Greenhouse Gas Emissions Information for Decision Making

Human-produced contributions to the current warming trend are driven mainly by the well-mixed greenhouse gases (CO₂, CH₄, N₂O, fluorinated gases), which account for about 82% of present-day warming. About 12% of warming comes from non-methane volatile organic compounds (NMVOCs) and carbon monoxide (CO), which can increase concentrations of harmful atmospheric ozone (O₃). About 5% of warming is from black carbon.

The United Nations Framework Convention on Climate Change (UNFCCC) went into force in 1994, establishing the need for GHG emissions information as part of a formal international treaty. GHG emissions information is used to inform GHG policy and mitigation considerations, monitor progress towards commitments, and support the scientific community and public assessment of GHG emissions.

Since the 2015 Paris Agreement, the number of cities, state and regional governments, and private actors pledging and implementing their climate actions has grown. The UNFCCC’s Global Climate Action Portal recorded 11,355 city and 270 regional governments pledging some form of individual climate mitigation pledge or participation in a transnational climate network, such as the Global Covenant of Mayors for Climate and Energy (GCoM), which has nearly 12,000 cities participating as of July 2022.

Over 40% of the world’s 2,000 largest publicly traded companies have committed to net-zero GHG emissions or other climate targets. The success of these commitments rely on accurate GHG inventories and transparent reporting of the progress. Contrasting governments’ geographic focus, this scale places particular emphasis on supply-chain approaches and ownership boundaries. In addition, over 90% of S&P 500 and 80% of the Russell 1000 companies issue corporate environmental, social, and governance reports with GHG reporting as a key performance indicator.

Activity-based approaches (often referred to as “bottom-up” approaches) use data on activities that are drivers of GHG emissions within each system, such as fuel consumption statistics, traffic counts, local air pollution quantities, population, or land area. These activity measures are multiplied by an “operator” or emission factor that represents the emission or removal of a GHG per unit of activity.

Activity-based approaches are most familiar to decision makers—for example, the UNFCCC, national and subnational policymakers, corporations, and the public—and have been most commonly deployed for decision making purposes. A wide range of institutions and researchers have been generating, curating, and disseminating GHG information from these approaches.

View example global and national energy-related emissions inventories.

Atmospheric-based approaches (often referred to as “top-down” approaches) use atmospheric measurements and an understanding of atmospheric transport and chemical processes (in some cases) to infer information on emissions and sinks. A number of different surface-, aircraft-, and space-based measurement techniques are used to gather atmospheric measurements, and a range of analysis approaches transform them to estimates of emissions or removals.

Because many GHG emissions have both human and natural sources (e.g., carbon dioxide and methane), complex analyses are needed to determine human-related contributions. “Mass balance” approaches quantify emissions on urban to regional scales, for example using aircraft to directly measure a plume over a city to infer the city’s emissions. “Isotopic analyses” use radiocarbon measurements to distinguish human-produced and natural emissions. “Inverse modeling” uses atmospheric data in combination with other information, for example the activity-based approaches described above, to infer emissions.

Hybrid approaches generate GHG emissions information through the combination and more complete integration of activity-based and atmospheric-based approaches, and/or other data sources, data assimilation, or emerging digital technologies. Hybrid approaches may take advantage of a range of new or nontraditional data sources combined with machine learning techniques that can efficiently analyze large datasets and derive relationships between activity, infrastructure, and GHG emissions in potentially new ways. Hybrid approaches are nascent and hold the possibility of combining multiple measurement streams, atmospheric-, and activity-based approaches to produce more complete and accurate estimates of GHG emissions and sinks.

The INFLUX Experiment: An Urban Hybrid Approach

Usability and Timeliness [Methods: Medium, Data: Medium]: Although many GHG inventories use the same methodological foundation, the methods and data often require expert knowledge to understand and use. Regarding timeliness, many are not updated regularly and the majority of activity-based GHG inventories have latencies of 2–3 years. Because of the time latency and the requirement of expert knowledge to understand the information, usability of activity-based methods and data is medium.

Information Transparency [Methods: High, Data: Medium]: Information transparency is ranked high for methods because global/national GHG inventories typically have well-defined, transparent, and documented methodologies. This may be lower at smaller scales. However, many data sources are not publicly available or clearly identified so information transparency for data is ranked medium.

Evaluation and validation [Methods: Medium, Data: Low]: At the global level, there is a mix of method evaluation and validation efforts ranging from more internationally-set standards to more limited evaluative practices. Evaluation and validation of input data and data products is limited and inconsistent. Methods is ranked medium and data is ranked low.

Completeness [Methods: Medium, Data: Medium]: There is variation of methodological completeness across gases, sources, and sectors, so completeness of methods is ranked medium. The medium ranking for data is driven by the fact that input data sources are often “sole-source,” not availing of the potential for overlapping data sources or data constraints that exist at more than one space or time scale.

Inclusivity [Methods: Low, Data: Low]: Inclusivity is low for both methods and data. Methodological development as well as input and output information are typically built and gathered by experts. Local scales may offer more opportunities for more inclusive practices.

Communication [Methods: Medium, Data: Medium]: Communication is medium for both methods and data because they span a wide range. Global/national GHG inventory methods and data are typically better communicated to decision makers compared to smaller scales. Overall, communication remains limited and ill-suited to the decision-making community.

Usability and timeliness [Methods: Low, Data: Medium]: Usability of methods and data can be low because of their complexity, coarseness, and lack of specific attribution of emissions sectors. However, data from some approaches are highly usable so usability and timeliness of data is medium due to this variation. Timeliness varies, time lags ranging from at least a year to longer.

Information Transparency [Methods: High, Data: Medium]: Methods are generally well-document so methods is ranked high for information transparency. Input data and estimates are not always provided in published literature so information transparency for data is ranked as medium.

Evaluation and validation [Methods: Medium, Data: High]: Although evaluation and validation is robust, some aspects of methodology are difficult to evaluate. For this reason, evaluation and validation of methods is medium. For data and results, evaluation and validation are strong because observations are typically calibrated and reported following standard practices.

Completeness [Methods: Medium, Data: Medium]: Atmospheric-based approaches are typically comprehensive of all sources and sinks, but incomplete in terms of specifying source sectors. Therefore, methods and data completeness is ranked as medium, because they sense all sources but often with a single gas analysis, limited spatial and temporal information, and difficulty separating sources and sinks.

Inclusivity [Methods: Low, Data: Low]: Inclusivity is low for both methods and data. Generally, there is little input from stakeholders on the methodology and data collection. In some regional and local work, there may be more collaboration but these are typically exceptions to the standard.

Communication [Methods: Low, Data: Medium]: Method communication is low because the primary venue for presentation and discussion of this work is in scientific literature and specialized conferences. They are also documented in technical and complex language. Data communication is medium because data is often communicated in academic literature but some efforts have been effectively communicated to decision makers.

Usability and timeliness [Low]: The low ranking is driven by the fact that this work is still in development in a small community of experts, and demonstration of relevance and usability by decision makers is not well established. The approach has the potential to provide timely data, and if developed with attention to standardization of definitions and units and the key needs of decision makers, it could score very well against this pillar.

Information transparency [Low]: Information transparency is ranked low because it has many of the characteristics of the atmospheric-based approach, with complex methods, the need for expert knowledge, and some limits of access to information and methodologies that are not always well documented.

Evaluation and validation [Medium]: Evaluation and validation was ranked medium, as the hybrid approach should include evaluation and validation as part of the development and peer review of the methods. Some aspects of the approaches may be difficult to evaluate, however. Data products may be compared to other results, although not all products have independent evaluation.

Completeness [Medium]: The integration of data, potentially including atmospheric measurement data, activity data, and ancillary information aims to provide a robust and complete picture, with the potential to rank high. However, it may be challenging to address all gases and sectors with a high degree of data coverage and data constraints.

Inclusivity [Low]: Inclusivity was scored as low, as this work is currently conducted by a small group of experts, with methods that are not uniformly disseminated widely.

Communication [Low]: Communication is ranked low for the current generation of hybrid approaches, given the limited dissemination of results and details. So far, much of this information is in conference proceedings, technical journals, or hard to access reports. Some emerging hybrid approaches could address this pillar at the outset.