Missed carbon emissions from forests
Comparing countries’ estimates submitted to UNFCCC to biophysical estimates
Bibliographic Data
| ID | 15548185 |
|---|---|
| Authors | Keiko Nomura (0000-0001-5500-738X, University of Edinburgh, corresponding author), Edward T A Mitchard (0000-0002-5690-4055, University of Edinburgh), Edward TA Mitchard, Samuel Bowers (0000-0001-5418-0359, University of Edinburgh), Samuel J Bowers, Genevieve Patenaude (0000-0001-7552-7470, University of Edinburgh) |
| Year | 2019 |
| Volume | 14 |
| Issue | 2 |
| Pages | 024015-024015 |
| Publication date | 2019-01-08 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Environmental Research Letters (JOURNAL) |
| Journal identifiers | ISSN: 1748-9326 • E-ISSN: 1748-9326 |
| Publisher | IOP Publishing (PUBLISHER • GB) |
| DOI | 10.1088/1748-9326/aafc6b |
| OpenAlex | W2910593843 |
| Language | EN |
| Citations received | 2 |
| References cited | 16 |
Reducing forest loss has the potential to reduce global carbon emissions, but paying countries to do so will only work if activities are targeting areas with rapid deforestation or high threat. As of December 2017, 25 countries reported their benchmark greenhouse gas emissions from forests (‘reference levels’) under the United Nations Framework Convention on Climate Change, with the aim of receiving payments if they end up releasing less or removing more. There remains however a question as to whether the eventual emission trajectories compared to these reference levels represent real emission reductions, as the benchmarks rely on a variety of different methods and limited datasets. To examine whether the forest areas historically associated with significant emissions are targeted in the reference levels, we compared the forest area estimates submitted by seven countries in Asia and the Pacific (Cambodia, Indonesia, Malaysia, Nepal, Papua New Guinea, Sri Lanka, and Vietnam) with forest area estimates using the Global Forest Change v1.4 (GFC) dataset from 2000–2016, processed to closely match national forest definitions. GFC provides standardised tree cover change data based on biophysical characteristics using an extensive collection of satellite images. We found consistent differences, with most countries reporting considerably less forest loss than the GFC-based analysis. These differences are due to the countries’ selection of activities to report, as well as their choice of forest types and land use, defining the forest areas to be monitored. Our study highlights an urgent need to address the gap between the forests monitored by countries and those sources of emissions. The current approaches, even successfully implemented, may not lead to emission reductions, thereby challenging the effectiveness of carbon payments
Carbon stock · Climate change · Deforestation (computer science · Economics · Environmental protection · Environmental resource management · Forest cover · Geography · Greenhouse gas · Illegal logging · Kyoto Protocol · Land use · Land use, land-use change and forestry · Logging · Natural resource economics · Reducing emissions from deforestation and forest degradation · United Nations Framework Convention on Climate Change · Conservation, Biodiversity, and Resource Management · Environmental Science · Forest Management and Policy · Land Use and Ecosystem Services · Ecology · Forestry
Dynamics of Land-Use and Land-Cover Change in Tropical Regions
Carbon emissions from land use and land-cover change
Making better use of accuracy data in land change studies
Challenges in using land use and land cover data for global change studies
Tropical forests are a net carbon source based on aboveground measurements of gain and loss
High-Resolution Global Maps of 21st-Century Forest Cover Change
Quantifying long-term changes in carbon stocks and forest structure from Amazon forest degradation
Redd + research
Brazil submitted the first Redd+ reference level to the UNFCCC—Implications regarding climate effectiveness and cost-efficiency
| Unique citing works | 2 |
|---|---|
| Citations per year | 0.33 |
| Citation span | 2020 - 2022 (3) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 2 |