Title of dataset: Mismanaged plastic waste as a predictor for plastic pollution along the Odaw river

Creators: Rose Boahemaa Pinto, Tim H.M. van Emmerik, Kwame Duah, Martine van der Ploeg, Remko Uijlenhoet


Related Publication: Mismanaged plastic waste as a predictor for plastic pollution along the Odaw river

	Description: 
Here we present a one year field monitoring data of macroplastic transport and density between December 2021-December 2022 in the Odaw catchment, Accra, Ghana at three different environmental compartments (land, riverbank, and river) 
at different spatial points along the catchment. This was done to examine the seasonal differences in macroplastic transport and density as well as investigate the drivers of plastic transport variations in this catchment. 
In view of that, we examined the influences of both anthropigenic (mismanaged plastic waste and population density) and hydrometeorological (rain, discharge and windspeed) variables on these variations using spatial correlation 
and multiple regression analysis. Additionally, we assessed correlations of plastic transport peaks with discharge, windspeed, and rainfall peaks, defined with the 90th percentile of a distribution as threshold. 

	Study variables and their acquisition description of:
  
	I. Floating macroplastics:

We monitored the floating plastic and other non-plastic litter in the river using the visual counting approach. This method involved the counting of floating litter (macroplastics and non-plastics) from bridges.
Ten bridge locations based on safety and accessibility along the Odaw river were selected for monitoring. Each bridge was sectioned into monitoring waypoints depending on the width of the bridge,
the amount of litter (macroplastics and non plastics) floating at that bridge, and the field view of an observer.
Three waypoints were identified for six bridges, two waypoints for three bridges and one waypoint for only one bridge. 

At each bridge waypoint, floating macroplastics were monitored four times at a 2 minute timestep. Counted non-plastics were also segregated into rubber, textile, paper, wood, metal, glass, sanitary, and medical.
Overall time spent in monitoring at each bridge was 30 minutes.

	II. Land and riverbank monitoring:

A  5 by 2 m2 area was indicated as the standard survey area for each land and riverbank location in the catchment. 
However, due to insanitary and unsafe conditions at some locations, limiting the accessibility for sampling, the surveyed area varied.
Sampled litter within a survey area at either land or riverbank was collected, counted, and categorised according to the River-OSPAR list. 
This River-OSPAR list allows for the detailed categorisation of 110 litter items.

Some litter items were added (water sachet, glue small bottle, pieces of rubber carpet, electronics, ceramics, and  facemask) or removed (nurdles) from the Ospar list to fit the mismanaged litter found in the catchment during field work.

	III. Anthropogenic  variables:
Population density and Mismanaged plastic waste were the anthropogenic variables collected for this study. Both were obtained from global models. Population density was acquired online as population counts from the LandScan Global 2022 model
with a high resolution (approximately 1 km2) distribution of long-term projections of population. Since the resolution is 1 km2, the acquired population counts were considered as population density for subsequent analysis. 
Mismanaged plastic waste data were derived from the global MPW projections at approximately 1 km2 resolution using the model by Lebreton & Andrady (2019). This model is based on country-level data on waste management, 
gross domestic product (GDP) per country and high-resolution long-term population projections.

	IV.Hydro- meteorological variables
In this study, two meteorological (rainfall and windspeed) variables and one hydrological (discharge) variable were quantified. Rainfall data was accessible through the TAHMO website upon login. 
This data was obtained from 11 rain gauges installed in the catchment all equipped with ATMOS 41 Sensors electronic drop-counting gauges. Since some of the raingauges were defunct during the study period,
data from raingauges TA00391, TA00651, TAOO127, and TA00127 were used for the later analysis.

Windspeed data was accessible on the Meteostat platform, an open source global climate data provider. 
Both rainfall and windspeed variables were collected between December 2021 and December 2022. Rainfall is recorded in mm and windspeed in m/s.

Discharge was estimated from the field collected velocity and water level measurements using the velocity-area method.
At each section of a monitored bridge, velocity, water level, and bridge width were measured. Velocity was measured using the flow watch meter (JDC Electronic SA, Yverdon-les-Bains, Switzerland), 
and water level was determined using a marked wooden rod. Velocity and water level measurements were taken four times at each section concurrently with the visual counting of plastics
Since velocity at each section was measured at a specific depth, a default velocity index factor of 0.85 was applied to the measured velocities to relate the velocity over the entire depth of the river. 
Discharge data for this study is available only for the period between July and December 2022, since this was the period the flow meter was available for field work.


Note for this study, only macroplastic data was analysed though we monitored and sampled non plastics.


Keywords: seasonality, peak plastic transport, catchment, specific plastic item, anthropogenic impact


This dataset contains 
an excel file named "Odaw_fielddata.xlsx" which contains
        - coordinates for all sampling locations (Sheet 1: Sampling_location_coordinates), 
        - data on the floating macroplastics, non plastic litter, velocity, and water level (Sheet 2: River_monitoring),
        - data on the riverbank and land sampled litter (macroplastics and non plastic) (Sheet 3: Riverbank_and_land_sampling),
	- Meta data on the raingauges in the catchment (Sheet 4: Raingauges_metadata),
        - Rainfall data (Sheet 5: Rainfall),
	- Windspeed data (Sheet 6: Windspeed)
       
This dataset is published under the CC BY (Attribution) license. This license allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator.
