Version : base carbone® V23.4 Voir le suivi des modifications apportées par la V23.4 La Base Carbone® est une base de données publique de facteurs d'émissions, nécessaires à la réalisation d’un bilan d’émissions de gaz à effet de serre (GES) et plus généralement tout exercice de comptabilité carbone. Elle est la base de données de référence de l'article 75 de la loi Grenelle II, relatif à l’obligation de réalisation d’un Bilan GES pour les entreprises de plus de 500 salariés, les établissements publics de plus de 250 agents et les collectivités de plus de 50 000 habitants. Administrée par l'ADEME, sa gouvernance est multi acteurs : 14 membres la composent tels que le Ministère de la Transition écologique et solidaire (MTES), le Mouvement des entreprises de France (MEDEF), le Réseau Action Climat (RAC), l’Association des Professionnels en Conseil Climat (APCC), etc. Retrouvez le descriptif complet de la Base dans la rubrique « Base Carbone » du site Base Empreinte, ainsi que toute sa documentation explicitant périmètre et sources des données proposées pour s’assurer d’une utilisation robuste des données. Pour toute question, n’hésitez pas à nous contacter via base-empreinte@ademe.fr

The Carbon Base is a public database, managed by ADEME, of emission factors necessary for carrying out carbon accounting exercises. (An emission factor is a ratio of greenhouse gas emissions related to an object, material, or service). ADEME gives the following description on its site:

Today, it is the reference database of Article 75 of the Grenelle II Act and is fully consistent with Article L1341-3 of the Transport Code and the default values of the European Emissions Trading System. Administered by ADEME, its governance is multi-stakeholder: 14 members make up it such as the Ministry of Ecological and Solidarity Transition (MTES), the Mouvement des entreprises de France (MEDEF), the Climate Action Network (RAC), the Association of Professionals in Climate Council (APCC), etc. Its enrichment is open to all through the possibility of external contributions.

Access to the official base

The legal framework is as follows: Article L312-1-1** of the Code of Relations between the Public and Administration (CRPA) stipulates that administrations are obliged to publish online “*data, regularly updated, whose publication is of economic, social, health or environmental interest*”. * Article D323-2-1** of the RCAP states that, if the administration wishes to restrict the possible re-use of the data, it may choose one of the following licenses: “Open License” or “Open Database License”. If it wishes to impose another licence, it must be the subject of prior approval (Article D323-2-2). * Article L300-4** of the CRPA adds that the data must be published “in an open standard, easily reusable and usable by an automated processing system*”.

Until 28 May 2020, the “Base Carbone” files could only be viewed online one by one (after creating a user account). This did not allow automated processing. The complete download of the database was restricted (subject to the supply of a Kbis and the signing of a licence not approved within the meaning of Article D323-2-2). The ADEME offered free download, under the Open License, only one extract of 858 lines (version 14.0). This extract represented only 6 % of the base, and was not up to date with the latest version.

Since 28 May 2020, ADEME has been broadcasting Base Carbone v18.0 on the same site, in trilingual version and with v18.0 data, without requiring the creation of a user account or the signing of a specific license. Unfortunately, the license chosen is not indicated on this page. It is nevertheless from this dataset that we have to leave for any new analysis.

Description of the proposed game

Here we keep a work of artisan consolidation of the complete base, which was useful before the publication by ADEME dated May 28, 2020 of the database in open data: * the game is distributed in two formats: * a format XLSX, for easy opening in Excel, for the general public, * a format CSV, with encoding UTF-8, separator virgul, for automated use in a standard format, for computer scientists, * the data are those of the version 17.0 (14 November 2019) which is therefore no longer the latest version, * column names are chosen from the official extract from the Carbon Base proposed for download, * only fields in French are taken up, saving time, * the “Element Type” field is not completed because it does not understand its definition.

Documentation

The best available documentation is the one written and disseminated by ADEME, for example from the User Manual page of the official website. Reading this excellent documentation is essential to fully understand the meaning of the data. In addition, the official website contains additional information on how to calculate emission factors.

La base de données de référence de l'article 75 de la loi Grenelle II et est entièrement homogène avec l'article L1341-3 du Code des Transports et les valeurs par défaut du système d'échange des quotas d'émissionseuropéen.Administrée par l'ADEME, sa gouvernance est multi acteurs : 14 membres la composent tels que le Ministère de la Transition écologique et solidaire (MTES), le Mouvement des entreprises de France (MEDEF), le Réseau Action Climat (RAC), l’Association des Professionels en Conseil Climat (APCC), etc. Son enrichissement est ouvert à tous via la possibilité de contributions externes.

La Base Carbone est une base de données publiques, gérée par l'ADEME, de facteurs d'émissions nécessaires à la réalisation d'exercices de comptabilité carbone. (Un facteur d'émission est un ratio permettant de connaître les émissions de gaz à effet de serre liées à un objet, une matière, ou un service). L'ADEME en donne, sur son site, la description suivante :

Aujourd'hui, elle est la base de données de référence de l'article 75 de la loi Grenelle II et est entièrement homogène avec l'article L1341-3 du Code des Transports et les valeurs par défaut du système d'échange des quotas d'émissions européen. Administrée par l'ADEME, sa gouvernance est multi acteurs : 14 membres la composent tels que le Ministère de la Transition écologique et solidaire (MTES), le Mouvement des entreprises de France (MEDEF), le Réseau Action Climat (RAC), l’Association des Professionels en Conseil Climat (APCC), etc. Son enrichissement est ouvert à tous via la possibilité de contributions externes.

Accès à la base officielle

Le cadre légal est le suivant : * L'**article L312-1-1** du Code des Relations entre le Public et l'Administration (CRPA) dispose que les administrations ont l'obligation de publier en ligne "*les données, mises à jour de façon régulière, dont la publication présente un intérêt économique, social, sanitaire ou environnemental*". * L'**article D323-2-1** du CRPA précise que, si l'administration souhaite restreindre les réutilisations possibles des données, elle peut choisir une des licences suivantes : "Licence Ouverte" ou "Open Database License". Si elle souhaite imposer une autre licence, celle-ci doit faire l'objet d'une homologation préalable (article D323-2-2). * L'**article L300-4** du CRPA ajoute que les données doivent être publiées "*dans un standard ouvert, aisément réutilisable et exploitable par un système de traitement automatisé*".

Jusqu'au 28 mai 2020, les fiches de la "Base Carbone" n'étaient visualisables en ligne qu'une par une (après création d'un compte utilisateur). Cela ne permettait pas un traitement automatisé. Le téléchargement complet de la base était restreint (soumis à la fourniture d'un Kbis et à la signature d'une licence n'ayant pas fait l'objet d'une homologation au sens de l'article D323-2-2). L'ADEME proposait au téléchargement libre, sous la Licence Ouverte, uniquement un extrait de 858 lignes (version 14.0). Cet extrait représentait seulement 6% de la base, et n'était pas à jour avec la dernière version.

Depuis le 28 mai 2020, l'ADEME diffuse la Base Carbone v18.0 sur ce même site, en version trilingue et avec les données v18.0, sans exiger la création d'un compte utilisateur, ni la signature d'une licence spécifique. La licence choisie n'est hélas pas indiquée sur cette page. C'est néanmoins désormais de ce jeu de données qu'il faut partir pour toute nouvelle analyse.

Description du jeu proposé

Nous conservons ici un travail de consolidation artisanale de la base complète, qui était utile avant la publication par l'ADEME datant du 28 mai 2020 de la base en open data : * le jeu est distribué sous deux formats : * un format XLSX, pour une ouverture facile dans Excel, à destination du grand public, * un format CSV, avec un encodage UTF-8, séparateur virgule, pour un usage automatisé dans un format standard, à destination des informaticien-ne-s, * les données sont celles de la version 17.0 (14 novembre 2019) qui n'est donc plus la dernière version, * les noms de colonne sont choisis à partir de l'extrait officiel de la Base Carbone proposé au téléchargement, * seuls les champs en langue française sont repris, par gain de temps, * le champ de "Type de l'élément" n'est pas complété, faute d'avoir compris sa définition.

Documentation

La meilleure documentation disponible est celle rédigée et diffusée par l'ADEME, par exemple à partir de la page Manuel d'utilisation du site officiel. La lecture de cette excellente documentation est indispensable pour bien comprendre le sens des données. De plus, le site officiel contient d'autres informations supplémentaires sur les modalités de calcul des facteurs d'émission.

Only the codes relevant to at least one of the six laboratories were given a non-null value. (XLSX)

PAGE WEB base-carboner

Consumption-based accounting (CBA) of emissions (also called carbon footprints calculated using MRIO methods) accounts for emissions associated with imported and exported goods. CBA reports the total emissions associated with final demand in each country.

Emissions physically occurring in a country are its territorial emissions. This is sometimes called production-based accounting (PBA). This is the standard reporting of GHG emissions as reported by CDIAC, IEA, the JRC EDGAR database, UNFCCC, and others.

CBA can be calculated using a global multi-region input-output (MRIO) model which traces global supply chains. This dataset uses the Eora MRIO model to calculate the CBA emissions for each country.

Emissions from fossil fuel combustion and cement production are reattributed to the countries where final demand induced the production associated with those emissions. Emissions from aviation and marine bunker fuels are not included in the CBA inventory, as no method has yet been developed to allocate emissions from bunker fuels to countries other than where the fuel is bunkered.

In this dataset, territorial emissions are taken from the PRIMAP emissions database using the HISTCR scenario. Population and GDP data are from the World Bank. CBA results are from the Eora MRIO model (https://worldmrio.com) v199.82, years 1990-2018, by Daniel Moran, Keiichiro Kanemoto, and Arne Geschke.

Sources: OECD (2021), OECD Inter-Country Input-Output Database, https://oe.cd/icio; International Monetary Fund (IMF), Statistics Department Questionnaire; IMF staff calculations.Category: Climate FinanceData series:Carbon Footprint of Bank Loans (Based on emission intensities)Carbon Footprint of Bank Loans (Based on emission intensities - normalized)Carbon Footprint of Bank Loans (Based on emission multipliers)Carbon Footprint of Bank Loans (Based on emission multipliers - normalized)Metadata:For relevant literature see Guan, Rong, Haitao Zheng, Jie Hu, Qi Fang, and Ruoen Ren. 2017. “The Higher Carbon Intensity of Loans, the Higher Non-Performing Loan Ratio: The Case of China.” Sustainability 9 (4) (April 22): 667. https://dx.doi.org/10.3390/su9040667.Methodology:The IMF has developed the Carbon Footprint of Bank Loans (CFBL) indicator for selected countries. CFBL indicator requires (i) deposit takers’ domestic loans by industry data, and (ii) the estimation of carbon emission factors (CEFs) by industry.The IMF has conducted a data collection exercise to obtain deposit takers’ domestic loans by industry data. The CEFs are calculated based on (i) direct metric tons of carbon emissions from fuel consumption per million $US of output by country and industry (CO2 emission intensities), and (ii) direct and indirect carbon emissions from fuel consumption per million $US of output by country (CO2 emission multipliers). The output multipliers and carbon emission intensities for 66 countries and 45 industries are sourced from the OECD Input-Output Database. Direct and indirect carbon emission factors are calculated by multiplying the Leontief inverse (also known as input-output multipliers) from the OECD World Input-Output Table by the carbon emissions from fuel consumption intensities.CFBL indicator is obtained by multiplying domestic loans to a specific industry by their corresponding carbon emission factors, summing over all industries and dividing the final result by total domestic loans. For a limited number of countries, updated CFBL information until 2018 will be posted in due course. CFBL is an experimental indicator. The index requires a nuanced reading. For instance, a sharp increase in the share of a brown industry in the deposit takers’ loans portfolio may create a negative impact on this indicator in the short term, but longer term results could diverge significantly if these loans were allocated for transition to low carbon environment or for continuing unsustainable brown activities. The emission coefficients applied to loans related to the emissions of the industry and not the emissions resulting from the consumption of the goods the industry produces. Also, the estimation methodology has a number of limitations. First, class level ISIC data could be more appropriate for the CFBL estimation, as it offers more detailed information to evaluate carbon footprint by industry. However, carbon emission factors are not available at this granularity. Also, the ISIC structure is not fully aligned with the needs of climate finance.Second, the granularity of the deposit takers’ domestic loans by industry data availability is not fully consistent across jurisdictions. It is not possible to obtain the loans by industry data at the same level of granularity from all participating countries. Third, the country coverage is limited as carbon intensity factors are available for only 66 countries. Fourth, input-output multipliers have limiting assumptions. Input-output multipliers are static (i.e., assume that there is a fixed input structure and fixed ratios for production for each industry) and do not take into account supply-side constraints or budget constraints. Please see additional information in this link.

Emission factors used for the calculation

The Emission factors used are those of ADEME's Base Carbone, according to the values ​​in force on the date the indicators are updated More information on the site: www.bilans-ges.ademe.fr

For calculations made in 2020 (reference year 2019), the emission factors are presented below. They include combustion emissions (direct) and upstream emissions (indirect) for each mode of transport:

Calcul des indicateurs GES pour les différents modes de transport

Les indicateurs sont calculés ci-après pour l’année 2019. Pour les modes opérés par différents opérateurs de transport, un facteur d’émission moyen est calculé à partir des émissions moyennes de chaque réseau, pondérées par ses voyageurs-kilomètres. C’est le cas pour les RER et trains ainsi que pour les bus.

There is no description for this dataset.

The Global Emissions Inventory Activity (GEIA) is an activity of the International Global Atmospheric Chemistry (IGAC) Core Project of the International Geosphere-Biosphere Program (IGBP). The focus of GEIA is to make global emissions available on a one degree grid.

A global data base of black carbon emissions to the atmosphere from fossil fuel combustion has been compiled for atmospheric chemistry and climate studies. The data base is on a 1 x 1 degree latitude/longitude grid and is based on the work of Matthews (1983), Lerner et al. (1988), and Dignon (1992). The original work of Penner et al. (1993) provides the emissions inventory data on a 5 x 5 degree grid.

Units of emission yield a global total of 12.6 TgC/y and are given as the mass in metric tons of carbon for each 1 x 1 degree grid cell. The emissions are expected to represent the emissions for a typical mid-1980's year. The distribution is based on national totals and then mapped to a 1 x 1 degree grid according to the updated population mapping of Logan (1993).

The online fashion-retailer Boohoo reported its location-based carbon dioxide emissions (CO2) released worldwide from 2020 to 2023. In 2021, Boohoo emitted about ************ metric tons of CO2. By 2023, the company's carbon emissions decreased to roughly ************ metric tons.

Die Carbon Base ist eine von der ADEME verwaltete öffentliche Datenbank von Emissionsfaktoren, die für die Durchführung von CO2-Buchführungsjahren erforderlich sind. (Ein Emissionsfaktor ist ein Verhältnis zur Kenntnis der Treibhausgasemissionen eines Objekts, eines Materials oder einer Dienstleistung). Die ADEME enthält auf ihrer Website folgende Beschreibung:

Heute ist sie die Referenzdatenbank des Artikels 75 des Gesetzes Grenelle II und ist vollständig homogen mit Artikel L1341-3 des Verkehrsgesetzbuchs und den Standardwerten des europäischen Emissionshandelssystems. Die von der ADEME verwaltete Governance ist eine Multi-Stakeholder-Governance: 14 Mitglieder bilden sie wie das Ministerium für ökologischen und solidarischen Übergang (MTES), die Société desEntreprises de France (MEDEF), das Netzwerk Climat Action (RAC), die Vereinigung der Fachleute im Klimarat (APCC), etc. Ihre Bereicherung steht allen durch die Möglichkeit von externen Beiträgen offen.

Zugriff auf die offizielle Basis

Der rechtliche Rahmen ist wie folgt: * Gemäß Artikel L312-1-1** des Code des Relations zwischen der Öffentlichkeit und der Verwaltung (CRPA) sind die Behörden verpflichtet, „die Daten, die regelmäßig aktualisiert werden und deren Veröffentlichung von wirtschaftlichem, sozialem, Gesundheits- oder Umweltinteresse ist, online zu veröffentlichen“. * In Artikel D323-2-1** des CRPA heißt es, dass die Verwaltung, wenn sie die mögliche Weiterverwendung der Daten einschränken möchte, eine der folgenden Lizenzen wählen kann: „Offene Lizenz“ oder „Open Database License“. Wenn sie eine andere Lizenz vorschreiben möchte, muss diese zuvor genehmigt werden (Artikel D323-2-2). * Artikel L300-4** des CRPA fügt hinzu, dass die Daten „*in einem offenen Standard veröffentlicht werden müssen, der leicht wiederverwendbar und über ein automatisiertes Verarbeitungssystem verwertbar ist*“.

Bis zum 28. Mai 2020 waren die Datenblätter der „Kohlenstoffbasis“ online nur einzeln (nach Erstellung eines Benutzerkontos) einsehbar. Dies erlaubte keine automatisierte Verarbeitung. Der vollständige Download der Basis war beschränkt (bedingt mit der Bereitstellung eines Kbis und der Unterzeichnung einer Lizenz, die nicht gemäß Artikel D323-2-2 genehmigt wurde). Die ADEME bot zum kostenlosen Download unter der Offenen Lizenz nur einen Auszug aus 858 Zeilen (Version 14.0) an. Dieser Extrakt machte nur 6 % der Basis aus und war mit der neuesten Version nicht auf dem neuesten Stand.

Seit dem 28. Mai 2020 verbreitet die ADEME die Base Carbone v18.0 auf derselben Website, in dreisprachiger Version und mit den Daten v18.0, ohne die Erstellung eines Benutzerkontos oder die Unterzeichnung einer bestimmten Lizenz zu verlangen. Die gewählte Lizenz ist leider nicht auf dieser Seite angegeben. Aber von diesem Datensatz muss man für jede weitere Analyse ausgehen.

Beschreibung des vorgeschlagenen Spiels

Hier behalten wir eine handwerkliche Konsolidierungsarbeit der vollständigen Basis vor, die vor der Veröffentlichung der Datenbank in open data durch die ADEME am 28. Mai 2020 nützlich war: * das Spiel wird in zwei Formaten vertrieben: * ein Format XLSX für ein einfaches Öffnen in Excel für die breite Öffentlichkeit, * ein Format CSV, mit Codierung UTF-8, Separator Semikolon, zur automatisierten Verwendung in einem Standardformat für Informatiker, * bei den Daten handelt es sich um die Version 17.0 (14. November 2019), die somit nicht mehr die neueste Version ist. * die Spaltennamen werden aus dem offiziellen Extrakt der Carbon Base ausgewählt, der zum Download angeboten wird. * nur Felder in französischer Sprache werden zur Zeitersparnis übernommen, * das Feld „Typ des Elements“ wird nicht ausgefüllt, da es seine Definition nicht verstanden hat.

Dokumentation

Die beste verfügbare Dokumentation ist die von der ADEME verfasste und verbreitete Dokumentation, z. B. auf der Seite Benutzerhandbuch der offiziellen Website. Das Lesen dieser ausgezeichneten Dokumentation ist unerlässlich, um die Bedeutung der Daten zu verstehen. Darüber hinaus enthält die offizielle Website weitere Informationen zur Berechnung der Emissionsfaktoren.

OverviewThis emissions layer is part of the forest carbon flux model described in Harris et al. (2021). This paper introduces a geospatial monitoring framework for estimating global forest carbon fluxes which can assist a variety of actors and organizations with tracking greenhouse gas fluxes from forests and in decreasing emissions or increasing removals by forests. Forest carbon emissions represent the greenhouse gas emissions arising from stand-replacing forest disturbances that occurred in each modeled year (megagrams CO2e emissions/ha, between 2001 and 2024). Emissions include all relevant ecosystem carbon pools (aboveground biomass, belowground biomass, dead wood, litter, soil organic carbon) and greenhouse gases (CO2, CH4, N2O). Emissions estimates for each pixel are calculated following IPCC Guidelines for national greenhouse gas inventories where stand-replacing disturbance occurred, as mapped in the Global Forest Change annual tree cover loss data of Hansen et al. (2013). The carbon emitted from each pixel is based on carbon densities in 2000, with adjustment for carbon accumulated between 2000 and the year of disturbance.Emissions reflect a gross estimate, i.e., carbon removals from subsequent regrowth are not included. Instead, gross carbon removals resulting from subsequent regrowth after clearing are accounted for in the companion forest carbon removals layer. The fraction of carbon emitted from each pixel upon disturbance (emission factor) is affected by several factors, including the direct driver of disturbance, whether fire was observed in the year of or preceding the observed disturbance event, whether the disturbance occurred on peat, and more. All emissions are assumed to occur in the year of disturbance. Emissions can be assigned to a specific year using the Hansen tree cover loss data; separate rasters for emissions for each year are not available from GFW. All input layers were resampled to a common resolution of 0.00025 × 0.00025 degrees each to match Hansen et al. (2013).We have made several updates to the model since its original release. For documentation through the current version, please refer to this blog. For a more detailed description of the changes included through the 2023 tree cover loss launch (released spring 2024) and a comparison of the model's fluxes with those from the Global Carbon Budget and national greenhouse gas inventories, please refer to this article.Three variations of emissions rasters are available for download:megagrams CO2e emissions/ha in pixels with >30% tree cover density (TCD) in 2000 or tree cover gain: Used for visualizing (mapping) emissions according to the default GFW TCD threshold because it represents the density of emissions per hectare. You would use this if you want to only include emissions in pixels that are more conservatively defined as forest.megagrams CO2e emissions/pixel in pixels with >30% TCD in 2000 or tree cover gain: Used for calculating the emissions in an area of interest (AOI) according to the default GFW TCD threshold because the values of the pixels in the AOI can be summed to obtain the total emissions for that area. You would use this if you want to only include emissions in pixels that are more conservatively defined as forest.megagrams CO2e emissions/pixel in pixels with any amount of tree cover in 2000 or tree cover gain: Used for calculating the emissions in an area of interest (AOI) without any TCD threshold because the values of the pixels in the AOI can be summed to obtain the total emissions for that area. This would represent the total emissions from tree cover loss in the AOI without applying a TCD threshold. You would use this if you want to include emissions in pixels that have low (<30%) TCD in 2000.The values in the megagrams CO2e/pixel layers were calculated by adjusting the emissions per hectare by the size of each pixel, which varies by latitude. Tree cover density in 2000 is according to Hansen et al. (2013) and tree cover gain between 2000 to 2020 is according to Potapov et al. (2022)Related Open Data Portal layers: Forest Carbon Removals, Net Forest Carbon FluxGoogle Earth Engine: asset (megagrams CO2e emissions/ha in pixels with >30% TCD) and visualization scriptResolution: 30 x 30mGeographic Coverage: GlobalFrequency of Updates: AnnualDate of Content: 2001-2024CautionsData are the product of modeling and thus have an inherent degree of error and uncertainty. Users are strongly encouraged to read and fully comprehend the metadata and other available documentation prior to data use.Values are applicable to forest areas only (canopy cover >30 percent and >5 m height or areas with tree cover gain). See Harris et al. (2021) for further information on the forest definition used in the analysis.Although emissions in each pixel are associated with a specific year of disturbance, emissions over an area of interest reflect the total over the model period of 2001-2024. Thus, values must be divided by 24 to calculate average annual emissions.Emissions reflect stand-replacing disturbances as observed in Landsat satellite imagery and do not include emissions from unobserved forest degradation.Emissions reflect a gross estimate, i.e., carbon removals from any regrowth that occurs after disturbance are not included. Instead, gross carbon removals are accounted for in the companion forest carbon removals layer.Emissions data contain temporal inconsistencies. Improvements in the detection of tree cover loss due to the incorporation of new satellite data and methodology changes between 2011 and 2015 may result in higher estimates of emissions in recent years compared to earlier years. Refer here for additional information.Forest carbon emissions do not reflect carbon transfers from ecosystem carbon pools to the harvested wood products (HWP) pool.This dataset has been updated since its original publication. See Overview for more information.

The city’s industrial transformation leads to a large amount of carbon emissions, which poses a thorny problem for the allocation of carbon responsibilities. This study established a multi-dimension long-term carbon emission analysis model to explore the characteristic of Beijing’s embodied carbon emissions, which could calculate the production-based, consumption-based and income-based carbon emissions. Then, structural decomposition analysis was adopted to quantify the contribution of socioeconomic factors in local and imported carbon emissions. In addition, emission linkage analysis was used for revealing the long-term evolutionary trajectories of sectors. The key discovery can be summarized as follows: 1) the fluctuation trend of production-side and income-side carbon emissions in Beijing is stable and decreased by 3.53% from 2002 to 2017, while consumption-side carbon emissions increased rapidly by 795.45%. 2) The energy, transportation and other services sectors from the supply, production and consumption perspectives. 3)Per capita consumption, production structure and consumption structure are the major contributors of carbon emissions. The study is expected to provide decision support for policymakers to reasonably formulate carbon mitigation policies and allocate carbon mitigation responsibilities from multiple perspectives, and promote the realization of the “carbon peak and carbon neutrality” strategy.

The United Nations Framework Convention on Climate Change (UNFCCC) requires the annual reporting of greenhouse gas emissions. These inventories focus on emissions within a territory, and do not capture the effect of de-carbonization in developed countries that has resulted simply by the relocation of emissions-intensive production to other countries. Consumption based carbon accounting (CBCA) has been proposed as a complementary method to capture the emissions occurring globally due to final demand in a country. A number of global models have been developed in the last decade in order to operationalise CBCA. However, direct comparison of results from different models yields significant discrepancies in country-level CBCA, which causes concern for the practical use of CBCA. There is a body of existing work on model intercomparison and reliability, but this literature has largely overlooked a main use case of CBCA results: trends over time. To facilitate temporal intercomparison, we present results of all the major global models and normalise the model results by looking at changes over time of each model relative to a common base year value. We give an analysis of the variability across the models, both before and after normalisation in order to give insights into robustness (variance) at both national and regional level. The paper is accompanied by the dataset of CBCA results of each country/year with harmonised results (based on the means) and measures of dispersion, providing a useful and often requested baseline dataset for CBCA validation and analysis.

The global Carbon Emission Real-time Monitoring Platform market is experiencing robust growth, projected to reach $1348.6 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 4.5% from 2025 to 2033. This expansion is driven by increasing regulatory pressure on industries to reduce their carbon footprint, coupled with growing awareness of environmental sustainability and the need for accurate, real-time emission data. Key drivers include stringent emission reduction targets set by governments worldwide, the rising adoption of sophisticated monitoring technologies (like satellite-based monitoring and advanced sensors), and the increasing demand for robust data analytics to optimize emission reduction strategies. The market's segmentation reveals a strong presence across various applications, including the steel, power, and chemical industries, with both on-premises and cloud-based solutions gaining traction. The competitive landscape is dynamic, featuring established players like ABB and Wood PLC alongside innovative startups such as GHGSat and Carbon Mapper, creating a diverse range of solutions tailored to specific industry needs. North America and Europe currently dominate the market share, however, the Asia-Pacific region is expected to demonstrate significant growth in the coming years, fueled by rapid industrialization and increasing environmental regulations in countries like China and India. The diverse applications of these platforms, ranging from precise emission quantification to optimizing operational efficiency, are pivotal to their continued success. The shift towards cloud-based solutions enhances accessibility, scalability, and cost-effectiveness, while advancements in AI and machine learning are improving data analysis and predictive capabilities. However, challenges such as high initial investment costs, the need for robust data infrastructure, and the complexity of integrating these platforms into existing operational systems remain. Nevertheless, the compelling need for accurate and timely emission data, coupled with technological advancements and supportive regulatory frameworks, will likely fuel further market expansion throughout the forecast period, creating significant opportunities for both established players and emerging companies within this rapidly evolving sector.

The Carbon Emission Monitoring Platform market is experiencing robust growth, driven by increasing regulatory pressure to reduce greenhouse gas emissions and a growing corporate focus on Environmental, Social, and Governance (ESG) initiatives. The market, estimated at $8 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 15% between 2025 and 2033, reaching approximately $25 billion by 2033. This expansion is fueled by several key trends, including the rising adoption of cloud-based solutions for enhanced scalability and accessibility, the increasing demand for sophisticated data analytics and reporting capabilities, and the growing integration of IoT sensors for real-time emission monitoring. Key application sectors driving growth include manufacturing, energy, and transportation, while the cloud-based segment dominates the market due to its cost-effectiveness and flexibility. However, the market faces challenges, including high initial investment costs for implementing comprehensive monitoring systems and concerns about data security and privacy. Despite these restraints, the long-term outlook remains positive, driven by stricter emission regulations globally and the increasing awareness of the critical role carbon emission monitoring plays in mitigating climate change. The competitive landscape is characterized by a mix of established players and emerging technology providers. Major vendors such as Sphera, Wolters Kluwer, and Honeywell are leveraging their expertise in environmental compliance and industrial automation to offer comprehensive solutions. Meanwhile, newer entrants are focusing on innovative technologies such as AI-powered analytics and blockchain for enhanced transparency and traceability. Geographical growth is largely driven by North America and Europe, given the mature regulatory landscape and strong corporate ESG focus in these regions. However, developing economies in Asia Pacific are poised for significant growth in the coming years as regulations tighten and environmental consciousness increases. The diversification of the market across various application sectors and the continuous innovation in monitoring technologies promise to fuel further market expansion in the coming decade.

The global carbon emission calculation software market is experiencing robust growth, driven by increasing regulatory pressures, heightened corporate sustainability initiatives, and a growing awareness of climate change's impact. The market, currently valued at approximately $2 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 15% from 2025 to 2033, reaching an estimated market size of over $6 billion by 2033. Key drivers include mandatory carbon reporting regulations, the increasing adoption of ESG (Environmental, Social, and Governance) investing strategies, and the rising demand for accurate and efficient carbon footprint measurement across various industries. The power, oil & gas, and chemical industries are significant adopters, utilizing software solutions to track emissions, identify reduction opportunities, and meet compliance requirements. Furthermore, the shift towards cloud-based solutions offers scalability, accessibility, and cost-effectiveness, fueling market expansion. Market segmentation reveals a strong preference for cloud-based software due to its inherent flexibility and ease of integration with existing enterprise systems. Competitive landscape analysis indicates a dynamic market with established players like Sphera and Envizi alongside emerging innovative startups such as Carbon Analytics and BraveGen constantly improving their offerings. Regional analysis shows strong growth across North America and Europe, with Asia-Pacific emerging as a rapidly developing market driven by increasing industrialization and government initiatives. However, challenges such as high initial investment costs and the complexity of integrating software across various business functions present potential restraints to market growth. Despite these restraints, the long-term outlook for the carbon emission calculation software market remains incredibly positive. The increasing urgency for climate action and the evolving regulatory landscape create a compelling environment for sustained growth. The continuous innovation in software capabilities, including the integration of advanced analytics and AI, will further enhance the value proposition for businesses and governments, driving wider adoption. The market is poised for continued expansion, fueled by the growing need for accurate, reliable, and efficient carbon accounting solutions across industries and geographies. This includes expanding adoption in smaller businesses and across various supply chains as businesses seek to measure their full scope 1, 2 and 3 emissions.