Long lived greenhouse gas (GHG; CO2, CH4, N2O, some CFCs) emissions play a critical role in regulating the Earth's climate. Urban environments increasingly lie at the core of many major environmental issues including climate change. Much of the human induced greenhouse gases (GHGs) emitted globally originate in or nearby cities. How do you measure the carbon balance of a mega-city? Society must be able to understand and predict the distribution of emitted GHGs within the urban atmosphere in order to assess the validity of emissions inventories, and the efficacy of any emission reduction programs. Uncertainties in self-reported 'bottom up' GHG emission inventories, derived from activity use data and generalized conversion factors, are often larger than emission reduction goals [IPCC, 2006; NRC, 2010]. This shortcoming can potentially be addressed by top-down (inverse) modeling that uses GHG measurements in the atmosphere, coupled with transport modeling and a priori flux constraints, to quantify source emissions.

This project, centered on observation and modeling of carbon fluxes in the Boston urban dome, has potentially broad impact, including: 1) use and refinement of the WRF-STILT model (which couples a research weather forecasting model with a Lagrangian particle dispersion model) to connect atmospheric (observation) with surface fluxes in large cities; 2) Regional and potentially worldwide applications of the model to verify regulatory, cap and trade and even global treaty needs; 3) Education of students and the public. Project data, results, and software will continue to be made publicly available during the proposed research.

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Harvard University
United States
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