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Team Name:

Team De-carboniser


Team Members:


Evidence of Work

De-carboniser

Project Info

Team De-carboniser thumbnail

Team Name


Team De-carboniser


Team Members


Trish , Jonathan , Belinda , Brett

Project Description


The problem we have tried to address is CO2 emissions due to people making short motor vehicle trips that could be walked or done on a bike. We wanted a way to translate this into a tangible action to help make a collective impact on emissions by making an app that lets a person know if the trip they just made was so short that it could have been walked or cycled.


#co2 emissions #travel #warnings #walking #cycling

Data Story


We used the dataset from Stats NZ New Zealand Household Travel Survey: Travel to work, by main urban area results (3-year moving average) To identify the average distant people in Christchurch travels on foot and by bike to work. This gave us the metrics used in our app to calibrate if a trip could have been walked or cycled.


Evidence of Work

Video

Team DataSets

New Zealand Household Travel Survey: Travel to work, by main urban area results (3-year moving average)

Description of Use New Zealand Household Travel Survey, contains data on how people travel to work.

Data Set

Challenge Entries

Being More Sustainable: Travelling using the most sustainable route

We all know the effect on climate change from CO2 emissions. How can we translate this into tangible action made by a citizen, that they know is making a collective impact?

Eligibility: At least one team member must be able to attend and present challenge if selected at the Te Pae Technology Expo in Oct 2021 (at their own cost).

Go to Challenge | 3 teams have entered this challenge.

Hack for a Circular Economy

In order to build a more sustainable community, how might we redesign, rethink, repair and repurpose spaces, places, materials, and digital infrastructure, systems and policies within cities in order to progress social, natural and economic development?

Eligibility: Must use at least one open dataset.

Go to Challenge | 14 teams have entered this challenge.