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Show HN: Planetary Facts – food and product impacts against the planet's limits

https://planetaryfacts.com
2•mikethemerry•1h ago
Hi HN

I'm Mike, CTO of Planetary Insights, a small NZ team. With our partners, Planetary Accounting Network (PAN), we've just released https://planetaryfacts.com - a dashboard for consumers to understand the impacts of food, products and lifestyle decisions in context of the planetary sustainability limits.

The idea: most environmental scores are relative ("30% less carbon than X") and/or carbon only. We put everything in context of the Planetary Boundaries, and the pathways to get back into the safe operating space of the planet. It means every product can be measured as a % of daily budget per category or in totality, and if everything you do is less than 100% across the board, then congratulations, you've got a lifestyle compatible with a long-term sustainable planet (including carbon, biogenic-GHG, water, nitrogen, phosphorus, biodiversity, forestland, ozone, air quality, waste).

The comparison feature is meant to be flexible to make it practical for decision making. For example, put protein sources side by side, per gram of nutritional protein: the same 75g of daily protein can be 5% or 70% of an entire daily budget (and you still have to fit in travel, electricity, clothes, etc). It's also not just food. We have petrol vs EV in there now as well, and we have done assessments for tourism experiences, buildings and more.

How the numbers are made: these are all Life Cycle Assessment (LCA) models built from international datasets, adapted for NZ, run through the Planetary Insights platform. The PAN team authored, QA'd and published these - 50 assessments so far. Honest limitations: these are generic/average benchmark datasets and within-product variation can be really high. We have a number of brands releasing their specific products (lamb, honey, a digital publication) over the coming weeks, and we're wanting more to do it.

Stack: the dashboard is Flask + TanStack. The PI for Products stack is Flask + React + OpenLCA with Postgres (incl. pgvector for some source-matching features we're working on).

Would love feedback, critiques, questions, and especially what else would you like to see in the dashboard. I'll be in the comments

Beautiful Type Erasure with C++26 Reflection

https://ryanjk5.github.io/posts/rjk-duck/
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