Direct observations of CO2 emission reductions due to COVID-19 lockdown across European urban districts

Nicolini, Giacomo; Antoniella, Gabriele; Carotenuto, Federico; Christen, Andreas; Ciais, Philippe; Feigenwinter, Christian; Gioli, Beniamino; Stagakis, Stavros; Velasco, Erik; Vogt, Roland; Ward, Helen C.; Barlow, Janet F.; Chrysoulakis, Nektarios; Duce, Pierpaolo; Graus, M.; Helfter, Carole; Heusinkveld, B.G.; Järvi, Leena; Karl, T.; Marras, Serena; Masson, Valéry; Matthews, Bradley; Meier, Fred; Nemitz, Eiko; Sabbatini, Simone; Scherer, Dieter; Schume, Helmut; Sîrca, C.; Steeneveld, G.J.; Vagnoli, Carolina; Wang, Yilong; Zaldei, Alessandro; Zheng, Bo; Papale, Dario

doi:10.1016/j.scitotenv.2022.154662

Cited by 55 publications

(34 citation statements)

References 36 publications

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“…The importance of atmospheric transport is also relevant for our analysis of the Amsterdam fluxes. We underestimate the fluxes, which we attribute to the small footprint of the flux tower, which is much smaller than the grid cells in our model (Nicolini et al, 2022). A minor contribution to the underestimation is that we do not account for human respiration in our model, which attributes roughly 3 % of the total CO 2 flux in urban areas (Ciais et al, 2020).…”

Section: Atmospheric Transportmentioning

confidence: 85%

Near-real-time CO₂ fluxes from CarbonTracker Europe for high-resolution atmospheric modeling

Woude

Kok²,

Smith³

et al. 2023

Earth Syst. Sci. Data

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Abstract. We present the CarbonTracker Europe High-Resolution (CTE-HR) system that estimates carbon dioxide (CO2) exchange over Europe at high resolution (0.1 × 0.2∘) and in near real time (about 2 months' latency). It includes a dynamic anthropogenic emission model, which uses easily available statistics on economic activity, energy use, and weather to generate anthropogenic emissions with dynamic time profiles at high spatial and temporal resolution (0.1×0.2∘, hourly). Hourly net ecosystem productivity (NEP) calculated by the Simple Biosphere model Version 4 (SiB4) is driven by meteorology from the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5th Generation (ERA5) dataset. This NEP is downscaled to 0.1×0.2∘ using the high-resolution Coordination of Information on the Environment (CORINE) land-cover map and combined with the Global Fire Assimilation System (GFAS) fire emissions to create terrestrial carbon fluxes. Ocean CO2 fluxes are included in our product, based on Jena CarboScope ocean CO2 fluxes, which are downscaled using wind speed and temperature. Jointly, these flux estimates enable modeling of atmospheric CO2 mole fractions over Europe. We assess the skill of the CTE-HR CO2 fluxes (a) to reproduce observed anomalies in biospheric fluxes and atmospheric CO2 mole fractions during the 2018 European drought, (b) to capture the reduction of anthropogenic emissions due to COVID-19 lockdowns, (c) to match mole fraction observations at Integrated Carbon Observation System (ICOS) sites across Europe after atmospheric transport with the Transport Model, version 5 (TM5) and the Stochastic Time-Inverted Lagrangian Transport (STILT), driven by ECMWF-IFS, and (d) to capture the magnitude and variability of measured CO2 fluxes in the city center of Amsterdam (the Netherlands). We show that CTE-HR fluxes reproduce large-scale flux anomalies reported in previous studies for both biospheric fluxes (drought of 2018) and anthropogenic emissions (COVID-19 pandemic in 2020). After applying transport of emitted CO2, the CTE-HR fluxes have lower median root mean square errors (RMSEs) relative to mole fraction observations than fluxes from a non-informed flux estimate, in which biosphere fluxes are scaled to match the global growth rate of CO2 (poor person's inversion). RMSEs are close to those of the reanalysis with the CTE data assimilation system. This is encouraging given that CTE-HR fluxes did not profit from the weekly assimilation of CO2 observations as in CTE. We furthermore compare CO2 concentration observations at the Dutch Lutjewad coastal tower with high-resolution STILT transport to show that the high-resolution fluxes manifest variability due to different emission sectors in summer and winter. Interestingly, in periods where synoptic-scale transport variability dominates CO2 concentration variations, the CTE-HR fluxes perform similarly to low-resolution fluxes (5–10× coarsened). The remaining 10 % of the simulated CO2 mole fraction differs by >2 ppm between the low-resolution and high-resolution flux representation and is clearly associated with coherent structures (“plumes”) originating from emission hotspots such as power plants. We therefore note that the added resolution of our product will matter most for very specific locations and times when used for atmospheric CO2 modeling. Finally, in a densely populated region like the Amsterdam city center, our modeled fluxes underestimate the magnitude of measured eddy covariance fluxes but capture their substantial diurnal variations in summertime and wintertime well. We conclude that our product is a promising tool for modeling the European carbon budget at a high resolution in near real time. The fluxes are freely available from the ICOS Carbon Portal (CC-BY-4.0) to be used for near-real-time monitoring and modeling, for example, as an a priori flux product in a CO2 data assimilation system. The data are available at https://doi.org/10.18160/20Z1-AYJ2 (van der Woude, 2022a).

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Section: Atmospheric Transportmentioning

confidence: 85%

Near-real-time CO₂ fluxes from CarbonTracker Europe for high-resolution atmospheric modeling

Woude

Kok²,

Smith³

et al. 2023

Earth Syst. Sci. Data

Self Cite

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“…Alternative ground-based atmospheric measurements were also used to assess ffCO 2 emission reductions during the pandemic. Strong reductions in CO 2 fluxes (−5 to −87%) were observed during lockdown periods relative to the same times in previous years in 11 European cities using eddy-covariance measurements of CO 2 exchange (Nicolini et al, 2022). Atmospheric oxygen measurements were applied as novel tracers for ffCO 2 emissions in the United Kingdom and detected a 23% (14%-32%) ffCO 2 reduction in 2020 annual emissions relative to a modeled scenario without the COVID-19 pandemic (Pickers et al, 2022).…”

mentioning

confidence: 92%

Reductions in California's Urban Fossil Fuel CO₂ Emissions During the COVID‐19 Pandemic

Hopkins

Tavares

et al. 2022

AGU Advances

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Carbon dioxide (CO 2 ) emissions associated with fossil fuel consumption (ffCO 2 ) are the dominant cause of climate change (IPCC, 2022). Hence, there is an urgent need to quantify ffCO 2 emissions to support the success of climate change mitigation efforts. Urban areas account for 30%-84% of global ffCO 2 emissions (Seto et al., 2014), despite encompassing less than 1% of the Earth's land area (Zhou et al., 2015). While being disproportional contributors to climate change, cities are also at the forefront of climate change mitigation actions (Rosenzweig et al., 2010), making them a top priority for quantifying and monitoring ffCO 2 emission reduction efforts.Satellite-borne instruments can detect CO 2 enhancements (i.e., 6 ppm above background) over large cities (Kiel et al., 2021;Schwandner et al., 2017), and urban tower networks continuously measure CO 2 levels in a small selection of cities in more economically developed countries. However, these atmospheric observation systems

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“…Air quality worsens as people move from their residences to their destinations such as places of work, recreation centers, and grocery shops and becomes better as movement lessens. Indeed, air quality improved during COVID-19 lockdowns around the world (Sannigrahi et al 2021 ; Yechezkel et al 2021 ; Wijnands et al 2022 ; Naseer et al 2022 ; Benchrif et al 2021 ; Mishra et al 2021 ; Broomandi et al 2022 ; Arora et al 2020 ; Li et al 2022 ; Khan et al 2021 ; Nicolini et al 2022 ; Marinello et al 2021 ; Bar et al 2021 ), with most gains in air quality lost when the lockdowns were lifted, indicating that air quality could depict mobility patterns of individuals.…”

Section: Introductionmentioning

confidence: 99%

Air pollution and mobility patterns in two Ugandan cities during COVID-19 mobility restrictions suggest the validity of air quality data as a measure for human mobility

Galiwango

Bainomugisha

Kivunike

et al. 2022

Environ Sci Pollut Res

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We explored the viability of using air quality as an alternative to aggregated location data from mobile phones in the two most populated cities in Uganda. We accessed air quality and Google mobility data collected from 15th February 2020 to 10th June 2021 and augmented them with mobility restrictions implemented during the COVID-19 lockdown. We determined whether air quality data depicted similar patterns to mobility data before, during, and after the lockdown and determined associations between air quality and mobility by computing Pearson correlation coefficients ($$R$$ R ), conducting multivariable regression with associated confidence intervals (CIs), and visualized the relationships using scatter plots. Residential mobility increased with the stringency of restrictions while both non-residential mobility and air pollution decreased with the stringency of restrictions. In Kampala, PM2.5 was positively correlated with non-residential mobility and negatively correlated with residential mobility. Only correlations between PM2.5 and movement in work and residential places were statistically significant in Wakiso. After controlling for stringency in restrictions, air quality in Kampala was independently correlated with movement in retail and recreation (− 0.55; 95% CI = − 1.01– − 0.10), parks (0.29; 95% CI = 0.03–0.54), transit stations (0.29; 95% CI = 0.16–0.42), work (− 0.25; 95% CI = − 0.43– − 0.08), and residential places (− 1.02; 95% CI = − 1.4– − 0.64). For Wakiso, only the correlation between air quality and residential mobility was statistically significant (− 0.99; 95% CI = − 1.34– − 0.65). These findings suggest that air quality is linked to mobility and thus could be used by public health programs in monitoring movement patterns and the spread of infectious diseases without compromising on individuals’ privacy.

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Direct observations of CO2 emission reductions due to COVID-19 lockdown across European urban districts

Cited by 55 publications

References 36 publications

Near-real-time CO₂ fluxes from CarbonTracker Europe for high-resolution atmospheric modeling

Near-real-time CO₂ fluxes from CarbonTracker Europe for high-resolution atmospheric modeling

Reductions in California's Urban Fossil Fuel CO₂ Emissions During the COVID‐19 Pandemic

Air pollution and mobility patterns in two Ugandan cities during COVID-19 mobility restrictions suggest the validity of air quality data as a measure for human mobility

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Direct observations of CO2 emission reductions due to COVID-19 lockdown across European urban districts

Cited by 55 publications

References 36 publications

Near-real-time CO2 fluxes from CarbonTracker Europe for high-resolution atmospheric modeling

Near-real-time CO2 fluxes from CarbonTracker Europe for high-resolution atmospheric modeling

Reductions in California's Urban Fossil Fuel CO2 Emissions During the COVID‐19 Pandemic

Air pollution and mobility patterns in two Ugandan cities during COVID-19 mobility restrictions suggest the validity of air quality data as a measure for human mobility

Contact Info

Product

Resources

About

Near-real-time CO₂ fluxes from CarbonTracker Europe for high-resolution atmospheric modeling

Near-real-time CO₂ fluxes from CarbonTracker Europe for high-resolution atmospheric modeling

Reductions in California's Urban Fossil Fuel CO₂ Emissions During the COVID‐19 Pandemic