Measure-and-remeasure as an economically feasible approach to crediting soil organic carbon at scale
Agricultural carbon crediting predominantly relies on process-based biogeochemical models to estimate accrual of soil organic carbon stock (SOC). We investigate the conditions under which it may be economical to estimate SOC accrual by measuring and remeasuring SOC, which relies on fewer assumptions...
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IOP Publishing
2025-01-01
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| Series: | Environmental Research Letters |
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| Online Access: | https://doi.org/10.1088/1748-9326/ada16c |
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| author | Eric Potash Mark A Bradford Emily E Oldfield Kaiyu Guan |
| author_facet | Eric Potash Mark A Bradford Emily E Oldfield Kaiyu Guan |
| author_sort | Eric Potash |
| collection | DOAJ |
| description | Agricultural carbon crediting predominantly relies on process-based biogeochemical models to estimate accrual of soil organic carbon stock (SOC). We investigate the conditions under which it may be economical to estimate SOC accrual by measuring and remeasuring SOC, which relies on fewer assumptions than modeling. We analyze multi-field measure-and-remeasure SOC projects with two key features: first, practice assignment is randomized to compare the effect of a treatment (e.g. no tillage) to a control (e.g. conventional tillage); second, a random subset of fields is sampled (two stage cluster sampling) to cost-effectively measure SOC changes. We use statistical modeling to characterize the estimated treatment effect, accounting for within-field and between-field variability in SOC change, as well as measurement error. We then use these statistics to evaluate how prices for measurement, treatment, and carbon credits influence the economics of measure-and-remeasure projects. We specifically investigate the potential advantages of larger spatial scale (number of fields) and temporal scale (years before remeasurement). We find economies of both spatial and temporal scale so that projects with thousands of fields, with only about 10% of fields measured for SOC change, are likely to yield a competitive return on investment in five years if the treatment effects found in the research literature can be achieved commercially. Our analysis suggests that measure-and-remeasure can be cost effective in both market and non-market SOC projects at scale. Moreover, measure-and-remeasure projects provide valuable data for independent validation on commercial farms of the accrual rates estimated by biogeochemical models using field trials. We provide next steps and software for researchers, credit registries, and project developers to move forward with measure-and-remeasure SOC projects. |
| format | Article |
| id | doaj-art-286f368a3b074ea7aeb396ca8bd4f2b5 |
| institution | Kabale University |
| issn | 1748-9326 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IOP Publishing |
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| series | Environmental Research Letters |
| spelling | doaj-art-286f368a3b074ea7aeb396ca8bd4f2b52025-01-17T08:57:00ZengIOP PublishingEnvironmental Research Letters1748-93262025-01-0120202402510.1088/1748-9326/ada16cMeasure-and-remeasure as an economically feasible approach to crediting soil organic carbon at scaleEric Potash0https://orcid.org/0000-0003-4658-9802Mark A Bradford1https://orcid.org/0000-0002-2022-8331Emily E Oldfield2https://orcid.org/0000-0002-6181-1267Kaiyu Guan3https://orcid.org/0000-0002-3499-6382Agroecosystem Sustainability Center, Institute for Sustainability, Energy, and Environment, University of Illinois Urbana-Champaign , Urbana, IL 61801, United States of America; Department of Natural Resources and Environmental Sciences, College of Agricultural, Consumer and Environmental Sciences, University of Illinois Urbana Champaign , Urbana, IL 61801, United States of AmericaThe Forest School, Yale School of the Environment, Yale University , New Haven, CT 06511, United States of America; Yale Center for Natural Carbon Capture, Yale University , New Haven, CT 06511, United States of AmericaThe Forest School, Yale School of the Environment, Yale University , New Haven, CT 06511, United States of America; Environmental Defense Fund , New York, NY, United States of AmericaAgroecosystem Sustainability Center, Institute for Sustainability, Energy, and Environment, University of Illinois Urbana-Champaign , Urbana, IL 61801, United States of America; Department of Natural Resources and Environmental Sciences, College of Agricultural, Consumer and Environmental Sciences, University of Illinois Urbana Champaign , Urbana, IL 61801, United States of AmericaAgricultural carbon crediting predominantly relies on process-based biogeochemical models to estimate accrual of soil organic carbon stock (SOC). We investigate the conditions under which it may be economical to estimate SOC accrual by measuring and remeasuring SOC, which relies on fewer assumptions than modeling. We analyze multi-field measure-and-remeasure SOC projects with two key features: first, practice assignment is randomized to compare the effect of a treatment (e.g. no tillage) to a control (e.g. conventional tillage); second, a random subset of fields is sampled (two stage cluster sampling) to cost-effectively measure SOC changes. We use statistical modeling to characterize the estimated treatment effect, accounting for within-field and between-field variability in SOC change, as well as measurement error. We then use these statistics to evaluate how prices for measurement, treatment, and carbon credits influence the economics of measure-and-remeasure projects. We specifically investigate the potential advantages of larger spatial scale (number of fields) and temporal scale (years before remeasurement). We find economies of both spatial and temporal scale so that projects with thousands of fields, with only about 10% of fields measured for SOC change, are likely to yield a competitive return on investment in five years if the treatment effects found in the research literature can be achieved commercially. Our analysis suggests that measure-and-remeasure can be cost effective in both market and non-market SOC projects at scale. Moreover, measure-and-remeasure projects provide valuable data for independent validation on commercial farms of the accrual rates estimated by biogeochemical models using field trials. We provide next steps and software for researchers, credit registries, and project developers to move forward with measure-and-remeasure SOC projects.https://doi.org/10.1088/1748-9326/ada16ccarbon marketsnatural climate solutionscausal inferenceclimate smart agriculturesoil organic carbon |
| spellingShingle | Eric Potash Mark A Bradford Emily E Oldfield Kaiyu Guan Measure-and-remeasure as an economically feasible approach to crediting soil organic carbon at scale Environmental Research Letters carbon markets natural climate solutions causal inference climate smart agriculture soil organic carbon |
| title | Measure-and-remeasure as an economically feasible approach to crediting soil organic carbon at scale |
| title_full | Measure-and-remeasure as an economically feasible approach to crediting soil organic carbon at scale |
| title_fullStr | Measure-and-remeasure as an economically feasible approach to crediting soil organic carbon at scale |
| title_full_unstemmed | Measure-and-remeasure as an economically feasible approach to crediting soil organic carbon at scale |
| title_short | Measure-and-remeasure as an economically feasible approach to crediting soil organic carbon at scale |
| title_sort | measure and remeasure as an economically feasible approach to crediting soil organic carbon at scale |
| topic | carbon markets natural climate solutions causal inference climate smart agriculture soil organic carbon |
| url | https://doi.org/10.1088/1748-9326/ada16c |
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