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Incomplete combustion processes lead to the formation of many gaseous byproducts that can be challenging to monitor in flue gas released via chimneys. This study presents ground-based remote sensing approaches to make greenhouse gas (GHG) flux measurements of methane (CH 4 ) and nitrous oxide (N 2 O) from a waste incineration chimney at distances of 150–200 m. The study found emission of N 2 O (corresponding to 30–40 t yr −1 ), which is a consequence of adding the reduction agent urea to decrease NO X emissions due to NO X regulation; a procedure that instead increases N 2 O emissions (which is approximately 300 times more potent as a GHG than CO 2 on a 100-year time scale). CH 4 emissions of 7–11 t yr −1 was also detected from the studied chimney despite the usage of a high incineration temperature. For this particular plant, local knowledge is high and emission estimates at corresponding levels have been reported previously. However, emissions of CH 4 are often not included in GHG emission inventories for waste incineration. This study highlights the importance of monitoring combustion processes, and shows the possibility of surveying CH 4 and N 2 O emissions from waste incineration at distances of several hundred meters. [ABSTRACT FROM AUTHOR]

Methane (CH 4 ) and nitrous oxide (N 2 O) are two very potent greenhouse gases, with highly heterogeneous distributions in both space and time. Mapping hot-spots and source areas, and measuring fluxes in different environments has so far not been possible on a local scale using direct measurements. We have developed a method for simultaneous mapping of methane (CH 4 ) and nitrous oxide (N 2 O), also including water vapor (H 2 O), using ground-based remote sensing on a landscape-sized scale by utilizing Imaging Fourier Transform Spectrometers (IFTS) with high spectral resolution and imaging rates. The approach uses calculated libraries of transmission spectra at the spectroscopic resolutions of the IFTS, based on the HITRAN database of spectroscopic lines and our own line-by-line radiative transfer model (LBLRTM). For each species, 1024 spectra have been made, resulting in 1024 3 combinations of column densities. Using an adaptive grid, solutions are found for each line of sight at a spectral resolution of up to 0.25 cm − 1 using the full spectral region of the detector. The modeling is multi-layered, calculating temperatures of the background, air, and any additional gas layers, also accounting for reflected cold sky. Background distances can be mapped from the amount of water vapor in each line of sight. The described approach can be used to identify sources, quantify gas distributions, and to calculate fluxes. Visualizations can produce gas distribution images, as well as air motion videos, which are used to map fluxes using the same data set, without the need for additional instruments for wind measurements. [ABSTRACT FROM AUTHOR]

The spatial extent of northern peatlands remains highly uncertain in spite of rapidly developing satellite observation datasets. This is limiting progress in the understanding of fundamental biogeochemical processes, such as the global carbon (C) cycle and climate feedback effects on C fluxes. In this study, we evaluated the capabilities of two new satellite datasets that enable regional scale mapping of peatland extent at high spatial resolution, including Sentinel-1 synthetic aperture radar (SAR) and the Arctic digital elevation model (ArcticDEM). Terrain indices and temporal features derived from these datasets provided input to Random Forest models for delineating four main land cover classes (forest, open upland, water and peatland) in an area in northern Sweden consisting of both lowland and mountainous terrain. The contribution of ArcticDEM to the classification accuracy was assessed by comparing the results with those derived when a high quality LiDAR based DEM (LiDEM) was used as alternative model input. This study shows that multi-seasonal SAR alone can produce reasonable classification results in terms of overall accuracy (OA; 81.6%), but also that it has limitations. The inclusion of terrain indices improved classification performance substantially. OA increased to 87.5% and 90.9% when terrain indices derived from ArcticDEM and LiDEM were included, respectively. The largest increase in accuracy was achieved for the peatland class, which suggests that terrain indices do have the ability to capture the features in the geographic context that aid the discrimination of peatland from other land cover classes. The relatively small difference in classification accuracy between LiDEM and ArcticDEM is encouraging since the latter provides circumpolar coverage. Thus, the combination of Sentinel-1 time series and terrain indices derived from ArcticDEM presents opportunities for substantially improving regional estimates of peatland extent at high latitudes. • Sentinel-1 and terrain indices from digital elevation models (DEM) were evaluated. • ArcticDEM was compared to local scale DEM based on LiDAR. • Inclusion of terrain indices increased overall accuracy considerably. • Largest gain in classification accuracy occurred for peatlands. • ArcticDEM proved to be a valuable data source for northern peatland mapping. [ABSTRACT FROM AUTHOR]

Lakes are major sources of methane (CH4) to the atmosphere that contribute significantly to the global budget. Recent studies have shown that diffusive fluxes, ebullition and surface water CH4 concentrations can differ significantly within lakes-spatially and temporally. CH4 fluxes may be affected at longer scales in response to seasons, temperature, lake mixing events, short term weather events like pressure variations, shifting winds and diel cycles. Frequent measurements of fluxes in the same system and integrated assessments of the impacts of the spatio-temporal variability are rare. Thereby, large scale assessments frequently lack information on this variability which can potentially lead to biased estimates. In this study, we analysed the variability of CH4 fluxes and surface water CH4 concentrations across open water areas of lakes in a small catchment in southwest Sweden over two annual cycles. Significant patterns in CH4 concentrations, diffusive fluxes, ebullition and total fluxes were observed in space (between and within lakes) and in time (over diel cycles to years). Differences observed among the lakes can be associated with lake characteristics. The spatial variability within lakes was linked to depth or distance to stream inlets. Temporal variability was observed at diel to seasonal scales and was influenced by weather events. The fluxes increased exponentially with temperature in all three lakes, with stronger temperature dependence with decreasing depth. By comparing subsets of our data with estimates using all data we show that considering the spatio-temporal variability in CH4 fluxes is critical when making whole lake or annual budgets. [ABSTRACT FROM AUTHOR]

The hydrodynamics within small boreal lakes have rarely been studied, yet knowing whether turbulence at the air--water interface and in the water column scales with metrics developed elsewhere is essential for computing metabolism and fluxes of climate-forcing trace gases. We instrumented a humic, 4.7 ha, boreal lake with two meteorological stations, three thermistor arrays, an infrared (IR) camera to quantify surface divergence, obtained turbulence as dissipation rate of turbulent kinetic energy (ε) using an acoustic Doppler velocimeter and a temperature-gradient microstructure profiler, and conducted chamber measurements for short periods to obtain fluxes and gas transfer velocities (k). Near-surface ε varied from 10-8 to 10-6 m² s-3 for the 0-4 ms-1 winds and followed predictions from Monin-Obukhov similarity theory. The coefficient of eddy diffusivity in the mixed layer was up to 10-3 m² s-1 on the windiest afternoons, an order of magnitude less other afternoons, and near molecular at deeper depths. The upper thermocline upwelled when Lake numbers (LN) dropped below four facilitating vertical and horizontal exchange. k computed from a surface renewal model using ε agreed with values from chambers and surface divergence and increased linearly with wind speed. Diurnal thermoclines formed on sunny days when winds were < 3 m s-1, a condition that can lead to elevated near-surface ε and k. Results extend scaling approaches developed in the laboratory and for larger water bodies, illustrate turbulence and k are greater than expected in small wind-sheltered lakes, and provide new equations to quantify fluxes. [ABSTRACT FROM AUTHOR]

Methane (CH 4), one of the key long-lived atmospheric greenhouse gases, is primarily produced from organic matter. Accordingly, net primary production of organic matter sets the boundaries for CH 4 emissions. Plants, being dominant primary producers, are thereby indirectly sustaining most global CH 4 emissions, albeit with delays in time and with spatial offsets between plant primary production and subsequent CH 4 emission. In addition, plant communities can enhance or hamper ecosystem production, oxidation, and transport of CH 4 in multiple ways, e.g., by shaping carbon, nutrient, and redox gradients, and by representing a physical link between zones with extensive CH 4 production in anoxic sediments or soils and the atmosphere. This review focuses on how plants and other primary producers influence CH 4 emissions with the consequences at ecosystem scales. We outline mechanisms of interactions and discuss flux regulation, quantification, and knowledge gaps across multiple ecosystem examples. Some recently proposed plant-related ecosystem CH 4 fluxes are difficult to reconcile with the global atmospheric CH 4 budget and the enigmas related to these fluxes are highlighted. Overall, ecosystem CH 4 emissions are strongly linked to primary producer communities, directly or indirectly, and properly quantifying magnitudes and regulation of these links are key to predicting future CH 4 emissions in a rapidly changing world. [Display omitted] • Plants have major indirect influence on global emissions of methane. • Improved quantitative knowledge on plant-methane interactions is needed. • Systematic long-term observations of both methane and plant communities are key. [ABSTRACT FROM AUTHOR]