I'm Tom Zinnen. I work here at the UW Madison Biotech Center and for UW Extension Cooperative Extension,
and on behalf of the Wisconsin Alumni Association, the Science Alliance here at UW Madison, and Wisconsin Public Television,
thanks for coming to Wednesday Nite at the Lab. We do this every Wednesday night, 50 times a year.
Tonight I'm delighted to be able to introduce to you Professor Tracey Holloway. She's the director of the Center
for Sustainability and the Global Environment, known by its acronym, SAGE. It's a cross-disciplinary
research center based in the Nelson Institute for Environmental Studies here at UW-Madison.
Professor Holloway's research examines air pollution chemistry and transport at regional and global scales, including links
between air quality and climate, energy, land use, health, and public policy. She earned her PhD in
atmospheric, oceanic, and space sciences, is that correct? AOS? >> Atmospheric and oceanic
sciences. No space. >> No space. No final frontier.
And it's from Princeton University. It was in 2001 and she completed a certificate in science
technology and environmental policy from the Woodrow Wilson School of Public and International Affairs.
And as we all know, where was President Wilson president before he was president of the United States?
At Princeton. Her undergraduate degree is from Brown University in applied mathematics, and her
postdoctoral work was done at Columbia University's Earth Institute. Please join me in welcoming
Professor Holloway to Wednesday Nite at the Lab. [APPLAUSE] >> Tracey Holloway: Thank you
very much. Thank you all very much for coming. It's really an honor to be here,
and we're particularly excited because the next four weeks will really showcase a breadth of work at our research center,
which we call SAGE. And as mentioned in the great introduction, thanks very much for that, SAGE stands for the
Nelson Institute for Center for Sustainability and the Global Environment. So I've been the director for
the past three years. I'm actually taking the year off to focus on my research, which is what I'm really talking here
most about. So I'm happy to answer questions after the talk either about the center broadly or about the
material that I'm presenting here. So the focus of my work is looking at air quality on large
regional scales up to global scales. And there's a lot of reasons to care about air quality.
In fact, as I just heard this morning, there was a White House report just issued yesterday which actually pointed out that
air quality regulations are the single largest regulatory expense in the United States. And in fact, about nearly 50% of
all costs across all US rules relate to air pollution control. And of those the number one pollution that is being
controlled is particulate matter, which we'll talk about quite a bit over the next hour. Despite these big costs, there
are actually enormous health benefits to controlling air quality. And in fact, this same White
House report valued that the benefits for controlling air pollution end up being valued somewhere between twice as much
and over 20 times as much as the cost of controlling them in terms of reduced mortality and reduced sickness and loss of
days of work or days of school across the United States. Beyond these numbers and big picture costs and benefits, air
pollution is something that really impacts all of our day-to-day life. It affects where we live,
whether you choose to live near the highway or inland, whether you choose to live in Madison or Los Angeles, and maybe when you
choose to go outside for a walk or when you choose to exercise. It also impacts our cities and skylines.
Every city that we look at that has smokestacks, the only reason that those smokestacks are there is because of air quality.
Although in the United States we have strong rules in place that are acting to improve or air quality on an ongoing basis,
worldwide this is a huge global health challenge. So I'm going to focusing mostly here on the United States, but
keep in mind that if you go to Beijing or to cities in India or even to rural villages in parts of Africa, the air quality there
is much worse than anything that we're facing here in the US, and so thinking about how our solutions could translate into
an international context is an important part of our work. All of our energy choices and climate policies all tie back
into air pollution. And in fact, that's going to be the focus of some of the work this I'm presenting later.
How do all of these different policies that we may be approaching separately, the Office of Energy Independence or
carbon reduction, how do those all tie into this overarching concern that we've been regulating since 1970 and
earlier of how do we get our air to be clean and healthy. But one reason I personally like working on air quality is that
in many ways it's an environmental success story. The air in the United States has been getting cleaner and cleaner
decade by decade since the Clean Air Act was passed in the 1970s, and I think it can really serve as a great inspiration for
tackling some of these thornier issues like climate change or deforestation where the policies are emerging and are not as far
along. So of all the chemicals that you may have learned about in chemistry class or all the
compounds in the air, there's really two that we're going to be talking about over the rest of this talk.
And these are really public enemy number one and number two from the perspective of the EPA in terms of air quality impacts
on public health. So we're going to be seeing these over and over. I hope the lighting is okay to
see these slides. But public enemy number one is particulate matter. And this is regulated in terms
of how coarse it is, with the coarser type of particulate matter, called PM10, which is particulate matter smaller than
10 microns, and the main concern is particulate matter that's even smaller than that that has an diameter of less than
2.5 microns. And this means that it's so small we can't even see it, much smaller than the diameter of a
human hair. And because it's so small it can penetrate into the lungs and going deeper down and maybe even
penetrate into the blood stream. So the way in the United States we consider these particles is by size.
So there's all different flavors of all particles that are all regulated pretty much in the same way.
So what I'm showing up here is the slide over our public enemy number one, particulate matter, is what are the different
flavors of particulate matter in major urban cities across the United States? And what you'll see is that the
yellow is a big chunk, over 25%, of particulate matter in urban areas across the eastern United States.
And that yellow is sulfate. And sulfate is formed in the atmosphere through reactions coming from sulfur dioxide.
And sulfur dioxide is primarily emitted from coal burning power plants. So when you see the yellow chunk
of particulate matter, you can really think to yourself that is coal fired electricity production.
The green wedge is ammonium, and that's primarily coming from agriculture. The red is nitrate and that's
coming, a large amount from transportation, also coming from electricity production and other industrial sources.
And the gray, which is really a large fraction across the United States, that can be a wide mix of everything from the black
smoke coming out of your diesel exhaust to smoke coming off of a barbeque to particles that are created in the atmosphere
through chemical reactions. In California you see a lot of big pies out there. They have a lot of particulate
matter problems, but there you see that the red plays a much bigger role and that's because the particles in California
arise primarily from transportation, whereas coal burning electricity plays a much bigger role in the Midwest and
the eastern United States. So even though the whole United States is subject to the same rules and the pollution affects
people's health in the same way, at least according to the current state of the science of public health, it's really
coming from a wide mix of different sources. So we'll come back to PM2.5 quite a bit.
Our other big public enemy is ozone. And ozone is often referred to in the popular press as smog.
And it is created in the atmosphere from two main ingredients: nitrogen oxide, these are ones that come from
both transportation and power plants and our other manufacturing sources, and volatile organic compounds, and
this is a wide mix of chemicals and every time you walk through a pine forest and you smell that nice piney smell, that is a VOC.
And every time you go to fill up your gas tank and there's that little rubber collar where the gas pump meets your car, that's
actually a VOC reduction technology to prevent gasoline evaporation. So VOCs come from a wide mix of
sources, NOx come from a wide mix of sources. Both are invisible and both react in the atmosphere to form
ozone, which is also invisible. So it's invisible but it is still very damaging to public health and agriculture.
So what I'm showing here, and it's hard to see, but this is yesterday's maximum particulate matter on the left and ozone on
the right. And what you'll see is that anywhere there's yellow dots, that's considered moderate air
pollution in eyes of the EPA. And what moderate means is that we would not want to is it every day of the year, in fact it
would be illegal to have it every day of the year, but from time to time it's okay to go into the yellow.
And as soon as it gets into the orange, that is actually considered too high, even for a single day.
So just yesterday for public enemy number one, almost all of the west coast, all of California, is in the yellow and
about half or a third of the monitors across the eastern United States are in the yellow and there's a few oranges
yesterday around Chicago area and then in the southeast. So just yesterday we have a ton of areas that are unhealthy for
sensitive groups and not that healthy for most people. And then if we look at ozone, that's the plot on the right,
again this is yesterday's values, we see lots of areas in California, Texas and Oklahoma, the Midwest, and the east coast
that are in the orange area, the unhealthy for sensitive groups. So I pull these slides up every time I give a public lecture.
And I don't have to look for a special day when it was particularly bad, any day I'll have orange and yellow dots on
these EPA maps. And if you're ever interested in checking out what the air pollution levels are, a great
website is called AIRnow.gov. >> What do you mean by sensitive groups? >> Well, that's how the EPA, the
EPA defines sensitive groups as, broadly, children, people with respiratory disease, and the elderly.
But the truth is it's not healthy for anybody. That's just sort of a way of communicating how bad is bad.
But the way that, the science community, we talk about things in terms of concentrations and micrograms per meter cubed, but
this AIRNow website is specifically designed by the EPA to communicate air pollution to the public, and so they try to
convert it into green, yellow, orange, red, kind of like the Homeland Security system or stoplights or something like
that. And so basically, when it's orange, it is not good. When it's yellow, it's still not
good but from time to time that's expected. So this is just what it was doing yesterday.
We'll get a little more general. The reason we care about unhealthy for sensitive groups or moderate air quality or
really bad air quality is because of the health impacts. Primarily asthma and other respiratory diseases but there's
also very strong evidence linking it to heart disease, diabetes, infant mortality, actually increased mortality for
everyone, and other risks. And just to put a number on it, reducing PM2. 5 just by 10 micrograms per
meter cubed was found, across 50 cities in the United States, to extend life expectancy by about seven months.
And just to put what does 10 micrograms per meter cubed mean, just that yellow zone, that spans 20 micrograms
per meter cubed. So moving from orange down to green would give you about twice as much of a benefit as this
seven-month metric. So these are big numbers that really do have direct impacts for all of us.
And with air pollution and health risk, just like with eating cheese burgers and heart disease, or smoking and lung
cancer, you can't draw a one-to-one relationship. But this is something that strongly increases the risk
factor. And I'll say from my own experience, I grew up with asthma, and when I'm in an
environment that has elevated air pollution, I definitely find myself reaching for my inhaler more often than I would
otherwise. So who's affected? Many, many people. Over a third of the US live in
cities that are affected by one of these two major air pollutants. And although more people live in
counties where the ozone is above the standard defined by the EPA as healthy, actually PM2.5 is the more damaging
and dangerous pollutant. But all together, about a third of the US is in counties that are above these thresholds.
And these thresholds are actually constantly under revision, and they're under revision based on new science
that's coming out of the public health community. And so actually just this summer, later this month, we're
expecting to have a revision on the ozone standard. So that should be something that you might see in the newspapers
in the next few weeks. So we see that there's these sort of this pass/fail defined by United States Environmental
Protection Agency. And if we look at our two major pollutants, this is a ballpark map for each of them about who
is failing. And we see because these standards are being revised, these may not be the most
up-to-date maps, but it gives you an idea of what are the areas that tend to have the worst air pollution.
And on the left these are the counties that are out of attainment with the particulate matter standards, and on the
right those are the counties that are out of attainment with the ozone standards. And so we see there's more areas
out of attainment with the ozone standard, which is one reason why more people were affected by ozone on our previous plot.
California, of course famous for its smog and bad air quality, is out of attainment with both of them almost everywhere, but
large regions of the east coast and the Midwest are both affected by these pollutants. Now these maps from the EPA,
this just says passing or failing. But just like if your kid brought home a report card that
said they were getting a D, you wouldn't be that happy. And so just because you're passing doesn't mean that you're
really doing a great job. And so to dig a little bit deeper into some of these numbers, the American Lung
Association actually took this metaphor literally and started issuing grades to counties and cities across the United States
to say just because you're not failing, just because you're not colored in on these maps up here, doesn't mean that
everything is hunky dory. So they use the same data from the EPA, pretty much the same calculation methods that the EPA
uses, the American Lung Association was a little bit stricter in how they graded for particulate matter pollution,
but the data is exactly the same as the EPA uses. So on my next slide I'm going to tell you who are the worst
cities according to the American Lung Association based on measured data, for particulate matter and for ozone.
And I might think to yourself who you would suspect to be in each of those categories. Well, for short-term, first I'll
talk about ozone. That's pretty much what we would expect. Los Angeles, more in California,
New York, Atlanta, Pittsburgh, but you'll probably be surprised here we are in Wisconsin to see that among the 25 dirtiest
cities for short-term particulate matter, three are right here in Wisconsin. Number 17 on their list is the
Chicago zone that extends into Michigan City, Indiana, and into southern Wisconsin. And we could say that's not
really Wisconsin, that's Chicago. But we can't quite say the same thing when we get to number 23,
which is Green Bay, Wisconsin, and number 24, which is right here in Madison extending up to the Baraboo area, which you
might find surprising is tied with Phoenix, Arizona. If any of you have been there it's quite smoggy there from
time to time. >> Phoenix just exceeded us, by the way. >> Okay, they just passed us?
We were tied with them according to what I checked. >> We don't have all that dust cloud.
Oh, right with the big dust cloud. Absolutely, absolutely. The big dust cloud that just
came through Phoenix yesterday, thanks for bringing that up, actually that is exactly the kind of particulate matter that
we're talking about, but there it's coming from a natural source. And so you might think to
yourself, is a place like Phoenix going to be penalized by this big dust storm? Does this mean that they start
failing these standards? And that's a very complicated question as to what really counts for passing and failing.
In the same way that a student might say to the teacher but this time there was an exception of why I wasn't able to meet the
standard. But actually because forest fires, dust storms, that kind of thing, do happen and really are
beyond the control of the cities and the counties that they do get a pass for that. So that dust storm that happened
will not be affecting the grade that Phoenix gets, either from the American Lung Association or from the EPA.
So now that we see that these two pollutants actually are a problem even right here in Wisconsin, I was surprised to
see Green Bay on the list, but then actually I drove up to Green Bay last week and found this picture on the Internet
which pretty much is a nice overview of the city, and you see that big plant right in the background with big billowing
smoke coming out of the smokestack. So it's not hard to see why Green Bay might wind up in that
category, although it certainly surprised me when I saw it. >> Do you know if that's smoke or is that water vapor?
That, to me, looks like smoke because it's kind of gray. It could be water vapor but even with water vapor there are a lot
of invisible gas chemicals. So anytime you see something like smoke in the air, that's particulate matter.
But beyond what you actually see in the air, there's a lot of chemicals that can combine to make particulate matter or ozone
or other pollutants. And these are all emitting from active smokestacks, whether you see them or not.
So why isn't the US scoring an "A"? We have the technology, we have the knowledge, but why are these
two public enemies so elusive? Why can't we catch them? And one problem is that many different emission sources
contribute to both ozone and particulate matter. It's not just a one-to-one if we control this power plant or that
car we'll solve the problem. It's a very multifaceted challenge that cuts across almost every sector of our
economy. Once these chemicals are emitted from tailpipes and smokestacks and agricultural fields, they
then react in the atmosphere in complicated ways and that may depend on whether it's warm or cold or humid or cloudy.
So the weather conditions really affect the chemical reactions and the weather conditions also affect where a particular plume
of smoke or air mass of ozone is transported, whether pollution from Chicago moves up across the lake to hit Door County or
whether emissions from China are coming across the Pacific Ocean to hit the United States. Beyond weather and all the
emission sources, what the land cover is also affects pollution. We often get the highest ozone right over Lake Michigan.
Now there's no emission sources, or there's some ships, but no major, major emission sources over Lake Michigan, but once
chemicals are in the air above the lake they stay there because the lake surface isn't really sticky to chemicals.
In contrast, leaves and grass and ground cover actually take up quite a lot of chemicals in the air just because it's, we
refer to it in the air pollution field as dry deposition. But you can really just think of it as how sticky are these
surfaces to the chemicals. So when you're over water, water is not sticky and the chemicals stay in the air longer and can
build up. And so all of these things together means that when you have ozone in the atmosphere or
particulates in the atmosphere, they can mix over a very wide geographic area. So it's not enough to control
what's in your own backyard. States have to be working together and even countries may have to be working together to
truly keep air quality at levels deemed safe. So the work that's going on in my group at SAGE really focuses
on... Excuse me. On answering what-if questions that can inform the development
of strategies for cleaner air. Questions like, what if we conserved more electricity, or had cleaner trucks, or what if
we expanded or solar energy production or moved more freight by rail instead of truck? What if the climate gets warmer
or windier? And what happens as other countries are growing and their air emissions are moving over
to the United States? What would that do to the health of the air over the United States?
Would that improve our grade? Not that we are focused so much on that but just building on this metaphor.
So to answer these questions, there's a few challenges. We have to take account of all the emissions because you can't
look at just emissions from trucks without thinking about how they interact with weather conditions and emissions from
agriculture and emissions from electricity production. You have to look at these emissions as they change.
They change hour to hour. Think about rush hour traffic versus the middle of the night. Month to month, summer versus
winter has very different patterns in terms of energy use and land cover. And, of course, year to year,
in part because of emission controls. And in part because of changing population, changing patterns
of energy consumption and land use. So then we think about how these pollutants move through the
atmosphere in three dimensions and how they respond to changing weather conditions. So the approach that we use to
answer this is to use computer models. What we do really is sit in front of computers all day.
So this Wednesday Nite at the Lab, if you were to come to our lab it wouldn't have any fancy gizmos or we wouldn't be wearing
lab coats but this is one room that we use at our building at the university to be looking at data and doing computer
programming. And these models are based on mathematical equations. And when you're thinking about
what kind of math is being invoked, hark back to your calculus class because your calculus is the science to
describe change. And what we're talking about here are chemical changes, changes with fluid dynamic
motion, changes in the amount of radiation coming through the atmosphere. So all of these changing
processes can be described with derivatives. And once you start solving those derivatives with differential
equations, that's as far down the math route as I'll go, then you can actually start kind of backing out what we would expect
in terms of chemical concentrations and temperatures and transport of how much one chemical plant or one city
contributes to air pollution downwind. We solve these mathematical equations with powerful
computers and then use software to make pretty plots like this plot on the lower left. Actually what that is,
is an elevation, one of the inputs that goes into our model, but it gives you an idea of the kind of maps that we're
generating from this process. The flow chart in the upper left corner just shows the different components that go into this
modeling system. We need to take account of weather. So we have to have gridded
weather on three dimensions, calculated, really, minute by minute. We use it every 15 minutes but
to calculate it every 15 minutes you almost have to do it minute by minute. So we have three-dimensional
weather conditions calculated minute by minute and then those combine with emissions from all of these different sectors that
I just noted earlier. Both man-made and natural emissions. The boundary conditions, you
think about what is flowing into our area from outside, our local sources, and then we calculate it up in terms of chemical
reactions and other mathematical processes. So that's the ballpark of what we do.
The models that we use are really the state of the science for doing this kind of analysis. Our chemical models are from the
United States Environmental Protection Agency and our meteorology models are from the National Center for Atmospheric
Research in Boulder, Colorado. So we have a nice team here, in fact one of our gang is in the back.
And the graduate students, undergraduates, and occasional postdocs who I work are really the ones who are out in the
trenches drudging through sometimes challenging software problems, but at the end of the day we're all addressing issues
that connect these sort of real world what-if questions with air quality and public health. So I could tell you seven
different stories about the work that we're doing, but I just want to focus on one since we only have an hour and now moving
into about 20 minutes. A few years ago, our past Wisconsin governor, Jim Doyle, initiated the Global Warming
Task Force. And you may remember this. It was an effort to say what would be the most cost effective
ways for the state of Wisconsin to reduce our carbon emissions. So a great project. And they hired consultants and
scientists and they really worked together to think renewable energy and energy conservation and what would be
the best strategies for our state to reduce carbon emissions. But of all the things they
thought about, air quality was really never explicitly part of that discussion. And not because air quality
isn't relevant for Wisconsin, we've already seen that it definitely is, but that actually it's very difficult to start
bringing all of these other pollutants that mix in the atmosphere with weather conditions into the same
discussion as energy efficiency and carbon reductions. And so across the United States and around the world, almost
nobody analyzes the direct air pollution benefits of clean energy choices. Really, the air pollution people
are over here, the energy and climate people are on the other side of the room, and there's not many people running back and
forth to relay messages. So all of these policies were developed by the Task Force on Global Warming and we thought it
would be interesting so say, okay, let's imagine that these are implemented, would that help us get cleaner air in Wisconsin?
What would be the benefits of these proposed policies? And so we got funding from the Wisconsin Focus on Energy
program and we focused on electric power production in the state of Wisconsin answering this question: how would these
low carbon policies benefit air quality? So the approach that we have to use to calculate these
co-benefits from energy efficiency and renewables is a bit convoluted, but believe it or not this is a simplification
of what we're really doing. First, you start up in the upper left corner where you actually have some set of policies, and
we were fortunate to just build on all the hard work that the task force had already done so we just took their policies as a
starting point. Once you say okay those are the policies, what would that actually mean in terms of
reduced fossil fuel combustion? And of course, that doesn't mean that every plant is reducing by, say, 20%.
Some power plants are going to be turned off entirely. Some are going to be scaled back.
Others might actually be scaled up to compensate for renewable intermittency. Then you calculate what the
changes in different pollutants being emitted from the power plants would be and we take this as input to our model.
We take every other emission because, again, we can't look at just electricity in isolation. We bring in all the information
on weather conditions and we churn it all through our equations in our computers to calculate the change in air
pollution and the resulting change in air quality. So this kind of approach is really a team effort.
And in our case we worked very closely with Dr. Paul Meier, who is the director of the University Wisconsin Energy
Institute. And he had developed an electricity model called myPower that relies totally on
transparent publicly available data from the Department of Energy. There are, of course, a lot of
electricity models in operation, but they're all proprietary and extremely expensive to license. And when I say extremely
expensive, we're talking about like $100,000 for a one-year license. And so we really can't afford
that here in our research group. So Paul, as part of his PhD, actually built an electricity model from the ground up, and we
used that to say if these policies were implemented, which power plants would be on, which would be off, and what would
really be the net change in these key pollutant emissions. Then we took weather calculations from a former
student and now scientist working with me, Caitlin Littlefield, who used this atmospheric weather model, we
call it WRF, the weather researching and forecasting model. And then one of my former
students and another current part-time scientist working with me is Steve Plachinski, and Steve took the emissions
information and the weather information and calculated what the air quality would be. And so most of the work that I'm
showing here is from Steve's master's thesis and a paper that we'll be submitting actually tomorrow to the journal
Environmental Science and Technology. So the first thing that we want to do is to say how good are
these models. And consistently we check our models with ground-based measurements, mostly from the US
EPA, and more and more against satellite data from NASA. For the energy model, the best data to compare with were
reported emissions from what's called the Clean Air Markets Program. And so on the bottom axis are
the estimates of electricity generation, NOx emissions, and SO2 emissions from the this clean air market, so this is the
real world. And on the Y axis is what was calculated by Paul Meier's model.
And if things are perfect, they lie right along that one-to-one line. And amazingly these red dots
pretty much do lie along that one-to-one line. I mean, we were so happy to see this because this was actually
the first time that Paul's model was used across the state of Wisconsin and that we had this data to compare.
In fact, the total NOx and sulfur dioxide emissions agree within 1% between the two if you totaled them all up.
Of course some individual power plants are not within 1%. But that's great. We were really excited.
So then the next thing we did is we focused on emissions of NOx and emissions of SO2. And just to sort of tie us back
to our pie chart that we saw earlier in the talk, the SO2 relates to those yellow pies and the NOx relates to the red pies.
And actually the green pieces of pie, that's from agriculture and that's almost always tagged on to either the NOx or the nitrate
or the sulfate. So by just looking at particulates resulting from NOx and SO2 emissions, we're still
covering over 50% of the particles across this region. So then we wanted to see how good is the atmospheric model.
And this is the kind of plots that I'm more used to looking at. And this is pretty good.
This is about the state of the science that some places the model does well, some places not so well.
But if we have observations on the X axis here and the model on the Y axis and we see that for sulfate, and that's the yellow
pie, that the red dots are pretty much hugging that one-to-one line. They're not perfect for sure but
it's definitely when the observations are high, the model is high; when the observations are low, the model is low.
We'll skip over the middle chart for a moment and go to ozone. And again ozone, when the observations are high, the model
is high; when the observations are low, the model is low. The model is a little bit too high overall, that's why the
bulge is kind of above that line. But that's actually typical of almost every one of both global
and regional air quality models for ozone. The models do a really good job at linking cause and effect but
for some reason there's always a little bit too much ozone for most of these models. Now for nitrate in the middle
we don't do a good job. I'm not going to lie to you. But actually almost nobody does a good job for nitrate so this
is an area in the models that's really evolving. So overall we do pretty good on our comparison across this
particular region and this particular year, which was 2003. We were as happy as we expected to be.
We could always do better but this is kind of what we thought we'd see. So using this set of models now
that we know that they're all pretty reliable, the first thing we did was to calculate emissions associated with this
policy that was proposed by the Task Force on Global Warming. And what that policy was to have by 2024 a 12% increase in
demand rather than the business as usual assumption of a 35% increase in demand. So in either case over the next
15 years, demand is going up. But is it going to go up by 35% or can we use energy efficiency measures to keep that at a more
modest 12%? And already on the books is a plan for a 12% renewable portfolio standard, and the task
force recommended doubling this to a 24% renewable portfolio standard. So these were the policies.
This was sort of the input to our analysis. This is what we had to start from.
And using Paul Meier's myPower model, then we said comparing current conditions, 2008, this 2004 business as usual, if we
don't change anything, and then a 2024 policy case. What happens to total electricity generation, what
happens to the percent of renewable energy, and then what happens to emissions, not just of carbon dioxide, but of NOx
and SO2? And I won't go into the details on this chart except to say that the generation goes up in the
future but goes up by much less with the renewable and efficiency standards in place. And that even if we don't do
anything we have scheduled reductions in NOx and SO2 on the books, but we get more reduction in these pollutants if we go
with this efficiency and demand reduction. Yeah? >> With the CO2, are you
distinguishing between fossil CO2 and biological CO2? >> Well, this is using currently built plants.
And so there are no-- biomass is a very small part of this calculation, if it's included at all.
Yeah, good question. So after running these scenarios through the electricity model and then through the air quality
model, we come up with something that looks like this for Milwaukee. And again we look just at one
month, July, and one year, 2004, so I caution against generalizing these results too much, but this was really more
of a proof of concept to say how can we link all of these tools together to answer these kind of questions.
We're actually moving forward to answer them on a longer term over a wider area. But what you get here in
Milwaukee, and this is looking at sulfate, that yellow piece of the pie, is that, and I'd like you to focus your attention on
the red line and the blue line. The blue line is current conditions, 2008, base case. The red line is with the planned
improvements as well as the efficiency in the renewable portfolio standards. So if you look at the red line
and the blue line, through much of this month they're really indistinguishable. So it's not like this reduction
just has a small effect throughout the year. No. They're almost indistinguishable
except in certain periods. Like here around the July 6th through 7th we see the most notable difference where the
planned improvements and the additional improvements under this policy really reduce the concentrations of sulfate over
Milwaukee by quite a lot. And there are other periods, we marked them with gray on this chart, where we do see the
larger differences between this what-if scenario and business as usual. So then we said, okay, this is
great, this is sulfate, this is one piece of the pie, but what about the total PM? That's what we're concerned
about, that's what the American Lung Association is grading us on, and that's what's affecting public health.
And so what we find, again in this one month in Milwaukee, is that on the days that we saw the biggest change in our two
scenarios, that the air pollution tended to be not the dirtiest of the dirty, but certainly not the cleanest of
the clean either. That it tended to be these sort of middle days. This would be yellow on our air
quality index framework where we saw the biggest change in pollution. So we thought to ourselves this
is interesting for Milwaukee, what about across the whole region and across the whole state?
Do these measures make the dirtiest days cleaner? That's what we'd hope. Or do they just make the
cleanest days a little bit cleaner? So what we did is to first look at right now across the region
how many hours is the PM2.5 above 15? 15 is the threshold where you move from green into yellow
on our air quality index. And so how many hours in the month have pollution above that level?
And so out of 744 hours in the month of July, we had, across the region, many places that had over 250 hours above that
threshold and then some regions that were even above 350, so had almost half of the hours in the month above that cutoff value.
In Wisconsin, we're doing a little bit better. Most of our area has somewhere between either zero or in the
southeast and northeast parts of the state between, say, 10 and 200 hours that are above that health-based threshold.
So this is the number of hours that we have bad air. Are we doing any better with these scenarios?
And the answer is yes. We actually saw, just with these pretty modest changes, that we're having somewhere around 5
to 10 fewer hours in the month of July of bad air. And what this actually means when we start doing some
percentage calculations is that across much of the region, and this is the plot on the right, in Wisconsin we actually have
about half the state seeing 5% to 20% fewer hours of unhealthy air. And that's a pretty big
punchline considering that these policies were designed without even thinking about these sort of free benefits to public
health. So there's some lessons learned from this kind of analysis. First of all, that even simple
clean energy policies that didn't even consider air pollution can still yield big benefits.
But, of course, if these are the benefits that we kind of got accidentally from the way that the renewable portfolio standard
would be implemented across the state, the benefits to air quality could be much greater if energy policies and climate
policies were designed to coordinate management of air pollution, energy strategies, and climate change.
And so hopefully those air pollution people on one side of the room and the energy and climate people on the other side
of the room actually start talking to each other more because when we're spending so much to regulate air pollution
it just doesn't make sense to not be integrating that with our energy planning decisions. And even in our Wisconsin's case
state, the changes that are concentrated in northeast Wisconsin end up affecting the Green Bay area, which we already
saw was ranked as number 23 by the American Lung Association for exactly this type of thing, short-term particle pollution.
And in Green Bay about 9% of the population has asthma and about 27% has heart disease. So this is not a negligible
issue to benefit those citizens just of that one city. So a 10% reduction in short-term bad air could make a difference.
So as we move into-- These models are very powerful, but as we've seen, they're not perfect.
And so of course there's an interest of bringing to bear as many new tools and data as possible.
And a really exciting area that I'm getting involved in now is to be linking satellite data with air quality management.
And in fact, NASA has just put together what they're calling the Air Quality Applied Sciences Team.
It's a five-year project and it just is starting this month. And so I'm one of 16 researchers across the US who's a member of
that team, and it's going to be very exciting to move forward and try to link these space and the final frontier data sets
with real world decision-making and air quality management needs. What I'm showing you here is one
example of the kind of work that we're doing where on the upper left panel are viewing these invisible air pollutants, we
can't see them with our eyes, but the satellites can see them from outer space. So this is seeing NO2, one of
those pollutants we've mentioned a few times today. And of course we see that NO2 is highest in population centers
like the eastern United States and parts of the Midwest, but we also see that in pretty rural areas, like even in the western
United States, where there are rail lines and where there are a lot of trucks on the road, you can see that pollution from the
satellites from outer space. And, again, this NO2, this is invisible. So seeing these patterns is
really cool. So I'm just going to give you a foreshadowing of what you'll see in the next three weeks.
The kind of work that I've been talking about here, using computer models, satellite data, ground-based measurements, is
very typical of the kind of work that my colleagues and I are doing at our center SAGE. And whereas my work focuses on
air quality, others focus on public health, urban environment, agriculture, water, climate, energy, and the links
between these. So I think that the next three talks should be really a treat. You have some great speakers
coming up. And you're very welcome to check out our website which is SAGE.wisc.edu.
We're part of the Nelson Institute for Environmental Studies and I'm a professor in the Nelson Institute and so
these broader scientific approaches really fit into broader themes of conservation and education and awareness.
That's one reason why it's really a delight to be here with you this evening. So thanks very much and I'm
happy to take any questions. [APPLAUSE]