Air quality monitoring to machine learning: Fund for Climate Solutions awards six new grants
The second round of 2024 Fund for Climate Solutions (FCS) awardees has been announced. The FCS advances innovative, solutions-oriented climate science through a competitive, internal, and cross-disciplinary funding process. Generous donor support has enabled us to raise more than $10 million towards the FCS, funding 69 research grants since 2018. The latest cohort of grantees includes three projects focused on driving impact through collaboration and community-building, and three projects exploring new horizons in technology with timely policy relevance.
Arctic wildfire pollutants: Towards improving emissions estimates and developing tribally-led monitoring
Lead: Scott Zolkos
Collaborators: Brendan Rogers, Sue Natali, Kyle Arndt, Elise Sunderland (Harvard University)
Increasing wildfire activity in northern high-latitude regions is threatening global climate goals and public health. When organic matter in soils and vegetation burns, greenhouse gasses, fine particulates (PM2.5), and contaminants including mercury are released to the environment. Currently, there is sparse data for understanding how wildfires contribute to the northern mercury cycle, as well as gaps in infrastructure for monitoring PM2.5 in Alaska Native communities. This project will develop a network to measure and monitor the release of mercury and PM2.5 from wildfire, with an emphasis on peatlands. Leveraging ongoing work by Permafrost Pathways, the team will install mercury sampling equipment on existing eddy covariance flux towers across Alaska and Canada. Alongside Permafrost Pathways and their tribal partners, the team will also consult with Alaska Native communities in the Yukon-Kuskokwim Delta to co-develop a tribally-led air quality monitoring program.
Workshop: Innovative sensors and applications in environmental research
Lead: Kathleen Savage
Collaborators: Zoë Dietrich, Marcia Macedo
Many of the Woods Hole science community’s cutting-edge researchers, including several scientists at Woodwell Climate, are developing creative, do-it-yourself (DIY) tools using relatively simple components to further explore their research questions. However, despite the six institutions’ similar applications and geographic proximity, there are few opportunities for exchange and knowledge, both across Woods Hole institutions and more broadly with Cape Cod educational institutions. The project team will convene a one-day workshop to bring together aquatic, atmospheric, and terrestrial science researchers and educators from the Woods Hole science community and local community colleges. The event will focus on three main themes: development of new sensor systems that use existing technologies in novel ways; new data storage or transmission solutions; and community initiatives to facilitate continued creation and sharing of new technologies. Sessions will foster knowledge exchange, build networks, and develop community resources focused on innovative DIY research solutions, and a hybrid virtual option will be offered for oral presentations to broaden participation.
Soil Spectroscopy for Global Good network
Lead: José Lucas Safanelli
Collaborators: Jonathan Sanderman
The Soil Spectroscopy for Global Good (SS4GG) initiative is a collaborative network of hundreds of soil scientists and others focused on using soil spectroscopy as a means to generate high-quality soil data at significantly reduced costs. It was created in 2020 by the Woodwell Climate Research Center, the University of Florida, and the OpenGeoHub Foundation (the Netherlands) with support from many national and international institutions and researchers. SS4GG created and supports the Open Soil Spectral Library (OSSL), an open source of soil spectroscopy data, and a broad community of practitioners uses the library and collaborates on related science. This award will extend the activities of the SS4GG initiative with a focus on training and further engagement with the soil science community. The project team will continue to add data sets and new models to the OSSL, as well as engage with the soil science community by attending international conferences and providing a training workshop. The funds will also support hosting a visiting soil biogeochemist at the Woodwell Climate campus—Dr. Raj Setia from the Punjab Remote Sensing Center.
Pathways of carbon metabolism under cover crops
Lead: Taniya RoyChowdhury
Collaborator: Jonathan Sanderman
Sequestering, or capturing carbon in soils has a high potential to mitigate climate change. It is challenging to specifically predict how successful carbon sequestration may be, as current models used to evaluate agronomic management oversimplify soil microbial properties. This project will test for the key pathways of carbon transformations using soil samples taken under cover crops from a long-term study site. The team will quantify the chemical diversity of carbon substrates that microbes in the soil take up, and use data mining to predict the impacts of that diversity on soil carbon sequestration and nutrient cycling. The research outcomes will also lay a foundation for future collaborative research within the Department of Energy scientific community, and the soil health research community more broadly.
Bringing confidence to carbon markets through improved monitoring
Lead: Seth Gorelik
Collaborator: Wayne Walker
The protection, improved management, and restoration of forests are key nature-based solutions to the climate crisis, yet implementation and maintenance of these forest-based solutions requires sustainable and substantial financing. The voluntary carbon market (VCM) has the potential to deliver the necessary level of financing; however, a significant gap exists between its potential and actual performance. Improving the accuracy of forest carbon monitoring is crucial for the VCM to deliver effective, meaningful climate change mitigation. This project will enhance the credibility and effectiveness of forest carbon markets by evaluating new remote sensing methods for measuring forest carbon and showing that these methods provide more robust data than the conventional approach. Research findings could lead to updated global standards and policies for issuing carbon credits, which would increase market confidence and promote sustainable forest management.
Applying machine learning models to link river hydrology and fire risk forecasting in the Amazon
Lead: Andrea D. de Almeida Castanho
Collaborators: Michael Coe, Marcia Macedo
In recent decades, extreme drought events have increased forest flammability, fire severity, and the likelihood of fire escaping and spreading into adjacent forests and working lands, as illustrated by the wildfires seen throughout Amazonia during the 2023-24 drought. The project team will explore the potential of using river stage (water level) data as a proxy for landscape dryness, to ultimately reveal the short-term risk of wildfires spreading into forests. If confirmed, this innovative hypothesis could provide the scientific basis for developing new metrics of river stage to improve early-warning systems that forecast high fire risk days to weeks in advance. These improvements would create benefits not only for tropical forest protection, but also for biodiversity, greenhouse gas emissions, and human health.
Fund for Climate Solutions awards five new grants
From the Arctic to the Tropics, the 2024 winter cohort of FCS projects fills information gaps to produce actionable insights
Quantifying large greenhouse gas emissions from a retrogressive thaw slump in Alaska
Lead: Jennifer Watts
Collaborators: Kyle Arndt, Patrick Murphy
Retrogressive thaw slumps (RTS) are extreme permafrost thaw landscape features, which occur when a section of ice-rich permafrost becomes warm enough to cause the ground ice to melt and soils to collapse. Once they start, RTS continue to expand and destroy nearby permafrost for months to years. Many RTS have been identified, but because they are often in extremely remote arctic locations, very little is known about the potentially substantial carbon emissions from RTS in the form of carbon dioxide and methane. This study will provide the first continuous measurements of carbon emissions from a RTS, collected over at least a year via an eddy covariance tower. The research is also supported by an equipment loan provided through the U.S. Department of Energy AmeriFlux Rapid Response program, which recognized this project as a valuable opportunity to advance science. The data collected will also serve as a “proof of concept” for a subsequent $1.3M proposal to the National Science Foundation for continued research at the site.
Assessing the impacts of ecosystem disturbance on carbon emissions from Arctic and Amazon ponds
Lead: Elchin Jafarov
Collaborators: Zoë Dietrich, Andrew Mullen, Jackie Hung, Marcia Macedo, Kathleen Savage
Freshwater ecosystems are significant sources of the greenhouse gases that persist in the atmosphere and contribute to warming. However, research is lacking an understanding of how disturbances like wildfire and agriculture can change these emissions. This project will address these information gaps by collecting measurements of carbon emissions from ponds, using autonomous floating chambers developed with funding from a previous FCS grant. With this new high-resolution data, the team will unlock the ability to predict year-round greenhouse gas emissions from ponds in the Arctic and the Amazon. Floating chambers will be deployed in ponds in Alaska affected by wildfires, and in agricultural reservoirs in the Amazon-Cerrado frontier. In both locations, the ability to take more frequent measurements of carbon emissions will help researchers improve models and better assess the ponds’ impacts on regional carbon budgets.
The Polaris Project: Data synthesis from almost two decades of research and student participation
Lead: Nigel Golden
Collaborator: Sue Natali
Established in 2008, the Polaris Project has earned global recognition for its leadership in Arctic research, education, and outreach. Through the commitment to providing students with hands-on experience, Polaris has enabled numerous publications and presentations. Polaris is approaching a critical juncture in the next funding cycle, and this project will complete the first-ever comprehensive synthesis of Polaris Project research to help sustain Woodwell Climate’s sole undergraduate research program. By consolidating past research and educational achievements, the team will create a data synthesis paper to be submitted to a peer-reviewed, open-access scientific research journal, as well as a retrospective analysis of undergraduates’ research experiences with Polaris to be submitted to an education research journal. The team will also launch an online communications piece that documents past Polaris participants’ field experiences and unique journeys with a variety of narrative and artistic communications styles and elements.
Determining the climate sensitivity of coastal rivers to guide ecosystem restoration across SE Massachusetts
Lead: Abra Atwood
Collaborators: Marcia Macedo, Chris Neill, Linda Deegan, Scott Zolkos
Coastal rivers, like those that flow into Massachusetts’ Buzzards Bay and Vineyard Sound, are fragile environments that serve critical ecological functions for native fish, downstream estuaries, and coastal wetlands. Different rivers are uniquely sensitive to changes in air temperature based on a variety of characteristics, such as their water source or shade. However, land use changes, including housing development and cranberry bogs, have affected key river characteristics and stream temperatures. This project will investigate MA coastal rivers’ sensitivity to changing air temperature, as well as how that sensitivity is affected by both connection to groundwater and the creation or restoration of cranberry bogs. The temperature sensors and geochemical analyses used in this research may be scalable beyond these rivers and yield insights to inform research approaches relevant to rivers around the world.
A drought early warning system for the DRC: Developing a seasonal forecast based on novel machine learning approaches
Lead: Carlos Dobler-Morales
Collaborators: Christopher Schwalm, Glenn Bush
Seasonal weather forecasts hold immense potential to improve risk management from agricultural failure, water stress, and extreme events. However, significant advances in technical forecasting capabilities remain largely unavailable to communities without the resources to develop or customize them for their region. In 2023, Woodwell Climate Just Access co-produced a national climate risk assessment with the Democratic Republic of Congo’s Ministry of Environment and Sustainable Development. That report identified drought as a major climate threat to the DRC—one which stands to affect almost the entire country. In response, this project will develop a seasonal drought forecasting model tailored to the DRC using cutting-edge machine-learning methods. The forecast will be able to deliver precise rainfall anomaly predictions up to six months in advance for the whole country, and serve as an early warning system to help local people and decision-makers anticipate the impacts of escalating drought risk.
Learn more about the Fund for Climate Solutions.