- Welcome, everyone, to Wednesday Nite @ The Lab.
I'm Tom Zinnen.
I work here at the UW-Madison Biotechnology Center.
I also work for UW-Extension Cooperative Extension.
And on behalf of those folks and our other co-organizers,
Wisconsin Public Television, Wisconsin Alumni Association,
and the UW-Madison Science Alliance,
thanks again for coming to Wednesday Nite @ The Lab.
We do this every Wednesday night, fifty times a year.
Tonight it's my pleasure to introduce to you
Tracey Holloway.
She's a Professor of Atmospheric and Oceanic Sciences here.
She's also with the Nelson Institute
for Environmental Studies.
She was born in Evanston, Illinois,
and graduated from New Trier High School.
She got her undergraduate degree in Applied Mathematics
at Brown University, then got her PhD
at Princeton University in Atmospheric and Oceanic Sciences.
Did a post-doc at Columbia and then came here in 2003.
Tonight she gets to talk with us
about, "Every Breath You Take:
"The Past and Future of Air Quality in The United States."
Please join me in welcoming Tracey Holloway
back to Wednesday Nite @ The Lab.
(audience applauding)
- Thank you so much.
And thank you, Tom, for that lovely introduction.
It is such an honor to be here tonight
at Wednesday Nite @ The Lab talking about my favorite topic,
which is air quality in the US.
And I hope that by the end of this evening's talk
that you might find it to be a pretty exciting topic too,
because even though here in the United States
we've been regulating air pollution for public health,
and visibility, and clean lakes,
and healthy plants going back to 1970 on a national scale,
and before, back to the late 1800s in individual cities,
it's a topic that a lot of people don't really think about
when they think about environment and energy issues.
But really, air quality is fundamental to our public health,
to our energy systems, and to our environment.
And I think we'll have a lot of fun tonight
digging into some of the issues.
I'll start out with kind of a dark, hard to see slide,
but if you look carefully you'll see John Lithgow.
He's peering out of a window in London
in 1952 on December 7,
in one of my favorite mini-series from Netflix, The Crown.
If you watched The Crown you may remember,
I think it's Episode 4,
which focuses on a major air pollution event in London.
There's a reason that this air pollution event
was such a big deal that they devoted a whole episode
of The Crown to its discussion.
It's because it is really one of the hallmark episodes
of air pollution that was a catastrophe for public health
in London at that time.
One thing about this
extreme air pollution episode in London,
which still characterizes air pollution around the world,
is that when we're thinking about what makes
for bad air there are two key issues.
One is, what's being emitted?
What's the flux of chemicals into the air?
The other is, what are the weather conditions?
You need have a perfect storm,
where you have chemicals being emitted into the air
and weather conditions that trap those chemicals
over a city or a community so they can't just mix away.
The reason that this air pollution episode
occurred in London in December 1952,
was because they were already emitting a lot of smoke,
sulfur dioxide and other pollutants.
This is an actual picture of the London smog of 1952.
And there was a weather system that came in
and trapped the pollution in place.
We can see from the data from that episode
just how definitive this air pollution event was,
and the associated public health impacts.
If you look at this figure,
which is from data taken in the 1950s during this time,
and published shortly thereafter,
you see three different lines on the plot.
The red dots represent smoke.
So, just how much smoke is in the air.
And in London in the 1950s,
no day was a perfectly clear day,
but on average you had about 400,
a little less than 400 micrograms of smoke per meter cubed.
The blue triangles represent sulfur dioxide,
because in London they got a tremendous amount
of their electricity, and energy, and lighting,
and home heating from coal back in the 1950s.
And coal is a fuel that contains sulfur
along with carbon and other elements
that are naturally occurring in the coal.
So when you burn it, it emits smoke,
it emits carbon dioxide, and it emits sulfur dioxide
and other pollutants.
So, when the weather trapped the smoke
it also trapped the sulfur dioxide.
So you see the sulfur dioxide compounds rose
exactly in sync with the smoke.
But, what's different here is the green,
that line at the top, the little squares.
These are the number of deaths that occurred in London
during this event.
And what the line shows,
if you look at the early part of December,
is that on your average day in London
around 300 people might die.
These were people who might have had a heart attack,
or gotten sick, or had been hit by a bus, who knows?
What we seek is that then as the air pollution builds up,
that the number of deaths per day doubles from 300 to 600
and then again to 900, before it slowly begins to come down.
And even when the air pollution
has cleared back to its standard levels,
the average number of people that die each day
is still quite a bit higher than it was before the smog.
This is because when people get sick
during a high-pollution episode,
they may be sick for a few days before they die.
So, I really like using this graph
when I am teaching in classes and giving public talks,
because the basic idea here is that we know air pollution
is bad for people's health
because we can see it in the data.
In many parts of the world, thankfully,
the relationships are not this extreme.
There's a lot of things that determine
when kids go to the hospital with an asthma attack,
or when someone reports
a heart attack in the hospital records.
But statisticians, epidemiologists
compare these health records with air pollution records
to kind of back out what is the risk of air pollution.
Individual air pollutants in individual cities
have different risk factors,
but the basic idea ties back to the same idea
shown here from 1952 in London.
Moving forward from the smog of 1952 in London,
we continue to see episodes of bad air pollution
in the United States, but we also see great improvements.
In many ways air quality is an environmental success story.
The air has been getting cleaner and cleaner,
and especially in the US, where we have some of the most
aggressive air pollution regulations in the world.
What I am showing here is 1988 in New York City.
Here's 2011 in Milwaukee.
Here's 2014 in Pittsburgh.
What's notable about all of these pictures
is that you can see the pollution in the air.
Anytime you can see air pollution
you're really dealing with what's called particulate matter,
or PM.
Most gases, really every gas that's in the atmosphere
at typical concentrations, is invisible to the eye.
So, anytime you're seeing air pollution,
it's liquids or solids that are suspended in air.
These could be made of directly emitted smoke
from a barbecue or windblown dust,
but they also are often made of chemically-formed particles,
so that that sulfur dioxide
cooks up to make sulfate particles.
Invisible nitrogen oxides cook up to make nitrate particles.
And these chemically-formed particles
and the directly emitted particles
both contribute to the haze that we see.
But just like in London, we don't see this kind of pollution
every day in most parts of the US.
It really depends on whether the weather conditions
are in place to trap the air pollutants or cook them up.
When thinking about air quality, here in the US
we think about two big categories of pollutants.
One category is called air toxics,
and these are also known as hazardous air pollutants.
Air toxics include about 187 different chemicals
that are associated with cancer, neurological disease,
birth defects, and other issues.
For these pollutants there's no safe level,
so they're regulated mostly on an industry-by-industry basis
to minimize the health risks.
But there are six pollutants that are really the ones
that you think of when you think of air quality,
both in the United States and around the world.
These are the most wanted pollutants if you were
to imagine them on the wall of the FBI.
These include carbon monoxide, lead, nitrogen dioxide,
ozone, particles, the ones that you can see,
and sulfur dioxide.
And I won't go into the levels here
except to say that since 1970, the EPA has set a limit
for each of these six pollutants.
That's kind of like a class where there's
a level where there's a passing and a failing grade.
And every county in the United States
that measures air pollution has the pollution compared
with this pass/fail level, and it's determined to be either
passing or failing the standard.
So, if you've ever lived in a place
where you had to take your car to be emissions-tested,
that has been because it was a county
that was failing in the ozone standard.
Not every county that's failing the ozone standard
has vehicle testing, but it's pretty typical.
My parents live in Chicago and they've been taking their car
to be emissions-tested for many years.
I lived in New Jersey, emissions-tested.
My sister lives in California, emissions-test.
All of those are above the federal standard for ozone.
Depending on the pollutant,
the impacts of a county failing the standard
may be different.
It may affect how industries can file for permits,
or how power plants can expand their facilities.
So these are really big issues that affect a wide range
of industries in Wisconsin and across the United States.
The policies that we've had in place though,
are really working.
Air pollution has been coming down, down, down.
This plot shows going back to 1990.
And the dash line is showing the pass/fail limit
for each of the pollutants.
What you see is that today every single pollutant,
on average, is below the line.
We're in the clear in most areas on average for everything.
Now there are still select counties
that are above the standards for PM2.5,
the tiniest of the particles for ozone,
and to a lesser degree for sulfur dioxide,
and some of the other pollutants.
But overall it is a clear downward trend.
And since 1990, lead has decreased 99% in the air,
mostly due to unleaded gasoline becoming the norm.
Sulfur dioxide has decreased over 80% since 1990,
mostly due to scrubbers on coal-fired power plants,
and a growing role of natural gas
for electricity generation.
Carbon monoxide has gone down by nearly 80%
due to cleaner burning cars and trucks.
And really, we could go through the list.
They're all going down, down, down.
Another way to look at how
air is getting cleaner in the United States
is to compare with satellite data.
Satellite data is one of my favorite sources of data.
I'm not sure if everybody has a favorite source of data,
but mine is satellites.
And what you're seeing here is a yearly average of NO2,
one of these invisible gases,
taken over the United States in the year 2005.
Now the reason I show 2005 is because this data
is from a satellite called the Aura satellite.
The Aura satellite was launched by NASA in 2004,
around the summertime.
Each satellite contains lots of different instruments.
One of the instruments on board Aura is called Omi, O-M-I.
Omi measures a whole bunch of different gases
and particles in the atmosphere.
NO2 is especially useful
because the images are pretty clear, as you can see,
that's not too noisy, and because NO2 is emitted by cars,
trucks, power plants, forest fires.
Anything that burns emits NO2.
So when we see these patterns in NO2,
it's a really good tracer of other types of air pollutants,
a lot of different types,
and also human activity and energy use.
What you see here in 2005 is you can very clearly
see the major cities, Chicago, New York, Los Angeles.
You can see in Indiana and Ohio the high levels of NO2
associated with electricity production.
A lot of US power plants are located
in the Ohio River Valley,
and these power plants are a major source of NOx.
You also see some power plants in the western United States,
where otherwise it's pretty clear.
There's a lot fewer people out there.
And some interesting patterns like,
you may not be able to quite make it out,
but in southern Idaho there's a line
that stretches across from east to west,
and that runs right parallel with trains
burning diesel fuel, and with a major highway
where there's a lot of trucks and cars.
What's great about this is that these satellites
take a snapshot of the entire Earth every single day.
So this is showing what the US looked like in 2005,
and here's what it looked like just five years later in 2010.
I could show you 2015 and it would look even cleaner.
In fact, over the ten-year period between 2005 and 2015,
many cities in the US had 40% or more of a reduction in NO2.
This is really due to cleaner cars, cleaner trucks,
cleaner power plants, cleaner energy.
To give you an idea of how the US compares
with other countries in terms of our clean energy,
one way to think about it is how clean our cars have to be.
This and the next couple of plots
are taken from an International Energy Agency report
that I'll show you at the end of this talk.
But if you've ever dreamed about importing
a sports car from Europe,
you might have had it cross your mind,
that you can't just go to Europe, buy a car,
and bring it to the US.
The reason is that here in the US,
we have some of the tightest vehicle-emissions standards
in the world.
That is why our air is getting so clean.
This is ranking many major countries in terms
of how clean their standard is for light-duty vehicles,
that means cars and small trucks.
The US and Canada have, you know,
something stricter than the strictest rule in Europe.
Europe, Japan, Korea, Australia are in the same zone.
Turkey, China, Russia, Brazil, Argentina.
And then India is less strict.
Mexico, Indonesia, South Africa, and Saudi Arabia.
So every country sets their own policies on how clean
they want their car engines to be.
And the US, we're one of the cleanest.
Another way to look at this,
that was looking at light-duty vehicles especially,
but diesel is used for trucks and buses.
In many parts of the world diesel is used as a common
fuel for cars and electricity production.
But one of the questions is,
how much sulfur is allowed to exist in the fuel?
In the US we have some of the lowest allowed
sulfur diesel levels,
especially compared to other parts of the world.
All of these rules and others
contribute to relatively small energy emissions.
Here now we're looking at particles,
kind of the smoke that you've seen coming sometimes out of
trucks or off a barbecue.
And you see that in the United States our little pie
is quite small compared to many,
to the rest of the world.
Now that's interesting because in the US
we use a lot of energy.
We use about twice as much energy as the average person
in Germany, about five times as much
as the average person in China.
That we could be using so much energy
and yet having clean air is really the evidence
of this big investment that the US has made.
There's different ways of counting up the benefits
of this investment in clean air.
One is by thinking about how many people didn't die,
or didn't get asthma,
or didn't check into the emergency room
because of policies that were put in place.
The first binding policies for the US were in 1970,
but there was a big sweeping addition in 1990,
the 1990 Amendments to the Clean Air Act.
This is, you don't have to pay attention to the numbers,
the kind of benefits that you expect to see
from these investments in clean air.
You expect infant and adult mortality to go down.
You expect chronic bronchitis to go down.
Heart disease to go down, asthma down.
Emergency room visits are going down.
Fewer days lost of school, fewer days lost at work.
And that's exactly what we find.
But the funny thing about air quality is that
it's very hard to know who specifically benefited.
And I think this is one of the reasons why people
aren't as aware of the benefits of air pollution control
is because when somebody has dirty water,
you know who had the dirty water.
You can see it.
You can probably turn on their tap and measure it.
It's very clear the specific person who benefited
from clean water or was adversely impacted by dirty water.
With air it's different.
We just saw in London in 1952 that the number of deaths
went from about 300 a day to 900 a day.
But if you were to find one person who died,
would that person maybe have died anyway?
It's really hard to say.
My sister lives in Los Angeles,
and after moving to Los Angeles, developed asthma.
Would she have developed it anyway or not?
It's really hard to tell.
Now the idea that more people in Los Angeles have asthma,
and that you are at higher risk when you're exposed
to higher levels of air pollution, that is a fact.
But pinpointing the specific people is different.
It's more of a statistic population way to.
We know that they're saved, we just don't know who they are.
And when you translate these benefits into dollars,
the benefits are huge.
This is really because in the US we value,
we spend a lot to be safer, we spend a lot to be healthier.
We'll pay more for a safer car,
we'll eat kale and invest in expensive vitamins
to be a little healthier.
Anything that we can do that's going to extend our life,
and improve the quality of our life
is something that we put a lot of money in.
If you add up all the money that we put into
each increment of improved living,
it ends up being about $6 million per person.
So the value of avoiding death is,
in the US, ballpark $6 million.
So when we can avoid the adverse impacts of air pollution,
that adds up very quickly to high amounts of money.
To put this in sort of a news-you-can-use framework,
another statistic that I like came from a study
at the Harvard School of Public Health.
They looked at different cities across the United States
and controlled for smoking, and income,
and access to healthcare.
And looked at how long did the people live in those cities.
They found that for the cities that had,
I'm going to say 10 units,
and I'll come back to the units in a second,
but for every 10 units cleaner air
that one city had over another,
the people in the cleaner city
lived about seven months longer.
These 10 units, right now the standard for
our annual average PM2.5 is 12 micrograms per meter cubed.
So when we are saying 10 units on average,
it's 10 micrograms per meter cubed,
meaning that if it went from 22 micrograms to 12 micrograms,
that on average people would live seven months longer.
It is not uncommon in many parts of the world to have PM2.5
in the hundreds of micrograms per meter cubed.
So here in the US if a city,
or if a monitor anywhere reads higher than 35,
it's sort of a ding, ding, ding,
that's too high, period.
But on a day-in-day-out basis
we want it to actually be lower than 12.
To get this level of clean air we spend a lot of money,
on average about $50 billion a year.
That often comes in the form of how much
you're paying for your electricity,
how expensive your car is.
That's why you can't go to Germany
and pick a car and bring it back here.
But the benefits are in our health.
Now I want to bring you into my lab
here at the University of Wisconsin-Madison,
because I work with a team of students
and professional researchers
to tackle some of these questions.
What we are interested in knowing is,
what controls air pollution?
How do different energy strategies lead to clean air?
How can we use satellite data
and other new tools to do better science
and have better information to give to decision-makers?
And how do all of these complex weather
and energy and chemistry processes feed together?
What I think is really exciting about this
is that it let me works with students
from all across the campus,
from Engineering to Public Health,
from Geography to Chemistry.
It's a lot of fun but it's also a really effective way
of tackling some of these complex crosscutting issues.
My lab at the University is in the
Institute for Enzyme Research.
There's actually no enzymes used in our research at all.
But here on campus, like many universities,
buildings were sometimes named
for what they were first used for,
or what they're mostly used for,
and we're very happy to have
the Enzyme Institute as our home.
We do a lot of goofing around,
but actually this was a bit of an old picture,
and now my lab has about 15 or 16 people in it,
most of whom are undergraduates.
In this picture, which is actually omitting
some of the students in my lab who don't yet
have their pictures up on our website,
most of the top two rows are undergraduates.
I have three graduate students,
a professional researcher who does the computer modeling
and scientific data analysis, Monica Harkey,
a PhD in History who helps with our communications
and outreach and writing, Daegan Miller, and then me.
One way that I like to think about research is,
where does the idea come from?
And the typical approach in science is for a scientist,
a professor, a researcher in a lab
to be sitting and just have that eureka moment,
Aha, or to come up with just some question out of thin air
to spend their time studying.
This is typical, where the research idea
comes from a scientist, they do the work,
they publish it in peer-reviewed journals
that are really not very easy to read.
And if they're lucky, maybe it's covered by a press release,
or covered in a news magazine to reach the public.
But my group and I
tend to take a more applied approach to research.
We figure there's so many important questions
out there in the world that need to be answered,
why should we just be dreaming up questions out of the blue?
So we like to work with users,
whether at the Department of Natural Resources, or the EPA,
whether at private companies or non-profits,
whether cities, or counties, or countries
that we engage with and ask them,
what do you need to know?
What would be helpful to you?
Working with different people who actually are working
in air and energy fields,
finding out what are the open questions
that really need to be answered,
using that to develop a research plan,
yes, writing the research publications,
but also thinking about what are useful outcomes
for other audiences.
Not everybody needs a research paper written.
Some people like to have data given that they can analyze,
images for a report, a finding that can help them
make a decision.
So we try to deliver the research in traditional means,
but also means that can reach new audiences.
Once we document the success,
we try to share the work that we're doing,
building awareness, forging new relationships,
getting new questions.
A cycle.
There are three tools in our toolbox
that we use to answer these questions.
But before I begin talking about the tools in the toolbox,
I'll just give one example of this kind of cycle
of question and answering.
I spoke at a meeting for the Western US states
a couple of years ago, and I was talking about
satellite data and how effective it could be
for answering different air pollution problems.
The reason I was talking about satellite data
is because for the past few years
I've been involved with efforts at NASA
to make satellite data more usable by different communities.
There's been hundreds of millions of dollars
invested in advanced satellite technology,
but often it isn't getting used by all of the people
who could use it.
So in 2011 NASA set up a team called the
Air Quality Applied Sciences Team, or AQAST,
and I was the deputy leader of AQAST.
AQAST was trying to be a front door to connect NASA
with the people who are interested
in air quality, air pollution issues.
Because if you were somebody who worked on air pollution
and you thought I want to use satellite data,
who do you turn to?
It's really hard to know where is the front door.
So AQAST was trying to be that front door
and part of that was going and talking to potential users
who would be interested in this
and meeting them where they are already working.
So I was very happy to go out to Denver, Colorado,
and give a talk to Western US states
who were meeting on a once-every-couple-of-years basis
to trade information,
share insights, learn from each other.
At that meeting, in the elevator,
I met an air quality manager from a major city
in the Western United States.
He said, you know, I really liked your talk.
I'm thinking maybe we could start using satellite data.
I said, yeah, great idea!
So I actually went out to visit about three months later,
and I gave a talk to he and his colleagues.
They were interested.
They had not heard about how satellite data
could be used for air quality before...
but that got him thinking.
He said, you know, I'm not sure.
Without getting into all the details,
he said, I've run the numbers.
I've looked at some of the data you showed me,
and I'm just not sure that it will work for our city.
I looked at his numbers and I said,
you know what, I think you're right.
We need to look into how the satellite data
really should be used in your city.
We don't want to be over-selling.
The whole point is to try to get good science
into the decision process.
If it's not the right tool, well,
let's go back to the drawing board,
let's try to improve it,
but if it doesn't work it doesn't work.
And who knows better than somebody where his whole life
is focusing on air pollution in that city?
So actually I've come back to Wisconsin,
and I'm working with undergraduates to help address
the specific questions that he pointed out
and keeping him in the loop as we're doing that.
So just as an example of the loop.
And the students love it because they really want to work
on questions that matter.
I think a lot of students don't like the idea of research
because it sounds esoteric.
It sounds kind of like you're just working
on one little project at a lab bench.
But actually a lot of the research,
not just in my group but all across
the University of Wisconsin,
is addressing some of the biggest problems
that are facing humanity.
And so the students to be looped into it in a way
that they can clearly see.
They've heard that it was a problem,
they can see how their work is going to contribute,
and then they're excited to get to work.
So there are three toolboxes that air quality
and health managers use for looking at air pollution.
And if these are the three toolboxes
that the professionals use, they're the three toolboxes
that I want myself and my students to use
so that we're best able to interact with the groups
who do this for a living.
One approach is direct measurements.
Just to show you what we're talking about,
we're talking about instruments that are out on the ground,
across the United States that are actually measuring
what's in the air.
Here in Madison, Wisconsin, our main monitoring site
is a big trailer behind East High School.
But there are monitors across the state,
and I'll show you a map.
This is actually a map of monitors that measure PM2.5,
those tiny particles that are bad for our health.
And you can see from this map that there are
a lot of monitors in the eastern US,
and a lot of monitors in California
and the Pacific Northwest.
The Great Plains has fewer monitors.
But this plot is taken from one of my favorite websites
which is airnow.gov, airnow.gov.
And it is put up by the EPA to show you
what is in the air, now.
So I pulled this plot off just about two hours ago,
and this is showing that across most of the US
the monitors are showing green.
We are well below the threshold for health-damaging PM2.5
according to the standards.
But in the eastern United States the dots are yellow.
This is the moderate zone, showing that we're above
what's considered good for a yearly average,
but we're still below the red-light zone for a daily limit.
So we're between 12 and 35 in the yellow.
There are no orange dots that I can see on the plot,
but there is one red dot in the unhealthy zone,
which means it's quite high above 35,
and that looks to be somewhere in California
and probably is due to a local fire.
I had a colleague once who said
that the reason he liked studying air pollution
was because every day was a science experiment.
I feel that way often when I look at the data on airnow.gov,
but when we're trying to see how healthy
our air is over all, the question isn't what it is today,
what it is this evening.
But the question is, if we look across the year,
how many days did he get really high?
And on the days that it got high, how high did it get?
Here is a plot of ozone.
Now this is a different pollutant.
This is an invisible gas in the atmosphere,
but it has many of the same health impacts as PM2.5.
What you are seeing here is the first of all the location
of ozone monitors across Wisconsin.
What you're looking at is a metric called the Design Value.
That's kind of nerdy, but it's showing
on the fourth-highest day how high was the ozone,
on average, across these three years.
Because just like in baseball where you have
three strikes and you're out,
for ozone it is four strikes and you're out.
They don't pay attention to the highest,
the second-highest, the third-highest.
Okay, those are,
you can take those strikes.
But the fourth-highest is the one they zoom in on
to determine whether we are passing or failing
the federal allowed standard for ozone.
And what this plot is showing is the green dots
are where this average fourth-highest value
is below 65.
And that is well in the green zone because the standard,
I should focus on that, that's at the lower-left corner.
The current standard for ozone is 70 parts per billion.
Seventy is the pass/fail limit.
This was just implemented in 2015
and is not yet being enforced.
We are still in the process of regulating
based on the 2008 standard of 75.
One of the reasons why the newer standard
isn't being enforced is that you need three years of data,
and that was just passed in 2015.
But this is color-coded and you can see whether
it's passing the 70 or the 75.
The green is in the clear for both standards,
and that's across the northern part of the state,
and most of the inland art of the state.
But as you get close to Lake Michigan
we see quite a few dots that are red,
that are between 71 and 75,
meaning that all those dots that are red
are failing the new standard,
although they would have passed the old standard.
Then there are a few dots at Sheboygan and Chiwaukee Prairie
that are higher than 75, meaning that they would be failing
even the old and the new.
This idea that the standards are getting tighter and tighter
and pose new challenges for industries
to meet these air quality regulations
is something that there are a lot of people
who could argue about that,
because on the one hand it's improving public health,
on the other hand it is very expensive
to meet these regulations and poses costs to industries
that are having to pay high electric bills,
or buy fuel or things like that.
Kind of leading up to, back to why I love satellites,
here we have a lot of great data,
but there is much more of the state
that doesn't have a dot than does have a dot.
Most of the the US has no monitor,
most of Wisconsin has no monitor.
So just like if a tree falls in the forest,
and no one is there to hear it does it make a sound?
When you have a county with no air pollution monitor,
and it's a high air pollution event, it does not register.
Nobody knows about it.
So when it comes to satellites, they can fill in the gaps.
They're not as good as ground-level monitors
for many different reasons.
One is that they're mostly once-a-day measurements
rather than all-day.
They don't measure all the different pollutants.
They don't see the surface where we're breathing,
they kind of see more the columns.
But when you're choosing between having no information
from a measurement source or a satellite data,
they can really be a nice complement.
Actually here at Wisconsin,
we are a hot-spot of satellite data to study the atmosphere.
And not just air pollution.
The whole idea of studying weather
and atmospheric processes
with satellites is something that was developed
here at Wisconsin with Verner Suomi,
and continues to be a huge strength of the university
on a global scale with our
Cooperative Institute for Meteorological Satellite Studies.
When we're thinking about air quality,
there's a collection of satellites
that are producing information that we can use.
And I mentioned AQAST,
that was the Air Quality Applied Sciences Team.
Just this past summer in 2016,
NASA launched the Health and Air Quality
Applied Sciences Team, or HAQAST.
And this is a national team of researchers
now trying to connect satellite data and other NASA tools
with health and air quality stakeholders.
I'm the leader of this national team,
and there are 12 other researchers from across the US
and a wide range of institutions.
We're actually meeting next week in Seattle
at the University of Washington in Seattle,
where a big part of our mission is to hear
from potential users who could use satellite data,
who might use satellite data who are using satellite data,
and trying to say, what are your research questions?
And how can we answer those questions?
Outreach has been a big part of our activities
with AQAST and HAQAST.
We have been doing research on those trends in NO2
that I showed you earlier, how it's going down in the US,
but up in many other countries.
And actually one of my colleagues from AQAST, Bryan Duncan,
was on CNN a couple of years ago talking about this.
We were actually really thrilled that the Discovery Channel
then picked up on some of this research with NO2,
and asked former President Obama to discuss
how air pollution in the US compared with other countries.
And he did so by talking almost exclusively
about satellite data.
Because satellite see the entire world,
you really can compare different areas
in an apples-to-apples fashion.
If you are interested in that 60-second Discovery clip,
you can find it at tinyurl.com/obamaNO2.
I'm going to talk for just a few seconds about an example
of the kind of research that I'm doing here
with an undergraduate named Elise Penn.
One of the things we were interested in
is how representative the satellite data
was of NO2 on the ground.
We see that it's going down. That's great news.
But the problem is the best satellite that's up there,
the best instrument up there,
the OMI instrument on the Aura satellite
only passes over in the early afternoon.
If you look at NO2 at the surface,
what we find is that that early afternoon time period
is the minimum NO2.
What you're looking at here is the hours of the day
from midnight to midnight.
You can just look at the top two panels.
I should have removed the lower ones.
But if you look at the top two panels,
you see that in the urban areas, the red line,
it goes up in the morning, down, then up.
Same happens in suburban, same happens in rural.
That's really mostly due to rush hour traffic
combined with the way
that the atmosphere moves during the day.
So the OMI satellite instrument passes over
in the early afternoon.
But we were wondering if maybe by
comparing with another satellite,
this one from the European Space Agency,
we might be able to see the change in NO2
over the course of the day.
When we took the difference between these two products,
what we saw was really remarkable.
We could see rush hour traffic in the satellite data.
And it's not super obvious,
especially with the color schemes
that you're seeing right here,
but in many cities what we see is a bull's-eye,
where the satellite that is in the morning
shows higher NO2 in the suburbs,
and the satellite in the afternoon
shows higher NO2 in the center of the city.
We see this in Phoenix, we see it in San Diego,
we see it in Chicago, in Philadelphia, and Houston.
You can zoom in on these individual cities.
We also see that power plants,
especially in the summertime in the Western US,
are higher in the afternoon when these power plants
are cranking to meet that air-conditioning demand.
And what we found is that, actually,
if we looked at the cities that we saw
where the rush-hour traffic patterns
popped up in in the satellites,
these were the same cities that the US Census Bureau
finds have the most commuters commuting
from the suburbs to the inner-city.
So that was pretty cool that this pattern
that popped up with the satellites is something
that is consistent with what we would expect
from rush-hour traffic,
but it's something we would not have been able to see
with monitor data because there aren't enough monitors.
So that was one kind of neat study that we did.
But the third tool in our toolbox is computer models.
Tom mentioned that my undergraduate major is applied math.
In applied math some people focus a lot on statistics,
but other people focus on calculus.
I am a calculus person.
I love calculus.
One of the reasons I love calculus
is that it is the science of change.
What is a derivative but it is showing change.
And if you want to look at how things are changing in time,
it is the derivative with respect to time.
But if you're trying to solve equations
that have derivatives, it becomes really complicated,
and most of the time you can't solve it
with a pencil and paper.
You need a computer.
So the whole idea of computer models
to study the atmosphere is based on the idea
that we can use physics and chemistry
to write differential equations, as they're called,
equations with a derivative,
and then use computers to solve them.
And the kind of chemistry and physics
that are in these computer models
are the emissions of chemicals into the air,
how weather patterns move them around,
specific chemical reactions that occur, rainout.
And what we are interested in is how do
all of these processes combine to create
high or low levels of air pollution at a particular place
on a particular day.
I haven't talked very much about
all the different chemical processes that go into play,
but as one just quick example,
we talked about ozone in Wisconsin,
and how we're passing standards in some places
and not in other places.
But ozone is not directly emitted.
It cooks up in the atmosphere from two big ingredients,
NOx and VOCs.
So to understand where the ozone is going to be high
and where it's going to be low,
we need to take a count of chemical reactions
involving NOx and VOC reacting with hydrogen,
and oxygen, and sunlight.
It's really fun chemistry but it's hard to do
without a computer model.
Just as one example of the kind of questions
that we have answered with these computer models
is one study that is just tying up right now
from a graduate student of mine, David Abel.
We worked with the National Renewable Energy Laboratory
to answer a basic question,
how much would solar electricity improve our air?
Surprisingly, it is really hard to figure out
how energy efficiency, wind energy, or solar
will really play out in terms
of cleaner air and public health.
So we worked with the National Renewable Energy Laboratory
to use some of their fancy electricity models,
and used those to calculate what power plants
are going to change their generation, when and where,
if we had more solar.
Then we translated that into changes
in sulfur dioxide and nitrogen oxides.
We spent some time to look at how much of the change
was coming from changes in coal versus natural gas,
and where and when these are occurring.
And then we dumped them into our computer model
with the weather and the chemistry included,
so that we could figure out where these little particles
in the air cooked up, in this case looking at PM2.5.
And the first thing we want to do is look at
what is the business-as-usual case.
Create a computer model that has everything included,
compare it with observations to make sure
we are in the right zone of reality.
But once we have a computer model that looks right,
then we can use it to test things
that we could never test in real life.
So, we took our computer model
and then we just waived our magic wand and poof,
20% solar electricity across the Eastern US.
And we found that it decreased PM2.5 pretty much everywhere
across the Eastern US and in some places
over 10% on average.
Some places almost 15%.
But what we're really interested in
is not just what's happening on average,
but what about those dirty days?
Is solar electricity making the dirtiest days cleaner?
And what we found is, yes.
The greatest benefits from solar
happen on the dirtiest days.
So we looked here at a few different cities,
Indianapolis, Columbus, Philadelphia, Chicago, and New York.
Each one showed a somewhat different relationship
between the benefits of solar
and the reductions in particulate matter,
which are mostly in the zone of five to 15%.
But it was promising to see that,
at least in our computer model,
putting in solar energy doesn't just make
the clean days cleaner, but it really targets
those dirty days that are bad for public health.
As we wrap up, I wanted to leave you with a few resources.
If you're as excited as I am about air pollution
and want to go further,
some great online resources that may be of interest.
One is Our Nation's Air, which is a 2016 report from the EPA
and that's where some of those figures
that I talked about showing how air pollution
had gone down in the United States.
Another is a report from the International Energy Agency
that talks about global energy and air pollution
and how different countries compare.
Here in Wisconsin, the Department of Natural Resources
puts out an air trends report,
and has one that just came out at the end of 2016,
talking about how air is in Wisconsin.
And I added the URL of that report there
since it may be of particular interest.
And finally, I have written a lot of different things
on my webpage, but one that may be of interest
is in a blog out of Arizona State University called UGEC,
the Urbanization and Global Environmental Change,
on what's next for air quality in the United States?
I'll end with my favorite plot.
And it's really been a pleasure talking to you this evening.
Thank you very much.
(audience applauding)