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The terrestrial biosphere plays a major role in the global carbon cycle, and there is a recognized need for regularly updated estimates of land‐atmosphere exchange at regional and global scales. An international ensemble of Dynamic Global Vegetation Models (DGVMs), known as the "Trends and drivers of the regional scale terrestrial sources and sinks of carbon dioxide" (TRENDY) project, quantifies land biophysical exchange processes and biogeochemistry cycles in support of the annual Global Carbon Budget assessments and the REgional Carbon Cycle Assessment and Processes, phase 2 project. DGVMs use a common protocol and set of driving data sets. A set of factorial simulations allows attribution of spatio‐temporal changes in land surface processes to three primary global change drivers: changes in atmospheric CO2, climate change and variability, and Land Use and Land Cover Changes (LULCC). Here, we describe the TRENDY project, benchmark DGVM performance using remote‐sensing and other observational data, and present results for the contemporary period. Simulation results show a large global carbon sink in natural vegetation over 2012–2021, attributed to the CO2 fertilization effect (3.8 ± 0.8 PgC/yr) and climate (−0.58 ± 0.54 PgC/yr). Forests and semi‐arid ecosystems contribute approximately equally to the mean and trend in the natural land sink, and semi‐arid ecosystems continue to dominate interannual variability. The natural sink is offset by net emissions from LULCC (−1.6 ± 0.5 PgC/yr), with a net land sink of 1.7 ± 0.6 PgC/yr. Despite the largest gross fluxes being in the tropics, the largest net land‐atmosphere exchange is simulated in the extratropical regions. Plain Language Summary: Around one third of human‐induced CO2 emissions are absorbed by land ecosystems and thus act to mitigate climate change. It is essential to understand the processes, ecosystems and regions responsible for this natural carbon sink, to inform on the efficiency of the sinks into the future. These sinks are susceptible to year‐to‐year variation in response to climate variations and extremes. At the same time deforestation and other forms of land management are changing the land surface, which overall adds significantly to the human‐induced CO2 emissions. There is a need to regularly update our estimate of land carbon dynamics to aid global stock takes for the Paris agreement to avoid dangerous climate change. Here we present an international initiative that on an annual basis assesses "Trends and drivers of the regional scale terrestrial sources and sinks of carbon dioxide" (TRENDY) using computer models of the land carbon cycle. We quantify the land sink during the contemporary period (2012–2021), and attribute to processes, mainly the large opposing effects of CO2 fertilization enhancing plant productivity and land‐use change. Forests and semi‐arid ecosystems are largely responsible for the mean and trend in the land sink, with the latter most important for its year‐to‐year variation. Key Points: We quantify and attribute land carbon dynamics to underlying processes at regional scales, contributing bottom‐up estimates to RECCAP‐2Models simulate a contemporary net land sink of 1.7 ± 0.6 PgC/yr, with large opposing effects of CO2 fertilization and land‐use changeDespite the largest gross fluxes being in the tropics, the largest net land‐atmosphere exchange is simulated in the extratropical regions [ABSTRACT FROM AUTHOR]

To effectively monitor the highly heterogeneous urban CO2 emissions using atmospheric observations, there is a need to deploy cost-effective CO2 sensors at multiple locations within the city with sufficient accuracy to capture the concentration gradients in urban environments. Its measurements could be used as input of an atmospheric inversion system for the quantification of emissions at the sub-city scale or separate specific sectors. Such quantification would offer valuable insights into the efficacy of local initiatives and could also identify unknown emission hotspots that require attention. Here we present the development and evaluation of a mid-cost CO2 instrument designed for continuous monitoring of atmospheric CO2 concentrations with a target accuracy of 1 ppm on hourly mean measurement. We assess the sensor sensitivity in relation to environmental factors such as humidity, pressure, temperature and CO2 signal, which leads to the development of an effective calibration algorithm. Since July 2020, eight mid-cost instruments have been installed within the city of Paris and its vicinity to provide continuous CO2 measurements, complementing the seven high-precision Cavity Ring-Down Spectroscopy (CRDS) stations that have been in operation since 2016. A data processing system, called CO2 calqual, has been implemented to automatically handle data quality control, calibration and storage, which enables the management of extensive real-time CO2 measurements from the monitoring network. Colocation assessments with the high-precision instrument show that the accuracies of the eight mid-cost instruments are within the range of 1.0 to 2.4 ppm for hourly afternoon (12–17 UTC) measurements. The long-term stability issues require manual data checks and instrument maintenance. The analyses show that CO2 measurements can provide evidence for underestimations of CO2 emissions in the Paris region and a lack of several emission point sources in the emission inventory. Our study demonstrates promising prospects in integrating mid-cost measurements along with high precision data into the subsequent atmospheric inverse modeling to improve the accuracy of quantifying the fine-scale CO2 emissions in the Paris metropolitan area. [ABSTRACT FROM AUTHOR]

To effectively monitor the highly heterogeneous urban CO2 emissions using atmospheric observations, there is a need to deploy cost-effective CO2 sensors at multiple locations within the city with sufficient accuracy to capture the concentration gradients in urban environments. Its measurements could be used as input of an atmospheric inversion system for the quantification of emissions at the sub-city scale or separate specific sectors. Such quantification would offer valuable insights into the efficacy of local initiatives and could also identify unknown emission hotspots that require attention. Here we present the development and evaluation of a mid-cost CO2 instrument designed for continuous monitoring of atmospheric CO2 concentrations with a target accuracy of 1 ppm on hourly mean measurement. We assess the sensor sensitivity in relation to environmental factors such as humidity, pressure, temperature and CO2 signal, which leads to the development of an effective calibration algorithm. Since July 2020, eight mid-cost instruments have been installed within the city of Paris and its vicinity to provide continuous CO2 measurements, complementing the seven high-precision Cavity Ring-Down Spectroscopy (CRDS) stations that have been in operation since 2016. A data processing system, called CO2calqual, has been implemented to automatically handle data quality control, calibration and storage, which enables the management of extensive real-time CO2 measurements from the monitoring network. Colocation assessments with the high-precision instrument show that the accuracies of the eight mid-cost instruments are within the range of 1.0 to 2.4 ppm for hourly afternoon (12–17 UTC) measurements. The long-term stability issues require manual data checks and instrument maintenance. The analyses show that CO2 measurements can provide evidence for underestimations of CO2 emissions in the Paris region and a lack of several emission point sources in the emission inventory. Our study demonstrates promising prospects in integrating mid-cost measurements along with high precision data into the subsequent atmospheric inverse modeling to improve the accuracy of quantifying the fine-scale CO2 emissions in the Paris metropolitan area. [ABSTRACT FROM AUTHOR]

Background: Urban agglomerates play a crucial role in reaching global climate objectives. Many cities have committed to reducing their greenhouse gas emissions, but current emission trends remain unverifiable. Atmospheric monitoring of greenhouse gases offers an independent and transparent strategy to measure urban emissions. However, careful design of the monitoring network is crucial to be able to monitor the most important sectors as well as adjust to rapidly changing urban landscapes. Results: Our study of Paris and Munich demonstrates how climate action plans, carbon emission inventories, and urban development plans can help design optimal atmospheric monitoring networks. We show that these two European cities display widely different trajectories in space and time, reflecting different emission reduction strategies and constraints due to administrative boundaries. The projected carbon emissions rely on future actions, hence uncertain, and we demonstrate how emission reductions vary significantly at the sub-city level. Conclusions: We conclude that quantified individual cities' climate actions are essential to construct more robust emissions trajectories at the city scale. Also, harmonization and compatibility of plans from various cities are necessary to make inter-comparisons of city climate targets possible. Furthermore, dense atmospheric networks extending beyond the city limits are needed to track emission trends over the coming decades. [ABSTRACT FROM AUTHOR]

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 6 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 MtCO2 in 2020 to 34.3 ± 2.3 MtCO2 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. [ABSTRACT FROM AUTHOR]

Existing CO2 emissions reported by city inventories usually lag 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 the 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, both fossil fuel and biogenic sources and sinks, over six 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 WRF-Chem transport model to simulate atmospheric boundary layer dynamics constrained by observed layer heights. Our results show a long-term decreasing trend by around 2 % per year in annual CO2 emissions over the Paris region. The impact of COVID-19 pandemic led to a 13 %±1 % reduction in annual fossil fuel CO2 emissions in 2020 with respect to 2019. Then, annual emissions increased by 5.2 % from 32.6±2.2 MtCO2 in 2020 to 34.3±2.3 MtCO2 in 2021. Based on a combination of up-to-date inventories, high-resolution atmospheric modeling, and high-precision observations, our current capacity could deliver near real-time CO2 emission estimates at city scale in less than a month, and the results agree within 10 % with independent estimates from multiple city-scale inventories. [ABSTRACT FROM AUTHOR]

The top-down atmospheric inversion method that couples atmospheric CO 2 observations with an atmospheric transport model has been used extensively to quantify CO 2 emissions from cities. However, the potential of the method is limited by several sources of misfits between the measured and modeled CO 2 that are of different origins than the targeted CO 2 emissions. This study investigates the critical sources of errors that can compromise the estimates of the city-scale emissions and identifies the signal of emissions that has to be filtered when doing inversions. A set of 1-year forward simulations is carried out using the WRF-Chem model at a horizontal resolution of 1 km focusing on the Paris area with different anthropogenic emission inventories, physical parameterizations, and CO 2 boundary conditions. The simulated CO 2 concentrations are compared with in situ observations from six continuous monitoring stations located within Paris and its vicinity. Results highlight large nighttime model–data misfits, especially in winter within the city, which are attributed to large uncertainties in the diurnal profile of anthropogenic emissions as well as to errors in the vertical mixing near the surface in the WRF-Chem model. The nighttime biogenic respiration to the CO 2 concentration is a significant source of modeling errors during the growing season outside the city. When winds are from continental Europe and the CO 2 concentration of incoming air masses is influenced by remote emissions and large-scale biogenic fluxes, differences in the simulated CO 2 induced by the two different boundary conditions (CAMS and CarbonTracker) can be of up to 5 ppm. Nevertheless, our results demonstrate the potential of our optimal CO 2 atmospheric modeling system to be utilized in atmospheric inversions of CO 2 emissions over the Paris metropolitan area. We evaluated the model performances in terms of wind, vertical mixing, and CO 2 model–data mismatches, and we developed a filtering algorithm for outliers due to local contamination and unfavorable meteorological conditions. Analysis of model–data misfit indicates that future inversions at the mesoscale should only use afternoon urban CO 2 measurements in winter and suburban measurements in summer. Finally, we determined that errors related to CO 2 boundary conditions can be overcome by including distant background observations to constrain the boundary inflow or by assimilating CO 2 gradients of upwind–downwind stations rather than by assimilating absolute CO 2 concentrations. [ABSTRACT FROM AUTHOR]

To respect the Paris agreement targeting a limitation of global warming below 2°C by 2100, and possibly below 1.5°C, drastic reductions of greenhouse gas emissions are mandatory but not sufficient. Large-scale deployment of other climate mitigation strategies is also necessary. Among these, increasing soil organic carbon (SOC) stocks is an important lever because carbon in soils can be stored for long periods and land management options to achieve this already exist and have been widely tested. However, agricultural soils are also an important source of nitrous oxide (N2O), a powerful greenhouse gas, and increasing SOC may influence N2O emissions, likely causing an increase in many cases, thus tending to offset the climate change benefit from increased SOC storage. Here we review the main agricultural management options for increasing SOC stocks. We evaluate the amount of SOC that can be stored as well as resulting changes in N2O emissions to better estimate the climate benefits of these management options. Based on quantitative data obtained from published meta-analyses and from our current level of understanding, we conclude that the climate mitigation induced by increased SOC storage is generally overestimated if associated N2O emissions are not considered but, with the exception of reduced tillage, is never fully offset. Some options (e.g. biochar or non-pyrogenic C amendment application) may even decrease N2O emissions. [ABSTRACT FROM AUTHOR]

In 2015, the Greenhouse gas Laser Imaging Tomography Experiment (GreenLITE™) measurement system was deployed for a long-duration experiment in the center of Paris, France. The system measures near-surface atmospheric CO2 concentrations integrated along 30 horizontal chords ranging in length from 2.3 to 5.2 km and covering an area of 25 km 2 over the complex urban environment. In this study, we use this observing system together with six conventional in situ point measurements and the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) and two urban canopy schemes (Urban Canopy Model – UCM; Building Effect Parameterization – BEP) at a horizontal resolution of 1 km to analyze the temporal and spatial variations in CO2 concentrations within the city of Paris and its vicinity for the 1-year period spanning December 2015 to November 2016. Such an analysis aims at supporting the development of CO2 atmospheric inversion systems at the city scale. Results show that both urban canopy schemes in the WRF-Chem model are capable of reproducing the seasonal cycle and most of the synoptic variations in the atmospheric CO2 point measurements over the suburban areas as well as the general corresponding spatial differences in CO2 concentration that span the urban area. However, within the city, there are larger discrepancies between the observations and the model results with very distinct features during winter and summer. During winter, the GreenLITE™ measurements clearly demonstrate that one urban canopy scheme (BEP) provides a much better description of temporal variations and horizontal differences in CO2 concentrations than the other (UCM) does. During summer, much larger CO2 horizontal differences are indicated by the GreenLITE™ system than both the in situ measurements and the model results, with systematic east–west variations. [ABSTRACT FROM AUTHOR]

CO2 emission estimates from urban areas can be obtained with a network of in situ instruments measuring atmospheric CO2 combined with high-resolution (inverse) transport modelling. Because the distribution of CO2 emissions is highly heterogeneous in space and variable in time in urban areas, gradients of atmospheric CO2 (here, dry air mole fractions) need to be measured by numerous instruments placed at multiple locations around and possibly within these urban areas. This calls for the development of lower-cost medium-precision sensors to allow a deployment at required densities. Medium precision is here set to be a random error (uncertainty) on hourly measurements of ±1 ppm or less, a precision requirement based on previous studies of network design in urban areas. Here we present tests of newly developed non-dispersive infrared (NDIR) sensors manufactured by Senseair AB performed in the laboratory and at actual field stations, the latter for CO2 dry air mole fractions in the Paris area. The lower-cost medium-precision sensors are shown to be sensitive to atmospheric pressure and temperature conditions. The sensors respond linearly to CO2 when measuring calibration tanks, but the regression slope between measured and assigned CO2 differs between individual sensors and changes with time. In addition to pressure and temperature variations, humidity impacts the measurement of CO2 , with all of these factors resulting in systematic errors. In the field, an empirical calibration strategy is proposed based on parallel measurements with the lower-cost medium-precision sensors and a high-precision instrument cavity ring-down instrument for 6 months. The empirical calibration method consists of using a multivariable regression approach, based on predictors of air temperature, pressure and humidity. This error model shows good performances to explain the observed drifts of the lower-cost medium-precision sensors on timescales of up to 1–2 months when trained against 1–2 weeks of high-precision instrument time series. Residual errors are contained within the ±1 ppm target, showing the feasibility of using networks of HPP3 instruments for urban CO2 networks. Provided that they could be regularly calibrated against one anchor reference high-precision instrument these sensors could thus collect the CO2 (dry air) mole fraction data required as for top-down CO2 flux estimates. [ABSTRACT FROM AUTHOR]

Providing timely information on urban greenhouse gas (GHG) emissions and their trends to stakeholders relies on reliable measurements of atmospheric concentrations and the understanding of how local emissions and atmospheric transport influence these observations. Portable Fourier transform infrared (FTIR) spectrometers were deployed at five stations in the Paris metropolitan area to provide column-averaged concentrations of CO2 (XCO2) during a field campaign in spring of 2015, as part of the Collaborative Carbon Column Observing Network (COCCON). Here, we describe and analyze the variations of XCO2 observed at different sites and how they changed over time. We find that observations upwind and downwind of the city centre differ significantly in their XCO2 concentrations, while the overall variability of the daily cycle is similar, i.e. increasing during night-time with a strong decrease (typically 2–3 ppm) during the afternoon. An atmospheric transport model framework (CHIMERE-CAMS) was used to simulate XCO2 and predict the same behaviour seen in the observations, which supports key findings, e.g. that even in a densely populated region like Paris (over 12 million people), biospheric uptake of CO2 can be of major influence on daily XCO2 variations. Despite a general offset between modelled and observed XCO2 , the model correctly predicts the impact of the meteorological parameters (e.g. wind direction and speed) on the concentration gradients between different stations. When analyzing local gradients of XCO2 for upwind and downwind station pairs, those local gradients are found to be less sensitive to changes in XCO2 boundary conditions and biogenic fluxes within the domain and we find the model–data agreement further improves. Our modelling framework indicates that the local XCO2 gradient between the stations is dominated by the fossil fuel CO2 signal of the Paris metropolitan area. This further highlights the potential usefulness of XCO2 observations to help optimize future urban GHG emission estimates. [ABSTRACT FROM AUTHOR]

Most of the global fossil fuel CO2 emissions arise from urbanized and industrialized areas. Bottom-up inventories quantify them but with large uncertainties. In 2010-2011, the first atmospheric in situ CO2 measurement network for Paris, the capital of France, began operating with the aim of monitoring the regional atmospheric impact of the emissions coming from this megacity. Five stations sampled air along a northeast--southwest axis that corresponds to the direction of the dominant winds. Two stations are classified as rural (Traînou -- TRN; Montgé-en-Goële -- MON), two are peri-urban (Gonesse -- GON; Gif-sur-Yvette -- GIF) and one is urban (EIF, located on top of the Eiffel Tower). In this study, we analyze the diurnal, synoptic and seasonal variability of the in situ CO2 measurements over nearly 1 year (8 August 2010-13 July 2011).We compare these datasets with remote CO2 measurements made at Mace Head (MHD) on the Atlantic coast of Ireland and support our analysis with atmospheric boundary layer height (ABLH) observations made in the center of Paris and with both modeled and observed meteorological fields. The average hourly CO2 diurnal cycles observed at the regional stations are mostly driven by the CO2 biospheric cycle, the ABLH cycle and the proximity to urban CO2 emissions. Differences of several µmol mol-1(ppm) can be observed from one regional site to the other. The more the site is surrounded by urban sources (mostly residential and commercial heating, and traffic), the more the CO2 concentration is elevated, as is the associated variability which reflects the variability of the urban sources. Furthermore, two sites with inlets high above ground level (EIF and TRN) show a phase shift of the CO2 diurnal cycle of a few hours compared to lower sites due to a strong coupling with the boundary layer diurnal cycle. As a consequence, the existence of a CO2 vertical gradient above Paris can be inferred, whose amplitude depends on the time of the day and on the season, ranging from a few tenths of ppm during daytime to several ppm during nighttime. The CO2 seasonal cycle inferred from monthly means at our regional sites is driven by the biospheric and anthropogenic CO2 flux seasonal cycles, the ABLH seasonal cycle and also synoptic variations. Enhancements of several ppm are observed at peri-urban stations compared to rural ones, mostly from the influence of urban emissions that are in the footprint of the peri-urban station. The seasonal cycle observed at the urban station (EIF) is specific and very sensitive to the ABLH cycle. At both the diurnal and the seasonal scales, noticeable differences of several ppm are observed between the measurements made at regional rural stations and the remote measurements made at MHD, that are shown not to define background concentrations appropriately for quantifying the regional (~100 km) atmospheric impact of urban CO2 emissions. For wind speeds less than 3 m s-1, the accumulation of local CO2 emissions in the urban atmosphere forms a dome of several tens of ppm at the peri-urban stations, mostly under the influence of relatively local emissions including those from the Charles de Gaulle (CDG) Airport facility and from aircraft in flight. When wind speed increases, ventilation transforms the CO2 dome into a plume. Higher CO2 background concentrations of several ppm are advected from the remote Benelux--Ruhr and London regions, impacting concentrations at the five stations of the network even at wind speeds higher than 9 m s-1. For wind speeds ranging between 3 and 8 m s-1, the impact of Paris emissions can be detected in the peri-urban stations when they are downwind of the city, while the rural stations often seem disconnected from the city emission plume. As a conclusion, our study highlights a high sensitivity of the stations to wind speed and direction, to their distance from the city, but also to the ABLH cycle depending on their elevation. We learn some lessons regarding the design of an urban CO2 network: (1) careful attention should be paid to properly setting regional (~100 km) background sites that will be representative of the different wind sectors; (2) the downwind stations should be positioned as symmetrically as possible in relation to the city center, at the peri-urban/rural border; (3) the stations should be installed at ventilated sites (away from strong local sources) and the air inlet set up above the building or biospheric canopy layer, whichever is the highest; and (4) high-resolution wind information should be available with the CO2 measurements. [ABSTRACT FROM AUTHOR]

The ability of a Bayesian atmospheric inversion to quantify the Paris region's fossil fuel CO2 emissions on a monthly basis, based on a network of three surface stations operated for 1 year as part of the CO2-MEGAPARIS experiment (August 2010-July 2011), is analysed. Differences in hourly CO2 atmospheric mole fractions between the near-ground monitoring sites (CO2 gradients), located at the north-eastern and south-western edges of the urban area, are used to estimate the 6 h mean fossil fuel CO2 emission. The inversion relies on the CHIMERE transport model run at 2 km × 2 km horizontal resolution, on the spatial distribution of fossil fuel CO2 emissions in 2008 from a local inventory established at 1 km × 1 km horizontal resolution by the AIRPARIF air quality agency, and on the spatial distribution of the biogenic CO2 fluxes from the C-TESSEL land surface model. It corrects a prior estimate of the 6 h mean budgets of the fossil fuel CO2 emissions given by the AIRPARIF 2008 inventory. We found that a stringent selection of CO2 gradients is necessary for reliable inversion results, due to large modelling uncertainties. In particular, the most robust data selection analysed in this study uses only mid-afternoon gradients if wind speeds are larger than 3 m s-1 and if the modelled wind at the upwind site is within ±15° of the transect between downwind and upwind sites. This stringent data selection removes 92 % of the hourly observations. Even though this leaves few remaining data to constrain the emissions, the inversion system diagnoses that their assimilation significantly reduces the uncertainty in monthly emissions: by 9 % in November 2010 to 50 % in October 2010. The inverted monthly mean emissions correlate well with independent monthly mean air temperature. Furthermore, the inverted annual mean emission is consistent with the independent revision of the AIRPARIF inventory for the year 2010, which better corresponds to the measurement period than the 2008 inventory. Several tests of the inversion's sensitivity to prior emission estimates, to the assumed spatial distribution of the emissions, and to the atmospheric transport modelling demonstrate the robustness of the measurement constraint on inverted fossil fuel CO2 emissions. The results, however, show significant sensitivity to the description of the emissions' spatial distribution in the inversion system, demonstrating the need to rely on high-resolution local inventories such as that from AIRPARIF. Although the inversion constrains emissions through the assimilation of CO2 gradients, the results are hampered by the improperly modelled influence of remote CO2 fluxes when air masses originate from urbanised and industrialised areas north-east of Paris. The drastic data selection used in this study limits the ability to continuously monitor Paris fossil fuel CO2 emissions: the inversion results for specific months such as September or November 2010 are poorly constrained by too few CO2 measurements. The high sensitivity of the inverted emissions to the prior emissions' diurnal variations highlights the limitations induced by assimilating data only during the afternoon. Furthermore, even though the inversion improves the seasonal variation and the annual budget of the city's emissions, the assimilation of data during a limited number of suitable days does not necessarily yield robust estimates for individual months. These limitations could be overcome through a refinement of the data processing for a wider data selection, and through the expansion of the observation network. [ABSTRACT FROM AUTHOR]

The Paris climate agreement aims at holding global warming to well below 2 ∘, while howglobal soil carbon in response to such presupposed social economic scenarios is still lessknown. In this study, we analyzed global soil carbon changes in historical period and in nextcentury using seven land surface models in the Inter-Sectoral Impact Model Inter-comparisonProject (ISIMIP) under two concentration pathways (low RCP2.6 and high RCP6.0). In ourresults, ISIMIP2b ensemble suggested a global soil carbon sink of 0.31±0.74 Pg Cyr−1 from 1861 to 2005, and projected stronger carbon sink capacity in the nextcentury from 2005 to 2099 (0.83±0.97 Pg C yr−1 for RCP2.6 and 1.01±1.35 Pg Cyr−1 for RCP6.0). For the future global soil carbon changes, climate change ratherthan land use change is the most important influential factor. At biome scale, wealso find different changes of carbon sink capacity under the future RCPs amongdifferent biome, which mainly influenced by regional climate change and land usechange. Although these results implied that global soil carbon pool will continuallybe a sink under predesigned social economic scenarios, current state-of-the-artcoupled climate/carbon-cycle models for projecting soil carbon balance still has largeuncertainties. We attempted to attribute the structural uncertainties of land surfacemodels in regional and global SOC changes to the change in soil inputs (NPP), initialdifferences in SOC, and changes in decomposition rate following Todd Brown’s method. [ABSTRACT FROM AUTHOR]

Urban decarbonization is one of the pillars for strategies to achieve carbon neutrality around the world. However, the current speed of urban decarbonization is insufficient to keep pace with efforts to achieve this goal. Rooftop photovoltaics (PVs) integrated with electric vehicles (EVs) as battery is a promising technology scalable to supply CO 2 -free, affordable, and dispatchable electricity in urban environments ("SolarEV City Concept"). Here, we evaluated Paris, France for the decarbonization potentials of rooftop "PV + EV" in comparison to the surrounding suburban area Ile-de-France and the reference city Kyoto, Japan. We assessed various scenarios by calculating energy sufficiency, self-consumption, self-sufficiency, cost savings, and CO 2 emission reduction of the PV + EV system or PV only system. We found that above a certain roof coverage 50–60% of the total roof area for Paris or 20–30% for Ile-de-France, PV electricity production regularly exceeds the demand. Above that roof coverage, feed-in-tariffs (FIT) or storage are needed to further realize the potential of the rooftop PV system. The combination of PVs with EVs is more effective in Ile-de-France than in Paris because large surplus electricity from rooftop PV in suburban area requires large storage. With already low-carbon electricity of France by nuclear power, the maximum potential CO 2 abatement through the implementation of SolarEV City Concept in Paris (0.020 kg CO2 /kWh reduction from 0.063 kg CO2 /kWh) is limited in comparison to that in Kyoto (0.270 kg CO2 /kWh reduction from 0.352 kg CO2 /kWh). However, with declining costs of PVs and EVs in the coming decades, low-cost dispatchable electricity by the PV + EV system throughout Paris and Ile-de-France may facilitate the electrification of CO 2 emitting appliances, potentially allowing rapid CO 2 emission reductions from Paris. • From roof coverage of 50–60% PV production regularly exceeds demand in Paris. • PV + EV system is more effective in Ile-de-France than Paris for larger roof area. • PV + EV system is less effective in Paris than in Kyoto for reducing CO2 emissions. [ABSTRACT FROM AUTHOR]

Greenhouse gases (GHGs) are the main driver of the anthropogenic excess radiative forcingand thereby largely contribute to the current increase of global mean temperature. Out of theGHGs, carbon dioxide (CO2) and methane (CH4) are the most important species with respectto radiative forcing. The importance of reducing GHGs has been acknowledged byinternational parties, leading to the Kyoto protocol and subsequent PARIS COP21agreement. For the successful implementation of the mitigation goals cities are of special importance.Currently, over 50 % of the human population lives in urban areas and the populationgrowth is predicted to occur predominantly in urban centers. At present, cities areestimated to be responsible for 53 % - 87 % of fossil fuel CO2 emissions and arepredicted to further increase. While emissions of CO2 can be estimated rather preciselyon the national scale, higher uncertainties are reported for urban GHG emissions,especially CH4. The large uncertainty of the global contribution of urban areas to GHGemissions is why a new generation of city-scale observing and modelling systems isneeded. Here, newly developed, mobile, solar absorption Fourier Transform spectrometers(EM27/SUN) measuring column-averaged dry air mole fractions of trace gases (Xgas) areutilized to quantify city scale emissions of CO2 and CH4. This novel technique wassuccessfully tested by KIT and partners during several campaigns for detecting emissionsfrom various sources. We present results from two campaigns carried out in April – May2015 in Paris and in September – October 2018 in Madrid. Five EM27/SUN spectrometerswere operated on the outer perimeter of the cities along the prevailing wind axis upwind anddownwind of the city source. For Paris, we focus on CO2 and present a comprehensive study comparing measuredXCO2 and CHIMERE-CAMS atmospheric transport modelling results. We find that themodel correctly predicts the impact of meteorological parameters on the concentrationgradients between the different stations. The modelling framework indicates that the localXCO2 gradients detected between the sites are dominated by fossil fuel CO2 emissions. Forthe eastern part of Paris, the modelled gradients are significantly smaller than the observedgradients, likely due to suboptimal emission estimates in the modelling framework. Thishighlights the usefulness of XCO2 observations for the optimization of urban GHG emissioninventories. For Madrid, we analyze XCO2, XCH4 and XCO and present preliminary campaignresults. Similarly to Paris, fossil fuel emissions are mainly responsible for CO2emissions, while CH4 enhancements are strongly linked to waste treatment. Dueto the proximity of a waste disposal site to the Madrid Metropolitan area, verylarge XCH4 enhancements up to 140 ppbv were observed during the campaign. [ABSTRACT FROM AUTHOR]

While networks of atmospheric greenhouse gas measurements are being deployed across various urban centers to support the assessment of greenhouse gas emissions, the socio-economic drivers, and hence the potential pathways toward emission reductions, vary widely between fast- and slow-growing cities. Vast conurbations in fast-developing economies tend to increase emissions despite current efforts to utilize energy-efficient technologies. By contrast, slow-growing cities tend to level-out or even reduce their carbon footprints, but the rapid extension of suburban areas poses a challenge to monitoring solutions and governing bodies as sources and sinks are displaced outside the city limits. We review here four different cases in widely different contexts, from single cities (Paris, Indianapolis, Mexico city) to conurbations in slow- (Los Angeles) and fast-growing (Jakarta) demographics. Urban system designs for atmospheric inversions are presented and discussed in the context of emission mitigation strategies and their manifestations at different spatial and temporal scales. In addition to ground-based networks, remote sensing solutions are evaluated (e.g. OCO-3) for similar applications shedding light on current technical limitations but also opportunities to support coherent and efficient mitigation strategies. [ABSTRACT FROM AUTHOR]