Increasing atmospheric CO₂ measurements in North America, especially in urban areas, may help enable the development of an operational CO₂ emission monitoring system. However, isolating the fossil fuel emission signal in the atmosphere requires factoring out CO₂ fluctuations due to the biosphere, especially during the growing season. To help improve simulations of the biosphere, here we customize the Vegetation Photosynthesis and Respiration Model (VPRM) at high-resolution for an eastern North American domain, upwind of coastal cities from Washington D.C. to Boston, MA, optimizing parameters using domain-specific flux tower data from 2001 to the present. We run three versions of VPRM from November 2016 to October 2017 using i) annual (VPRM_ann) and ii) seasonal parameters (VPRM_seas), and then iii) modifying the respiration equation to include the Enhanced Vegetation Index (EVI), a squared temperature term and interactions between temperature and water stress (VPRM_new). VPRM flux estimates are evaluated by comparison with other models (the Carnegie-Ames-Stanford Approach model, or CASA, and the Simple Biosphere Model v4), and with comparison to atmospheric CO₂ mole fraction data at 21 surface towers. Results show that VPRM_new is relatively unbiased and outperforms all other models in explaining CO₂ variability from April to October, while VPRM_ann overestimates growing season sinks by underestimating summertime respiration. Despite unknown remaining errors in VPRM_new, and uncertainties associated with other components of the atmospheric CO₂ comparisons, VPRM_new appears to hold promise for more effectively separating anthropogenic and biospheric signals in atmospheric inversion systems in eastern North America.