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Nitrous oxide (N2O) emissions from permafrost-affected terrestrial ecosystems have received little attention, largely because they have been thought to be negligible. Recent studies, however, have shown that there are habitats in the subarctic tundra emitting N2O at high rates, such as bare peat (BP) surfaces on permafrost peatlands. Nevertheless, the processes behind N2O production in these high-emission habitats are poorly understood. In this study, we established an in situ 15N-labeling experiment with two main objectives: (1) to partition the microbial sources of N2O emitted from BP surfaces on permafrost peatlands and (2) to study the fate of ammonium and nitrate in these soils and in adjacent vegetated peat (VP) surfaces showing low N2O emissions. Our results confirm the hypothesis that denitrification is mostly responsible for the high N2O emissions from BP. During the study period, denitrification contributed ∼ 79 % of the total N2O emissions from BP, whereas the contribution from ammonia oxidation was less (about 19 %). Both gross N mineralization and gross nitrification rates were higher in BP than in VP, with high C/N ratios and a low water content likely limiting N transformation processes and, consequently, N2O production in the latter soil type. Our results show that multiple factors contribute to high N2O production in BP surfaces on permafrost peatlands, with the most important factors being the absence of plants, an intermediate to high water content and a low C/N ratio, which all affect the mineral-N availability for soil microbes, including those producing N2O. The process understanding produced here is important for the development of process models that can be used to evaluate future permafrost–N feedbacks to the climate system.

Carbon monoxide (CO) is an important reactive trace gas in the atmosphere, while its sources and sinks in the biosphere are poorly understood. Soils are generally considered as a sink of CO due to microbial oxidation processes, while emissions of CO have been reported from a wide range of soil–plant systems. We measured CO fluxes using the micrometeorological eddy covariance method from a bioenergy crop (reed canary grass) in eastern Finland from April to November 2011. Continuous flux measurements allowed us to assess the seasonal and diurnal variability and to compare the CO fluxes to simultaneously measured net ecosystem exchange of CO2, N2O and heat fluxes as well as to relevant meteorological, soil and plant variables in order to investigate factors driving the CO exchange.The reed canary grass (RCG) crop was a net source of CO from mid-April to mid-June and a net sink throughout the rest of the measurement period from mid-June to November 2011, excluding a measurement break in July. CO fluxes had a distinct diurnal pattern with a net CO uptake in the night and a net CO emission during the daytime with a maximum emission at noon. This pattern was most pronounced in spring and early summer. During this period the most significant relationships were found between CO fluxes and global radiation, net radiation, sensible heat flux, soil heat flux, relative humidity, N2O flux and net ecosystem exchange. The strong positive correlation between CO fluxes and radiation suggests abiotic CO production processes, whereas the relationship between CO fluxes and net ecosystem exchange of CO2, and night-time CO fluxes and N2O emissions indicate biotic CO formation and microbial CO uptake respectively. The study shows a clear need for detailed process studies accompanied by continuous flux measurements of CO exchange to improve the understanding of the processes associated with CO exchange.

One of the strategies to reduce carbon dioxide (CO2) emissions from the energy sector is to increase the use of renewable energy sources such as bioenergy crops. Bioenergy is not necessarily carbon neutral because of greenhouse gas (GHG) emissions during biomass production, field management and transportation. The present study focuses on the cultivation of reed canary grass (RCG, Phalaris arundinacea L.), a perennial bioenergy crop, on a mineral soil. To quantify the CO2 exchange of this RCG cultivation system, and to understand the key factors controlling its CO2 exchange, the net ecosystem CO2 exchange (NEE) was measured from July 2009 until the end of 2011 using the eddy covariance (EC) method. The RCG cultivation thrived well producing yields of 6200 and 6700 kg DW ha−1 in 2010 and 2011, respectively. Gross photosynthesis (GPP) was controlled mainly by radiation from June to September. Vapour pressure deficit (VPD), air temperature or soil moisture did not limit photosynthesis during the growing season. Total ecosystem respiration (TER) increased with soil temperature, green area index and GPP. Annual NEE was −262 and −256 g C m−2 in 2010 and 2011, respectively. Throughout the study period from July 2009 until the end of 2011, cumulative NEE was −575 g C m−2. Carbon balance and its regulatory factors were compared to the published results of a comparison site on drained organic soil cultivated with RCG in the same climate. On this mineral soil site, the RCG had higher capacity to take up CO2 from the atmosphere than on the comparison site.

Methane (CH4) fluxes were investigated in a subarctic Russian tundra site in a multi-approach study combining plot-scale data, ecosystem-scale eddy covariance (EC) measurements, and a fine-resolution land cover classification scheme for regional upscaling. The flux data as measured by the two independent techniques resulted in a seasonal (May–October 2008) cumulative CH4 emission of 2.4 (EC) and 3.7 g CH4 m−2 (manual chambers) for the source area representative of the footprint of the EC instruments. Upon upscaling for the entire study region of 98.6 km2, the chamber measured flux data yielded a regional flux estimate of 6.7 g CH4 m−2 yr−1. Our upscaling efforts accounted for the large spatial variability in the distribution of the various land cover types (LCTs) predominant at our study site. Wetlands with emissions ranging from 34 to 53 g CH4 m−2 yr−1 were the most dominant CH4-emitting surfaces. Emissions from thermokarst lakes were an order of magnitude lower, while the rest of the landscape (mineral tundra) was a weak sink for atmospheric methane. Vascular plant cover was a key factor in explaining the spatial variability of CH4 emissions among wetland types, as indicated by the positive correlation of emissions with the leaf area index (LAI). As elucidated through a stable isotope analysis, the dominant CH4 release pathway from wetlands to the atmosphere was plant-mediated diffusion through aerenchyma, a process that discriminates against 13C-CH4. The CH4 released to the atmosphere was lighter than that in the surface porewater, and δ13C in the emitted CH4 correlated negatively with the vascular plant cover (LAI). The mean value of δ13C obtained here for the emitted CH4, −68.2 ± 2.0 ‰, is within the range of values from other wetlands, thus reinforcing the use of inverse modelling tools to better constrain the CH4 budget. Based on the IPCC A1B emission scenario, a temperature increase of 6.1 °C relative to the present day has been predicted for the European Russian tundra by the end of the 21st Century. A regional warming of this magnitude will have profound effects on the permafrost distribution leading to considerable changes in the regional landscape with a potential for an increase in the areal extent of CH4-emitting wet surfaces.

Four gas analysers capable of measuring nitrous oxide (N2O) concentration at a response time necessary for eddy covariance flux measurements were operated from spring until winter 2011 over a field cultivated with reed canary grass (RCG, Phalaris arundinacea, L.), a perennial bioenergy crop in eastern Finland. The instruments were TGA100A (Campbell Scientific Inc.), CW-TILDAS-CS (Aerodyne Research Inc.), N2O / CO-23d (Los Gatos Research Inc.) and QC-TILDAS-76-CS (Aerodyne Research Inc.). The period with high emissions, lasting for about 2 weeks after fertilization in late May, was characterized by an up to 2 orders of magnitude higher emission, whereas during the rest of the campaign the N2O fluxes were small, from 0.01 to 1 nmol m−2 s−1. Two instruments, CW-TILDAS-CS and N2O / CO-23d, determined the N2O exchange with minor systematic difference throughout the campaign, when operated simultaneously. TGA100A produced the cumulatively highest N2O estimates (with 29% higher values during the period when all instruments were operational). QC-TILDAS-76-CS obtained 36% lower fluxes than CW-TILDAS-CS during the first period, including the emission episode, whereas the correspondence with other instruments during the rest of the campaign was good. The reasons for systematic differences were not identified, suggesting further need for detailed evaluation of instrument performance under field conditions with emphasis on stability, calibration and any other factors that can systematically affect the accuracy of flux measurements. The instrument CW-TILDAS-CS was characterized by the lowest noise level (with a standard deviation of around 0.12 ppb at 10 Hz sampling rate) as compared to N2O / CO-23d and QC-TILDAS-76-CS (around 0.50 ppb) and TGA100A (around 2 ppb). We identified that for all instruments except CW-TILDAS-CS the random error due to instrumental noise was an important source of uncertainty at the 30 min averaging level and the total stochastic error was frequently of the same magnitude as the fluxes when N2O exchange was small at the measurement site. Both instruments based on continuous-wave quantum cascade laser, CW-TILDAS-CS and N2O / CO-23d, were able to determine the same sample of low N2O fluxes with a high mutual coefficient of determination at the 30 min averaging level and with minor systematic difference over the observation period of several months. This enables us to conclude that the new-generation instrumentation is capable of measuring small N2O exchange with high precision and accuracy at sites with low fluxes.

We report here the carbon dioxide (CO2) budget of a 98.6 km2 subarctic tundra area in northeast European Russia based on measurements at two different scales and two independent upscaling approaches. Plot-scale measurements (chambers on terrestrial surfaces, gas gradient method and bubble collectors on lakes) were carried out from July 2007 to October 2008. The landscape-scale eddy covariance (EC) measurements covered the snow-free period of 2008. The annual net ecosystem exchange (NEE) of different land cover types ranged from −251 to 84 g C m−2. Leaf area index (LAI) was an excellent predictor of the spatial variability in gross photosynthesis (GP), NEE and ecosystem respiration (ER). The plot-scale CO2 fluxes were first scaled up to the EC source area and then to the whole study area using two data sets: a land cover classification and a LAI map, both based on field data and a 2.4 m pixel-sized QuickBird satellite image. The good agreement of the CO2 balances for the EC footprint based on the different measuring techniques (−105 to −81 g C m−2 vs. −79 g C m−2; growing season 2008) justified the integration of the plot-scale measurements over the larger area. The regional CO2 balance based on area-integrated plot-scale measurements was −41 or −79 g C m−2 yr−1 according to the two upscaling methods, the land cover classification and the LAI map, respectively. Due to the heterogeneity of tundra, the effect of climate change on CO2 uptake will vary strongly according to the land cover type and, moreover, likely changes in their relative coverage in the future will have great impact on the regional CO2 balance.

This article provides an overview of the effects of land-use on the fluxes of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) and from peatlands in the Nordic countries based on the field data from about 100 studies. In addition, this review aims to identify the gaps in the present knowledge on the greenhouse gas (GHG) balances associated with the land-use of these northern ecosystems. Northern peatlands have accumulated, as peat, a vast amount of carbon from the atmosphere since the last glaciation. However, the past land-use and present climate have evidently changed their GHG balance. Unmanaged boreal peatlands may act as net sources or sinks for CO2 and CH4 depending on the weather conditions. Drainage for agriculture has turned peatlands to significant sources of GHGs (mainly N2O and CO2). Annual mean GHG balances including net CH4, N2O and CO2 emissions are 2260, 2280 and 3140 g CO2 eq. m−2 (calculated using 100 year time horizon) for areas drained for grass swards, cereals or those left fallow, respectively. Even after cessetion of the cultivation practices, N2O and CO2 emissions remain high. The mean net GHG emissions in abandoned and afforested agricultural peatlands have been 1580 and 500 g CO2 eq. m−2, respectively. Peat extraction sites are net sources of GHGs with an average emission rate of 770 g CO2 eq. m−2. Cultivation of a perennial grass (e.g., reed canary grass) on an abandoned peat extraction site has been shown to convert such a site into a net sink of GHGs (−330 g CO2 eq. m−2). In contrast, despite restoration, such sites are known to emit GHGs (mean source of 480 g CO2 eq. m−2, mostly from high CH4 emissions). Peatland forests, originally drained for forestry, may act as net sinks (mean −780 g CO2 eq. m−2). However, the studies where all three GHGs have been measured at an ecosystem level in the forested peatlands are lacking. The data for restored peatland forests (clear cut and rewetted) indicate that such sites are on average a net sink (190 g CO2 eq. m−2). The mean emissions from drained peatlands presented here do not include emissions from ditches which form a part of the drainage network and can contribute significantly to the total GHG budget. Peat soils submerged under water reservoirs have acted as sources of CO2, CH4 and N2O (mean annual emission 240 g CO2 eq. m−2). However, we cannot yet predict accurately the overall greenhouse gas fluxes of organic soils based on the site characteristics and land-use practices alone because the data on many land-use options and our understanding of the biogeochemical cycling associated with the gas fluxes are limited.

Agricultural soils are the most important sources for the greenhouse gas nitrous oxide (N2O), which is produced and emitted from soils also at low temperatures. The processes behind emissions at low temperatures are still poorly known. Snow is a good insulator and it keeps soil temperature rather constant. To simulate the effects of a reduction in snow depth on N2O emission in warming climate, snow pack was removed from experimental plots on three different agricultural soils (sand, mull, peat). Removal of snow lowered soil temperature and increased the extent and duration of soil frost in sand and mull soils. This led to enhanced N2O emissions during freezing and thawing events. The cumulative emissions during the first year when snow was removed over the whole winter were 0.25, 0.66 and 3.0 g N2O-N m−2 yr−1 in control plots of sand, mull and peat soils, respectively. In the treatment plots, without snow cover, the respective cumulative emissions were 0.37, 1.3 and 3.3 g N2O-N m−2 yr−1. Shorter snow manipulation during the second year did not increase the annual emissions. Only 20% of the N2O emission occurred during the growing season. Thus, these results highlight the importance of the winter season for this exchange and that the year-round measurements of annual N2O emissions from boreal soils are integral for estimating their N2O source strength. N2O accumulated in the frozen soil during winter and the soil N2O concentration correlated with the depth of frost but not with the winter N2O emission rates per se. Also laboratory incubations of soil samples showed high production rates of N2O at temperatures below 0°C, especially in the sand and peat soils.

This study explores the variability in concentrations of dissolved CH4 and annual flux estimates in the pelagic zone in a statistically defined sample of 207 lakes in Finland. The lakes were situated in the boreal zone, in an area where the mean annual air temperature ranges from −2.8 to 5.9°C. We examined how lake CH4 dynamics related to regional lake types assessed according to the EU water framework directive. Ten lake types were defined on the basis of water chemistry, color, and size. Lakes were sampled for dissolved CH4 concentrations four times per year, at four different depths at the deepest point of each lake. We found that CH4 concentrations and fluxes to the atmosphere tended to be high in nutrient rich calcareous lakes, and that the shallow lakes had the greatest surface water concentrations. Methane concentration in the hypolimnion was related to oxygen and nutrient concentrations, and to lake depth or lake area. The surface water CH4 concentration was related to the depth or area of lake. Methane concentration close to the bottom can be viewed as proxy of lake status in terms of frequency of anoxia and nutrient levels. The mean pelagic CH4 release from randomly selected lakes was 49 mmol m−2 a−1. The sum CH4 flux (storage and diffusion) correlated with lake depth, area and nutrient content, and CH4 release was greatest from the shallow nutrient rich and humic lakes. Our results support earlier lake studies regarding the regulating factors and also the magnitude of global emission estimate. These results propose that in boreal region small lakes have higher CH4 fluxes per unit area than larger lakes, and that the small lakes have a disproportionate significance regarding to the CH4 release.

Closed (non-steady state) chambers are widely used for quantifying carbon dioxide (CO2) fluxes between soils or low-stature canopies and the atmosphere. It is well recognised that covering a soil or vegetation by a closed chamber inherently disturbs the natural CO2 fluxes by altering the concentration gradients between the soil, the vegetation and the overlying air. Thus, the driving factors of CO2 fluxes are not constant during the closed chamber experiment, and no linear increase or decrease of CO2 concentration over time within the chamber headspace can be expected. Nevertheless, linear regression has been applied for calculating CO2 fluxes in many recent, partly influential, studies. This approach has been justified by keeping the closure time short and assuming the concentration change over time to be in the linear range. Here, we test if the application of linear regression is really appropriate for estimating CO2 fluxes using closed chambers over short closure times and if the application of nonlinear regression is necessary. We developed a nonlinear exponential regression model from diffusion and photosynthesis theory. This exponential model was tested with four different datasets of CO2 flux measurements (total number: 1764) conducted at three peatlands sites in Finland and a tundra site in Siberia. Thorough analyses of residuals demonstrated that linear regression was frequently not appropriate for the determination of CO2 fluxes by closed-chamber methods, even if closure times were kept short. The developed exponential model was well suited for nonlinear regression of the concentration over time c(t) evolution in the chamber headspace and estimation of the initial CO2 fluxes at closure time for the majority of experiments. However, a rather large percentage of the exponential regression functions showed curvatures not consistent with the theoretical model which is considered to be caused by violations of the underlying model assumptions. Especially the effects of turbulence and pressure disturbances by the chamber deployment are suspected to have caused unexplainable curvatures. CO2 flux estimates by linear regression can be as low as 40% of the flux estimates of exponential regression for closure times of only two minutes. The degree of underestimation increased with increasing CO2 flux strength and was dependent on soil and vegetation conditions which can disturb not only the quantitative but also the qualitative evaluation of CO2 flux dynamics. The underestimation effect by linear regression was observed to be different for CO2 uptake and release situations which can lead to stronger bias in the daily, seasonal and annual CO2 balances than in the individual fluxes. To avoid serious bias of CO2 flux estimates based on closed chamber experiments, we suggest further tests using published datasets and recommend the use of nonlinear regression models for future closed chamber studies.