Browsing by Author "Cohan, Daniel S"

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    Implementing and Improved Soil NOx Parameterization in the Community Multiscale Air Quality Model: Implications for Air Pollution
    (2014-12-05) Lash, Benjamin; Cohan, Daniel S; Griffin, Robert; Masiello, Caroline
    Soil NO emissions are critical to accurate atmospheric simulations which inform decisions to protect human health. Several studies indicate that the scheme, Yienger and Levy 1995 (YL95), underestimates soil NO emissions by a significant amount. The Berkeley Dalhousie Soil NOx Parameterization (BDSNP) updates soil NO emissions to be more consistent with satellite measurements. This work implements the BDSNP algorithm into CMAQ, adapting it to a 12km grid and comparing the resulting ozone, particulate, and other pollutants with results from the current YL95 algorithm for 2005 satellite data. Results show that summer NO emissions over the US double during the day, and in some places soil NO exceeds industrial sources. A comparison with satellite data, however, does not show strong evidence of the YL underestimation, contrary to other published results.
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    Mechanistic representation of soil nitrogen emissions in atmospheric modeling
    (2018-08-02) Rasool, Quazi Ziaur; Cohan, Daniel S
    Soils are a major and long overlooked source of reactive nitrogen emissions below our feet. These emissions include species like nitric oxide (NO), nitrous acid (HONO), nitrous oxide (N2O), and ammonia (NH3). Their prevalence in the summer ozone season (growing season) may become increasingly important as fertilizer use grows and fossil fuel combustion sources of nitrogen decline. Most air quality models, including the Community Multiscale Air Quality (CMAQ) model, use outdated parametric emissions schemes that neglect HONO and tend to underpredict soil NO and misrepresent its variability in time and space. This work introduces a mechanistic, process-oriented representation of soil emissions of N species (NO, HONO, N2O, and NH3) in a regional air quality model. The mechanistic scheme accounts for biogeochemical processes for soil N transformations such as mineralization, volatilization, nitrification, and denitrification. The rates of these processes are influenced by soil parameters, meteorology, land use, and mineral nitrogen availability. We account for spatial heterogeneity in soil conditions and biome types by using a global dataset for soil carbon and nitrogen across terrestrial ecosystems to estimate daily mineral N availability in non-agricultural soils, which was not accounted in earlier parametrizations for soil NO. Our mechanistic scheme also uses daily year-specific fertilizer data from the Environmental Policy Integrated Climate (EPIC) agricultural model. A soil map with sub-grid biome definitions was used to represent conditions over the continental United States. CMAQ modeling for May and July 2011 shows that the mechanistic scheme improves model performance for simulating Ozone Monitoring Instrument (OMI) satellite-observed NO2 columns for regions where soils are the dominant source of NO emissions. We also assess how the new scheme affects model performance for NOx (NO+NO2), nitrate (NO3) fine particulate matter, and ozone observed by various ground-based monitoring networks. Soil NO emissions in the new mechanistic scheme tend to fall between the magnitudes of the previous parametric schemes and display much more spatial heterogeneity. The enhanced representation of soil biogeochemical processes introduced here could enable future studies to explore how agricultural practices and climate change impact soil emissions and air quality.
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    Sensitivities of Biogenic Volatile Organic Compounds to Climatological Factors Affected by Drought
    (2015-03-27) Chavez-Figueroa, Erin Michelle; Cohan, Daniel S; Griffin, Rob; Raun, Loren
    Drought is expected to increase in both intensity and duration in our changing climate. However, the combined effects of drought conditions on the emissions of biogenic volatile organic compounds (BVOC) from vegetation are uncertain due to contradictory responses to the individual drought components. While increased temperature causes an increase in emissions, for instance, low enough soil moisture causes a decrease. This study therefore explored the impacts of variations in individual climate conditions on BVOC emissions. The sensitivity of BVOC emissions to leaf area index (LAI), photosynthetically active radiation (PAR), temperature, and precipitation were assessed using both ground measurements and the model MEGAN. While variations in PAR and LAI were less important than temperature in explaining variation in BVOC emissions, the choice of input data proved important. Satellite PAR produced lower isoprene emissions estimates than PAR generated by the meteorological model WRF. Higher resolution LAI data produced more spatial variability in isoprene emissions estimates. Drought was not found to correspond well to BVOC emissions, with temperature providing a much better predictor of emissions at a given location.