Hello, dear friend, you can consult us at any time if you have any questions, add WeChat: daixieit

SCIE1000 Semester Two, 2022

Python and Communication Assignment

The scenario

A new public science museum in St Lucia is developing an exhibit. A feature of the museum is that each exhibit item is accompanied by two explanations, each written for a different audience. One explanation is pitched to the “science rookie” and the other to the “science enthusiast”. Patrons read the explanation tailored to the level at which they feel most comfortable. Some characteristics of a typical audience member in each category are described in Table 1.

Patron Type

Typical characteristics

Science Rookie

Not familiar with scientific terminology or notation;

will need terminology explained using a simple vocabulary; is unfamiliar with graphs;

may be a younger person, possibly 10+ years of age;

likes to press buttons.

Science Enthusiast

Familiar with common scientific terminology and notation (not overly technical);

can handle terminology explained using somewhat sophisticated vocabulary; is prepared to read longer passages of moderate complexity;

likes to know about modelling assumptions and limitations; is familiar with graphs;

likes to press buttons.

Table 1: Characteristics of different patrons

The museum is planning an exhibition called “Plastics: A Cautionary Tale” which examines how humankind’s voracious appetite for the production and consumption of plastic products can have calamitous consequences for the natural environment around us. The aim of the exhibition is sum- marised in the following passage from the exhibition prospectus:

Plastics have revolutionised the cost-effectiveness and versatility of manufacturing in the post-war era. Plastics have become so commonplace in modern times that it is hard to imagine life without them. However, as plastic  consumption  has  increased,  so  too  has our knowledge and understanding of the potentially devastating impacts of mismanaged plastic waste. As we plan for a more sustainable future, we must examine our dependency on plastics and the consequences of inaction on the future health and prosperity of the planet.

In this particular exhibit patrons will gain a sense of scale for the rate at which plastic products are produced, and explore potential interactions between plastics and the marine environment, both now, and in the future.

The museum director has asked the SCIE1000 teaching team for help in finding skilled volunteers to develop exhibit items. Once developed, the items will be maintained and potentially modified by museum staff, each of whom has a strong background in high-school mathematics combined with a beginners level of Python experience. The director has been informed that SCIE1000 students are skilled at: making mathematical models using a mathematical toolkit familiar to any student of Mathematical Methods (aka Maths B, or equivalent); writing Python programs, including those which use arrays, loops, plots and new functions; and communicating scientific information to various audiences.

An overview of the task

You will write an interactive Python program that will run on a machine in the exhibition hall at the new science museum as part of this exhibition. Your program will guide users to a better under- standing of the scale of plastic production and the impact this may have on marine environments. The information you need to create the relevant models is provided in Section 5 of this document, and a high-level overview of how to complete the task is provided in Section 6.

This assignment requires you to produce two deliverables, (D1) and (D2), as outlined below:

(D1) A Python code file that satisfies the specifications in Section 7. This includes following the logical flow laid out in the flowchart provided in Figure 3 (see Page 9).

(D2) An audio-video screencapture file (3-5 minutes long) in which you show your code and give an overview of your approaches to modelling, programming and communication, aimed at museum staff who will need to maintain your code. One way to create such a file is by recording with Zoom (open a Zoom meeting, share your screen, and select Record Record to this computer). Please note that 5 minutes is a hard upper limit for the recording, and museum staff will stop watching your video at the 5 minute mark.

Submission and grading

Both deliverables (D1) and (D2) are to be uploaded via the Blackboard submission link by 1pm on 21 October, 2022. If your video file is large, or if there are many other Blackboard users, it can take time for your video file to load and you need to wait for your browser to complete the submission. The UQ guidelines on Blackboard assignment submissions recommend submitting at least 3 hours be- fore the deadline, in case of any internet/computer/technical issues. If you do have technical issues, you should contact the student IT service “AskUs” at the library. Late submissions without an approved extension will be penalised according to the policy in the ECP; consult Section

5.3 of the Electronic Course Profile for more information.

Your submitted code will be run and tested as part of this grading process. A rubric (grading criteria) for this assignment is on Page 10. The file that you submit will be checked using software which is specially designed to detect plagiarism in code. Consult Section 6.1 of the ECP for more information and procedures concerning plagiarism.

This assignment has an advanced section which must be attempted by students aiming for grades of 6 or 7 (see the grading criteria for more explanation). The shaded section of the flowchart indicates the requirements of this advanced section. If you have any questions, please contact the course lecturers via the course discussion board (see Section 4 below).

About getting help

This assignment is a piece of summative assessment, designed to let you demonstrate your level of mastery of several learning objectives in this course. As such, it is very important that the work you submit is all your own. This does not mean that you cannot receive help in regards to this assignment, but that help must be limited to general advice about modelling, Python and communication. This task sheet has been carefully constructed, and part of your job is to interpret the information it contains. Some choices have been left to your judgement, and this is intentional. Using regression software such as Excel or Desmos or similar to develop any of the models is not permitted.

Remember that you must not look at anyone else’s code and you must not show your code to anyone. Both of these actions are examples of behaviour that may be considered academic misconduct. No code from your assignment attempt should be posted on the course discussion board, or any other site, at any time. However, if you have problems with your code, you may develop some generic sample code that demonstrates the issue that you are having (but does not relate to the assignment). This can be discussed with others and/or posted to the course discussion board for assistance. All such discussion board posts must be made visible to all students, so that everyone can see the question and the answer from lecturers.

Modelling plastic production

5.1 Plastic production

The term plastic refers to a broad group of synthetic polymers that have become ubiquitous in modern manufacturing due to their low production cost and broad utility across a huge range of dif- ferent industries including packaging, consumer products, textiles, transportation, construction and electronics. The origin of large scale plastic production dates back to the 1950s and global plastic production has increased year-on-year in all but three years since then [1].

Figure 1: Examples of different modern plastic.

The museum exhibit aims to convey to patrons the scale of plastic production both now and into the future, and what implications this may have for our oceans.

Selected data for the global rate of plastic production between 1975 and 2014 is provided in Table 2 [2]. You should use this data to formulate a model for the global rate of plastic production over time. For modelling purposes, you may assume that any relationship you derive for the global rate of plastic production over the interval 1975–2014 can be extrapolated to future years. However, you should clearly communicate to patrons when your model is being used to make predictions beyond the scope of the data provided.

Year

Global plastic production (tonnes·year1)

1975

46,000,000

1978

64,000,000

1981

72,000,000

1984

86,000,000

1987

104,000,000

1990

120,000,000

1993

137,000,000

1996

168,000,000

1999

202,000,000

2002

231,000,000

2005

263,000,000

2008

281,000,000

2011

325,000,000

2014

367,000,000

Table 2: Data for the annual global rate of plastic production from 1975–2014, sourced from [2] via [3].

5.2 Plastics entering the marine environment

The lifespan of a plastic product is the time that elapses between its creation until it becomes waste. The lifespan of plastics varies significantly depending upon the type of plastic and how it is used. For example, plastics used in building and construction typically have longer lifespans on the order of decades, whereas plastics used in packaging may have an average lifespan on the order of months [4]. There are many different pathways for dealing with plastic wastes including reuse, recycling, thermal destruction and disposal. However, reused and recycled plastics eventually need to be disposed of, since these processes cannot be repeated indefinitely [1]. Mismanagement of plastic waste can lead to plastics entering the marine environment.

Estimating how much plastic enters the world’s oceans is a complex problem. Jambeck et al. (2015) developed a framework for estimating the amount of mismanaged plastic waste from coastal popu- lations that could potentially become marine debris. Based on data from 2010, they estimated that approximately 2.96% of the plastic produced in that year ended up as ocean plastic [5], as depicted in Figure 2. Using this information, and your model for plastic production, you should develop a new model which estimates the global rate at which plastics enter the world’s oceans. You may assume that this relationship between plastic produced and plastic entering the oceans holds true in other years, however, discerning science enthusiast patrons would value an explanation of any limitations of your model that follow from such an assumption.

Figure 2: Infographic produced by [3] depicting the proportion of plastic produced that ended up in the world’s oceans in 2010 based on [5].

5.3 A compounding problem

Once plastics have entered the marine environment they can remain there for a long time. In the ocean, plastics do not generally biodegrade on a timescale that would contribute to the removal of plastics from the environment. Instead, plastics at the sea surface are likely to undergo solar UV- induced photodegradation reactions. This “weathering” of plastic materials in the ocean can cause larger macroplastics to break down into microplastic debris [6]. The small size of such debris creates additional problems for effective detection and can hamper efforts to remove plastics from the ocean. Consequently, without targeted intervention, we can assume that all plastics that have entered the ocean remain in the ocean. We can estimate the accumulation of ocean plastics over time as the area under the curve of the rate of plastics entering the ocean over a given interval.

5.4 Impact of plastic on marine environments

Ingestion or interaction with marine plastics (such as through entanglement, ghost fishing, dispersal by rafting and habitat alteration) has been shown to affect more than 800 marine species, many of which are listed as being at risk according to the International Union for Conservation of Nature

[7, 8]. These effects can include ill health and death. Microplastics have been shown to collect in the gut, digestive tract and gills of various marine species when ingested, and some species have been shown to accumulate microplastics in other tissues through translocation [8].

5.5 Looking to the future

Geyer (2020) suggests that, based on current trends in plastic production, waste generation, and waste management, recycling and incineration will not be sufficient to sustainably manage plastic in the long term. Hence it will be important to consider mechanisms for reducing the amount of plastic produced and consumed [1]. Furthermore, sustainable consumption and production have been identified by the United Nations as a key sustainable development goal as part of a larger collective of 17 goals aimed at providing a global vision for achieving a sustainable, just, and safe planet [9].

A detailed overview of the task

Your assignment submission must follow the specifications listed in Section 7. Below, we first give a high-level overview of how to approach the main section and the advanced section.

To complete the main section, you will need to:

• Determine an appropriate mathematical function to model the global production rate of plas- tics as a function of time using the information provided in Section 5.1. You will write a function plastic_production in your code which implements this model. Your function plastic_production should take one input, time in years since 1975, and return the global production rate of plastics (in tonnes· year1) at that time.

• Determine an appropriate mathematical function to model the global rate at which plastics enter the marine environment as a function of time using the information provided in Sec- tion 5.2, and clearly communicate the potential scale of this issue to patrons. You will write a function new_ocean_plastic in your code which implements this model. Your function new_ocean_plastic should take one input, time in years since 1975, and return an estimate of the global rate at which plastics enter the marine environment (in tonnes year1) at that time.

• Inform the user how long it will take for the rate of plastics entering the marine environment to double from the present day value, based on your model.

• Communicate appropriately with museum patrons as informed by the main section of the flowchart in Figure 3.

• Include a description of how you approached this section of your code in your screencapture video (D2), including (briefly) how you developed your models and the overall code structure.

To complete the advanced section, you will need to:

• Use appropriate numerical techniques to estimate the accumulation of marine plastics by cal- culating the area under the curve of the model of the global rate of plastics entering the ocean.

You will write a function total_ocean_plastics in your code which implements this nu- merical integration algorithm. Your function total_ocean_plastics should take two inputs representing the start and end times, given in years since 1975, of the interval over which ac- cumulated plastic will be calculated and return an estimate of the total mass of plastics that have entered the marine environment (in tonnes) over this interval.

• Communicate appropriately with museum patrons as informed by the the advanced section of the flowchart in Figure 3. In communicating the potential scale of ocean plastic accumulation to patrons you should utilise conditionals to produce at least three simple comparisons for pa- trons to consider which depend on the magnitude of the output of the total_ocean_plastics calculation. Your comparisons should provide patrons with a clearer understanding of the scale of plastic accumulation, using everyday terminology/references the general public will understand.

• Include a description of how you approached this section of your code in your screencapture video (D2), including how you developed your models.

Specifications for your submitted file

Specifications about the Python:

• Museum staff have supplied a flowchart describing how the program should run (Figure 3 on Page 9. Your code must be an implementation of the flowchart provided.

• Your code must be well-structured and follow the guidelines for programming practice, as introduced in SCIE1000.

• Whenever you prompt the user for information, you may assume they enter a suitable number, and you can store their answer as an integer or as a floating point number as appropriate. You do not need to check for incorrect inputs.

• You may only use Python commands introduced in SCIE1000. Recall that museum staff must be able to maintain and modify the code, so you may only use commands that they understand. Museum staff have a beginner’s level of experience using Python, which you may regard as the equivalent of a student who has taken SCIE1000. The Python commands you have covered in this course should be more than sufficient to complete the assignment.

• Museum staff have identified several functions that they think will be useful in possible modi- fications and extensions of the code. You must define these functions in your code, with the exact names specified in Section 6. You should use these functions in your code as appropriate. You may define other new functions as needed.

Specifications about the communication:

• All messages to the user, including prompts to enter data, should communicate in a manner

appropriate for the level of patron and should serve the purpose of the program.


• You should write no more than a couple of sentences for each piece of information you explain to the user. Follow the principles for communication in science as described in Appendix B of the lecture book. Be precise, clear and concise!

• You should use units appropriately in your communication with the user. Make sure you are aware of the units of values being passed into functions and the units of values being returned from functions.

• You should include useful and appropriate comments in your code to help the museum staff who may need to maintain and modify the code. Any variable names and function names you define should be chosen with communication in mind.

• Whenever you produce a graph you should provide appropriate labels and accompanying explanatory text.

• Your screencapture video should provide a clear overview of how your code works and why you made the choices you did. This does not replace excellent commenting in the code.

• To reference sources other than those cited in this task sheet, you should include a bibliography as comments at the end of your code, to show the museum staff maintaining the code where you obtained any relevant information you used. Any referencing style is fine.

File type and file name:

• Your assignment (D1) should be saved as a .py file called PlasticOceans********.py with the string ******** replaced by your student number.

• Your screencapture audio/video file (D2) should be saved as Explanation********.mp4

with the string ******** replaced by your student number.

• It is your responsibility to ensure that the file types are correct.