Carbon Credits
Client
CareerFoundry
Year
2021
Working with a UX/UI Designer in a collaborative project to analyse and visualise carbon offsets data in an interactive dashboard.
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To help people learn about carbon offsets, their usage, and the impact they have on addressing the climate emergency
Context & Goals
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Carbon offsets are a new way to address the issue of carbon consumption and its impact on the urgent climate emergency. However, many people are unaware of what climate offsets do, how they’re used, and whether or not they have any real impact. Your challenge is to analyze and visualize carbon offsets data in a way that’s accessible and understandable to the general public
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User Story:
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​"As someone interested in the impact of new initiatives on alleviating the climate emergency, I’d like access to accurate information on how carbon offsets are being used so that I can evaluate their impact."
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Key Questions
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How are carbon offsets used around the world?
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Are there certain countries that use more offsets and certain countries that supply more?
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How useful are carbon offsets in addressing the climate emergency?
Tools
​Data Analysis Tools:
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Excel
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Tableau
Collaboration Tools:
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Miro
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Trello Kanban Board
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Google Drive
Data
2021 Voluntary Registry of Carbon Offsets
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Source (excel):
Skills
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Data cleaning & integration
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Visual analysis
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Storytelling in Tableau
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Collaborative working
The Team & Main Deliverables
FARID CHEHRAZ
UX/UI Designer
Data Analyst
Data Analyst: Deliver understandable data that the UX/UI designer can use to create an accurate dashboard for educating people about carbon offsets.
UX/UI Designer: Design a dashboard that educates users on how carbon offsets are used around the world and how carbon is distributed.
The Collaborative Process
1) Understanding the carbon credits domain
4) Framing the project objective using the ‘user story’
7) Data analysis & insights presentation
2) Understanding the data set provided
5) Data analysis
8) Dashboard designs, presentation and finalising designs
3) Understanding the project objective and deliverables
6) Agreement on collaborative working methods & tools
9) Project retrospective review
Data Analysis & Insights
The above graph shows a continuous surplus of credits. This could be considered a measure of effectiveness, given more credits issued equates to a reduction of carbon emissions.
The largest contributing project types by far to be Forestry & Land Use and Renewable Energy
We can see from the below map that the largest numbers of credits are issued in USA, India, China and Brazil - countries often considered to be industrial powerhouses.
For the last 7 years renewable energy project types have proportionately increased whilst forestry and land use has proportionately decreased
For the 7 years ending in 2019, there was an upward trend in credits issued in North America, Asia and to a lesser extent in Africa, as well as a decline in South America.
We can see a steep decline in credits issued in the last two years. Could this be the impact of Covid?
Dashboard Design
An Iterative Process
The data analysis uncovered a number or interesting insights but discussing initial findings with the UX/UI Designer helped focus further analyses. Working with someone with design as their specialism gave me a better understanding of how to present my findings. That was done through creating new graphs and combining different data points.
Focusing on key messages
Given the large number of insights uncovered, we had to hone in on what the key messages we wanted to share were. Keeping the user experience as the central focus, we came up with key areas that the dashboard was going to explore:
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Effectiveness of carbon credits​
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Types of projects which generate carbon credits
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Where are projects based?
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How have carbon credit projects changed over time?
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The final desktop version of the dashboard is shown below:
Final Dashboard Design
Collaborative Working - Key Learnings
What worked well?
Collaborative working: We were respectful of each other’s time constraints and were both flexible when scheduling meetings and agreeing deadlines some of which were brought forward to allow for an extra buffer which helped with limiting stress. The various tools we used were particularly useful in communicating asynchronously e.g., Kanban board, Google calendar, email etc.
Idea generation: Presenting our initial findings and then allowing the other to have their input, taking the role as the ‘user’ meant we were able to overcome blocks quickly, often deriving solutions we would not have thought of had we not been working collaboratively.
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What could be improved
Meeting time-keeping: As the synchronous meetings we had were few, we were keen to make them work and get the most from them. However, this meant went over the initially agreed time, and were kicked out from Zoom unexpectedly on a few occasions.
Managing stress with wanting to meet deadlines: Working to the deadlines meant that we put pressure on ourselves because we didn’t want to let each other down. Fortunately, we are both similar in this instance and we able to support each other and be understanding.
Future Analysis
How could we derive more insights from further data analysis?
• Future data: Given that the volume of vintage credits issued decreased sharply in 2020 and 2021, it would be interesting to revisit the data set with 2022 and future years’ data to assess whether it was the start of a downward trend or simply the impact of Covid
• Supplementary data: Assessing the effectiveness of carbon credits with the data set used for the project in isolation is very limited and likely tainted with bias. Supplementing the data analysis with other data e.g., other climate data such as temperature changes could help with that assessment