Estimating biogenic CO2 fluxes is essential to quantify urban anthropogenic emissions, yet urban vegetation heterogeneity presents a significant challenge to making accurate estimations. We have developed an hourly temporal, 10-m spatial resolution biogenic CO2 flux estimation framework based on the Vegetation Photosynthesis and Respiration Model (VPRM) and its variants (UrbanVPRM and VPRM-modified). Unlike lower-resolution models, our approach captures finer-scale variability, particularly in fragmented urban green spaces like street trees and lawns. Results show that vegetation in Munich offsets 2.0%–2.8% of annual anthropogenic CO2 emissions in the study domain, with tree-covered areas as primary sinks and grasslands as net sources. During summer, daytime CO2 uptake can match or exceed anthropogenic emissions. Evaluations employing city park field measurements and eddy covariance towers confirm strong performance of our models, while highlighting VPRM-modified's advantage in grasslands and croplands, and UrbanVPRM's improvements in urban areas via impervious surface correction. These findings highlight the value of high-resolution modeling in improving urban carbon flux assessments.
Li et al. (Thu,) studied this question.