A53L-3378:
CO2 Biogenic vs Anthropogenic Sectoral Contribution for INFLUX
Abstract:
The Indianapolis Flux Experiment (INFLUX) aims to use a top-down inversion methodology to quantify sources of Greenhouse Gas (GHG) emissions over an urban domain with high spatial and temporal resolution. This project is an experimental test bed which is intended to establish reliable methods for quantifying and validating GHG emissions independently of the inventory methods typically used for Measurement, Reporting and Verification (MRV) of pollution sources. Analyzing the contribution of different source types or sectors is a fundamental step in order to achieve an accuracy level desired for such MRV applications. This is especially challenging when attempting to determine anthropogenic emissions during the growing season since biological GHG fluxes reach a maximum at this time.To this end, the Weather Research and Forecasting Model (WRF-ARW) version 3.5.1 was used along with a modified version of the Green House Gases chemistry module for simulating the CO2 mole fraction transport during September and October 2013. Sectoral anthropogenic CO2 emissions were obtained from Hestia 2012 and from Vulcan 2002 beyond the spatial coverage of Hestia. Biogenic CO2 emissions were simulated by using an augmented version of the “Vegetation Photosynthesis and Respiration Model” (VPRM) included in WRF-CHEM. An implementation of the unconstrained nonlinear global optimization method of Nelder and Mead was employed to find the optimum values for the VPRM parameters for each vegetation category by using data from Ameriflux eddy covariance flux towers.
Here we present a preliminary assessment of the relative contribution of biological vs sectoral anthropogenic CO2 fluxes on the INFLUX measurements network. The simulations are compared to tower and aircraft measurements that include trace gases with the capacity to distinguish observationally anthropogenic and biogenic CO2 sources and sinks. In addition, an evaluation of the sensitivity of the sectoral attribution to meteorological errors is discussed.