Åsa Kasimir

Convenient in situ methods are key for detecting, quantifying, and mitigating gas emissions. Uncrewed aerial vehicles (UAVs), comprising drones equipped with lightweight integrated instruments, offer a promising platform for mapping greenhouse gas (GHG) emissions. However, flux area attribution can be challenging, and the low-weight gas analyzers or sensors required for drones may exhibit drift over time that degrades detection limits and increases measurement uncertainty. We have developed a UAS (uncrewed aerial system) based approach with all instrumentation onboard, mapping gases, here focusing on simultaneous measurements of the GHGs methane (CH₄), carbon dioxide (CO₂), nitrous oxide (N₂O), and ethane (C₂H₆). The key innovations are the combination of onboard multi-gas measurements, in-flight drift correction using onboard reference air, and integration of controlled tracer gas (C₂H₆) release to constrain the area attribution of detected fluxes. We explore four different flight patterns (box, two-wall, long wall, and 2D-mapping), each suited to different measurement scenarios, and demonstrate their application in diverse environments, including a rewetted peatland, the littoral zone of a lake, manure wells, and a barn housing dairy cows. Our results show the importance of in-flight drift correction or drift control, and that this can reduce baseline-related uncertainty of UAS-based mass balance approaches, which can be key for improving detection limits and estimation of GHG fluxes in a wide range of environments and settings. Furthermore, combining tracer gas emissions with drone flights aids in separation of sources in the area of interest, verification that targeted emissions are intercepted by the sampling walls, and determination of the upper integration height needed to capture source-related transport.

Convenient in situ methods are key for detecting, quantifying, and mitigating gas emissions. Uncrewed aerial vehicles (UAVs), comprising drones equipped with lightweight integrated instruments, offer a promising platform for mapping greenhouse gas (GHG) emissions. However, flux area attribution can be challenging, and the low-weight gas analyzers or sensors required for drones may exhibit drift over time that degrades detection limits and increases measurement uncertainty. We have developed a UAS (uncrewed aerial system) based approach with all instrumentation onboard, mapping gases, here focusing on simultaneous measurements of the GHGs methane (CH₄), carbon dioxide (CO₂), nitrous oxide (N₂O), and ethane (C₂H₆). The key innovations are the combination of onboard multi-gas measurements, in-flight drift correction using onboard reference air, and integration of controlled tracer gas (C₂H₆) release to constrain the area attribution of detected fluxes. We explore four different flight patterns (box, two-wall, long wall, and 2D-mapping), each suited to different measurement scenarios, and demonstrate their application in diverse environments, including a rewetted peatland, the littoral zone of a lake, manure wells, and a barn housing dairy cows. Our results show the importance of in-flight drift correction or drift control, and that this can reduce baseline-related uncertainty of UAS-based mass balance approaches, which can be key for improving detection limits and estimation of GHG fluxes in a wide range of environments and settings. Furthermore, combining tracer gas emissions with drone flights aids in separation of sources in the area of interest, verification that targeted emissions are intercepted by the sampling walls, and determination of the upper integration height needed to capture source-related transport.

Convenient in situ methods are key for detecting, quantifying, and mitigating gas emissions. Uncrewed aerial vehicles (UAVs), comprising drones equipped with lightweight integrated instruments, offer a promising platform for mapping greenhouse gas (GHG) emissions. However, flux area attribution can be challenging, and the low-weight gas analyzers or sensors required for drones may exhibit drift over time that degrades detection limits and increases measurement uncertainty. We have developed a UAS (uncrewed aerial system) based approach with all instrumentation onboard, mapping gases, here focusing on simultaneous measurements of the GHGs methane (CH4), carbon dioxide (CO2), nitrous oxide (N2O), and ethane (C2H6). The key innovations are the combination of onboard multi-gas measurements, in-flight drift correction using onboard reference air, and integration of controlled tracer gas (C2H6) release to constrain the area attribution of detected fluxes. We explore four different flight patterns (box, two-wall, long wall, and 2D-mapping), each suited to different measurement scenarios, and demonstrate their application in diverse environments, including a rewetted peatland, the littoral zone of a lake, manure wells, and a barn housing dairy cows. Our results show the importance of in-flight drift correction or drift control, and that this can reduce baseline-related uncertainty of UAS-based mass balance approaches, which can be key for improving detection limits and estimation of GHG fluxes in a wide range of environments and settings. Furthermore, combining tracer gas emissions with drone flights aids in separation of sources in the area of interest, verification that targeted emissions are intercepted by the sampling walls, and determination of the upper integration height needed to capture source-related transport.

The EU Nature Restoration Law (NRL) is critical for the restoration of degraded ecosystems and active afforestation of degraded peatlands has been suggested as a restoration measure under the NRL. Here, we discuss the current state of scientific evidence on the climate mitigation effects of peatlands under forestry. Afforestation of drained peatlands without restoring their hydrology does not fully restore ecosystem functions. Evidence on long-term climate benefits is lacking and it is unclear whether CO₂ sequestration of forest on drained peatland can offset the carbon loss from the peat over the long-term. While afforestation may offer short-term gains in certain cases, it compromises the sustainability of peatland carbon storage. Thus, active afforestation of drained peatlands is not a viable option for climate mitigation under the EU Nature Restoration Law and might even impede future rewetting/restoration efforts. Instead, restoring hydrological conditions through rewetting is crucial for effective peatland restoration.

We compiled published peer-reviewed CO₂, CH₄, and N₂O data on managed drained organic forest soils in boreal and temperate zones to revisit the current Tier 1 default emission factors (EFs) provided in the IPCC (2014) Wetlands Supplement: to see whether their uncertainty may be reduced; to evaluate possibilities for breaking the broad categories used for the IPCC EFs into more site-type-specific ones; and to inspect the potential relevance of a number of environmental variables for predicting the annual soil greenhouse gas (GHG) balances, on which the EFs are based. Despite a considerable number of publications applicable for compiling EFs being added, only modest changes were found compared to the Tier 1 default EFs. However, the more specific site type categories generated in this study showed narrower confidence intervals compared to the default categories. Overall, the highest CO₂ EFs were found for temperate afforested agricultural lands and boreal forestry-drained sites with very low tree stand productivity. The highest CH₄ EFs in turn prevailed in boreal nutrient-poor forests with very low tree stand productivity and temperate forests irrespective of nutrient status, while the EFs for afforested sites were low or showed a sink function. The highest N₂O EFs were found for afforested agricultural lands and forestry-drained nutrient-rich sites. The occasional wide confidence intervals could be mainly explained by single or a few highly deviating estimates rather than the broadness of the categories applied. Our EFs for the novel categories were further supported by the statistical models connecting the annual soil GHG balances to site-specific soil nutrient status indicators, tree stand characteristics, and temperature-associated weather and climate variables. The results of this synthesis have important implications for EF revisions and national emission reporting, e.g. by the use of different categories for afforested sites and forestry-drained sites, and more specific site productivity categories based on timber production potential.

We compiled published peer-reviewed CO₂, CH₄ and N₂O data on drained organic forest soils in boreal and temperate zones, to revisit the current Tier 1 default emission factors (EFs) provided in the IPCC (2014) Wetlands Supplement: to see whether their uncertainty may be reduced, to evaluate possibilities for breaking the broad categories used for the IPCC EFs into more site-type specific ones, and to inspect the potential relevance of a number of environmental variables for predicting the annual soil greenhouse gas (GHG) balances, on which the EFs are based. Despite a considerable number of publications applicable for compiling EFs was added, only modest changes were found compared to the Tier 1 default EFs. However, the more specific site-type categories generated in this study showed narrower confidence intervals compared to the default categories. Overall, the highest CO₂ EFs were found for temperate afforested agricultural lands, and boreal forestry-drained sites with very low tree-stand productivity. The highest CH₄ EFs in turn prevailed at boreal nutrient-poor forests with very low tree-stand productivity and temperate forests irrespective of nutrient status, while the EFs for afforested sites were low or showed a sink function. The highest N₂O EFs were found for afforested agricultural lands and forestry-drained nutrient-rich sites. The occasional wide confidence intervals could be mainly explained by single or few highly deviating estimates, rather than the broadness of the categories applied. Our EFs for the novel categories were further supported by the statistical models connecting the annual soil GHG balances to site-specific soil nutrient status indicators, tree stand characteristics, and temperature-associated weather and climate variables. The results of this synthesis have important implications for EF revisions and national emission reporting, e.g., by the use of different categories for afforested sites and forestry-drained sites, and more specific site productivity categories based on timber production potential.

Nutrient-rich peat soils have previously been demonstrated to lose carbon despite higher photosynthesis and litter production compared to nutrient-poor soils, where instead carbon accumulates. To understand this phenomenon, we used a process-oriented model (CoupModel) calibrated on data from two closely located drained peat soil sites in boreal forests in Finland, Kalevansuo and Lettosuo, with different soil C/N ratios. Uncertainty-based calibrations were made using eddy-covariance data (hourly values of net ecosystem exchange) and tree growth data. The model design used two forest scenarios on drained peat soil, one nutrient-poor with dense moss cover and another with lower soil C/N ratio with sparse moss cover. Three vegetation layers were assumed: conifer trees, other vascular plants, and a bottom layer with mosses. Adding a moss layer was a new approach, because moss has a modified physiology compared to vascular plants. The soil was described by three separate soil organic carbon (SOC) pools consisting of vascular plants and moss litter origin and decomposed organic matter. Over 10 years, the model demonstrated a similar photosynthesis rate for the two scenarios, 903 and 1,034 g C m⁻² yr⁻¹, for the poor and rich site respectively, despite the different vegetation distribution. For the nutrient-rich scenario more of the photosynthesis produce accumulated as plant biomass due to more trees, while the poor site had abundant moss biomass which did not increase living aboveground biomass to the same degree. Instead, the poor site showed higher litter inputs, which compared with litter from vascular plants had low turnover rates. The model calibration showed that decomposition rate coefficients for the three SOC pools were similar for the two scenarios, but the high quantity of moss litter input with low decomposability for the nutrient poor scenario explained the major difference in the soil carbon balance. Vascular plant litter declined with time, while SOC pools originating from mosses accumulated with time. Large differences between the scenarios were obtained during dry spells where soil heterotrophic respiration doubled for the nutrient-rich scenario, where vascular plants dominated, owing to a larger water depletion by roots. Where moss vegetation dominated, the heterotrophic respiration increased by only 50% during this dry period. We suggest moss vegetation is key for carbon accumulation in the poor soil, adding large litter quantities with a resistant quality and less water depletion than vascular plants during dry conditions.

Most national GHG inventories estimating direct N₂O emissions from managed soils rely on a default Tier 1 emission factor (EF₁) amounting to 1% of nitrogen inputs. Recent research has, however, demonstrated the potential for refining the EF₁ considering variables that are readily available at national scales. Building on existing reviews, we produced a large dataset (n = 848) enriched in dry and low latitude tropical climate observations as compared to former global efforts and disaggregated the EF₁ according to most meaningful controlling factors. Using spatially explicit N fertilizer and manure inputs, we also investigated the implications of using the EF₁ developed as part of this research and adopted by the 2019 IPCC refinement report. Our results demonstrated that climate is a major driver of emission, with an EF₁ three times higher in wet climates (0.014, 95% CI 0.011–0.017) than in dry climates (0.005, 95% CI 0.000–0.011). Likewise, the form of the fertilizer markedly modulated the EF₁ in wet climates, where the EF₁ for synthetic and mixed forms (0.016, 95% CI 0.013–0.019) was also almost three times larger than the EF₁ for organic forms (0.006; 95% CI 0.001–0.011). Other factors such as land cover and soil texture, C content, and pH were also important regulators of the EF₁. The uncertainty associated with the disaggregated EF₁ was considerably reduced as compared to the range in the 2006 IPCC guidelines. Compared to estimates from the 2006 IPCC EF₁, emissions based on the 2019 IPCC EF₁ range from 15% to 46% lower in countries dominated by dry climates to 7%–37% higher in countries with wet climates and high synthetic N fertilizer consumption. The adoption of the 2019 IPCC EF₁ will allow parties to improve the accuracy of emissions’ inventories and to better target areas for implementing mitigation strategies.

Nutrient rich peat soils have earlier been shown to loose carbon despite higher photosynthesis and litter production compared to nutrient poor soils, where instead carbon accumulated. To understand this phenomena data from two drained Finnish sites, nutrient poor Kalevansuo and nutrient rich Lettosuo, was combined with a process-oriented model (CoupModel). Uncertainty based calibrations were made using eddy-covariance data (hourly values of net ecosystem exchange) and tree growth data. The model design was three vegetation layers: trees, smaller vascular plants and a bottom layer with mosses, all with different LAI and degree of coverage. Adding a moss layer was a new approach, having a modified physiology compared to vascular plants. Soil organic carbon was described by two separate litter pools for vascular plants and mosses together with a common inert pool of decomposed organic matter. Over a period of 10 years the model showed similar photosynthesis rate for the two sites but higher biomass accumulation for the fertile stand. Moss biomass did not increase, instead mosses delivered high litter inputs with low turnover rates compared with litter from vascular plants. Both the soil organic carbon received from vascular plant litter and the old decomposed matter declined by time, while litter originating from mosses was accumulating by time. Large differences between the sites were obtained during dry spells where soil heterotrophic decomposition was enhanced in the vascular plants dominated site, due to a larger water depletion by roots. Important for carbon accumulation in the poor soil was the mosses, adding larger litter quantities with a resistant quality together with less water depletion in dry spells.This project was funded by the Swedish Research Council FORMAS, the Research Council of Norway (MYR-project), and the Swedish strategic research area BECC.