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Dr. Daniel Cohan
Associate Professor
Civil and Environmental Engineering
Rice University
6100 Main Street MS 519
Houston, TX 77005

Phone: 713-348-5129
Office: Keck Hall 116B
Email: cohan 'at' rice.edu

The research group of Prof. Daniel Cohan at Rice University focuses on the application of photochemical models to air quality management. Current research includes:


Improving Biogenic Emission Estimates using Satellite DataImproving Biogenic Emission Estimates using Satellite Data
Vegetation is the leading source of volatile organic compound (VOC) emissions, which can affect regional and urban air quality by contributing to ozone and particulate matter formation. Biogenic VOC emission estimates depend on temperature, vegetation conditions, and the amount of sunlight (specifically, photosynthetically active radiation (PAR)) reaching the ground. Due to the frequent underestimation of clouds in meteorological models, PAR estimates in current biogenic emission models are largely uncertain.read more »
Soil Emissions ModelingSoil Emissions Modeling
Emissions of reactive nitrogen compounds from soil are important, but potentially underestimated, contributors to atmospheric chemistry. In particular, some studies suggest soil emissions of NO may be twice as large as previous estimates; other studies suggest soils represent a previously unrecognized source of HONO. read more »
Energy System and Electricity Sector ModelingEnergy System and Electricity Sector Modeling
Models that capture interactions across the energy-economy-environment system can be used to better inform and guide policy decisions. In order to be used most effectively, however, such a model should consider all three aspects of the system in sufficient detail and be able to take full advantage of the linkages between them.
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Retrospective Assessments of Air Quality PlansRetrospective Assessments of Air Quality Plans
While EPA sets and revises National Ambient Air Quality Standards (NAAQS) for a criteria air pollutant, it is the States that must develop state implementation plans (SIPs) for attaining those standards. Despite the critical importance of these plans to air quality, the efficacy of SIPs has rarely been examined retrospectively.

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Satellite Data to Enhance Ozone ModelingSatellite Data to Enhance Ozone Modeling
Satellites provide opportunities to remotely sense atmospheric data with far greater spatial coverage than is possible from ground-based observational networks. Our research is exploring the incorporation of two types of data – photolysis rates based on GOES satellite measurements of clouds, and NO2 measurements from the OMI satellite – to enhance photochemical modeling of ground-level ozone. read more »