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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 (NOx) 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 NOx emissions by approx. 30 % on top of long-term trends, in agreement with sector-specific changes in NOx 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 NO2 pollution in the city, with low-speed (

The continually changing atmospheric conditions over densely populated coastal urban regions make it challenging to produce models that accurately capture the complex interactions of anthropogenic and environmental emissions, chemical reactions, and unique meteorological processes, such as sea- and land-breeze circulations. The purpose of this study is to determine and identify the influence of synoptic scale wind patterns on the development of local scale sea breeze circulations and air quality over the New York City (NYC) metropolitan area. This study utilizes column integrated nitrogen dioxide observations made during the Long Island Sound Tropospheric Ozone Study (LISTOS) field campaign, ground level ozone observations, the HRRR numerical weather prediction model, and trajectory model simulations using the NOAA HYSPLIT model. A cluster analysis within the HYSPLIT modeling system was performed to determine that there were six unique synoptic scale transport pathways for NYC. Stagnant conditions or weak transport out of the northwest resulted in the worst air quality for NYC. Weak synoptic scale forcings associated with these conditions allowed for local scale sea breeze circulations to develop resulting in air pollution to recirculate and mix with freshly emitted pollutants.

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 (NO(2)) dynamics and the role of meteorology in shaping relative contributions from different emission sectors to NO(2) 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 NO(2) 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 NO(2) 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 NO(2) cycle. Extending our analysis to more than a year after the initial lockdown captured a gradual recovery in NO(2) across the NY/NJ/CT tri-state area in summer and fall 2020, as social restrictions eased, followed by a second decline in NO(2) coincident with the second wave of the pandemic and resurgence of lockdown measures in winter 2021. Meteorology was not found to have a strong NO(2) biassing effect in New York City after the first pandemic wave. Winds, however, were favorable for low NO(2) conditions in Manhattan during the second wave of the pandemic, resulting in larger column NO(2) 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 NO(2) 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 NO(2) measurements in assessing the effects of rapid meteorological changes on air quality conditions and the effectiveness of sector-specific NO(x) emission control strategies.

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.

Tidal wetlands are a significant source of dissolved organic matter (DOM) to coastal ecosystems, which impacts nutrient cycling, light exposure, carbon dynamics, phytoplankton activity, microbial growth, and ecosystem productivity. There is a wide variety of research on the properties and sources of DOM; however, little is known about the characteristics and degradation of DOM specifically sourced from tidal wetland plants. By conducting microbial and combined UV exposure and microbial incubation experiments of leachates from fresh and senescent plants in Chesapeake Bay wetlands, it was demonstrated that senescent material leached more dissolved organic carbon (DOC) than fresh material (77.9 ± 54.3 vs 21.6 ± 11.8 mg DOC L−1, respectively). Degradation followed an exponential decay pattern, and the senescent material averaged 50.5 ± 9.45% biodegradable DOC (%BDOC), or the loss of DOC due to microbial degradation. In comparison, the fresh material averaged a greater %BDOC (72.6 ± 19.2%). Percent remaining of absorbance (83.3 ± 26.7% for fresh, 90.1 ± 10.8% for senescent) was greater than percent remaining DOC, indicating that colored DOM is less bioavailable than non-colored material. Concentrations of DOC leached, %BDOC, and SUVA280 varied between species, indicating that the species composition of the marsh likely impacts the quantity and quality of exported DOC. Comparing the UV + microbial to the microbial only incubations did not reveal any clear effects on %BDOC but UV exposure enhanced loss of absorbance during subsequent dark incubation. These results demonstrate the impacts of senescence on the quality and concentration of DOM leached from tidal wetland plants, and that microbes combined with UV impact the degradation of this DOM differently from microbes alone.

The role of tidal wetlands as hotspots for carbon and nutrient exchange with adjacent waters has been well documented, but large uncertainties remain regarding the physical and biogeochemical controls on these fluxes, which have significant implications for coastal carbon cycling and budgets. This study elucidates the variability in lateral wetland dissolved organic (DOC) fluxes tidally, seasonally, and during extreme weather events for a brackish wetland within a sub-estuary of the northwestern Chesapeake Bay, USA. Continuous fluxes from the wetland-draining tidal creek were calculated based on DOC concentrations ([DOC]) estimated using optical and physicochemical properties measured in situ with concurrent water flow data. Mean export was found to be 8.59 (±1.20) kg C (n=1,128) tidal cycle−1 and annual flux from the wetland to sub-estuary was 200.66 (±28.09) gCm−2yr−1. Peaks in DOC flux were associated with Hurricane Joaquin in 2015, where just two tidal cycles accounted for ∼5% of annual export. Analysis of tidal creek water quality measurements reveal seasonal and tidal dependencies. Highest [DOC] and largest low versus high tide differences were observed in summer, corresponding to more fresh plant biomass and its mobilization, consistent with results from Fourier transform ion cyclotron resonance mass spectrometry. Despite summer highs in tidal creek [DOC], monthly DOC fluxes were greatest in early fall due to higher water flows. The annual flux presented here is higher than fluxes previously reported for this system, highlighting the importance of continuous measurements for monitoring carbon export under a wide range of environmental conditions.

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.

Retrievals of total column NO2 (TCNO2) are compared for 14 sites from the Ozone Measuring Instrument (OMI using OMNO2-NASA v3.1) on the AURA satellite and from multiple ground-based PANDORA spectrometer instruments making direct-sun measurements. While OMI accurately provides the daily global distribution of retrieved TCNO2, OMI almost always underestimates the local amount of TCNO2 by 50 % to 100 % in polluted areas, while occasionally the daily OMI value exceeds that measured by PANDORA at very clean sites. Compared to local ground-based or aircraft measurements, OMI cannot resolve spatially variable TCNO2 pollution within a city or urban areas, which makes it less suitable for air quality assessments related to human health. In addition to systematic underestimates in polluted areas, OMI's selected 13:30 Equator crossing time polar orbit causes it to miss the frequently much higher values of TCNO2 that occur before or after the OMI overpass time. Six discussed Northern Hemisphere PANDORA sites have multi-year data records (Busan, Seoul, Washington DC, Waterflow, New Mexico, Boulder, Colorado, and Mauna Loa), and one site in the Southern Hemisphere (Buenos Aires, Argentina). The first four of these sites and Buenos Aires frequently have high TCNO2 (TCNO2 > 0.5 DU). Eight additional sites have shorter-term data records in the US and South Korea. One of these is a 1-year data record from a highly polluted site at City College in New York City with pollution levels comparable to Seoul, South Korea. OMI-estimated air mass factor, surface reflectivity, and the OMI 24 km × 13 km FOV (field of view) are three factors that can cause OMI to underestimate TCNO2. Because of the local inhomogeneity of NOx emissions, the large OMI FOV is the most likely factor for consistent underestimates when comparing OMI TCNO2 to retrievals from the small PANDORA effective FOV (measured in m2) calculated from the solar diameter of 0.5∘.

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.

Coastal regions have historically represented a significant challenge for air quality investigations because of 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 National Oceanic and Atmospheric Administration (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 National Aeronautics and Space Administration (NASA) Tropospheric Emissions: Monitoring of Pollution (TEMPO), and current low-Earth-orbiting satellites, such as the European Space Agency’s Sentinel-5 Precursor (S5-P) with its Tropospheric Monitoring Instrument (TROPOMI).

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 (NO(2)) 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 NO(2) 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 NO(2), we explore, for the first time, relationships between TC NO(2) and surface AQ in this coastal region. Three case studies illustrate the value of the PSI as well as complexities in the surface-column NO(2) relationship caused by varying meteorological conditions. Case Study 1 (25-26 May 2016) exhibited a high correlation of surface NO(2) to TC NO(2) measured by both PSI and Aura’s Ozone Monitoring Instrument (OMI) but two other cases displayed poor relationships between in situ and TC NO(2) due to decoupling of pollution layers from the surface. With suitable interpretation the PSI TC NO(2) measurement demonstrates good potential for working with upcoming geostationary satellites to advance diurnal tracking of pollution.

Carbon cycling in the coastal zone affects global carbon budgets and is critical for understanding the urgent issues of hypoxia, acidification, and tidal wetland loss. However, there are no regional carbon budgets spanning the three main ecosystems in coastal waters: tidal wetlands, estuaries, and shelf waters. Here, we construct such a budget for Eastern North America using historical data, empirical models, remote-sensing algorithms, and process-based models. Considering the net fluxes of total carbon at the domain boundaries, 59 ± 12% (± 2 standard errors) of the carbon entering is from rivers and 41 ± 12% is from the atmosphere, while 80 ± 9% of the carbon leaving is exported to the open ocean and 20 ± 9% is buried. Net lateral carbon transfers between the three main ecosystem types are comparable to fluxes at the domain boundaries. Each ecosystem type contributes substantially to exchange with the atmosphere, with CO2 uptake split evenly between tidal wetlands and shelf waters, and estuarine CO2 outgassing offsetting half of the uptake. Similarly, burial is about equal in tidal wetlands and shelf waters, while estuaries play a smaller but still substantial role. The importance of tidal wetlands and estuaries in the overall budget is remarkable given that they respectively make up only 2.4 and 8.9% of the study domain area. This study shows that coastal carbon budgets should explicitly include tidal wetlands, estuaries, shelf waters and the linkages between them; ignoring any of them may produce a biased picture of coastal carbon cycling.

Observations taken over the last few decades indicate that dramatic changes are occurring in the ArcticBoreal Zone (ABZ), which are having significant impacts on ABZ inhabitants, infrastructure, flora and fauna, and economies. While suitable for detecting overall change, the current capability is inadequate for systematic monitoring and for improving processbased and largescale understanding of the integrated components of the ABZ, which includes the cryosphere, biosphere, hydrosphere, and atmosphere. Such knowledge will lead to improvements in Earth system models, enabling more accurate prediction of future changes and development of informed adaptation and mitigation strategies. In Duncan et al. (2020), we review the strengths and limitations of current spacebased observational capabilities for several important ABZ components and make recommendations for improving upon these current capabilities. We recommend an interdisciplinary and stepwise approach to develop a comprehensive ABZ Observing Network (ABZON), beginning with an initial focus on observing networks designed to gain processbased understanding for individual ABZ components and systems that can then serve as the building blocks for a comprehensive ABZON.

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.

Estuarine and coastal wetlands are among the most productive, ecologically valuable, and economically important ecosystems on Earth. Through tidal inundation and lateral export, estuarine marshes exert a strong influence on the amount and quality of carbon and nutrients exchanged between the land and the ocean. Yet, current understanding of the role of these “blue carbon” ecosystems on estuarine optics, biogeochemistry, and ecology is largely based on limited field observations at point locations, due to the coarse resolution of existing and heritage satellite ocean color sensors. Here, for the first time, we merged high resolution data from the constellation of Landsat-8/Operational Land Imager (OLI) and Sentinel-2A/B MultiSpectral Instruments (MSI) to examine dissolved organic carbon (DOC) dynamics in a tidally influenced marsh–estuarine system. Often referred to as the “Everglades of the North”, the Blackwater National Wildlife Refuge is the largest marsh system in the Chesapeake Bay and one of the most ecologically important areas in the United States. A multiple linear regression approach linking DOC to the spectral shape of water remote sensing reflectance was used to capture marsh DOC export and examine spatial features and temporal changes in DOC over a broad range of conditions (DOC in the range of 2.32–19.9 mg/L), across multiple years, different seasons, and tidal regimes, with a relative error (mean average percent difference) of 23%. Data consistency between satellite sensors was evaluated, followed by the generation of a long term, multi-sensor DOC data record that provided more frequent observations. Combining data from the three satellites revealed the strong impact of marsh outwelling at the larger ecosystem scale, its seasonal variability, and the importance of other environmental factors, including wind conditions, river discharge, and extreme weather events, in shaping DOC dynamics along complex, tidally influenced terrestrial–aquatic interfaces.

Tidal wetlands are critically important ecosystems that provide ecosystem services including carbon sequestration, storm surge mitigation, water filtration, and wildlife habitat provision while supporting high levels of biodiversity. Despite their importance, monitoring these systems over large scales remains challenging due to difficulties in obtaining extensive up-to-date ground surveys and the need for high spatial and temporal resolution satellite imagery for effective space-borne monitoring. In this study, we developed methodologies to advance the monitoring of tidal marshes and adjacent deepwaters in the Mid-Atlantic and Gulf Coast United States. We combined Sentinel-1 SAR and Landsat 8 optical imagery to classify marshes and open water in both regions, with user’s and producer’s accuracies exceeding 89%. This methodology enables the assessment of marsh loss through conversion to open water at an annual resolution. We used time-series Sentinel-1 imagery to classify persistent and non-persistent marsh vegetation with greater than 93% accuracy. Non-persistent marsh vegetation serves as an indicator of salinity regimes in tidal wetlands. Additionally, we mapped two invasive species: wetlands invasive Phragmites australis (common reed) with greater than 80% accuracy and deepwater invasive Trapa natans (water chestnut) with greater than 96% accuracy. These results have important implications for improved monitoring and management of coastal wetlands ecosystems.

The 2017–2027 National Academies' Decadal Survey, Thriving on Our Changing Planet, recommended Surface Biology and Geology (SBG) as a “Designated Targeted Observable” (DO). The SBG DO is based on the need for capabilities to acquire global, high spatial resolution, visible to shortwave infrared (VSWIR; 380–2500 nm; ~30 m pixel resolution) hyperspectral (imaging spectroscopy) and multispectral midwave and thermal infrared (MWIR: 3–5 μm; TIR: 8–12 μm; ~60 m pixel resolution) measurements with sub-monthly temporal revisits over terrestrial, freshwater, and coastal marine habitats. To address the various mission design needs, an SBG Algorithms Working Group of multidisciplinary researchers has been formed to review and evaluate the algorithms applicable to the SBG DO across a wide range of Earth science disciplines, including terrestrial and aquatic ecology, atmospheric science, geology, and hydrology. Here, we summarize current state-of-the-practice VSWIR and TIR algorithms that use airborne or orbital spectral imaging observations to address the SBG DO priorities identified by the Decadal Survey: (i) terrestrial vegetation physiology, functional traits, and health; (ii) inland and coastal aquatic ecosystems physiology, functional traits, and health; (iii) snow and ice accumulation, melting, and albedo; (iv) active surface composition (eruptions, landslides, evolving landscapes, hazard risks); (v) effects of changing land use on surface energy, water, momentum, and carbon fluxes; and (vi) managing agriculture, natural habitats, water use/quality, and urban development. We review existing algorithms in the following categories: snow/ice, aquatic environments, geology, and terrestrial vegetation, and summarize the community-state-of-practice in each category. This effort synthesizes the findings of more than 130 scientists.

Accurately capturing the evolution of episodic stratosphere-to-troposphere transport is critical due to the potential impacts on both climate and air quality. Until now, investigating associated spatiotemporal gradients in total column ozone (TCO) has primarily been the task of observations from polar-orbiting satellites as well as high-resolution models. We explore how a network of five ground-based Pandora spectrometer systems can be utilized in a similar fashion. The passage of a strong mid-latitude cyclone in March 2018 and its associated stratospheric intrusion is used as a case demonstrating the ability of networked Pandora observations to contextualize these regions of transport across space and time. Results show that the high temporal resolution of Pandora observations and the networked approach were able to resolve increases in TCO associated with stratosphere-to-troposphere transport and to capture the spatial context of the chosen episode. The use of networked Pandora observations shows promise for additional transport studies and for supporting future geostationary atmospheric composition satellite missions and modeling efforts.

Ocean color measured from satellites provides daily global, synoptic views of spectral water-leaving 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.

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.

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.

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 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.