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Particle size is one of the key factors influencing how aerosol particles affect their climate and health effects. Therefore, a better understanding of particle size distributions from various sources is crucial. In urban environments, aerosols are produced in a large number of varying processes and conditions. This study intended to develop the source apportionment of urban aerosols by utilising a novel approach to positive matrix factorisation (PMF). The particle source profiles were detected in particle number size distribution data measured simultaneously in a street canyon and at a nearby urban background station between February 2015 and June 2019 in Helsinki, southern Finland. The novelty of the method is combining the data from both sites and finding profiles for the unified data. Five aerosol sources were found. Four of them were detected at both of the stations: slightly aged traffic (TRA2), secondary combustion aerosol (SCA), secondary aerosol (SecA), and long-range-transported aerosol (LRT). One of the sources, fresh traffic (TRA1) was only detected at a street canyon. The factors were identified based on available auxiliary data. Additionally, the trends of the found factors were studied, and statistically significant decreasing trends were found for TRA1 and SecA. A statistically significant increasing trend was found for TRA2. This work implies that traffic-related aerosols remain important in urban environments and that aerosol sources can be detected using only particle number size distribution data as input in the PMF method.

Soil moisture plays a key role in soil nutrient and carbon cycling; plant productivity; and energy, water, and greenhouse gas exchanges between the land and the atmosphere. The knowledge on drivers of spatiotemporal soil moisture dynamics in subarctic landscapes is limited. In this study, we used the Spatial Forest Hydrology (SpaFHy) model, in situ soil moisture data, and Sentinel-1 synthetic aperture radar (SAR)-based soil moisture estimates to explore spatiotemporal controls of soil moisture in a subarctic headwater catchment in northwestern Finland. The role of groundwater dynamics and lateral flow in soil moisture was studied through three groundwater model conceptualizations: (i) omission of groundwater storage and lateral flow, (ii) conceptual TOPMODEL approach based on topographic wetness index, and (iii) explicit 2D lateral groundwater flow. The model simulations were compared against continuous point soil moisture measurements, distributed manual measurements, and novel SAR-based soil moisture estimates available at high spatial and temporal resolutions. Based on model scenarios and model–data comparisons, we assessed when and where the lateral groundwater flow shapes shallow soil moisture and under which conditions soil moisture variability is driven more by local ecohydrology, i.e., the balance of infiltration, drainage, and evapotranspiration. The choice of groundwater flow model was shown to have a strong impact on modeled soil moisture dynamics within the catchment. All model conceptualizations captured the observed soil moisture dynamics in the upland forests, but accounting for the lateral groundwater flow was necessary to reproduce the saturated conditions common in the peatlands and occasionally in lowland forest grid cells. We further highlight the potential of integrating multi-scale observations with land surface and hydrological models. The results have implications for ecohydrological and biogeochemical processes, as well as for modeling hydrology and Earth system feedbacks in subarctic and boreal environments.

Oceans alleviate the accumulation of atmospheric CO2 by absorbing approximately a quarter of all anthropogenic emissions. In the deep oceans, carbon uptake is dominated by aquatic phase chemistry, whereas in biologically active coastal seas the marine ecosystem and biogeochemistry play an important role in the carbon uptake. Coastal seas are hotspots of organic and inorganic matter transport between the land and the oceans, and thus they are important for the marine carbon cycling. In this study, we investigate the net air–sea CO2 exchange at the Utö Atmospheric and Marine Research Station, located at the southern edge of the Archipelago Sea within the Baltic Sea, using the data collected during 2017–2021. The air–sea fluxes of CO2 were measured using the eddy covariance technique, supported by the flux parameterization based on the pCO2 and wind speed measurements. During the spring–summer months (April–August), the sea was gaining carbon dioxide from the atmosphere, with the highest monthly sink fluxes typically occurring in May, being −0.26 µmol m−2 s−1 on average. The sea was releasing the CO2 to the atmosphere in September–March, and the highest source fluxes were typically observed in September, being 0.42 µmol m−2 s−1 on average. On an annual basis, the study region was found to be a net source of atmospheric CO2, and on average, the annual net exchange was 27.1 gC m−1 yr−1, which is comparable to the exchange observed in the Gulf of Bothnia, the Baltic Sea. The annual net air–sea CO2 exchanges varied between 18.2 (2018) and 39.1 gC m−1 yr−1 (2017). During the coldest year, 2017, the spring–summer sink fluxes remained low compared to the other years, as a result of relatively high seawater pCO2 in summer, which never fell below 220 µatm during that year. The spring–summer phytoplankton blooms of 2017 were weak, possibly due to the cloudy summer and deeply mixed surface layer, which restrained the photosynthetic fixation of dissolved inorganic carbon in the surface waters. The algal blooms in spring–summer 2018 and the consequent pCO2 drawdown were strong, fueled by high pre-spring nutrient concentrations. The systematic positive annual CO2 balances suggest that our coastal study site is affected by carbon flows originating from elsewhere, possibly as organic carbon, which is remineralized and released to the atmosphere as CO2. This coastal source of CO2 fueled by the organic matter originating probably from land ecosystems stresses the importance of understanding the carbon cycling in the land–sea continuum.

The urgent need to mitigate climate change has evoked a broad interest in better understanding and estimating nitrous oxide (N2O) emissions from different ecosystems. Part of the uncertainty in N2O emission estimates still comes from an inadequate understanding of the temporal and small-scale spatial variability of N2O fluxes. Using 4.5 years of N2O flux data collected in a drained peatland forest with six automated chambers, we explored temporal and small-scale spatial variability of N2O fluxes. A random forest with conditional inference trees was used to find immediate and delayed relationships between N2O flux and environmental conditions across seasons and years. The spatiotemporal variation of the N2O flux was large, with daily mean N2O flux varying between −10 and +1760 µgN2Om-2h-1 and annual N2O budgets of different chambers between +60 and +2110 mgN2Om-2yr-1. Spatial differences in fluxes persisted through years of different environmental conditions. Soil moisture, water table level, and air temperature were the most important variables explaining the temporal variation of N2O fluxes. N2O fluxes responded to precipitation events with peak fluxes measured on average 4 d after peaks in soil moisture and water table level. The length of the time lags varied in space and between seasons indicating possible interactions with temperature and other soil conditions. The high temporal variation in N2O flux was related to (a) temporal variation in environmental conditions, with the highest N2O fluxes measured after summer precipitation events and winter soil freezing, and (b) to annually varying seasonal weather conditions, with the highest N2O emissions measured during wet summers and winters with discontinuous snow cover. Climate change may thus increase winter N2O emissions, which may be offset by lower summer N2O emissions in dry years. The high sensitivity of N2O fluxes to seasonal weather conditions suggests increasing variability in annual peatland forest N2O budgets as the frequency of extreme weather events, such as droughts, is predicted to increase.

The snowpack has a major influence on the land surface energy budget. Accurate simulation of the snowpack energy and radiation budget is challenging due to, e.g., effects of vegetation and topography, as well as limitations in the theoretical understanding of turbulent transfer in the stable boundary layer. Studies that evaluate snow, hydrology and land surface models against detailed observations of all surface energy balance components at high latitudes are scarce. In this study, we compared different configurations of the SURFEX land surface model against surface energy flux, snow depth and soil temperature observations from four eddy-covariance stations in Finland. The sites cover two different climate and snow conditions, representing the southern and northern subarctic zones, as well as the contrasting forest and peatland ecosystems typical for the boreal landscape. We tested different turbulent flux parameterizations implemented in the Crocus snowpack model. In addition, we examined common alternative approaches to conceptualize soil and vegetation, and we assessed their performance in simulating surface energy fluxes, snow conditions and soil thermal regime. Our results show that a stability correction function that increases the turbulent exchange under stable atmospheric conditions is imperative to simulate sensible heat fluxes over the peatland snowpacks and that realistic peat soil texture (soil organic content) parameterization greatly improves the soil temperature simulations. For accurate simulations of surface energy fluxes, snow and soil conditions in forests, an explicit vegetation representation is necessary. Moreover, we demonstrate the high sensitivity of surface fluxes to a poorly documented parameter involved in snow cover fraction computation. Although we focused on models within the SURFEX platform, the results have broader implications for choosing suitable turbulent flux parameterization and model structures depending on the potential use cases for high-latitude land surface modeling.

Condensable vapors, including highly oxygenated organic molecules (HOMs), govern secondary organic aerosol formation and thereby impact the quantity, composition, and properties (e.g., toxicity) of aerosol particles. These vapors are mainly formed in the atmosphere through the oxidation of volatile organic compounds (VOCs). Urban environments contain a variety of VOCs from both anthropogenic and biogenic sources, as well as other species, for instance nitrogen oxides (NOx), that can greatly influence the formation pathways of condensable vapors like HOMs. During the last decade, our understanding of HOM composition and formation has increased dramatically, with most experiments performed in forests or in heavily polluted urban areas. However, studies on the main sources for condensable vapors and secondary organic aerosols (SOAs) in biogenically influenced urban areas, such as suburbs or small cities, have been limited. Here, we studied the HOM composition, measured with two nitrate-based chemical ionization mass spectrometers and analyzed using positive matrix factorization (PMF), during late spring at two locations in Helsinki, Finland. Comparing the measured concentrations at a street canyon site and a nearby urban background station, we found a strong influence of NOx on the HOM formation at both stations, in agreement with previous studies conducted in urban areas. Even though both stations are dominated by anthropogenic VOCs, most of the identified condensable vapors originated from biogenic precursors. This implies that in Helsinki anthropogenic activities mainly influence HOM formation by the effect of NOx on the biogenic VOC oxidation. At the urban background station, we found condensable vapors formed from two biogenic VOC groups (monoterpenes and sesquiterpenes), while at the street canyon, the only identified biogenic HOM precursor was monoterpenes. At the street canyon, we also observed oxidation products of aliphatic VOCs, which were not observed at the urban background station. The only factors that clearly correlate (temporally and composition-wise) between the two stations contained monoterpene-derived dimers. This suggests that HOM composition and formation mechanisms are strongly dependent on localized emissions and the oxidative environment in these biogenically influenced urban areas, and they can also change considerably within distances of 1 km within the urban environment. This further suggests that studies should be careful when extrapolating single-point measurements in an urban setting to be representative of district or city scales.

Urban air consists of a complex mixture of gaseous and particulate species from anthropogenic and biogenic sources that are further processed in the atmosphere. This study investigated the characteristics and sources of volatile organic compounds (VOCs) and submicron organic aerosol (OA) in a traffic environment in Helsinki, Finland, in late summer. The anthropogenic VOCs (aVOCs; aromatic hydrocarbons) and biogenic VOCs (bVOCs; terpenoids) relevant for secondary-organic-aerosol formation were analyzed with an online gas chromatograph mass spectrometer, whereas the composition and size distribution of submicron particles was measured with a soot particle aerosol mass spectrometer. This study showed that aVOC concentrations were significantly higher than bVOC concentrations in the traffic environment. The largest aVOC concentrations were measured for toluene (campaign average of 1630 ng m−3) and p/m xylene (campaign average of 1070 ng m−3), while the dominating bVOC was α-pinene (campaign average of 200 ng m−3). For particle-phase organics, the campaign-average OA concentration was 2.4 µg m−3. The source apportionment analysis extracted six factors for OA. Three OA factors were related to primary OA sources – traffic (24 % of OA, two OA types) and a coffee roastery (7 % of OA) – whereas the largest fraction of OA (69 %) consisted of oxygenated OA (OOA). OOA was divided into less oxidized semi-volatile OA (SV-OOA; 40 % of OA) and two types of low-volatility OA (LV-OOA; 30 %). The focus of this research was also on the oxidation potential of the measured VOCs and the association between VOCs and OA in ambient air. Production rates of the oxidized compounds (OxPR) from the VOC reactions revealed that the main local sources of the oxidation products were O3 oxidation of bVOCs (66 % of total OxPR) and OH radical oxidation of aVOCs and bVOCs (25 % of total OxPR). Overall, aVOCs produced a much smaller portion of the oxidation products (18 %) than bVOCs (82 %). In terms of OA factors, SV-OOA was likely to originate from biogenic sources since it correlated with an oxidation product of monoterpene, nopinone. LV-OOA consisted of highly oxygenated long-range or regionally transported OA that had no correlation with local oxidant concentrations as it had already spent several days in the atmosphere before reaching the measurement site. In general, the main sources were different for VOCs and OA in the traffic environment. Vehicle emissions impacted both VOC and OA concentrations. Due to the specific VOCs attributed to biogenic emissions, the influence of biogenic emissions was more clearly detected in the VOC concentrations than in OA. In contrast, the emissions from the local coffee roastery had a distinctive mass spectrum for OA, but they could not be seen in the VOC measurements due to the measurement limitations for the large VOC compounds. Long-range transport increased the OA concentration and oxidation state considerably, while its effect was observed less clearly in the VOC measurements due to the oxidation of most VOC in the atmosphere during the transport. Overall, this study revealed that in order to properly characterize the impact of different emission sources on air quality, health, and climate, it is of importance to describe both gaseous and particulate emissions and understand how they interact as well as their phase transfers in the atmosphere during the aging process.

The subarctic landscape consists of a mosaic of forest, peatland, and aquatic ecosystems and their ecotones. The carbon (C) exchange between ecosystems and the atmosphere through carbon dioxide (CO2) and methane (CH4) fluxes varies spatially and temporally among these ecosystems. Our study area in Kaamanen in northern Finland covered 7 km2 of boreal subarctic landscape with upland forest, open peatland, pine bogs, and lakes. We measured the CO2 and CH4 fluxes with eddy covariance and chambers between June 2017 and June 2019 and studied the C flux responses to varying meteorological conditions. The landscape area was an annual CO2 sink of −45 ± 22 and −33 ± 23 g C m−2 and a CH4 source of 3.0 ± 0.2 and 2.7 ± 0.2 g C m−2 during the first and second study years, respectively. The pine forest had the largest contribution to the landscape-level CO2 sink, −126 ± 21 and −101 ± 19 g C m−2, and the fen to the CH4 emissions, 7.8 ± 0.2 and 6.3 ± 0.3 g C m−2, during the first and second study years, respectively. The lakes within the area acted as CO2 and CH4 sources to the atmosphere throughout the measurement period, and a lake located downstream from the fen with organic sediment showed 4-fold fluxes compared to a mineral sediment lake. The annual C balances were affected most by the rainy peak growing season in 2017, the warm summer in 2018, and a heatwave and drought event in July 2018. The rainy period increased ecosystem respiration (ER) in the pine forest due to continuously high soil moisture content, and ER was on a level similar to the following, notably warmer, summer. A corresponding ER response to abundant precipitation was not observed for the fen ecosystem, which is adapted to high water table levels, and thus a higher ER sum was observed during the warm summer 2018. During the heatwave and drought period, similar responses were observed for all terrestrial ecosystems, with decreased gross primary productivity and net CO2 uptake, caused by the unfavourable growing conditions and plant stress due to the soil moisture and vapour pressure deficits. Additionally, the CH4 emissions from the fen decreased during and after the drought. However, the timing and duration of drought effects varied between the fen and forest ecosystems, as C fluxes were affected sooner and had a shorter post-drought recovery time in the fen than forest. The differing CO2 flux response to weather variations showed that terrestrial ecosystems can have a contrasting impact on the landscape-level C balance in a changing climate, even if they function similarly most of the time.

The role of precipitation (P) variability with respect to evapotranspiration (ET) and its two components, transpiration (T) and evaporation (E), from savannas continues to draw significant research interest given its relevance to a number of ecohydrological applications. Our study reports on 6 years of measured ET and estimated T and E from a grazed savanna grassland at Welgegund, South Africa. Annual P varied significantly with respect to amount (508 to 672 mm yr−1), with dry years characterized by infrequent early-season rainfall. T was determined using annual water-use efficiency and gross primary production estimates derived from eddy-covariance measurements of latent heat flux and net ecosystem CO2 exchange rates. The computed annual T for the 4 wet years with frequent early wet-season rainfall was nearly constant, 326±19 mm yr−1 (T/ET=0.51), but was lower and more variable between the 2 dry years (255 and 154 mm yr−1, respectively). Annual T and T/ET were linearly related to the early wet-season storm frequency. The constancy of annual T during wet years is explained by the moderate water stress of C4 grasses as well as trees' ability to use water from deeper layers. During extreme drought, grasses respond to water availability with a dieback–regrowth pattern, reducing leaf area and transpiration and, thus, increasing the proportion of transpiration contributed by trees. The works suggest that the early-season P distribution explains the interannual variability in T, which should be considered when managing grazing and fodder production in these grasslands.

Vegetation phenology, which refers to the seasonal changes in plant physiology, biomass and plant cover, is affected by many abiotic factors, such as precipitation, temperature and water availability. Phenology is also associated with the carbon dioxide (CO2) exchange between ecosystems and the atmosphere. We employed digital cameras to monitor the vegetation phenology of three northern boreal peatlands during five growing seasons. We derived a greenness index (green chromatic coordinate, GCC) from the images and combined the results with measurements of CO2 flux, air temperature and high-resolution satellite data (Sentinel-2). From the digital camera images it was possible to extract greenness dynamics on the vegetation community and even species level. The highest GCC and daily maximum gross photosynthetic production (GPPmax) were observed at the site with the highest nutrient availability and richest vegetation. The short-term temperature response of GCC depended on temperature and varied among the sites and months. Although the seasonal development and year-to-year variation in GCC and GPPmax showed consistent patterns, the short-term variation in GPPmax was explained by GCC only during limited periods. GCC clearly indicated the main phases of the growing season, and peatland vegetation showed capability to fully compensate for the impaired growth resulting from a late growing season start. The GCC data derived from Sentinel-2 and digital cameras showed similar seasonal courses, but a reliable timing of different phenological phases depended upon the temporal coverage of satellite data.

Understanding chemical processes leading to the formation of atmospheric aerosol particles is crucial to improve our capabilities in predicting the future climate. However, those mechanisms are still inadequately characterized, especially in polar regions. In this study, we report observations of neutral and charged aerosol precursor molecules and chemical cluster composition (qualitatively and quantitatively), as well as air ions and aerosol particle number concentrations and size distributions from the Marambio research station (64∘15′ S, 56∘38′ W), located north of the Antarctic Peninsula. We conducted measurements during the austral summer, between 15 January and 25 February 2018. The scope of this study is to characterize new particle formation (NPF) event parameters and connect our observations of gas-phase compounds with the formation of secondary aerosols to resolve the nucleation mechanisms at the molecular scale. NPF occurred on 40 % of measurement days. All NPF events were observed during days with high solar radiation, mostly with above-freezing temperatures and with low relative humidity. The averaged formation rate for 3 nm particles (J3) was 0.686 cm−3 s−1, and the average particle growth rate (GR3.8–12 nm) was 4.2 nm h−1. Analysis of neutral aerosol precursor molecules showed measurable concentrations of iodic acid (IA), sulfuric acid (SA), and methane sulfonic acid (MSA) throughout the entire measurement period with significant increase in MSA and SA concentrations during NPF events. We highlight SA as a key contributor to NPF processes, while IA and MSA likely only contribute to particle growth. Mechanistically, anion clusters containing ammonia and/or dimethylamine (DMA) and SA were identified, suggesting significant concentration of ammonia and DMA as well. Those species are likely contributing to NPF events since SA alone is not sufficient to explain observed nucleation rates. Here, we provide evidence of the marine origin of the measured chemical precursors and discuss their potential contribution to the aerosol phase.

Arctic tundra is facing unprecedented warming, resulting in shifts in the vegetation, thaw regimes, and potentially in the ecosystem–atmosphere exchange of carbon (C). However, the estimates of regional carbon dioxide (CO2) and methane (CH4) budgets are highly uncertain. We measured CO2 and CH4 fluxes, vegetation composition and leaf area index (LAI), thaw depth, and soil wetness in Tiksi (71∘ N, 128∘ E), a heterogeneous site located within the prostrate dwarf-shrub tundra zone in northeastern Siberia. Using the closed chamber method, we determined the net ecosystem exchange (NEE) of CO2, ecosystem respiration in the dark (ER), ecosystem gross photosynthesis (Pg), and CH4 flux during the growing season. We applied a previously developed high-spatial-resolution land cover map over an area of 35.8 km2 for spatial extrapolation. Among the land cover types varying from barren to dwarf-shrub tundra and tundra wetlands, the NEE and Pg at the photosynthetically active photon flux density of 800 µmol m−2 h−1 (NEE800 and Pg800) were greatest in the graminoid-dominated habitats, i.e., streamside meadow and fens, with NEE800 and Pg800 of up to −21 (uptake) and 28 mmol m−2 h−1, respectively. Vascular LAI was a robust predictor of both NEE800 and Pg800 and, on a landscape scale, the fens were disproportionately important for the summertime CO2 sequestration. Dry tundra, including the dwarf-shrub and lichen tundra, had smaller CO2 exchange rates. The fens were the largest source of CH4, while the dry mineral soil tundra consumed atmospheric CH4, which on a landscape scale amounted to −9 % of the total CH4 balance during the growing season. The largest seasonal mean CH4 consumption rate of 0.02 mmol m−2 h−1 occurred in sand- and stone-covered barren areas. The high consumption rate agrees with the estimate based on the eddy covariance measurements at the same site. We acknowledge the uncertainty involved in spatial extrapolations due to a small number of replicates per land cover type. This study highlights the need to distinguish different land cover types including the dry tundra habitats to account for their different CO2 and CH4 flux patterns, especially the consumption of atmospheric CH4, when estimating tundra C exchange on a larger spatial scale.

In the global methane budget, the largest natural source is attributed to wetlands, which encompass all ecosystems composed of waterlogged or inundated ground, capable of methane production. Among them, northern peatlands that store large amounts of soil organic carbon have been functioning, since the end of the last glaciation period, as long-term sources of methane (CH4) and are one of the most significant methane sources among wetlands. To reduce uncertainty of quantifying methane flux in the global methane budget, it is of significance to understand the underlying processes for methane production and fluxes in northern peatlands. A methane model that features methane production and transport by plants, ebullition process and diffusion in soil, oxidation to CO2, and CH4 fluxes to the atmosphere has been embedded in the ORCHIDEE-PEAT land surface model that includes an explicit representation of northern peatlands. ORCHIDEE-PCH4 was calibrated and evaluated on 14 peatland sites distributed on both the Eurasian and American continents in the northern boreal and temperate regions. Data assimilation approaches were employed to optimized parameters at each site and at all sites simultaneously. Results show that methanogenesis is sensitive to temperature and substrate availability over the top 75 cm of soil depth. Methane emissions estimated using single site optimization (SSO) of model parameters are underestimated by 9 g CH4 m−2 yr−1 on average (i.e., 50 % higher than the site average of yearly methane emissions). While using the multi-site optimization (MSO), methane emissions are overestimated by 5 g CH4 m−2 yr−1 on average across all investigated sites (i.e., 37 % lower than the site average of yearly methane emissions).

Aerosol particles play an important role in the microphysics of clouds and hence in their likelihood to precipitate. In the changing climate already-dry areas such as the United Arab Emirates (UAE) are predicted to become even drier. Comprehensive observations of the daily and seasonal variation in aerosol particle properties in such locations are required, reducing the uncertainty in such predictions. We analyse observations from a 1-year measurement campaign at a background location in the United Arab Emirates to investigate the properties of aerosol particles in this region, study the impact of boundary layer mixing on background aerosol particle properties measured at the surface, and study the temporal evolution of the aerosol particle cloud formation potential in the region. We used in situ aerosol particle measurements to characterise the aerosol particle composition, size, number, and cloud condensation nuclei (CCN) properties; in situ SO2 measurements as an anthropogenic signature; and a long-range scanning Doppler lidar to provide vertical profiles of the horizontal wind and turbulent properties to monitor the evolution of the boundary layer. Anthropogenic sulfate dominated the aerosol particle mass composition in this location. There was a clear diurnal cycle in the surface wind direction, which had a strong impact on aerosol particle total number concentration, SO2 concentration, and black carbon mass concentration. Local sources were the predominant source of black carbon as concentrations clearly depended on the presence of turbulent mixing, with much higher values during calm nights. The measured concentrations of SO2, instead, were highly dependent on the surface wind direction as well as on the depth of the boundary layer when entrainment from the advected elevated layers occurred. The wind direction at the surface or of the elevated layer suggests that the oil refineries and the cities of Dubai and Abu Dhabi and other coastal conurbations were the remote sources of SO2. We observed new-aerosol-particle formation events almost every day (on 4 d out of 5 on average). Calm nights had the highest CCN number concentrations and lowest κ values and activation fractions. We did not observe any clear dependence of CCN number concentration and κ parameter on the height of the daytime boundary layer, whereas the activation fraction did show a slight increase with increasing boundary layer height due to the change in the shape of the aerosol particle size distribution where the relative portion of larger aerosol particles increased with increasing boundary layer height. We believe that this indicates that size is more important than chemistry for aerosol particle CCN activation at this site. The combination of instrumentation used in this campaign enabled us to identify periods when anthropogenic pollution from remote sources that had been transported in elevated layers was present and had been mixed down to the surface in the growing boundary layer.

Past efforts to synthesize and quantify the magnitude and change in carbon dioxide (CO2) fluxes in terrestrial ecosystems across the rapidly warming Arctic–boreal zone (ABZ) have provided valuable information but were limited in their geographical and temporal coverage. Furthermore, these efforts have been based on data aggregated over varying time periods, often with only minimal site ancillary data, thus limiting their potential to be used in large-scale carbon budget assessments. To bridge these gaps, we developed a standardized monthly database of Arctic–boreal CO2 fluxes (ABCflux) that aggregates in situ measurements of terrestrial net ecosystem CO2 exchange and its derived partitioned component fluxes: gross primary productivity and ecosystem respiration. The data span from 1989 to 2020 with over 70 supporting variables that describe key site conditions (e.g., vegetation and disturbance type), micrometeorological and environmental measurements (e.g., air and soil temperatures), and flux measurement techniques. Here, we describe these variables, the spatial and temporal distribution of observations, the main strengths and limitations of the database, and the potential research opportunities it enables. In total, ABCflux includes 244 sites and 6309 monthly observations; 136 sites and 2217 monthly observations represent tundra, and 108 sites and 4092 observations represent the boreal biome. The database includes fluxes estimated with chamber (19 % of the monthly observations), snow diffusion (3 %) and eddy covariance (78 %) techniques. The largest number of observations were collected during the climatological summer (June–August; 32 %), and fewer observations were available for autumn (September–October; 25 %), winter (December–February; 18 %), and spring (March–May; 25 %). ABCflux can be used in a wide array of empirical, remote sensing and modeling studies to improve understanding of the regional and temporal variability in CO2 fluxes and to better estimate the terrestrial ABZ CO2 budget. ABCflux is openly and freely available online (Virkkala et al., 2021b, https://doi.org/10.3334/ORNLDAAC/1934).

This study investigated the sources of black carbon (BC) at two contrasting urban environments in Helsinki, Finland: residential area and street canyon. The measurement campaign in the residential area was conducted in winter–spring 2019, whereas in the street canyon the measurements were carried out in autumn 2015. The sources of BC were explored by using positive matrix factorization (PMF) for the organic and refractory black carbon (rBC) mass spectra collected with a soot particle aerosol mass spectrometer (SP-AMS). Based on the PMF analysis, two sites had different local BC sources; the largest fraction of BC originated from biomass burning at the residential site (38 %) and from the vehicular emissions in the street canyon (57 %). Also, the mass size distribution of BC diverged at the sites as BC from traffic was found at the particle size of ∼100–150 nm whereas BC from biomass combustion was detected at ∼300 nm. At both sites, a large fraction of BC was associated with urban background or long-range-transported BC indicated by the high oxidation state of organics related to those PMF factors. The results from the PMF analysis were compared with the source apportionment from the Aethalometer model calculated with two pairs of absorption Ångström values. It was found that several PMF factors can be attributed to wood combustion and fossil fuel fraction of BC provided by the Aethalometer model. In general, the Aethalometer model showed less variation between the sources within a day than PMF, indicating that it was less responsive to the fast changes in the BC sources at the site, or it could not distinguish between as many sources as PMF due to the similar optical properties of the BC sources. The results of this study increase understanding of the limitations and validity of the BC source apportionment methods in different environments. Moreover, this study advances the current knowledge of BC sources and especially the contribution of residential combustion in urban areas.

Most of the anthropogenic air pollution sources are located in urban environments. The contribution of these sources to the population of atmospheric particles in the urban environment is poorly known. In this study, we investigated the aerosol particle number concentrations in a diameter range from 1 to 800 nm at a street canyon site and at a background station within 1 km from each other in Helsinki, Finland. We use these number size distribution data together with complementary trace gas data and develop a method to estimate the relative contributions of traffic and atmospheric new particle formation (NPF) to the concentrations of sub-3 nm particles. During the daytime, the particle concentrations were higher at the street canyon site than at the background station in all analyzed modes: sub-3 nm particles, nucleation mode (3–25 nm), Aitken mode (25–100 nm), and accumulation mode (100–800 nm). The population of sub-3 nm and nucleation mode particles was linked to local sources such as traffic, while the accumulation mode particles were more related to non-local sources. Aitken mode particles were dominated by local sources at the street canyon site, while at the background station they were mainly influenced by non-local sources. The results of this study support earlier research showing direct emissions of the sub-3 nm particles from traffic. However, by using our new method, we show that, during NPF events, traffic contribution to the total sub-3 nm particle concentration can be small and during daytime (6:00–20:00) in spring it does not dominate the sub-3 nm particle population at either of the researched sites. In the future, the contribution of traffic to particle number concentrations in different urban environments can be estimated with a similar approach, but determining the relationships between the gas and particle concentrations from observations needs to be conducted with longer data sets from different urban environments.

Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions due to quasi-continuous and high-temporal-resolution CH4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20∘ S to 20∘ N) the spring onset of elevated CH4 emissions starts 3 d earlier, and the CH4 emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH4 emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH4 modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH4 cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.

Atmospheric aerosols play an important role in air pollution. Aerosol particle chemical composition is highly variable depending on the season, hour of the day, day of the week, meteorology, and location of the measurement site. Long measurement periods and highly time-resolved data are required in order to achieve a statistically relevant amount of data for assessing those variations and evaluating pollution episodes. In this study, we present continuous atmospheric PM1 (particulate matter < 1 µm) concentration and composition measurements at an urban street canyon site located in Helsinki, Finland. The study was performed for 4.5 years (2015–2019) and involved highly time-resolved measurements by taking advantage of a suite of online state-of-the-art instruments such as an aerosol chemical speciation monitor (ACSM), a multi-angle absorption photometer (MAAP), a differential mobility particle sizer (DMPS), and an Aethalometer (AE). PM1 consisted mostly of organics, with mean mass concentrations of 2.89 µg m−3 (53 % of PM1) followed by inorganic species (1.56 µg m−3, 29 %) and equivalent black carbon (eBC, 0.97 µg m−3, 18 %). A trend analysis revealed a decrease in BC from fossil fuel (BCFF), organics, and nitrate over the studied years. Clear seasonal and/or diurnal variations were found for the measured atmospheric PM1 constituents. Particle number and mass size distributions over different seasons revealed the possible influence of secondary organic aerosols (SOAs) during summer and the dominance of ultrafine traffic aerosols during winter. The seasonality of measured constituents also impacted the particle's coating and absorptive properties. The investigation of pollution episodes observed at the site showed that a large fraction of aerosol particle mass was comprised of inorganic species during long-range transport, while during local episodes eBC and organics prevailed together with elevated particle number concentration. Overall, the results increased knowledge of the variability of PM1 concentration and composition in a Nordic traffic site and its implications on urban air quality. Considering the effects of PM mitigation policies in northern Europe in the last decades, the results obtained in this study may be considered illustrative of probable future air quality challenges in countries currently adopting similar environmental regulations.

Water flows in peatland margins is an under-researched topic. This study examines recharge from a peatland to an esker aquifer in an aapa mire complex of northern Finland. Our objective was to study how the aapa mire margin is hydrogeologically connected to the riverside aquifer and spatial and temporal variations in the recharge of peatland water to groundwater (GW). Following geophysical studies and monitoring of the saturated zone, a GW model (MODFLOW) was used in combination with stable isotopes to quantify GW flow volumes and directions. Peatland water recharge to the sandy aquifer indicated a strong connection at the peatland–aquifer boundary. Recharge volumes from peatland to esker were high and rather constant (873 m3 d−1) and dominated esker recharge at the study site. The peat water recharging the esker boundary was rich in dissolved organic carbon (DOC). Stable isotope studies on water (δ18O, δ2H, and d-excess) from GW wells verified the recharge of DOC-rich water from peatlands to mineral soil esker. Biogeochemical analysis revealed changes from DOC to dissolved inorganic carbon in the flow pathway from peatland margin to the river Kitinen. This study highlights the importance of careful investigation of aapa mire margin areas and their potential role in regional GW recharge patterns. HIGHLIGHTS Peatland water recharge to aquifer showed connection at the peatland–aquifer boundary.; Analysis revealed changes from dissolved organic carbon to dissolved inorganic carbon in groundwater flow pathway from peatland.; Connection between an aapa mire margin and riverside esker was documented.;

The patterned microtopography of subarctic mires generates a variety of environmental conditions, and carbon dioxide (CO2) and methane (CH4) dynamics vary spatially among different plant community types (PCTs). We studied the CO2 and CH4 exchange between a subarctic fen and the atmosphere at Kaamanen in northern Finland based on flux chamber and eddy covariance measurements in 2017–2018. We observed strong spatial variation in carbon dynamics between the four main PCTs studied, which were largely controlled by water table level and differences in vegetation composition. The ecosystem respiration (ER) and gross primary productivity (GPP) increased gradually from the wettest PCT to the drier ones, and both ER and GPP were larger for all PCTs during the warmer and drier growing season 2018. We estimated that in 2017 the growing season CO2 balances of the PCTs ranged from −20 g C m−2 (Trichophorum tussock PCT) to 64 g C m−2 (string margin PCT), while in 2018 all PCTs were small CO2 sources (10–22 g C m−2). We observed small growing season CH4 emissions (< 1 g C m−2) from the driest PCT, while the other three PCTs had significantly larger emissions (mean 7.9, range 5.6–10.1 g C m−2) during the two growing seasons. Compared to the annual CO2 balance (−8.5 ± 4.0 g C m−2) of the fen in 2017, in 2018 the annual balance (−5.6 ± 3.7 g C m−2) was affected by an earlier onset of photosynthesis in spring, which increased the CO2 sink, and a drought event during summer, which decreased the sink. The CH4 emissions were also affected by the drought. The annual CH4 balance of the fen was 7.3 ± 0.2 g C m−2 in 2017 and 6.2 ± 0.1 g C m−2 in 2018. Thus, the carbon balance of the fen was close to zero in both years. The PCTs that were adapted to drier conditions provided ecosystem-level resilience to carbon loss due to water level drawdown.

In this study, we present results from 12 years of black carbon (BC) measurements at 14 sites around the Helsinki metropolitan area (HMA) and at one background site outside the HMA. The main local sources of BC in the HMA are traffic and residential wood combustion in fireplaces and sauna stoves. All BC measurements were conducted optically, and therefore we refer to the measured BC as equivalent BC (eBC). Measurement stations were located in different environments that represented traffic environment, detached housing area, urban background, and regional background. The measurements of eBC were conducted from 2007 through 2018; however, the times and the lengths of the time series varied at each site. The largest annual mean eBC concentrations were measured at the traffic sites (from 0.67 to 2.64 µg m−3) and the lowest at the regional background sites (from 0.16 to 0.48 µg m−3). The annual mean eBC concentrations at the detached housing and urban background sites varied from 0.64 to 0.80 µg m−3 and from 0.42 to 0.68 µg m−3, respectively. The clearest seasonal variation was observed at the detached housing sites where residential wood combustion increased the eBC concentrations during the cold season. Diurnal variation in eBC concentration in different urban environments depended clearly on the local sources that were traffic and residential wood combustion. The dependency was not as clear for the typically measured air quality parameters, which were here NOx concentration and mass concentration of particles smaller that 2.5 µm in diameter (PM2.5). At four sites which had at least a 4-year-long time series available, the eBC concentrations had statistically significant decreasing trends that varied from −10.4 % yr−1 to −5.9 % yr−1. Compared to trends determined at urban and regional background sites, the absolute trends decreased fastest at traffic sites, especially during the morning rush hour. Relative long-term trends in eBC and NOx were similar, and their concentrations decreased more rapidly than that of PM2.5. The results indicated that especially emissions from traffic have decreased in the HMA during the last decade. This shows that air pollution control, new emission standards, and a newer fleet of vehicles had an effect on air quality.

Northern peatlands are projected to be crucial in future atmospheric methane (CH4) budgets and have a positive feedback on global warming. Fens receive nutrients from catchments via inflowing water and are more sensitive than bogs to variations in their ecohydrology. Yet, due to a lack of data detailing the impacts of moving water on microhabitats and CH4 fluxes in fens, large uncertainties remain with respect to predicting CH4 emissions from these sites under climate changes. We measured CH4 fluxes with manual chambers over three growing seasons (2017–2019) at a northern boreal fen. To address the spatial variation at the site where a stream flows through the long and narrow valley fen, we established sample plots at varying distances from the stream. To link the variations in CH4 emissions to environmental controls, we quantified water levels, peat temperature, dissolved oxygen concentration, vegetation composition, and leaf area index in combination with flux measurements during the growing season in 2019. We found that due to the flowing water, there was a higher water level, cooler peat temperatures, and more oxygen in the peat close to the stream, which also had the highest total leaf area and gross primary production (GPP) values but the lowest CH4 emissions. CH4 emissions were highest at an intermediate distance from the stream where the oxygen concentration in the surface peat was low but GPP was still high. Further from the stream, the conditions were drier and produced low CH4 emissions. Our results emphasize the key role of ecohydrology in CH4 dynamics in fens and, for the first time, show how a stream controls CH4 emissions in a flow-through fen. As valley fens are common peatland ecosystems from the Arctic to the temperate zones, future projections of global CH4 budgets need to take flowing water features into account.

We have studied biogenic volatile organic compound (BVOC) emissions and their ambient concentrations at a sub-Arctic wetland (Lompolojänkkä, Finland), which is an open, nutrient-rich sedge fen and a part of the Pallas-Sodankylä Global Atmosphere Watch (GAW) station. Measurements were conducted during the growing season in 2018 using an in situ thermal-desorption–gas-chromatograph–mass-spectrometer (TD-GC-MS). Earlier studies have shown that isoprene is emitted from boreal wetlands, and it also turned out to be the most abundant compound in the current study. Monoterpene (MT) emissions were generally less than 10 % of the isoprene emissions (mean isoprene emission over the growing season, 44 µg m−2 h−1), but sesquiterpene (SQT) emissions were higher than MT emissions all the time. The main MTs emitted were α-pinene, 1,8-cineol, myrcene, limonene and 3Δ-carene. Of SQTs cadinene, β-cadinene and α-farnesene had the major contribution. During early growing season the SQT∕MT emission rate ratio was ∼10, but it became smaller as summer proceeded, being only ∼3 in July. Isoprene, MT and SQT emissions were exponentially dependent on temperature (correlation coefficients (R2) 0.75, 0.66 and 0.52, respectively). Isoprene emission rates were also found to be exponentially correlated with the gross primary production of CO2 (R2=0.85 in July). Even with the higher emissions from the wetland, ambient air concentrations of isoprene were on average > 100, > 10 and > 6 times lower than MT concentrations in May, June and July, respectively. This indicates that wetland was not the only source affecting atmospheric concentrations at the site, but surrounding coniferous forests, which are high MT emitters, contribute as well. Daily mean MT concentrations had high negative exponential correlation (R2=0.96) with daily mean ozone concentrations indicating that vegetation emissions can be a significant chemical sink of ozone in this sub-Arctic area.

Low-cost particulate matter (PM) sensors have been under investigation as it has been hypothesized that the use of low-cost and easy-to-use sensors could allow cost-efficient extension of the currently sparse measurement coverage. While the majority of the existing literature highlights that low-cost sensors can indeed be a valuable addition to the list of commonly used measurement tools, it often reiterates that the risk of sensor misuse is still high and that the data obtained from the sensors are only representative of the specific site and its ambient conditions. This implies that there are underlying reasons for inaccuracies in sensor measurements that have yet to be characterized. The objective of this study is to investigate the particle-size selectivity of low-cost sensors. Evaluated sensors were Plantower PMS5003, Nova SDS011, Sensirion SPS30, Sharp GP2Y1010AU0F, Shinyei PPD42NS, and Omron B5W-LD0101. The investigation of size selectivity was carried out in the laboratory using a novel reference aerosol generation system capable of steadily producing monodisperse particles of different sizes (from ∼0.55 to 8.4 µm) on-line. The results of the study show that none of the low-cost sensors adhered to the detection ranges declared by the manufacturers; moreover, cursory comparison to a mid-cost aerosol size spectrometer (Grimm 1.108, 2020) indicates that the sensors can only achieve independent responses for one or two size bins, whereas the spectrometer can sufficiently characterize particles with 15 different size bins. These observations provide insight into and evidence of the notion that particle-size selectivity has an essential role in the analysis of the sources of errors in sensors.

The Station for Measuring Ecosystem–Atmosphere Relations (SMEAR) II is well known among atmospheric scientists due to the immense amount of observational data it provides of the Earth–atmosphere interface. Moreover, SMEAR II plays an important role for the large European research infrastructure, enabling the large scientific community to tackle climate- and air-pollution-related questions, utilizing the high-quality long-term data sets recorded at the site. So far, this well-documented site was missing the description of the seasonal variation in aerosol chemical composition, which helps understanding the complex biogeochemical and physical processes governing the forest ecosystem. Here, we report the sub-micrometer aerosol chemical composition and its variability, employing data measured between 2012 and 2018 using an Aerosol Chemical Speciation Monitor (ACSM). We observed a bimodal seasonal trend in the sub-micrometer aerosol concentration culminating in February (2.7, 1.6, and 5.1 µg m−3 for the median, 25th, and 75th percentiles, respectively) and July (4.2, 2.2, and 5.7 µg m−3 for the median, 25th, and 75th percentiles, respectively). The wintertime maximum was linked to an enhanced presence of inorganic aerosol species (ca. 50 %), whereas the summertime maximum (ca. 80 % organics) was linked to biogenic secondary organic aerosol (SOA) formation. During the exceptionally hot months of July of 2014 and 2018, the organic aerosol concentrations were up to 70 % higher than the 7-year July mean. The projected increase in heat wave frequency over Finland will most likely influence the loading and chemical composition of aerosol particles in the future. Our findings suggest strong influence of meteorological conditions such as radiation, ambient temperature, and wind speed and direction on aerosol chemical composition. To our understanding, this is the longest time series reported describing the aerosol chemical composition measured online in the boreal region, but the continuous monitoring will also be maintained in the future.

The impact of atmospheric reactive nitrogen (Nr) deposition on carbon (C) sequestration in soils and biomass of unfertilized, natural, semi-natural and forest ecosystems has been much debated. Many previous results of this dC∕dN response were based on changes in carbon stocks from periodical soil and ecosystem inventories, associated with estimates of Nr deposition obtained from large-scale chemical transport models. This study and a companion paper (Flechard et al., 2020) strive to reduce uncertainties of N effects on C sequestration by linking multi-annual gross and net ecosystem productivity estimates from 40 eddy covariance flux towers across Europe to local measurement-based estimates of dry and wet Nr deposition from a dedicated collocated monitoring network. To identify possible ecological drivers and processes affecting the interplay between C and Nr inputs and losses, these data were also combined with in situ flux measurements of NO, N2O and CH4 fluxes; soil NO3- leaching sampling; and results of soil incubation experiments for N and greenhouse gas (GHG) emissions, as well as surveys of available data from online databases and from the literature, together with forest ecosystem (BASFOR) modelling. Multi-year averages of net ecosystem productivity (NEP) in forests ranged from −70 to 826 g C m−2 yr−1 at total wet + dry inorganic Nr deposition rates (Ndep) of 0.3 to 4.3 g N m−2 yr−1 and from −4 to 361 g C m−2 yr−1 at Ndep rates of 0.1 to 3.1 g N m−2 yr−1 in short semi-natural vegetation (moorlands, wetlands and unfertilized extensively managed grasslands). The GHG budgets of the forests were strongly dominated by CO2 exchange, while CH4 and N2O exchange comprised a larger proportion of the GHG balance in short semi-natural vegetation. Uncertainties in elemental budgets were much larger for nitrogen than carbon, especially at sites with elevated Ndep where Nr leaching losses were also very large, and compounded by the lack of reliable data on organic nitrogen and N2 losses by denitrification. Nitrogen losses in the form of NO, N2O and especially NO3- were on average 27 % (range 6 %–54 %) of Ndep at sites with Ndep −2 yr−1 versus 65 % (range 35 %–85 %) for Ndep > 3 g N m−2 yr−1. Such large levels of Nr loss likely indicate that different stages of N saturation occurred at a number of sites. The joint analysis of the C and N budgets provided further hints that N saturation could be detected in altered patterns of forest growth. Net ecosystem productivity increased with Nr deposition up to 2–2.5 g N m−2 yr−1, with large scatter associated with a wide range in carbon sequestration efficiency (CSE, defined as the NEP ∕ GPP ratio). At elevated Ndep levels (> 2.5 g N m−2 yr−1), where inorganic Nr losses were also increasingly large, NEP levelled off and then decreased. The apparent increase in NEP at low to intermediate Ndep levels was partly the result of geographical cross-correlations between Ndep and climate, indicating that the actual mean dC∕dN response at individual sites was significantly lower than would be suggested by a simple, straightforward regression of NEP vs. Ndep.

The effects of atmospheric nitrogen deposition (Ndep) on carbon (C) sequestration in forests have often been assessed by relating differences in productivity to spatial variations of Ndep across a large geographic domain. These correlations generally suffer from covariation of other confounding variables related to climate and other growth-limiting factors, as well as large uncertainties in total (dry + wet) reactive nitrogen (Nr) deposition. We propose a methodology for untangling the effects of Ndep from those of meteorological variables, soil water retention capacity and stand age, using a mechanistic forest growth model in combination with eddy covariance CO2 exchange fluxes from a Europe-wide network of 22 forest flux towers. Total Nr deposition rates were estimated from local measurements as far as possible. The forest data were compared with data from natural or semi-natural, non-woody vegetation sites. The response of forest net ecosystem productivity to nitrogen deposition (dNEP ∕ dNdep) was estimated after accounting for the effects on gross primary productivity (GPP) of the co-correlates by means of a meta-modelling standardization procedure, which resulted in a reduction by a factor of about 2 of the uncorrected, apparent dGPP ∕ dNdep value. This model-enhanced analysis of the C and Ndep flux observations at the scale of the European network suggests a mean overall dNEP ∕ dNdep response of forest lifetime C sequestration to Ndep of the order of 40–50 g C per g N, which is slightly larger but not significantly different from the range of estimates published in the most recent reviews. Importantly, patterns of gross primary and net ecosystem productivity versus Ndep were non-linear, with no further growth responses at high Ndep levels (Ndep > 2.5–3 g N m−2 yr−1) but accompanied by increasingly large ecosystem N losses by leaching and gaseous emissions. The reduced increase in productivity per unit N deposited at high Ndep levels implies that the forecast increased Nr emissions and increased Ndep levels in large areas of Asia may not positively impact the continent's forest CO2 sink. The large level of unexplained variability in observed carbon sequestration efficiency (CSE) across sites further adds to the uncertainty in the dC∕dN response.

Elevated ambient concentrations of sub-3 nm particles (nanocluster aerosol, NCA) are generally related to atmospheric new particle formation events, usually linked with gaseous sulfuric acid (H2SO4) produced via photochemical oxidation of sulfur dioxide. According to our measurement results of H2SO4 and NCA concentrations, traffic density, and solar irradiance at an urban traffic site in Helsinki, Finland, the view of aerosol formation in traffic-influenced environments is updated by presenting two separate and independent pathways of traffic affecting the atmospheric NCA concentrations: by acting as a direct nanocluster source and by influencing the production of H2SO4. As traffic density in many areas is generally correlated with solar radiation, it is likely that the influence of traffic-related nanoclusters has been hidden in the diurnal variation and is thus underestimated because new particle formation events also follow the diurnal cycle of sunlight. Urban aerosol formation studies should, therefore, be updated to include the proposed formation mechanisms. The formation of H2SO4 in urban environments is here separated into two routes: primary H2SO4 is formed in hot vehicle exhaust and is converted rapidly to the particle phase; secondary H2SO4 results from the combined effect of emitted gaseous precursors and available solar radiation. A rough estimation demonstrates that ∼85 % of the total NCA and ∼68 % of the total H2SO4 in urban air at noontime at the measurement site are contributed by traffic, indicating the importance of traffic emissions.

We calibrated the JSBACH model with six different stomatal conductance formulations using measurements from 10 FLUXNET coniferous evergreen sites in the boreal zone. The parameter posterior distributions were generated by the adaptive population importance sampler (APIS); then the optimal values were estimated by a simple stochastic optimisation algorithm. The model was constrained with in situ observations of evapotranspiration (ET) and gross primary production (GPP). We identified the key parameters in the calibration process. These parameters control the soil moisture stress function and the overall rate of carbon fixation. The JSBACH model was also modified to use a delayed effect of temperature for photosynthetic activity in spring. This modification enabled the model to correctly reproduce the springtime increase in GPP for all conifer sites used in this study. Overall, the calibration and model modifications improved the coefficient of determination and the model bias for GPP with all stomatal conductance formulations. However, only the coefficient of determination was clearly improved for ET. The optimisation resulted in best performance by the Bethy, Ball–Berry, and the Friend and Kiang stomatal conductance models. We also optimised the model during a drought event at a Finnish Scots pine forest site. This optimisation improved the model behaviour but resulted in significant changes to the parameter values except for the unified stomatal optimisation model (USO). Interestingly, the USO demonstrated the best performance during this event.

Natural wetlands constitute the largest and most uncertain source of methane (CH4) to the atmosphere and a large fraction of them are found in the northern latitudes. These emissions are typically estimated using process (“bottom-up”) or inversion (“top-down”) models. However, estimates from these two types of models are not independent of each other since the top-down estimates usually rely on the a priori estimation of these emissions obtained with process models. Hence, independent spatially explicit validation data are needed. Here we utilize a random forest (RF) machine-learning technique to upscale CH4 eddy covariance flux measurements from 25 sites to estimate CH4 wetland emissions from the northern latitudes (north of 45∘ N). Eddy covariance data from 2005 to 2016 are used for model development. The model is then used to predict emissions during 2013 and 2014. The predictive performance of the RF model is evaluated using a leave-one-site-out cross-validation scheme. The performance (Nash–Sutcliffe model efficiency =0.47) is comparable to previous studies upscaling net ecosystem exchange of carbon dioxide and studies comparing process model output against site-level CH4 emission data. The global distribution of wetlands is one major source of uncertainty for upscaling CH4. Thus, three wetland distribution maps are utilized in the upscaling. Depending on the wetland distribution map, the annual emissions for the northern wetlands yield 32 (22.3–41.2, 95 % confidence interval calculated from a RF model ensemble), 31 (21.4–39.9) or 38 (25.9–49.5) Tg(CH4) yr−1. To further evaluate the uncertainties of the upscaled CH4 flux data products we also compared them against output from two process models (LPX-Bern and WetCHARTs), and methodological issues related to CH4 flux upscaling are discussed. The monthly upscaled CH4 flux data products are available at https://doi.org/10.5281/zenodo.2560163 (Peltola et al., 2019).

An air-to-air ultrafine particle concentrator (Aerosol Dynamics Inc. concentrator; ADIc) has been designed to enhance online chemical characterization of ambient aerosols using aerosol mass spectrometry. The ADIc employs a three-stage, moderated water-based condensation growth tube coupled to an aerodynamic focusing nozzle to concentrate fine particles into a portion of the flow. The system can be configured to sample between 1.0 and 1.7 L min−1, with an output concentrated flow between 0.08 and 0.12 L min−1, resulting in a theoretical concentration factor (sample flow / output flow) ranging from 8 to 21. Laboratory tests with monodisperse particles show that the ADIc is effective for particles as small as 10 nm. Laboratory experiments conducted with the Aerosol Mass Spectrometer (AMS) showed no shift in the particle size with the ADIc, as measured by the AMS particle time-of-flight operation. The ADIc-AMS system was operated unattended over a 1-month period near Boston, Massachusetts. Comparison to a parallel AMS without the concentrator showed concentration factors of 9.7±0.15 and 9.1±0.1 for sulfate and nitrate, respectively, when operated with a theoretical concentration factor of 10.5±0.3. The concentration factor of organics was lower, possibly due to the presence of large particles from nearby road-paving operations and a difference in aerodynamic lens cutoff between the two AMS instruments. Another field deployment was carried out in Helsinki, Finland. Two ∼10 d measurement periods showed good correlation for the concentrations of organics, sulfate, nitrate and ammonium measured with an Aerosol Chemical Speciation Monitor (ACSM) with the ADIc and a parallel AMS without the concentrator. Additional experiments with an AMS alternating between the ADIc and a bypass line demonstrated that the concentrator did not significantly change the size distribution or the chemistry of the ambient aerosol particles.

The non-uniform spatial integration, an inherent feature of the eddy covariance (EC) method, creates a challenge for flux data interpretation in a heterogeneous environment, where the contribution of different land cover types varies with flow conditions, potentially resulting in biased estimates in comparison to the areally averaged fluxes and land cover attributes. We modelled flux footprints and characterized the spatial scale of our EC measurements in Tiksi, a tundra site in northern Siberia. We used leaf area index (LAI) and land cover class (LCC) data, derived from very-high-spatial-resolution satellite imagery and field surveys, and quantified the sensor location bias. We found that methane (CH4) fluxes varied strongly with wind direction (−0.09 to 0.59 µgCH4m-2s-1 on average) during summer 2014, reflecting the distribution of different LCCs. Other environmental factors had only a minor effect on short-term flux variations but influenced the seasonal trend. Using footprint weights of grouped LCCs as explanatory variables for the measured CH4 flux, we developed a multiple regression model to estimate LCC group-specific fluxes. This model showed that wet fen and graminoid tundra patches in locations with topography-enhanced wetness acted as strong sources (1.0 µgCH4m-2s-1 during the peak emission period), while mineral soils were significant sinks (−0.13 µgCH4m-2s-1). To assess the representativeness of measurements, we upscaled the LCC group-specific fluxes to different spatial scales. Despite the landscape heterogeneity and rather poor representativeness of EC data with respect to the areally averaged LAI and coverage of some LCCs, the mean flux was close to the CH4 balance upscaled to an area of 6.3 km2, with a location bias of 14 %. We recommend that EC site descriptions in a heterogeneous environment should be complemented with footprint-weighted high-resolution data on vegetation and other site characteristics.

Similarities and differences in the submicron atmospheric aerosol chemical composition are analyzed from a unique set of measurements performed at 21 sites across Europe for at least one year. These sites are located between 35 and 62°N and 10° W – 26°E, and represent various types of settings (remote, coastal, rural, industrial, urban). Measurements were all carried out on-line with a 30-min time resolution using mass spectroscopy based instruments known as Aerosol Chemical Speciation Monitors (ACSM) and Aerosol Mass Spectrometers (AMS) and following common measurement guidelines. Data regarding organics, sulfate, nitrate and ammonium concentrations, as well as the sum of them called non-refractory submicron aerosol mass concentration ([NR-PM1]) are discussed. NR-PM1 concentrations generally increase from remote to urban sites. They are mostly larger in the mid-latitude band than in southern and northern Europe. On average, organics account for the major part (36–64%) of NR-PM1 followed by sulfate (12–44%) and nitrate (6–35%). The annual mean chemical composition of NR-PM1 at rural (or regional background) sites and urban background sites are very similar. Considering rural and regional background sites only, nitrate contribution is higher and sulfate contribution is lower in mid-latitude Europe compared to northern and southern Europe. Large seasonal variations in concentrations (μg/m³) of one or more components of NR-PM1 can be observed at all sites, as well as in the chemical composition of NR-PM1 (%) at most sites. Significant diel cycles in the contribution to [NR-PM1] of organics, sulfate, and nitrate can be observed at a majority of sites both in winter and summer. Early morning minima in organics in concomitance with maxima in nitrate are common features at regional and urban background sites. Daily variations are much smaller at a number of coastal and rural sites. Looking at NR-PM1 chemical composition as a function of NR-PM1 mass concentration reveals that although organics account for the major fraction of NR-PM1 at all concentration levels at most sites, nitrate contribution generally increases with NR-PM1 mass concentration and predominates when NR-PM1 mass concentrations exceed 40 μg/m³ at half of the sites.

Surface–atmosphere energy exchange is strongly ecosystem-specific. At the same time, as the energy balance constitutes responses of an ecosystem to environmental stressors including precipitation, humidity and solar radiation, it results in feedbacks of potential importance for the regional climate. Northern peatlands represent a diverse class of ecosystems that cover nearly 6 × 106 km2 in the Boreal region, which makes the inter-comparison of their energy balances an important objective. With this in mind we studied energy exchange across a broad spectrum of peatlands from pristine fens and bogs to forested and agriculturally managed peatlands, which represent a large fraction of the landscape in Finland and Sweden. The effects of management activities on the energy balance were extensively examined from the micrometeorological point of view, using eddy covariance data from eight sites in these two countries (56º 12'–62º 11' N, 13º 03'–30º 05' E). It appears that the surface energy balance varies widely amongst the different peatland types. Generally, energy exchange features including the Bowen ratio, surface conductance, coupling to the atmosphere, responses to water table fluctuations and vapour pressure deficit could be associated directly with the peatland type. The relative constancy of the Bowen ratio in natural open mires contrasted with its variation in tree-covered and agricultural peatlands. We conclude that the impacts of management and the consequences of land-use change in peatlands for the local and regional climate might be substantial.

Drainage of peatlands is expected to turn these ecosystems into carbon sources to the atmosphere. We measured carbon dynamics of a drained forested peatland in southern Finland over 4 years, including one with severe drought during growing season. Net ecosystem exchange (NEE) of carbon dioxide (CO2) was measured with the eddy covariance method from a mast above the forest. Soil and forest floor CO2 and methane (CH4) fluxes were measured from the strips and from ditches with closed chambers. Biomass and litter production were sampled, and soil subsidence was measured by repeated levellings of the soil surface. The drained peatland ecosystem was a strong sink of carbon dioxide in all studied years. Soil CO2 balance was estimated by subtracting the carbon sink of the growing tree stand from NEE, and it showed that the soil itself was a carbon sink as well. A drought period in one summer significantly decreased the sink through decreased gross primary production. Drought also decreased ecosystem respiration. The site was a small sink for CH4, even when emissions from ditches were taken into account. Despite the continuous carbon sink, peat surface subsided slightly during the 10-year measurement period, which was probably mainly due to compaction of peat. It is concluded that even 50 years after drainage this peatland site acted as a soil C sink due to relatively small changes in the water table and in plant community structure compared to similar undrained sites, and the significantly increased tree stand growth and litter production. Although the site is currently a soil C sink, simulation studies with process models are needed to test whether such sites could remain C sinks when managed for forestry over several tree-stand rotations.

Arctic tundra ecosystems will play a key role in future climate change due to intensifying permafrost thawing, plant growth and ecosystem carbon exchange, but monitoring these changes may be challenging due to the heterogeneity of Arctic landscapes. We examined spatial variation and linkages of soil and plant attributes in a site of Siberian Arctic tundra in Tiksi, northeast Russia, and evaluated possibilities to capture this variation by remote sensing for the benefit of carbon exchange measurements and landscape extrapolation. We distinguished nine land cover types (LCTs) and to characterize them, sampled 92 study plots for plant and soil attributes in 2014. Moreover, to test if variation in plant and soil attributes can be detected using remote sensing, we produced a normalized difference vegetation index (NDVI) and topographical parameters for each study plot using three very high spatial resolution multispectral satellite images. We found that soils ranged from mineral soils in bare soil and lichen tundra LCTs to soils of high percentage of organic matter (OM) in graminoid tundra, bog, dry fen and wet fen. OM content of the top soil was on average 14 g dm−3 in bare soil and lichen tundra and 89 g dm−3 in other LCTs. Total moss biomass varied from 0 to 820 g m−2, total vascular shoot mass from 7 to 112 g m−2 and vascular leaf area index (LAI) from 0.04 to 0.95 among LCTs. In late summer, soil temperatures at 15 cm depth were on average 14 °C in bare soil and lichen tundra, and varied from 5 to 9 °C in other LCTs. On average, depth of the biologically active, unfrozen soil layer doubled from early July to mid-August. When contrasted across study plots, moss biomass was positively associated with soil OM % and OM content and negatively associated with soil temperature, explaining 14–34 % of variation. Vascular shoot mass and LAI were also positively associated with soil OM content, and LAI with active layer depth, but only explained 6–15 % of variation. NDVI captured variation in vascular LAI better than in moss biomass, but while this difference was significant with late season NDVI, it was minimal with early season NDVI. For this reason, soil attributes associated with moss mass were better captured by early season NDVI. Topographic attributes were related to LAI and many soil attributes, but not to moss biomass and could not increase the amount of spatial variation explained in plant and soil attributes above that achieved by NDVI. The LCT map we produced had low to moderate uncertainty in predictions for plant and soil properties except for moss biomass and bare soil and lichen tundra LCTs. Our results illustrate a typical tundra ecosystem with great fine-scale spatial variation in both plant and soil attributes. Mosses dominate plant biomass and control many soil attributes, including OM % and temperature, but variation in moss biomass is difficult to capture by remote sensing reflectance, topography or a LCT map. Despite the general accuracy of landscape level predictions in our LCT approach, this indicates challenges in the spatial extrapolation of some of those vegetation and soil attributes that are relevant for the regional ecosystem and global climate models.

Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (Vcmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r2 = 0.76; Nash–Sutcliffe modeling efficiency, MEF = 0.76) and ecosystem respiration (ER, r2 = 0.78, MEF = 0.75), with lesser accuracy for latent heat fluxes (LE, r2 = 0.42, MEF = 0.14) and and net ecosystem CO2 exchange (NEE, r2 = 0.38, MEF = 0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r2 values (0.57–0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r2 values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r2 Vcmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average Vcmax value.

In recent years, monitoring of the status of ecosystems using low-cost web (IP) or time lapse cameras has received wide interest. With broad spatial coverage and high temporal resolution, networked cameras can provide information about snow cover and vegetation status, serve as ground truths to Earth observations and be useful for gap-filling of cloudy areas in Earth observation time series. Networked cameras can also play an important role in supplementing laborious phenological field surveys and citizen science projects, which also suffer from observer-dependent observation bias. We established a network of digital surveillance cameras for automated monitoring of phenological activity of vegetation and snow cover in the boreal ecosystems of Finland. Cameras were mounted at 14 sites, each site having 1–3 cameras. Here, we document the network, basic camera information and access to images in the permanent data repository (http://www.zenodo.org/communities/phenology_camera/). Individual DOI-referenced image time series consist of half-hourly images collected between 2014 and 2016 (https://doi.org/10.5281/zenodo.1066862). Additionally, we present an example of a colour index time series derived from images from two contrasting sites.

Wetlands are one of the most significant natural sources of methane (CH4) to the atmosphere. They emit CH4 because decomposition of soil organic matter in waterlogged anoxic conditions produces CH4, in addition to carbon dioxide (CO2). Production of CH4 and how much of it escapes to the atmosphere depend on a multitude of environmental drivers. Models simulating the processes leading to CH4 emissions are thus needed for upscaling observations to estimate present CH4 emissions and for producing scenarios of future atmospheric CH4 concentrations. Aiming at a CH4 model that can be added to models describing peatland carbon cycling, we composed a model called HIMMELI that describes CH4 build-up in and emissions from peatland soils. It is not a full peatland carbon cycle model but it requires the rate of anoxic soil respiration as input. Driven by soil temperature, leaf area index (LAI) of aerenchymatous peatland vegetation, and water table depth (WTD), it simulates the concentrations and transport of CH4, CO2, and oxygen (O2) in a layered one-dimensional peat column. Here, we present the HIMMELI model structure and results of tests on the model sensitivity to the input data and to the description of the peat column (peat depth and layer thickness), and demonstrate that HIMMELI outputs realistic fluxes by comparing modeled and measured fluxes at two peatland sites. As HIMMELI describes only the CH4-related processes, not the full carbon cycle, our analysis revealed mechanisms and dependencies that may remain hidden when testing CH4 models connected to complete peatland carbon models, which is usually the case. Our results indicated that (1) the model is flexible and robust and thus suitable for different environments; (2) the simulated CH4 emissions largely depend on the prescribed rate of anoxic respiration; (3) the sensitivity of the total CH4 emission to other input variables is mainly mediated via the concentrations of dissolved gases, in particular, the O2 concentrations that affect the CH4 production and oxidation rates; (4) with given input respiration, the peat column description does not significantly affect the simulated CH4 emissions in this model version.

The influence of drought on plant functioning has received considerable attention in recent years, however our understanding of the response of carbon and water coupling to drought in terrestrial ecosystems still needs to be improved. A severe soil moisture drought occurred in southern Finland in the late summer of 2006. In this study, we investigated the response of water use efficiency to summer drought in a boreal Scots pine forest (Pinus sylvestris) on the daily time scale mainly using eddy covariance flux data from the Hyytiälä (southern Finland) flux site. In addition, simulation results from the JSBACH land surface model were evaluated against the observed results. Based on observed data, the ecosystem level water use efficiency (EWUE; the ratio of gross primary production, GPP, to evapotranspiration, ET) showed a decrease during the severe soil moisture drought, while the inherent water use efficiency (IWUE; a quantity defined as EWUE multiplied with mean daytime vapour pressure deficit, VPD) increased and the underlying water use efficiency (uWUE, a metric based on IWUE and a simple stomatal model, is the ratio of GPP multiplied with a square root of VPD to ET) was unchanged during the drought. The decrease in EWUE was due to the stronger decline in GPP than in ET. The increase in IWUE was because of the decreased stomatal conductance under increased VPD. The unchanged uWUE indicates that the trade-off between carbon assimilation and transpiration of the boreal Scots pine forest was not disturbed by this drought event at the site. The JSBACH simulation showed declines of both GPP and ET under the severe soil moisture drought, but to a smaller extent compared to the observed GPP and ET. Simulated GPP and ET led to a smaller decrease in EWUE but a larger increase in IWUE because of the severe soil moisture drought in comparison to observations. As in the observations, the simulated uWUE showed no changes in the drought event. The model deficiencies exist mainly due to the lack of the limiting effect of increased VPD on stomatal conductance during the low soil moisture condition. Our study provides a deeper understanding of the coupling of carbon and water cycles in the boreal Scots pine forest ecosystem and suggests possible improvements to land surface models, which play an important role in the prediction of biosphere–atmosphere feedbacks in the climate system.

Recent satellite observations of sun-induced chlorophyll fluorescence (SIF) are thought to provide a large-scale proxy for gross primary production (GPP), thus providing a new way to assess the performance of land surface models (LSMs). In this study, we assessed how well SIF is able to predict GPP in the Fenno-Scandinavian region and what potential limitations for its application exist. We implemented a SIF model into the JSBACH LSM and used active leaf-level chlorophyll fluorescence measurements (Chl F) to evaluate the performance of the SIF module at a coniferous forest at Hyytiälä, Finland. We also compared simulated GPP and SIF at four Finnish micrometeorological flux measurement sites to observed GPP as well as to satellite-observed SIF. Finally, we conducted a regional model simulation for the Fenno-Scandinavian region with JSBACH and compared the results to SIF retrievals from the GOME-2 (Global Ozone Monitoring Experiment-2) space-borne spectrometer and to observation-based regional GPP estimates. Both observations and simulations revealed that SIF can be used to estimate GPP at both site and regional scales. At regional scale the model was able to simulate observed SIF averaged over 5 years with r2 of 0.86. The GOME-2-based SIF was a better proxy for GPP than the remotely sensed fAPAR (fraction of absorbed photosynthetic active radiation by vegetation). The observed SIF captured the seasonality of the photosynthesis at site scale and showed feasibility for use in improving of model seasonality at site and regional scale.

We measured methane (CH4) exchange rates with automatic chambers at the forest floor of a nutrient-rich drained peatland in 2011–2013. The fen, located in southern Finland, was drained for forestry in 1969 and the tree stand is now a mixture of Scots pine, Norway spruce, and pubescent birch. Our measurement system consisted of six transparent chambers and stainless steel frames, positioned on a number of different field and moss layer compositions. Gas concentrations were measured with an online cavity ring-down spectroscopy gas analyzer. Fluxes were calculated with both linear and exponential regression. The use of linear regression resulted in systematically smaller CH4 fluxes by 10–45 % as compared to exponential regression. However, the use of exponential regression with small fluxes ( 4 m−2 h−1) typically resulted in anomalously large absolute fluxes and high hour-to-hour deviations. Therefore, we recommend that fluxes are initially calculated with linear regression to determine the threshold for low fluxes and that higher fluxes are then recalculated using exponential regression. The exponential flux was clearly affected by the length of the fitting period when this period was 4 flux: the forest floor acted as a CH4 sink particularly from early summer until the end of the year, while in late winter the flux was very small and fluctuated around zero. However, the magnitude of fluxes was relatively small throughout the year, ranging mainly from −130 to +100 µg CH4 m−2 h−1. CH4 emission peaks were observed occasionally, mostly in summer during heavy rainfall events. Diurnal variation, showing a lower CH4 uptake rate during the daytime, was observed in all of the chambers, mainly in the summer and late spring, particularly in dry conditions. It was attributed more to changes in wind speed than air or soil temperature, which suggest that physical rather than biological phenomena are responsible for the observed variation. The annual net CH4 exchange varied from −104 ± 30 to −505 ± 39 mg CH4 m−2 yr−1 among the six chambers, with an average of −219 mg CH4 m−2 yr−1 over the 2-year measurement period.

Tropical savannas and grasslands are estimated to contribute significantly to the total primary production of all terrestrial vegetation. Large parts of African savannas and grasslands are used for agriculture and cattle grazing, but the carbon flux data available from these areas are limited. This study explores carbon dioxide fluxes measured with the eddy covariance method for 3 years at a grazed savanna grassland in Welgegund, South Africa. The tree cover around the measurement site, grazed by cattle and sheep, was around 15 %. The night-time respiration was not significantly dependent on either soil moisture or soil temperature on a weekly temporal scale, whereas on an annual timescale higher respiration rates were observed when soil temperatures were higher. The carbon dioxide balances of the years 2010–2011, 2011–2012 and 2012–2013 were −85 ± 16, 67 ± 20 and 139 ± 13 gC m−2 yr−1, respectively. The yearly variation was largely determined by the changes in the early wet season fluxes (September to November) and in the mid-growing season fluxes (December to January). Early rainfall enhanced the respiratory capacity of the ecosystem throughout the year, whereas during the mid-growing season high rainfall resulted in high carbon uptake.

Subarctic and boreal emissions of CH4 are important contributors to the atmospheric greenhouse gas (GHG) balance and subsequently the global radiative forcing. Whilst N2O emissions may be lower, the much greater radiative forcing they produce justifies their inclusion in GHG studies. In addition to the quantification of flux magnitude, it is essential that we understand the drivers of emissions to be able to accurately predict climate-driven changes and potential feedback mechanisms. Hence this study aims to increase our understanding of what drives fluxes of CH4 and N2O in a subarctic forest/wetland landscape during peak summer conditions and into the shoulder season, exploring both spatial and temporal variability, and uses satellite-derived spectral data to extrapolate from chamber-scale fluxes to a 2 km × 2 km landscape area.From static chamber measurements made during summer and autumn campaigns in 2012 in the Sodankylä region of northern Finland, we concluded that wetlands represent a significant source of CH4 (3.35 ± 0.44 mg C m−2 h−1 during the summer campaign and 0.62 ± 0.09 mg C m−2 h−1 during the autumn campaign), whilst the surrounding forests represent a small sink (−0.06 ± −2 h−1 during the summer campaign and −0.03 ± −2 h−1 during the autumn campaign). N2O fluxes were near-zero across both ecosystems.We found a weak negative relationship between CH4 emissions and water table depth in the wetland, with emissions decreasing as the water table approached and flooded the soil surface and a positive relationship between CH4 emissions and the presence of Sphagnum mosses. Temperature was also an important driver of CH4 with emissions increasing to a peak at approximately 12 °C. Little could be determined about the drivers of N2O emissions given the small magnitude of the fluxes.A multiple regression modelling approach was used to describe CH4 emissions based on spectral data from PLEIADES PA1 satellite imagery across a 2 km × 2 km landscape. When applied across the whole image domain we calculated a CH4 source of 2.05 ± 0.61 mg C m−2 h−1. This was significantly higher than landscape estimates based on either a simple mean or weighted by forest/wetland proportion (0.99 ± 0.16, 0.93 ± 0.12 mg C m−2 h−1, respectively). Hence we conclude that ignoring the detailed spatial variability in CH4 emissions within a landscape leads to a potentially significant underestimation of landscape-scale fluxes. Given the small magnitude of measured N2O fluxes a similar level of detailed upscaling was not needed; we conclude that N2O fluxes do not currently comprise an important component of the landscape-scale GHG budget at this site.

We examined parameter optimisation in the JSBACH (Kaminski et al., 2013; Knorr and Kattge, 2005; Reick et al., 2013) ecosystem model, applied to two boreal forest sites (Hyytiälä and Sodankylä) in Finland. We identified and tested key parameters in soil hydrology and forest water and carbon-exchange-related formulations, and optimised them using the adaptive Metropolis (AM) algorithm for Hyytiälä with a 5-year calibration period (2000–2004) followed by a 4-year validation period (2005–2008). Sodankylä acted as an independent validation site, where optimisations were not made. The tuning provided estimates for full distribution of possible parameters, along with information about correlation, sensitivity and identifiability. Some parameters were correlated with each other due to a phenomenological connection between carbon uptake and water stress or other connections due to the set-up of the model formulations. The latter holds especially for vegetation phenology parameters. The least identifiable parameters include phenology parameters, parameters connecting relative humidity and soil dryness, and the field capacity of the skin reservoir. These soil parameters were masked by the large contribution from vegetation transpiration. In addition to leaf area index and the maximum carboxylation rate, the most effective parameters adjusting the gross primary production (GPP) and evapotranspiration (ET) fluxes in seasonal tuning were related to soil wilting point, drainage and moisture stress imposed on vegetation. For daily and half-hourly tunings the most important parameters were the ratio of leaf internal CO2 concentration to external CO2 and the parameter connecting relative humidity and soil dryness. Effectively the seasonal tuning transferred water from soil moisture into ET, and daily and half-hourly tunings reversed this process. The seasonal tuning improved the month-to-month development of GPP and ET, and produced the most stable estimates of water use efficiency. When compared to the seasonal tuning, the daily tuning is worse on the seasonal scale. However, daily parametrisation reproduced the observations for average diurnal cycle best, except for the GPP for Sodankylä validation period, where half-hourly tuned parameters were better. In general, the daily tuning provided the largest reduction in model–data mismatch. The models response to drought was unaffected by our parametrisations and further studies are needed into enhancing the dry response in JSBACH.

Digital repeat photography has become a widely used tool for assessing the annual course of vegetation phenology of different ecosystems. By using the green chromatic coordinate (GCC) as a greenness measure, we examined the feasibility of digital repeat photography for assessing the vegetation phenology in two contrasting high-latitude ecosystems. Ecosystem–atmosphere CO2 fluxes and various meteorological variables were continuously measured at both sites. While the seasonal changes in GCC were more obvious for the ecosystem that is dominated by annual plants (open wetland), clear seasonal patterns were also observed for the evergreen ecosystem (coniferous forest). Daily and seasonal time periods with sufficient solar radiation were determined based on images of a grey reference plate. The variability in cloudiness had only a minor effect on GCC, and GCC did not depend on the sun angle and direction either. The daily GCC of wetland correlated well with the daily photosynthetic capacity estimated from the CO2 flux measurements. At the forest site, the correlation was high in 2015 but there were discernible deviations during the course of the summer of 2014. The year-to-year differences were most likely generated by meteorological conditions, with higher temperatures coinciding with higher GCCs. In addition to depicting the seasonal course of ecosystem functioning, GCC was shown to respond to environmental changes on a timescale of days. Overall, monitoring of phenological variations with digital images provides a powerful tool for linking gross primary production and phenology.

The applicability, methods and limitations of constrained peak fitting on mass spectra of low mass resolving power (m∕Δm50 ∼ 500) recorded with a time-of-flight aerosol chemical speciation monitor (ToF-ACSM) are explored. Calibration measurements as well as ambient data are used to exemplify the methods that should be applied to maximise data quality and assess confidence in peak-fitting results. Sensitivity analyses and basic peak fit metrics such as normalised ion separation are employed to demonstrate which peak-fitting analyses commonly performed in high-resolution aerosol mass spectrometry are appropriate to perform on spectra of this resolving power. Information on aerosol sulfate, nitrate, sodium chloride, methanesulfonic acid as well as semi-volatile metal species retrieved from these methods is evaluated. The constants in a commonly used formula for the estimation of the mass concentration of hydrocarbon-like organic aerosol may be refined based on peak-fitting results. Finally, application of a recently published parameterisation for the estimation of carbon oxidation state to ToF-ACSM spectra is validated for a range of organic standards and its use demonstrated for ambient urban data.

Sodankylä, in the heart of Arctic Research Centre of the Finnish Meteorological Institute (FMI ARC) in northern Finland, is an ideal site for atmospheric and environmental research in the boreal and sub-Arctic zone. With temperatures ranging from −50 to &plus;30 °C, it provides a challenging testing ground for numerical weather forecasting (NWP) models as well as weather forecasting in general. An extensive set of measurements has been carried out in Sodankylä for more than 100 years. In 2000, a 48 m-high micrometeorological mast was erected in the area. In this article, the use of Sodankylä mast measurements in NWP model verification is described. Starting in 2000, with the NWP model HIRLAM and Sodankylä measurements, the verification system has now been expanded to include comparisons between 12 NWP models and seven measurement masts, distributed across Europe. A case study, comparing forecasted and observed radiation fluxes, is also presented. It was found that three different radiation schemes, applicable in NWP model HARMONIE-AROME, produced somewhat different downwelling longwave radiation fluxes during cloudy days, which however did not change the overall cold bias of the predicted screen-level temperature.

Four years of continuous aerosol number size distribution measurements from the Arctic Climate Observatory in Tiksi, Russia, are analyzed. Tiksi is located in a region where in situ information on aerosol particle properties has not been previously available. Particle size distributions were measured with a differential mobility particle sizer (in the diameter range of 7–500 nm) and with an aerodynamic particle sizer (in the diameter range of 0.5–10 μm). Source region effects on particle modal features and number, and mass concentrations are presented for different seasons. The monthly median total aerosol number concentration in Tiksi ranges from 184 cm−3 in November to 724 cm−3 in July, with a local maximum in March of 481 cm−3. The total mass concentration has a distinct maximum in February–March of 1.72–2.38 μg m−3 and two minimums in June (0.42 μg m−3) and in September–October (0.36–0.57 μg m−3). These seasonal cycles in number and mass concentrations are related to isolated processes and phenomena such as Arctic haze in early spring, which increases accumulation and coarse-mode numbers, and secondary particle formation in spring and summer, which affects the nucleation and Aitken mode particle concentrations. Secondary particle formation was frequently observed in Tiksi and was shown to be slightly more common in marine, in comparison to continental, air flows. Particle formation rates were the highest in spring, while the particle growth rates peaked in summer. These results suggest two different origins for secondary particles, anthropogenic pollution being the important source in spring and biogenic emissions being significant in summer. The impact of temperature-dependent natural emissions on aerosol and cloud condensation nuclei numbers was significant: the increase in both the particle mass and the CCN (cloud condensation nuclei) number with temperature was found to be higher than in any previous study done over the boreal forest region. In addition to the precursor emissions of biogenic volatile organic compounds, the frequent Siberian forest fires, although far away, are suggested to play a role in Arctic aerosol composition during the warmest months. Five fire events were isolated based on clustering analysis, and the particle mass and cloud condensation nuclei number were shown to be somewhat affected by these events. In addition, during calm and cold months, aerosol concentrations were occasionally increased by local aerosol sources in trapping inversions. These results provide valuable information on interannual cycles and sources of Arctic aerosols.