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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.

During permafrost thaw, nitrogen can be released as the greenhouse gas nitrous oxide, but the magnitude of this flux is unknown. Nitrous oxide emissions from ice-rich permafrost deposits are reported here, showing that emissions increase after thawing and stabilization and could represent an unappreciated positive climate feedback in the Arctic.

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.

Abstract BackgroundComputerized clinical decision support systems (CDSSs) are increasingly adopted in health care to optimize resources and streamline patient flow. However, they often lack scientific validation against standard medical care. ObjectiveThe purpose of this study was to assess the performance, safety, and usability of a CDSS in a university hospital emergency department setting in Kuopio, Finland. MethodsPatients entering the emergency department were asked to voluntarily participate in this study. Patients aged 17 years or younger, patients with cognitive impairments, and patients who entered the unit in an ambulance or with the need for immediate care were excluded. Patients completed the CDSS web-based form and usability questionnaire when waiting for the triage nurse’s evaluation. The CDSS data were anonymized and did not affect the patients’ usual evaluation or treatment. Retrospectively, 2 medical doctors evaluated the urgency of each patient’s condition by using the triage nurse’s information, and urgent and nonurgent groups were created. The International Statistical Classification of Diseases, Tenth Revision ResultsIn total, our analyses included 248 patients. Regarding urgency, the mean sensitivities were 85% and 19%, respectively, for urgent and nonurgent cases when assessing the performance of CDSS evaluations in comparison to that of physicians. The mean sensitivities were 85% and 35%, respectively, when comparing the evaluations between the two physicians. Our CDSS did not miss any cases that were evaluated to be emergencies by physicians; thus, all emergency cases evaluated by physicians were evaluated as either urgent cases or emergency cases by the CDSS. In differential diagnosis, the CDSS had an exact match accuracy of 45.5% (97/213). The usability was good, with a mean System Usability Scale score of 78.2 (SD 16.8). ConclusionsIn a university hospital emergency department setting with a large real-world population, our CDSS was found to be equally as sensitive in urgent patient cases as physicians and was found to have an acceptable differential diagnosis accuracy, with good usability. These results suggest that this CDSS can be safely assessed further in a real-world setting. A CDSS could accelerate triage by providing patient-provided data in advance of patients’ initial consultations and categorize patient cases as urgent and nonurgent cases upon patients' arrival to the emergency department.

The occurrence of dark fixation of CO2 by heterotrophic microorganisms in soil is generally accepted, but its importance for microbial metabolism and soil organic carbon (C) sequestration is unknown, especially under C-limiting conditions. To fill this knowledge gap, we measured dark 13CO2 incorporation into soil organic matter and conducted a 13C-labelling experiment to follow the 13C incorporation into phospholipid fatty acids as microbial biomass markers across soil profiles of four tundra ecosystems in the northern circumpolar region, where net primary productivity and thus soil C inputs are low. We further determined the abundance of various carboxylase genes and identified their microbial origin with metagenomics. The microbial capacity for heterotrophic CO2 fixation was determined by measuring the abundance of carboxylase genes and the incorporation of 13C into soil C following the augmentation of bioavailable C sources. We demonstrate that dark CO2 fixation occurred ubiquitously in arctic tundra soils, with increasing importance in deeper soil horizons, presumably due to increasing C limitation with soil depth. Dark CO2 fixation accounted on average for 0.4, 1.0, 1.1, and 16% of net respiration in the organic, cryoturbated organic, mineral and permafrost horizons, respectively. Genes encoding anaplerotic enzymes of heterotrophic microorganisms comprised the majority of identified carboxylase genes. The genetic potential for dark CO2 fixation was spread over a broad taxonomic range. The results suggest important regulatory function of CO2 fixation in C limited conditions. The measurements were corroborated by modeling the long-term impact of dark CO2 fixation on soil organic matter. Our results suggest that increasing relative CO2 fixation rates in deeper soil horizons play an important role for soil internal C cycling and can, at least in part, explain the isotopic enrichment with soil depth.

BackgroundThe detection of atrial fibrillation (AF) is a major clinical challenge as AF is often paroxysmal and asymptomatic. Novel mobile health (mHealth) technologies could provide a cost-effective and reliable solution for AF screening. However, many of these techniques have not been clinically validated. ObjectiveThe purpose of this study is to evaluate the feasibility and reliability of artificial intelligence (AI) arrhythmia analysis for AF detection with an mHealth patch device designed for personal well-being. MethodsPatients (N=178) with an AF (n=79, 44%) or sinus rhythm (n=99, 56%) were recruited from the emergency care department. A single-lead, 24-hour, electrocardiogram-based heart rate variability (HRV) measurement was recorded with the mHealth patch device and analyzed with a novel AI arrhythmia analysis software. Simultaneously registered 3-lead electrocardiograms (Holter) served as the gold standard for the final rhythm diagnostics. ResultsOf the HRV data produced by the single-lead mHealth patch, 81.5% (3099/3802 hours) were interpretable, and the subject-based median for interpretable HRV data was 99% (25th percentile=77% and 75th percentile=100%). The AI arrhythmia detection algorithm detected AF correctly in all patients in the AF group and suggested the presence of AF in 5 patients in the control group, resulting in a subject-based AF detection accuracy of 97.2%, a sensitivity of 100%, and a specificity of 94.9%. The time-based AF detection accuracy, sensitivity, and specificity of the AI arrhythmia detection algorithm were 98.7%, 99.6%, and 98.0%, respectively. ConclusionsThe 24-hour HRV monitoring by the mHealth patch device enabled accurate automatic AF detection. Thus, the wearable mHealth patch device with AI arrhythmia analysis is a novel method for AF screening. Trial RegistrationClinicalTrials.gov NCT03507335; https://clinicaltrials.gov/ct2/show/NCT03507335

Our earlier laboratory measurements showed that low-velocity sand impacts release fine

BackgroundAtrial fibrillation (AF) is the most common tachyarrhythmia and associated with a risk of stroke. The detection and diagnosis of AF represent a major clinical challenge due to AF’s asymptomatic and intermittent nature. Novel consumer-grade mobile health (mHealth) products with automatic arrhythmia detection could be an option for long-term electrocardiogram (ECG)-based rhythm monitoring and AF detection. ObjectiveWe evaluated the feasibility and accuracy of a wearable automated mHealth arrhythmia monitoring system, including a consumer-grade, single-lead heart rate belt ECG device (heart belt), a mobile phone application, and a cloud service with an artificial intelligence (AI) arrhythmia detection algorithm for AF detection. The specific aim of this proof-of-concept study was to test the feasibility of the entire sequence of operations from ECG recording to AI arrhythmia analysis and ultimately to final AF detection. MethodsPatients (n=159) with an AF (n=73) or sinus rhythm (n=86) were recruited from the emergency department. A single-lead heart belt ECG was recorded for 24 hours. Simultaneously registered 3-lead ECGs (Holter) served as the gold standard for the final rhythm diagnostics and as a reference device in a user experience survey with patients over 65 years of age (high-risk group). ResultsThe heart belt provided a high-quality ECG recording for visual interpretation resulting in 100% accuracy, sensitivity, and specificity of AF detection. The accuracy of AF detection with the automatic AI arrhythmia detection from the heart belt ECG recording was also high (97.5%), and the sensitivity and specificity were 100% and 95.4%, respectively. The correlation between the automatic estimated AF burden and the true AF burden from Holter recording was >0.99 with a mean burden error of 0.05 (SD 0.26) hours. The heart belt demonstrated good user experience and did not significantly interfere with the patient’s daily activities. The patients preferred the heart belt over Holter ECG for rhythm monitoring (85/110, 77% heart belt vs 77/109, 71% Holter, P=.049). ConclusionsA consumer-grade, single-lead ECG heart belt provided good-quality ECG for rhythm diagnosis. The mHealth arrhythmia monitoring system, consisting of heart-belt ECG, a mobile phone application, and an automated AF detection achieved AF detection with high accuracy, sensitivity, and specificity. In addition, the mHealth arrhythmia monitoring system showed good user experience. Trial RegistrationClinicalTrials.gov NCT03507335; https://clinicaltrials.gov/ct2/show/NCT03507335

Atrial fibrillation is often asymptomatic and intermittent making its detection challenging. A photoplethysmography (PPG) provides a promising option for atrial fibrillation detection. However, the shapes of pulse waves vary in atrial fibrillation decreasing pulse and atrial fibrillation detection accuracy. This study evaluated ten robust photoplethysmography features for detection of atrial fibrillation. The study was a national multi-center clinical study in Finland and the data were combined from two broader research projects (NCT03721601, URL: https://clinicaltrials.gov/ct2/show/NCT03721601 and NCT03753139, URL: https://clinicaltrials.gov/ct2/show/NCT03753139). A photoplethysmography signal was recorded with a wrist band. Five pulse interval variability, four amplitude features and a novel autocorrelation-based morphology feature were calculated and evaluated independently as predictors of atrial fibrillation. A multivariate predictor model including only the most significant features was established. The models were 10-fold cross-validated. 359 patients were included in the study (atrial fibrillation n = 169, sinus rhythm n = 190). The autocorrelation univariate predictor model detected atrial fibrillation with the highest area under receiver operating characteristic curve (AUC) value of 0.982 (sensitivity 95.1%, specificity 93.7%). Autocorrelation was also the most significant individual feature (p < 0.00001) in the multivariate predictor model, detecting atrial fibrillation with AUC of 0.993 (sensitivity 96.4%, specificity 96.3%). Our results demonstrated that the autocorrelation independently detects atrial fibrillation reliably without the need of pulse detection. Combining pulse wave morphology-based features such as autocorrelation with information from pulse-interval variability it is possible to detect atrial fibrillation with high accuracy with a commercial wrist band. Photoplethysmography wrist bands accompanied with atrial fibrillation detection algorithms utilizing autocorrelation could provide a computationally very effective and reliable wearable monitoring method in screening of atrial fibrillation.

Soils are important sources of nitric oxide (NO) and nitrous acid (HONO) in the atmosphere. These nitrogen (N)-containing gases play a crucial role in atmospheric chemistry and climate at different scales because of reactions modulated by NO and hydroxyl radicals (OH), which are formed via HONO photolysis. Northern permafrost soils have so far remained unexplored for HONO and NO emissions despite their high N stocks, capacity to emit nitrous oxide (N _2 O), and enhancing mineral N turnover due to warming and permafrost thawing. Here, we report the first HONO and NO emissions from high-latitude soils based on measurements of permafrost-affected subarctic peatlands. We show large HONO (0.1–2.4 µ g N m ^−2 h ^−1 ) and NO (0.4–59.3 µ g N m ^−2 h ^−1 ) emissions from unvegetated peat surfaces, rich with mineral N, compared to low emissions (⩽0.2 µ g N m ^−2 h ^−1 for both gases) from adjacent vegetated surfaces (experiments with intact peat cores). We observed HONO production under highly variable soil moisture conditions from dry to wet. However, based on complementary slurry experiments, HONO production was strongly favored by high soil moisture and anoxic conditions. We suggest urgent examination of other Arctic landscapes for HONO and NO emissions to better constrain the role of these reactive N gases in Arctic atmospheric chemistry.

The paradigm that permafrost-affected soils show restricted mineral nitrogen (N) cycling in favor of organic N compounds is based on the observation that net N mineralization rates in these cold climates are negligible. However, we find here that this perception is wrong. By synthesizing published data on N cycling in the plant-soil-microbe system of permafrost ecosystems we show that gross ammonification and nitrification rates in active layers were of similar magnitude and showed a similar dependence on soil organic carbon (C) and total N concentrations as observed in temperate and tropical systems. Moreover, high protein depolymerization rates and only marginal effects of C:N stoichiometry on gross N turnover provided little evidence for N limitation. Instead, the rather short period when soils are not frozen is the single main factor limiting N turnover. High gross rates of mineral N cycling are thus facilitated by released protection of organic matter in active layers with nitrification gaining particular importance in N-rich soils, such as organic soils without vegetation. Our finding that permafrost-affected soils show vigorous N cycling activity is confirmed by the rich functional microbial community which can be found both in active and permafrost layers. The high rates of N cycling and soil N availability are supported by biological N fixation, while atmospheric N deposition in the Arctic still is marginal except for fire-affected areas. In line with high soil mineral N production, recent plant physiological research indicates a higher importance of mineral plant N nutrition than previously thought. Our synthesis shows that mineral N production and turnover rates in active layers of permafrost-affected soils do not generally differ from those observed in temperate or tropical soils. We therefore suggest to adjust the permafrost N cycle paradigm, assigning a generally important role to mineral N cycling. This new paradigm suggests larger permafrost N climate feedbacks than assumed previously.

Lakes account for about 10% of the boreal landscape and are responsible for approximately 30% of biogenic methane emissions that have been found to increase under changing climate. However, the quantification of this climate-sensitive methane source is fraught with large uncertainty under warming climate conditions. Only a few studies have addressed the mechanism of climate impact on the increase of northern lake methane emissions. This study uses a large observational dataset of lake methane concentrations in Finland to constrain methane emissions with an extant process-based lake biogeochemical model. We found that the total current diffusive emission from Finnish lakes is 0.12 ± 0.03 Tg CH _4 yr ^−1 and will increase by 26%–59% by the end of this century depending on different warming scenarios. We discover that while warming lake water and sediment temperature plays an important role, the climate impact on ice-on periods is a key indicator of future emissions. We conclude that these boreal lakes remain a significant methane source under the warming climate within this century.

As the permafrost region warms, its large organic carbon pool will be increasingly vulnerable to decomposition, combustion, and hydrologic export. Models predict that some portion of this release will be offset by increased production of Arctic and boreal biomass; however, the lack of robust estimates of net carbon balance increases the risk of further overshooting international emissions targets. Precise empirical or model-based assessments of the critical factors driving carbon balance are unlikely in the near future, so to address this gap, we present estimates from 98 permafrost-region experts of the response of biomass, wildfire, and hydrologic carbon flux to climate change. Results suggest that contrary to model projections, total permafrost-region biomass could decrease due to water stress and disturbance, factors that are not adequately incorporated in current models. Assessments indicate that end-of-the-century organic carbon release from Arctic rivers and collapsing coastlines could increase by 75% while carbon loss via burning could increase four-fold. Experts identified water balance, shifts in vegetation community, and permafrost degradation as the key sources of uncertainty in predicting future system response. In combination with previous findings, results suggest the permafrost region will become a carbon source to the atmosphere by 2100 regardless of warming scenario but that 65%–85% of permafrost carbon release can still be avoided if human emissions are actively reduced.

Aim: Atrial fibrillation (AF) detection is challenging because it is often asymptomatic and paroxysmal. We evaluated continuous photoplethysmogram (PPG) for signal quality and detection of AF.Methods: PPGs were recorded using a wrist-band device in 173 patients (76 AF, 97 sinus rhythm, SR) for 24 h. Simultaneously recorded 3-lead ambulatory ECG served as control. The recordings were split into 10-, 20-, 30-, and 60-min time-frames. The sensitivity, specificity, and F1-score of AF detection were evaluated for each time-frame. AF alarms were generated to simulate continuous AF monitoring. Sensitivities, specificities, and positive predictive values (PPVs) of the alarms were evaluated. User experiences of PPG and ECG recordings were assessed. The study was registered in the Clinical Trials database (NCT03507335).Results: The quality of PPG signal was better during night-time than in daytime (67.3 ± 22.4% vs. 30.5 ± 19.4%, p

Cork oak woodlands (montado) are agroforestry systems distributed all over the Mediterranean basin with a very important social, economic and ecological value. A generalized cork oak decline has been occurring in the last decades jeopardizing its future sustainability. It is unknown how loss of tree cover affects microbial processes that are consuming greenhouse gas fluxes in the montado ecosystem. The study was conducted under two different conditions in the natural understory of a cork oak woodland in center Portugal: under tree canopy (UC) and open areas without trees (OA). Fluxes of methane and nitrous oxide were measured with a static chamber technique. In order to quantify methanotrophs and bacteria capable of nitrous oxide consumption, we used quantitative real-time PCR targeting the pmoA and nosZ gene encoding the subunit of particulate methane mono-oxygenase and catalytic subunit of the nitrous oxide reductase, respectively. A significant seasonal effect was found on CH4 and N2O fluxes and pmoA and nosZ gene abundance. Tree cover had no effect on methane fluxes; conversely, whereas the UC plots were net emitters of nitrous oxide, the loss of tree cover resulted in a shift in the emission pattern such that the OA plots were a net sink for nitrous oxide. In a seasonal time scale, the UC had higher gene abundance of Type I methanotrophs. Methane flux correlated negatively with abundance of Type I methanotrophs in the UC plots. Nitrous oxide flux correlated negatively with nosZ gene abundance at the OA plots in contrast to that at the UC plots. In the UC soil, SOM had a positive effect on soil extracellular enzyme activities (EEA), which correlated positively with the N2O flux. Our results demonstrated that tree cover affects soil properties, key enzyme activities and abundance of microorganisms and, consequently net CH4 and N2O exchange.

We studied the sources, compositions and size distributions of aerosol particles during long-range transport (LRT) PM2.5 episodes which occurred on 12–15 August, 26–28 August and 5–6 September 2002 in Finland. Backward air mass trajectories, satellite detections of fire areas and dispersion modelling results indicate that emissions from wildfires in Russia and other Eastern European countries arrived in Finland during these episodes. Elemental analyses using scanning electron microscopy (SEM) coupled with energy dispersive X-ray microanalyses (EDX) showed that the proportions of S-rich particles and agglomerates (agglomeration was caused partly by the sampling method used) increased during the episodes, and they contained elevated fractions of K, indicating emissions from biomass burning. These aerosols were mixed with S-rich emissions from fossil fuel burning during transport since air masses came through polluted areas of Europe. Minor amounts of coarse Ca-rich particles were also brought by LRT during the episodes, and they probably originated from wildfires and/or from Estonian and Russian oil-shale-burning industrial areas. Ion chromatography analysis showed that concentrations of sulphate (SO42-), total nitrate (NO3-+HNO3(g)) and total ammonium (NH4++NH3(g)) increased during the episodes, but the ratio of the total amount of these ions to PM10 concentration decreased, indicating unusually high fractions of other chemical components. Particle number size distribution measurements with differential mobility particle sizer (DMPS) revealed that concentrations of particles 90–500 nm increased during the episodes, while concentrations of particles smaller than 90 nm decreased. The reduction of the smallest particles was caused by suppressed new particle formation due to vapour and molecular cluster uptake of LRT particles. Our results show that emissions from wildfires in Russian and other Eastern European countries deteriorated air quality of very large areas, even at distances of over 1000 km from the fire areas.

We studied methane (CH4) flux rates from experimental excreta patches on a dairy pasture with a chamber technique during snow free seasons and with a gas gradient technique during winter from timothy-meadow fescue sward with mineral N fertilization (220 kg ha-1) and from grass-white clover mixture without fertilization. The dung and urine patches were applied in June or August two consecutive grazing seasons and the measurements were carried out for a year following each application. There were no significant differences in CH4 fluxes between plant species and emissions originated mainly from the fresh dung pats. The average annual CH4 fluxes from the control sites without excreta were -0.60±0.1 and with the excreta 0.47±0.3 kg CH4 ha-1. Thus, excreta originating from dairy cows can turn boreal swards from weak sinks to small sources of CH4. However, these emissions are only 0.2% of the total CH4 emissions from a dairy cow.

Methane is the second most abundant greenhouse gas in the atmosphere. A major part of the total methane emissions from lake ecosystems are emitted from littoral wetlands. Methane emissions are significantly reduced by methanotrophs as they use methane as the sole energy and carbon source. Function of methanotrophs can be either activated or suppressed by nitrogen. However, the effects of nitrogen on methanotrophs in littoral wetlands are unknown. Here we report how nitrogen loading in situ affected the function and diversity of methanotrophs in a littoral wetland. Methanotrophic community composition and functional diversity were analyzed with particulate methane monooxygenase (pmoA) gene targeted microarray. Nitrogen load had no effects on methane oxidation potential and methane fluxes. Nitrogen load activated pmoA gene transcription of type I (Methylobacter, Methylomonas and LW21-freshwater phylotypes) methanotrophs, but decreased the relative abundance of type II (Methylocystis, Methylosinus trichosporium and Methylosinus phylotypes) methanotrophs. Hence, the overall activity of a methanotroph community in littoral wetlands is unlikely to be affected by nitrogen leached from the catchment area.