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Future changes in society and climate are expected to affect wildfire activity in the south-eastern United States. The objective of this research was to understand how changes in both climate and society may affect wildfire in the coming decades.Weestimated a three-stage statisticalmodel of wildfire area burned by ecoregion province for lightning and human causes (1992–2010) based on precipitation, temperature, potential evapotranspiration, forest land use, human population and personal income. Estimated parameters from the statistical models were used to project wildfire area burned from 2011 to 2060 under nine climate realisations, using a combination of three Intergovernmental Panel on Climate Change-based emissions scenarios (A1B, A2, B2) and three general circulation models. Monte Carlo simulation quantifies ranges in projected area burned by county by year, and in total for higher-level spatial aggregations. Projections indicated, overall in the Southeast, that median annual area burned by lightning-ignited wildfire increases by 34%, human-ignited wildfire decreases by 6%, and total wildfire increases by 4%by 2056–60 compared with 2016–20.Total wildfire changes varywidely by state (–47 to +30%) and ecoregion province (–73 to +79%). Our analyses could be used to generate projections of wildfire-generated air pollutant exposures, relevant to meeting the National Ambient Air Quality Standards. [ABSTRACT FROM AUTHOR]

As a component of fine particulate matter (PM2.5), black carbon (BC) is associated with premature human mortality. BC also affects climate by absorbing solar radiation and reducing planetary albedo. Several studies have examined the climate impacts of BC emissions, but the associated health impacts have been studied less extensively. Here, we examine the surface PM2.5 and premature mortality impacts of halving anthropogenic BC emissions globally and individually from eight world regions and three major economic sectors. We use a global chemical transport model, MOZART-4, to simulate PM2.5 concentrations and a health impact function to calculate premature cardiopulmonary and lung cancer deaths. We estimate that halving global anthropogenic BC emissions reduces outdoor population-weighted average PM2.5 by 542 ngm-3 (1.8 %) and avoids 157 000 (95% confidence interval, 120 000-194 000) annual premature deaths globally, with the vast majority occurring within the source region. Most of these avoided deaths can be achieved by halving emissions in East Asia (China; 54 %), followed by South Asia (India; 31 %), however South Asian emissions have 50% greater mortality impacts per unit BC emitted than East Asian emissions. Globally, halving residential, industrial, and transportation emissions contributes 47 %, 35 %, and 15% to the avoided deaths from halving all anthropogenic BC emissions. These contributions are 1.2, 1.2, and 0.6 times each sector's portion of global BC emissions, owing to the degree of co-location with population globally. We find that reducing BC emissions increases regional SO4 concentrations by up to 28% of the magnitude of the regional BC concentration reductions, due to reduced absorption of radiation that drives photochemistry. Impacts of residential BC emissions are likely underestimated since indoor PM2.5 exposure is excluded. We estimate ~8 times more avoided deaths when BC and organic carbon (OC) emissions are halved together, suggesting that these results greatly underestimate the full air pollution-related mortality benefits of BC mitigation strategies which generally decrease both BC and OC. The choice of concentration-response factor and health effect thresholds affects estimated global avoided deaths by as much as 56% but does not strongly affect the regional distribution. Confidence in our results would be strengthened by reducing uncertainties in emissions, model parameterization of aerosol processes, grid resolution, and PM2.5 concentration-mortality relationships globally. [ABSTRACT FROM AUTHOR]

Abstract Background Synoptic circulation patterns (large-scale tropospheric motion systems) affect air pollution and, potentially, air-pollution-morbidity associations. We evaluated the effect of synoptic circulation patterns (air masses) on the association between ozone and hospital admissions for asthma and myocardial infarction (MI) among adults in North Carolina. Methods Daily surface meteorology data (including precipitation, wind speed, and dew point) for five selected cities in North Carolina were obtained from the U.S. EPA Air Quality System (AQS), which were in turn based on data from the National Climatic Data Center of the National Oceanic and Atmospheric Administration. We used the Spatial Synoptic Classification system to classify each day of the 9-year period from 1996 through 2004 into one of seven different air mass types: dry polar, dry moderate, dry tropical, moist polar, moist moderate, moist tropical, or transitional. Daily 24-hour maximum 1-hour ambient concentrations of ozone were obtained from the AQS. Asthma and MI hospital admissions data for the 9-year period were obtained from the North Carolina Department of Health and Human Services. Generalized linear models were used to assess the association of the hospitalizations with ozone concentrations and specific air mass types, using pollutant lags of 0 to 5 days. We examined the effect across cities on days with the same air mass type. In all models we adjusted for dew point and day-of-the-week effects related to hospital admissions. Results Ozone was associated with asthma under dry tropical (1- to 5-day lags), transitional (3- and 4-day lags), and extreme moist tropical (0-day lag) air masses. Ozone was associated with MI only under the extreme moist tropical (5-day lag) air masses. Conclusions Elevated ozone levels are associated with dry tropical, dry moderate, and moist tropical air masses, with the highest ozone levels being associated with the dry tropical air mass. Certain synoptic circulation patterns/air masses in conjunction with ambient ozone levels were associated with increased asthma and MI hospitalizations.

The United States Environmental Protection Agency (US EPA) has developed a set of annual North American emissions data for multiple air pollutants across 18 broad source categories for 2002 through 2017. The sixteen new annual emissions inventories were developed using consistent input data and methods across all years. When a consistent method or tool was not available for a source category, emissions were estimated by scaling data from the EPA's 2017 National Emissions Inventory with scaling factors based on activity data and/or emissions control information. The emissions datasets are designed to support regional air quality modeling for a wide variety of human health and ecological applications. The data were developed to support simulations of the EPA's Community Multiscale Air Quality model but can also be used by other regional scale air quality models. The emissions data are one component of EPA's Air Quality Time Series Project which also includes air quality modeling inputs (meteorology, initial conditions, boundary conditions) and outputs (e.g., ozone, PM 2.5 and constituent species, wet and dry deposition) for the Conterminous US at a 12 km horizontal grid spacing., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships which have or could be perceived to have influenced the work reported in this article., (© 2023 The Author(s).)

Volatile chemical products (VCPs) are a significant source of reactive organic carbon emissions in the United States with a substantial fraction (>20% by mass) serving as secondary organic aerosol (SOA) precursors. Here, we incorporate a new nationwide VCP inventory into the Community Multiscale Air Quality (CMAQ) model with VCP-specific updates to better model air quality impacts. Model results indicate that VCPs mostly enhance anthropogenic SOA in densely populated areas with population-weighted annual average SOA increasing 15-30% in Southern California and New York City due to VCP emissions (contribution of 0.2-0.5 μg m -3 ). Annually, VCP emissions enhance total population-weighted PM 2.5 by ∼5% in California, ∼3% in New York, New Jersey, and Connecticut, and 1-2% in most other states. While the maximum daily 8 h ozone enhancements from VCP emissions are more modest, their influence can cause a several ppb increase on select days in major cities. Printing Inks, Cleaning Products, and Paints and Coatings product use categories contribute ∼75% to the modeled VCP-derived SOA and Cleaning Products, Paints and Coatings, and Personal Care Products contribute ∼81% to the modeled VCP-derived ozone. Overall, VCPs enhance multiple criteria pollutants throughout the United States with the largest impacts in urban cores.

Per- and polyfluoroalkyl substances (PFASs) have been released into the environment for decades, yet contributions of air emissions to total human exposure, from inhalation and drinking water contamination via deposition, are poorly constrained. The atmospheric transport and fate of a PFAS mixture from a fluoropolymer manufacturing facility in North Carolina were investigated with the Community Multiscale Air Quality (CMAQ) model applied at high resolution (1 km) and extending ∼150 km from the facility. Twenty-six explicit PFAS compounds, including GenX, were added to CMAQ using current best estimates of air emissions and relevant physicochemical properties. The new model, CMAQ-PFAS, predicts that 5% by mass of total emitted PFAS and 2.5% of total GenX are deposited within ∼150 km of the facility, with the remainder transported out. Modeled air concentrations of total GenX and total PFAS around the facility can reach 24.6 and 8500 ng m -3 but decrease to ∼0.1 and ∼10 ng m -3 at 35 km downwind, respectively. We find that compounds with acid functionality have higher deposition due to enhanced water solubility and pH-driven partitioning to aqueous media. To our knowledge, this is the first modeling study of the fate of a comprehensive, chemically resolved suite of PFAS air emissions from a major manufacturing source.

Aviation is a unique anthropogenic source with four-dimensional varying emissions, peaking at cruise altitudes (9-12 km). Aircraft emission budgets in the upper troposphere lower stratosphere region and their potential impacts on upper troposphere and surface air quality are not well understood. Our key objective is to use chemical transport models (with prescribed meteorology) to predict aircraft emissions impacts on the troposphere and surface air quality. We quantified the importance of including full-flight intercontinental emissions and increased horizontal grid resolution. The full-flight aviation emissions in the Northern Hemisphere contributed ~1.3% (mean, min-max: 0.46, 0.3-0.5 ppbv) and 0.2% (0.013, 0.004-0.02 μg/m 3 ) of total O 3 and PM 2.5 concentrations at the surface, with Europe showing slightly higher impacts (1.9% (O 3 0.69, 0.5-0.85 ppbv) and 0.5% (PM 2.5 0.03, 0.01-0.05 μg/m 3 )) than North America (NA) and East Asia. We computed seasonal aviation-attributable mass flux vertical profiles and aviation perturbations along isentropic surfaces to quantify the transport of cruise altitude emissions at the hemispheric scale. The comparison of coarse (108 × 108 km 2 ) and fine (36 × 36 km 2 ) grid resolutions in NA showed ~70 times and ~13 times higher aviation impacts for O 3 and PM 2.5 in coarser domain. These differences are mainly due to the inability of the coarse resolution simulation to capture nonlinearities in chemical processes near airport locations and other urban areas. Future global studies quantifying aircraft contributions should consider model resolution and perhaps use finer scales near major aviation source regions.

This work describes a methodology for modeling the impact of traffic-generated air pollutants in an urban area. This methodology presented here utilizes road network geometry, traffic volume, temporal allocation factors, fleet mixes, and emission factors to provide critical modeling inputs. These inputs, assembled from a variety of sources, are combined with meteorological inputs to generate link-based emissions for use in dispersion modeling to estimate pollutant concentration levels due to traffic. A case study implementing this methodology for a large health study is presented, including a sensitivity analysis of the modeling results reinforcing the importance of model inputs and identify those having greater relative impact, such as fleet mix. In addition, an example use of local measurements of fleet activity to supplement model inputs is described, and its impacts to the model outputs are discussed. We conclude that with detailed model inputs supported by local traffic measurements and meteorology, it is possible to capture the spatial and temporal patterns needed to accurately estimate exposure from traffic-related pollutants.