Location Key to Pollution’s Real Cost
This more recent research has its earliest foundation in a limited analysis Mendelsohn completed 20 years ago of emissions at a single Connecticut power plant. In what he calls a “very basic” analysis, Mendelsohn determined that the economic costs of pollution would rise and fall sharply depending on where that power plant was located in-state, with the costs of damages lowest in more rural areas. To the contrary, “moving it closer to New York City would be a very bad idea,” he says.
“We used that as a conceptual launching point,” says Muller, who beginning in the early 2000s took the lead in vastly expanding that simple concept to include estimates of the multifaceted damage done from every known air pollution location in the United States. The project took nearly five years of detailed analysis and number crunching, he says. Called the Air Pollution Emission Experiments and Policy analysis model (APEEP) and published in 2007, the resulting product is a model that allows researchers to understand the damages caused by existing emissions in each U.S. county.
APEEP includes calculations for 10,000 U.S. locations that emit any of six major air pollutants: ammonia, fine particu-lates, coarse particulates, SO2, NOx and volatile organic compounds (VOCs). Ammonia, SO2 and NOx combine to form small particulates, which are particularly harmful to health. NOx and VOCs react in the atmosphere to produce ozone, which at ground level (as opposed to a beneficial ozone layer formed naturally high in the stratosphere) is harmful to both health and crops.
According to Muller, the next step was to organize the existing data in order to estimate damage. Muller tapped into a wealth of data from such diverse sources as the Department of Agriculture (crops grown by county), the EPA (pollution dispersion models), the epidemiology literature (mortality and morbidity effects) and the economic valuation literature (the value of small mortality risks).
Working from existing literature on the effects of air pollution concentrations on health, he was able to estimate location-specific rates of such pollution-related illnesses as asthma and bronchitis and of premature deaths, as well as yields of crops and board feet of timber diminished by pollution.
“As an example, if I was looking at the effect of ozone on soybeans, well, that’s been extensively studied. I could look at [a given increase in ozone levels] in a county in Illinois and plug in the effects on soybean yields of that change from the existing crop science literature.” The result would be a change in yields (bushels of specific crops).
The task of calculating and recalculating multiple damages for each pollutant, county by county, and relating them to emissions meant concentrated work that crossed multiple disciplines, from economics to atmospheric science, to public health sciences, to forestry and agronomy.
“For me the finished model really embodies the interdisciplinary spirit of the Forestry School,” says Muller.
There were other complications. Both economists admit that while valuing a bushel of soybeans is not controversial, estimating the costs of illness and premature death can be a contentious matter. For APEEP, they used various generally accepted existing economic models to produce a range of values. With human death and illness accounting for as much as 95 percent of total damages, their total calculation of gross annual U.S. damages in 2002 (from the most recent data then available) was notable no matter how conservative the illness and mortality models, ranging from $75 billion to $280 billion, or from 0.7 percent to 2.8 percent of the nation’s total gross domestic product.
The APEEP model served as a basis for the most recent study and helped confirm a hunch that a more economically efficient air pollution control regime, targeted at the highest-damage locations, could yield large net savings.
To show the magnitude of divergences in cost, Mendelsohn and Muller point out in their report that the economic benefit of eliminating one ton of SO2 in Hudson County, New Jersey, upwind of New York City, would do as much economic good as eliminating 50 tons of SO2 in a very rural place like Josephine City, Ore.
“We suspected that there would be a large gradient,” says Mendelsohn, “but we were surprised at how huge it turned out to be.”
A highly economically efficient emissions trading scheme would address that divergence. As an extreme example, that New Jersey county upwind of New York would earn 50 times more credit for each unit of pollution it eliminated than would a source in rural Josephine City that elimi-nated the same amount. Over time, pollution cleanup dollars would be spent where they do the most good, increasing the efficiency of regulations.
But what about equity? If one happens to live in a small town or rural America, does this approach imply that polluters will eventually relocate their emissions in ways that mean living with dirtier air?
“There are always going to be some questions of equity when you employ criteria based on economic efficiency,” says Muller. But he points out that the proposal begins with maintaining existing air quality standards everywhere. Since overall pollution levels would decrease substantially, he says “there isn’t going to be an area that experiences considerably more harm.”
So far, no policymaker has proposed reforming U.S. air pollution laws based on such an approach. However, the EPA has taken interest. It is providing the economists with funding to help expand their research over the next four years.
Then there are matters that the researchers intentionally haven’t yet integrated into their work, including the effects on electricity prices.
“I’d call this a sort of stylized experiment,” says Muller. “We’re hoping we’ve created an argument that will move discussions forward.”
Mendelsohn adds that, in any case, the research firmly established one simple basis for further discussion. “We’ve shown that the money you spend to protect the environment buys you a lot more value if you spend it wisely,” he says. “By spending wisely, you can get a lot more bang for your buck.”