Urban CO2 Flux Research Articles

Urban sources of methane characterised by long-term eddy covariance observations in central Europe

Multiyear eddy covariance measurements of methane and carbon dioxide were performed in Innsbruck, Austria, a mid-sized European city in the Alps. Annual mean methane and carbon dioxide fluxes were on the order of 21.6 nmol/m2/s and 11.7 μmol/m2/s respectively. Methane fluxes increased significantly with decreasing temperature and showed a negligible weekend to weekday effect. Accompanying non-methane volatile organic compound (NMVOC) measurements provided additional constraints on urban methane sources during an intensive 6-week campaign in 2021. Positive matrix factorization analysis identified a unique and dominant methane source. Contributions from biomass burning and vehicle emissions were found to be small. No evidence was found for a large unknown biogenic source. A second intensive campaign in 2023 revealed that the measured ethane to methane enhancement in turbulent plumes showed a typical ratio of 5.2 ± 0.6%, close to the unburned ratio of natural gas (5%) in Austria. The analysis suggests that urban methane fluxes are likely to be dominated by end-user releases rather than natural gas leaks in the pipeline system. Long-term eddy flux observations also allowed identifying the existence of urban super-emitters, which brought area weighted methane fluxes up to 39 nmol/m2/s in 2022. On average, the 100 y global warming potential of methane emitted by natural gas combustion activities is 6% relative to the total urban CO2 flux, and ∼12% relative to CO2 emissions from the residential, commercial and public sectors in Innsbruck.

A high-resolution monitoring approach of urban CO2 fluxes. Part 2 – surface flux optimisation using eddy covariance observations

Achieving climate neutrality by 2050 requires ground-breaking technological and methodological advancements in climate change mitigation planning and actions from local to regional scales. Monitoring the cities' CO2 emissions with sufficient detail and accuracy is crucial for guiding sustainable urban transformation. Current methodologies for CO2 emission inventories rely on bottom-up (BU) approaches which do not usually offer information on the spatial or temporal variability of the emissions and present substantial uncertainties. This study develops a novel approach which assimilates direct CO2 flux observations from urban eddy covariance (EC) towers with very high spatiotemporal resolution information from an advanced urban BU surface flux model (Part 1 of this study, Stagakis et al., 2023) within a Bayesian inversion framework. The methodology is applied to the city centre of Basel, Switzerland (3 × 3 km domain), taking advantage of two long-term urban EC sites located 1.6 km apart. The data assimilation provides optimised gridded CO2 flux information individually for each urban surface flux component (i.e. building heating emissions, commercial/industrial emissions, traffic emissions, human respiration emissions, biogenic net exchange) at 20 m resolution and weekly time-step. The results demonstrate that urban EC observations can be consistently used to improve high-resolution BU surface CO2 flux model estimations, providing realistic seasonal variabilities of each flux component. Traffic emissions are determined with the greatest confidence among the five flux components during the inversions. The optimised annual anthropogenic emissions are 14.7 % lower than the prior estimate, the human respiration emissions have decreased by 12.1 %, while the biogenic components transformed from a weak sink to a weak source. The root-mean-square errors (RMSEs) of the weekly comparisons between EC observations and model outputs are consistently reduced. However, a slight underestimation of the total flux, especially in locations with complex CO2 source/sink mixture, is still evident in the optimised fluxes.

A high-resolution monitoring approach of urban CO2 fluxes. Part 1 - bottom-up model development

Monitoring carbon dioxide (CO2) emissions of urban areas is increasingly important to assess the progress towards the Paris Agreement goals for climate neutrality. Cities are currently voluntarily developing their local inventories, however, the approaches used across different cities are not systematically assessed, present consistency issues, neglect the biogenic fluxes and have restricted spatial and temporal resolution. In order to assess the accuracy of the urban emission inventories and provide information which is useful for planning local climate change mitigation actions, high resolution modelling approaches combined or evaluated with atmospheric observations are needed. This study presents a new high-resolution bottom-up (BU) model which provides hourly maps of all major components contributing to the local urban surface CO2 flux (i.e. building emissions, traffic emissions, human respiration, soil respiration, plant respiration, plant photosynthetic uptake) and can therefore be used for direct comparison with in-situ atmospheric observations and development of local scale atmospheric inversion methodologies. The model design aims to be simple and flexible using inputs that are available in most cities, facilitating transferability to different locations. The inputs are primarily based on open geospatial datasets, census information, road traffic monitoring and basic meteorological parameters. The model is applied on the city centre of Basel, Switzerland, for the year 2018 and the results are compared to a local inventory. It is demonstrated that the model captures the highly dynamic spatiotemporal variability of the urban CO2 fluxes according to main environmental drivers, population activity dynamics and geospatial information proxies. The annual modelled emissions from buildings and traffic are estimated 14.8 % and 9 % lower than the respective information derived by the local inventory. The differences are mainly attributed to the emissions from the industrial areas and the highways which are beyond the geographical coverage of the model.

Spatiotemporal variations in urban CO2 flux with land-use types in Seoul

BackgroundCities are a major source of atmospheric CO2; however, understanding the surface CO2 exchange processes that determine the net CO2 flux emitted from each city is challenging owing to the high heterogeneity of urban land use. Therefore, this study investigates the spatiotemporal variations of urban CO2 flux over the Seoul Capital Area, South Korea from 2017 to 2018, using CO2 flux measurements at nine sites with different urban land-use types (baseline, residential, old town residential, commercial, and vegetation areas).ResultsAnnual CO2 flux significantly varied from 1.09 kg C m− 2 year− 1 at the baseline site to 16.28 kg C m− 2 year− 1 at the old town residential site in the Seoul Capital Area. Monthly CO2 flux variations were closely correlated with the vegetation activity (r = − 0.61) at all sites; however, its correlation with building energy usage differed for each land-use type (r = 0.72 at residential sites and r = 0.34 at commercial sites). Diurnal CO2 flux variations were mostly correlated with traffic volume at all sites (r = 0.8); however, its correlation with the floating population was the opposite at residential (r = − 0.44) and commercial (r = 0.80) sites. Additionally, the hourly CO2 flux was highly related to temperature. At the vegetation site, as the temperature exceeded 24 ℃, the sensitivity of CO2 absorption to temperature increased 7.44-fold than that at the previous temperature. Conversely, the CO2 flux of non-vegetation sites increased when the temperature was less than or exceeded the 18 ℃ baseline, being three-times more sensitive to cold temperatures than hot ones. On average, non-vegetation urban sites emitted 0.45 g C m− 2 h− 1 of CO2 throughout the year, regardless of the temperature.ConclusionsOur results demonstrated that most urban areas acted as CO2 emission sources in all time zones; however, the CO2 flux characteristics varied extensively based on urban land-use types, even within cities. Therefore, multiple observations from various land-use types are essential for identifying the comprehensive CO2 cycle of each city to develop effective urban CO2 reduction policies.

Tall tower eddy covariance measurements of CO2 fluxes in Vienna, Austria

This study reports on three years (2018–2020) of turbulent CO2 fluxes measured at 144 m above the city of Vienna, Austria using an eddy covariance system installed on the A1 Arsenal radio tower. Overall CO2 flux data availability after quality control filtering (49%) was comparable to that observed by other studies of urban and suburban eddy covariance measurements. Average monthly CO2 fluxes followed seasonal trends in temperature-based proxies of heating demand, with the highest fluxes observed in the winter months. When analysing separate trends for the two dominating wind directions, this seasonality was most pronounced for the flows from the north-west when flux footprints overlapped with Vienna's most populated and urbanised districts and fluxes. For flows from the south-east, when flux footprints covered areas of built-up and industrial land yet were dominated by green urban spaces and arable land, the seasonality was much less marked and average monthly CO2 fluxes were generally lower, particularly in winter. Weekday-weekend patterns as well as weekday diurnal variations in CO2 generally followed respective trends in local traffic counts; however, flux correlations with hourly traffic counts on weekends and public holidays were much weaker. Weekend/public holiday diurnal trends in CO2 fluxes indicated an influence of vegetation fluxes on net CO2 flux variations between midday and late afternoon in spring and summer. Furthermore, variations in weekend/public holiday CO2 fluxes from night-time to morning periods suggested a partial night-time decoupling between turbulent exchange at 144 m and the net fluxes at the surface. While the influence of CO2 advection could not be quantified, the pronounced morning flux peaks indicated that CO2 released to the atmosphere during these partially decoupled, night-time periods accumulated to some extent and was subsequently mixed vertically with the morning increase in boundary layer depth. Indeed, the calculated annual fluxes suggested that positive and negative 30-min biases were largely offset when averaging over longer time intervals. The 2018 flux of 10.89 kt CO2 km−2 was in close agreement with the annual CO2 emissions estimate of 10.19 kt CO2 km−2 derived from an official emissions inventory (excluding large point source emissions). A similar annual flux was observed in 2019; however, the substantially lower flux in 2020 likely reflected emissions reductions associated with the COVID-19 pandemic. Comparison of normalised daytime CO2 fluxes between years indicated that the initial lockdown led to a ca. 50–60% reduction in net CO2 emissions from Vienna's most populated and urbanised districts. This study thus provides further evidence that defensible estimates of urban CO2 fluxes can be achieved with tall tower eddy covariance.

Synthesis of Urban CO2 Emission Estimates from Multiple Methods from the Indianapolis Flux Project (INFLUX).

Urban areas contribute approximately three-quarters of fossil fuel derived CO2 emissions, and many cities have enacted emissions mitigation plans. Evaluation of the effectiveness of mitigation efforts will require measurement of both the emission rate and its change over space and time. The relative performance of different emission estimation methods is a critical requirement to support mitigation efforts. Here we compare results of CO2 emissions estimation methods including an inventory-based method and two different top-down atmospheric measurement approaches implemented for the Indianapolis, Indiana, U.S.A. urban area in winter. By accounting for differences in spatial and temporal coverage, as well as trace gas species measured, we find agreement among the wintertime whole-city fossil fuel CO2 emission rate estimates to within 7%. This finding represents a major improvement over previous comparisons of urban-scale emissions, making urban CO2 flux estimates from this study consistent with local and global emission mitigation strategy needs. The complementary application of multiple scientifically driven emissions quantification methods enables and establishes this high level of confidence and demonstrates the strength of the joint implementation of rigorous inventory and atmospheric emissions monitoring approaches.

Joint inverse estimation of fossil fuel and biogenic CO2 fluxes in an urban environment: An observing system simulation experiment to assess the impact of multiple uncertainties

The Indianapolis Flux Experiment aims to utilize a variety of atmospheric measurements and a high-resolution inversion system to estimate the temporal and spatial variation of anthropogenic greenhouse gas emissions from an urban environment. We present a Bayesian inversion system solving for fossil fuel and biogenic CO2 fluxes over the city of Indianapolis, IN. Both components were described at 1 km resolution to represent point sources and fine-scale structures such as highways in the a priori fluxes. With a series of Observing System Simulation Experiments, we evaluate the sensitivity of inverse flux estimates to various measurement deployment strategies and errors. We also test the impacts of flux error structures, biogenic CO2 fluxes and atmospheric transport errors on estimating fossil fuel CO2 emissions and their uncertainties. The results indicate that high-accuracy and high-precision measurements produce significant improvement in fossil fuel CO2 flux estimates. Systematic measurement errors of 1 ppm produce significantly biased inverse solutions, degrading the accuracy of retrieved emissions by about 1 µmol m–2 s–1 compared to the spatially averaged anthropogenic CO2 emissions of 5 µmol m–2 s–1. The presence of biogenic CO2 fluxes (similar magnitude to the anthropogenic fluxes) limits our ability to correct for random and systematic emission errors. However, assimilating continuous fossil fuel CO2 measurements with 1 ppm random error in addition to total CO2 measurements can partially compensate for the interference from biogenic CO2 fluxes. Moreover, systematic and random flux errors can be further reduced by reducing model-data mismatch errors caused by atmospheric transport uncertainty. Finally, the precision of the inverse flux estimate is highly sensitive to the correlation length scale in the prior emission errors. This work suggests that improved fossil fuel CO2 measurement technology, and better understanding of both prior flux and atmospheric transport errors are essential to improve the accuracy and precision of high-resolution urban CO2 flux estimates.

Statistical partitioning of a three-year time series of direct urban net CO2 flux measurements into biogenic and anthropogenic components

Eddy covariance flux measurements are increasingly used to quantify the net carbon dioxide exchange (FC) in urban areas. FC represents the sum of anthropogenic emissions, biogenic carbon release from plant and soil respiration, and carbon uptake by plant photosynthesis. When FC is measured in natural ecosystems, partitioning into respiration and photosynthesis is a well-established procedure. In contrast, few studies have partitioned FC at urban flux tower sites due to the difficulty of accounting for the temporal and spatial variability of the multiple sources and sinks. Here, we partitioned a three-year time series of flux measurements from a suburban neighborhood of Minneapolis-Saint Paul, Minnesota, USA. We segregated FC into one subset that captured fluxes from a residential neighborhood and into another subset that covered a golf course. For both land use types we modeled anthropogenic flux components based on winter data and extrapolated them to the growing season, to estimate gross primary production (GPP) and ecosystem respiration (Reco) at half-hourly, daily, monthly and annual scales. During the growing season, GPP had the largest magnitude (up to − 9.83 g C m−2 d−1) of any component CO2 flux, biogenic or anthropogenic, and both GPP and Reco were more dynamic seasonally than anthropogenic fluxes. Owing to the balancing of Reco against GPP, and the limitations of the growing season in a cold temperate climate zone, the net biogenic flux was only 1.5%–4.5% of the anthropogenic flux in the dominant residential land use type, and between 25%–31% of the anthropogenic flux in highly managed greenspace. Still, the vegetation sink at our site was stronger than net anthropogenic emissions on 16–20 days over the residential area and on 66–91 days over the recreational area. The reported carbon flux sums and dynamics are a critical step toward developing models of urban CO2 fluxes within and across cities that differ in vegetation cover.

Optimizing the Spatial Resolution for Urban CO2 Flux Studies Using the Shannon Entropy

The ‘Hestia Project’ uses a bottom-up approach to quantify fossil fuel CO2 (FFCO2) emissions spatially at the building/street level and temporally at the hourly level. Hestia FFCO2 emissions are provided in the form of a group of sector-specific vector layers with point, line, and polygon sources to support carbon cycle science and climate policy. Application to carbon cycle science, in particular, requires regular gridded data in order to link surface carbon fluxes to atmospheric transport models. However, the heterogeneity and complexity of FFCO2 sources within regular grids is sensitive to spatial resolution. From the perspective of a data provider, we need to find a balance between resolution and data volume so that the gridded data product retains the maximum amount of information content while maintaining an efficient data volume. The Shannon entropy determines the minimum bits that are needed to encode an information source and can serve as a metric for the effective information content. In this paper, we present an analysis of the Shannon entropy of gridded FFCO2 emissions with varying resolutions in four Hestia study areas, and find: (1) the Shannon entropy increases with smaller grid resolution until it reaches a maximum value (the max-entropy resolution); (2) total emissions (the sum of several sector-specific emission fields) show a finer max-entropy resolution than each of the sector-specific fields; (3) the residential emissions show a finer max-entropy resolution than the commercial emissions; (4) the max-entropy resolution of the onroad emissions grid is closely correlated to the density of the road network. These findings suggest that the Shannon entropy can detect the information effectiveness of the spatial resolution of gridded FFCO2 emissions. Hence, the resolution-entropy relationship can be used to assist in determining an appropriate spatial resolution for urban CO2 flux studies. We conclude that the optimal spatial resolution for providing Hestia total FFCO2 emissions products is centered around 100 m, at which the FFCO2 emissions data can not only fully meet the requirement of urban flux integration, but also be effectively used in understanding the relationships between FFCO2 emissions and various social-economic variables at the U.S. census block group level.

Soil respiration contributes substantially to urban carbon fluxes in the greater Boston area

Urban areas are the dominant source of U.S. fossil fuel carbon dioxide (FFCO2) emissions. In the absence of binding international treaties or decisive U.S. federal policy for greenhouse gas regulation, cities have also become leaders in greenhouse gas reduction efforts through climate action plans. These plans focus on anthropogenic carbon flows only, however, ignoring a potentially substantial contribution to atmospheric carbon dioxide (CO2) concentrations from biological respiration. Our aim was to measure the contribution of CO2 efflux from soil respiration to atmospheric CO2 fluxes using an automated CO2 efflux system and to use these measurements to model urban soil CO2 efflux across an urban area. We find that growing season soil respiration is dramatically enhanced in urban areas and represents levels of CO2 efflux of up to 72% of FFCO2 within greater Boston's residential areas, and that soils in urban forests, lawns, and landscaped cover types emit 2.62 ± 0.15, 4.49 ± 0.14, and 6.73 ± 0.26 μmolCO2 m−2 s−1, respectively, during the growing season. These rates represent up to 2.2 times greater soil respiration than rates found in nearby rural ecosystems in central Massachusetts (MA), a potential consequence of imported carbon amendments, such as mulch, within a general regime of landowner management. As the scientific community moves rapidly towards monitoring, reporting, and verification of CO2 emissions using ground based approaches and remotely-sensed observations to measure CO2 concentrations, our results show that measurement and modeling of biogenic urban CO2 fluxes will be a critical component for verification of urban climate action plans.

A new inversion method to calculate emission inventories without a prior at mesoscale: Application to the anthropogenic CO2 emission from Houston, Texas

We developed a new inversion method to calculate an emission inventory for an anthropogenic pollutant without a prior emission estimate at mesoscale. This method employs slopes between mixing ratio enhancements of a given pollutant (CO2, for instance) with other co‐emitted tracers in conjunction with the emission inventories of those tracers (CO, NOy, and SO2 are used in this example). The current application of this method employed in situ measurements onboard the NOAA WP‐3 research aircraft during the 2006 Texas Air Quality Study (TexAQS 2006). We used 3 different transport models to estimate the uncertainties introduced by the transport models in the inversion. We demonstrated the validity of the new inversion method by calculating a 4 × 4 km2 emission inventory of anthropogenic CO2 in the Houston area in Texas, and comparing it to the 10 × 10 km2 Vulcan emission inventory for the same region. The calculated anthropogenic CO2 inventory for the Houston Ship Channel, home to numerous major industrial and port emission sources, showed excellent agreement with Vulcan. The daytime CO2 average flux from the Ship Channel is the largest urban CO2 flux reported in the literature. Compared to Vulcan, the daytime urban area CO2 emissions were higher by 37% ± 6%. Those differences can be explained by uncertainties in emission factors in Vulcan and by increased emissions from point sources and on‐road emitters between 2002, the reference year in Vulcan, and 2006, the year that the TexAQS observations were made.