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Carbon storage by the ocean and by the land is usually quantified separately, and does not fully take into account the land-to-ocean transport of carbon through inland waters, estuaries, tidal wetlands and continental shelf waters—the ‘land-to-ocean aquatic continuum’ (LOAC). Here we assess LOAC carbon cycling before the industrial period and perturbed by direct human interventions, including climate change. In our view of the global carbon cycle, the traditional ‘long-range loop’, which carries carbon from terrestrial ecosystems to the open ocean through rivers, is reinforced by two ‘short-range loops’ that carry carbon from terrestrial ecosystems to inland waters and from tidal wetlands to the open ocean. Using a mass-balance approach, we find that the pre-industrial uptake of atmospheric carbon dioxide by terrestrial ecosystems transferred to the ocean and outgassed back to the atmosphere amounts to 0.65 ± 0.30 petagrams of carbon per year (±2 sigma). Humans have accelerated the cycling of carbon between terrestrial ecosystems, inland waters and the atmosphere, and decreased the uptake of atmospheric carbon dioxide from tidal wetlands and submerged vegetation. Ignoring these changing LOAC carbon fluxes results in an overestimation of carbon storage in terrestrial ecosystems by 0.6 ± 0.4 petagrams of carbon per year, and an underestimation of sedimentary and oceanic carbon storage. We identify knowledge gaps that are key to reduce uncertainties in future assessments of LOAC fluxes. An assessment of the land-to-ocean cycling of carbon through inland waters, estuaries, tidal wetlands and continental shelf waters provides a perspective on the global carbon cycle and identifies key knowledge gaps.

The relative abundance of nitrate (N) over phosphorus (P) has increased over the period since 1980 in the marginal seas bordering the northwestern Pacific Ocean, located downstream of the populated and industrialized Asian continent. The increase in N availability within the study area was mainly driven by increasing N concentrations and was most likely due to deposition of pollutant nitrogen from atmospheric sources. Atmospheric nitrogen deposition had a high temporal correlation with N availability in the study area (r = 0.74 to 0.88), except in selected areas wherein riverine nitrogen load may be of equal importance. The increase in N availability caused by atmospheric deposition and riverine input has switched extensive parts of the study area from being N-limited to P-limited.

The Chesapeake Bay is a large coastal-plain estuary that has experienced considerable anthropogenic change over the past century. At the regional scale, land-use change has doubled the nutrient input from rivers and led to an increase in riverine carbon and alkalinity. The bay has also experienced global changes, including the rise of atmospheric temperature and CO2. Here we seek to understand the relative impact of these changes on the inorganic carbon balance of the bay between the early 1900s and the early 2000s. We use a linked land–estuarine–ocean modeling system that includes both inorganic and organic carbon and nitrogen cycling. Sensitivity experiments are performed to isolate the effect of changes in (1) atmospheric CO2, (2) temperature, (3) riverine nitrogen loading and (4) riverine carbon and alkalinity loading. Specifically, we find that over the past century global changes have increased ingassing by roughly the same amount (∼30 Gg-C yr−1) as has the increased riverine loadings. While the former is due primarily to increases in atmospheric CO2, the latter results from increased net ecosystem production that enhances ingassing. Interestingly, these increases in ingassing are partially mitigated by increased temperatures and increased riverine carbon and alkalinity inputs, both of which enhance outgassing. Overall, the bay has evolved over the century to take up more atmospheric CO2 and produce more organic carbon. These results suggest that over the past century, changes in riverine nutrient loads have played an important role in altering coastal carbon budgets, but that ongoing global changes have also substantially affected coastal carbonate chemistry.

Climate-induced changes in hypoxia are among the most serious threats facing estuaries, which are among the most productive ecosystems on Earth. Future projections of estuarine hypoxia typically involve long-term multi-decadal continuous simulations or more computationally efficient time slice and delta methods that are restricted to short historical and future periods. We make a first comparison of these three methods by applying a linked terrestrial–estuarine model to the Chesapeake Bay, a large coastal-plain estuary in the eastern United States. Results show that the time slice approach accurately captures the behavior of the continuous approach, indicating a minimal impact of model memory. However, increases in mean annual hypoxic volume by the mid-twenty-first century simulated by the delta approach (+ 19%) are approximately twice as large as the time slice and continuous experiments (+ 9% and + 11%, respectively), indicating an important impact of changes in climate variability. Our findings suggest that system memory and projected changes in climate variability, as well as simulation length and natural variability of system hypoxia, should be considered when deciding to apply the more computationally efficient delta and time slice methods.

Public awareness of microplastics and their widespread presence throughout most bodies of water are increasingly documented. The accumulation of microplastics in the ocean, however, appears to be far less than their riverine inputs, suggesting that there is a “missing sink” of plastics in the ocean. Estuaries have long been recognized as filters for riverine material in marine biogeochemical budgets. Here we use a model of estuarine microplastic transport to test the hypothesis that the Chesapeake Bay, a large coastal-plain estuary in eastern North America, is a potentially large filter, or “sink,” of riverine microplastics. The 1-year composite simulation, which tracks an equal number of buoyant and sinking 5-mm diameter particles, shows that 94% of riverine microplastics are beached, with only 5% exported from the Bay, and 1% remaining in the water column. We evaluate the robustness of this finding by conducting additional simulations in a tributary of the Bay for different years, particle densities, particle sizes, turbulent dissipation rates, and shoreline characteristics. The resulting microplastic transport and fate were sensitive to interannual variability over a decadal (2010–2019) analysis, with greater export out of the Bay during high streamflow years. Particle size was found to be unimportant while particle density – specifically if a particle was buoyant or not – was found to significantly influence overall fate and mean duration in the water column. Positively buoyant microplastics are more mobile due to being in the seaward branch of the residual estuarine circulation while negatively buoyant microplastics are transported a lesser distance due to being in the landward branch, and therefore tend to deposit on coastlines close to their river sources, which may help guide sampling campaigns. Half of all riverine microplastics that beach do so within 7–13 days, while those that leave the bay do so within 26 days. Despite microplastic distributions being sensitive to some modeling choices (e.g., particle density and shoreline hardening), in all scenarios most of riverine plastics do not make it to the ocean, suggesting that estuaries may serve as a filter for riverine microplastics.

Categorization of storm surge with the Saffir–Simpson hurricane scale has been a useful means of communicating potential impacts for decades. However, storm surge was removed from this scale following Hurricane Katrina (2005), leaving no scale-based method for storm surge risk communication despite its significant impacts on life and property. This study seeks to create a new, theoretical storm surge scale based on fiscal damage for effective risk analysis. Advanced Circulation model simulation output data of maximum water height and velocity were obtained for four storms: Hurricane Katrina, Hurricane Gustav, Hurricane Ike, and Superstorm Sandy. Four countywide fiscal loss methods were then considered. The first three use National Centers for Environmental Information Storm Events Database (SED) property damages and Bureau of Economic Analysis (BEA) population, per capita personal income, or total income. The fourth uses National Flood Insurance Program total insured coverage and paid claims. Initial correlations indicated the statistical mode of storm surge data above the 90th percentile was most skillful; this metric was therefore chosen to represent countywide storm surge. Multiple linear regression assessed the most skillful combination of storm surge variables (height and velocity) and fiscal loss method (SED property damages and BEA population, i.e., loss per capita), and defined the proposed scale, named the Kuykendall scale. Comparison with the four storms’ actual losses shows skillful performance, notably a 20% skill increase over surge height-only approaches. The Kuykendall scale demonstrates promise for skillful future storm surge risk assessment in the analytical, academic, and operational domains.

Coastal ecosystems release or absorb carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), but the net effects of these ecosystems on the radiative balance remain unknown. We compiled a dataset of observations from 738 sites from studies published between 1975 and 2020 to quantify CO2, CH4 and N2O fluxes in estuaries and coastal vegetation in ten global regions. We show that the CO2-equivalent (CO2e) uptake by coastal vegetation is decreased by 23–27% due to estuarine CO2e outgassing, resulting in a global median net sink of 391 or 444 TgCO2e yr−1 using the 20- or 100-year global warming potentials, respectively. Globally, total coastal CH4 and N2O emissions decrease the coastal CO2 sink by 9–20%. Southeast Asia, North America and Africa are critical regional hotspots of GHG sinks. Understanding these hotspots can guide our efforts to strengthen coastal CO2 uptake while effectively reducing CH4 and N2O emissions.The authors show that estuarine and coastal vegetation are collectively a greenhouse gas (GHG) sink for the atmosphere, but methane and nitrous oxide emissions counteract the carbon dioxide uptake. Critical coastal GHG sink hotspots are identified in Southeast Asia, North America and Africa.

A challenge for climate impact studies is the selection of a limited number of climate model projections among the dozens that are typically available. Here, we examine the impacts of methods for climate model selection on projections of runoff change for five different watersheds across the conterminous USA. The results from an ensemble of 29 global climate models and 29 corresponding hydrological model simulations are compared with the results that would have been obtained by applying six different selection methods to the climate model data and using only the selected models to drive the hydrological model. We evaluate each selection method based on whether the runoff projections produced by the method meet the method’s objective and on whether the results are sensitive to the number of models chosen. The Katsavounidis–Kuo–Zhang (KKZ) method, which is intended to maximize the spread in the projected climate change, was the only method that met both criteria for suitability. Although the KKZ method generally performed well, the results from both it and the other methods varied somewhat unpredictably based on region and number of models chosen. This study shows that the methods and models used in similar top–down studies should be carefully chosen and that the results obtained should be interpreted with caution.

Rapid bio-oxidation of carbon monoxide (CO), a photoproduct of dissolved organic matter, results in diel cycles reflecting photochemical-biogeochemical-physical interactions. These cycles were characterized by time-series studies of hydrography, meteorology, insolation, optics, and CO concentration ([CO]). Diel patterns of near-surface [CO] generally varied little seasonally, despite different forcings. In summer 30% of CO was below the mixed layer (ML); ML depths and optics indicate that two-layer photochemistry is common elsewhere. [CO] decayed at similar rates in both isolated layers. In spring CO extended to 150 m, reflecting nocturnal mixing. Cruise-average profiles indicated a shallower ML defined by CO than that defined by density, illustrating short-lived CO's sensitivity to recent mixing. Below the ML, [CO] dropped exponentially with depth on scales controlled by photoproduction in summer but mixing in spring. Mass-balance modeling of diurnal variations in CO column burden (CB) gave similar production rates in summer and spring (~50 /miol m⁻² d⁻¹ CO), but different biooxidation rates, 1.5 ± 0.2 d⁻¹ (summer, 0-50 m) and 0.52-0.66 d⁻¹ (spring, 0-200 m). Outgassing averaged 4% of bio-oxidation in summer and 14% in spring. Similar production and differing sinks resulted in different CBs: 39.3 µmol m⁻² (summer) versus 94.9 µmol m⁻² (spring). Insolation-normalized CO productions were 1.8 times those in the oligotrophic equatorial Pacific. Improved, well-blanked analyses found [CO] at 200 m always <0.1 nmol L⁻¹ in summer, and usually in spring. Prior reports of [CO] systematically >0.2 nmol L⁻¹ at depth in well-stratified, oxic blue waters may be high because of method artifacts.

Numerical models are often used to simulate estuarine physics and water quality under scenarios of future climate conditions. However, representing the wide range of uncertainty about future climate often requires an infeasible number of computationally expensive model simulations. Here, we develop and test a computationally inexpensive statistical model, or metamodel, as a surrogate for numerical model simulations. We show that a metamodel fit using only 12 numerical model simulations of Chesapeake Bay can accurately predict the early summer mean salinity, stratification, and circulation simulated by the numerical model given the input sea level, winter–spring streamflow, and tidal amplitude along the shelf. We then use this metamodel to simulate summer salinity and circulation under sampled probability distributions of projected future mean sea level, streamflow, and tidal amplitudes. The simulations from the metamodel show that future salinity, stratification, and circulation are all likely to be higher than present-day averages. We also use the metamodel to quantify how uncertainty about the model inputs transfers to uncertainty in the output and find that the model projections of salinity and stratification are highly sensitive to uncertainty about future tidal amplitudes along the shelf. This study shows that metamodels are a promising approach for robustly estimating the impacts of future climate change on estuaries.