Poster Session Index

Coastal regions in the Northeastern United States face escalating environmental risks; including sea level rise, intensifying storms, and ecosystem degradation, while supporting a $100+ billion blue economy rooted in fisheries, offshore wind, maritime trade, and coastal tourism. Innovative financial mechanisms are urgently needed to fund climate-resilient, ocean-positive development. Blue bonds, debt instruments that channel capital toward marine conservation and sustainable ocean economies, offer a promising but underutilized tool in developed economies.

This study conducts a systematic comparative analysis of five global blue bond case studies (Seychelles, Nordic Investment Bank, Bank of China, Indonesia, and Ecuador) across ten criteria, including financial structure, governance, environmental impact, and scalability, to identify transferable lessons for the Northeast U.S. Findings reveal high-potential applications in three areas: (1) financing offshore wind infrastructure and marine spatial planning, (2) deploying nature-based solutions (e.g., oyster reefs, wetland restoration) for coastal resilience, and (3) supporting transitions to sustainable fisheries and aquaculture.

Critical success factors include standardized impact metrics (e.g., Coastal Protection Index, Sustainable Fisheries Yield), multistate coordination, and blended finance models that de-risk investments. Key barriers such as market immaturity, regulatory fragmentation, and risks of “blue washing” are identified. The study concludes with actionable recommendations resilience-linked bond structures that align with NOAA and state climate adaptation plans.

New Jersey (NJ) administrative code requires reporting incidents or injuries to NJ Safe Schools Program (NJSS). Students or teachers sustained injuries from participating in career and technical education programs, on- or off-campus, and required treatment by a licensed medical doctor.
In 2012 into 2013, NJSS transitioned physical reporting forms to an online platform, fully implemented by 2014. For 2012-2024, 495 reported injuries analyzed. Ambient/outdoor environmental data were obtained from NJ public online archives. We analyzed 166 of 495 injuries with environmental data: 28 outdoors, 35 semi-enclosed, 103 possibly semi-enclosed (construction/architecture, welding). Other injuries (329) were excluded: indoors (162), in-transit/travel (6); location undetermined (161).
Most reported injuries involved hands, fingers, wrists; type of reported injury as skin injuries, which included abrasions, cuts/lacerations and scratches; and were in Architecture and Construction, Agriculture, Food and Natural Resources, and Transportation, Distribution and Logistics Career Clusters. Potential associations with higher outdoor air temperature on the day of injury (average, maximum) and average outdoor relative humidity on day of injury were noted.
Understanding environmental factors contributing to reported injuries among susceptible, vulnerable young workers can inform future policies to reduce identified physical exposures or weather-related risk factors and develop new or enhance existing workplace safety trainings.

Cross-sectional surveys of psychological distress were conducted among 12 training cohorts of NJ secondary school teachers for winter of 2021-22 school year (SY) – 2023-24 SY. We assessed symptoms associated with general mental health with Kessler-6 tool (K6+). Utilizing data from NJDEP/U.S. EPA Air Quality Monitoring Stations (AQMS), an estimated exposures to ambient/outdoor air quality database was constructed for initial environmental epidemiological study with ecological design. Cohorts were broken down by school district (SD) and paired with AQMS based on approximate geographic proximity for each SD’s school utilizing NJDEP’s NJ-GeoWeb after retrieving school addresses from NJ School Performance Reports database. Once addresses were reported and associated with 2+ AQMS, associated reviewed daily criteria pollutant data were retrieved from 2021-2023 for particulate matter (PM, PM10 and PM2.5) and ozone; 2024 data currently preliminary. Data downloaded were refined to include those associated with 12 virtual training date-ranges related to specified teacher cohorts, including two live session trainings per date-range consisting of 30 calendar days prior to its date to relate to K6+ questions. Data averaged for relevant stations.
We present 2021-24 K6+ and environmental data analyses to spark discussion and inform future collaborative work in mental health and effects of environmental factors.

Coral health decline, due to stress or disease, is a serious and prevalent issue, with most coral reefs globally affected. Rising ocean temperatures and acidification causes significant metabolic stress to corals, increasing their mortality and weakening the health of survivors, elevating the rate of total ecosystem collapse. No tools currently exist for rapid, early detection of stress before visual decline and death occurs, preventing proactive management and conservation practices by local communities. Thus, our project focuses on the development of point-of-care tools for the diagnosis of coral health status. One goal is to utilize nucleic acid-based detection of stress or disease in corals, through loop-mediated isothermal amplification (LAMP). This approach requires less technical equipment and reagents than traditional polymerase chain reaction (PCR) amplification. The low reagent requirement increases the suitability for use in low resource areas. These regions are often devastated by the loss in food and employment opportunities due to climate change but are least able to mitigate its impacts. We have shown that the LAMP-based approach is sensitive and specific for a model template sequence in a laboratory setting, demonstrating its potential for field applications with coral specific markers.

Ozone and hydroxyl radicals are crucial for atmospheric chemistry, as they oxidize organic molecules like carbon monoxide and methane – which have radiative effects on climate. They react with volatile organic compounds (VOCs), affecting the greenhouse and albedo effect. Thus, understanding ozone and hydroxyl radicals is vital for studying climate change.

A source of hydroxyl radicals is peroxyl radicals, which are difficult to measure due to factors such as short lifespans and inconsistencies. Peroxyl radical research is limited to alkyl radicals, which do not reflect atmospheric environments.

This study focuses on functionalized organic iodide precursor 3-iodo-1-propanol and its reactivity under different atmospheric conditions. The organic iodide precursor was photolyzed in a flow reactor using 254 nm, 300 nm and 350 nm light. The resulting products were monitored and quantified using iodide adduct chemical ionization mass spectrometry (I–CIMS). The primary isomerization product formed upon photolysis was identified as 4-hydroperoxybutanal (m/Q = 217), the major bimolecular photolysis products 3-hydroxypropanal (m/Q = 201), 1,3-propanediol (m/Q = 203), 3-hydroperoxy-1-propanol (m/Q = 219), and the dimer bis(3-hydroxypropyl) peroxide (m/Q = 277). The distribution of photolysis products was found to vary significantly with the three wavelengths and the residence time within the flow reactor system.

The Multi-Dimensional Strategic Curriculum Studies (MDSCS) framework, applied within the Our Planet’s Wonder Project (PWP_MDSCS), integrates science, art, and technology and its innovations to foster environmental awareness and sustainable learning from early childhood through lifelong education. This project represents a proactive and flexible curriculum, in which the aim is the acquisition of meta-cognitive abilities in life as a strategy to facilitate learners’ participation in the cycle of wisdom management, through transformative interaction among bases, principles, factors, and adaptable elements in both theoretical and practical dimensions of curriculum studies. The framework connects interdisciplinary themes through inquiry, creativity, and reflection, emphasizing process-based evaluation of learners’ skills, attitudes, and values toward sustainability. To date, 22 theses and more than 100 articles and workshops have been developed based on this approach, demonstrating its adaptability across cultural and educational contexts. It highlights that fostering transformative relationships with the environment requires flexible learning spaces that integrate lifelong, cross-curricular themes through the living and non-living components of our planet, using artistic and technological discovery-based methods. This holistic vision positions environmental education as a foundation for sustainable thinking, scientific reasoning, creative problem-solving, and human–nature harmony. The author welcomes opportunities for collaboration and shared research.

The Delaware River Basin Commission (DRBC) is developing a Water Resources Resilience Plan that adapts the traditional climate resilience plan framework to apply to Basin-wide water resources. The 13,500-mi2 Delaware River Basin provides drinking water for 14.2 million people in New York, New Jersey, Pennsylvania, and Delaware. As the federal-interstate agency charged with managing, protecting, and improving shared water resources in the Basin, the DRBC is well poised to convene partners to advance the resilience of these resources.

The DRBC began collecting input to inform the plan’s scope in December 2024, hosting an online comment card and 12 listening sessions. So far 150 Basin stakeholders have shared their thoughts. In subsequent phases, a vulnerability assessment will explore how seven broad water resource assets—streamflow, groundwater, reservoir storage, water quality, salinity gradient, aquatic life, and habitat—are most vulnerable to climate change-driven hazards, including flooding, drought, saltwater intrusion, and wildfire. A gap analysis will define a goal outcome for each asset, outline a pathway for achieving that outcome, and identify any gaps in knowledge, equity, or action that need to be addressed. Recommended actions that DRBC can take to improve climate resilience will be drawn from these gaps.

Developing fully recycled, low-carbon concrete provides a path toward sustainable construction and contributes to lowering the annual global CO₂ emissions produced by traditional concrete production. This research investigates the integration of concrete waste materials into wollastonite-based concrete formulations that harden through carbonation curing. Waste concrete was crushed and sieved into three particle size fractions before being incorporated into wollastonite-based concrete mixtures. These mixtures exhibited compressive strengths comparable to structural concrete. Formulations containing wollastonite, 3/8” aggregate, sand, and crushed concrete rubble achieved a baseline compressive strength of 10 ksi (68+ MPa) with peak values exceeding 12 ksi (80 MPa) for 3” × 6” cylinders after carbonation curing. In addition, concrete waste was used as a full replacement for sand and aggregate. A formulation containing only wollastonite and concrete waste exceeded 7 ksi (49 MPa) after carbonation curing. The incorporation of concrete rubble into these materials warrants further research and experimentation to optimize the use of recycled waste in carbonate concrete products.

Nitrogen Oxide (NOx) emission estimates from bottom-up inventories have considerable uncertainties. Space-based observations of NO2 columns offer information on surface NOx emissions through inverse modeling techniques such as the iterative finite difference mass balance (IFDMB) method. In this study, first, we evaluate the effective horizontal resolution for IFDMB method by conducting inversion experiments using the high-performance configuration of the GEOS‐Chem chemical transport model (GCHP). We simulate synthetic NO2 column density as observed by the Tropospheric Ozone Monitoring Instrument (TROPOMI) over eastern North America to test the ability of the IFDMB method to recover known NOx emissions as a function of resolution. Our synthetic tests with horizontal resolutions of 200 km, 100 km, and 55 km grids for June-August 2019 reveal that 100 km horizontal resolution simulations can recover the “true emissions” with a normalized mean error (NME) of 15.4% as compared to 200 km (NME = 16.4%) and 55 km (NME = 19.7%) grids after six iterations (no further change in tolerance). We further use this resolution-optimized mass balance approach (ROMBA) to retrieve surface NOx emissions using TROPOMI observed NO2 columns for June-August 2019. We use TROPOMI observed NO2 columns for June-August 2019 and GCHP simulated a priori at 100 km horizontal resolution to derive top-down NOx estimates. Our global a posteriori estimates for June-August 2019 land surface NOx emissions (42.1 Tg NO2) agrees closely with the CEDSv2 a priori (38.4), with the highest agreement over the eastern United States (10-15%). We observed significant regional differences with higher a posteriori NOx emission (30–60%) in the northern part of South America and Africa, southern Europe, western Canada and the United States, and the Middle-East. We observe lower a posteriori NOx emission (50-100%) over southern parts of South America, Africa, and India, and eastern parts of Europe and China.

To fabricate a polymer-ceramic material, a powder mixture of the two components is mixed in a Spex mill. Through a low-temperature solidification method, Gas-Reactive Hydrothermal Liquid Phase Densification (g-rHLPD), the composite strengthens and can sequester 0.38g of CO2 per gram of starting ceramic powder. The polymer is introduced into the ceramic matrix as a mechanism to induce toughness. The uniform distribution of polymer particles throughout the matrix is essential to inducing desirable and consistent mechanical properties. A methodology has been developed to statistically evaluate the accuracy of mixing within one batch in the Spex mill. 30 random samples from one batch were collected. Using a simultaneous thermal analysis (STA), the polymer fraction of these mixtures was burned off and quantified. The average mass loss for the set of thirty samples is found to be 5.92% ± 0.213 and is compared to 5.74%, the expected mass percent of polymer, through a t-test. For a significance level of 0.05, the resulting p-value is equal to 0.999, which indicates that there is no statistically significant difference between the average percent mass loss and the expected value. As a follow-up, 4 mixed batches will be evaluated for the batch-to-batch consistency of the mixtures.

Concrete, the most widely used construction material, imposes substantial environmental costs due to its high demand for natural resources, significant greenhouse gas emissions, and the generation of large volumes of concrete and demolition waste. A sustainable strategy to mitigate these impacts involves cleanly separating concrete’s constituent phases; cement hydrates, sand, and aggregates at the end of their life cycle for reuse in new formulations without compromising structural integrity. Conventional physical separation methods, such as electric pulse fragmentation, magnetic separation, thermal activation, and specialized crushing, encounter numerous energy, economic, and environmental challenges. This study investigates a novel mechanical process as an energy-efficient, low-cost method for selectively separating cement hydrates from aggregates in concrete rubble. It leverages the particle–particle collisions, promoting selective fracture based on intrinsic material property differences among concrete components. Preliminary results demonstrate that in less than ten minutes, the process produces smooth, clean aggregates concentrated in the coarser size fractions, while cement hydrate accumulate in the finer fractions. Although early trials showed some contamination of the cement hydrate, the results encourage that further process optimization could achieve efficient, selective separation and advance circularity in concrete recycling.

Electrocatalytic hydrogenation is an emerging sustainable alternative to traditional thermal hydrogenation, with potential application in biofuel upgrading, renewable energy storage with liquid organic hydrogen carriers, and fine chemical synthesis. Transition metal-hydride complexes provide a valuable platform for mechanistic investigations into the key electron and hydrogen transfer processes involved in the electrocatalytic hydrogenation reaction. A central focus lies in understanding how catalyst properties influence thermodynamic and kinetic hydricity, where the former represents the reaction free energy for heterolytic H– release (ΔGH–) and the latter governs the hydride transfer rate to a given hydride acceptor. Linear free energy relationships (LFERs), which correlate thermodynamic and kinetic parameters, can be employed to elucidate structure-activity relationships and guide further catalyst optimization. Our group has focused on [Cp*Ir(bpy)H][PF6], a known thermal hydrogenation and transfer hydrogenation catalyst and is also an active electrohydrogenation for reduction of carbonyl compounds. This complex has ΔGH− = 62 kcal/mol and pKa = 23.3 in MeCN. In this research, hydride transfer from a family of iridium-hydride complexes to four organic hydride acceptors N-methylacridinium, 10-Methyl-9-phenylacridinium, trityl, and 3,5-Bis(ethoxycarbonyl)-1,2,6-trimethylpyridinium that was confirmed by 1H-NMR spectroscopy, with reactions complete within 15 minutes, indicating thermodynamic favorability.

I analyze data on bird species in New Jersey that are at high risk of extinction due to climate change. The quantitative data come from the National Audubon Society, whose scientists compiled over 140 million bird observations to map the current distributions of 604 North American species. Complementing this, I will collect qualitative data through a participatory activity: participants will randomly select a high-risk bird species and mark on a map where in New Jersey they have seen it. This process encourages participants to reflect on how these birds appear in their daily lives, recall when and where they have encountered them, and imagine the impact of their absence from local environments.

Vertical motions (i.e., upwelling and downwelling) are crucial for the Southern Ocean’s role in global ocean circulation and climate, as they govern the transport of heat, carbon, and nutrients. However, a comprehensive analysis of their variability is still needed. This study investigates the spatial and temporal variability of vertical velocities in the Southern Ocean using the ECCOv4 ocean state estimate. At the surface, there is a large-scale pattern of upwelling south of ~55°S and downwelling to the north, consistent with conventional wind-driven patterns. In deeper layers, this pattern is less uniform, with topography emerging as a key driver. We also find significant temporal variability on interannual scales, with potential links to the Southern Annular Mode and the El Niño-Southern Oscillation (ENSO). We find that positive SAM phase is moderately correlated with enhanced upwelling south of ~60°S and increased downwelling to the north. A moderate negative correlation exists between the Niño 3.4 Index and vertical velocity across most of the Pacific sector south of 50°S, indicating that El Niño conditions tend to suppress upwelling in this region. These findings suggest that SAM and ENSO can exert opposing influences on vertical mass transport in the Southern Ocean. This research provides a clearer picture of the vertical motions and mechanisms controlling vertical exchange in this climatically vital region.

Resource booms ultimately reshape the structural composition of an economy. With sectors having varied relative economic and environmental contributions, these resource-induced structural changes also affect emissions pathways. We utilize a generalized synthetic control model and the KAYA identity to provide a harmonized methodology for assessing commercial oil production in tropical countries affects the structural composition, population, carbon intensity, energy intensities and total emissions trajectories. We extend the growing literature that combines treatment-effect modeling and emissions decomposition. We find evidence of the adverse effects of oil production on the agriculture and services sectors, alongside significant industrialization. Energy intensity also falls significantly below their counterfactual levels, but this sustainability improvement alongside and reductions in non-extractive sectors are insufficient to offset the higher emissions from economic expansion and increasing GHG intensity. Our findings support the mediating role of government policy and income distribution, and the potential for low-carbon development.

Scaling the Carbonation of Cementitious Materials Using Plastic Forming One of the major challenges in sequestering CO2 by carbonation with cementitious materials is effectively scaling the procedure to be attractive for large scale adoption. The research attempts to create an analytical way of inducing plasticity in the cementitious materials so that low cost production methods, such as extrusion, become possible. A sample workable system was developed by controlling particle interactions such as particle size and measuring the resulting properties. The resulting system was able to be hand formed and demonstrated shear thinning behavior under shear. Further investigation will focus on improving the cohesion of the resulting system and testing the methodology on other cementitious materials.

The Caribbean Through-Flow (CTF) is a critical conduit linking tropical and subtropical Atlantic waters, modulating the exchange of heat and freshwater between low and high latitudes. Using historical observations since 1960, we document pronounced changes in upper-ocean water mass properties within the CTF: subsurface warming of ~0.2 °C decade⁻¹, surface freshening of ~0.13 g kg⁻¹ decade⁻¹, and subsurface salinification of ~0.05 g kg⁻¹ decade⁻¹. In the upper 0–200 m, temperature and stability increases are nearly three and twenty times larger, respectively, than global averages, underscoring the region’s outsized sensitivity to climate forcing. These shifts alter stratification, water mass transformation, and downstream export to the North Atlantic Subtropical Gyre, with potential consequences for the Atlantic Meridional Overturning Circulation (AMOC) and Atlantic-wide heat and salt budgets. By identifying the CTF as both a bottleneck and amplifier of upper-ocean change, our results highlight its role in Atlantic connectivity and stress the need for sustained subsurface observations to constrain the pathways and variability of climatically important water masses.

Understanding the vertical structure of vegetation is essential for quantifying photosynthesis, transpiration, and carbon–water exchange. The Global Ecosystem Dynamics Investigation (GEDI) lidar provides detailed canopy vertical profiles but with limited spatial and temporal coverage, constraining its ability to monitor global structural dynamics. To overcome this limitation, we developed the GEDI-informed Two-Layer Canopy (GTLC) Plant Area Index (PAI) dataset by integrating GEDI canopy profiles with MODIS Nadir BRDF-Adjusted Reflectance and ancillary environmental variables using a random forest framework. The GTLC PAI provides monthly estimates of overstory (above 5m) and understory (below 5m) PAI at 0.005° (~500 m) resolution from 2001 to 2022. Validation against airborne lidar data and field-measured LAI demonstrates robust accuracy. The GTLC product reveals not only widespread terrestrial greening but also substantial vertical heterogeneity in forest structural changes across seasonal and annual timescales. By bridging footprint-scale lidar and global optical observations, the GTLC dataset enables large-scale monitoring of forest vertical structure and provides new opportunities to investigate ecosystem resilience, carbon dynamics, and vegetation–climate interactions.

Background: Healthcare systems are responsible for 8.5 percent of total greenhouse gas emissions in the United States, and this has increased six percent from 2010 to 2018. Of this, pharmaceuticals account for 18 percent. Anticoagulants are used to prevent and treat blood clots and are available in subcutaneous (sub-Q) or oral (PO) forms. Sub-Q and PO forms may have different impacts on climate health and formal life cycle assessment (LCA) can support the sustainable usage of medications. Objective: To quantify the difference in waste produced through sub-Q versus PO anticoagulant administration in the inpatient setting in preparation for an LCA.

Supraglacial streams on the Greenland ice sheet transport meltwater, accelerate surface melting, and route meltwater into the ice sheet’s subsurface, causing fluctuations in ice sheet velocity. However, fine-scale supraglacial stream detection has faced challenges because prior studies rely on coarse-resolution satellite images and manual detection techniques.  In this study, we use high-resolution drone imagery from a study site in the southwest Greenland ice sheet. Three years of imagery were analyzed (2017, 2023, and 2024), each representing a range of melting conditions. Manual classification of this imagery was used to train two different types of deep learning (DL) segmentation models to identify pixels corresponding to supraglacial streams. The first was a semantic segmentation model called U-Net, which classifies each pixel as stream or non-stream without distinguishing between separate stream objects. The second was an instance segmentation model called Mask R-CNN, which identifies and separates individual stream features. The trained DL models were subsequently tested on independent imagery from 2019. Model performance was evaluated using three different geostatistical methods: 1) intersection-over-union (IoU), which quantifies the spatial overlap of predicted and true stream areas, 2) precision and recall, which measure the accuracy and completeness of stream detection, 3) inference speed, which reflects how quickly each model processes the imagery. The U-Net model significantly outperformed the Mask R-CNN model, achieving an IoU of  0.83 on training imagery (precision = ~0.89, recall = ~0.75) compared to an IoU of ~0.52 for Mask R-CNN (precision = ~0.49, recall = ~0.41). When applied to the independent 2019 dataset, the trained U-Net model showed promising generalization (IoU of 0.77 for U-Net, and IoU of 0.47 for Mask R-CNN) beyond the training imagery by accurately classifying supraglacial streams and smaller water bodies in some cases. Separating these features would require additional model refinement. These findings demonstrate that DL models, particularly U-Net, offer a viable and accurate approach for detecting supraglacial streams from drone images.

This poster was inspired by my father’s 2025 Arctic expedition aboard ARAON, South Korea’s first icebreaking research vessel operated by the Korea Polar Research Institute (KOPRI). His photographs of melting glaciers and polar bears transformed the distant notion that “the Earth is melting” into a tangible reality. Over the past fifty years (1975–2025), the global sea level has risen by about 11–12 centimeters, reflecting profound environmental change. According to the National Snow and Ice Data Center (NSIDC), Arctic sea ice has been declining at an average rate of 13% per decade, with summer ice extent now less than half of what it was in the late 1970s. This drastic loss of sea ice has a direct impact on polar bears, whose hunting and migration depend on stable ice platforms. Research shows that declining ice cover has led to longer fasting periods, lower cub survival rates, and shrinking population ranges across the Arctic. By combining qualitative data—my father’s photographs and records—with quantitative data on temperature rise, sea ice loss, and glacier melt, this project explores how climate data can be felt rather than only understood. The work seeks to evoke empathy and awareness, transforming scientific information into a sensory and emotional experience.

Hudson County, New Jersey’s most densely populated and urbanized county, faces a growing flood threat as climate change intensifies. This study uses a multi-criteria evaluation approach to assess flood risk under historical and future climate scenarios (RCP 4.5 and RCP 8.5, 2077-2099). Five primary drivers were integrated using weighted overlay analysis: precipitation at a resolution of 4km, proximity to streams, slope, elevation, and land cover.

The results indicate that the likelihood of flooding will significantly escalate in all future scenarios. Historical conditions showed 81.34% of the county at moderate risk and 14.56% at high risk. Under RCP 4.5 scenario, high-risk areas expanded to 86.75% of the county, while virtually the whole county is classified at high risk and severe vulnerability under RCP 8.5. Transition analysis shows 71.76% of moderate-risk areas in historical scenario transist to high risk under RCP 4.5, while 81.30% shift to high risk under RCP 8.5.

These findings show the localized impact of climate change and the urgent need for adaptation strategies, infrastructure improvements, and enhanced flood mitigation planning within the county.

Approximately 85% of oyster reefs are now functionally extinct, posing a significant threat to coastal ecosystems. Oyster larvae rely on existing shells to settle and grow, but shell supplies from wild populations and recycling programs are insufficient for large-scale restoration efforts. To address this, concrete artificial reef structures are deployed to promote the restoration of oyster habitats. Although effective, the production of concrete accounts for 8% of global CO₂ emissions, raising sustainability concerns. This study investigates a low-carbon alternative for oyster habitat restoration. Larval settlement and juvenile oyster attachment strength were evaluated across several substrate types: a low-carbon-footprint cement with and without oyster shell, Oyster Castle®, and natural oyster shell. In a series of experiments, larval settlement and growth into spat and later-stage juvenile oysters were observed over a 2-month period. Oyster larvae showed a preference for the low-carbon cement in initial settlement. Two months post-settlement, differences in oyster densities across all tested materials were statistically insignificant – the low-carbon cement performed as well as oyster shell. Surface adhesion was weaker on the low-carbon cement. These findings suggest that the low-carbon cement offers a viable alternative for oyster reef restoration, striking a balance between ecological function and environmental sustainability.

The Mid-Atlantic region is set to be one of the first and largest contributors to the offshore wind energy goals of the United States. Yet, the same region is home to a diverse marine ecosystem comprising important marine species such as the critically endangered North Atlantic right whale (NARW). To support the responsible development and operation of the planned offshore wind farms, there is a need for high-resolution modeling of NARW presence. Towards this, we leverage highly localized observations from nine glider deployments in the Mid-Atlantic to propose a machine learning approach for modeling NARW presence conditioned on a diverse set of glider- and satellite-based oceanic, physical, and contextual information. We find that tree- and ensemble-based models achieve the highest levels of accuracy, while maintaining a sensible balance of missed and false alarms. Interpretation of the machine-learnt features reveals interesting insights on the relative value of well-resolved satellite surface measurements to well-resolved vertical information from glider sampling in explaining the species-habitat patterns of NARWs. Our work constitutes the first machine learning attempt to jointly leverage glider- and satellite-based information for modeling of NARWs.

Portland cement accounts for approximately 8% of anthropogenic CO2 emissions. Emission reduction can be achieved by replacing Portland cement with carbonate cements, which are binders that cure upon reaction with CO2 and sequester it within the concrete product. The large-scale use of carbonate cements is limited by non-uniform curing, a phenomenon in which concrete parts cure on their outer surfaces but retain a soft, powdery interior. An approach to solving this problem begins with reviewing physical and chemical phenomena that occur during carbonation curing. Building on the fundamental understanding of carbonation developed in this review, novel instrumentation is designed to study the carbonation curing process and engineer methods to limit or eliminate nonuniformity in carbonate concrete materials.

Harmful algal blooms (HABs) are increasingly common in New Jersey waters due to nutrient pollution and rising temperatures, producing organic toxins that threaten ecosystems and public health. Under climate change, HABs are expected to occur more frequently and become more widespread. This study investigates twelve HAB-associated toxins across freshwater and estuarine sites in New Jersey. Environmental parameters, including temperature, salinity, dissolved oxygen, and chlorophyll, were measured in situ using a YSI sonde. Water samples were filtered, extracted via solid phase extraction, and analyzed with ultrahigh performance liquid chromatography–tandem mass spectrometry (LC-MS/MS) to detect and quantify toxins. Pectenotoxin-2 (PTX2) and Dinophysistoxin-2 (DTX2) showed a strong correlation (r = 0.99), indicating co-occurrence of toxin-producing algae such as Dinophysis spp., while microcystin-YR (MC-YR) was more abundant in lower-salinity environments (r = –0.57), suggesting freshwater prevalence. The highest PTX2 concentrations (140 ng/L) were recorded at the Metedeconk River (a brackish site), likely produced by Dinophysis spp., while Brevetoxin PbTx2 levels remained low (<20 ng/L) across all sites. These findings show that HAB toxin distribution in New Jersey waters is linked to environmental conditions. Establishing and validating an LC-MS/MS protocol supports monitoring HAB drivers, guiding mitigation, and protecting aquatic ecosystems under changing climates.

The shift from fossil fuels to sustainable electricity sources is essential for mitigating CO₂ emissions and addressing global energy challenges. Hydrogen fuel is a promising pathway toward sustainable electricity generation, serving as a clean energy carrier that stores energy from renewable sources, such as solar and wind, and later releases it through fuel cells, which produce electricity with water as the only byproduct. Only a few homogeneous transition metal catalysts have been reported for electrochemical H2 oxidation, highlighting a key research gap for fuel utilization. Hydrogen oxidation may proceed via heterolytic H2 splitting where H2 is cleaved into a proton that is transferred to an exogenous base and hydride that is delivered to the catalyst, forming the metal-hydride complex. In this work, we have demonstrated that a cobalt-phosphine complex featuring a pendent-basic ligand reacts with H2 in a heterolytic fashion under ambient pressure in the presence of different bases. Reactivity studies reveal a clear correlation between base strength and formation of the cobalt-hydride complex: stronger bases result in faster conversion via multi-step proton- and electron-transfer equilibria. Furthermore, reactivity studies on the analogous complex without pendent-basic ligand sites showed negligible activity for H2 splitting, indicating the key role of these groups, likely as intramolecular proton relays.

Massive influxes of pelagic Sargassum spp. across the tropical Atlantic and Caribbean regions have created urgent ecological and economic challenges that need to be met to stabilize ecosystems. Use of this abundant resource as a source of bioproducts is a promising avenue but this requires elucidating the microbial processes that regulate Sargassum degradation, which are poorly understood. Here, we investigated the microbial degradation of the benthic Sargassum filipendula using multi-omics approaches. As expected, bacterial taxa with putative polysaccharide-degrading capabilities were enriched over time. Metagenomic and metatranscriptomic analyses identified diverse carbohydrate-active enzymes (CAZymes), including alginate lyases, fucoidanases, and cellulases, which were differentially expressed over the course of the degradation timeline. Compositional analysis supported the expression patterns of these lyase genes, particularly alginate, which was the most active class of CAZymes and showed a significant decrease between the start and end of the experimental period. Furthermore, we identified the need for arsenic detoxification pathways in organisms utilizing Sargassum derived substrates. We observed a suite of factors influencing microbial dynamics including prokaryotic competition, arsenic detoxification, viruses, and substrate availability. These factors appeared to influence prokaryote composition, with lineages capable of degrading recalcitrant polysaccharides like fucoidan rapidly outcompeted by other bacteria which utilized simpler sugars. These results highlight the metabolic potential of marine microbial communities to degrade complex Sargassum polysaccharides. Our findings elucidate microbial ecosystem dynamics during Sargassum stranding and provide novel insights that can be used to advance development of biotechnological approaches that leverage Sargassum biomass as a renewable resource.

Background: Clearcutting and removal of trees can disrupt soil structure and alter soil permeability, leading to increased runoff and reduced carbon storage, exacerbating climate change. This study investigates the impact of a 2022 manual clearcutting event on soil permeability by comparing infiltration rates in recently clearcut and intact forested sites. Methods: Soil samples were collected at 15 cm depth from five locations within each land cover type in December 2024. Permeability was assessed through water percolation tests and infiltration times were recorded for statistical comparison using the Mann–Whitney U test. Results: Results indicate a slower mean percolation time in clearcut soils (100.9 ± 44.6 s) compared to forested soils (59.5 ± 32.1 s), suggesting reduced infiltration in disturbed sites, p = 0.0947. Although the statistical outcome did not support the initial hypothesis, the observed numerical trend highlights a possible trajectory toward long-term soil degradation. Implications: These findings reinforce the importance of managing deforested areas to preserve soil hydrological function. While limited by sample size and methodology, this investigation contributes local evidence of the ecological effects of manual deforestation. Studying this process at Black Rock Forest, NY, an important living research laboratory in our geographical area, helps scientists understand the local changes in ecosystem dynamics and can inform strategies to mitigate adverse climate effects.

The urban heat island (UHI) effect increases urban residents’ heat exposure risk compared to their nonurban counterparts. We aim to identify and quantify the spatiotemporal modes of temperature variability across New Jersey relevant to urban heat amplification. First, average hourly temperatures from a subset of 43 Office of the New Jersey State Climatologist Mesonet weather stations from 2016–2024 were altitude corrected for lapse rate effects and compared to percentage of impervious surface surrounding the stations. The Mesonet stations do not show clear evidence of an air temperature UHI, which is unsurprising given that Mesonet sites exclude highly urbanized areas. Interestingly, the Pennsauken station, which is surrounded by the highest impervious percentage, is found to be consistently warmer. Given that factors besides urbanization appear to more strongly modulate Mesonet station temperature behavior, we seek to account for these through application of a suite of empirical orthogonal function, K-means clustering, and self-organizing maps analyses of both station-level and gridded reanalysis weather data from ERA5. Preliminarily, such analyses do show evidence of a weak UHI effect in the Mesonet stations. Our ongoing research explores the synoptic conditions that likely play a role in transient expression of the UHI and its spatial variability.

Plum curculio (Conotrachelus nenuphar) is a significant pest of pomaceous and stone fruits, including apples, peaches, plums, cherries, and blueberries. Its management is challenging due to potential overlap between optimal pesticide application timing and pollinator activity during bloom. To explore how blueberry bloom and PC activity periods may coincide, we analyzed monitoring data from 2012–2024 (bloom) and 2016–2024 (PC captures), converting each to percent progression per year. Logistic curves were fit to progression and accumulated degree days using a nonlinear mixed-effects model approach to account for variability across farms and years. These models help identify windows when honeybees might be safely removed to initiate PC control. On average, modeled peak bloom occurred around day 117 and peak PC activity around day 145, with significant farm-level variation. In both cases, progression start is highly variable while the development itself is consistent between sites. Differences in progression rates suggest that bloom–PC overlap may shift with warming springs. To explore future dynamics, we applied the developed models to temperature projections from 16 CMIP6 climate models for 2035–2065. This analysis can help inform adaptive pest management strategies that balance crop protection with pollinator safety with climate change.

Carbonyl sulfide (OCS) is taken up by plants during photosynthesis along similar pathways to carbon dioxide. Because OCS is not respired, it is a potential tracer gas for terrestrial carbon uptake. The OCS fluxes of other ecosystem components must be known for OCS to be used to estimate gross primary production. The OCS fluxes of bryophytes such as mosses and liverworts are relatively understudied. They may vary with environmental conditions such as moisture, temperature, and UV light exposure. This work addresses the uncertainty in bryophyte OCS fluxes by measuring gas fluxes from bryophyte samples under laboratory manipulations of temperature. Moss samples were collected from Harvard Forest, MA, a transition hardwood forest, in June and November 2024. Samples were placed in a PFA jar with a self-contained thermocouple and data logger to measure temperature. OCS and CO2 concentrations were measured with a quantum cascade laser first at room temperature, and then at a range of temperatures from 15° C to 35° C. The fluxes were then calculated. OCS fluxes were mostly positive, indicating uptake.

Scalloped ice surfaces, commonly observed beneath glaciers, bottom of floating ice, and other turbulent water-ice interface, emerge from a self-organized interaction between turbulent flow and melting topography. To uncover the physical mechanisms governing their equilibrium geometry, we performed two-dimensional simulations of flat and scalloped ice–water interfaces by developing a high fidelity Computational Fluid Dynamics model. Results reveal that scalloped geometries intensify near-wall shear, generate recirculating dipole vortices within troughs, and enhance local heat transfer leading to spatially varying melt rates. Compared to flat surfaces, scallops exhibit stronger turbulence melt coupling and distinct phase lags between turbulent energy production and melting peaks. These processes, observed at the microscale, are fundamental to understanding how turbulence modulates ice–ocean heat exchange and the overall rate of ice mass loss. The findings provide a mechanistic link between laboratory-scale dynamics and global ice melting processes, offering improved parameterizations for climate and ocean models that seek to predict sea-level rise more accurately.

In Wilmington, Delaware, climate change–driven increases in precipitation and sea level rise are straining the city’s aging combined sewer and stormwater systems. Green stormwater infrastructure (GSI) offers a sustainable strategy to mitigate flooding, improve water quality, and enhance community resilience; however, if inequitably implemented, GSI can reinforce environmental injustice. This research focuses on Northeast Wilmington, a community severely impacted by fluvial flooding during Hurricane Ida in 2021. The study integrates hydrologic data with community perspectives to identify GSI types and locations that align with both physical conditions and resident priorities. Using community-engaged methods—including twenty-six semi-structured interviews, sixty-one surveys, and three participatory mapping exercises—the project examines local experiences with flooding, perceptions of GSI, and barriers to adoption and maintenance. Results highlight frequent flooding along key corridors such as the 11th Street Bridge, Market Street, and E. 12th Street, and emphasize residents’ preferences for practical, attractive, and well-maintained GSI such as rain barrels, tree trenches, and sidewalk planters. Participants underscored the need for equitable investment, consistent maintenance, and inclusion in planning processes. Findings inform resilience planning by identifying community-supported and hydrologically appropriate sites for GSI, contributing to broader understanding of how participatory, place-based approaches advance equitable climate adaptation.

This poster visualizes how current climate change threatens coral reefs. It highlights three major stressors: (1) thermal stress from rising sea-surface temperatures, which disrupts coral–zooxanthellae symbiosis and triggers bleaching and mortality; (2) sea-level rise that increases suspended sediments and gradually smothers corals; and (3) ocean acidification from elevated CO₂, which weakens coral skeleton formation. A single coral is used as the central figure, with different sections of the same organism showing how it deforms or adapts under each stressor, supported by concise data labels and mini-charts. The narrative suggests a coral living in a warming era and being pushed into three parallel, pressured futures—yet ones that remain alterable through human interventions. Dark backgrounds and a highly saturated, high-contrast rendering of the coral emphasize damage, causality, and current responses.

Distributed energy resources offer a control-based option to improve distribution system reliability by ensuring system states that positively impact component failure rates. This option is an attractive complement to otherwise costly and lengthy physical infrastructure upgrades. However, required models that adequately map operational decisions and environmental conditions to system failure risk are lacking because of data unavailability and the fact that distribution system failures remain rare events. Our project addresses this gap and proposes a multi-source data model that consistently maps comprehensive weather and system state information to component failure rates. To manage collinearity in the available features, we propose two ensemble tree-based models that systematically identify the most influential features and reduce the dataset’s dimensionality based on each feature’s impact on failure rate estimates. These estimates are embedded within a sequential, non-convex optimization procedure, that dynamically updates operational control decisions. We perform a numerical experiment to demonstrate the cost and reliability benefits that can be achieved through this reliability-aware control approach and to analyze the properties of each proposed estimation model.

As the cornerstone of modern infrastructure and one of the largest CO2 contributors, the cement industry is a key driver of climate change. In 2023, global cement production reached approximately 4.1 billion tons, releasing about 1.6 billion tons of CO2-eq, or 8% of total anthropogenic emissions. Meanwhile, the United States generated over 400 million tons of concrete waste, containing a substantial amount of recoverable cementitious materials that remain underutilized. The dual challenge of large carbon emissions and increasing construction waste underscores the urgent need for circular and low-carbon solutions in the cement industry. Recovering cement from waste concrete provides a sustainable and cost-effective pathway, mitigating both carbon emissions and waste generation. This study evaluates three potential mechanical and chemical routes for cement recovery from waste concrete and analyzes their environmental and economic performance. The results indicate that these pathways can significantly lower the carbon footprint of cement production, while being market competitive with traditional Portland cement through co-product sales and tipping fee revenues. Such recovery-based strategies advance low-emission cement production and support the broader goal of deep decarbonization in the construction materials sector.