David Bastviken

Air pollution is one of the largest risk factors for premature death, yet current portable monitoring technology could not provide adequate protection at a local community level. TRIAGE aimed to develop a smart, compact, and cost-effective air quality sensor network for the hyperspectral detection of relevant atmospheric pollution gases. Tema M, Linköping University, tested the developed devices in environmental settings.

This project was a collaboration among nine university and company partners. The Technical University of Denmark was the host institution. For more information, please see the TRIAGE project's webpage.

Funding: EU, Horizon 2020

The United Nations Paris climate agreement of 2015 profoundly changed how societies need to assess and manage greenhouse gas (GHG) emissions. Extensive human land use and climate feedbacks undermined attempts to separate anthropogenic and natural GHG fluxes. Land-use-related, non-carbon dioxide emissions already accounted for 30-50% of the global warming potential emitted yearly. The shift to a temperature target therefore meant that all landscape emissions affecting temperatures needed consideration. The Paris Agreement also included obligations to verify that efforts to reduce emissions were effective. The methodology based on aggregated emission factors determined by the IPCC was highly uncertain for land-use related GHG fluxes and clearly not suitable for verifying local mitigation efforts. It was unclear what methods were available for societies to meet the new needs for more accurate GHG assessments, and how societies could establish capacity to verify GHG mitigation efforts.

This synthesis project (1) surveyed what methods for GHG assessments were available for society, (2) evaluated how well these methods matched the new knowledge needs, (3) assessed what new GHG-related methods were under development and how they could serve society, and (4) recommended what new development of methods/approaches were needed and how to establish necessary measurement capacity to effectively reach climate goals. This was critical to enable informed decisions and priorities to reach the climate goals.

Funding: Formas

Tema M contact: David Bastviken, Alex Enrich Prast, Magnus Gålfalk, Martin Karlson, Tina Neset, Julie Wilk

Our ability to understand, predict, mitigate, and adapt to climate change depends on reliable means to measure greenhouse gas (GHG) fluxes. The recent global temperature targets made this even more important as both anthropogenic and natural fluxes of all GHGs affect temperatures. However, our present knowledge was highly biased because we lacked methods to efficiently assess spatio-temporal variability across landscapes. This variability was critical due to the importance of hot-spot or hot-moment fluxes, and new GHG measurement methods were urgently needed. This project introduced such methods, including flux mapping by sensor networks and hyperspectral imaging. The first large-scale tests of these methods were made in aquatic environments, which were relevant as highly challenging test environments and as some of the largest but also most uncertain natural net GHG fluxes.

This project was a collaboration among Linköping University (host institution), Stockholm University, and Gothenburg University.

Funding: Swedish Reserach Council, VR

Environmental objectives are often detected at large scales while the local processes creating the problems were too expensive to map by measurements. The environmental objective Reduced Climate Impact was such an example, being described from global or regional measurements while mitigation efforts needed to have local targets. It was desirable to optimize local processes or activities to minimize greenhouse gas (GHG, including carbon dioxide, methane, and nitrous oxide) emissions while minimizing negative impacts on other goals. Unfortunately, it was too expensive to measure GHGs locally, and mitigation efforts were blind and could not be evaluated. The willingness to invest in GHG mitigation measures with unknown efficiency was obviously limited, and the lack of affordable GHG measurement capacity thereby hampered progress.

In this project, we developed small, low-power, and cost-efficient GHG sensors for all three mentioned GHGs, for use in sensor networks in all types of environments, to e.g., map sources and sinks in space and time, allow process and activity optimization, and evaluate mitigation efforts.

The project was a collaboration between SenseAir, NEP-Norrtelje Elektronikpartner, and the Department of Thematic Studies – Environmental Change, Linköping University, Sweden, with funding from VINNOVA.

Methane (CH₄) is one of the most important greenhouse gases, with many unresolved questions regarding sources and sinks. The project aimed to develop a camera to visualise CH₄ concentrations in the landscape. This enabled the identification of both natural and anthropogenic CH₄ sources in a new way with high resolution, while also rapidly covering large areas. Patterns over time could also be uniquely identified by allowing the camera to continuously record images.

The project combined knowledge from the fields of methane biogeochemistry and remote trace gas detection from astronomy. The grant financed a custom-made camera using a technique based on hyperspectral IR imaging by Fourier transform spectroscopy. The camera opened possibilities to survey different CH₄ sources/sinks, both man-made and natural, using a single technique that made it easier to directly compare the influence of very different types of environments/activities on the amounts of CH₄ in the atmosphere. This was important for improving predictions of future climate and for finding information about how CH₄ emissions could best be managed.

Funding: Knut and Alice Wallenberg Foundation

nland fresh waters play important roles in carbon cycling and emission of greenhouse gases (GHG). Data were limited, however, and current estimates were very uncertain. Developing better measurement techniques was crucial. This project engaged researchers in Sweden, Finland, Russia, and the USA to better understand energy and GHG budgets in lake ecosystems at high latitudes, which are potentially sensitive to ongoing and future climate changes.

In the last two decades, the important role of inland fresh waters (lakes, rivers, reservoirs, ponds) in processing large amounts of organic carbon and emitting greenhouse gases has been recognised. However, measurements of lake GHG emissions were limited, and current estimates were very uncertain, because they were mostly based on indirect methods and short-term field measurements. At the time, a comprehensive, continuous, and long-term lake energy and GHG exchange measurement network did not exist.

The GHG-LAKE joint research programme aimed to increase mobility and exchange of researchers between Sweden, Finland, Russia, and the USA to obtain a better understanding of energy and greenhouse gases (methane and carbon dioxide) budgets in lake ecosystems at high latitudes, which are potentially sensitive to ongoing and future climate changes. Factors controlling the carbon cycles were investigated by means of existing and new field measurements and process-based modelling.

Freshwater environments have been recognized as considerable net sources of carbon dioxide (CO2) and methane (CH4). However, current data for aquatic GHG fluxes have been far from robust. Emission estimates have often relied on measurements of surface water concentrations in combination with very simple models. This project performed and evaluated empirical measurements using several different approaches and suggested improved methods for estimating gas exchange.

Robust measurements of greenhouse gas (GHG) emissions are important for constraining GHG budgets at all scales and for assessing climate feedbacks on natural fluxes to improve climate models. Freshwater environments have recently been recognized as considerable net sources of carbon dioxide (CO2) and methane (CH4) to the atmosphere. However, current data for aquatic GHG fluxes have been far from robust, and emission estimates have often relied on measurements of surface water concentrations in combination with very simple models of the gas exchange coefficient (piston velocity; k). These models have been highly uncertain since they were often developed in single systems but applied widely in very different systems without calibration.

This project carried out empirical measurements of k using different approaches and used the data to evaluate these methods and suggest ways to improve GHG emission estimates from aquatic environments.

Funding: The Swedish Research Council

The greenhouse gas (GHG) exchange of landscapes and the balance between local sources and sinks are poorly understood. Forests are generally seen as carbon sinks because of measurements of vertical GHG exchange between vegetation and the atmosphere. However, horizontal transport via water to streams and lakes has largely been ignored, as well as the subsequent exchange between the atmosphere and surface waters. This project quantified GHG and carbon balances at a landscape scale in forested regions, including land-atmosphere, land-water, and water-atmosphere exchange.

The accounting of continental greenhouse gas budgets has relied on measurements of vertical carbon dioxide (CO2) exchange between vegetation and the atmosphere. These budgets have ignored dissolved carbon (C) and nitrogen (N) transport in water to streams and lakes and the subsequent exchange between the atmosphere and surface waters. Aquatic habitats can be significant net sources of CO2 and methane (CH4) and potential hot spots for N2O release, all important for natural greenhouse gas (GHG) emissions. Inland waters need to be included in the C and GHG balances for terrestrial landscapes.

This project quantified GHG balances at the landscape scale in a forested catchment, including land-atmosphere, land-water, and water-atmosphere exchange of CO2, CH4, and N2O. New measurements and technologies, as well as available data from ongoing environmental monitoring, were used to estimate the overall landscape net C and GHG balances at different scales by linking data with models.

The project combined expertise in terrestrial, aquatic, and atmospheric processes, and biogeochemical cycling and modelling, at six Swedish universities. It took advantage of major national and international research infrastructure networks and provided knowledge regarding landscape management to minimise GHG release.

Funding: FORMAS