National Oceanic Atmospheric Administration Research Articles

Identification of microplastics in fish from the local fish market of Yogyakarta Province, Indonesia

Marine pollution, mainly plastic waste, has become a worldwide problem, especially in Indonesia. Indonesia is the second contributing country after China, with 10% contribution of the source of plastic pollution in the world. In the ocean, plastic will fragment into smaller pieces (less than 5 mm), known as microplastics (MPs). MPs can harm wildlife, especially fish, due to their toxic characteristics or other toxic substances attached to them. Indonesia, especially coastal areas, is known for its high consumption of marine fish, so this study aims to investigate the microplastics in fish sold at lokal fish markets in Bantul Regency, Yogyakarta Province, Indonesia. The fish sold came from the southern sea of Java (Indian ocean) around Depok Beach, Cemorosewu Beach, and Parangkusumo Beach. Three types of fish dominate namely Skipjack, Snapper, and Pomfret. The National Oceanic Atmospheric Administration (NOAA) and Wet Peroxide Oxidation (WPO) methods were used to examine fish samples. Identification of MPs was made based on shape and colour. The results showed that the most common MPs found were fibres with a total number of 36-91 particles/fish. The dominant colour of MPs is transparent, with a total of 552 particles from total samples. Although the analysis was only conducted in fish intestinal, there is potential that MPs will be found in fish meat. The chemical characteristics of MPs were determined using the Fourier Transport InfraRed (FTIR). The types of plastics found were Polyethylene (PE), Polypropylene (PP), and Nylon.

Maneuvering into the future: Open-Architecture Data Repository (OADR) prototype: Towards civil and commercial space traffic coordination

In 2018, the US National Space Council released Space Policy Directive-3 (SPD-3), which instructed relevant US government agencies to begin re-assigning many aspects of space traffic management (STM) and space traffic coordination (STC) serving non-military US space operators. This was identified as a ‘whole of government’ approach, and the organization identified to lead many of the efforts was the National Oceanic & Atmospheric Administration (NOAA) Office of Space Commerce (OSC), in the US Department of Commerce (DOC). The US Congress, in Public Law 116–93, Consolidated Appropriations Act, 2020, legislation directed that the Secretary of Commerce contract with the National Academy of Public Administration (NAPA) to study the Trump Administration's proposal. The NAPA study affirmed OSC would be best suited. Congress also mandated that OSC accomplish an important first step: assemble an Open Architecture Data Repository11Since this paper was first presented, the name for the effort, the Open Architecture Data Repository (OADR), has been changed to TraCSS (Traffic Coordination System for Space). As the focus of this work is on the prototype demonstration system, we will retain the use of OADR in this paper. (OADR) prototype to demonstrate the efficacy of the approach and architecture.OSC, along with The Aerospace Corporation, MITER, MIT Lincoln Laboratories and the University of Texas-Austin, architected and assembled a working prototype in 2021. The team obtained two-months of data from the US Space Surveillance Network (SSN), along with data from commercial space surveillance data providers and satellite operator ephemerides. Using the prototype, the authors analyzed the data, identified potential satellite conjunctions, calculated probabilities of collision, and generated Conjunction Data Messages (CDMs). The team compared the results to existing operational systems, with good agreement. OSC and their partners demonstrated the OADR prototype results to the Congress, as funded and directed by Public Law 116–260, the Consolidated Appropriations Act of 2021. This paper describes some of the background and rationale for the prototype, goals and derived requirements of the prototype, the architecture, software deployed, data utilized, conjunction analysis results, comparison of the prototype's results with existing operational US government systems, and possible next steps for the OADR.

Epidemiological profile of Visceral Leishmaniasis in Brazil between 2011-2020

The purpose of this study was to carry out an epidemiological analysis of Visceral Leishmaniasis cases registered by the Notifiable Diseases Information System (SINAN-DATASUS) in Brazil between the years 2011 and 2020. The variables verified were: year, region of notification, gender, age group, and disease progression. In the time range studied, 34,386 cases were registered in the Brazilian territory. The year 2017 stood out with the highest number of cases: 4,462, and 2020 presented the lowest number: 1,908. Such variations proved to be related to global climatic and epidemiological events: 2017 was evaluated as the 3rd hottest year in history by the North American Entity NOAA (National Oceanic Atmospheric Administration), with the consulted literature pointing to relations of growth in the incidence of high temperature climatic events. The year 2020 faced the COVID-19 pandemic break-out. There was a predominance of cases in the Northeast (54.96%), followed by the Southeast (18.67%), North (18.05%), Midwest (8.01%) and South (0.31%). The gender variable shows a predominance of incidence of 65.08% in males and 34.91% in females, which is compatible with the literature. Another parameter that remains within the literature is the age group, where the highest incidence in the 1-4 age group was 23.77%, remaining a disease that severely affects children. The percentages found are in line with the literature and the disease has changed its spread in the Northeast region of the country from about 90% to 55% in two decades, still remaining the most affected region of the country. The disease appears to be more widespread and urban in current studies. There are new and efficient multidisciplinary resources – pharmacological, geographic, climatic and environmental – which, if continued, expanded, and articulated, can strengthen the fight against this serious harm to human health.

Spatiotemporal variability of precipitation and surface temperature in the southern mesoregion of amazonas, Brazil, during the occurrence of ENSO

Impacts of El Niño – Southern Oscillation (ENSO) climatic phenomena in the southern mesoregion of the Amazon is still poorly understood. Thus, the objective of this study was to analyze the impacts of ENSO of moderate and strong categories on precipitation (ppt) and surface temperature (ts) in the southern mesoregion of Amazonas. The research was carried out with ppt data obtained by the product TRMM_3B43 and ts of the product MOD11C3 in the municipalities of Apuí, Boca do Acre, Canutama, Humaitá, Lábrea, Manicoré and Novo Aripuanã. The Niño Indices were obtained from the National Oceanic Atmospheric Administration. Ts was organized into averages and ppt in seasonal totals from 1998 to 2019, to obtain its provisional climatological normal in the dry and wet seasons. The results showed that ENSO significantly influenced the pattern of ppt and ts in the southern mesoregion of Amazonas. El Niño (EN) had more impact on changing the pattern of ppt and ts than La Niña (LN). The largest reductions in ppt and increases in Ts occurred in the EN periods of 1998/01 and 2015/16, while the occurrence of LN decreased the ppt more expressively in the periods of 2007/08 and 2011/12.

Assessment of the change of trend in precipitation over Afghanistan in 1979–2019

The civil war, harsh climate, tough topography, and lack of accurate meteorological stations have limited the number of consecutive synoptic data across Afghanistan. The global data (gridded precipitation datasets) pave the way to assess the precipitation indicators of climate, where stations are sparsely located. This study assessed the mean annual precipitation trend in 33 stations over Afghanistan. Non-parametric linear regression technique was employed to find upward and downward trends and magnitudes. The daily of precipitation was obtained from the database of the CPC-NOAA (Climate Prediction Center - National Oceanic Atmospheric Administration) for the period of 1979–2019. The CPC spatial resolution of daily precipitation is 0.5×0.5 degree. Analysis of mean annual precipitation showed a significant decreasing trend at six provinces in the north, while an increasing trend of 9.2 mm per decade has been observed at three provinces. In the south, a notable reduction of the precipitation trend has been experienced in Helmand, Kandahar, and Nimruz provinces, but Ghazni and Uruzgan show a positive trend. Data revealed that mean annual precipitation has remarkably decreased in the western part of Afghanistan. According to the study period, the mean annual rainfall in the central regions indicates a raise of 37.5 mm per decade in Kabul, while in Vardak, the precipitation increases up to 9.21 mm per year. Eastern regions include 8 provinces, and the eastern highland covers the smallest area that is mainly covered by rangeland and the largest existing forests. These regions are directly influenced by the moist air masses of Indian monsoon getting trapped at the high mountain slopes, and it can lead to an increase of rain. Data reveals an upward trend of precipitation in the eastern part of Afghanistan.

Event of harmattan dust transport in Kano State of Nigeria

The study was conducted at Kano state of Nigeria with data from the National Oceanic Atmospheric Administration (NOAA) using the meteorological station of Mallam Aminu international airport of Kano state.

Numerical approximation to the effects of the atmospheric stability conditions on the dispersion of pollutants over flat areas

Using the Computational Fluid Dynamics technique (CFD), we explored the effects of the atmospheric stability conditions on the dispersion of solid and gas-phase pollutants emitted from an area source located on a flat region. As an application, the dispersion of pollutants emitted from roads located on flat terrains was considered. Toward that end, we set up a model that describes the dispersion of air pollutants in a small region (< 1 km long) near the ground surface (< 250 m high). It consists of a neutrally stratified model modified to account for the atmospheric stability effects by imposing the near-ground stratification through the Monin–Obukhov similarity theory and the k–ε turbulence model adjusted for each atmospheric stability condition. Using this model, we simulated the dispersion of pollutants emitted from the road and plotted the resulting downwind concentrations in terms of dimensionless numbers. Results from our CFD-based model were highly correlated (R2 > 0.95) with the SF6 concentrations measured downwind a line source of this trace gas by the U.S. National Oceanic Atmospheric Administration in 2008 under different conditions of atmospheric stability. Numerical and experimental results showed that, under any of the stability conditions explored, the near-road pollutant concentrations are highly correlated (R2 > 0.87) to the concentrations observed under neutral conditions. When the atmosphere is extremely stable, those concentrations were up to 12 times higher than those observed under neutral conditions. We report the constant of proportionality obtained for every stability condition.

Path to Automating Ocean Health Monitoring

Marine ecosystems directly and indirectly impact human health, providing benefits such as essential food sources, coastal protection and biomedical compounds. Monitoring changes in marine species is important because impacts such as overfishing, ocean acidification and hypoxic zones can negatively affect both human and ocean health. The US west coast supports a diverse assemblage of deep-sea corals that provide habitats for fish and numerous other invertebrates. Currently, National Oceanic Atmospheric Administration (NOAA) scientists manually track the health of coral species using extractive methods. In this paper, we test the viability of using a machine learning algorithm Convolutional Neural Network (CNN) to automatically classify coral species, using field-collected coral images in collaboration with NOAA. We fine tune the hyperparameters of our model to surpass the human F-score. We also highlight a scalable opportunity to monitor ocean health automatically while preserving corals.

Incorporating features from the Stochastic Time-Inverted Lagrangian Transport (STILT) model into the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model: a unified dispersion model for time-forward and time-reversed applications

AbstractThe Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model is a state-of-the-science atmospheric dispersion model that is developed and maintained at the National Oceanic Atmospheric Administration’s (NOAA) Air Resources Laboratory (ARL). In the early 2000s, HYSPLIT served as the starting point for development of the Stochastic Time-Inverted Lagrangian Transport (STILT) model that emphasizes backward-in-time dispersion simulations to determine source regions of receptors. STILT continued its separate development and gained a wide user base. Since STILT was built on a now outdated version of HYSPLIT and lacks long-term institutional support to maintain the model, incorporating STILT features into HYSPLIT allows these features to stay up to date. This paper describes the STILT features incorporated into HYSPLIT, which include: a new vertical interpolation algorithm for WRF derived meteorological input files, a detailed algorithm for estimating boundary layer height, a new turbulence parameterization, a vertical Lagrangian timescale that varies in time and space, a complex dispersion algorithm, and two new convection schemes. An evaluation of these new features was performed using tracer release data from the Cross Appalachian Tracer Experiment and the Across North America Tracer Experiment. Results show the dispersion module from STILT, which takes up to double the amount of time to run, is less dispersive in the vertical and in better agreement with observations than the existing HYSPLIT option. The other new modeling features from STILT were not consistently statistically different than existing HYSPLIT options. Forward-time simulations from the new model were also compared against backward-time equivalents and found to be statistically comparable to one another.

How could operational underwater sound from future offshore wind turbines impact marine life?

Offshore wind farms are part of the transition to a sustainable energy supply and both the total numbers and size of wind turbines are rapidly increasing. While the impact of underwater sound related to construction work has been in the focus of research and regulation, few data exist on the potential impact of underwater sound from operational wind farms. Here, we reviewed published sound levels of underwater sound from operational wind farms and found an increase with size of wind turbines expressed in terms of their nominal power. This trend was identified in both broadband and turbine-specific spectral band sound pressure levels (SPLs). For a nominal power of 10 MW, the trends in broadband SPLs and turbine-specific spectral band SPLs yielded source levels of 170 and 177 dB re 1 μPa m, respectively. The shift from using gear boxes to direct drive technology is expected to reduce the sound level by 10 dB. Using the National Oceanic Atmospheric Administration criterion for behavioral disruption for continuous noise (i.e., level B), a single 10 MW direct drive turbine is expected to cause behavioral response in marine mammals up to 1.4 km distance from the turbine, compared to 6.3 km for a turbine with gear box.

Polycyclic aromatic hydrocarbon status in post-hurricane Harvey sediments: Considerations for environmental sampling in the Galveston Bay/Houston Ship Channel region

Hurricane Harvey led to a broad redistribution of sediment throughout Galveston Bay and the Houston Ship Channel (GB/HSC), but the resulting changes in chemical contaminant distributions have yet to be characterized. To address this question, we collected and analyzed post-Harvey sediment for concentrations of the EPA 16 Priority Pollutant polycyclic aromatic hydrocarbon (PAHs), determining the extent to which the spatial distribution and sourcing of contaminants may have changed in contrast to historical surface sediment data (<5 cm) from the National Oceanic Atmospheric Administration (NOAA) available for the years 1996–2011. We found a small, but detectable increase from pre- to post-Harvey in PAH concentrations, with PAH diagnostic sourcing indicating combustion origins. Of the detected PAHs, none exceeded Sediment Quality Guideline values. Overall, we have added to the understanding of PAH spatial trends within the GB/HSC region, and developed a reference PAH baseline to inform future studies.

Profiling of formaldehyde, glyoxal, methylglyoxal, and CO over the Amazon: normalized excess mixing ratios and related emission factors in biomass burning plumes

Abstract. We report on airborne measurements of tropospheric mixing ratios and vertical profiles of formaldehyde (CH2O), glyoxal (C2H2O2), methylglyoxal and higher carbonyls (C3H4O2*) (see below), and carbon monoxide (CO) over the Amazon Basin during the ACRIDICON-CHUVA campaign from the German High Altitude and Long-range research aircraft (HALO) in autumn 2014. The joint observation of in situ CO and remotely measured CH2O, C2H2O2, and C3H4O2*, together with visible imagery and air mass back-trajectory modelling using NOAA HYSPLIT (National Oceanic Atmospheric Administration, HYbrid Single-Particle Lagrangian Integrated Trajectory), allows us to discriminate between the probing of background tropical air, in which the concentration of the measured species results from the oxidation of biogenically emitted volatile organic compounds (VOCs, mostly isoprene), and measurements of moderately to strongly polluted air masses affected by biomass burning emissions or the city plume of Manaus. For 12 near-surface measurements of fresh biomass burning plumes, normalized excess mixing ratios of C2H2O2 and C3H4O2* with respect to CH2O are inferred and compared to recent studies. The mean glyoxal-to-formaldehyde ratio RGF=0.07 (range 0.02–0.11) is in good agreement with recent reports which suggest RGF to be significantly lower than previously assumed in global chemical transport models (CTMs). The mean methylglyoxal-to-formaldehyde ratio RMF=0.98 (range 0.09–1.50) varies significantly during the different observational settings but overall appears to be much larger (up to a factor of 5) than previous reports suggest even when applying a correction factor of 2.0±0.5 to account for the additional dicarbonyls included in the C3H4O2* measurements. Using recently reported emission factors of CH2O for tropical forests, our observations suggest emission factors of EFG=0.25 (range 0.11 to 0.52) g kg−1 for C2H2O2 and EFM = 4.7 (range 0.5 to 8.64) g kg−1 for C3H4O2*. While EFG agrees well with recent reports, EFM is (like RMF) slightly larger than reported in other studies, presumably due to the different plume ages or fuels studied. Our observations of these critical carbonyls and intermediate oxidation products may support future photochemical modelling of air pollution over tropical vegetation, as well as validate past and present space-borne observations of the respective species.

Quantifying the influence of urban sources on night light emissions

Light pollution in urban locations is a complex, serious problem, but researchers have paid more attention to light pollution on natural, non-urban environments. Understanding the sources of artificial light radiance intensity is the first step in minimizing damage from light pollution in urban areas. The purpose of this study is to quantitatively examine the relationship between light pollution and urban built environments. We developed databases for a series of urban–built environment data with composite Visible Infrared Imaging Radiometer Suite day-night band (VIIRS-DNB) data from the Earth Observation Group of the United States National Oceanic Atmospheric Administration’s National Geophysical Data Center to apply regression models (production functions) with grid cells at a spatial resolution of 15 arc seconds. Based on the results, we identified urban-development and land-use characteristics and built-environment factors that caused high levels of light emissions in a city. First, high levels of light emissions are associated with urban spatial-development patterns, such as roads, office buildings, commercial facilities, higher proportions of “station influence areas,” and urban-development intensity. Second, more seriously, the infiltration of commercial facilities into urban residential areas makes them brighter and increases the risk of exposure to light pollution. Therefore, the development of commercial areas and commercial facilities that emit light should be properly managed, especially for areas mixed with residential land use. Third, our quantitative model with intra-city-level analyses can estimate a high level of the baseline light-emission propensity in Seoul, which indicates that a city’s light-emission intensity can be highly associated with its sociocultural and institutional characteristics for lighting and light uses.

Diurnal Variation in Cloud Liquid Water Path Derived from Five Cross-Track Microwave Radiometers Onboard Polar-Orbiting Satellites

The Advanced Microwave Sounding Unit (AMSU)-A/Advanced Technology Microwave Sounder (ATMS) onboard the National Oceanic Atmospheric Administration (NOAA)-18/-19, MetOp-A/-B, and Suomi National Polar-orbiting Partnership satellites provide global observations of the cloud Liquid Water Path (LWP) almost 10 times a day. This study explores the possibility of capturing the diurnal cycle of the LWP. An inter-satellite cross-calibration is first carried out using a double-difference method. A remapping is then used to obtain the AMSU-A-like LWP to account for beam shape discrepancies between the ATMS and AMSU-A. We finally examine the diurnal cycle of the LWP over the Southeast Pacific Ocean using the ATMS and AMSU-A data from the five satellites mentioned above. Results show that the remapped ATMS results agree well with the AMSU-A results at the same local time over a stratocumulus region. LWP retrievals from multiple satellite cross-track microwave radiometers can well reproduce the diurnal variation characteristics of LWP in 2015 over the East Pacific Ocean, including the seasonal variation of the diurnal variation. This study presents the first step toward merging LWP data from all ATMS and AMSU-A radiometers and will be of interest to many researchers studying LWP-related weather and climate changes, especially considering the possible loss of higher-resolution microwave-frequency conical-scanning sensors in the coming years.

Sunspot area as unexplored trend inside radial growth of European beech in Krkonoše Mountains: a forest science from different perspective

Many studies have examined the relationships between the effects of the sunspot area and growth of trees; however, none of them considered European beech (Fagus sylvatica L.). We investigated the relationships between the sunspot area, climate factors (temperature and precipitation) and radial growth of beech in the Krkonose Mts. in the Czech Republic. We used the core samples of 199 beech trees representing the century-long growth, two sets of climate data (local short-term data and general long-term climate data), and more than a century-long sunspot area dataset acquired from the National Oceanic Atmospheric Administration. Our results showed the significant effects of the sunspot area, temperature and precipitation on the radial growth of beech. The correlations between sunspot area and tree-ring width index varied from 0.9 to 0.5 in the period between 1986 and 2017, a period during which none of the significant anthropogenic disturbances occurred in the study area. The strong correlations were found between the sunspot area and climate factors for a longer period. The largest effect of the sunspot area on the radial growth was observed in the previous year, especially in growing season. Structurally diversified (heterogeneous) beech stands were less affected by the sunspot area compared to the homogeneous stands. In conclusion, the sunspot area is one of the important factors that significantly influence the radial growth of beech in the Krkonose Mts. Our results will be useful for understanding beech forests in the context of global change, and will have an important contribution to the knowledge for predicting potential impact of the sunspot area on the Earth’s surface.

Use of a high-resolution-satellite-based precipitation product in mapping continental-scale rainfall erosivity: A case study of the United States

A rainfall erosivity map is useful for understanding the spatial variability of rainfall erosivity, and for identifying regions vulnerable to soil erosion by rainfall. This study addresses a new approach to mapping rainfall erosivity on a continental scale, based on a high-resolution-satellite-based precipitation product—the National Oceanic and Atmospheric and Atmospheric Administration’s Climate Precipitation Center morphing technique (CMORPH). For this purpose, a rainfall erosivity map of the contiguous United States is experimentally developed, and is analyzed from the perspectives of the corresponding hydrological basins and climate features. In general, we conclude that the CMORPH precipitation product is useful for mapping rainfall erosivity on a continental scale. In the contiguous United States, the mean of rainfall erosivity was 1260 MJ mm ha−1 h−1 yr−1, with high variability by region. The coastal regions showed the highest rainfall erosivity, at 20%. The seasonality of the rainfall erosivity was evident in most coastal regions (rainfall erosivity depends on climates). The rainfall erosivity in the tropical climate zone was the highest, whereas it was the lowest in the arid climate zone (and spatially homogeneous). However, corrections were required for improving the accuracy of the CMORPH precipitation in most coastal regions, i.e., to secure a better rainfall erosivity product. Compared to a rain gauge-based rainfall erosivity map, the CMORPH’s rainfall erosivity map tended to underestimate the rainfall erosivity in coastal regions near the Gulf of Mexico and Atlantic Ocean, but overestimated it in coastal regions near the Pacific Ocean.

Optimizing an Inner-Continental Shelf Geologic Framework Investigation through Data Repurposing and Machine Learning

The U.S. Geological Survey (USGS) and the National Oceanic Atmospheric Administration (NOAA) have collected approximately 5400 km2 of geophysical and hydrographic data on the Atlantic continental shelf between Delaware and Virginia over the past decade and a half. Although originally acquired for different objectives, the comprehensive coverage and variety of data (bathymetry, backscatter, imagery and physical samples) presents an opportunity to merge collections and create high-resolution, broad-scale geologic maps of the seafloor. This compilation of data repurposes hydrographic data, expands the area of geologic investigation, highlights the versatility of mapping data, and creates new geologic products that would not have been independently possible. The data are classified using a variety of machine learning algorithms, including unsupervised and supervised methods. Four unique classes were targeted for classification, and source data include bathymetry, backscatter, slope, curvature, and shaded-relief. A random forest classifier used on all five source data layers was found to be the most accurate method for these data. Geomorphologic and sediment texture maps are derived from the classified acoustic data using over 200 ground truth samples. The geologic data products can be used to identify sediment sources, inform resource management, link seafloor environments to sediment texture, improve our understanding of the seafloor structure and sediment pathways, and demonstrate how ocean mapping resources can be useful beyond their original intent to maximize the footprint and scientific impact of a study.

The Influence of Weather on the Incidence of Primary Spontaneous Intracerebral Hemorrhage

BackgroundIntracerebral hemorrhage has been associated with changes in various weather conditions. The primary aim of this study was to examine the collective influence of temperature, barometric pressure, and dew point temperature on the incidence of primary spontaneous intracerebral hemorrhage (sICH). MethodsBetween January 2013 and December 2016, patients with sICH due to hypertension or amyloid angiopathy with a known time of onset were identified prospectively. Meteorological variables 6 hours prior to time of onset were obtained from the National Oceanic Atmospheric Administration via two weather stations. Using a Monte-Carlo simulation, random populations of meteorological conditions in a 6-hour time window during the same years were generated. The actual meteorological conditions 6-hours prior to sICH were compared to those from the randomly generated populations. The false discovery rate method was used to identify significant meteorological variables. ResultsTime of onset was identified in 455 of 603 (75.5%) patients. Distribution curves for change in temperature, mean barometric pressure, and change in barometric pressure 6-hours prior to hemorrhage ictus were found to be significantly different from the random populations. (FDR approach P < .05). For a given change in temperature associated with intracerebral hemorrhage, mean barometric pressure was higher (1018 millibar (mb) versus 1016 mb, P = .03). Barometric pressure data was not influenced by variations in temperature. ConclusionsWe concluded that barometric pressure primarily influences the incidence of intracerebral hemorrhage. The association described in the literature between temperature and intracerebral hemorrhage is likely confounded by variations in barometric pressure.

Power Estimates of Coastal Zone Winds and Waves via Box, Whisker and Outlier Distributions at Atlantic Eastern Seaboard and Pacific Ocean Energy Sites

The U.S. Bureau of Ocean Energy Management (BOEM) has a congressional mandate and the U.S. Department of Energy (DOE) both have mandates to assess oceanic wind and oceanic wave energy and power resources and impacts; both structural and potentially ecological. Oceanic offshore winds and waves are viewed as being relatively steady sources of energy. However assessments of the amount of the wind resources and wave resources in U.S. coastal and oceanic environments have not been evaluated and have only been estimated by several rudimentary modeling efforts. As such, there are many National Oceanic & Atmospheric Administration (NOAA) National Data Buoy Center (NDBC) Marine Buoys which have collected considerable data on both wind and waves that can be harvested and evaluated for in-situ observations. Also the U.S. Department of the Interior, Bureau of Safety and Environmental Enforcement (BSEE) is charged with the development of hazard curves for wind energy areas off the Atlantic Seaboard. As such BOEM has several proposed U. S. Eastern Seaboard, Atlantic Ocean energy/power sites. Likewise DOE is interested not only in potential Atlantic sites, but Pacific sites as well. In this manuscript we captured several representative time series of winds and waves from NOAA buoys, and evaluated those sites for their oceanic wind energy and wave energy potential, by employing a basic statistical methodology. The data sets are very self-consistent, and levels of energy vary as a function of locale, monthly, seasonally and annually. While ecological studies are called for at BOEM sites, such as on fisheries and other living marine resources, those are beyond the scope of this study.

Assessment of Polychlorinated Biphenyls (PCBs) in water, sediments and biota from e-waste dumpsites in Lagos and Osun States, South-West, Nigeria

The levels of PCBs in sediments, water, leachate and aquatic fauna ( Tilapia guineensis , Callinectes amnicola and Cardiosoma armatum ) found in and around e-waste dumpsites in Lagos and Osun States, South-West, Nigeria were analyzed using Gas Chromatography Electron Capture Detector (GC ECD) Agilent 7820A. All the 28 PCBs congeners studied were detected with the Σhexa-PCBs dominating in Lagos (21%) while the Σtetra-PCBs (24%) enriched the samples from Osun State. The concentrations of Σ- PCBs in decreasing order were Lagos: sediment ˃ fish gill ˃ fish muscles ˃ water ˃ crab ˃ leachate and Osun: fish gill ˃ fish muscle ˃ sediment ˃ crab ˃ water ˃ leachate. The concentrations of total indicator PCBs ( Σ7PCBs) in the sediment from Lagos (4.19 μg/kg) and Osun (8.58 μg/kg) exceeded the Canadian Sediment Quality standard threshold effect level (CSQ TEL) (0.03 μg/kg) and the National Oceanic Atmospheric Administration threshold effect level (NOAA TEL) for fresh and marine sediments.. The calculated toxic equivalent quotient (TEQ) for fish from Lagos and Osun (3.7 and 4.4) respectively further suggests a likely occurrence of adverse effects to humans who consume the fish. This study reveals the high health and ecological risks associated with e waste pollution in the aquatic environment. Keywords: e-waste, polychlorinated Biphenyls, aquatic environment, leachate