Assessing nutrient critical load exceedances requires complete and accurate atmospheric deposition budgets for reactive nitrogen (N). The exceedance is the total amount of N deposited to the ecosystem in excess of the critical load, which is the amount of N input below which harmful effects do not occur. Total deposition includes all forms of N (i.e., organic and inorganic) deposited to the ecosystem by wet and dry pathways. Here we present results from the Southern Appalachian Nitrogen Deposition Study (SANDS), in which a combination of measurements and field-scale modeling was used to develop a complete annual N deposition budget for a deciduous forest at the Coweeta Hydrologic Laboratory. Wet deposition of ammonium, nitrate, nitrite, and bulk organic N were measured directly. The dry deposited N fraction was estimated using a bidirectional resistance-based model driven with speciated measurements of N air concentrations (e.g., ammonia, ammonium aerosol, nitric acid, nitrate aerosol, bulk organic N in aerosol, total alkyl nitrates, and total peroxy nitrates), micrometeorology, canopy structure, and biogeochemistry. Total annual deposition was ~6.7 kg N ha yr, which is on the upper end of N critical load estimates recently developed for similar ecosystems in the nearby Great Smoky Mountains National Park. Of the total (wet + dry) budget, 51.1% was contributed by reduced forms of N , with oxidized and organic forms contributing ~41.3% and 7.6%, respectively. Our results indicate that reductions in deposition would be needed to achieve the lowest estimates (~3.0 kg N ha yr) of N critical loads in southern Appalachian forests.

Separating the components of ecosystem-scale carbon exchange is crucial in order to develop better models and future predictions of the terrestrial carbon cycle. However, there are several uncertainties and unknowns related to current photosynthesis estimates. In this study, we evaluate four different methods for estimating photosynthesis at a boreal forest at the ecosystem scale, of which two are based on carbon dioxide (CO) flux measurements and two on carbonyl sulfide (COS) flux measurements. The CO-based methods use traditional flux partitioning and artificial neural networks to separate the net CO flux into respiration and photosynthesis. The COS-based methods make use of a unique 5-year COS flux data set and involve two different approaches to determine the leaf-scale relative uptake ratio of COS and CO (LRU), of which one (LRU) was developed in this study. LRU was based on a previously tested stomatal optimization theory (CAP), while LRU was based on an empirical relation to measured radiation. For the measurement period 2013-2017, the artificial neural network method gave a GPP estimate very close to that of traditional flux partitioning at all timescales. On average, the COS-based methods gave higher GPP estimates than the CO-based estimates on daily (23% and 7% higher, using LRU and LRU, respectively) and monthly scales (20% and 3% higher), as well as a higher cumulative sum over 3 months in all years (on average 25% and 3% higher). LRU was higher than LRU estimated from chamber measurements at high radiation, leading to underestimation of midday GPP relative to other GPP methods. In general, however, use of LRU gave closer agreement with CO-based estimates of GPP than use of LRUPAR. When extended to other sites, LRU may be more robust than LRU because it is based on a physiological model whose parameters can be estimated from simple measurements or obtained from the literature. In contrast, the empirical radiation relation in LRU may be more site-specific. However, this requires further testing at other measurement sites.

Waters impounded behind dams (i.e., reservoirs) are important sources of greenhouses gases (GHGs), especially methane (CH), but emission estimates are not well constrained due to high spatial and temporal variability, limitations in monitoring methods to characterize hot spot and hot moment emissions, and the limited number of studies that investigate diurnal, seasonal, and interannual patterns in emissions. In this study, we investigate the temporal patterns and biophysical drivers of CH emissions from Acton Lake, a small eutrophic reservoir, using a combination of methods: eddy covariance monitoring, continuous warm-season ebullition measurements, spatial emission surveys, and measurements of key drivers of CH production and emission. We used an artificial neural network to gap fill the eddy covariance time series and to explore the relative importance of biophysical drivers on the interannual timescale. We combined spatial and temporal monitoring information to estimate annual whole-reservoir emissions. Acton Lake had cumulative areal emission rates of 45.6 ± 8.3 and 51.4 ± 4.3 g CH m in 2017 and 2018, respectively, or 109 ± 14 and 123 ± 10 Mg CH in 2017 and 2018 across the whole 2.4 km area of the lake. The main difference between years was a period of elevated emissions lasting less than 2 weeks in the spring of 2018, which contributed 17 % of the annual emissions in the shallow region of the reservoir. The spring burst coincided with a phytoplankton bloom, which was likely driven by favorable precipitation and temperature conditions in 2018 compared to 2017. Combining spatially extensive measurements with temporally continuous monitoring enabled us to quantify aspects of the spatial and temporal variability in CH emission. We found that the relationships between CH emissions and sediment temperature depended on location within the reservoir, and we observed a clear spatiotemporal offset in maximum CH emissions as a function of reservoir depth. These findings suggest a strong spatial pattern in CH biogeochemistry within this relatively small (2.4 km) reservoir. In addressing the need for a better understanding of GHG emissions from reservoirs, there is a trade-off in intensive measurements of one water body vs. short-term and/or spatially limited measurements in many water bodies. The insights from multi-year, continuous, spatially extensive studies like this one can be used to inform both the study design and emission upscaling from spatially or temporally limited results, specifically the importance of trophic status and intra-reservoir variability in assumptions about upscaling CH emissions.

Fixation of organic carbon by phytoplankton is the foundation of nearly all open-ocean ecosystems and a critical part of the global carbon cycle. But quantification and validation of ocean primary productivity at large scale remains a major challenge, due to limited coverage of ship-based measurements and the difficulty of validating diverse measurement techniques. Accurate primary productivity measurements from autonomous platforms would be highly desirable, due to much greater potential coverage. In pursuit of this goal we estimate gross primary productivity over two months in the springtime North Atlantic from an autonomous Lagrangian float using diel cycles of particulate organic carbon derived from optical beam attenuation. We test method precision and accuracy by comparison against entirely independent estimates from a locally parameterized model based on chlorophyll and light measurements from the same float. During nutrient replete conditions (80% of the study period), we obtain strong relative agreement between the independent methods across an order of magnitude of productivities (r=0.97), with slight under-estimation by the diel cycles method (-19±5 %). At the end of the diatom bloom, this relative difference increases to -58 % for a six-day period, likely a response to SiO4 limitation, which is not included in the model. In addition, we estimate gross oxygen productivity from O diel cycles and find strong correlation with diel cycles-based gross primary productivity over the entire deployment, providing further qualitative support to both methods. Finally, simultaneous estimates of net community productivity, carbon export and particle size suggest that bloom growth is halted by a combination of reduced productivity due to SiO limitation and increased export efficiency due to rapid aggregation. After the diatom bloom, high chlorophyll normalized productivity indicates that low net growth during this period is due to increased heterotrophic respiration and not nutrient limitation. These findings represent a significant advance in the accuracy and completeness of upper ocean carbon cycle measurements from an autonomous platform.

Streams and rivers are significant sources of nitrous oxide (NO), carbon dioxide (CO), and methane (CH) globally, and watershed management can alter greenhouse gas (GHG) emissions from streams. We hypothesized that urban infrastructure significantly alters downstream water quality and contributes to variability in GHG saturation and emissions. We measured gas saturation and estimated emission rates in headwaters of two urban stream networks (Red Run and Dead Run) of the Baltimore Ecosystem Study Long-Term Ecological Research project. We identified four combinations of stormwater and sanitary infrastructure present in these watersheds, including: (1) stream burial, (2) inline stormwater wetlands, (3) riparian/floodplain preservation, and (4) septic systems. We selected two first order catchments in each of these categories and measured GHG concentrations, emissions, and dissolved inorganic and organic carbon (DIC and DOC) and nutrient concentrations biweekly for 1 year. From a water quality perspective, the DOC : NO ratio of streamwater was significantly different across infrastructure categories. Multiple linear regressions including DOC : NO and other variables (dissolved oxygen, DO; total dissolved nitrogen, TDN; and temperature) explained much of the statistical variation in nitrous oxide (NO, r = 0.78), carbon dioxide (CO, r = 0.78) and methane (CH4, r 2 = 0.50) saturation in stream water. We measured NO saturation ratios, which were among the highest reported in the literature for streams, ranging from 1.1 to 47 across all sites and dates. NO saturation ratios were highest in streams draining watersheds with septic systems and strongly correlated with TDN. The CO saturation ratio was highly correlated with the NO saturation ratio across all sites and dates, and the CO saturation ratio ranged from 1.1 to 73. CH was always supersaturated, with saturation ratios ranging from 3.0 to 2157. Longitudinal surveys extending form headwaters to third-order outlets of Red Run and Dead Run took place in spring and fall. Linear regressions of these data yielded significant negative relationships between each gas with increasing watershed size as well as consistent relationships between solutes (TDN or DOC, and DOC : TDN ratio) and gas saturation. Despite a decline in gas saturation between the headwaters and stream outlet, streams remained saturated with GHGs throughout the drainage network, suggesting that urban streams are continuous sources of CO, CH, and NO. Our results suggest that infrastructure decisions can have significant effects on downstream water quality and greenhouse gases, and watershed management strategies may need to consider coupled impacts on urban water and air quality.

In the taiga-tundra ecotone (TTE), site-dependent forest structure characteristics can influence the subtle and heterogeneous structural changes that occur across the broad circumpolar extent. Such changes may be related to ecotone form, described by the horizontal and vertical patterns of forest structure (e.g., tree cover, density and height) within TTE forest patches, driven by local site conditions, and linked to ecotone dynamics. The unique circumstance of subtle, variable and widespread vegetation change warrants the application of spaceborne data including high-resolution (< 5m) spaceborne imagery (HRSI) across broad scales for examining TTE form and predicting dynamics. This study analyzes forest structure at the patch-scale in the TTE to provide a means to examine both vertical and horizontal components of ecotone form. We demonstrate the potential of spaceborne data for integrating forest height and density to assess TTE form at the scale of forest patches across the circumpolar biome by (1) mapping forest patches in study sites along the TTE in northern Siberia with a multi-resolution suite of spaceborne data, and (2) examining the uncertainty of forest patch height from this suite of data across sites of primarily diffuse TTE forms. Results demonstrate the opportunities for improving patch-scale spaceborne estimates of forest height, the vertical component of TTE form, with HRSI. The distribution of relative maximum height uncertainty based on prediction intervals is centered at ~40%, constraining the use of height for discerning differences in forest patches. We discuss this uncertainty in light of a conceptual model of general ecotone forms, and highlight how the uncertainty of spaceborne estimates of height can contribute to the uncertainty in identifying TTE forms. A focus on reducing the uncertainty of height estimates in forest patches may improve depiction of TTE form, which may help explain variable forest responses in the TTE to climate change and the vulnerability of portions of the TTE to forest structure change.

The trace fossil is proposed as an indicator of fossil bioelectric bacterial activity at the oxic-anoxic interface zone of marine sediments. This fulfils the idea that such processes, commonly found in the modern realm, should be also present in the geological past. is an exceptional trace fossil due to its very thin diameter (mostly less than 1 mm) and common pyritic filling. It is ubiquitous in some fine-grained sediments, where it has been interpreted as a burrow formed deeper than any other trace fossils, below the redox boundary. , formerly referred to as deeply burrowed invertebrates, has been found as remnant of a fossilized intrasediment bacterial mat that is pyritized. As visualized in 3-D by means of X-ray computed microtomography scanner, forms dense filamentous fabric, which reflects that it is produced by modern large, mat-forming, sulfide-oxidizing bacteria, belonging mostly to -related taxa, which are able to house a complex bacterial consortium. Several stages of formation, including filamentous, bacterial mat and its pyritization, are proposed to explain an electron exchange between oxic and suboxic/anoxic layers in the sediment. Therefore, can be considered a fossilized "electric wire".

The methane (CH) and nitrous oxide (NO) exchange of a temperate mountain grassland near Neustift, Austria, was measured during 2010-2012 over a time period of 22 months using the eddy covariance method. Exchange rates of both compounds at the site were low, with 97% of all half-hourly CH and NO fluxes ranging between ±200 and ±50 ng m s, respectively. The meadow acted as a sink for both compounds during certain time periods, but was a clear source of CH and NO on an annual timescale. Therefore, both gases contributed to an increase of the global warming potential (GWP), effectively reducing the sink strength in terms of CO equivalents of the investigated grassland site. In 2011, our best guess estimate showed a net greenhouse gas (GHG) sink of -32 g CO equ. m yr for the meadow, whereby 55% of the CO sink strength of -71 g COm yr was offset by CH (NO) emissions of 7 (32) g CO equ. m yr. When all data were pooled, the ancillary parameters explained 27 (42)% of observed CH (NO) flux variability, and up to 62 (76)% on shorter timescales in-between management dates. In the case of NO fluxes, we found the highest emissions at intermediate soil water contents and at soil temperatures close to 0 or above 14 °C. In comparison to CO, HO and energy fluxes, the interpretation of CH and NO exchange was challenging due to footprint heterogeneity regarding their sources and sinks, uncertainties regarding post-processing and quality control. Our results emphasize that CH and NO fluxes over supposedly well-aerated and moderately fertilized soils cannot be neglected when evaluating the GHG impact of temperate managed grasslands.

Exposure to bioaerosol allergens such as pollen can cause exacerbations of allergenic airway disease (AAD) in sensitive populations, and thus cause serious public health problems. Assessing these health impacts by linking the airborne pollen levels, concentrations of respirable allergenic material, and human allergenic response under current and future climate conditions is a key step toward developing preventive and adaptive actions. To that end, a regional-scale pollen emission and transport modeling framework was developed that treats allergenic pollens as non-reactive tracers within the WRF/CMAQ air-quality modeling system. The imulator of the iming nd agnitude of ollen eason (STaMPS) model was used to generate a daily pollen pool that can then be emitted into the atmosphere by wind. The STaMPS is driven by species-specific meteorological (temperature and/or precipitation) threshold conditions and is designed to be flexible with respect to its representation of vegetation species and plant functional types (PFTs). The hourly pollen emission flux was parameterized by considering the pollen pool, friction velocity, and wind threshold values. The dry deposition velocity of each species of pollen was estimated based on pollen grain size and density. An evaluation of the pollen modeling framework was conducted for southern California for the period from March to June 2010. This period coincided with observations by the University of Southern California's Children's Health Study (CHS), which included O, PM, and pollen count, as well as measurements of exhaled nitric oxide in study participants. Two nesting domains with horizontal resolutions of 12 km and 4 km were constructed, and six representative allergenic pollen genera were included: birch tree, walnut tree, mulberry tree, olive tree, oak tree, and brome grasses. Under the current parameterization scheme, the modeling framework tends to underestimate walnut and peak oak pollen concentrations, and tends to overestimate grass pollen concentrations. The model shows reasonable agreement with observed birch, olive, and mulberry tree pollen concentrations. Sensitivity studies suggest that the estimation of the pollen pool is a major source of uncertainty for simulated pollen concentrations. Achieving agreement between emission modeling and observed pattern of pollen releases is the key for successful pollen concentration simulations.

Changes in land use and management have been strongly affecting mountain grassland, however, their effects on the net ecosystem exchange of CO(2) (NEE) and its components have not yet been well documented. We analysed chamber-based estimates of NEE, gross primary productivity (GPP), ecosystem respiration (R) and light use efficiency (LUE) of six mountain grasslands differing in land use and management, and thus site fertility, for the growing seasons of 2002 to 2008. The main findings of the study are that: (1) land use and management affected seasonal NEE, GPP and R, which all decreased from managed to unmanaged grasslands; (2) these changes were explained by differences in leaf area index (LAI), biomass and leaf-area-independent changes that were likely related to photosynthetic physiology; (3) diurnal variations of NEE were primarily controlled by photosynthetically active photon flux density and soil and air temperature; seasonal variations were associated with changes in LAI; (4) parameters of light response curves were generally closely related to each other, and the ratio of R at a reference temperature/ maximum GPP was nearly constant across the sites; (5) similarly to our study, maximum GPP and R for other grasslands on the globe decreased with decreasing land use intensity, while their ratio remained remarkably constant. We conclude that decreasing intensity of management and, in particular, abandonment of mountain grassland lead to a decrease in NEE and its component processes. While GPP and R are generally closely coupled during most of the growing season, GPP is more immediately and strongly affected by land management (mowing, grazing) and season. This suggests that management and growing season length, as well as their possible future changes, may play an important role for the annual C balance of mountain grassland.

Soil respiration (SR) constitutes the largest flux of CO(2) from terrestrial ecosystems to the atmosphere. However, there still exist considerable uncertainties as to its actual magnitude, as well as its spatial and interannual variability. Based on a reanalysis and synthesis of 80 site-years for 57 forests, plantations, savannas, shrublands and grasslands from boreal to tropical climates we present evidence that total annual SR is closely related to SR at mean annual soil temperature (SR(MAT)), irrespective of the type of ecosystem and biome. This is theoretically expected for non water-limited ecosystems within most of the globally occurring range of annual temperature variability and sensitivity (Q(10)). We further show that for seasonally dry sites where annual precipitation (P) is lower than potential evapotranspiration (PET), annual SR can be predicted from wet season SR(MAT) corrected for a factor related to P/PET. Our finding indicates that it can be sufficient to measure SR(MAT) for obtaining a well constrained estimate of its annual total. This should substantially increase our capacity for assessing the spatial distribution of soil CO(2) emissions across ecosystems, landscapes and regions, and thereby contribute to improving the spatial resolution of a major component of the global carbon cycle.

Grasslands comprise natural tropical savannah over managed temperate fields to tundra and cover one quarter of the Earth's land surface. Plant growth, maintenance and decay result in volatile organic compound (VOCs) emissions to the atmosphere. Furthermore, biogenic VOCs (BVOCs) are emitted as a consequence of various environmental stresses including cutting and drying during harvesting. Fluxes of BVOCs were measured with a proton-transfer-reaction-mass-spectrometer (PTR-MS) over temperate mountain grassland in Stubai Valley (Tyrol, Austria) over one growing season (2008). VOC fluxes were calculated from the disjunct PTR-MS data using the virtual disjunct eddy covariance method and the gap filling method. Methanol fluxes obtained with the two independent flux calculation methods were highly correlated ( = 0.95×-0.12, = 0.92). Methanol showed strong daytime emissions throughout the growing season - with maximal values of 9.7 nmol m s, methanol fluxes from the growing grassland were considerably higher at the beginning of the growing season in June compared to those measured during October (2.5 nmol m s). Methanol was the only component that exhibited consistent fluxes during the entire growing periods of the grass. The cutting and drying of the grass increased the emissions of methanol to up to 78.4 nmol m s. In addition, emissions of acetaldehyde (up to 11.0 nmol m s), and hexenal (leaf aldehyde, up to 8.6 nmol m s) were detected during/after harvesting.

The broad-band normalised difference vegetation index (NDVI) and the simple ratio (SR) were calculated from measurements of reflectance of photosynthetically active and short-wave radiation at two temperate mountain grasslands in Austria and related to the net ecosystem CO exchange (NEE) measured concurrently by means of the eddy covariance method. There was no significant statistical difference between the relationships of midday mean NEE with narrow- and broad-band NDVI and SR, measured during and calculated for that same time window, respectively. The skill of broad-band NDVI and SR in predicting CO fluxes was higher for metrics dominated by gross photosynthesis and lowest for ecosystem respiration, with NEE in between. A method based on a simple light response model whose parameters were parameterised based on broad-band NDVI allowed to improve predictions of daily NEE and is suggested to hold promise for filling gaps in the NEE time series. Relationships of CO flux metrics with broad-band NDVI and SR however generally differed between the two studied grassland sites indicting an influence of additional factors not yet accounted for.

Using a six year data set of eddy covariance flux measurements of sensible and latent heat, soil heat flux, net radiation, above-ground phytomass and meteorological driving forces energy partitioning was investigated at a temperate mountain grassland managed as a hay meadow in the Stubai Valley (Austria). The main findings of the study were: (i) Energy partitioning was dominated by latent heat, followed by sensible heat and the soil heat flux; (ii) When compared to standard environmental forcings, the amount of green plant matter, which due to three cuts varied considerably during the vegetation period, explained similar, and partially larger, fractions of the variability in energy partitioning; (iii) There were little, if any, indications of water stress effects on energy partitioning, despite reductions in soil water availability in combination with high evaporative demand, e.g. during the summer drought of 2003.

Increases in nitrogen (N) availability and mobility resulting from anthropogenic activities have substantially altered the N cycle, both locally and globally. Taiwan characterized by the subtropical montane landscape with abundant rainfall, downwind of the most rapidly industrializing eastern coast of China, can be a demonstration site for extremely high N input and riverine DIN (dissolved inorganic N) export. We used 49 watersheds with similar climatic and landscape settings but classified into low, moderate, and highly disturbed categories based on population density to illustrate their differences in nitrogen inputs (through atmospheric N deposition, synthetic fertilizers, and human emission) and DIN export ratios. Our results showed that the island-wide average riverine DIN export is ~ 3800 kg N km yr, approximately 18 times the global average. The average riverine DIN export ratios are 0.30-0.51, which are much higher than the averages of 0.20-0.25 of large rivers around the world, indicating excessive N input relative to ecosystem demand or retention capacity. The low disturbed watersheds have a high N retention capacity and DIN export ratios of 0.06-0.18 in spite of the high N input (~ 4900 kg N km yr). The high retention capacity is likely due to effective uptake by secondary forests in the watersheds. The moderately disturbed watersheds show a linear increase in DIN export with increases in total N inputs and mean DIN export ratios of 0.20 to 0.31. The main difference in land use between low and moderately disturbed watersheds is the greater proportion of agricultural land cover in the moderately disturbed watersheds. Thus, their greater DIN export could be attributed to N fertilizers used in the agricultural lands. The greater export ratios also imply that agricultural lands have a lower proportional N retention capacity and that reforestation could be an effective land management practice to reduce riverine DIN export. The export ratios of the highly disturbed watersheds are very high, 0.42-0.53, suggesting that much of the N input is transported downstream directly, and urges the need to increase the proportion of households connected to a sewage system and improve the effectiveness of wastewater treatment systems. The increases in the riverine DIN export ratio along the gradient of human disturbance also suggest a gradient in N saturation in subtropical Taiwan. Our results help to improve our understanding of factors controlling riverine DIN export and provide empirical evidence that calls for sound N emission/pollution control measures.

Forty years ago, lichens were identified as extraordinary biological ice nucleators (INs) that enable ice formation at temperatures close to 0°C. By employing INs, lichens thrive in freezing environments that surpass the physiological limits of other vegetation, thus making them the majority of vegetative biomass in northern ecosystems. Aerosolized lichen INs might further impact cloud glaciation and have the potential to alter atmospheric processes in a warming Arctic. Despite the ecological importance and formidable ice nucleation activities, the abundance, diversity, sources, and role of ice nucleation in lichens remain poorly understood. Here, we investigate the ice nucleation capabilities of lichens collected from various ecosystems across Alaska. We find ice-nucleating activity in lichen to be widespread, particularly in the coastal rainforest of Southeast Alaska. Across 29 investigated lichen, all species show ice nucleation temperatures above -15 °C and ~30% initiate freezing at temperatures above -6 °C. Concentration series of lichen ice nucleation assays in combination with statistical analysis reveal that the lichens contain two subpopulations of INs, similar to previous observations in bacteria. However, unlike the bacterial INs, the lichen INs appear as independent subpopulations resistant to freeze-thaw cycles and against temperature treatment. The ubiquity and high stability of the lichen INs suggest that they can impact local atmospheric processes and that ice nucleation activity is an essential trait for their survival in cold environments.

This study describes and implements an integrated, multimedia, process-based system-level approach to estimating nitrogen (N) fate and transport in large river basins. The modeling system includes the following components: (1) Community Multiscale Air Quality (CMAQ),(2) Weather Research and Forecasting Model (WRF), (3) Environmental Policy Integrated Climate (EPIC), and (4) Soil and Water Assessment Tool (SWAT). The previously developed Fertilizer Emission Scenario Tool for CMAQ (FEST-C), an advanced user interface, integrated EPIC with the WRF model and CMAQ. The FEST-C system, driven by process-based WRF weather simulations, includes atmospheric N additions to agricultural cropland and agricultural cropland contributions to ammonia emissions. This study focuses on integrating the watershed hydrology and water quality model with FEST-C system so that a full multimedia assessment on water quality in large river basins to address impacts of fertilization, meteorology, and atmospheric N deposition on water quality can be achieved. Objectives of this paper are to describe how to expand the previous effort by integrating the SWAT model with the FEST-C (CMAQ/WRF/EPIC) modeling system, as well as to demonstrate application of the Integrated Modeling System (IMS) to the Mississippi River basin (MRB) to simulate streamflow and dissolved N loadings to the Gulf of Mexico (GOM). IMS simulation results generally agree with US Geological Survey (USGS) observations/estimations; the annual simulated streamflow is 218.9 mm and USGS observation is 211.1 mm and the annual simulated dissolved N is 2.1 kg ha and the USGS estimation is 2.8 kg ha. Integrating SWAT with the CMAQ/WRF/EPIC modeling system allows for its use within large river basins without losing EPIC's more detailed biogeochemistry processes, which will strengthen the assessment of impacts of future climate scenarios, regulatory and voluntary programs for N oxide air emissions, and land use and land management on N transport and transformation in large river basins.

A new global estimate of surface turbulent fluxes, latent heat flux (LE) and sensible heat flux (H), and gross primary production (GPP) is developed using a machine learning approach informed by novel remotely sensed Solar-Induced Fluorescence (SIF) and other radiative and meteorological variables. This is the first study to jointly retrieve LE, H and GPP using SIF observations. The approach uses an artificial neural network (ANN) with a target dataset generated from three independent data sources, weighted based on triple collocation (TC) algorithm. The new retrieval, named Water, Energy, and Carbon with Artificial Neural Networks (WECANN), provides estimates of LE, H and GPP from 2007 to 2015 at 1° × 1° spatial resolution and on monthly time resolution. The quality of ANN training is assessed using the target data, and the WECANN retrievals are evaluated using eddy covariance tower estimates from FLUXNET network across various climates and conditions. When compared to eddy covariance estimates, WECANN typically outperforms other products, particularly for sensible and latent heat fluxes. Analysing WECANN retrievals across three extreme drought and heatwave events demonstrates the capability of the retrievals in capturing the extent of these events. Uncertainty estimates of the retrievals are analysed and the inter-annual variability in average global and regional fluxes show the impact of distinct climatic events - such as the 2015 El Niño - on surface turbulent fluxes and GPP.

Bubbles adsorb and transport particulate matter both in industrial and marine systems. While methane-containing bubbles emitted from anoxic sediments are found extensively in aquatic ecosystems, relatively little attention has been paid to the possibility that such bubbles transport particle-associated chemical or biological material from sediments to surface waters of freshwater lakes. We quantified transport of particulate material from sediments to the surface by bubbles in Upper Mystic Lake, MA and in a 15 m tall experimental column. Vertical particle transport was positively correlated with the volume of gas bubbles released from the sediment. Particles transported by bubbles originated almost entirely in the sediment, rather than being scavenged from the water column. Concentrations of arsenic, chromium, lead, and cyanobacterial cells in bubble-transported particulate material were similar to those of bulk sediment, and particles were transported from depths exceeding 15 m, resulting in daily fluxes as large as 0.18 mg of arsenic m and 2 × 10 cyanobacterial cells m in the strongly stratified Upper Mystic Lake. While bubble-facilitated arsenic transport currently appears to be a modest component of total arsenic cycling in this lake, bubble-facilitated cyanobacterial transport could comprise as much as 17% of recruitment in this lake and may thus be of particular importance in large, deep, stratified lakes.

We have compared a suite of recent global CO atmospheric inversion results to independent airborne observations and to each other, to assess their dependence on differences in northern extratropical (NET) vertical transport and to identify some of the drivers of model spread. We evaluate posterior CO concentration profiles against observations from the High-Performance Instrumented Airborne Platform for Environmental Research (HIAPER) Pole-to-Pole Observations (HIPPO) aircraft campaigns over the mid-Pacific in 2009-2011. Although the models differ in inverse approaches, assimilated observations, prior fluxes, and transport models, their broad latitudinal separation of land fluxes has converged significantly since the Atmospheric Carbon Cycle Inversion Intercomparison (TransCom 3) and the REgional Carbon Cycle Assessment and Processes (RECCAP) projects, with model spread reduced by 80% since TransCom 3 and 70% since RECCAP. Most modeled CO fields agree reasonably well with the HIPPO observations, specifically for the annual mean vertical gradients in the Northern Hemisphere. Northern Hemisphere vertical mixing no longer appears to be a dominant driver of northern versus tropical (T) annual flux differences. Our newer suite of models still gives northern extratropical land uptake that is modest relative to previous estimates (Gurney et al., 2002; Peylin et al., 2013) and near-neutral tropical land uptake for 2009-2011. Given estimates of emissions from deforestation, this implies a continued uptake in intact tropical forests that is strong relative to historical estimates (Gurney et al., 2002; Peylin et al., 2013). The results from these models for other time periods (2004-2014, 2001-2004, 1992-1996) and reevaluation of the TransCom 3 Level 2 and RECCAP results confirm that tropical land carbon fluxes including deforestation have been near neutral for several decades. However, models still have large disagreements on ocean-land partitioning. The fossil fuel (FF) and the atmospheric growth rate terms have been thought to be the best-known terms in the global carbon budget, but we show that they currently limit our ability to assess regional-scale terrestrial fluxes and ocean-land partitioning from the model ensemble.

Rapid Arctic warming, a lengthening growing season, and the increasing abundance of biogenic volatile-organic-compound-emitting shrubs are all anticipated to increase atmospheric biogenic volatile organic compounds (BVOCs) in the Arctic atmosphere, with implications for atmospheric oxidation processes and climate feedbacks. Quantifying these changes requires an accurate understanding of the underlying processes driving BVOC emissions in the Arctic. While boreal ecosystems have been widely studied, little attention has been paid to Arctic tundra environments. Here, we report terpenoid (isoprene, monoterpenes, and sesquiterpenes) ambient mixing ratios and emission rates from key dominant vegetation species at Toolik Field Station (TFS; 68°38' N, 149°36' W) in northern Alaska during two back-to-back field campaigns (summers of 2018 and 2019) covering the entire growing season. Isoprene ambient mixing ratios observed at TFS fell within the range of values reported in the Eurasian taiga (0-500 parts per trillion by volume - pptv), while monoterpene and sesquiterpene ambient mixing ratios were respectively close to and below the instrumental quantification limit (~ 2 pptv). Isoprene surface emission rates ranged from 0.2 to 2250 μgC m h (mean of 85 μgC m h) and monoterpene emission rates remained, on average, below 1 μgC m h over the course of the study. We further quantified the temperature dependence of isoprene emissions from local vegetation, including spp. (a known isoprene emitter), and compared the results to predictions from the Model of Emissions of Gases and Aerosols from Nature version 2.1 (MEGAN2.1). Our observations suggest a 180 %-215 % emission increase in response to a 3-4°C warming, and the MEGAN2.1 temperature algorithm exhibits a close fit with observations for enclosure temperatures in the 0-30°C range. The data presented here provide a baseline for investigating future changes in the BVOC emission potential of the under-studied Arctic tundra environment.