Carbon Monitor Europe near-real-time daily CO2 emissions for 27 EU countries and the United Kingdom

With the urgent need to implement the EU countries pledges and to monitor the effectiveness of Green Deal plan, Monitoring Reporting and Verification tools are needed to track how emissions are changing for all the sectors. Current official inventories only provide annual estimates of national CO2 emissions with a lag of 1+ year which do not capture the variations of emissions due to recent shocks including COVID lockdowns and economic rebounds, war in Ukraine. Here we present a near-real-time country-level dataset of daily fossil fuel and cement emissions from January 2019 through December 2021 for 27 EU countries and UK, which called Carbon Monitor Europe. The data are calculated separately for six sectors: power, industry, ground transportation, domestic aviation, international aviation and residential. Daily CO2 emissions are estimated from a large set of activity data compiled from different sources. The goal of this dataset is to improve the timeliness and temporal resolution of emissions for European countries, to inform the public and decision makers about current emissions changes in Europe.


Background & Summary
The European Union and the United Kingdom is the world's third energy consumer and CO2 emitter, accounting for 12% of global emissions [1][2][3] .The EU27 announced the Green Deal in December 2019, and set up a road map for cutting greenhouse gas emissions by at least 55% by 2030 and reaching carbon neutrality by 2050 4 .With increasing focus and effort on reducing CO2 emissions, there is a growing need for more reliable data as well as for data with a lower latency.Most CO2 emission inventories including national inventories reported to the United Nations Framework Convention on Climate Change (UNFCCC) lag reality by one years or more 2,[5][6][7][8][9][10] .
Lower latency estimates of CO2 emissions are generally delayed by several months as data must be gathered from numerous sources and then verified.For example, Eurostat has been producing early estimates of annual and country-level CO2 emissions in the EU since at least 2012, with a delay for about 5 months 11 .The Global Carbon Project publishes projections of the current year's global fossil CO2 emissions since 2012 by the end of the current year 12 .As the COVID-19 pandemic profoundly disrupted human activities in the year 2020, existing inventories were not able to monitor changes in activity and assess the COVID-19 impacts on CO2 emissions during that period and the following recovery.Le Quéré et al. 13 and Forster et al. 14 developed methods for estimating daily, global CO2 emissions, based on confinement index and Google mobility indexes respectively 13,14 .These two approaches captured first order pandemic related reductions but were not tested for subsequent variations when lockdowns were finished, and did not continue to provide near-real-time, daily and country-level estimates emissions.Following the pandemics, few EU countries and the UK started to publish quarterly or monthly estimates of emissions from preliminary energy data [15][16][17][18][19] .Further, the private company Kayrros released a daily estimate of emissions from regulated sectors (European Trading Scheme) in November 2021 using site-level satellite monitoring of industrial activity, called Carbon Watch 20 .The Carbon Monitor international research initiative developed a new near-real-time daily dataset of CO2 emissions with global coverage and countrylevel estimates for 12 countries which lags reality by only one month 1,3,[21][22][23][24][25] .
Here, we present a near-real-time, sector-specific, country-level estimates of daily fossil fuel and cement CO2 emissions for 27 European Union countries and the United Kingdom based on an extension of Carbon Monitor called Carbon Monitor Europe (CM-EU).We present the methodology and the results for changes in emissions between January 1, 2019 and December 31, 2021.Details of our data sources and approach are in the Methods section.An evaluation of CM-EU against national quarterly emissions estimates and Carbon Watch is provided in the technical validation section.The data Carbon Monitor Europe are publicly available at https://eu.carbonmonitor.org/.

Methods
Carbon Monitor Europe (CM-EU) is a new regional improved version of the global Carbon Monitor system, providing near-real-time daily estimates of CO2 emissions for six sectors over the globe with separate estimates for 12 countries or groups of countries 21 .CM-EU presents country-level estimates of daily CO2 emissions from January 2019 through December 2021 for 27 countries of European Union (EU27) and the United Kingdom (UK).We used annual CO2 emissions of EU27 & UK from the Emissions Database for Global Atmospheric Research (EDGAR) 8 as the baseline data for emissions in the year 2019, then disaggregated tis estimate into daily scale and make a projection to 2020 and 2021 based on time variations of activity data.Below we describe the calculation process in detail.

Annual country-level and sectoral CO2 emissions in the baseline year 2019
Annual fossil fuel combustion and cement production CO2 emissions by sector in 2019 for all European Union countries and United Kingdom are directly obtained from the Fossil CO2 emissions of all world countries -2020 Report 8 released by the Emissions Database for Global Atmospheric Research (EDGAR).Emissions of EDGAR are derived using the IPCC Tier 1 approach according to the 2006 IPCC Guidelines 26 , with 35 sectors based on IPCC categories.We aggregated 11 energyrelated and cement production sectors of EDGAR into six main sectors, including power, industry, ground transportation, residential (public, commercial buildings and households), domestic and international aviation.By convention, emissions from international flights are assigned to the country of departure.Table 1 shows the correspondence table between aggregated sectors of CM-EU and EDGAR sectors based on IPCC (first column).

Data acquisition and processing of daily CO2 emissions in 2019, 2020 and 2021
Carbon Monitor follows the IPCC guidelines for emissions reporting 26 in computing CO2 emissions from a country / region by multiplying activity data (AD) by corresponding emissions factors (EF): where i, j, k denote regions, sectors, and fuel types respectively.We assume that emission factors and structure of each sector remain unchanged for each country in 2020 and 2021 compared with 2019.Thus, the rate of change of the emission is calculated based solely on the change of the activity data in 2020 and 2021 compared to the same period of 2019.The emissions were calculated following this equation separately for the power sector, the industrial sector, the ground transportation sector, the aviation sector (including the domestic and international aviation sector) and the residential sector.

Power sector
For the power sector, daily emissions were calculated from hourly electricity generation data by production types at resolution of 1 h to 15 min.Data of 22 EU countries (Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Netherlands, Poland, Portugal, Slovakia, Slovenia and Spain) and United Kingdom are available from the ENTSO-E Transparency platform (https://transparency.entsoe.eu/dashboard/show)and Balancing Mechanism Reporting Service (BMRS) (https://www.bmreports.com/)respectively (Table 2).We removed outliers and filled the N/A values by using the "interpolate()" function in Python Pandas packages, then aggregated the thermal production data into daily level.The electricity generation data used in this study from ENTSO-E and BMRS are include several fuel types with coal, gas, oil and peat.The average yearly emission factor of the whole power sector is assumed to remain constant at its 2019 value, so that daily emissions are estimated by:  %&'(),*+!,-,./01=  %&'(),-(+),-,./01

Industry sector
Daily emissions from industry are estimated using the monthly industrial production index (IPI) from several datasets and daily power generation data (Table 2).As daily production data are not available for industrial and cement production, the monthly CO2 emissions are estimated by using monthly statistics of industrial production and daily data of electricity generation to disaggregate the monthly CO2 emissions into a daily scale.This approach is based on two assumptions: 1.A linear relationship is assumed between industrial production index and emissions from industrial and cement production.2. A linear relationship is assumed between daily industry activity and daily electricity production, from ENSTO-E and our approach for the five Other-EU countries.Therefore, the monthly and daily industry emissions are estimated following:

Ground transportation sector
Carbon Monitor uses TomTom congestion global level data (Table 2) from the TomTom website (https://www.tomtom.com/en_gb/traffic-index/) to capture the daily variations in the ground transportation activity.The TomTom traffic congestion level (called G hereafter) represents the extra time spent on a trip in congested conditions, as a percentage, compared to uncongested conditions.TomTom congestion level data cover 203 cities across 24 EU countries (Austria, Belgium, Bulgaria, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Ireland, Italy, Latvia, Lithuania, Luxembourg, Netherlands, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden) and the United Kingdom at a temporal resolution of one hour (Table 3).Note that a zero-congestion level means the traffic is fluid or 'normal' but does not mean there are no vehicles and zero emissions.The lower threshold of emissions when the congestion level is zero was estimated using real-time data from an average of 70 main roads in the city of Paris.The daily mean car counts (called Q hereafter) were calculated by a sigmoid function based on regression: where Qd is the mean vehicle number per hour in day d, Emisground transport,d is the ground transport emission in day d, Emisground transport,yearly is the annual road transportation emissions from EDGAR, n is the number of days in a year.For countries not covered by TomTom (Croatia, Cyprus, Malta), we assume that their emission changes follow the patterns of total daily emissions from the average other 24 EU countries and the United Kingdom.

Aviation sector
Emissions of the aviation sector separated into domestic and international aviation, are estimated by individual commercial flights data (Table 2) from the Flightradar24 database (https://www.flightradar24.com).We compute CO2 emissions by assuming a constant emissions factor of aviation in CO2 emissions per km flown, called EFaviation across the whole fleet of aircraft (regional, narrowbody passenger, widebody passenger and freight operations) as the share of flight types has not significantly changed since 2019.The aviation sector separates domestic flights and international flights departing from countries considered in this study.The flights within EU but different countries are considered as international.The daily emissions of the aviation sector are estimated as: where DKF is the distance flown that is computed using great circle distance between the take-off, cruising, descent and landing points for each flight and are cumulated over all flights.For countries with overseas territories (mainly France, UK, Denmark) aviation emissions of flights to / from overseas territories are counted in this study as international emissions, whereas they would be reported as domestic emissions by national estimates.

Residential sector
Carbon Monitor uses the fluctuation of air temperature (Table 2) to capture the daily variations in the energy consumption of residential and commercial buildings.In this approach, only temperature is assumed to cause variation of emissions.Ciais et al. 27 looked at changes of natural gas use in the residential sector for few European countries from ENSTO-G pipeline data during the first half of the year 2020 and found that temperature variations dominated the observed changes, excepted for France and Italy where a reduced consumption signal independent of temperature was found during the weeks of strict confinements.The calculation of residential emissions was performed in three steps: (1) Calculation of population-weighted heating degree days for each country of EU27 & UK and for each day based on the ERA5 reanalysis of 2-m air temperature 28,29 , (2) Using annual residential emissions in 2019 from EDGAR as the baseline.For each country, the residential emissions were split into two parts, i.e., cooking emissions and heating emissions, according to the EDGAR guidelines.The emissions from cooking were assumed to remain stable, while the emissions from heating were assumed to depend on and vary by the heating demand.(3) Based on the change of population-weighted heating degree days in each country, we scaled the EDGAR 2019 residential emissions to 2020 and 2021.Since the index of heating degree days are daily values, we get daily emission updates for the residential sources.The EDGAR residential emissions are downscaled to daily values based on daily variations in population-weighted heating degree days as follows: Where m is the month,  *+!,-the population-weighted heating degree day, Ratioheating,monthly the percentage of residential emissions from heating demand monthly, Nm the number of days in month m, Popgrid the gridded population data derived from Gridded Population of the World, Version 4 28 ,  ?)!*,*+!,-is the daily average air temperature at 2 meters derived from ERA5 29 , and 18 is a HDD reference temperature of 18 °C following ref. 30.

Data Records
The CM-EU dataset is an CSV file containing country-level emission of 27 European Union countries and the United Kingdom from 01/01/2019 to 31/12/2021 for six sectors: power, industry, ground transportation, domestic and international aviation.At the time of writing this article, this dataset has been updated to December 31, 2021, and the full dataset can be downloaded at Figshare 31 .Latest updates and related information are available for view and download on our website https://eu.carbonmonitor.org/.Among countries, the emission declines in 2020 and rebounds in 2021 varied considerably as shown in Fig. 1.The emissions in Germany decreased most in 2020 (-65.5 Mt CO2) and rebounded most in 2021 (+53.5 Mt CO2) (Figure 3).The country with the largest relative decrease in 2020 and increase in 2021 is Estonia, with -30% and +34% respectively (Figure 4).Lithuania is the only country where emissions did not fall in 2020 (+2.4%) and continued to grow in 2021 (+8.5%) (Figure 4).
Regrading sectors, the emission declines in 2020 and rebounds in 2021 of EU27 & UK show a change in the sectoral structure of the emissions (Figure 2 and Figure 3).Most sectors had significant reductions in emissions by 2020, especially the international aviation sector (-111 Mt CO2).Emissions from each sector gradually recovered to pre-pandemic levels, as lockdown restrictions eased.However, the emissions of the domestic and international aviation in 2021 did not recover to the level of 2019 and remained lower by 31.7% (-3.81 Mt CO2) and 48.3% (-91.16 Mt CO2) compared with their 2019 level, respectively.

Comparison with national emissions estimates, yearly and sub-yearly in selected countries, and Kayrros Carbon Watch data
To evaluate the CO2 emissions data from CM-EU, we compared our results with three different existing emissions estimates of various timescale.The first evaluation data are annual country-level CO2 emissions of EU27 & UK in 2019 and 2020 from EDGAR 8 , BP 7 , IEA 32 , GCP 2 and Eurostat 33 .The second evaluation data are preliminary emissions publicly disclosed on a monthly or quarterly scale with a latency of few months to one year by national statistics offices / inventory agencies of Netherlands, Sweden, UK, France and Germany, which are from Centraal Bureau van Statistiek 18 , Statistics Sweden 19 , gov.uk 17 , Citepa 16 and Umwelt Bundesamt 15 respectively.The third evaluation data are daily country-level CO2 emissions of EU countries and UK from 2019 to 2021 from the Carbon Watch data of Kayrros 20 focusing on regulated sectors (ETS).As the Carbon Watch data methodology is not fully published, we provide a description as follows.There are four sectors in the data of Carbon Watch, including domestic flight, power, industry and transport.Domestic Flights.Kayrros Carbon Watch computes the emissions from all the flights inside the European Economic Area, excluding the outermost regions.For each flight, the emissions are computed depending on the aircraft type and an estimation of the passenger load factor, as well as the distance flown 34 .The emissions are then aggregated by operators (the company responsible for the flight).Each company is then associated with a country based on its head office's location.If the head office of the operator is not located, it is attributed to the country where it operates the most, as per the ETS accounting methodology.Thus, these emissions are not 'territorial' like those of CM-EU based on the country from which planes take-off.Carbon Watch also includes emissions from flights to overseas territories as 'domestic' whereas they are considered as 'international' by Carbon Monitor.
Power.Kayrros Carbon Watch computes the emissions of the power sector using country-wise figures for electricity production by fuel type from the same data sources as CM-EU.Then an emission factor based on the fuel type and average plant's efficiency is used, based on the ETS register of CO2 emissions by each plant whereas CM-EU uses and aggregated emission factor for all the plants using the same fuel type.
Industry.Kayrros Carbon Watch computes the emissions of this sector by detecting activity signals from satellites and multiplying the activity by an emission factor.The activity signal of each site during cloud-free periods is detected using Sentinel 2 satellite images, interpolated in time for missing data, and aggregated for all sites of the same sub sector (e.g.all the cement plants).Subsectors currently not measured via satellites are modeled.In total, Kayrros Carbon Watch coverage currently includes the full scope of regulated industrial installations.
Ground transport.Kayrros Carbon Watch computes Ground Transport emissions through geolocation data from cellular phones, with a coverage of few percent of the population in EU countries.It computes the total distance traveled by all high-quality users (people with more than 20 daily pings).Then this proxy is converted to emissions based on IEA total ground transportation.CO2 emissions data 35 using an average emission factor by country based on the local split of gasoline and diesel.The results of all validation datasets are shown in Table 4.
Figure 5 shows the comparison of annual CO2 emissions in 2019 and 2020 and changes between the two years for EU27 & UK, Germany, UK, Italy, Poland, France, Spain, Netherlands and the rest of EU between CM-EU, EDGAR, BP, IEA, GCP and Eurostat.In terms of annual total amount, the results of the six databases are relatively similar, and the main difference comes from the scope difference of each dataset.As for changes between 2019 and 2020, our estimates are lying in the middle range, close to most other datasets.Figure 6 shows the comparison of annual or quarterly CO2 emissions in 2019 and changes between 2020 and 2019 or 2021 and 2020 for Netherlands, UK, Sweden and Germany between this study and estimates from Citepa (France), Centraal Bureau van Statistiek (Netherlands), gov.uk (UK), Statistics Sweden (Sweden) and Umwelt Bundesamt (Germany).It illustrates that our estimates are close to the official estimates in terms of annual or quarterly totals for 2019 and for changes between 2019 and 2020 (at the beginning of COVID-19 pandemic), with relative differences from 0.07% to 3.17% at annual scale and 0.2% to 5.63% at quarterly scale.Our estimates differ more (in terms of relative differences) from these official estimates for quarterly and annual changes between 2020 and 2021, a period characterized by smaller changes, with relative differences from 0.81% to 3.34% at annual scale and 0.19% to 9.94% at quarterly scale.
We also compared the monthly CO2 emissions of EU27 & UK and France for four / five sectors (power, industry, ground transport, domestic aviation and residential) from 2019 to 2021, with the Kayrros Carbon Watch data and the official Citepa in Figure 7.
For domestic aviation, we found that that CM-EU emissions are lower than Kayrros both in EU27 & UK and France in 2019 (Fig. 7).This is because our definition of domestic flights for France includes only metropolitan-France (mainland) trips whereas Kayrros includes France to EU, and metropolitan-France to overseas French territories emissions.This explains why Kayrros' estimates are larger.The same is true for EU27 & UK.Nevertheless, Kayrros emissions for domestic aviation are lower than CM-EU after the COVID-19 pandemic outbreak.This may be because a passenger load factor was considered for the estimates of Kayrros but not in CM-EU.The passenger load factors of flights have dropped significantly since the COVID-19 pandemic.The reason why Citepa emissions are higher than CM-EU and Kayrros for domestic aviation (Fig. 7) is because the definition of domestic flights for Citepa is all flights in and out of metropolitan-France (mainland), and half of flights between Mainland and French overseas territories (the other half is considered of the responsibility/accounting of the overseas territories).Non-commercial flights are also considered for the estimates of Citepa, which are not in CM-EU and Kayrros.
For industry, the CM-EU emissions are higher than Kayrros, but lower than Citepa.This is because the scope of Kayrros covering the regulated industrial installations is lower than the total industry sector of CM-EU, and there are the balances of attributions between power and industry for power production on industrial sites in Kayrros.While all the manufacturing industries, construction and cement production are considered in CM-EU and Citepa.Citepa also considers other industrial productions.
For power, the CM-EU emissions in EU27 & UK are almost the same as Kayrros but small differences in winter peak and summer trough (Fig. 7).This is because both datasets use the electricity production by fuel type as activity data from the same data sources.Kayrros can catch the differences from fuel burning efficiency in facility level while CM-EU can't.But the differences canceled each other when aggregating data for all countries, though they used different annual power emissions as baseline and different emission factors.In France, CM-EU only consider the emissions from power generation in the 'power' sector.While urban heating and other electricity selfproducers industries are considered in Citepa.Thus, Citepa emissions for 'power' are larger than CM-EU.While Kayrros used the annual power emissions from individual French ETS plants annual reporting as the baseline, which are nearly twice larger than those of CM-EU, with largest differences during the cold season.Kayrros also considered the fuel burning efficiency in facility level.This indicates that the aggregate 'emission factor' based on 2019 data from EDGAR in CM-EU is lower than the emission factors deduced by Kayrros from ETS declared plant level emissions, a difference that deserves further investigation in the future.Thus, the data of Kayrros have almost the same temporal pattern but are larger with the CM-EU.
For ground transport, the CM-EU emissions are almost the same than those of the Citepa, but the Kayrros emissions are larger in the summer and lower in the winter.The mobility from trains, expected to increase in the vacation period, was not filtered from vehicles in Kayrros, so the data in the period from July to September were removed.
For residential emissions, the CM-EU emissions are higher in the summer than Citepa.This may be because we assume that the residential emissions in the summer are equal to the emissions from cooking, and cooking emissions were assumed to remain stable all the year, while the emissions from heating were assumed to depend on and vary by the heating demand.

Technical validation for ground transportation sector and residential sector
For technical validation, the CM-EU near-real-time daily activity data used for the ground transport sector, we compared our estimates to annual traffic counts and CO2 emissions or fossil fuel use of ground transport sector for EU countries and the United Kingdom from 2010 to 2019 in Figure 8.The annual traffic counts data we used come from Eurostat 36 , defined as motor vehicle movements on national territory (irrespective of registration country), covering 26 EU countries (Belgium, Bulgaria, Czech Republic, Denmark, Germany, Estonia, Ireland, Spain, France, Croatia, Italy, Cyprus, Latvia, Lithuania, Luxembourg, Hungary, Malta, Netherlands, Austria, Poland, Portugal, Romania, Slovenia, Slovakia, Finland, Sweden) and the United Kingdom.The annual fossil fuel use of ground transport sector data come from IEA 37 , including five types of fossil fuel (coal, crude, oil, natural gas and peat).The CO2 emissions data of ground transport are from EDGAR 8 , including road transportation no resuspension, rail transportation, inland navigation and other transportation.The comparison statistics shown in Figure 8 indicate that the coefficient of determination (R 2 ) values are 0.7891 between traffic counts and CM-EU ground transport emissions and 0.7834 between traffic counts and fossil fuel use of ground transport, respectively.
For the residential sector, we compared daily emissions from CM-EU with estimates derived from natural gas use from ENSTO-G 38 in Germany, France, Italy, Poland, Netherlands, Belgium, Hungary, Romania and Luxembourg.Here we use natural gas use data from ENTSO-G as activity data instead, and annual residential emissions in 2019 from EDGAR as baseline.The average yearly emission factor of the whole residential sector is assumed to remain constant at its 2019 value, so that daily emissions are estimated as:  39 for the German and e-control 40 for Austria.Note that the consumption sectors are not provided by e-control dataset.We further split the consumption into more detailed sectors, including household and public buildings heating, industry, and others based on energy balance datasets from Eurostat 41 following the method from Zhou et al. 42 Note that the consumption for the power sector was refined based on ENTSO-E (Carbon monitor data) as it provides higher temporal resolutions.The activity data used here are only from gas fuel and we assume that there is a linear relationship between gas fuel use and total fossil fuel use for residential sector.The results in Figure 9 show that the variation of residential emissions in our study are similar to those of ENTSO-G in all countries (R 2 ranges from 0.5 to 0.56), but ENTSO-G has a more prenounced winter peak and summer trough.

Uncertainty analysis
There are two main sources of uncertainties in the CM-EU data. 1.The uncertainty inherited from the EDGAR annual national emissions used for the reference year 2019.2. Uncertainty from daily activity data and models used to downscale them into daily emissions.The uncertainty analysis was conducted based on the 2006 IPCC Guidelines for National Greenhouse Gas Inventories 26 .First, uncertainties were calculated for each sector based on the global Carbon Monitor methodology described in ref. 21.For the power sector, CM-EU uses daily statistics of actual thermal production as activity data.When no uncertainty information is available, the 2-sigma uncertainty of the power activity data is assumed to be ±5% according to the IPCC recommended default uncertainty range of energy statistics 26 .In addition, for emission factors, the uncertainties mainly come from the variability of coal emission factors (as coal has a wide range of emission factors of different coal types) and changes in the mix of fuels in thermal power production.CM-EU calculates emission factors based on annual thermal production 7 and annual power emissions 43 , and the uncertainty range is ±13%.We used error propagation equations to combine the aforementioned uncertainties of each part and estimated the uncertainties of annual power emissions as ±10%.For the industry sector, a 2-sigma uncertainty (±36%) of CO2 emissions from industry and cement production is estimated from monthly production data and sectoral emission factors.The uncertainty of industrial output data is assumed to be ±20% in the industry sector 44 .For the sectoral emission factor uncertainty, according to Carbon Monitor methodology, we calculate national emission factors in 2010-2012 in USA, France, Japan, Brazil, Germany, and Italy according to data availability of monthly emission data and IPI data, and their 2-sigma uncertainties vary from ±14% to ±28.Thus, we adopt a conservative uncertainty of ±30% for CM-EU emissions in this sector.For the ground transport sector, the global Carbon Monitor methodology assessed a 2sigma uncertainty of ±9.3% from the prediction interval of the regression model built in Paris to estimate the emissions from this sector.Note that the regression model in Paris between car counts and the TomTom congestion index was based on assuming a relative magnitude in car counts; thus, emissions follow a similar relationship with the TomTom congestion index in Paris.For the residential sector, global Carbon Monitor compares the estimates by using our methodology with estimates from publicly available natural gas daily consumption data by residential and commercial buildings for France (https://www.smart.grtgaz.com/fr/consommation).The 2-sigma uncertainty of the daily emission estimations is further quantified as ±40%.For the aviation sector, global Carbon Monitor compares estimates by using two different activity data, i.e., the flight route distance (what we used in this study) and the number of flights and calculate the average difference to quantify the uncertainty of ±10.2% in the aviation sector.Overall, the uncertainty ranges of the power, ground transportation, industry, residential, and aviation are ±10.0%,±9.3%, ±30.0%, ±40.0%, and ±10.2%, respectively and the uncertainty in the emission of EDGAR for 2019 is estimated as ±7.1% 45 .Then, we combine all the uncertainties by following the error propagation equation.
where Us and μs are the percentage and quantity (daily mean emissions) of the uncertainty of sector s, s respectively.The overall uncertainty is quantified as ±13.6%.We also make the technical validation for CM-EU.Therefore, the uncertainty is equal to the maximum value between the uncertainty ranges and the mean relative uncertainty from technical validation data.Finally, the overall uncertainty range of CM-EU is estimated as ±13.6%.

Usage Notes
The generated datasets are available from https://doi.org/10.6084/m9.figshare.20219024.v1.We recommend loading the data with a script that can handle large datasets.Users should also note that the unit of emissions in this dataset is Mt CO2.Latest updates and related information are available for view and download on our website https://eu.carbonmonitor.org/.

1 . 7 -
Figure 1.7-days smoothed (running mean) daily CO2 emissions for EU27+UK, Germany, the United Kingdom, Italy, Poland, France, Spain, Netherlands and the rest of European countries in 2019, 2020 and 2021.Grey shaded areas indicates the changes between 2019 and 2020.The percentage and numbers in the top of each panel reflect the relative and absolute change in 2021 compared with 2019.Bars at the bottom show the sectoral shares of annual emissions in 2021.(Aviation includes the domestic and international aviation).

Figure 3 .
Figure 3. Changes in EU27 & UK emissions from 2019 to 2020 and 2021 across regions and sectors (a).Contribution by major countries / emitters and sectors in 2019, 2020 and 2021 (b).

Figure 5 .Figure 6 .
Figure 5.Comparison of annual CO2 emissions in 2019 and 2020 and the relative changes between the two years among six datasets (CM-EU, EDGAR, BP, IEA, GCP and Eurostat) for EU27 & UK, Germany, UK, Italy, Poland, France, Spain, Netherlands and the rest of EU.

Figure 7 .Figure 8 .
Figure 7. Technical validation of short-term emissions changes with other available 'high frequency' data.(a) Comparison of monthly CO2 emissions for four sectors (power, industry, ground transport and domestic aviation) for EU27 & UK from 2019 to 2021 between CM-EU and Kayrros Carbon Watch data (see text).(b) Comparison of monthly CO2 emissions in France for power, industry, ground transport, domestic aviation and residential from 2019 to 2021 between CM-EU, Kayrros Carbon Watch data20 and Citepa monthly emission bulletin16 (P+I+G+D means the total emissions of power, industry, ground transport and domestic aviation).

Figure 9 .
Figure 9.Comparison of daily CO2 emissions of residential sector from 2019 to 2021 between CM-EU and ENTSO-G for Germany, France, Italy, Poland, Netherlands, Belgium, Hungary, Romania and Luxembourg.

Table 3 .
Cities (203 across 24 EU countries and UK) where TomTom congestion level data are available.

Table 4 .
List of CO2 emissions datasets used for technical validation of CM-EU products