This fileset provides data and SEM images described in: Reisser J, Shaw J, Hallegraeff G, Proietti M, Barnes DKA, Thums M, Wilcox C, Hardesty BD, Pattiaratchi (2014) Millimeter-sized Marine Plastics: A New Pelagic Habitat for Microorganisms and Invertebrates. PLOS ONE

If you have any question/comment, please contact us at jureisser@gmail.com

Description of files DataTable.xlsx --> contains information related to the collection sites, plastic characteristics, and organism/surface microtexture presence-absence data decribed in the PLOS ONE manuscript. .tif files --> scanning electron microscopy images of marine plastic debris (N = 1143 images). The first number of the file name is the identification number of the plastic imaged (N = 68 pieces; see 1st column of DataTable.xls).

.txt files --> Polymer type as estimated by Perkin-Elmer ATR of Polymers Library (N = 66).

Description of the variables/columns of DataTable.xlsx

-> plastic identification number. Goes from 1 untill 68.

Type -> type of plastic. Hard (rigid fragment), Soft (flexible fragment), Pellet (raw material used to make plastic objects - see http://www.pelletwatch.org), Styro (expanded polystyrene/Styrofoam fragment). Polymer -> polymer the plastic piece is made of. PE (polyethylene), PP (polypropylene), PS (polystyrene). Length -> plastic length, in millimeters. Measured using ImageJ. Solidity -> plastic solidity index. Measured using ImageJ. Area -> plastic area, in squared millimeters. Measured using ImageJ. Perimeter -> plastic perimeter, in millimeters. Measured using ImageJ. Circularity -> plastic circularity index. Measured using ImageJ AspectRatio -> plastic aspect ratio. Measured using ImageJ. Roundness -> plastic roundness index. Measured using ImageJ. LinearFracture -> presence/absence of linear fracture on the plastic. 1=present, 0=absent. ConchoidalFracture -> presence/absence of conchoidal fracture on the plastic. 1=present, 0=absent. Pit -> presence/absence of pit on the plastic. 1=present, 0=absent. Groove -> presence/absence of groove on the plastic. 1=present, 0=absent. Diatom -> presence/absence of diatom on the plastic. 1=present, 0=absent. Coccolith -> presence/absence of coccolith on the plastic. 1=present, 0=absent. Dinoflagellate -> presence/absence of dinoflagellate on the plastic. 1=present, 0=absent. Round presence/absence of rounded cell smaller than 1 micrometer on the plastic. 1=present, 0=absent. Round>=1micron -> presence/absence of rounded cell bigger than 1 micrometer on the plastic. 1=present, 0=absent. Elong presence/absence of elongated cell smaller than 1 micrometer on the plastic. 1=present, 0=absent. Elong>=1micron -> presence/absence of elongated cell bigger than 1 micrometer on the plastic. 1=present, 0=absent. Spiral -> presence/absence of spiral cell on the plastic. 1=present, 0=absent. Bryo -> presence/absence of bryozoan on the plastic. 1=present, 0=absent. Lepas -> presence/absence of Lepas on the plastic. 1=present, 0=absent. Isopod -> presence/absence of isopod on the plastic. 1=present, 0=absent. Egg -> presence/absence of egg on the plastic. 1=present, 0=absent. Worm -> presence/absence of worm on the plastic. 1=present, 0=absent. Region -> marine region where the plastic was collected. North West, South West, South East, Temperate East, Coral Sea, and Pacific (see Figure 1 of the paper). Date -> date (day.month.year) when the plastic was collected. SeaTemperature -> Sea surface water temperature (in degrees celsius) of the plastic collection site. Salinity -> Sea surface salinity of the plastic collection site. Latitute -> latitude (in degrees) of the plastic collection site.

Longitude -> longitude (in degrees) of the plastic collection site.

The Canadian Environmental Sustainability Indicators (CESI) program provides data and information to track Canada's performance on key environmental sustainability issues. The Monitoring disposal at sea indicator shows if marine disposal site activities have an environmental impact. It reports the number of monitored ocean disposal sites that show no evidence of marine pollution from disposal activities. Managing what is discarded at sea prevents marine pollution by controlling the material disposed of at marine disposal sites. This indicator supports the measurement of progress towards the following 2016–2019 Federal Sustainable Development Strategy long-term goal: Coasts and oceans support healthy, resilient and productive ecosystems. Information is provided to Canadians in a number of formats including: static and interactive maps, charts and graphs, HTML and CSV data tables and downloadable reports. See the supplementary documentation for the data sources and details on how the data were collected and how the indicator was calculated. Supplemental Information Canadian Environmental Sustainability Indicators - Home page: https://www.canada.ca/environmental-indicators

This metadata record contains an Excel file containing total petroleum hydrocarbon data from analysis of marine sediments collected at Davis Station from December 2009 to March 2010. Refer to the Davis STP reports lodged under metadata record Davis_STP for the full Davis Sewage Treatment Project methods and result details.

Davis STP - Total petroleum hydrocarbons Hydrocarbons were extracted from a 10g sub-sample of homogenised wet soil by tumbling overnight with a mixture of 10 mL of deionised water, 10 mL of dichlormethane (DCM), and 1 mL of DCM spiked with internal standards: 254 mg/L bromoeicosane; 55.2 mg/L 1,4 dichlorobenzene; 51.2 mg/L p-terphenyl; 52.2 mg/L tetracosane-d50; and 255 mg/L cyclo-octane. Samples were then centrifuged for 5 minutes at 1000 rpm, this was repeated a further 3 times to ensure complete separation of the organic and aqueous fractions. The DCM fraction was then extracted and placed into GC-vials. Extracts were analysed for total petroleum hydrocarbons (TPH) by gas chromatography using flame ionisation detection (GC-FID; Agilent 6890N with a split/splitless injector) and an auto-sampler (Agilent 7683 ALS). Separation was achieved using an SGE BP1 column (25 m x 0.22 mm ID, 0.25 µm film thickness). 1 µL of extract was injected (5:1 pulsed split) at 310° C and 17.7 psi of helium carrier gas. After 1.3 minutes, the carrier gas pressure was adjusted to maintain constant flow at 3.0 mL/min for the duration of the oven program. The oven temperature program was started at 36 °C (held for 3 minutes) and increased to 320 °C at 18 °C/min. Detector temperature was 330 °C. TPH concentrations were determined using a calibration curve, generated from standard solutions of special Antarctic blend diesel (SAB), and standard diesel. TPH was measured using the ratio of the total detector response of all hydrocarbons to the internal standard peak response. List of compounds analysed - C8-C28 individual hydrocarbon components - Naphthalene - Biomarkers (phytanes) - Total signal and area, and resolved compounds from C8 to C40, over specific ranges (e.g. C9-C18, SAB) Reporting limit - 0.3 mg.kg-1 on a dry matter basis (DMB) for individual components - 2.5-160 mg.kg-1 on a dry matter basis (DMB) for various calculated ranges Analytical uncertainty - Analytical precision: (a) 3 samples extracted and analysed in triplicate, (b) 3 extracts analysed by GC-FID in duplicate; only 1 of each set greater than RL (160): (a) RSD = 2%, (b) RSD = 0.4% - Site heterogeneity: reproducibility (RSD) of mean data from site replicate samples (mostly duplicates) was 24% (mean, SD 20%, range 4-60%, n=8) - From the limited data on reproducibility summarised above, it can be concluded that site heterogeneity contributes most to the uncertainty of the TPH data for the site locations.

Background of the Davis STP project

Refer to the Davis STP reports lodged under metadata record Davis_STP.

This dataset accompanies our Science Advances manuscript investigating the aerosolization of wastewater-derived contaminants from the Tijuana River along the U.S.–Mexico border. It includes raw and processed data used to assess the spatial distribution and atmospheric transport of contaminants from coastal waters into the air. Files include: (1) Data tables with air mass origin assignments and quantified contaminant concentrations; (2) raw mass spectrometry data files and (3) links to external repositories hosting pre-processed MS and MS/MS data, as well as Global Natural Products Social Molecular Networking (GNPS) visualizations. These data support the spatial and chemical analyses presented in the manuscript and are intended to facilitate transparency, reproducibility, and further research on coastal aerosol pollution., , # Identifying Wastewater Chemicals in Coastal Aerosols

Dataset DOI: 10.5061/dryad.ksn02v7gp

Description of the data and file structure

This dataset accompanies our Science Advances manuscript investigating the aerosolization of wastewater-derived contaminants from the Tijuana River along the U.S.–Mexico border. It includes raw and processed data used to assess the spatial distribution and atmospheric transport of contaminants from coastal waters into the air. Files include: Data tables in .csv format of (1) calibration curve data, (2) mass spectral intensities and concentrations of field sample data, (3) concentration metadata, (4) air mass origin assignments, and (5) raw mass spectrometry data files that may be viewed or processed in mzmine or similar software packages available externally. These data support the spatial and chemical analyses presented in the manuscript and are intended to facilitate transparency, reproducibility, and further research...,

No description is available. Visit https://dataone.org/datasets/53350d217eaea3d70ea903646badb532 for complete metadata about this dataset.

The Canadian Environmental Sustainability Indicators (CESI) program provides data and information to track Canada's performance on key environmental sustainability issues. The Marine pollution spills indicator reports the volume of marine pollution spills detected from 2010 to 2017. The indicator also presents data with respect to known sources, including volume and detections per patrol hour of aircraft surveillance. The National Aerial Surveillance Program monitors ships transiting waters under Canadian jurisdiction. The indicator provides an understanding of how active surveillance impacts the occurrence of marine pollution spills. Spills come from ship operations, intentional dumping and accidents. Aerial surveillance is widely adopted worldwide and is considered to be the most effective method for detection of marine pollution spills. The presence of surveillance aircraft acts as a deterrent by discouraging illegal discharges of pollutants at sea. The information gathered is used to enforce the provisions of Canadian legislation applicable to illegal discharges from ships. Information is provided to Canadians in a number of formats including: static and interactive maps, charts and graphs, HTML and CSV data tables and downloadable reports. See the supplementary documentation for the data sources and details on how the data were collected and how the indicator was calculated. Supplemental Information Canadian Environmental Sustainability Indicators - Home page: https://www.canada.ca/environmental-indicators

IntroductionCoastal areas are considered potential sinks for plastic in marine environments. Data from a Lagrangian numerical simulation at a coastal scale using high-resolution hydrodynamic information and observational data of river debris discharge were analysed to determine the environmental variables from meteorological forcing or coastline orientation contributing to particle beaching.MethodA beaching likelihood parameter was developed to quantitatively measure the propensity for an area to receive or accumulate particles from a known outflow source. Statistical analyses of particle beaching were conducted to reveal possible relationships with hydrodynamic variables. A debris mass budget was calculated from the river release observational data used in the simulation.ResultsAreas close to the release points received the highest amounts of particles and also registered the highest beaching likelihood values. Significant wave height mildly affected particle beaching (Pearson’s r=0.36). Relative perpendicular wave directions promoted beaching in coastlines with lower azimuths (vertical orientation), whereas those with higher azimuths (horizontal orientation) were more affected by relative alongshore wave directions. The mass contribution from river discharge on beaches where cleanup data was available was 6.0% of the total debris collected.DiscussionThe beaching likelihood parameter revealed the influence of coastal geometry on particle deposition in an area. Comparisons with other studies regarding beaching amounts and particle residence times are challenging due to the scale difference. The complexity of the beaching process makes it difficult to establish relationships with hydrodynamic variables, although a clear association between the coastline orientation and wave direction was established. The debris mass contribution from the two rivers included in the simulation was two orders of magnitude lower than indicated in other studies for the area.

This is a table of all known citizen science projects that collect data on plastic pollution, how open their data is, their website, the region their data covers, and the system their data is in.

Russia Ocean: Tax Revenue: USD: Pollution data was reported at 0.000 USD mn in 2021. This stayed constant from the previous number of 0.000 USD mn for 2020. Russia Ocean: Tax Revenue: USD: Pollution data is updated yearly, averaging 0.000 USD mn from Dec 1994 (Median) to 2021, with 28 observations. The data reached an all-time high of 0.000 USD mn in 2021 and a record low of 0.000 USD mn in 2021. Russia Ocean: Tax Revenue: USD: Pollution data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Russian Federation – Table RU.OECD.ESG: Environmental: Environmentally Related Tax Revenue: Cross Cutting Domains: Non OECD Member: Annual.

The ASPeCt - Bio dataset is a compilation of currently available sea ice chlorophyll a (chl-a) data from pack ice (i.e., excluding fast ice) cores collected during 32 cruises to the Southern Ocean sea ice zone from 1983 to 2008 (Table S1). Data come from peer-reviewed publications, cruise reports, data repositories and direct contributions by field-research teams. During all cruises the chl-a concentration (in micrograms per litre) was measured from melted ice core sections, using standard procedures, e.g., by melting the ice at less than 5 degrees C in the dark; filtering samples onto glassfibre filters; and fluorometric analysis according to standard protocols [Holm-Hansen et al., 1965; Evans et al., 1987]. Ice samples were melted either directly or in filtered sea water, which does not yield significant differences in chl-a concentration [Dieckmann et al., 1998]. The dataset consists of 1300 geo-referenced ice cores, consisting of 8247 individual ice core sections, and including 990 vertical profiles with a minimum of three sections.

An updated dataset was provided in 2017-12-15, which included a compilation Net CDF file.

Plastic accounts for 80% of material waste in the ocean. The field of marine microplastic research is relatively new and is growing rapidly, in terms of published papers as well as institutions and countries conducting research. To combat plastic pollution, there is sufficient evidence that policies can lead to reduced plastic production and consumption both locally and globally. We aim to understand how marine plastics research and policies have grown and spread. Specifically, we used scientometric and spatial diffusion methods to best explain how ideas (in this case science and policy) clustered and spread geographically through time. We performed systematic literature searches to determine the spatial and temporal growth of marine microplastic publications and national plastic policies from 1900-2019. We found that more countries adopted national plastic policies than those that have conducted marine plastic research. Doubling times of each temporal growth rate analyzed (research paper, institution, country, and national policy) ranged from 1.1 – 4.05 years. Further, each temporal growth rate had a break point where doubling time changed significantly. Marine microplastic research has grown exponentially since 2006, and the topics of inquiry have increased steadily. Marine microplastic publication spread at the institution level is best explained by a hybrid of expansion and relocation diffusion while national plastic policy spread is best explained by expansion diffusion. Marine microplastic research activity was not a good indicator of a country’s resources or motivation toward national plastic policies.

Methods Marine plastic peer reviewed paper selection: Growth of marine microplastic (MP) publications was compared to other types of plastic research by performing a systematic literature search of peer-reviewed papers from Scopus, Elsevier’s abstract and citation database, in April 2020. The search used five sets of keywords: marine AND plastic*, marine AND “plastic bag*”, marine AND “single use plastic*,” marine AND microbead*, and marine AND microplastic*. The asterisk at the end of a word ensured both the singular and plural forms were considered. Within each of these sets of keywords the “analyze search results” feature was used in Scopus to record the quantity of papers published annually and cumulative number of papers published by country for 1900-2019. We note that many early papers studying mussel feeding physiology used poly-microbeads since the 1980s but were not included in any of the keyword searches. Papers were randomly spot-checked to ensure they fit within the keywords, if they did not, they were removed from our selection.

Metadata from marine MP papers were collected from a systematic literature search of peer-reviewed papers from Web of Science in April 2020. The search criteria used were the keywords marine AND microplastic* and all years (1900-2019), the same as the Scopus search. Publishing date, institution of lead author (including latitude and longitude), country of lead author, journal, and title were collected. Papers addressing non-marine MP topics (e.g. table salt or freshwater), highlights, commentary, news features, correspondences, opinion, and review papers were removed. Each marine MP paper was categorized based on focus topic: chemistry, environment, organism, policy, or review. If a paper studied multiple focus topics, only the predominate one was recorded. Organism papers were further categorized into functional groups: bacteria, fungus, invertebrate, small vertebrate, large vertebrate, macroalgae, phytoplankton, and zooplankton (includes fish larvae). If a paper studied multiple organisms, all were categorized by functional group and included.

National plastic policy selection: To evaluate plastic policy growth and diffusion, a systematic literature search for national plastic policies implemented through 2019 was conducted. Policy data was collected from Xanthos and Walker (2017), Schnurr et al. (2018), Lam et al. (2018), Plastic Policy Inventory from Duke’s Nicholas Institute for Environmental Policy Solutions (2020), and news articles from Wikipedia’s “phase-out of lightweight plastic bags” page (April 2020). Country, implementation year, type (plastic bag, microbead, single use plastic; SUP), and level (levy, ban) were recorded. All policies were cross-validated with an internet news search and policies that failed cross-validation were not included. Voluntary national plastic levies and bans were not included. Policies were evaluated at a national level, where countries with multiple levels or types of policies were only counted once in analyses.

United States Water Pollution: Tax Revenue: USD: Pollution data was reported at 1.205 USD bn in 2021. This records an increase from the previous number of 986.704 USD mn for 2020. United States Water Pollution: Tax Revenue: USD: Pollution data is updated yearly, averaging 686.191 USD mn from Dec 1994 (Median) to 2021, with 28 observations. The data reached an all-time high of 1.205 USD bn in 2021 and a record low of 254.866 USD mn in 1999. United States Water Pollution: Tax Revenue: USD: Pollution data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s United States – Table US.OECD.ESG: Environmental: Environmentally Related Tax Revenue: Environmental Protection Domains: OECD Member: Annual.

Summary of category 3 water pollution incidents reported to the Environment Agency are held on the National Incident Reporting System. Sum of incidents reported between 2001 and 2020 summarised by WFD Operational Catchment.Extracted from NIRS for Closed Category 3 and 4 Incidents classified as 3 and 4 in the Water Environmental Level code field from 01/01/2020 until date of extraction 20/05/2024. This data includes grid references for each incident. These Grid references were then used to map each Incident within ArcMap and analyse using the Spatial Join Tool how many incidents are located within each WFD Operational. Within the data tab shows a table of Counts of Category 3 and 4 Incidents within each WFD Operational Catchments from 01/01/2020 to data extraction date (20/05/2024).

The Reasons for Not Achieving Good Status (RNAGs) 2023 dataset provides insight into the activities and sectors responsible for preventing water bodies from achieving good ecological status, as defined by environmental regulations like the Water Framework Directive (WFD). It helps identify pressures affecting water quality and guides efforts to improve England’s rivers, lakes, and coastal waters. This dataset is obtained through DEFRA and is available on the Catchment Data Explorer: DEFRA RNAG Dataset About the Pivot Table The RNAG data has been analysed and presented in a pivot table for a clearer understanding of RNAGs by waterbody. Use the table to filter by: Operational Catchment, Waterbody, Reason for Not Achieving Good Status. The pivot table provides a count of RNAGs per waterbody, helping to better understand key environmental pressures in each stream, catchment, and waterbody. Key RNAG Categories (Based on 2022 River Basin Management Plans) Some of the most common factors preventing water bodies from reaching good status include: Physical Modifications – Dams, flood defences, and urban development alter water flow and habitats. Pollution from Agriculture & Rural Areas – Runoff from fertilizers, pesticides, and livestock waste contaminates rivers and groundwater. Pollution from Water Industry Wastewater – Sewage discharges, storm overflows, and outdated treatment plants introduce harmful contaminants. Invasive Non-Native Species (INNS) – Non-native plants and animals disrupt ecosystems and threaten native species. Urban & Transport Pollution – Heavy metals, hydrocarbons, and pollutants from roads, industry, and urban runoff degrade water quality. Changes to Water Levels & Flows – Over-abstraction for agriculture, industry, and domestic use depletes rivers and aquifers. Chemical Pollution – Toxic substances like PFAS, mercury, and pesticides pose risks to aquatic life and human health. Pollution from Abandoned Mines – Heavy metals and acidic drainage from old mining sites continue to contaminate rivers. Plastic Pollution – Macro- and microplastics enter waterways, impacting ecosystems and water quality. Why RNAG Data Matters By identifying the pressures and pollution sources affecting water bodies, RNAG data helps prioritize interventions and implement policies to restore and protect England’s water environments.

These data provide a snap shot of beach litter surveys submitted by Citizen Scientist ‘Monitoring Groups’ up to April, 2019. As defined by the United Nations Environment Programme (UNEP, 2009), marine litter is any persistent, manufactured or processed solid material discarded, disposed of, abandoned or lost in the marine and coastal environment. Marine litter washed onto beaches is one of the most obvious signs of marine pollution, and can have either land or sea-based origins. Land-based sources of marine litter include input from rivers, sewage and storm water outflows, tourism and recreation, illegal dumping, and waste disposal sites. Sea-based sources include commercial shipping, fisheries and aquaculture activities, recreational boating and offshore installations.

UNEP, 2009. Marine Litter: A Global Challenge. Nairobi: UNEP. 232 pp.

More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

Metadata record for data from ASAC Project 2794 See the link below for public details on this project.

Public: This study will use innovative technology to measure the winter spatial foraging patterns and net energy gain of adult female elephant seals (and potentially Weddell seals), while simultaneously providing high-resolution data on the physical nature of the water column in which the seals live. By combining biological and physical data with satellite derived sea-ice information, this study will improve our understanding of predator foraging success (and therefore mechanisms which regulate population trajectories) and provide physical oceanographers with fundamental data on the importance mechanisms that determine the winter ice and bottom water formation that under-pin the Antarctic marine ecosystem.

Project objectives: The extent and nature of Antarctic winter sea ice is thought to have profound impacts on biological productivity, the recruitment of Antarctic krill, and the flow-on effects through the Antarctic marine food web. 1. Winter sea-ice formation is also hypothesised to play an important, yet highly-variable role in ocean circulation patterns through the production of cold, dense winter bottom water. 2. The mechanisms determining the inter-annual variation in winter ice formation are poorly understood, as are the complex feedback processes involved, but they are nonetheless recognised as being vulnerable to human-induced climate change. 3. Given the dynamically-linked nature of winter-ice and biological productivity, long-term climatic changes will have broad scale influences on Antarctic biota.

This study will use innovative technological developments to quantify the response of one of the major Antarctic marine predators, the southern elephant seal (Mirounga leonina), to inter-annual variation in winter ice conditions. We will measure the winter spatial foraging patterns and net energy gain of adult female elephant seals while simultaneously providing high-resolution data on the physical nature of the water column in which the seals are living. The combination of these biological and physical data with satellite-derived sea-ice information will relate variation in the winter-ice to broad scale biological production through the foraging success (maternal investment and therefore demographic performance) of a top Antarctic marine predator, as well as providing physical oceanographers with fundamental data on the important mechanisms that determine the winter ice and bottom water formation that under-pin the Antarctic marine ecosystem. The specific objectives are to:

1. Measure the foraging performance of the seals in terms of spatially-specific net energy gain while at sea, in relation to intra- and inter-annual variation in sea-ice and oceanic processes.
2. Use newly-developed (and tested) animal-borne satellite-linked Conductivity-Temperature-Depth Satellite Relay Data Loggers (CTD-SRDLs) to provide oceanographic quality data on local physical characteristics (temperature and salinity).
3. Record fine-scale foraging parameters (dive depth, duration, swimming speed) using "Dead-Reckoning" Data Loggers (DRDLs) and feeding events using Stomach Temperature Sensors (STSs).
4. Integrate these data collected in years and regions of different winter ice extent and conditions.
5. Assess diet during the winter months using stable isotope and fatty acid signature analysis.
6. Combine the biological and physical information to refine current models of predator performance based on annual climatic features. These models will be used to examine a range of climate-change scenarios, initially for elephant seals but with a view to broadening the species application at a later stage.

Taken from the 2008-2009 Progress Report: Progress against objectives: Due to logistic constraints, no satellite telemetry was conducted at Casey or Macquarie Island this year, but preliminary surveys of the region were conducted for both elephant and Weddell seals (see report for 2753). However we did deploy CTD satellite tags on elephant seals at Isles Kerguelen and Elephant Island to contribute to the IPY MEOP program. These animals either traversed the Southern Ocean to forage over the Antarctic continental shelf, or remained very close to their breeding island, indicating that even within a population there are markedly different foraging strategies.

Taken from the 2010-2011 Progress Report: Public summary of the season progress: Due to pre-departure accident for one of the field team leaders we were unable to reach Casey this year to complete that component of the program. Forty CTD satellite tags were successfully deployed at Vestfold Hills in January and February 2011. These tags are currently still transmitting from foraging locations along the Antarctic continental shelf and the ice edge.

Project 2695 (ASAC_2695) was incorporated into this project.

An Access database containing data from this project is available for download at the provided URL.

The data have also been loaded into the Australian Antarctic Data Centre's ARGOS tracking database. The database can be accessed at the provided URLs.

United States Water Pollution: Tax Revenue: % of GDP: Pollution data was reported at 0.005 % in 2021. This records an increase from the previous number of 0.005 % for 2020. United States Water Pollution: Tax Revenue: % of GDP: Pollution data is updated yearly, averaging 0.004 % from Dec 1994 (Median) to 2021, with 28 observations. The data reached an all-time high of 0.006 % in 2010 and a record low of 0.002 % in 2005. United States Water Pollution: Tax Revenue: % of GDP: Pollution data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s United States – Table US.OECD.ESG: Environmental: Environmentally Related Tax Revenue: Environmental Protection Domains: OECD Member: Annual.

Mexico Water Pollution: Tax Revenue: % of GDP: Pollution data was reported at 0.002 % in 2022. This records a decrease from the previous number of 0.003 % for 2021. Mexico Water Pollution: Tax Revenue: % of GDP: Pollution data is updated yearly, averaging 0.000 % from Dec 1994 (Median) to 2022, with 29 observations. The data reached an all-time high of 0.003 % in 2015 and a record low of 0.000 % in 2013. Mexico Water Pollution: Tax Revenue: % of GDP: Pollution data remains active status in CEIC and is reported by Organisation for Economic Co-operation and Development. The data is categorized under Global Database’s Mexico – Table MX.OECD.ESG: Environmental: Environmentally Related Tax Revenue: Environmental Protection Domains: OECD Member: Annual.