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Retired Miner With Black Lung Begs EPA To Save Power Plant Rules: ‘We’re Literally Dying’

In 2014, Stanley Sturgill traveled 1,300 miles from his home in Harlan County, Kentucky, to Denver, where the Environmental Protection Agency held one of four public hearings and 11 listening sessions on new rules to limit pollution from power plants. The retired coal miner ― diagnosed with black lung and chronic obstructive pulmonary disease from his years toiling underground ― begged the agency for help: “We’re dying, literally dying for you to help us.”On Tuesday, Sturgill, 72, drove three hours to Charleston, West Virginia, for the EPA’s only public hearing on the Trump administration’s proposal to repeal the Obama-era Clean Power Plan. Hunched in front of a microphone at a rounded wooden table in the Senate Judiciary Committee Room of the West Virginia Legislature, he made his plea once again: “We’re still dying ― we’re still literally dying ― for you to help us.”“Just how many people must pay the supreme price of death for a few rich, greedy people to bank a few dollars?” Sturgill said. He noted how long he and his wife, Sharon, had trekked just to speak for a few minutes. “We may be old, but we still love living.”His testimony, about 90 minutes into the 9-to-5 hearing, punctuated a morning packed with fawning praise for President Donald Trump, back-patting Republican lawmakers, and exhausted public health advocates who’ve spent years repeating the same statistics on climate change and asthma.“Do I really think that this administration cares what this old, worn-out coal miner has to say? Well, I don’t know. I really doubt it. But I had to be here,” Sturgill said, “as long as I can draw breath.” The EPA estimates the social cost of carbon ― climate-change related damages to property, human health, economic growth and agriculture ― to be between $11 and $105 per ton of carbon dioxide pollution. But the real cost could be 129 times higher, according to a study released this month from Purdue University, which found that existing models relied on decades-old agricultural data.

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