The islands of Sardinia and Sicily accounted for the largest contaminated sea area in the country, according to surveys conducted between 2016 and 2021. The largest contaminated sea site in Italy was in Sardinia.

Rising sea levels (SLR) will cause coastal groundwater to rise in many coastal urban environments. Inundation of contaminated soils by groundwater rise (GWR) will alter the physical, biological, and geochemical conditions that influence the fate and transport of existing contaminants. These transformed products can be more toxic and/or more mobile under future conditions driven by SLR and GWR. We reviewed the vulnerability of contaminated sites to GWR in a US national database and in a case comparison with the San Francisco Bay region to estimate the risk of rising groundwater to human and ecosystem health. The results show that 326 sites in the US Superfund program may be vulnerable to changes in groundwater depth or flow direction as a result of SLR, representing 18.1 million hectares of contaminated land. In the San Francisco Bay Area, we found that GWR is predicted to impact twice as much coastal land area as inundation from SLR alone, and 5,297 state-managed sites of contamination may be vulnerable to inundation from GWR in a 1-meter SLR scenario. Increases of only a few centimeters of elevation can mobilize soil contaminants, alter flow directions in a heterogeneous urban environment with underground pipes and utility trenches, and result in new exposure pathways. Pumping for flood protection will elevate the salt water interface, changing groundwater salinity and mobilizing metals in soil. Socially vulnerable communities are more exposed to this risk at both the national scale and in a regional comparison with the San Francisco Bay Area. Methods Data Dryad This data set includes data from the California State Water Resources Control Board (WRCB), the California Department of Toxic Substances Control (DTSC), the USGS, the US EPA, and the US Census. National Assessment Data Processing: For this portion of the project, ArcGIS Pro and RStudio software applications were used. Data processing for superfund site contaminants in the text and supplementary materials was done in RStudio using R programming language. RStudio and R were also used to clean population data from the American Community Survey. Packages used include: Dplyr, data.table, and tidyverse to clean and organize data from the EPA and ACS. ArcGIS Pro was used to compute spatial data regarding sites in the risk zone and vulnerable populations. DEM data processed for each state removed any elevation data above 10m, keeping anything 10m and below. The Intersection tool was used to identify superfund sites within the 10m sea level rise risk zone. The Calculate Geometry tool was used to calculate the area within each coastal state that was occupied by the 10m SLR zone and used again to calculate the area of each superfund site. Summary Statistics were used to generate the total proportion of superfund site surface area / 10m SLR area for each state. To generate population estimates of socially vulnerable households in proximity to superfund sites, we followed methods similar to that of Carter and Kalman (2020). First, we generated buffers at the 1km, 3km, and 5km distance of superfund sites. Then, using Tabulate Intersection, the estimated population of each census block group within each buffer zone was calculated. Summary Statistics were used to generate total numbers for each state. Bay Area Data Processing: In this regional study, we compared the groundwater elevation projections by Befus et al (2020) to a combined dataset of contaminated sites that we built from two separate databases (Envirostor and GeoTracker) that are maintained by two independent agencies of the State of California (DTSC and WRCB). We used ArcGIS to manage both the groundwater surfaces, as raster files, from Befus et al (2020) and the State’s point datasets of street addresses for contaminated sites. We used SF BCDC (2020) as the source of social vulnerability rankings for census blocks, using block shapefiles from the US Census (ACS) dataset. In addition, we generated isolines that represent the magnitude of change in groundwater elevation in specific sea level rise scenarios. We compared these isolines of change in elevation to the USGS geological map of the San Francisco Bay region and noted that groundwater is predicted to rise farther inland where Holocene paleochannels meet artificial fill near the shoreline. We also used maps of historic baylands (altered by dikes and fill) from the San Francisco Estuary Institute (SFEI) to identify the number of contaminated sites over rising groundwater that are located on former mudflats and tidal marshes. The contaminated sites' data from the California State Water Resources Control Board (WRCB) and the Department of Toxic Substances (DTSC) was clipped to our study area of nine-bay area counties. The study area does not include the ocean shorelines or the north bay delta area because the water system dynamics differ in deltas. The data was cleaned of any duplicates within each dataset using the Find Identical and Delete Identical tools. Then duplicates between the two datasets were removed by running the intersect tool for the DTSC and WRCB point data. We chose this method over searching for duplicates by name because some sites change names when management is transferred from DTSC to WRCB. Lastly, the datasets were sorted into open and closed sites based on the DTSC and WRCB classifications which are shown in a table in the paper's supplemental material. To calculate areas of rising groundwater, we used data from the USGS paper “Projected groundwater head for coastal California using present-day and future sea-level rise scenarios” by Befus, K. M., Barnard, P., Hoover, D. J., & Erikson, L. (2020). We used the hydraulic conductivity of 1 condition (Kh1) to calculate areas of rising groundwater. We used the Raster Calculator to subtract the existing groundwater head from the groundwater head under a 1-meter of sea level rise scenario to find the areas where groundwater is rising. Using the Reclass Raster tool, we reclassified the data to give every cell with a value of 0.1016 meters (4”) or greater a value of 1. We chose 0.1016 because groundwater rise of that little can leach into pipes and infrastructure. We then used the Raster to Poly tool to generate polygons of areas of groundwater rise.

The sea area of Sulcis, Iglesiente, and Giuspinese, in the island of Sardinia, was the largest contaminated area offshore the coasts of Italy as of 2021, with an extension of over 32,000 hectares. The contaminated sea and land sites in the country are undergoing safety assessments and remediation procedures.

Full title:

Diatom and associated data for a manipulative field experiment which translocated control and contaminated sediments between locations within the Windmill Islands, Antarctica.

A manipulative field experiment was performed to assess the effects of heavy metals and petroleum hydrocarbons on benthic diatom communities in the Windmill Islands. Three treatments were used (control, metal contaminated, and petroleum hydrocarbon contaminated), with replicates of each treatment deployed at three locations (Sparkes Bay, Brown Bay and O'Brien Bay). The datasets associated with this experiment include the concentrations of metals within the sediments as well as diatom data (raw counts, and the relative abundance of benthic species).

This work was completed as part of ASAC project 1130 (ASAC_1130) and project 2201 (ASAC_2201).

Public summary from project 1130:

Algal mats grow on sea floor in most shallow marine environments. They are thought to contribute more than half of the total primary production in many of these areas, making them a critical food source for invertebrates and some fish. We will establish how important they are in Antarctic marine environments and determine the effects of local sewerage and tip-site pollution. We will also investigate the impact on the algal mats of the additional UV radiation which results from the ozone hole.

Public summary from project 2201:

As a signatory to the Protocol on Environmental Protection to the Antarctic Treaty Australia is committed to comprehensive protection of the Antarctic environment. This protocol requires that activities in the Antarctic shall be planned and conducted on the basis of information sufficient to make prior assessments of, and informed judgements about, their possible impacts on the Antarctic environment. Most of our activities in the Antarctic occur along the narrow fringe of ice-free rock adjacent to the sea and many of our activities have the potential to cause environmental harm to marine life. The Antarctic seas support the most complex and biologically diverse plant and animal communities of the region. However, very little is known about them and there is certainly not sufficient known to make informed judgements about possible environmental impacts.

The animals and plants of the sea-bed are widely accepted as being the most appropriate part of the marine ecosystem for indicating disturbance caused by local sources. Attached sea-bed organisms have a fixed spatial relationship with a given place so they must either endure conditions or die. Once lost from a site recolonisation takes some time, as a consequence the structure of sea-bed communities reflect not only present conditions but they can also integrate conditions in the past. In contrast, fish and planktonic organisms can move freely so their site of capture does not indicate a long residence time at that location. Because sea-bed communities are particularly diverse they contain species with widely differing life strategies, as a result different species can have very different levels of tolerance to stress; this leads to a range of subtle changes in community structure as a response to gradually increasing disturbance, rather than an all or nothing response.

This project will examine sea-bed communities near our stations to determine how seriously they are affected by human activities. This information will be used to set priorities for improving operational procedures to reduce the risk of further environmental damage.

The fields in this dataset are:

Species Arsenic Cadmium Copper Lead Silver Zinc Concentration Location Treatment Abundance Benthic Site

The NASA Scatterometer (NSCAT) Level 2 ocean wind vectors in 50 km wind vector cell (WVC) swaths contain daily data from ascending and descending passes. Wind vectors are accurate to within 2 m/s (vector speed) and 20 degrees (vector direction). Wind vectors are not considered valid in rain contaminated regions; rain flags and precipitation information are not provided. Data is flagged where measurements are either missing, ambiguous, or contaminated by land/sea ice. Winds are calculated using the NSCAT-2 model function. This is the most up-to-date version, which designates the final phase of calibration, validation and science data processing, which was completed in November of 1998, on behalf of the JPL NSCAT Project; wind vectors are processed using the NSCAT-2 geophysical model function.

This data set contains chemical parameters determined for marine sediment samples collected in the 2014-15 summer field season as part of the Thala Valley Long term Monitoring (TV-LTM) project. The aim of this project is to examine changes in the marine benthic ecosystem in the vicinity of Casey station following clean-up of the abandoned Thala Valley waste disposal ('tip') site in 2003-04.

The chemical parameters are: (1) 1 M hydrochloric acid-extractable elements (mainly metals) by ICP-AES (inductively coupled plasma - atomic emission spectrometry) (2) water-extractable nutrients by FIA (flow injection analysis) (3) petroleum hydrocarbon fractions (TPH: total petroleum hydrocarbons) and persistent organic pollutants (POPs) - polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs) - by GC-FID, GC-ECD and GC-MS (gas chromatography - flame ionization detector / electron capture detector / mass spectrometry), respectively (4) Loss on Ignition at 550 degrees Celsius (LOI; as a proxy for Total Organic Matter) and Dry Matter Fraction (DMF) by gravimetric analysis.

Data sets 1, 3 and 4 were obtained for composite samples prepared from the 0-5 cm section of 51 marine sediment cores collected by SCUBA divers from impacted (contaminated) and control (pristine) locations around Casey. Data set 2 was obtained for a subsample of the surface section (0-1 cm) of each of 74 marine sediment cores collected during the same sampling campaign.

Sample locations: * Brown Bay (BB) - inner, mid and outer sites * Casey Wharf * McGrady Cove * O'Brien Bay (OB) - OB1, OB2, OB3 sites * Shannon Bay * Wilkes (adjacent to abandoned station)

Analytical labs involved: * Wild Lab, AAD, Kingston, Tasmania (data sets 1 and 4; sample preparation for data set 2) * Analytical Services Tasmania (AST), New Town, Tasmania (data set 2) * Analytical Services Unit (ASU), Queen's University, Kingston, Ontario, Canada (data set 3)

Information concerning analytical data quality (method reporting limits, accuracy and precision), are included with each data set. Complete analytical method details are available in a separate summary document.

The NASA Scatterometer (NSCAT) Level 3 daily gridded ocean wind vectors are provided at 0.5 degree spatial resolution for ascending and descending passes; wind vectors are averaged at points where adjacent passes overlap. Wind vectors are not considered valid in rain contaminated regions; rain flags and precipitation information are not provided. Data is flagged where measurements are either missing, ambiguous, or contaminated by land/sea-ice. This is the most up-to-date version, which designates the final phase of calibration, validation and science data processing, which was completed in November of 1998, on behalf of the JPL NSCAT Project; wind vectors are processed using the NSCAT-2 geophysical model function.

According to a survey conducted on the treatment of water that was contaminated during the nuclear accident in 2011 in Japan, 47 percent of respondents believed there to be no other method than to release the treated contaminated water into the ocean. In 2011, the Great East Japan Earthquake and the following tsunami caused meltdowns at three reactors in the Fukushima Daiichi Nuclear Power Plant in Fukushima Prefecture.

Italy has about 3.3 thousand kilometers of beaches. Along 87 kilometers, it is forbidden to bath due to water pollution. The island of Sicily has the most beaches unsuitable for swimming. In this region, it is forbidden to swim for roughly 43 kilometers out of the 425 kilometers of beaches.

The purpose of this project is to map the surficial geology of the sea floor of Historic Area Remediation Site (HARS) and changes in surficial characteristics over time. This GIS project presents multibeam and other data in a digital format for analysis and display by scientists, policy makers, managers and the general public.

The data set consists of: Seafloor topography and backscatter intensity of HARS Boundary of the Cellar Dirt Disposal Site Locations of Dredged Material Placed in the HARS Sediment Texture Samples Taken in the HARS in 1996 and 1998

Open-File Report 00-503 may be ordered on DVD from USGS Information Services. The DVD contains the GIS data, which are not available online, due to size

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