student and faculty conducting research

PhD Students and Post-Doctoral Researchers

Srinidhi Balasubramanian

  • Advisor:
      • Professor Mark J Rood and Dr. Sotiria Koloutsou-Vakakis
  • Departments:
    • Civil and Environmental Engineering
  • Areas of Expertise:
      • Air quality modeling
      • Emissions inventories
      • Geographical Information Systems

  • Thesis Title:
  • Thesis abstract:
      • Managing impacts of the reactive nitrogen (Nr) cascade due to increasing food and fossil fuel requirements, has been recognized by the National Academy of Engineering as a Grand Engineering Challenge. Among the Nr species, ammonia (NH3) plays an important role for air quality. NH3 is a precursor to atmospheric particulate matter (PM) which is regulated worldwide for impacts on human health and visibility, with additional implications for climate change. Deposition of NH3 and other Nr species results in surface water eutrophication, soil acidification, and detrimental effects to vegetation where critical nutrient loads are exceeded. NH3 is primarily emitted from agriculture, with predominant contributions from chemical fertilizer usage in the Midwest U.S. Modeling air quality impacts of this source, using chemical transport models (CTMs), requires emission inventories that capture underlying spatial and temporal trends. Currently, NH3 emissions from chemical fertilizer usage are estimated by combining annual, county-level fertilizer sales with emission factors. Gridded emissions are subsequently developed using empirical spatial and temporal factors to match the high-spatial resolution and hourly time scales required by CTMs. This approach introduces uncertainties, as it does not capture the complex interactions between farm practices, crop and soil meteorological conditions. In response to these challenges, this research focuses on the development of a representative NH3 emission inventory for chemical fertilizer usage, for the Midwest U.S., by incorporating regional agricultural management data. First, existing spatial factors have been modified to include crop-specific nitrogen loading and allocate emissions to modeling grids of 4 km x 4 km resolution. This approach resulted in identification of NH3 emission hotspots (areas of intense emissions) at sub-county resolutions. Second, temporal variability in NH3 emissions was resolved at the daily scale by employing the Denitrification Decomposition (DNDC) model. By combining timing and amount of nitrogen loading with crop, soil and weather data, peaks in NH3 emissions in summer and fall were identified. Identified temporal trends in NH3 emissions will be validated using measurements of NH3 emissions over a corn canopy from an intensive field campaign. Additionally, the developed emission inventory will be evaluated in terms of its ability to model ambient NH3, PM10, PM2.5 and wet deposition of NH4+ using a state of the art air quality model. The need for high-spatial resolution inputs for CTMs will be also be evaluated. These effort are expected to culminate in an improved understanding of the role of NH3 emissions from chemical fertilizer usage in the Midwest U.S. to regional air quality and atmospheric deposition.
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