Driving factors of colored dissolved organic matter dynamics across a complex urbanized estuary.

The role of estuaries in sourcing and transforming dissolved organic matter - the largest reservoir of organic carbon in the ocean - still presents many unknowns for coastal biogeochemical cycles, and is further complicated by increasing human pressures and a changing climate. Here, we examined the major drivers of colored dissolved organic matter (CDOM) dynamics in Long Island Sound (LIS), a heavily urbanized estuary of National Significance with a storied water quality past. A comprehensive new optical dataset, including measurements of CDOM absorption and fluorescence signatures, was integrated with biological and hydrological measurements to capture the spatiotemporal heterogeneities of LIS, including its urban-to-rural gradient, dynamic river mouths, and blue carbon ecosystems across seasons, following episodic storm events, and over five years. Results reveal longitudinal gradients in both DOM amount and quality. While carbon-rich and humic terrigenous DOM was dominant in the heavily riverine-influenced Central to Eastern LIS, an uncoupling between CDOM absorption (aCDOM) and dissolved organic carbon (DOC) concentration in Western LIS, and a stronger correlation with Chlorophyll-a, indicated increased autochthonous CDOM production. Closer to the New York City urban core, aCDOM was highly correlated to turbidity, consistent with increased wastewater influences. Fluorescence PARAFAC analysis provided strong evidence for seasonal processing of CDOM in LIS, related to increased summertime photochemical degradation of humic-like components and shoulder-season microbial processing. Riverine CDOM export was influenced by discharge amount, residence time, and coastal wetlands acting as additional sources of strongly humic and aromatic organic matter. These measurements allowed us to assess how hydrologic, biological, and anthropogenic processes impact DOM dynamics and, subsequently, biogeochemical variability and trophic status in this complex urbanized estuary, with implications for water quality management and policy. Results discussed here are applicable beyond LIS, as urbanized estuaries globally face similar hydrological and anthropogenic forcings.

Phytoplankton assemblage responses to nitrogen following COVID-19 stay-in-place orders in western Long Island Sound (New York/Connecticut).

This study evaluated water quality, nitrogen (N), and phytoplankton assemblage linkages along the western Long Island Sound (USA) shoreline (Nov. 2020-Dec. 2021) following COVID-19 stay-in-place (SIP) orders through monthly surveys and N-addition bioassays. Ammonia-N (AmN; NH3+NH4+) negatively correlated with total chlorophyll-a (chl-a) at all sites; this was significant at Alley Creek, adjacent to urban wastewater inputs, and at Calf Pasture, by the Norwalk River (Spearman rank correlation, p < 0.01 and 0.02). Diatoms were abundant throughout the study, though dinoflagellates (Heterocapsa, Prorocentrum), euglenoids/cryptophytes, and both nano- and picoplankton biomass increased during summer. In field and experimental assessments, high nitrite + nitrate (N + N) and low AmN increased diatom abundances while AmN was positively linked to cryptophyte concentrations. Likely N + N decreases with presumably minimal changes in AmN and organic N during COVID-19 SIP resulted in phytoplankton assemblage shifts (decreased diatoms, increased euglenoids/cryptophytes), highlighting the ecological impacts of N-form delivered by wastewater to urban estuaries.

Intimately tracking NO2 pollution over the New York City - Long Island Sound land-water continuum: An integration of shipboard, airborne, satellite observations, and models.

Nitrogen dioxide (NO2) pollution remains a serious global problem, particularly near highly populated urbanized coasts that face increasing challenges with climate change. Yet, the combined impact of urban emissions, pollution transport, and complex meteorology on the spatiotemporal dynamics of NO2 along heterogeneous urban coastlines remains poorly characterized. Here, we integrated measurements from different platforms - boats, ground-based networks, aircraft, and satellites - to characterize total column NO2 (TCNO2) dynamics across the land-water continuum in the New York metropolitan area, the most populous area in the United States that often experiences the highest national NO2 levels. Measurements were conducted during the 2018 Long Island Sound Tropospheric Ozone Study (LISTOS), with a main goal to extend surface measurements beyond the coastline - where ground-based air-quality monitoring networks abruptly stop - and over the aquatic environment where peaks in air pollution often occur. Satellite TCNO2 from TROPOMI correlated strongly with Pandora surface measurements (r = 0.87, N = 100) both over land and water. Yet, TROPOMI overall underestimated TCNO2 (MPD = -12%) and missed peaks in NO2 pollution caused by rush hour emissions or pollution accumulation during sea breezes. Aircraft retrievals were in excellent agreement with Pandora (r = 0.95, MPD = -0.3%, N = 108). Stronger agreement was found between TROPOMI, aircraft, and Pandora over land, while over water satellite, and to a lesser extent aircraft, retrievals underestimated TCNO2 particularly in the highly dynamic New York Harbor environment. Combined with model simulations, our shipborne measurements uniquely captured rapid transitions and fine-scale features in NO2 behavior across the New York City - Long Island Sound land-water continuum, driven by the complex interplay of human activity, chemistry, and local scale meteorology. These novel datasets provide critical information for improving satellite retrievals, enhancing air quality models, and informing management decisions, with important implications for the health of diverse communities and vulnerable ecosystems along this complex urban coastline.

Deciphering the water quality impacts of COVID-19 human mobility shifts in estuaries surrounding New York City.

The COVID-19 pandemic altered human mobility, particularly in large metropolitan areas. In New York City (NYC), stay-at-home orders and social distancing led to significant decreases in commuting, tourism, and a surge of outward migration. Such changes could result in decreased anthropogenic pressure on local environments. Several studies have linked COVID-19 shutdowns with improvements in water quality. However, the bulk of these studies primarily focused on short-term impacts during shutdown periods, without assessing longer-term impacts as restrictions eased. Here, we examine both concurrent lockdown and societal reopening impacts on water quality, using pre-pandemic baseline conditions, in two highly urbanized estuaries surrounding NYC, the New-York Harbor estuary and Long Island Sound (LIS). We compiled datasets from 2017 to 2021 of mass-transit ridership, work-from-home trends, and municipal wastewater effluent to assess changes in human mobility and anthropogenic pressure during multiple waves of the pandemic in 2020 and 2021. These were linked to changes in water quality assessed using high spatiotemporal ocean color remote sensing, which provides near-daily observations across the estuary study regions. To distinguish anthropogenic impacts from natural environmental variability, we examined meteorological/hydrological conditions, primarily precipitation and wind. Our results show that nitrogen loading into the New York Harbor declined significantly in the spring of 2020 and remained below pre-pandemic values through 2021. In contrast, nitrogen loading into LIS remained closer to the pre-pandemic average. In response, water clarity in New-York Harbor significantly improved, with less of a change in LIS. We further show that changes in nitrogen loading had higher impact on water quality than meteorological conditions. Our study demonstrates the value of remote sensing observations in assessing water quality changes when field-based monitoring is hindered and highlights the complex nature of urban estuaries and their heterogeneous response to changes in extreme events and human behavior.

Marsh archive reveals human population history and future implications for estuarine health in Long Island Sound.

Coastal marshes are efficient ecosystems providing a multitude of benefits for invertebrates, birds, fish and humans alike. Yet despite these benefits, wetlands are threatened by anthropogenic inputs such as human wastewater which contain high levels of nitrogen (N). Increased nitrogen loads cause eutrophication and hypoxia in estuaries leading to further degradation of these valuable ecosystems that are already stressed by sea level rise and climate change. Policies to protect wetlands via wastewater treatments are reactive rather than proactive and a growing body of research shows that characteristics associated with population health and economic activity can be identified in wastewater. Analysis of a 2-m salt marsh sediment core reveals δN15 signatures indicative of human population rise and connects human impact to ecosystem health. Using key X-ray fluorescence (XRF), pollen, sediment and nitrogen signatures along the core, a robust chronology was produced dating back to 1700. This result was coupled with population data to observe the relationship between δN15 levels and population over three centuries. There is a statistically significant positive correlation between δN15 and population. Other external factors such as federal government policies (regulating clean water) show a clear reduction in this association but the use of synthetic nitrogen fertilizer masks the strength of this relationship. Further research to refine the relationship between population and δN15 could be beneficial in predicting nitrogen loads as human population grows, which in turn would create a proactive system to protect our coastal ecosystems.

Transitions in nitrogen and organic matter form and concentration correspond to bacterial population dynamics in a hypoxic urban estuary.

Nitrogen (N) inputs to developed coastlines are linked with multiple ecosystem and socio-economic impacts worldwide such as algal blooms, habitat/resource deterioration, and hypoxia. This study investigated the microbial and biogeochemical processes associated with recurrent, seasonal bottom-water hypoxia in an urban estuary, western Long Island Sound (WLIS), that receives high N inputs. A 2-year (2020-2021) field study spanned two hypoxia events and entailed surface and bottom depth water sampling for dissolved nutrients as inorganic N (DIN; ammonia-N and nitrite + nitrate (N + N)), organic N, orthophosphate, organic carbon (DOC), as well as chlorophyll a and bacterial abundances. Physical water quality data were obtained from concurrent conductivity, temperature, and depth casts. Results showed that dissolved organic matter was highest at the most-hypoxic locations, DOC was negatively and significantly correlated with bottom-water dissolved oxygen (Pearson's r = -0.53, p = 0.05), and ammonia-N was the dominant DIN form pre-hypoxia before declining throughout hypoxia. N + N concentrations showed the reverse, being minimal pre-hypoxia then increasing during and following hypoxia, indicating that ammonia oxidation likely contributed to the switch in dominant DIN forms and is a key pathway in WLIS water column nitrification. Similarly, at the most hypoxic sampling site, bottom depth bacteria concentrations ranged ~ 1.8 × 104-1.1 × 105 cells ml-1 pre-hypoxia, declined throughout hypoxia, and were positively and significantly correlated (Pearson's r = 0.57; p = 0.03) with ammonia-N, confirming that hypoxia influences N-cycling within LIS. These findings provide novel insight to feedbacks between major biogeochemical (N and C) cycles and hypoxia in urban estuaries. Supplementary Information: The online version contains supplementary material available at 10.1007/s10533-023-01021-2.

Optical classification of an urbanized estuary using hyperspectral remote sensing reflectance.

Optical water classification based on remote sensing reflectance (Rrs(λ)) data can provide insight into water components driving optical variability and inform the development and application of bio-optical algorithms in complex aquatic systems. In this study, we use an in situ dataset consisting of hyperspectral Rrs(λ) and other biogeochemical and optical parameters collected over nearly five years across a heavily urbanized estuary, the Long Island Sound (LIS), east of New York City, USA, to optically classify LIS waters based on Rrs(λ) spectral shape. We investigate the similarities and differences of discrete groupings (k-means clustering) and continuous spectral indexing using the Apparent Visible Wavelength (AVW) in relation to system biogeochemistry and water properties. Our Rrs(λ) dataset in LIS was best described by three spectral clusters, the first two accounting for the majority (89%) of Rrs(λ) observations and primarily driven by phytoplankton dynamics, with the third confined to measurements in river and river plume waters. We found AVW effective at tracking subtle changes in Rrs(λ) spectral shape and fine-scale water quality features along river-to-ocean gradients. The recently developed Quality Water Index Polynomial (QWIP) was applied to evaluate three different atmospheric correction approaches for satellite-derived Rrs(λ) from the Sentinel-3 Ocean and Land Colour Instrument (OLCI) sensor in LIS, finding Polymer to be the preferred approach. Our results suggest that integrative, continuous indices such as AVW can be effective indicators to assess nearshore biogeochemical variability and evaluate the quality of both in situ and satellite bio-optical datasets, as needed for improved ecosystem and water resource management in LIS and similar regions.

Investigating Changes in Ozone Formation Chemistry during Summertime Pollution Events over the Northeastern United States.

Understanding the local-scale spatial and temporal variability of ozone formation is crucial for effective mitigation. We combine tropospheric vertical column densities (VCDTrop) of formaldehyde (HCHO) and nitrogen dioxide (NO2), referred to as HCHO-VCDTrop and NO2-VCDTrop, retrieved from airborne remote sensing and the TROPOspheric Monitoring Instrument (TROPOMI) with ground-based measurements to investigate changes in ozone precursors and the inferred chemical production regime on high-ozone days in May-August 2018 over two Northeast urban domains. Over New York City (NYC) and Baltimore/Washington D.C. (BAL/DC), HCHO-VCDTrop increases across the domain, but higher NO2-VCDTrop occurs mainly in urban centers on ozone exceedance days (when maximum daily 8 h average (MDA8) ozone exceeds 70 ppb at any monitor in the region). The ratio of HCHO-VCDTrop to NO2-VCDTrop, proposed as an indicator of the sensitivity of local surface ozone production rates to its precursors, generally increases on ozone exceedance days, implying a transition toward a more NOx-sensitive ozone production regime that should lead to higher efficacy of NOx controls on the highest ozone days in NYC and BAL/DC. Warmer temperatures and enhanced influence from emissions in the local boundary layer on the high-ozone days are accompanied by slower wind speeds in BAL/DC but stronger, southwesterly winds in NYC.

Declines and peaks in NO2 pollution during the multiple waves of the COVID-19 pandemic in the New York metropolitan area.

The COVID-19 pandemic created an extreme natural experiment in which sudden changes in human behavior and economic activity resulted in significant declines in nitrogen oxide (NO x ) emissions, immediately after strict lockdowns were imposed. Here we examined the impact of multiple waves and response phases of the pandemic on nitrogen dioxide (NO2) dynamics and the role of meteorology in shaping relative contributions from different emission sectors to NO2 pollution in post-pandemic New York City. Long term (> 3.5 years), high frequency measurements from a network of ground-based Pandora spectrometers were combined with TROPOMI satellite retrievals, meteorological data, mobility trends, and atmospheric transport model simulations to quantify changes in NO2 across the New York metropolitan area. The stringent lockdown measures after the first pandemic wave resulted in a decline in top-down NO x emissions by approx. 30% on top of long-term trends, in agreement with sector-specific changes in NO x emissions. Ground-based measurements showed a sudden drop in total column NO2 in spring 2020, by up to 36% in Manhattan and 19%-29% in Queens, New Jersey (NJ), and Connecticut (CT), and a clear weakening (by 16%) of the typical weekly NO2 cycle. Extending our analysis to more than a year after the initial lockdown captured a gradual recovery in NO2 across the NY/NJ/CT tri-state area in summer and fall 2020, as social restrictions eased, followed by a second decline in NO2 coincident with the second wave of the pandemic and resurgence of lockdown measures in winter 2021. Meteorology was not found to have a strong NO2 biassing effect in New York City after the first pandemic wave. Winds, however, were favorable for low NO2 conditions in Manhattan during the second wave of the pandemic, resulting in larger column NO2 declines than expected based on changes in transportation emissions alone. Meteorology played a key role in shaping the relative contributions from different emission sectors to NO with low-speed (< 5 ms-1) SW-SE winds enhancing contributions from the high-emitting power-generation sector in NJ and Queens and driving particularly high NO2 pollution episodes in Manhattan, even during - and despite - the stringent early lockdowns. These results have important implications for air quality management in New York City, and highlight the value of high resolution NO2 measurements in assessing the effects of rapid meteorological changes on air quality conditions and the effectiveness of sector-specific NO x emission control strategies.

The Transformation and Export of Organic Carbon Across an Arctic River-Delta-Ocean Continuum.

The Arctic Ocean is surrounded by land that feeds highly seasonal rivers with water enriched in high concentrations of dissolved and particulate organic carbon (DOC and POC). Explicit estimates of the flux of organic carbon across the land-ocean interface are difficult to quantify and many interdependent processes makes source attribution difficult. A high-resolution 3-D biogeochemical model was built for the lower Yukon River and coastal ocean to estimate biogeochemical cycling across the land-ocean continuum. The model solves for complex reactions related to organic carbon transformation, including mechanistic photodegradation and multi-reactivity microbial processing, DOC-POC flocculation, and phytoplankton dynamics. The baseline DOC and POC flux out of the delta from April to September 2019, was 977 and 536 Gg C (∼80% of the annual total), but only 50% of the DOC and 25% of the POC exited the plume across the 10 m isobath. Microbial breakdown of DOC accounted for a net loss of 168 Gg C (17% of delta export) within the plume and photodegradation accounted for a net loss of 46.6 Gg C DOC (5% of delta export) in 2019. Flocculation decreased the total organic carbon flux by only 6.4 Gg C (∼1%), while POC sinking accounted for 63.3 Gg C (10%) settling in the plume. The loss of chromophoric dissolved organic matter due to photodegradation increased the light available for phytoplankton growth throughout the coastal ocean, demonstrating the secondary effects that organic carbon reactions can have on biological processes and the net coastal carbon flux.

DOM degradation by light and microbes along the Yukon River-coastal ocean continuum.

The Arctic is experiencing rapid warming, resulting in fundamental shifts in hydrologic connectivity and carbon cycling. Dissolved organic matter (DOM) is a significant component of the Arctic and global carbon cycle, and significant perturbations to DOM cycling are expected with Arctic warming. The impact of photochemical and microbial degradation, and their interactive effects, on DOM composition and remineralization have been documented in Arctic soils and rivers. However, the role of microbes, sunlight and their interactions on Arctic DOM alteration and remineralization in the coastal ocean has not been considered, particularly during the spring freshet when DOM loads are high, photoexposure can be quite limited and residence time within river networks is low. Here, we collected DOM samples along a salinity gradient in the Yukon River delta, plume and coastal ocean during peak river discharge immediately after spring freshet and explored the role of UV exposure, microbial transformations and interactive effects on DOM quantity and composition. Our results show: (1) photochemical alteration of DOM significantly shifts processing pathways of terrestrial DOM, including increasing relative humification of DOM by microbes by > 10%; (2) microbes produce humic-like material that is not optically distinguishable from terrestrial humics; and (3) size-fractionation of the microbial community indicates a size-dependent role for DOM remineralization and humification of DOM observed through modeled PARAFAC components of fluorescent DOM, either through direct or community effects. Field observations indicate apparent conservative mixing along the salinity gradient; however, changing photochemical and microbial alteration of DOM with increasing salinity indicate changing DOM composition likely due to microbial activity. Finally, our findings show potential for rapid transformation of DOM in the coastal ocean from photochemical and microbial alteration, with microbes responsible for the majority of dissolved organic matter remineralization.

Integrating Inland and Coastal Water Quality Data for Actionable Knowledge.

Water quality measures for inland and coastal waters are available as discrete samples from professional and volunteer water quality monitoring programs and higher-frequency, near-continuous data from automated in situ sensors. Water quality parameters also are estimated from model outputs and remote sensing. The integration of these data, via data assimilation, can result in a more holistic characterization of these highly dynamic ecosystems, and consequently improve water resource management. It is becoming common to see combinations of these data applied to answer relevant scientific questions. Yet, methods for scaling water quality data across regions and beyond, to provide actionable knowledge for stakeholders, have emerged only recently, particularly with the availability of satellite data now providing global coverage at high spatial resolution. In this paper, data sources and existing data integration frameworks are reviewed to give an overview of the present status and identify the gaps in existing frameworks. We propose an integration framework to provide information to user communities through the the Group on Earth Observations (GEO) AquaWatch Initiative. This aims to develop and build the global capacity and utility of water quality data, products, and information to support equitable and inclusive access for water resource management, policy and decision making.

Representing the function and sensitivity of coastal interfaces in Earth system models.

Between the land and ocean, diverse coastal ecosystems transform, store, and transport material. Across these interfaces, the dynamic exchange of energy and matter is driven by hydrological and hydrodynamic processes such as river and groundwater discharge, tides, waves, and storms. These dynamics regulate ecosystem functions and Earth's climate, yet global models lack representation of coastal processes and related feedbacks, impeding their predictions of coastal and global responses to change. Here, we assess existing coastal monitoring networks and regional models, existing challenges in these efforts, and recommend a path towards development of global models that more robustly reflect the coastal interface.

The benefits of lower ozone due to air pollution emission reductions (2002-2011) in the Eastern United States during extreme heat.

Using the Community Multiscale Air Quality (CMAQ) model and the Benefits Mapping and Analysis Program - Community Edition (BenMAP-CE) tool, we estimate the benefits of anthropogenic emission reductions between 2002 and 2011 in the Eastern United States (US) with respect to surface ozone concentrations and ozone-related health and economic impacts, during a month of extreme heat, July 2011. Based on CMAQ simulations using emissions appropriate for 2002 and 2011, we estimate that emission reductions since 2002 likely prevented 10- 15 ozone exceedance days (using the 2011 maximum 8-hr average ozone standard of 75 ppbv) throughout the Ohio River Valley and 5- 10 ozone exceedance days throughout the Washington, DC - Baltimore, MD metropolitan area during this extremely hot month. CMAQ results were fed into the BenMAP-CE tool to determine the health and health-related economic benefits of anthropogenic emission reductions between 2002 and 2011. We estimate that the concomitant health benefits from the ozone reductions were significant for this anomalous month: 160-800 mortalities (95% confidence interval (CI): 70-1,010) were avoided in July 2011 in the Eastern U.S, saving an estimated $1.3-$6.6 billion (CI: $174 million-$15.5 billion). Additionally, we estimate that emission reductions resulted in 950 (CI: 90-2,350) less hospital admissions from respiratory symptoms, 370 (CI: 180-580) less hospital admissions for pneumonia, 570 (CI: 0-1650) less Emergency Room (ER) visits from asthma symptoms, 922,020 (CI: 469,960-1,370,050) less minor restricted activity days (MRADs), and 430,240 (CI: -280,350-963,190) less symptoms of asthma exacerbation during July 2011.Implications: We estimate the benefits of air pollution emission reductions on surface ozone concentrations and ozone-related impacts on human health and the economy between 2002 and 2011 during an extremely hot month, July 2011, in the eastern United States (US) using the CMAQ and BenMAP-CE models. Results suggest that, during July 2011, emission reductions prevented 10-15 ozone exceedance days in the Ohio River Valley and 5-10 ozone exceedance days in the Mid Atlantic; saved 160-800 lives in the Eastern US, saving $1.3 - $6.5 billion; and resulted in 950 less hospital admissions for respiratory symptoms, 370 less hospital admissions for pneumonia, 570 less Emergency Room visits for asthma symptoms, 922,020 less minor restricted activity days, and 430,240 less symptoms of asthma exacerbation.

Comparison of Near-surface NO2 Pollution with Pandora Total Column NO2 during the Korea-United States Ocean Color (KORUS OC) Campaign.

Near-surface air quality (AQ) observations over coastal waters are scarce, a situation that limits our capacity to monitor pollution events at land-water interfaces. Satellite measurements of total column (TC) nitrogen dioxide (NO2) observations are a useful proxy for combustion sources but the once daily snapshots available from most sensors are insufficient for tracking the diurnal evolution and transport of pollution. Ground-based remote sensors like the Pandora Spectrometer Instrument (PSI) that have been developed to verify space-based total column NO2 and other trace gases are being tested for routine use as certified AQ monitors. The KORUS-OC (Korea-United States Ocean Color) cruise aboard the R/V Onnuri in May-June 2016 represented an opportunity to study AQ near the South Korean coast, a region affected by both local/regional and long-distance pollution sources. Using PSI data in direct-sun mode and in situ sensors for shipboard ozone, CO and NO2, we explore, for the first time, relationships between TC NO2 and surface AQ in this coastal region. Three case studies illustrate the value of the PSI as well as complexities in the surface-column NO2 relationship caused by varying meteorological conditions. Case Study 1 (25-26 May 2016) exhibited a high correlation of surface NO2 to TC NO2 measured by both PSI and Aura's Ozone Monitoring Instrument (OMI) but two other cases displayed poor relationships between in situ and TC NO2 due to decoupling of pollution layers from the surface. With suitable interpretation the PSI TC NO2 measurement demonstrates good potential for working with upcoming geostationary satellites to advance diurnal tracking of pollution.

The Ozone Water-Land Environmental Transition Study (OWLETS): An Innovative Strategy for Understanding Chesapeake Bay Pollution Events.

Coastal regions have historically represented a significant challenge for air quality investigations due to water-land boundary transition characteristics and a paucity of measurements available over water. Prior studies have identified the formation of high levels of ozone over water bodies, such as the Chesapeake Bay, that can potentially recirculate back over land to significantly impact populated areas. Earth-observing satellites and forecast models face challenges in capturing the coastal transition zone where small-scale meteorological dynamics are complex and large changes in pollutants can occur on very short spatial and temporal scales. An observation strategy is presented to synchronously measure pollutants 'over-land' and 'over-water' to provide a more complete picture of chemical gradients across coastal boundaries for both the needs of state and local environmental management and new remote sensing platforms. Intensive vertical profile information from ozone lidar systems and ozonesondes, obtained at two main sites, one over land and the other over water, are complemented by remote sensing and in-situ observations of air quality from ground-based, airborne (both personned and unpersonned), and shipborne platforms. These observations, coupled with reliable chemical transport simulations, such as the NOAA National Air Quality Forecast Capability (NAQFC), are expected to lead to a more fully characterized and complete land-water interaction observing system that can be used to assess future geostationary air quality instruments, such as the NASA Tropospheric Emissions: Monitoring of Pollution (TEMPO) as well as current low earth orbiting satellites, such as the European Space Agency's Sentinel 5-Precursor (S5-P) with its Tropospheric Monitoring Instrument (TROPOMI).

An overview of approaches and challenges for retrieving marine inherent optical properties from ocean color remote sensing.

Ocean color measured from satellites provides daily global, synoptic views of spectral waterleaving reflectances that can be used to generate estimates of marine inherent optical properties (IOPs). These reflectances, namely the ratio of spectral upwelled radiances to spectral downwelled irradiances, describe the light exiting a water mass that defines its color. IOPs are the spectral absorption and scattering characteristics of ocean water and its dissolved and particulate constituents. Because of their dependence on the concentration and composition of marine constituents, IOPs can be used to describe the contents of the upper ocean mixed layer. This information is critical to further our scientific understanding of biogeochemical oceanic processes, such as organic carbon production and export, phytoplankton dynamics, and responses to climatic disturbances. Given their importance, the international ocean color community has invested significant effort in improving the quality of satellite-derived IOP products, both regionally and globally. Recognizing the current influx of data products into the community and the need to improve current algorithms in anticipation of new satellite instruments (e.g., the global, hyperspectral spectroradiometer of the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission), we present a synopsis of the current state of the art in the retrieval of these core optical properties. Contemporary approaches for obtaining IOPs from satellite ocean color are reviewed and, for clarity, separated based their inversion methodology or the type of IOPs sought. Summaries of known uncertainties associated with each approach are provided, as well as common performance metrics used to evaluate them. We discuss current knowledge gaps and make recommendations for future investment for upcoming missions whose instrument characteristics diverge sufficiently from heritage and existing sensors to warrant reassessing current approaches.

Potential Dissociative Glucocorticoid Receptor Activity for Protopanaxadiol and Protopanaxatriol.

Glucocorticoids are steroid hormones that regulate inflammation, growth, metabolism, and apoptosis via their cognate receptor, the glucocorticoid receptor (GR). GR, acting mainly as a transcription factor, activates or represses the expression of a large number of target genes, among them, many genes of anti-inflammatory and pro-inflammatory molecules, respectively. Transrepression activity of glucocorticoids also accounts for their anti-inflammatory activity, rendering them the most widely prescribed drug in medicine. However, chronic and high-dose use of glucocorticoids is accompanied with many undesirable side effects, attributed predominantly to GR transactivation activity. Thus, there is a high need for selective GR agonist, capable of dissociating transrepression from transactivation activity. Protopanaxadiol and protopanaxatriol are triterpenoids that share structural and functional similarities with glucocorticoids. The molecular mechanism of their actions is unclear. In this study applying induced-fit docking analysis, luciferase assay, immunofluorescence, and Western blot analysis, we showed that protopanaxadiol and more effectively protopanaxatriol are capable of binding to GR to activate its nuclear translocation, and to suppress the nuclear factor-kappa beta activity in GR-positive HeLa and HEK293 cells, but not in GR-low level COS-7 cells. Interestingly, no transactivation activity was observed, whereas suppression of the dexamethasone-induced transactivation of GR and induction of apoptosis in HeLa and HepG2 cells were observed. Thus, our results indicate that protopanaxadiol and protopanaxatriol could be considered as potent and selective GR agonist.

Satellite sensor requirements for monitoring essential biodiversity variables of coastal ecosystems.

The biodiversity and high productivity of coastal terrestrial and aquatic habitats are the foundation for important benefits to human societies around the world. These globally distributed habitats need frequent and broad systematic assessments, but field surveys only cover a small fraction of these areas. Satellite-based sensors can repeatedly record the visible and near-infrared reflectance spectra that contain the absorption, scattering, and fluorescence signatures of functional phytoplankton groups, colored dissolved matter, and particulate matter near the surface ocean, and of biologically structured habitats (floating and emergent vegetation, benthic habitats like coral, seagrass, and algae). These measures can be incorporated into Essential Biodiversity Variables (EBVs), including the distribution, abundance, and traits of groups of species populations, and used to evaluate habitat fragmentation. However, current and planned satellites are not designed to observe the EBVs that change rapidly with extreme tides, salinity, temperatures, storms, pollution, or physical habitat destruction over scales relevant to human activity. Making these observations requires a new generation of satellite sensors able to sample with these combined characteristics: (1) spatial resolution on the order of 30 to 100-m pixels or smaller; (2) spectral resolution on the order of 5 nm in the visible and 10 nm in the short-wave infrared spectrum (or at least two or more bands at 1,030, 1,240, 1,630, 2,125, and/or 2,260 nm) for atmospheric correction and aquatic and vegetation assessments; (3) radiometric quality with signal to noise ratios (SNR) above 800 (relative to signal levels typical of the open ocean), 14-bit digitization, absolute radiometric calibration <2%, relative calibration of 0.2%, polarization sensitivity <1%, high radiometric stability and linearity, and operations designed to minimize sunglint; and (4) temporal resolution of hours to days. We refer to these combined specifications as H4 imaging. Enabling H4 imaging is vital for the conservation and management of global biodiversity and ecosystem services, including food provisioning and water security. An agile satellite in a 3-d repeat low-Earth orbit could sample 30-km swath images of several hundred coastal habitats daily. Nine H4 satellites would provide weekly coverage of global coastal zones. Such satellite constellations are now feasible and are used in various applications.

Plankton Aerosol, Cloud, Ocean Ecosystem Mission: atmosphere measurements for air quality applications.

We present the instrumentation and products of the NASA Plankton Aerosol, Cloud, ocean Ecosystem (PACE) mission relevant to air quality management. Since PACE will launch in the 2022 to 2023 timeframe, this paper discusses several activities in anticipation of a robust air quality applications program using PACE products. Products from the PACE ocean color imager and two multiangle polarimeters will be used synergistically to retrieve properties relevant to air quality applications. These instruments provide high spectral and spatial resolution measurements used to derive key properties of aerosols and clouds including effective particle radii, particle shapes, aerosol and cloud optical depths, refractive indices and single scattering albedos all of which are critical for characterizing airmasses for managing air quality, hazardous episodes of wildfire and volcanic emissions, and long range transport of pollution. Because of the number of products with potential societal benefits, the PACE mission is highly pertinent to NASA's Applied Sciences Program's efforts to promote, discover, and demonstrate innovative, practical, and sustainable uses of the Earth observations. We discuss plans to support these efforts by establishing a prelaunch early adopter program and outline communication strategies to engage the air quality user community.