This data resource contains information on anthropogenic litter from the Portoviejo River, in Ecuador, collected between years 2021 and 2022. This work is part of the Natural Environment Research Council project “Reducing the impacts of plastic waste in the Eastern Pacific Ocean” (NE/V005448/1). The purpose of collecting this dataset was to obtain consistent observational data of solid waste contamination in a South American river system using a newly developed clean-up technology called the Azure System. The dataset contains information of weight (in kilograms) of different categories of anthropogenic litter collected using the Azure System, a floating barrier designed as a litter extraction tool for rivers. The system was developed by Ichthion Limited (https://ichthion.com/), who were also responsible for data collection on site. The barrier was installed at the city of Portoviejo, where litter was collected from February 2021 until December 2022 and quantities were reported weekly for each month. Full details about this dataset can be found at https://doi.org/10.5285/e78e1cef-e30b-4313-8733-c03e1a7b7b2f

Here are a few use cases for this project:

1. Smart Waste Segregation: The "Waste" model can be deployed in waste management systems to facilitate automated sorting and segregation of waste into different categories. This technology could be particularly useful for recycling facilities to increase their efficiency.

2. Educational Tools: The model could be used to develop educational software or applications to teach about waste types and importance of recycling. Through the visualization of different waste types, users can learn how to properly sort waste in their daily lives.

3. Environment Impact Studies: Environmental researchers or NGOs can use this model to analyse and quantify waste in different environments, like cities, forests, or rivers, and quantify the types of human-derived waste polluting these areas.

4. Smart Trash Cans: The model could be incorporated in smart trash cans or bins to analyze what kind of waste is being thrown away, helping to better understand waste patterns in specific neighborhoods or cities, and to enforce proper disposal of recyclable materials.

5. Industrial Waste Management: Industries producing large amounts of waste could apply this model to monitor and manage their waste production, ensuring appropriate disposal and tracking of waste materials.

Here are a few use cases for this project:

1. Environmental Cleanup: Utilize Garbage_ydieh to identify and locate various types of garbage in public spaces like parks, beaches, and rivers to facilitate efficient cleanup efforts by volunteers or waste management teams.

2. Automated Waste Sorting: Implement Garbage_ydieh in recycling and waste management plants to automatically sort different types of garbage, improving waste processing efficiency and promoting proper recycling practices.

3. Marine Life Conservation: Employ Garbage_ydieh to monitor coastal areas, shorelines or fishing locations to detect and remove discarded fishing nets and plastic waste, ultimately aiding in the protection of marine ecosystems and wildlife.

4. Smart Trash Bins: Integrate Garbage_ydieh into smart trash bin systems installed in cities or residential communities to identify and sort waste items into appropriate compartments, enhancing recycling efficiency and reducing improper disposal.

5. Awareness and Education Campaigns: Use Garbage_ydieh to analyze large sets of images/videos from social media, online platforms, or urban spaces to determine the prevalence and distribution of garbage classes, informing targeted awareness campaigns, and driving data-driven policy-making.

The Environmental Department releases river water quality monitoring data, including River Pollution Index (RPI) and monitored values of major pollutants. Due to the need for monthly on-site sampling, laboratory testing and data quality control procedures, monitoring data is usually provided every other month.

Significant pressures have been identified for waterbodies that are At Risk of not meeting their water quality objectives under the Water Framework Directive. While there are a multitude of pressures in every waterbody, the significant pressures are those pressures which need to be addressed in order to improve water quality. Many of our waterbodies have multiple significant pressures. A robust scientific assessment process has been carried out to determine which pressures are the significant pressures. This has incorporated over 140 datasets, a suite of modelling tools, and local knowledge from field and enforcement staff from the Local Authorities, Inland Fisheries Ireland and EPA. Impacts from domestic waste water include nutrient and organic pollution. This assessment synthesises over a decade of field studies on on-site systems in Ireland across many different soils types and combines factors relating to the efficiency of the septic tank systems with attenuation factors for the hydrogeological flow pathway.

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).

This form is based on a standardised approach to monitoring litter in the environment, developed as part of the Preventing Plastic Pollution initiative. It's important to understand the origin of the plastics in the sea in order to effectively target the sources that release them. Globally, we lack a baseline of the extent of plastic pollution and where that pollution is coming from, making management of the problem piecemeal and costly. As plastic is an emerging pollutant, standardised methods to identify and quantify the types and amounts of plastic in the environment have yet to be established, particularly for rivers. In order to fill this gap the Preventing Plastic Pollution initiative has adapted the OSPAR Commission's methodology for monitoring marine litter on beaches and applied the same approach of identifying and categorising litter to land, rivers and streams. By adopting these pre-defined categories, the data collected by volunteers within the river catchment will be directly comparable to the data that is already being collected on beaches. This uniform way of monitoring will allow us to analyse the data and identify potential sources and pathways from land to sea. We can use this information to focus on developing and delivering effective mitigation measures, as well as assessing the effectiveness of existing legislation and regulations.We're calling on voluntary groups to help us gather detailed information on the types and amounts of plastic waste using this standardised methodology. The data will be assessed and sources of plastic pollution identified by both location and sector. This will be invaluable in helping to plan and deliver effective interventions to prevent plastic pollution from entering our rivers and seas.The Preventing Plastic Pollution initiative is supported by the Interreg France (Channel) England programme, funded by the European Regional Development Fund.

This dataset only includes substantiated completed and closed Environment Management incidents (predominantly pollution), where the environment impact level is either category 1 (major) or category 2 (significant) to at least 1 media (i.e. water, land or air). It is updated quarterly and provides a snapshot of data held in NIRS2. There is an inherent lag time in investigating and recording the necessary incident details to complete a record and recent incidents may not appear. The data may also be subject to change due to final QA and as further information becomes available. INFORMATION WARNING: Where these data indicate an incident occurred on a particular site or property no inference should be drawn that the site or property owner necessarily was responsible.

ABSTRACT This work had the objective to identify the suitability of the Almada River Watershed (ARW) front of the deployment areas for waste disposal from the recognition of physical environment and land use occupation characteristics. The methodology had initially its activities associated with the survey of environmental studies and consolidation of thematic maps already made in the ARW area. Then the plans of thematic information, like bedrock, soils and landforms, had its features framed in suitability classes to the implementation of waste disposal in accordance with the proposal of Zuquette. The results attested to the scenario in which the area of ARW has a higher concentration of severe and restrictive suitability located in the west, north and east portions, due to the extensive occurrence of permanent preservation areas in upper 45º slope areas and top portions of hills, associated with the presence of dense forest.

This dataset represents habitat measurements and fish sampling (https://data.kingcounty.gov/Environment-Waste-Management/Fish-data-for-Juvenile-Pacific-salmonid-habitat-us/hznk-dan4) from the Snoqualmie and Green rivers in the Puget Sound region of Washington State, USA. Using a cataraft mounted with a boat electrofisher, these data were collected between late winter and late spring from 2016 through 2022. Measurements were of 25-m-long transects along six different edge habitat types in the two rivers. The edge habitats represented in this dataset are ‘armored banks’, ‘biorevetment banks’, ‘unarmored banks’, ‘bars’, ‘backwaters’, and ‘side channels’. These data were collected as part of monitoring of eight habitat restoration or bioengineered bank stabilization projects in the Snoqualmie and Green rivers, along with three more general studies of fish-habitat relationships in the two rivers. These data are analyzed and presented in the journal article “Juvenile Pacific salmonid habitat use in two Puget Sound lowland Rivers”, published in the Transactions of the American Fisheries Society (https://afspubs.onlinelibrary.wiley.com/doi/10.1002/tafs.10457). All data were collected by the King County Water and Land Resources Division, Science and Technical Support Section. Habitat data were collected during the day and include measurements of the width of low-velocity habitat (≤ 0.45m/s) and water depth along each transect. Fish sampling occurred after darkness fell the evening following habitat data collection. Fish data include the number of each species sampled at each transect and the number of seconds each transect was electrofished. For additional details on the data and collection methods, please see the associated journal article or contact the article authors: Aaron David (adavid@kingcounty.gov), Christopher Gregersen (chris.gregersen@kingcounty.gov), Joshua Kubo (josh.kubo@kingcounty.gov), Daniel Lantz (dan.lantz@kingcounty.gov), and James Bower (james.bower@kingcounty.gov).

Layer created from Excel spreadsheet provided by the Environment Agency. The spreadsheet data was then joined to a merged shapefile of river, coastal and transitional waterbodies.

The Preventing Plastic Pollution initiative has co-developed a standardised approach for surveying litter in rivers and streams. Our aim is to pilot this methodology across 7 catchment areas in England and France.We're calling on voluntary groups to help us gather detailed information on the types and amounts of plastic waste in the river catchment. The data will be assessed and sources of plastic pollution identified by both location and sector. This will be invaluable in helping to plan and deliver effective interventions to prevent plastic pollution from entering our rivers and seas.As plastic is an emerging pollutant, standardised methods to identify and quantify the types and amounts of plastic in the environment have yet to be established, particularly for rivers. In order to fill this existing resource gap, we have adapted the OSPAR Commission's methodology for monitoring marine litter on beaches and applied the same approach of identifying and categorising litter to river catchments.

This database is the supplementary material for the scientific paper in preparation: Catchment scale assessment of macroplastic pollution in the Odaw river, Ghana. The database contains the field data of monitored and sampled litter (macroplastics and non plastics) in the river, on land, and at the riverbank at ten locations within the study area over the sampling period ( between 11-23 December, 2021). Since the

counted macroplastic items were categorised into the aggregated macroplastic polymer types, the file also contains the categorisation of the detailed items (River Ospar list ) into the macroplastic polymer types.

This dataset contains 2 csv files. The file Belize_Marine_Litter_Data.csv contains data on litter found on marine beaches, river banks and along city canals in Belize between May and June 2019. The number of items and the weight in kg is reported for each litter category. The list of litter categories was obtain merging OSPAR and Tangaroa Blue protocols with the addition of region-specific items. Item categories marked with '*' were added during the operations in South Pacific, while item categories marked with '**' were added during the operations in Belize. An array of metadata (location names, survey date, GPS coordinates in decimal degrees) is also reported per each data point.

The file Belize_Marine_Litter_Metadata.csv reports other metadata collected during the surveys following the OSPAR protocol to describe factors potentially influencing litter characteristics. A READ-ME text file contains a legend of the columns of the csv files.

This record is for Approval for Access product AfA162.1 'Historic GQA Headline Indicators of Water Courses - Chemistry - GQAHI (England)'. The General Quality Assessment (GQA) Headline Indicator scheme or GQAHI (previously known as GQA) was the Environment Agency's national indicator for water quality in rivers and canals. It was designed to provide an accurate and consistent assessment of the state of water quality and how it changed over time as a national picture. These assessments were made for Biological, Chemical and Nutrients and undertaken for discrete river stretches. The Chemistry GQAHI scheme had over 3000 sampling sites which provided information for approximately 22500 km of watercourses. In Wales we maintained the full GQA network until 2010 based on 800 sampling sites which provided information for approximately 4700km. Chemistry GQAHI/GQA sites were sampled twelve times a year, the samples being taken at the same spot on each sampling occasion to ensure consistency. In England each chemical sample was measured for ammonia and dissolved oxygen. In Wales each chemical sample was measured for biochemical oxygen demand (BOD), ammonia and dissolved oxygen (the most common types of organic pollution from sewage treatment works, agriculture and industry). A category was assigned using three years worth of samples for each sampled chemical and assigned a category assessed against chemical standards expressed as percentiles The data collected over three years were used to determine average nutrient concentrations. So the classification for the year 2008 includes the results for 2006 and 2007. Subsequently a category was assigned to each length of river according to the lowest standard achieved by any of the two or three measurements. The Chemistry GQA used in Wales described quality in terms of three chemical measurements that detect the most common types of organic pollution from sewage treatment works, agriculture and industry. The chemistry GQAHI scheme used in England used the same methods however the biochemical oxygen demand (BOD) component of the assessment had been removed.Grades of river quality for the chemical GQA, Chemical grade Likely uses and characteristics* A: Very good, All abstractions, Very good Salmonid fisheries, Cyprinid fisheries, Natural ecosystems. B: Good, All abstractions, Salmonid fisheries, Cyprinid fisheries, Ecosystems at or close to natural. C: Fairly good, Potable supply after advanced treatment, Other abstractions, Good Cyprinid fisheries, Natural ecosystems, or those corresponding to good Cyprinid fisheries D: Fair, Potable supply after advanced treatment, Other abstractions, Fair Cyprinid fisheries, Impacted ecosystems. E: Poor Low grade abstraction for industry, Fish absent or sporadically present, vulnerable to pollution**, Impoverished ecosystems** F: Bad, Very polluted rivers which may cause nuisance, Severely restricted ecosystems *Provided other standards are met **Where the grade is caused by discharges of organic pollution. 2009 is the final year of the scheme. In 2007 the England GQA river network was reduced to the GQAHI river network. The assessment was changed to be based on total ammonia and dissolved oxygen only. Biochemical oxygen demand (BOD) was removed from the assessment and all past grades re-calculated. The data described have been amended to be consistent and comparable for all years. Attribution statement: © Environment Agency copyright and/or database right 2015. All rights reserved.

According to Article 23 of the Water Environment Conservation Act and Article 32 of the Enforcement Decree of the same Act, this is data that the National Institute of Environmental Research has confirmed by comparing and reviewing with statistical data, etc., based on data submitted by 17 metropolitan and basic local governments (230) across the country every year. The survey items are 8 categories: living, livestock, industry, land (Ministry of Land, Infrastructure and Transport data), aquaculture, landfill, environmental infrastructure, and other water quality pollution sources, and statistical data is provided for each pollution source by the four major river basins (Han River, Nakdong River, Geum River, Yeongsan River).

Macroplastic pollution (> 0.5 cm) negatively impacts aquatic life and threatens human livelihood on land, in oceans and river systems. Reliable information on the origin, fate and pathways of plastic in river systems is required to optimize prevention, mitigation and reduction strategies. Yet, accurate and long-term data on plastic transport are still lacking. Current macroplastic monitoring strategies involve labor intensive sampling methods, require investment in infrastructure, and are therefore infrequent. Crowd-based observations of riverine macroplastic pollution may potentially provide frequent cost-effective data collection over a large geographical range. We extended the CrowdWater citizen science app for hydrological observations with a module for observations of plastic in rivers. In this paper, we demonstrate the potential of crowd-based observations of floating macroplastic and macroplastic on riverbanks. We analyzed data from two case studies: (1) floating plastic measured in the Klang (Malaysia), and (2) plastic on riverbanks along the Rhine (the Netherlands). Crowd-based observations of floating plastic in the Klang yield similar estimates of plastic transport (2,000–3,000 items h−1), cross-sectional distribution (3–7 percent point difference) and polymer categories (0–6 percent point difference) as reference observations. It also highlighted the high temporal variation in riverine plastic transport. The riverbank observations provided the first data of macroplastic pollution on the most downstream stretch of the Rhine, revealing peaks close to urban areas and an increasing plastic density toward the river mouth. The mean riverbank density estimates are also similar for the crowd-based and reference methods (573–1,033 items km−1). These results highlight the value of including crowd-based riverine macroplastic observations in future monitoring strategies. Crowd-based observations may provide reliable estimations of plastic transport, density, spatiotemporal variation and composition for a larger number of locations than conventional methods.

The Tijuana river estuary suffers from overwhelming solid-waste contamination such as marine bound plastics, tires, and sediment. Funded by the US EPA's Border 2020 program (SOLTA-C-19-008), this project intends to establish a framework for bi-national monitoring of trans-boundary, marine bound trash (TBMBT) using light-weight unmanned aerial systems (UASs), also known as drones. The developed framework is intended to benefit 1) border authorities through the establishment of a low-cost, minimally invasive, operational standard to monitor TBMBT in coastal ecosystems and optimize upstream trash capture interventions, 2) natural habitat in the Tijuana River Valley (TRV) and TRE through the identification of trash hotspots to guide clean-up operations, and 3) visitors and residents of the TRV and TRE through the long term benefits of reduced trash volumes from optimized interventions. Three surveys were carried out between 2020 and 2021 collecting data on trash locations using drones and ground-based smartphones. Drone imagery was processed to extract locations of trash using image classification algorithms, while ground-based data was used to complement the data collected from drones and to validate the accuracy of the drone generated data.

Survey data collected by citizen scientists using the Preventing Plastic Pollution methodology for assessing litter. This is a simplified version of the OSPAR Commission's methodology for monitoring marine litter on beaches. By adopting these pre-defined categories, the data collected by volunteers within the river catchment will be directly comparable to the data that is already being collected on beaches. This uniform way of monitoring will allow us to analyse the data and identify potential sources and pathways from land to sea. We can use this information to focus on developing and delivering effective mitigation measures, as well as assessing the effectiveness of existing legislation and regulations.The Preventing Plastic Pollution initiative is supported by the Interreg France (Channel) England programme, funded by the European Regional Development Fund.

Significant pressures have been identified for waterbodies that are At Risk of not meeting their water quality objectives under the Water Framework Directive. While there are a multitude of pressures in every waterbody, the significant pressures are those pressures which need to be addressed in order to improve water quality. Many of our waterbodies have multiple significant pressures. A robust scientific assessment process has been carried out to determine which pressures are the significant pressures. This has incorporated over 140 datasets, a suite of modelling tools, and local knowledge from field and enforcement staff from the Local Authorities, Inland Fisheries Ireland and EPA. Impacts from domestic waste water include nutrient and organic pollution. This assessment synthesises over a decade of field studies on-site systems in Ireland across many different Soils types and combines factors relating to the efficiency of the Septic tank systems with attenuation factors for the hydrogeological flow Pathway.