It should be fairly evident that living next to a busy road is not a great idea. In 2010, the Health Effects Institute examined over 700 studies and found sufficient evidence to link traffic pollution to childhood asthma, cardiovascular diseases and impaired lung function. Evidence linking traffic exposure to cancer was deemed inconclusive.
A new epidemiological study by Dr. Hong Chen and colleagues found that living near a major road is associated with an increased risk of dementia. The most common form of dementia is Alzheimer’s disease. The authors tracked all people between the ages of 20 and 85 living in Ontario, Canada (6.6 million people) between 2002 and 2012. Medical records were examined to determine whether they were diagnosed with dementia, Parkinson’s disease or multiple sclerosis. Their proximity to a major roadway was determined by postal code. The data analysis statistically controlled for alternative explanations such as socioeconomic status, education, smoking, diabetes and body mass index.
Living near a major highway was associated with dementia, but not Parkinson’s disease or MS. They identified 243,611 cases of dementia. Those who lived within 50 meters showed a 7% increase in the risk of dementia; those between 50 and 100 meters, a 4% increase; and those between 100 and 200 meters, a 2% increase. The greatest risk was found among those who had lived within 50 meters of the roadway for the entire decade, a 12% increase in the likelihood of dementia. According to their analysis, for those who lived within 50 meters, up to 1 in 10 cases (7-11%) of dementia were accounted for by traffic exposure.
Of course, this is a correlational study, and it is possible that other uncontrolled variables account for part of the effect. The fact that they measured diagnoses of dementia raises the possibility that the decision to seek treatment was a possible contaminant. However, it is not obvious why, in a country with universal healthcare, people living near major highways would be more likely to seek treatment.
The authors suggest that the effect may be due to a combination of air pollution and noise. They found that long-term exposure to two common pollutants, nitrogen dioxide and fine particulate matter, is related to dementia, but the effect is not large enough to explain their results. Studies have found toxic nanoparticles linked to Alzheimer’s disease in human brain tissue.
Noise is an environmental stressor that has been linked to declines in cognitive performance. Heat and crowding are two other stressors that may be plausibly linked to heavy traffic. A previous study found that children whose schools were located near major roadways in Barcelona showed smaller improvements in cognitive performance than other children from the same city.
In 2016, for the first time, the U. S. added more electricity-generating capacity from solar power plants than from natural gas, wind, or any other source of energy. The total of 9.5 gigawatts (GW) of solar generating capacity is triple the amount added in 2015 and is enough to provide electricity for 1.8 million homes. Here are the data as reported to the U. S. Energy Information Administration. (The apparent surge in new generating capacity in December is due to respondents’ habit of waiting until the end of the year to report new installations.)
The top five states adding new solar are California (3.9 GW), North Carolina (1.1 GW) Nevada (.9 GW), Texas (.7 GW) and Georgia (.7 GW). These data are for utility-scale photovoltaic solar installations and do not include distributed generation (rooftop solar). In addition to solar, 8 GW of natural gas and 6.8 GW of wind power were added. No new coal-fired plants were built last year.
What accounts for this rapid solar growth? It’s not federal investment tax credits, which remained at 30%, the same as in previous years. The explanation is the rapid decline in the cost of photovoltaic cells, which has dropped from $77/watt in 1977 to $.26/watt in 2016.
It’s difficult to get a handle on the cost of various sources of power, since it varies from one country to another and depends on whether government subsidies are included. The world’s average cost of solar is now the same or less than any other energy source except wind. (See the chart below.)
Levelized cost of energy refers to the net cost to install an energy system divided by its expected lifetime output. Levelized cost data typically include subsidies. The average levelized cost of solar had dropped to $600 per megawatt-hour (MWh) a decade ago and is now at or below $100/MWh, about the same as coal and natural gas. In other words, solar has reached grid parity with fossil fuels. The cost of land-based wind power is about $50/MWh.
The above figures are for the average of all countries. However, a recent Bloomberg report claims that for 58 emerging economies, including China, India and Brazil, the cost of new solar has dropped below that of wind. The difference may be due to the location of these emerging countries, which are nearer to the equator than wealthier countries, and their need to add new capacity quickly, which creates economies of scale. It had been anticipated for some time that solar would eventually be cheaper than wind power, but few analysts expected it to happen this fast.
The problem is subsidies. According to the International Energy Agency, fossil fuels received $493 billion in subsidies worldwide in 2014, the most recent year for which figures are available. This is more than four times the subsidies received by renewables. On a level playing field, there would be little reason to add anything but solar or wind power.
Here’s one of those animated charts that helps us to see things that might otherwise be difficult to visualize. It’s an animated version of the “hockey stick” graph, showing the increase in global temperature since 1850. This animation is under copyright by British climate scientist Dr. Ed Hawkins, and he grants permission to reproduce it provided he is given proper credit.
The year 1850 is chosen as the starting point since it was the approximate beginning of the Industrial Revolution. A change of 1.5 degrees Celsius equals 2.7 degrees Fahrenheit. Notice how the 2016 line stands apart from recent years, particularly during the first half of the year, when the temperature reached 1.5 degrees Celsius above baseline for the first time. In less than a week, 2016 will officially become the hottest year on record. Here’s how it compares to recent years.
When the lines in this spiral stop overlapping one another and begin to diverge noticeably, that is an indication that global temperature is increasing exponentially, rather than at a linear rate, as had previously been assumed. Exponential growth can lead to rapid change in a short period of time.
The primary reason for these temperature increases is the accumulation of greenhouse gases in the upper atmosphere. The most important greenhouse gas is carbon dioxide, and this second Hawkins animation shows its accumulation is parts per million.
This March, carbon dioxide reached 400 ppm for the first time, and it will continue to increase. 350 ppm is considered a “safe” level of carbon dioxide.
If humanity wishes to preserve a planet similar to that on which civilization developed and to which life on Earth is adapted, paleoclimate evidence and ongoing climate change suggest that CO2 will need to be reduced . . . to at most 350 ppm.
Dr. James Hansen
Although the world’s CO2 emissions have stabilized in recent years, that’s not the same as dropping to zero. CO2 continues to pile up in the atmosphere. The only way CO2 can be reduced is to stop using fossil fuels.
The Trump administration has threatened to elimate NASA’s $2 million per year budget for Earth science, which is the world’s major source of data on climate change, including the information in these charts. Maybe the theory is that what we don’t know can’t hurt us.
Here’s a bit of holiday cheer–a video about a community solar network that is bringing electricity and WiFi to an off-grid rural village in Bangladesh.
The question raised by this bottom-up approach is whether enough people can be helped to make a difference. The video says the sponsor, ME SOLshare, Ltd., plans to bring installations like this one to 1 million people by 2021. (The current population of Bangladesh is 170 million.)
If human life is to survive on this planet, we must switch to 100% renewable energy very soon—yesterday, if possible. There is now a demonstration project that can help us to visualize this possibility.
Ta’u is the largest island in American Samoa, a U. S. territory in the Southern Pacific Ocean. It’s about 17 square miles and has 790 inhabitants. It previously generated electricity by shipping in 109,500 gallons of diesel fuel every year. Not only was this expensive, but there were occasional interruptions of the supply due to rough seas.
Ta’u now runs on nearly 100% solar energy due to the installation of a 1.4 megawatt microgrid consisting of 5328 Solar City solar panels and 60 Tesla Powerpacks, which are batteries for energy storage. This not only gives them enough energy to supply the island’s needs 24/7, it provides enough storage capacity to last for three days without sunlight—a rare occurrence—and recharges in seven hours. Here’s a promotional video from Tesla advertising the project.
The $8 million project was funded by the American Samoa Economic Development Authority, the Department of the Interior and the Environmental Protection Agency. Solar power is almost free once the system is installed. (Three full-time workers are required for plant maintenance.) Unfortunately, I couldn’t find an estimate of the current yearly cost of their diesel fuel, so I can’t tell how long it will take to recover its cost.
Obviously, transforming this small demonstration project to a larger power grid poses all kinds of infrastructure problems, but they are problems that are soluble in principle, and at a much lower cost than the fossil fuel companies would lead us to believe. We have no choice but to do it.
A recent headline says that climate change will cost the millennial generation $8.8 trillion. But from where does this number come? The trail leads to a 2015 study by Marshall Burke of Stanford University and two colleagues from the University of California at Berkeley in which they attempted to measure the relationship between temperature and economic productivity.
We know that global temperatures are increasing, and we can estimate how much they will increase if nothing is done to mitigate climate change (the “business-as-usual” scenario). How can you measure the relationship between temperature and economic productivity? You can’t do it simply by comparing the economies of warmer and cooler countries, since there are many cultural and environmental differences between, for example, Sweden and Nigeria. But if you compare the productivity of each country during warmer- and cooler-than-usual years, each country serves as its own control group.
However, other variables that influence the economy may take on different values during warmer and cooler years. For example, a global trade agreement may have increased productivity in certain countries in certain years, and those years may also have happened to be warmer (or cooler). These confounding variables have to be measured and statistically removed from the data.
Burke and his colleagues gathered data from 166 countries over the 50-year span between 1960 and 2010. They used multiple regression to calculate the relationship between temperature and productivity, while eliminating the effects of “common contemporaneous shocks,” such as global price changes or technological innovations, “country-specific . . . trends in growth rates,” such as those produced by changing political institutions or economic policies, and the lagged effects of previous years’ temperature and rainfall. Their final curve is an average of the impact of temperature on productivity in the 166 countries, weighted by the countries’ population size.
They found that the relationship between temperature and productivity is a curve which peaks at 55 degrees Fahrenheit (13 degrees Celsius). That is, countries are most productive when their average annual temperature is 55 degrees, and their productivity declines the more the average deviates from that temperature in either direction. The curve is shown below, along with the average yearly temperatures of selected countries. The blue shaded area represents the 90% confidence interval around their best estimate. At right are separate breakdowns for rich and poor countries, years of measurement, and agricultural and non-agricultural productivity.
Next, they used this relationship to calculate the effects of expected future climate change, assuming business-as-usual, on future global income and the incomes of each country. The model predicts that global productivity will decline approximately 23% by 2100, as compared to the same future without global warming. While some cooler-than-average countries, such as Canada and Russia, will see their economies improve, the majority (77%) will see declines in income, especially those countries near the Equator. Since the countries that can anticipate the worst effects are already poorer than average, the result will be an increase in global inequality. Here is a brief presentation of their findings by Dr. Burke.
How can these results be explained? The authors found that agricultural productivity peaks at around the same temperature (see the chart above). They also mention increased energy costs and declines in health at warm and cool temperatures. Finally, they cite research showing that human cognitive errors and interpersonal conflicts increase at warmer temperatures.
Can we trust these predictions? An optimist might note that there is a danger of overestimating the damage climate change will cause if the peak in productivity at 55 degrees is actually due to confounding variables unrelated to temperature that are not controlled in their analysis. However, it’s difficult to think of phenomena not caused by temperature that would still produce a productivity curve peaking at 55 degrees.
The authors also point out that between 1960 and 2010 annual temperatures fluctuated fairly randomly. This provided little incentive for people to adapt to warmer or cooler temperatures. However, future temperatures are expected to increase consistently, which may instigate successful efforts to adapt to these warmer temperatures.
Optimists might also argue that the assumption of no climate action at all between now and 2100 is unrealistic. To the extent that effective action is taken to mitigate climate change, the loss of productivity will not be as great.
On the other hand, a pessimist could think of reasons why their analysis might underestimate climate change’s damage to the economy. The authors note that their model focuses only on the effects of temperature and those other phenomena that are directly influenced by temperature. But climate change will affect other things besides temperature, such as sea level rise and extreme weather events. If these other effects reduce productivity, the harm due to climate change will be greater than they predict.
They also note that their model predicts the effects of annual temperatures only within the range that they have been observed between 1960 and 2010. But if global temperatures increase substantially, the future may not be predictable from the past. For example, if temperature increases cause sustained droughts over large areas, the cumulative effects on agricultural productivity may be much greater than the effects of any known previous droughts. In reality, we probably have little idea of what future catastrophes await us.
We can now return to the effect of climate change on the incomes of millennials. Two nonprofits, Demos and NextGen Climate, have published an analysis of the lifetime cost of climate change to American millennials, using the data from Burke and his colleagues. The Burke analysis predicts that, in the absence of climate action, the United States economy will shrink 5% by 2050 and 36% by 2100—slightly more than the global average of 23%.
Millennials are typically defined as people born between the early 1980s and the early 2000s. The Demos/NGC paper calculated the lifetime earnings lost by Americans who turned 21 in 2015 (born in 1994) and those born in 2015. This is simply a matter of arithmetic, and the formulas are given in their appendix. Using these formulas, you can calculate the cost of climate change to any birth cohort. Obviously, the later the birth year, the greater the cost. The $8.8 trillion figure is the aggregated cost to all millenials.
The chart below illustrates the average cost of climate change to Americans turning 21 in 2015, calculated separately for college graduates and non-graduates.
The second chart compares wealth lost by 2015 college graduates due to climate change to two other drains on the income of their generation—college debt and the lingering effects of the Great Recession.
Of course, the accuracy of these figures depends entirely on the validity of the analysis by Burke and his colleagues.
On Tuesday, the Environmental Protection Agency (EPA) held a public hearing in downtown Pittsburgh on their proposed rules to limit methane emissions from oil and gas drilling. Methane is a potent greenhouse gas—84 times more potent than CO2—and a major contributor to heart and lung diseases. This was only one of three such hearings—the other two were in Denver and Dallas—so it was a pretty big deal. It’s also symbolically important since it was held in Pennsylvania, whose state government is a wholly-owned subsidiary of the natural gas industry, and in Pittsburgh, the epicenter of the fossil fuel companies’ latest “sacrifice zone.”
Two days later, an email from PennFuture, a statewide environmental nonprofit, stated that those who testified in favor of the new rules outnumbered opponents by 92-2! This was a surprise to me since I had read a newspaper account of the hearing (in the Pittsburgh Post-Gazette) and had no idea the distribution of presenters was so one-sided.
If you’ve read this blog before, you know that false balancing is one of my pet peeves. False balancing occurs when the media, following the journalistic norm of presenting both sides of an issue, give the false impression that there is an equal amount of evidence—or as in this case, there are an equal number of citizens—supporting each side. The classic example is news coverage of global warming, which for many years implicitly suggested that an approximately equal number of scientific experts believed or questioned that the climate was changing.
I located four articles about the hearings in the Post-Gazette, the Pittsburgh Tribune-Review, the Observer-Reporter (Washington County) and StateImpact PA. The Harrisburg Patriot-News had an article about methane leakage that day, but did not cover the hearing. I found no coverage in the national media.
The Tribune-Review led with a headline implying balance: “EPA officials hear from supporters, opponents of methane emissions rules.” Two opponents of the EPA rules, Matthew Todd, senior policy advisor for the American Petroleum Institute, and Eric Cowden, outreach director of the Marcellus Shale Coalition, were quoted at length, but with no indication that they were only two opponents present. Three supporters of the rules were quoted by name. The article correctly stated that about 100 speakers testified and said that representatives of a dozen environmental groups spoke. In all, there were 180 words of coverage of testimony by opponents of the EPA rules and 188 words of coverage of supporters.
The headline of the Observer-Reporter read “EPA hears pros, cons of its proposed methane reduction rules,” again implying balance. They noted that the were 100 speakers and that “environmental and oil and gas industry groups provided widely diverse views.” But their coverage was unbalanced. There were 366 words summarizing Mr. Todd and Mr. Cowden’s testimony, and 155 words about the presentations of two environmental group representatives.
“EPA hears comments on proposed methane rule for oil and gas” was the headline of the StateImpact PA article. The article contained quite a bit of neutral exposition, including an explanation of the rules by David Cozzie of the EPA, who may have been the moderator. They then devoted 170 words to comments by Mr. Todd and Mr. Cowden and 260 words to comments by three supporters of the rules, two of whom were representatives of PA’s Department of Enviromental Protection.
The Post-Gazette‘s article on their website differs from the one in the paper. That may be the case with some of the other articles as well, but this was my only chance to make a comparison. The headline in the newspaper reads “EPA rules find support at hearing.” Reporter Don Hopey compared the number of supporters and opponents and noted in the first paragraph that “most of the 100 or so who testified” supported the EPA rules. He devoted 86 words to the testimony of two supporters and 86 words to a summary of Mr. Cowden’s testimony. The word count in the website article was supporters, 153, and opponents, 92. It had a neutral headline and didn’t indicate which side had the greater number of speakers.
The overall average was 200 words by or about opponents of the rules and 172 words by or about supporters. The only opponents quoted by name, of course, were the two energy industry employees. If you read all four articles, you might deduce that they were the only opponents present. The four articles quoted various different supporters by name. Some were representatives of environmental groups and others were identified as private citizens with no organizational affiliation given. However, only the Post-Gazette article indicated that supporters were in the majority, and none of them stated how large that majority was. I would argue that the lopsided distribution of opponents and supporters was the most newsworthy item and should have been the lead of any article about the hearing.
I will grant that turning out 92 people to testify at a hearing on a Tuesday morning is not a great accomplishment, and only shows that the environmentalists were better organized and more highly motivated. It gives no indication of the distribution of public opinion in the area, where it’s likely that few citizens realize the importance of methane leakage. I also acknowledge that the oil and gas industries could have turned out just as many people friendly to their position if they had been willing to spend the time and effort. However, public opinion is less important for them. Their success depends primarily on the amount of money they spend on campaign contributions and lobbying. Of course, it also helps that they have the news media in their pockets.
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