Editing IPCC:AR6/WGIII/Chapter-2 (section)

== 2.9 Knowledge Gaps ==

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• Global GHG emissions estimates are published less frequently and with greater reporting lags than, for example, CO 2 from fossil fuel and industry. Data quality and reporting frequency remains an issue, particularly in developing countries where the statistical infrastructure is not well developed. Efforts to compile a global GHG emissions inventory by country, sector, and across time, that is annually updated based on the best-available inventory information, similar to ongoing activities for carbon dioxide (CO 2 ), methane (CH 4 ) or nitrous oxide (N 2 O), could fill this gap. Uncertainties and their methodological treatment in GHG emissions estimates are still not comprehensively understood.

'''•''' There is a more fundamental data gap for F-gas emissions, where data quality in global inventories is poor due to considerable gaps in the underlying activity data – particularly in developing countries. Comprehensive tracking of fluorinated gases (F-gas) emissions would also imply the inclusion of other gases not covered under the Paris Agreement, such as chlorofluorocarbons, hydrochlorofluorocarbons and others.

'''•''' Currently, despite advances in terms of data availability, sectoral and spatial resolution, the results in consumption-based emission estimates are dependent on the database used, the level of sectoral aggregation and country resolution. More fine-grained data at spatial resolution as well as the product level would support exploring the mitigation options at the sub-national level, companies and households.

'''•''' Consumption-based emission accounts suffer from lack of quantification of uncertainties at the subnational level and especially in data-scarce environments, such as for developing countries. A better understanding of drivers that caused decoupling of emissions at the national and especially sub-national level are important to explore.

'''•''' Understanding how socio-economic drivers modulate emission mitigation is crucial. Technological improvements (e.g., improved energy or land-use intensity of the economy) have shown a persistent pattern over the last few decades, but gains have been outpaced by increases in affluence (GDP per capita) and population growth, leading to continued emissions growth. Therefore the key gap in knowledge is how these drivers of emissions can be mitigated by demand management, alternative economic models, population control and rapid technological transition to different extents and in different settings. More research on decoupling and sustainability transformations would help to answer these questions. Key knowledge gaps also remain in the role of trade – in particular, how supporting low-carbon technologies in developing and exporting countries can counteract the upward-driving effect of trade, and how to achieve decoupling without outsourcing emissions to others and often to less developed regions.

'''•''' Understanding of how inequality affects emissions is in a nascent stage. Less is known about the causal mechanisms by which different dimensions of inequality – such as income, socio-economic, spatial, socio-cultural-gender and ethnicity – affect emissions. In particular, limited knowledge exists on the linkages between dimensions of inequality other than income or wealth and emissions arising from different service demands. Research gaps are apparent on how inequalities in living standards relate to emissions and how changes in inequalities between genders, social groups, and other marginalised communities impact emissions trends.

'''•''' Digitalisation of the economy is often quoted as providing new mitigation opportunities, but knowledge and evidences are yet limited – such as understanding of the role of smart apps and the potential and influence of disruptive technologies at the demand and supply side on GHG emissions.

'''•''' Despite growing evidence of technological progress across a variety of mitigation areas and the availability of increasingly precise datasets, knowledge gaps remain on technological change and innovation and evidence on speed of transitions to clarify what would make them fast or slow. Innovation is an inherently uncertain process and there will always be imperfect ex ante knowledge on technological outcomes and their effects on mitigation. The extent to which a low-carbon transition can proceed faster than historical examples is crucial to aid future mitigation. That depends on a better understanding of the speed of building, updating and replacing infrastructure. Additionally, how and whether financing for low-carbon technology investment in low- and middle-income countries can be delivered at low-cost and sustained over time are important questions. The emerging findings that small-scale technologies learn faster and are adopted more quickly need to be tested against a broader set of cases, and in particular against the large dispersion in data.

'''•''' Future CO 2 emissions from existing and planned infrastructure is not well understood and quantified outside the power sector. Further integration of bottom-up accounting and scenario approaches from integrated assessment seems promising. Comprehensive assessments of hard-to-abate residual fossil fuel emissions and their relationship to CO 2 removal activities are lacking, but will be important for informing net-zero emissions strategies.

'''•''' Empirical evidence of emission impacts from climate policies, including carbon pricing, is not sufficient for unambiguous attribution assessment, mainly due to the limited experience with climate-related policy experiments to date. More attention to the methodology for comprehensive evaluation of climate policies and measures, such as effective carbon rates is apparent. Key knowledge gaps also exist on ex-post evaluations of climate and non-climate policies and measures for their impact on emissions, particularly at the global scale, considering national circumstances and priorities.

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