This packages combines data collected as part of an MSc. Thesis Project and an MSc. Semester Project conducted in Durban, South Africa. The projects were supported by the Global Health Engineering group at ETH Zurich, Switzerland.
You can install the development version of durbanplasticwaste from GitHub with:
# install.packages("devtools")
devtools::install_github("Global-Health-Engineering/durbanplasticwaste")Alternatively, you can download the individual datasets as a CSV or XLSX file from the table below.
| dataset | CSV | XLSX |
|---|---|---|
| litterboom_counts | Download CSV | Download XLSX |
| litterboom_weights | Download CSV | Download XLSX |
| locations | Download CSV | Download XLSX |
Evaluating the potential of Extended Producer Responsibility returns for a small local waste collection company through a brand audit of riverine plastic waste in Durban, South Africa.
This Master’s Thesis Project focuses on determining the growth opportunities for a small-sized plastic recycling enterprise in light of the shift from a voluntary to a mandatory Extended Producer Responsibility (EPR) policy in South Africa.
To achieve this goal in the context of a small start-up in Durban, South Africa , a brand audit is conducted to identify the top brands that can be targeted for financing or partnership opportunities. The company, called TRI ECO Tours, is a small tourism and waste collection startup in Durban operated by Siphiwe Rakgabale.
What is the characterization by type, application, and brand of plastic waste collected in the uMngeni River system in Durban, South Africa?
The data was collected throughout two months in Durban, South Africa right before the rainy season. The collection took place in 6 different litterboom locations throughout Durban. The data gathered was the audit of the occurence of the brands washed into the litterbooms.
The package provides access to three data sets.
library(durbanplasticwaste)The litterboom_counts data set has 7 variables and 2784 observations.
For an overview of the variable names, see the following table.
litterboom_counts| variable_name | variable_type | description |
|---|---|---|
| date | date | Date of the collected litterboom sample. |
| location | character | Descriptive name of the sample location. See [locations] for longitude and latitude. |
| brand | character | Brand name of the collected item (e.g. Coca Cola). |
| group | character | Group name that owns the brand (e.g. Coca Cola Beverages South Africa). |
| plastic | character | Type of plastic of the item. Identified plastic types are PET, HDPE, and PP. HDPE and PP were categorised together as HDPE/PP. |
| category | character | Categorisation of waste into 15 product type categories (e.g. Alcohol, Milk, Tobacco, Water). |
| count | numeric | Number of counted items. |
The litterboom_weights data set has 4 variables and 14 observations.
For an overview of the variable names, see the following table.
| variable_name | variable_type | description |
|---|---|---|
| date | date | Date of the collected litterboom sample. |
| location | character | Descriptive name of the sample location. |
| pet | numeric | Weight (in kg) of PET items. |
| hpde_pp | numeric | Weight (in kg) of PET items. |
The locations data set has 3 variables and 6 observations. For an
overview of the variable names, see the following table.
| variable_name | variable_type | description |
|---|---|---|
| location | Descriptive name of the sample location. | NA |
| latitude | Latitude coordinate. | NA |
| longitude | Longitude coordinate. | NA |
Locations data as a map illustrating the six litterboom sampling
locations in Durban, South Africa. For an interactive map and other code
examples, see vignette("examples").
Examination of non-recycled marine plastic litter in order to identify recycling and beneficiation pathways in Durban, South Africa
This Semester Thesis Project focuses on determining the distribution of plastic litter on the Durban beachfront in order to identify key targets for policy and financial support through the South African EPR policy to reduce plastic spills into the environment and promote higher recycling rates. Research Question
What types and amounts of plastic are found along the beachfront in the mangroves of Durban-North, South Africa?
The litterboom_counts data identifies 40 unique groups that own the
identified brands. The top 10 brands are shown in the following table.
All other brands are lumped together as OTHER.
library(durbanplasticwaste)
library(dplyr)
library(forcats)
litterboom_counts |>
mutate(group = factor(group)) |>
mutate(group = fct_lump(group, n = 10, other_level = "OTHER")) |>
group_by(group) |>
summarise(
count = sum(count)
) |>
arrange(desc(count)) |>
mutate(percent = count / sum(count) * 100) |>
knitr::kable(digits = 0)| group | count | percent |
|---|---|---|
| OTHER | 8086 | 52 |
| Coca Cola Beverages South Africa | 4030 | 26 |
| unidentifiable | 1202 | 8 |
| Clover Industries LTD | 737 | 5 |
| Unilever | 442 | 3 |
| Tiger Brands | 232 | 2 |
| danone | 183 | 1 |
| Siqolo Foods | 144 | 1 |
| Willowton Group | 139 | 1 |
| Amka Products | 132 | 1 |
| RCL Foods | 95 | 1 |
Data are available as CC-BY.