Climate change

Google adds a search page dedicated to “climate change”


In addition to new features for Maps, Nest thermostats and flights, Google will be posting more information on how to make sustainable choices in research, shopping and finance. This includes a Google search results page dedicated to “climate change” and research into ineffective traffic lights.

Google will add a dedicated ‘climate change’ results page later this month. The “Overview” (with 10 blue links) and “News” tabs work the same, but “Causes”, “Effects” and “Take Action” are taken directly from United Nations data.

The search also makes it easier to find electric vehicles and other green vehicles. Google notes that interest in electric vehicles, as well as charging stations, has “never been higher”. The company will showcase climate-conscious models and allow users to compare models while helping users understand the benefits of electric vehicles.

There will be green tags for “Electric” and “Hybrid plug-in”, with results having a “Loading” tab. This notes the time it will take to refuel and the stations near you, as well as an “Annual Energy Cost Estimate” tool which allows you to “modify the parameters” and compare them to a vehicle. gasoline.

Meanwhile, Google Shopping will offer more cost-effective and sustainable alternatives when searching for power-hungry devices in the United States. This includes furnaces, dishwashers, water heaters, ranges and dryers.

Google Finance extends its sustainability score (from the Climate Disclosure Project) to your entire tracked portfolio. This will assess the sustainability of your investments and is currently “soon”.

Finally, Google today shared research on improving the efficiency of traffic lights to reduce idling time. This means less wasted fuel and less air pollution at street level. Optimizing, Israel’s early observations showed a 10-20% reduction in fuel delays and intersections. The company is currently piloting this effort in Rio de Janeiro and hopes to expand it to other cities.

So instead of manually measuring and calculating times, one of our AI research groups found a way to accurately calculate the traffic conditions and times at most intersections in cities around the world. , then they train a model on that data to optimize these inefficient intersections.

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