Plastic

This following section will present and explain estimations for quantity, type, and price of plastic. The estimations are presented in tables, with the following description of findings, and potential for improvement.

6.2.1. Quantity

There is a lack of data on plastic quantities in Brasilia. Because of this, an estimation using assumptions from universal models were created. The uncertainty in input numbers used and expected mean variance from correlation with the water cycle, three levels of estimations was created.

Estimation quantity Level of

quantity Population Generation rate (Kg/capita/day)

Table 2: Estimation of mismanaged plastic ton/year.

Source: Self-generated table (data from various sources)

Mismanaged plastic in this definition is everything that is not recycled properly. All storage of plastic in other garbage zones will be counted as mismanaged. The value is an expected value based on the cumulative probability distribution taken from (Hoornweg & Bhada-Tata, 2012). It is an estimated value but will not be referred to that later on in the text. We will assume the estimated value is the real value. Since we are only concerned with the plastic that ends up in the water a cumulative probability distribution of 𝑀_𝑀𝑃𝑊 is made and the quantity that leaks into the aquatic environment 𝑀_𝐴𝑃𝑊 is gathered from this.

𝑀_𝐴𝑃𝑊 ∼ 𝑀_𝑀𝑃𝑊

Table 3: Probability distribution of mismanaged plastic in tons

Source: Self-generated table, distribution % data from (Hoornweg & Bhada-Tata, 2012)

The potential waste disposal and treatment in Brasilia is defined in the following figure based on the percentage of usage in 2018. The estimation methodology is a universal model based on GDP. There is there for potential large variance between estimation and actual data. I.e.

large variance between the regression line and residual. Since no trustworthy data could be acquired from the city of Brasilia, we will use the estimated value stemming from Brazil being classified as an upper-middle-income country (Hoornweg & Bhada-Tata, 2012). The estimations operate with both a dump and landfills. As mentioned earlier (6.1) there are potential leaks from disposals. Brasilia as a city has recently moved over from dump disposal

Cumulative distribution of place

Distribution Percentage Minimum Expected Maximum

Landfill 91.3% 13568.67615 26534.30002 45731.46406

Compost 1.0% 142.1885055 278.0575218 479.2279259

Recycled 1.4% 207.8596856 406.481163 700.5641257

Incineration 0.1% 19.76078498 38.64331286 66.6011642 Lake Paranoá 6.2% 919.0993677 1797.349875 3097.705276

the high risk of contamination to the lake. Since it is no longer operational, we assume that potential leaks of plastic have already happened and are not something we expect is leaking in large quantities anymore. The new landfill in Brasilia is at a distance and placement that it is not connected to the river basin of Lake Paranoá. Level of mismanaged plastic going into dumps, can be assumed placed at landfills instead. We thus assume a zero leak from landfill and dumpsite into Lake Paranoá. This means that the estimation for "other" disposals is what is set to enter the lake each year. Improvements to this estimation could be made by taking the drainage basin into account. A better monitoring system of the plastic flow or data gathering from the lake would also improve the estimation.

By looking into possible extraction methods (6.3) it became evident that most methods are limited to top-side extraction. The estimated value of plastic entering thus requires a vertical distribution. Again, there is a lack of available data, and standardized monitoring or testing.

The most reliable source we found was for micro-plastic (Erni-Cassola, Zadjelovic, Gibson,

& Christie-Oleza, 2019), as this is the most studied field. We acknowledge that the use of micro-plastic distribution has faults. The ability to float for a piece of plastic will depend on more than just its density. The form of the piece surface and possible containment of air will change buoyancy. Due to the lack of data, the spatial distribution in water for plastic have been omitted. The estimation shows the estimated levels of plastic input to Lake Paranoá.

Since we have little information of input areas, and river behaviour a spatial distribution of the plastic has not been done. A further investigation into input zones should be done, to find most impactful areas of recovery. This could be done by creating a cumulative distribution chart with kilometres of the lake (circumference) on the x-axis, and the cumulative

probability on the y-axis.

6.2.2. Type of plastic

The Weight distribution has been simplified to concern the 4 most typical plastic types. PE contains both LDPE LLDPE and HDPE. It has not been vertically distributed, as there is not enough information to perform such a distribution with confidence. We recommend more thorough research of spatial macro-plastic distribution, with a standardized approach. Plastic type will affect end value, we have thus weighted the sales price of plastic with the type distribution.

Type distribution

Table 4: Type distribution of Plastic

Source: Self-generated table (data from various sources)

6.2.3. Price

There is a limited market for waste plastic. The prices acquired had little information about quality and state. We obtained three prices of waste plastic to show the value at different stages of the value chain. For further description of the prices, go to the methodology section (5.3.1)

Prices

Recycling markets EU Kunststoff

€

Table 5: Waste plastic price at different processing stages Source: Self-generated table (Data from various sources)