A decade of CO2 flux measured by the eddy covariance method including the COVID-19 pandemic period in an urban center in Sakai, Japan.

Cities constitute an important source of greenhouse gases, but few results originating from long-term, direct CO2 emission monitoring efforts have been reported. In this study, CO2 emissions were quasi-continuously measured in an urban center in Sakai, Osaka, Japan by the eddy covariance method from 2010 to 2021. Long-term CO2 emissions reached 22.2 ± 2.0 kg CO2 m-2 yr-1 from 2010 to 2019 (± denotes the standard deviation) in the western sector from the tower representing the densely built-up area. Throughout the decade, the annual CO2 emissions remained stable. According to an emission inventory, traffic emissions represented the major source of CO2 emissions within the flux footprint. The interannual variations in the annual CO2 flux were positively correlated with the mean annual traffic counts at two highway entrances and exits. The CO2 emissions decreased suddenly, by 32% ± 3.1%, in April and May 2020 during the period in which the first state of emergency associated with COVID-19 was declared. The annual CO2 emissions also decreased by 25% ± 3.1% in 2020. Direct long-term observations of CO2 emissions comprise a useful tool to monitor future emission reductions and sudden disruptions in emissions, such as those beginning in 2020 during the COVID-19 pandemic.

Impact of Singapore's COVID-19 confinement on atmospheric CO2 fluxes at neighborhood scale.

Singapore entered a two-month partial lockdown in April 2020 to curb the spread of COVID-19. The imposed measures in addition to contain the virus spread, cut the emissions of greenhouse gases as many economic activities stopped across the city. The advice of stay-at-home changed the pattern of carbon dioxide (CO2) emissions within the community. To examine how CO2 emissions responded to the COVID-19 measures at neighborhood scale, anonymized mobility data released by Google and Apple, and traffic congestion information from TomTom were used to track daily and diurnal changes in emissions related to driving, cooking and metabolic breathing in a residential neighborhood of Singapore, in which the anthropogenic and biogenic fluxes of CO2 have been widely characterized. During the lockdown, traffic emissions dropped 41%, but emissions from cooking and metabolic breathing increased 21% and 20%, respectively. The uptake of CO2 by vegetation was not able to offset these emissions, and after adding the biogenic contribution from soil and plants, a net reduction of 24% was found. During the following six months the city got its pace back, with the rate of CO2 emissions reaching similar or slightly higher levels than those predicted before the pandemic crisis. Unfortunately, the stark drop in emissions was just a temporary relief, which reduced only 3.5% the annual CO2 flux over the studied neighborhood.