High-Resolution Urban Emission Mapping: Sensor-Driven CO2 Inverse Modeling in Glasgow

This study presents a comprehensive analysis of CO₂ emissions in Glasgow, utilizing a dense network of Berkeley Environmental Air quality and CO2 Network (BEACON) CO2 sensors for the year 2022. The research employs a sophisticated model setup, integrating high-resolution meteorological data from the Weather Research and Forecasting (WRF) model with a Lagrangian Particle Dispersion model for footprint modeling. A Bayesian inversion framework  developed by University of California, Berkeley refines a prior emission inventory using observed CO₂ concentrations and sensitivity footprints. The analysis reveals a 23% increase in overall mean anthropogenic emission for the year 2022 compared to available prior inventory estimate with significant seasonal variations. Winter fluxes  were  70%  higher than prior estimates, driven by increased heating demands and diminished biospheric uptake. Summer showed a 29% reduction, a combined impact of less energy demand for domestic heating and CO₂ uptake . A moderate negative correlation (R² = 0.58) between winter emission episodes and minimum daily temperatures was observed, highlighting the impact of domestic heating on CO₂ emissions. The study also found a 9.8% increase in total posterior emissions on weekends compared to weekdays, a smaller gap than the 21.8% difference in prior values. Our inverse model actively adjusts the emission values based on the real time CO2 measurement from sensors and high-resolution meteorology driven transport model at finer temporal scale, which is very valuable in making adjustments and validating local authority inventory data. Spatial analysis revealed that the most substantial emission changes were concentrated in areas corresponding to the 95th percentile of the posterior-prior emission difference. These regions, consistently exhibiting higher emissions throughout the year, reflect the combined impact of transport and heating sources in the city. These results highlight the urgent necessity for both enhancing building energy efficiency and  targeted strategies to reduce street level vehicular emission. Furthermore, the results point out the importance of continuous, sensor-based measurements for achieving a more precise representation of urban emission sources. This study also examines the impact of Glasgow's Low Emission Zone (LEZ) implemented in June 2023. A comparative analysis of CO₂ emissions and concentrations before and after the LEZ implementation provides insights into its effectiveness in reducing urban emissions. The findings underscore the importance of seasonal variability in emission patterns and the need to account for both anthropogenic activities and natural processes when analysing CO₂ fluxes at finer temporal and spatial scales.