In addition to new features for Maps, Nest Thermostats, and Flights, Google is going to surface more information about making sustainable choices in Search, Shopping, and Finance. This includes a dedicated Google Search results page for “climate change” and research on traffic light inefficiencies.

Google is adding a dedicated results page for “climate change” later this month. The “Overview” (with 10 blue links) and “News” tabs operate the same, but “Causes,” “Effects,” and “Take action” are directly sourced with data from the United Nations.  

Search is also making it easier to find electric and other eco-friendly vehicles. Google notes that interest in EVs, as well as charging stations, has “never been higher.” The company will surface climate-conscious models and let users compare models while helping users understand the benefits of EVs.

There will be green tags for “Electric” and “Hybrid plug-in,” with results featuring a “Charging” tab. This notes how long it will take to refuel and stations near you, as well as an “Annual energy cost estimate” tool that allows you to “edit parameters” and compare to a gasoline vehicle. 

Meanwhile, Google Shopping will offer more cost-effective and sustainable alternatives when looking for energy-intensive appliances in the US. This includes furnaces, dishwashers, water heaters, stoves, and dryers.

Google Finance is expanding its sustainability score (sourced from the Climate Disclosure Project) to your entire tracked portfolio. This will rate how sustainable your investments are and is currently “coming soon.”

Lastly, Google today shared research on making traffic lights more efficient to reduce idling time. This means less wasted fuel and less street-level air pollution. By optimizing, early observations from Israel have shown a 10-20% reduction in fuel and intersection delays. The company is now piloting this effort in Rio de Janeiro and hopes to bring it to other cities.

So instead of manually measuring and calculating timings, one of our AI research groups has found a way to accurately calculate the traffic conditions and the timing at most intersections in cities around the world, and then they’re training a model on that data to optimize those inefficient intersections.

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About the Author

Abner Li

Editor-in-chief. Interested in the minutiae of Google and Alphabet. Tips/talk: