Evaluating the efficacy of climate mitigation measures requires quantifying urban greenhouse gas (GHG) emissions. Both anthropogenic and biogenic GHG fluxes are important in urban systems, and disaggregation is necessary to understand urban GHG fluxes. One vegetative community common in these urban environments is turfgrass, and the Vegetation Photosynthesis and Respiration Model (VPRM), commonly used to create prior fluxes necessary for determining urban carbon dioxide (CO2) fluxes via inversion modeling, had assumed this Plant Functional Type (PFT) to be dormant in the winter. Two urban turfgrass flux towers in Indianapolis show a photosynthetic drawdown in the winter. We use data from these towers to create a new turfgrass PFT parameter set for VPRM. The new turfgrass PFT enables VPRM to simulate photosynthetic activity during winter, unlike the previously used parameter sets for grassland. We also find that less-managed lawns like cemeteries need different parameters than heavily managed lawns like golf courses, and seasonally changing parameters are needed to model these turf lawns. We use the revised VPRM to explore daily and seasonal variability in turfgrass fluxes and their impact, integrated across the city, on urban ecosystem CO2 fluxes. This study illustrates the importance of representing turfgrass as a unique PFT when quantifying urban GHG fluxes and the biases resulting from misrepresentation.

We evaluated the ability of a simple ecosystem carbon dioxide (CO2) flux model, the Vegetation Photosynthesis and Respiration Model (VPRM), to capture complex CO2 background conditions observed in Indianapolis, IN. Using simulated biogenic CO2 fluxes and mole fraction tower influence functions, we estimated biogenic CO2 mole fractions at three background towers in the Indianapolis Flux Experiment (INFLUX) network from April 2017 to March 2020. The model captures afternoon average CO2 enhancements, the difference between the background towers and a common reference tower, at a monthly time scale with no significant bias, with monthly mean residuals rarely differing significantly from zero. Although not central to our application, the model could not capture day-to-day variations of observed afternoon average CO2 enhancements. Random errors, when averaged over monthly to yearly time scales, were an order of magnitude smaller than typical urban enhancements. VPRM captured site-to-site differences in the average observed daily cycle of CO2 fluxes at agricultural eddy covariance flux sites well. For 13 of 14 site-months, the modeled peak afternoon NEE was within 30% of that observed despite the observed peaks ranging from about -7 to -70 µmol m-2s-1. VPRM can be effectively used in CO2 inversions to represent complex seasonal variations in background conditions observed in Indianapolis. Indianapolis, a modest-size city surrounded by strong ecosystem fluxes, represents a rigorous test for the VPRM system. Further, this study presents an evaluation system that can be applied to assess the performance of other ecosystem CO2 flux models in cities with similar monitoring networks.