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electricitymaps
Create Seasonality in Food Models
A vegetable coming from a greenhouse as a much higher carbon footprint than a non-greenhouse grown equivalent. Heating can increase emissions by factor 2-3x, transport as well: https://www.researchgate.net/figure/fig2_256503477
Lucky for us, seasons for when vegetables and fruits (and even fish e.g.) are available locally are very clearly defined.
Idea: Create a very simple addition of seasonality to food items, an array that define the months that they are in season at what location (could be simplified as a region and not per country (northern europe, or even by climate). Based on the user's location and date, the seasonality multiplier is applied.
there are lot's of great resources for food seasonality: https://www.bbcgoodfood.com/seasonal-calendar/all
Would be great to expose this info to the user in the ActivityDetail screen, or even on the food input screen.
Both BBC and pdf show the Seasonal calendar for fruits (I hope so). But this project is about the carbon footprint. How is the seasonal calendar would help to calculate the carbon footprint? Maybe I could miss something.
Fyi seasonality is part of the source referenced in the huge ingredients PR (with other variables as well).
On Wed, Oct 2, 2019, 15:18 chandrakumar [email protected] wrote:
Both BBC and pdf show the Seasonal calendar for fruits (I hope so). But this project is about the carbon footprint. How is the seasonal calendar would help to calculate the carbon footprint? Maybe I could miss something.
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The climate impact of food items (and everything else, really) depends on a lot of factors related to their production. For example, tomatoes are grown in greenhouses when they are not in season. According to the paper I linked this can increase their carbon footprint by a factor of 2-3x. If we want to give people an accurate representation of their footprint, we should try to take these factors into account. Especially when they are actionable (meaning that people can change their footprint by making informed buying decisions)
Anecdotally, climate-type would be the best correlation between a user's geographic location and produce seasonality in my mind : https://en.wikipedia.org/wiki/K%C3%B6ppen_climate_classification. I live in a fairly intense microclimate that varies from the rest of the surrounding area so defining by country or even region would be a misrepresentation.
That's a great resource! We should keep that in mind when overhauling the food models
@sorensvejstrup and @corradio we should think about how we want to integrate this parameter in our footprint model. @alexisthual, maybe also a potential issue the contributors can look at?