Direct measurement forest carbon protocol: a commercial system-of-systems to incentivize forest restoration and management

Autor: Vinh Truong, J. William Munger, Bruno D.V. Marino, Richard Gyimah
Jazyk: angličtina
Rok vydání: 2020
Předmět:
Clean development mechanism
010504 meteorology & atmospheric sciences
Ankasa park ghana
lcsh:Medicine
Forest carbon trading
010501 environmental sciences
Carbon sequestration
Ecosystem Science
01 natural sciences
General Biochemistry
Genetics and Molecular Biology

Forest restoration
Clean Development Mechanism
Deforestation
Revenue
Climate action reserve
0105 earth and related environmental sciences
Biosphere Interactions
business.industry
General Neuroscience
lcsh:R
Global warming
Environmental resource management
Forest net ecosystem exchange
Forestry
General Medicine
Coupled Natural and Human Systems
Greenhouse gas
Forest carbon quantification
Climate Change Biology
Environmental science
Harvard forest
Paris agreement
Kyoto Protocol
General Agricultural and Biological Sciences
business
REDD+
Zdroj: PeerJ
PeerJ, Vol 8, p e8891 (2020)
ISSN: 2167-8359
Popis: Forest carbon sequestration offsets are methodologically uncertain, comprise a minor component of carbon markets and do not effectively slow deforestation. The objective of this study is to describe a commercial scale in situ measurement approach for determination of net forest carbon sequestration projects, the Direct Measurement Forest Carbon Protocol™, to address forest carbon market uncertainties. In contrast to protocols that rely on limited forest mensuration, growth simulation and exclusion of CO2 data, the Direct Measurement Forest Carbon Protocol™ is based on standardized methods for direct determination of net ecosystem exchange (NEE) of CO2 employing eddy covariance, a meteorological approach integrating forest carbon fluxes. NEE is used here as the basis for quantifying the first of its kind carbon financial products. The DMFCP differentiates physical, project and financial carbon within a System-of-Systems™ (SoS) network architecture. SoS sensor nodes, the Global Monitoring Platform™ (GMP), housing analyzers for CO2 isotopologues (e.g., 12CO2,13CO2, 14CO2) and greenhouse gases are deployed across the project landscape. The SoS standardizes and automates GMP measurement, uncertainty and reporting functions creating diverse forest carbon portfolios while reducing cost and investment risk in alignment with modern portfolio theory. To illustrate SoS field deployment and operation, published annual NEE data for a tropical (Ankasa Park, Ghana, Africa) and a deciduous forest (Harvard Forest, Petersham, MA, USA) are used to forecast carbon revenue. Carbon pricing scenarios are combined with historical in situ NEE annual time-series to extrapolate pre-tax revenue for each project applied to 100,000 acres (40,469 hectares) of surrounding land. Based on carbon pricing of $5 to $36 per ton CO2 equivalent (tCO2eq) and observed NEE sequestration rates of 0.48 to 15.60 tCO2eq acre−1 yr−1, pre-tax cash flows ranging from $230,000 to $16,380,000 across project time-series are calculated, up to 5× revenue for contemporary voluntary offsets, demonstrating new economic incentives to reverse deforestation. The SoS concept of operation and architecture, with engineering development, can be extended to diverse gas species across terrestrial, aquatic and oceanic ecosystems, harmonizing voluntary and compliance market products worldwide to assist in the management of global warming. The Direct Measurement Forest Carbon Protocol reduces risk of invalidation intrinsic to estimation-based protocols such as the Climate Action Reserve and the Clean Development Mechanism that do not observe molecular CO2 to calibrate financial products. Multinational policy applications such as the Paris Agreement and the United Nations Reducing Emissions from Deforestation and Degradation, constrained by Kyoto Protocol era processes, will benefit from NEE measurement avoiding unsupported claims of emission reduction, fraud, and forest conservation policy failure.
Databáze: OpenAIRE