs), have been developed to estimate the deposition rate above which damage is thought to occur. However, there remains no comprehensive comparison of when, where, and over what time periods individual CLs have been exceeded. We addressed this knowledge gap by combining several published data sources for historical and contemporary deposition, and overlaying these on six CL types from the National Critical Loads Database (NCLDv2.5; terrestrial acidification, aquatic acidification, lichen, nitrate leaching, plant community composition, and forest-tree health) to examine exceedances from 1800 to 2011. We expressed CLs as the minimum, 10th, and 50th percentiles within 12-km grid cells. Minimum CLs were relatively uniform across the country (200-400 eq·ha-1 ·yr-1 ), and have been exceeded for decades beginning in the early 20th century. The area exceeding minimum CLs peaked in the 1970s and 1980s, exposing 300,000 to 3 million km2 (depending on the CL type) to harmful levels of deposition, with a total area exceeded of 5.8 million km2 (~70% of the conterminous United States). Since then, deposition levels have dropped, especially for S, with modest reductions in exceedance by 2011 for all CL types, totaling 5.2 million km2 in exceedance. The 10th and 50th percentile CLs followed similar trends, but were not consistently available at the 12-km grid scale. We also examined near-term future deposition and exceedances in 2025 under current air quality regulations, and under various scenarios of climate change and additional nitrogen management controls. Current regulations were projected to reduce exceedances of any CL from 5.2 million km2 in 2011 to 4.8 million km2 in 2025. None of the additional N management or climate scenarios significantly affected areal exceedances, although exceedance severity declined. In total, it is clear that many CLs have been exceeded for decades, and are likely to remain so in the short term under current policies. Additionally, we suggest many areas for improvement to enhance our understanding of deposition and its effects to support informed decision making.