Errors and uncertainties in a gridded carbon dioxide emissions inventory

• Published in: Mitigation and adaptation strategies for global change Vol. 24; no. 6; pp. 1007 - 1050
• Main Authors: Oda, Tomohiro, Bun, Rostyslav, Kinakh, Vitaliy, Topylko, Petro, Halushchak, Mariia, Marland, Gregg, Lauvaux, Thomas, Jonas, Matthias, Maksyutov, Shamil, Nahorski, Zbigniew, Lesiv, Myroslava, Danylo, Olha, Horabik-Pyzel, Joanna
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.08.2019; Springer Nature B.V; Springer Verlag
• Subjects: Anthropogenic factors; Atmospheric models; Atmospheric Sciences; Best practices; Capacity development; Carbon dioxide; Carbon dioxide emissions; Carbon footprint; cities; climate; Climate change; Climate Change Management and Policy; Climate change mitigation; Climate models; compliance; Continental interfaces, environment; Disaggregation; Earth and Environmental Science; Earth Sciences; Emission analysis; Emission inventories; Emissions; Emissions control; Environmental Management; Errors; Estimates; Fossil fuels; Greenhouse effect; greenhouse gas emissions; Greenhouse gases; Guidelines; International organizations; inventories; Mitigation; Modelling; monitoring; Ocean, Atmosphere; Original Article; Paris Agreement; Poland; Pollution monitoring; Resolution; Rural areas; Sciences of the Universe; spatial data; Uncertainty; United Nations Framework Convention on Climate Change; United States; Urban areas; Urban policy; Poland; United States; Emission inventory; Carbon cycle; Climate mitigation; Greenhouse gas emission; Paris Agreement; Reporting and verification; Carbon dioxide; Uncertainty analysis; Remote sensing; Monitoring
• DOI: 10.1007/s11027-019-09877-2
• ISSN: 1381-2386

Emission inventories (EIs) are the fundamental tool to monitor compliance with greenhouse gas (GHG) emissions and emission reduction commitments. Inventory accounting guidelines provide the best practices to help EI compilers across different countries and regions make comparable, national emission estimates regardless of differences in data availability. However, there are a variety of sources of error and uncertainty that originate beyond what the inventory guidelines can define. Spatially explicit EIs, which are a key product for atmospheric modeling applications, are often developed for research purposes and there are no specific guidelines to achieve spatial emission estimates. The errors and uncertainties associated with the spatial estimates are unique to the approaches employed and are often difficult to assess. This study compares the global, high-resolution (1 km), fossil fuel, carbon dioxide (CO 2 ), gridded EI Open-source Data Inventory for Anthropogenic CO 2 (ODIAC) with the multi-resolution, spatially explicit bottom-up EI geoinformation technologies, spatio-temporal approaches, and full carbon account for improving the accuracy of GHG inventories (GESAPU) over the domain of Poland. By taking full advantage of the data granularity that bottom-up EI offers, this study characterized the potential biases in spatial disaggregation by emission sector (point and non-point emissions) across different scales (national, subnational/regional, and urban policy-relevant scales) and identified the root causes. While two EIs are in agreement in total and sectoral emissions (2.2% for the total emissions), the emission spatial patterns showed large differences (10~100% relative differences at 1 km) especially at the urban-rural transitioning areas (90–100%). We however found that the agreement of emissions over urban areas is surprisingly good compared with the estimates previously reported for US cities. This paper also discusses the use of spatially explicit EIs for climate mitigation applications beyond the common use in atmospheric modeling. We conclude with a discussion of current and future challenges of EIs in support of successful implementation of GHG emission monitoring and mitigation activity under the Paris Climate Agreement from the United Nations Framework Convention on Climate Change (UNFCCC) 21st Conference of the Parties (COP21). We highlight the importance of capacity building for EI development and coordinated research efforts of EI, atmospheric observations, and modeling to overcome the challenges.