WASHINGTON - The U.S. Department of Transportation (DOT), the U.S. Environmental Protection Agency (EPA) and the state of California have announced that they will work on a single timeframe, with a deadline of Sept. 1, 2011, for proposing fuel economy and greenhouse gas standards for model year 2017-2025 cars and light-duty trucks.
According to EPA, proposing the new standards on the same timeframe, by September 1, 2011, signals continued collaboration that could lead to an extension of the current National Clean Car Program.
Prior to today's announcement, CARB had announced its intention to propose greenhouse gas emission standards for model years 2017 to 2025 in March of this year, while EPA and NHTSA were working on an end of September timeline for proposal. Today's announcement is designed to ensure that both proposals will come out simultaneously after a joint review of all data available when the proposals are issued, EPA stated.
In April 2010, DOT and EPA established greenhouse gas emission and fuel economy standards for model year 2012-2016 light-duty cars and trucks. In the fall of 2010, California accepted compliance with these federal GHG standards as meeting similar state standards as adopted in 2004, resulting in the first coordinated national program. The standards require these vehicles to meet an estimated combined average emissions level of 250 grams of carbon dioxide per mile in model year 2016, which is equivalent to 35.5 miles per gallon.
In May 2010, President Obama announced that EPA, DOT, and California would begin working together to assess the performance and costs of a variety of technologies that could be available in model years 2017-2025 as the first step in possibly extending the current national emission and fuel economy standards. The three agencies completed an interim technology assessment and have since funded additional research critical to future rulemaking, according to EPA.
Mike Branch of Geotab and Dain Giesie of Enterprise Fleet Management will demonstrate how artificial intelligence (AI) and big data are being leveraged to spec vehicles based on vocation, topography, city density, and even local weather patterns.