Kirk R. Baker

Photochemical modeling of the Ozark isoprene volcano: MEGAN, BEIS, and their impacts on air quality predictions.

Biogenic volatile organic compounds (BVOCs) contribute substantially to atmospheric carbon, exerting influence on air quality and climate. Two widely used models, the Model of Emissions of Gases and Aerosols from Nature (MEGAN) and the Biogenic Emission Inventory System (BEIS) are employed to generate emissions for application in the CMAQ air quality model. Predictions of isoprene, monoterpenes, ozone, formaldehyde, and secondary organic carbon (SOC) are compared to surface and aloft measurements made during an intensive study in the Ozarks, a large isoprene emitting region. MEGAN and BEIS predict spatially similar emissions but magnitudes differ. The total VOC reactivity of the emissions, as developed for the CB05 gas-phase chemical mechanism, is a factor of 2 different between the models. Isoprene estimates by CMAQ-MEGAN are higher and more variable than surface and aloft measurements, whereas CMAQ-BEIS predictions are lower. CMAQ ozone predictions are similar and compare well with measurements using either MEGAN or BEIS. However, CMAQ-MEGAN overpredicts formaldehyde. CMAQ-BEIS SOC predictions are lower than observational estimates for every sample. CMAQ-MEGAN underpredicts SOC ∼ 80% of the time, despite overprediction of precursor VOCs. CMAQ-MEGAN isoprene predictions improve when prognostically predicted solar radiation is replaced with the GEWEX satellite product. CMAQ-BEIS does not exhibit similar photosensitivity.

The Recent and Future Health Burden of Air Pollution Apportioned Across U.S. Sectors

Recent risk assessments have characterized the overall burden of recent PM2.5 and ozone levels on public health, but generally not the variability of these impacts over time or by sector. Using photochemical source apportionment modeling and a health impact function, we attribute PM2.5 and ozone air quality levels, population exposure and health burden to 23 industrial point, area, mobile and international emission sectors in the Continental U.S. in 2005 and 2016. Our modeled policy scenarios account for a suite of emission control requirements affecting many of these sectors. Between these two years, the number of PM2.5 and ozone-related deaths attributable to power plants and mobile sources falls from about 68,000 (90% confidence interval from 48,000 to 87,000) to about 36,000 (90% confidence intervals from 26,000 to 47,000). Area source mortality risk grows slightly between 2005 and 2016, due largely to population growth. Uncertainties relating to the timing and magnitude of the emission reductions may affect the size of these estimates. The detailed sector-level estimates of the size and distribution of mortality and morbidity risk suggest that the air pollution mortality burden has fallen over time but that many sectors continue to pose a substantial risk to human health.

Characterizing the PM2.5-related health benefits of emission reductions for 17 industrial, area and mobile emission sectors across the U.S.

BACKGROUND Air pollution benefits assessments tend to be time and resource intensive. Reduced-form approaches offer computational efficiency, but may introduce uncertainty. Some reduced-form approaches apply simplified air quality models, which may not capture the complex non-linear chemistry governing the formation of certain pollutants such as PM₂.₅. Other approaches apply the results of sophisticated photochemical modeling, but characterize only a small number of source types in a limited geographic area. METHODS We apply CAMx source apportionment photochemical modeling, coupled with a PC-based human health benefits software program, to develop a suite of PM₂.₅ benefit per ton estimates. These per-ton estimates relate emission changes to health impacts and monetized benefits for 17 sectors across the continental U.S., including Electricity Generating Units (EGU), mobile, area and industrial point sources. RESULTS The benefit per ton of reducing directly emitted PM₂.₅ is about an order of magnitude larger than reducing emissions of PM₂.₅ precursor emissions. On a per-ton basis, the value of reducing directly emitted PM₂.₅ and PM₂.₅ precursors in 2005 ranges between approximately

Modeling the Current and Future Roles of Particulate Organic Nitrates in the Southeastern United States

1300 (2010

Fine-scale simulation of ammonium and nitrate over the South Coast Air Basin and San Joaquin Valley of California during CalNex-2010

) for reducing a ton of NO(x) from Ocean-Going Vessels to about

A Direct Sensitivity Approach to Predict Hourly Ozone Resulting from Compliance with the National Ambient Air Quality Standard

450,000 (2010

Measurements and modeling of the inorganic chemical composition of fine particulate matter and associated precursor gases in California's San Joaquin Valley during CalNex 2010

) for reducing a ton of directly emitted PM₂.₅ from Iron and Steel facilities. The benefit per ton estimates for 2016 are generally higher than the 2005 estimates. The values estimated here are generally comparable with those generated using photochemical modeling, but larger than those calculated using simplified air quality models. CONCLUSIONS Our approach characterizes well the per-ton benefits of reducing emissions from a broad array of 17 industrial point, EGU and mobile sectors, while our use of photochemical air quality modeling gives us greater confidence that we have accounted for the non-linear chemistry governing PM₂.₅ formation. The resulting benefit per-ton estimates thus represent a compromise between approaches that may simplify the treatment of PM₂.₅ air quality formation and those techniques that are based in photochemical modeling but account for only a small number of emission sources.

Chemical transport model simulations of organic aerosol in southern California: model evaluation and gasoline and diesel source contributions

Organic nitrates are an important aerosol constituent in locations where biogenic hydrocarbon emissions mix with anthropogenic NOx sources. While regional and global chemical transport models may include a representation of organic aerosol from monoterpene reactions with nitrate radicals (the primary source of particle-phase organic nitrates in the Southeast United States), secondary organic aerosol (SOA) models can underestimate yields. Furthermore, SOA parametrizations do not explicitly take into account organic nitrate compounds produced in the gas phase. In this work, we developed a coupled gas and aerosol system to describe the formation and subsequent aerosol-phase partitioning of organic nitrates from isoprene and monoterpenes with a focus on the Southeast United States. The concentrations of organic aerosol and gas-phase organic nitrates were improved when particulate organic nitrates were assumed to undergo rapid (τ = 3 h) pseudohydrolysis resulting in nitric acid and nonvolatile secondary organic aerosol. In addition, up to 60% of less oxidized-oxygenated organic aerosol (LO-OOA) could be accounted for via organic nitrate mediated chemistry during the Southern Oxidants and Aerosol Study (SOAS). A 25% reduction in nitrogen oxide (NO + NO2) emissions was predicted to cause a 9% reduction in organic aerosol for June 2013 SOAS conditions at Centreville, Alabama.

Synthesis of the Southeast Atmosphere Studies: Investigating Fundamental Atmospheric Chemistry Questions

National ambient air quality standards (NAAQS) have been set for PM_2.5 due to its association with adverse health effects. PM_2.5 design values in the South Coast Air Basin (SoCAB) and San Joaquin Valley of California exceed NAAQS levels, and NH^(+)_(4) and NO^(-)_(3) make up the largest fraction of total PM2.5 mass on polluted days. Here we evaluate fine-scale simulations of PM_(2.5) NH^(+)_(4) and NO^(-)_(3) with the Community Multiscale Air Quality model using measurements from routine networks and the California Research at the Nexus of Air Quality and Climate Change 2010 campaign. The model correctly simulates broad spatial patterns of NH^(+)_(4) and NO^(-)_(3) including the elevated concentrations in eastern SoCAB. However, areas for model improvement have been identified. NH_3 emissions from livestock and dairy facilities appear to be too low, while those related to waste disposal in western SoCAB may be too high. Analyses using measurements from flights over SoCAB suggest that problems with NH3 predictions can influence NO^(-)_(3) predictions there. Offline ISORROPIA II calculations suggest that overpredictions of NH_x in Pasadena cause excessive partitioning of total nitrate to the particle phase overnight, while underpredictions of Na^+ cause too much partitioning to the gas phase during the day. Also, the model seems to underestimate mixing during the evening boundary layer transition leading to excessive nitrate formation on some nights. Overall, the analyses demonstrate fine-scale variations in model performance within and across the air basins. Improvements in inventories and spatial allocations of NH_3 emissions and in parameterizations of sea spray emissions, evening mixing processes, and heterogeneous ClNO_2 chemistry could improve model performance.

Assessing Temporal and Spatial Patterns of Observed and Predicted Ozone in Multiple Urban Areas

In setting primary ambient air quality standards, the EPAs responsibility under the law is to establish standards that protect public health. As part of the current review of the ozone National Ambient Air Quality Standard (NAAQS), the US EPA evaluated the health exposure and risks associated with ambient ozone pollution using a statistical approach to adjust recent air quality to simulate just meeting the current standard level, without specifying emission control strategies. One drawback of this purely statistical concentration rollback approach is that it does not take into account spatial and temporal heterogeneity of ozone response to emissions changes. The application of the higher-order decoupled direct method (HDDM) in the community multiscale air quality (CMAQ) model is discussed here to provide an example of a methodology that could incorporate this variability into the risk assessment analyses. Because this approach includes a full representation of the chemical production and physical transport of ozone in the atmosphere, it does not require assumed background concentrations, which have been applied to constrain estimates from past statistical techniques. The CMAQ-HDDM adjustment approach is extended to measured ozone concentrations by determining typical sensitivities at each monitor location and hour of the day based on a linear relationship between first-order sensitivities and hourly ozone values. This approach is demonstrated by modeling ozone responses for monitor locations in Detroit and Charlotte to domain-wide reductions in anthropogenic NOx and VOCs emissions. As seen in previous studies, ozone response calculated using HDDM compared well to brute-force emissions changes up to approximately a 50% reduction in emissions. A new stepwise approach is developed here to apply this method to emissions reductions beyond 50% allowing for the simulation of more stringent reductions in ozone concentrations. Compared to previous rollback methods, this application of modeled sensitivities to ambient ozone concentrations provides a more realistic spatial response of ozone concentrations at monitors inside and outside the urban core and at hours of both high and low ozone concentrations.