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Toward a carbon neutral campus: a scalable approach to estimate carbon storage and biosequestration, an example from University of Michigan

Rebecca Tonietto (Department of Biology, University of Michigan – Flint, Flint, Michigan, USA)
Lara O’Brien (School for Environment and Sustainability, University of Michigan, Ann Arbor, Michigan, USA)
Cyrus Van Haitsma (School for Environment and Sustainability, University of Michigan, Ann Arbor, Michigan, USA)
Chenyang Su (School for Environment and Sustainability, University of Michigan, Ann Arbor, Michigan, USA)
Nicole Blankertz (Department of Biology, University of Michigan – Flint, Flint, Michigan, USA)
Hannah Grace Shaheen Mosiniak (School for Environment and Sustainability, University of Michigan, Ann Arbor, Michigan, USA)
Caleb Short (Department of Biology, University of Michigan – Flint, Flint, Michigan, USA)
Heather Ann Dawson (Department of Biology, University of Michigan – Flint, Flint, Michigan, USA)

International Journal of Sustainability in Higher Education

ISSN: 1467-6370

Article publication date: 10 June 2021

Issue publication date: 16 August 2021

777

Abstract

Purpose

The University of Michigan (U-M) is planning its course toward carbon neutrality. A key component in U-M carbon accounting is the calculation of carbon sinks via estimation of carbon storage and biosequestration on U-M landholdings. Here, this paper aims to compare multiple remote sensing methods across U-M natural lands and urban campuses to determine the accurate and efficient protocol for land assessment and ecosystem service valuation that other institutions may scale as relevant.

Design/methodology/approach

This paper tested three remote sensing methods to determine land use and land cover (LULC), namely, unsupervised classification, supervised classification and supervised classification incorporating delineated wetlands. Using confusion matrices, this paper tested remote sensing approaches to ground-truthed data, the paper obtained via field-based vegetation surveys across a subset of U-M landholdings.

Findings

In natural areas, supervised classification incorporating delineated wetlands was the most accurate and efficient approach. In urban settings, maps incorporating institutional knowledge and campus tree surveys better estimated LULC. Using LULC and literature-based carbon data, this paper estimated that U-M lands store 1.37–3.68 million metric tons of carbon and sequester 45,000–86,000 Mt CO2e/yr, valued at $2.2m–$4.3m annually ($50/metric ton, social cost of carbon).

Originality/value

This paper compared methods to identify an efficient and accurate remote sensing methodology to identify LULC and estimate carbon storage, biosequestration rates and economic values of ecosystem services provided.

Keywords

Acknowledgements

Authors acknowledge U-M President Mark Schlissel and the President’s Commission on Carbon Neutrality (PCCN). The PCCN is also the funding source for works presented here. Authors would specifically like to additionally thank the PCCN project coordinator Lydia Whitbeck and the following without whom this work would not have been possible: U-M Facilities and Operations, especially Andy Berki, Rob Doletzky and Mike Rutkofske in Ann Arbor, Tim Barden and Norm Engel in Flint and Steve Bernard in Dearborn; U-M SEAS property manager Sucila Fernandes for assistance with SEAS properties and for providing tree data for the Ann Arbor campus; and Melissa Starking for Trimble assistance.

Citation

Tonietto, R., O’Brien, L., Van Haitsma, C., Su, C., Blankertz, N., Mosiniak, H.G.S., Short, C. and Dawson, H.A. (2021), "Toward a carbon neutral campus: a scalable approach to estimate carbon storage and biosequestration, an example from University of Michigan", International Journal of Sustainability in Higher Education, Vol. 22 No. 5, pp. 1108-1124. https://doi.org/10.1108/IJSHE-05-2020-0188

Publisher

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Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

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