1 research outputs found
Can we use atmospheric CO<sub>2</sub> measurements to verify emission trends reported by cities? Lessons from a 6-year atmospheric inversion over Paris
Existing CO2 emissions reported by city inventories
usually lag in real-time by a year or more and are prone to large
uncertainties. This study responds to the growing need for timely and
precise estimation of urban CO2 emissions to support present and
future mitigation measures and policies. We focus on the Paris metropolitan
area, the largest urban region in the European Union and the city with the
densest atmospheric CO2 observation network in Europe. We performed
long-term atmospheric inversions to quantify the citywide CO2
emissions, i.e., fossil fuel as well as biogenic sources and sinks, over 6Â years
(2016–2021) using a Bayesian inverse modeling system. Our inversion
framework benefits from a novel near-real-time hourly fossil fuel CO2
emission inventory (Origins.earth) at 1 km spatial resolution. In addition
to the mid-afternoon observations, we attempt to assimilate morning CO2
concentrations based on the ability of the Weather Research and Forecasting model with Chemistry (WRF-Chem) transport model to
simulate atmospheric boundary layer dynamics constrained by observed layer
heights. Our results show a long-term decreasing trend of around
2 % ± 0.6 % per year in annual CO2 emissions over the Paris
region. The impact of the COVID-19 pandemic led to a 13 % ± 1 %
reduction in annual fossil fuel CO2 emissions in 2020 with respect to
2019. Subsequently, annual emissions increased by 5.2 % ± 14.2 % from
32.6 ± 2.2 Mt CO2 in 2020 to 34.3 ± 2.3 Mt CO2 in 2021.
Based on a combination of up-to-date inventories, high-resolution
atmospheric modeling and high-precision observations, our current capacity
can deliver near-real-time CO2 emission estimates at the city scale in
less than a month, and the results agree within 10 % with independent
estimates from multiple city-scale inventories.</p