University of Maryland's Campus Forest Carbon Project
Including campus forest carbon estimates in UMD climate mitigation planning
Including Forest Carbon in Climate Action Efforts at the University of Maryland
Funded by the UMD Office of Sustainability with support from Dr. Rachel Lamb and Dr. George Hurtt from the UMD Department of Geographical Sciences
Figure 1. UMD's GHG inventory from 2005-2020, including the percentage of emission sources by category.
Forest carbon sequestration is the total quantity of carbon annually removed from the atmosphere and stored within plant biomass (roots, trunks, branches, leaves) and soils. Currently, in the annual greenhouse gas (GHG) inventory, the University of Maryland (UMD) voluntarily reports a fixed estimate of sequestered forest carbon. Due to concerns about accuracy, these estimates are not formally counted toward the university’s GHG emissions reduction goals.
UMD forests are largely excluded from climate action planning...
The UMD Campus Forest Carbon Project aims to address this science gap by including annual estimates of forest carbon into the campus' carbon footprint by leveraging high-resolution NASA Carbon Monitoring System (CMS) science . These methods also position UMD for leadership on forest carbon as a signatory to Second Nature's Presidents' Climate Leadership Commitments .
Monitoring Annual Forest Carbon Change
The project estimated and mapped annual changes in forest carbon on UMD-owned and managed properties between 2011-2020.
This project quantifies and tracks changes in aboveground biomass (AGB), which is the amount of living plant matter above the soil, comprising at least 50% carbon. The foundational AGB dataset used for this initiative employs high-resolution remote sensing data and dynamic ecosystem modeling to produce 90-meter estimates of carbon stocks. Annual AGB estimates are based on the continued growth of existing trees, as detected by Lidar remote sensing in the base year of 2011, plus subsequent loss or gain of tree area as detected by Landsat-derived remote sensing data. Here, carbon stocks are calculated for the main UMD campus and auxiliary properties that are owned or managed by the University. Annual forest monitoring can help the University quantify carbon flux, which is the net gain in forest carbon after accounting for the carbon lost due to its release into the atmosphere from deforestation or disturbances. If more carbon is released (or lost) than gained in a given year the UMD properties are classified as a carbon source. When more carbon is stored than lost, the properties are considered a carbon sink.
AGB is measured in kilograms of carbon per meter squared (kg C/m2), where yellow signifies lower and blue signifies higher areas of annual AGB growth as shown in the legend above. Figure 2 highlights how the growth rate in each 90m pixel has changed between 2012 and 2020. In most cases, the campus has experienced an increase in growth rates between the two periods, as indicated by the increase in green pixels.
Figure 2. Comparison of yearly net AGB change for UMD-managed and owned properties in 2012 and 2020. Click on different regions on the map to see the specific flux value. Use the slider to compare flux between the two sets of years and zoom into the UMD campus and associated AGNR properties. Use the plus symbol to zoom in to show specific pixels and locations and the minus symbol to zoom out to reveal values for the whole state of Maryland.
Remaining Carbon Sequestration Potential
This project also calculated future forest carbon estimates for potential reforestation areas around campus.
The carbon sequestration potential gap (CSPG) dataset estimates the remaining amount of carbon that could be sequestered by existing and newly planted trees.
Estimates of projected forest carbon growth across space are valuable for determining strategic reforestation areas.
CSPG is measured in kilograms of carbon per square meter of land (Mg C/ha). The legend above reveals that having higher potential pixels (areas closer to blue than to yellow) means that these areas are able to hold more carbon in the future and could be target areas for tree planting in support of campus climate mitigation goals.
CSPG
Regrowth by 2050
Using projected estimates of aboveground biomass growth, we can also quantify exactly how much carbon we can sequester in any given area by a specific date.
In the context of a net-zero emissions goal, we can quantify how much of the CSPG can be realized over campus by 2050.
Figure 4. 2012 vs 2050 carbon stock estimates for UMD-managed and -owned properties excluding impervious surfaces. Click on areas to see specific carbon stock values and use the slider to compare changes between the two years. Use the plus symbol to zoom in to show specific pixels and locations and the minus symbol to zoom out to reveal values for the whole state of Maryland.
Learn more...
Click here to learn more about the Campus Forest Carbon Project.
Read more about the undergraduate researchers behind the work here .
This project uses products from NASA's Carbon Monitoring System (CMS). Learn more about NASA CMS here.
UMD is a signatory of Second Nature's Presidents' Climate Leadership Commitments. Learn more about the President's Climate Leadership Commitments here .
References:
- Hurtt, G., Zhao, M., Sahajpal, R., Armstrong, A., Birdsey, R., Campbell, E., ... & Tang, H. (2019). Beyond MRV: high-resolution forest carbon modeling for climate mitigation planning over Maryland, USA. Environmental Research Letters, 14(4), 045013. doi: 10.1088/1748-9326/ab0bbe
- Ma, L., Hurtt, G., Tang, H., Lamb, R., Campbell, E., Dubayah, R., ... & Silva, C. (2021). High-resolution forest carbon modelling for climate mitigation planning over the RGGI region, USA. Environmental Research Letters, 16(4), 045014. doi: 10.1088/1748-9326/abe4f4
- Tang, H., Ma, L., Lister, A., O’Neill-Dunne, J., Lu, J., Lamb, R. L., ... & Hurtt, G. (2021). High-resolution forest carbon mapping for climate mitigation baselines over the RGGI region, USA. Environmental Research Letters, 16(3), 035011. doi: 10.1088/1748-9326/abd2ef
