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Browsing Research Data by Author "Akherati, Ali"

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    ItemOpen Access
    Data associated with "Health and environmental justice implications of retiring two coal‐fired power plants in the southern Front Range region of Colorado"
    (Colorado State University. Libraries, 2019) Martenies, Sheena; Akherati, Ali; Jathar, Shantanu; Magzamen, Sheryl
    Despite improvements in air quality over the past 50 years, ambient air pollution remains an important public health issue in the United States. In particular, emissions from coal-fired power plants still have a substantial impact on both nearby and regional populations. Of particular concern is the potential for this impact to fall disproportionately on low-income communities and communities of color. We conducted a quantitative health impact assessment to estimate the health benefits of the proposed decommissioning of coal-fired boilers at two electricity generating stations in the Southern Front Range region of Colorado. We estimated changes in exposures to fine particulate matter (PM2.5) and ozone due to reductions in emission using the Community Multiscale Air Quality model and predicted avoided health impacts and related economic values. In addition to estimating health benefits of reduced emissions, we assessed the distribution of these benefits by population-level socioeconomic status using concentration curves. Across the study area, decommissioning the power plants would result in 4 (95% CI: 2 – 6) avoided premature deaths each year due to reduced PM2.5 exposures and greater reductions in hospitalizations and other morbidities. Health benefits resulting from the modeled shutdowns were greatest in areas with lower median incomes, lower percentages of high school graduates, and higher proportions of households with incomes below the poverty line. However, in our study area, we did not observe higher benefits when examining area-level percentage of residents of color, largely due to the distribution of the smaller proportion of the population in the region that identifies as non-White. Our results suggest that decommissioning the power plants in the southern Front Range and replacing them with zero-emissions sources could have broad public health benefits for residents of Colorado, with larger benefits for those that are socially disadvantaged and historically bear greater environmental pollution burdens. These results also suggested that researchers and decision makers need to consider the unique demographics of their study areas to ensure that important opportunities to reduce health disparities associated with point-source pollution.
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    ItemOpen Access
    Data associated with "Simulating secondary organic aerosol in a regional air quality model using the statistical oxidation model – Part 3: Assessing the influence of semi-volatile and intermediate-volatility organic compounds and NOx"
    (Colorado State University. Libraries, 2019) Akherati, Ali; Cappa, Christopher D.; Kleeman, Michael J.; Docherty, Kenneth S.; Jimenez, Jose L.; Griffith, Stephen M.; Dusanter, Sebastien; Stevens, Philip S.; Jathar, Shantanu H.
    Semi-volatile and intermediate-volatility organic compounds (SVOCs and IVOCs) from anthropogenic sources are likely to be important precursors of secondary organic aerosol (SOA) in urban airsheds, yet their treatment in most models is based on limited and obsolete data or completely missing. Additionally, gas-phase oxidation of organic precursors to form SOA is influenced by the presence of nitric oxide (NO), but this influence is poorly constrained in chemical transport models. In this work, we updated the organic aerosol model in the UCD/CIT (University of California at Davis and California Institute of Technology) chemical transport model to include (i) a semi-volatile and reactive treatment of primary organic aerosol (POA), (ii) emissions and SOA formation from IVOCs, (iii) the NOx influence on SOA formation, and (iv) SOA parameterizations for SVOCs and IVOCs that are corrected for vapor wall loss artifacts during chamber experiments. All updates were implemented in the statistical oxidation model (SOM) that simulates the oxidation chemistry, thermodynamics, and gas–particle partitioning of organic aerosol (OA). Model treatment of POA, SVOCs, and IVOCs was based on an interpretation of a comprehensive set of source measurements available up to the year 2016 and resolved broadly by source type. The NOx influence on SOA formation was calculated offline based on measured and modeled VOC:NOx ratios. Finally, the SOA formation from all organic precursors (including SVOCs and IVOCs) was modeled based on recently derived parameterizations that accounted for vapor wall loss artifacts in chamber experiments. The updated model was used to simulate a 2-week summer 30 episode over southern California at a model resolution of 8 km. When combustion-related POA was treated as semi-volatile, modeled POA mass concentrations were reduced by 15%-40% in the urban areas in southern California but were still too high when compared against "hydrocarbon-like organic aerosol" factor measurements made at Riverside, CA, during the Study of Organic Aerosols at Riverside (SOAR-1) campaign of 2005. Treating all POA (except that from marine sources) to be semi-volatile, similar to diesel exhaust POA, resulted in a larger reduction in POA mass concentrations and allowed for a better model–measurement comparison at Riverside, but this scenario is unlikely to be realistic since this assumes that POA from sources such as road and construction dust are semi-volatile too. Model predictions suggested that both SVOCs (evaporated POA vapors) and IVOCs did not contribute as much as other anthropogenic precursors (e.g., alkanes, aromatics) to SOA mass concentrations in the urban areas (<5% and <15% of the total SOA respectively) as the timescales for SOA production appeared to be shorter than the timescales for transport out of the urban airshed. Comparisons of modeled IVOC concentrations with measurements of anthropogenic SOA precursors in southern California seemed to imply that IVOC emissions were underpredicted in our updated model by a factor of 2. Correcting for the vapor wall loss artifact in chamber experiments enhanced SOA mass concentrations although the enhancement was precursor-dependent as well as NOx-dependent. Accounting for the influence of NOx using the VOC:NOx ratios resulted in better predictions of OA mass concentrations in rural/remote environments but still underpredicted OA mass concentrations in urban environments. The updated model's performance against measurements combined with the results from the sensitivity simulations suggests that the OA mass concentrations in southern California are constrained within a factor of 2. Finally, simulations performed for the year 2035 showed that, despite reductions in VOC and NOx emissions in the future, SOA mass concentrations may be higher than in the year 2005, primarily from increased hydroxyl radical (OH) concentrations due to lower ambient NO2 concentrations.
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    ItemOpen Access
    Data associated with the manuscript: Investigating diesel engines as an atmospheric source of isocyanic acid in urban areas
    (Colorado State University. Libraries, 2017) Jathar, Shantanu H.; Heppding, Christopher; Link, Michael F.; Farmer, Delphine K.; Akherati, Ali; Kleeman, Michael J.; de Gouw, Joost A.; Veres, Patrick R.; Roberts, James M.
    Isocyanic acid (HNCO), an acidic gas found in tobacco smoke, urban environments and biomass burning-affected regions, has been linked to adverse health outcomes. Gasoline- and diesel-powered engines and biomass burning are known to emit HNCO and hypothesized to emit precursors such as amides that can photochemically react to produce HNCO in the atmosphere. Increasingly, diesel engines in developed countries like the United States are required to use Selective Catalytic Reduction (SCR) systems to reduce tailpipe emissions of oxides of nitrogen. SCR chemistry is known to produce HNCO as an intermediate product, and SCR systems have been implicated as an atmospheric source of HNCO. In this work, we measure HNCO emissions from an SCR system-equipped diesel engine and, in combination with earlier data, use a three-dimensional chemical transport model (CTM) to simulate the ambient concentrations and source/pathway contributions to HNCO in an urban environment. Engine tests were conducted at three different engine loads, using two different fuels and at multiple operating points. HNCO was measured using an acetate chemical ionization mass spectrometer. The diesel engine was found to emit primary HNCO (3-90 mg kg-fuel-1) but we did not find any evidence that the SCR system or other aftertreatment devices (i.e., oxidation catalyst and particle filter) produced or enhanced HNCO emissions. The CTM predictions compared well with the only available observational data sets for HNCO in urban areas but under-predicted the contribution from secondary processes. The comparison implied that diesel-powered engines were the largest source of HNCO in urban areas. The CTM also predicted that daily-averaged concentrations of HNCO reached a maximum of ~110 pptv but were an order of magnitude lower than the 1 ppbv level that could be associated with physiological effects in humans. Precursor contributions from other combustion sources (gasoline and biomass burning) and wintertime conditions could enhance HNCO concentrations but need to be explored in future work.
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    ItemOpen Access
    Dataset associated with "Particle Size Distribution Dynamics Can Help Constrain the Phase State of Secondary Organic Aerosol"
    (Colorado State University. Libraries, 2021) He, Yicong; Akherati, Ali; Nah, Theodora; Nga, Ng; Garofalo, Lauren; Farmer, Delphine; Shiraiwa, Manabu; Zaveri, Rahul; Christopher, Cappa; Pierce, Jeff; Jathar, Shantanu
    Particle phase state is a property of atmospheric aerosols that has important implications for the formation, evolution, and gas/particle partitioning of secondary organic aerosol (SOA). In this work, we use a size-resolved chemistry and microphysics model (SOM-TOMAS), updated to include an explicit treatment of particle phase state, to constrain the bulk diffusion coefficient (Db) of SOA produced from alpha-pinene ozonolysis. By leveraging data from laboratory experiments performed in the absence of a seed and under dry conditions, we find that the Db for SOA can be constrained (1-5 ×10^-15 cm^2 s^-1 in these experiments) by simultaneously reproducing the time-varying SOA mass concentrations and the evolution of the particle size distribution. Another version of our model that used the predicted SOA composition to calculate the glass transition temperature, viscosity, and, ultimately, Db (~10-15 cm^2 s^-1) of the SOA was able to reproduce the mass and size distribution measurements when we included oligomer formation (oligomers accounted for about a fifth of the SOA mass). Our work highlights the potential of a size-resolved SOA model to constrain the particle phase state of SOA by utilizing historical measurements of the evolution of the particle size distribution.