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Charles Lee: Good afternoon, my name is
Charles Lee, I am the Senior Policy Advisor

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for Environmental Justice at the US
Environmental Protection Agency.

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We want to welcome you once again to the
second session of the Environmental Justice

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and Systemic Racism Speaker Series.

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We want to begin by sharing with you the
news of how this-- the topic of this series.

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It's really resonating with
members of the American public,

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one example of this is the fact that
more than 20,000 persons have registered

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for our first two sessions.

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We also want to make sure that you
have some important logistical information,

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and this relates to the question and
answer portion of the session,

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please, use your Q&A
pod to submit questions,

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and we will attempt to answer as many as
possible, including those we pose to our speakers.

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Our speakers today are Dr. Jeremy Hoffman,
from the Science Museum of Virginia

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and Dr. Vivek Shandas
of Portland State University.

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They are, among other things, the co-authors of
a 2020 study that correlates redlining maps

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from the 1930s with the current
location of urban heat islands.

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In my opinion, this study
is a harbinger of the future

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many other studies some of which they
in fact are working on will provide more

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evidence between systemic racism and
current environmental conditions,

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particularly those
related to the climate crisis.

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Their work speaks to the first
objective of this speaker series

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which is to provide information
that strengthens the evidentiary link

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between historical inequities and
current environmental conditions.

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Beyond this, our speakers will also speak
to how participatory community engagement

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lies at the heart of their work, please
advance the slide.

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I want to say a few words
to introduce the series.

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The series is predicated on the premise
that truly achieving environmental justice

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will require addressing systemic
racism and other structural inequities.

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Our objectives are and it bears repeating
again to provide information

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to strengthen the evidentiary
link between historical inequities

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and current environmental
conditions to inspire people everywhere

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to think about this question, to
align the best thinking available

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to create possible-- creative partnerships
and lastly to create the intellectual ferment

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necessary to effectuate truly
transformative change. Next slide.

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I want to show this slide quickly
to give everyone a mental picture

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of how environmental disparities have
their roots in systemic racism.

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Our colleagues at California EPA
overlaid the digitized redlining maps

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for the city of Oakland, California,
with the results of their environmental

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justice cumulative impact
mapping tool CalEnviroScreen.

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You can see the correlation
between those redlined areas classified

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as the hazardous and the worst
environmental disparities today. Next slide.

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I also want to quickly show this slide.

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Among other things, we work with states regarding
environmental justice integration training,

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and every time our colleagues
see the Oakland slide shown earlier

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they asked about how to develop these
slides or similar ones for their own states.

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Well, you cannot replicate that slide for
cities outside of the state of California,

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because CalEnviroScreen has
information only for that state.

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However US EPA's EJSCREEN
covers every part of the nation,

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and while it does not produce
a single cumulative score

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you can still do some mapping overlays
that reveal very meaningful information.

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Here, for example, is a map that overlays
the redlining maps for Richmond, Virginia

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and an EJSCREEN
respiratory hazard index.

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It turns out that one of our speakers
today is actually quite adept

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at the use of EJSCREEN and I will ask
Jeremy Hoffman to expand on this later.

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With that, I will hand it over to our
speakers, first to Jeremy,

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who will alternate with Vivek in
presenting the next set of slides.

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Jeremy Hoffman: Thank you so
much, thank you very much, Charles,

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and thanks everyone for your attention
this morning or afternoon,

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depending where you are in the country.

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And I want to kick this off by
giving the broader context around

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why we should care
about extreme heat to begin with,

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many of you may be surprised to
know or already know that extreme heat

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is the leading cause of weather-related fatality
in our country over the last several decades

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and it's a significant contributor to
summertime morbidity or illnesses

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though this has been shown to vary by age
and occupation and region in the country.

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Extreme heat, it disproportionately affects
those with underlying chronic health problems

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which are exacerbated by extreme
heat, things like respiratory cardiovascular

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and renal diseases as well as diabetes
and also underlying this-- these data

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on extreme heat mortality are the physical
characteristics of the built environment

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that may amplify extreme heat,
things like a level of social support

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or the neighborhood socioeconomics
and privilege, the characteristics

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of the individual housing itself and then
ultimately also access to air conditioning.

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All of which we know have structural
links to systems of oppression.

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And so if we go to the next slide, we
unfortunately learned a lot about these

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underlying indicators of
thermal sensitivity or inequity

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from the devastating heat wave that
occurred in Chicago, Illinois in the 90s.

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While this picture was being taken, just
a few miles away, I was growing up

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in a privileged middle class white
family in the northwestern suburbs of Chicago

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and in that second week in July in 1995, we
were having a yard party with slip and slides,

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and air conditioning and ice cream, I
remember having fun during this heat wave,

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but just a few miles away this photo
was being taken which showed the pain

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that was felt and experienced-- the
trauma experienced by many families

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on the south and
western sides of the city.

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And temperatures in Chicago
soared into the hundreds for multiple days

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you know temperatures didn't go down
under 80 degrees Fahrenheit overnight

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the air itself was stagnant polluted and
humid and rolling blackouts were caused

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by the extreme energy use and
pressure put on by people trying to use

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the energy to cool themselves down,
and then we even saw water pressure

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dropped in particular areas where fire
hydrants were open to provide relief,

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and this extended exposure to
heat set off a cascading disaster

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that disproportionately affected
elderly communities of color

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in the south and
west sides of the city.

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Over 700 people died and the
mortality was disproportionately felt

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in these socially fragmented and minorities--
minoritized elderly communities of color.

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This is detailed-- in magnificent and horrible
detail in Eric Klinenberg's book Heatwave,

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you can learn more about that
by reading that. Next slide, please.

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We also know that heat doesn't
express itself equally everywhere

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within human landscapes, and this is
determined by the underlying land use decisions

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that can either amplify or dampen
surface or skin temperature of the earth

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as well as the overlying air
temperatures.

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And this landscape which is just a picture
out of my office, here in Richmond, Virginia,

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looking out into a parking lot, we can learn
a lot about the thermal characteristics

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of land use decisions just from this
one picture, and a thermal camera

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can help us investigate that.
So please, go to the next slide,

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and we can see how much variation
exists just within this one picture.

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And you can see the dark asphalt
parking lot it absorbs more of the sun's energy

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throughout the day and into the evening
amplifying releasing that energy back

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into the air as heat throughout the
afternoon and into the evening

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the brighter temperatures or the brighter
colors here being the warmer temperatures

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on the flip side of that on the opposite
side of the spectrum are the big mature trees

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which provide those very the cooling
of the surfaces underneath them

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as well as the air that runs through them.

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And then everything in between, we learn
a lot about things like the surface

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the different types of building
materials that we might use,

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the colors of the cars determine partially what
the skin temperature of that surface,

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and then we can learn a lot
about the different types of plants.

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I could talk about this one
picture for a really long time,

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but what we don't have a lot of time to go
through it so what I will say is that

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we took thermal images from the LandSat
satellite in 100 urban areas around the country,

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and looked at those through the lens of
this historical races planning process

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known as redlining that may have
locked in this inequitable distribution

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of heat into our cities, and it's at this
point that I'll pass it over to my collaborator

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and mentor Vivek Shandas to tell you all about
the paper that we published back in January.

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Vivek Shandas: Great, thank you, Jeremy,
and thank you Charles, and the EPA staff

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for assembling this really really important
top, assembling this important topic

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and an opportunity to have a conversation
about getting ahead of some of this.

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So what I mean by getting
ahead of some of this is really

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building on what Jeremy had identified as
some of the lingering effects

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that had that occurs
as a result of heat waves,

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so in order to really
systematically study this,

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we don't have air temperature granular level
air temperature maps for the entire country

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though it's something we
are actively working on now,

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we do however have satellite imagery
similar to the infrared image that

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Jeremy showed of that parking lot, but
we wanted to do this at a city scale

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so we looked at a 108 different
cities across the United States

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using the University of Richmond's digitized
redlining maps for each of these 108 cities

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to evaluate the relationship between
whether to essentially to evaluate

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the relationship between the
heat that is present on the landscape

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in formally redlined areas in relation
to those that aren't redlined,

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and what we were able to really get into is
divide the country up into these different

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regions and with that within each
region there's specific microclimates,

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specific physical geographies that also affect
the heat though we wanted to look at this

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at a neighborhood level at really my--
granular scale, if you go to the next slide-

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When looking across all
of these particular cities

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what we were able to immediately
distinguish is the relationship between

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each of these four different categories
or grades of redlined neighborhoods

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that is A as the best, B which is
blue--A is the green B is the blue

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which is considered desirable still. C as
you might recall is considered declining

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and D would be considered hazardous
by the Homeowners'' Loan Corporation

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the federal administration who was
overseeing this particular policy,

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and what we were able to see across the
entire country and across all these 108 cities

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that we looked at was that the D
grades were systematically hotter

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than the A grades and that was really
for us a moment of reckoning in recognizing

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this isn't necessarily just a luxury effect
as the literature might describe that

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communities who have more wealth
would be able to add more greening

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and what have you at the individual
scale, this is more of a systematic pattern

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that we were seeing across the
country and that really caught us

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caught our attention and wanted
to dig into it a little bit more.

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So if you go to the next slide.

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And what this allowed us to look at is
the amount of what was on the landscape,

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and if you look at the
relationship between

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these hot areas and what's on
the landscape, we quickly see that

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the areas that are graded as D
were consistently having more

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what we call impervious surface or that's the
asphalt or the concrete that seals the surface

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and absorbs that sun solar radiation and
bakes it into the that specific location

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and so communities that were
living in these redlined areas

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were consistently finding a lot more asphalt
and concrete in and around their neighborhoods.

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And if you go to the next slide.

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And at the same time we were also
seeing that there were far fewer trees,

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now this plays out in a
really interesting way because

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what we're essentially talking about is
a policy that went in the 1930s

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as you heard from the previous
Environmental Justice webinar

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and when you are
disinvesting in the neighborhood

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what ends up happening is you're
attracting a lot of things

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that require large amounts of land
such as freeways, think about the 1950s

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as the Eisenhower Administration
was rolling out massive amounts

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of asphalt in the form of our interstate
system where were a lot of those freeways

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going they were often going
through neighborhoods

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that had the lowest rents and
those lowest rents by design

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were in those areas that were
redlined or in the C or D grades

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and that ends up then creating
this physical infrastructure

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where if you have industries
that are looking for a place to go

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that require a lot of land or if
you're even looking at big box stores

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that emerged, these are the places
that lowest land values by again by design

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would force the impervious surface
and really create a green squeeze

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or really make it much harder
to be able to bring green spaces

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into those environments due to the sealed
surface of a lot of asphalt or concrete.

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If we go to the next slide, I'll turn it
back over to Jeremy to talk a little bit about

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how these results have been confirmed in
recent research that's been coming out as well.

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Jeremy Hoffman: Thank you Vivek, and yeah,
we're, really pleased with the response

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that we've had to this work over the
last year or so a year and a few months,

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and we're actually we're--
encouraged that our conclusions

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as well as our observations have been
replicated in many ways across new studies

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that have been published in 2020 and early
2021, including here on the left getting

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to what Vivek was speaking to about
that kind of green space availability,

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based on the grades, we
have a paper by Nardone et al.

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which was just published environmental
health perspectives showing that

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by a grade you have a diminishing amount of
a green space in the form of the NDVI

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which is a vegetation index
that is remotely sensed as well.

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So this largely confirms the idea that there's
 large scale disinvestment in providing

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ecosystem services through green
space or that kind of dominance

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of the impervious surfaces making
these landscapes much warmer although

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that wasn't investigated
directly by this paper.

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Up in the top right, we have from us
several cities from around the country

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a similar estimation of their amount of
tree canopy per grade with as you

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march through the grades towards
the hazardous redline category

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we actually see diminishing
amounts of tree canopy percentages.

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This has also been now starting to
be investigated through the use of lidar

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and actually classifying tree heights,
we know now that in some cities not only

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are there fewer trees, but the ones that
are there in the formerly redlined areas

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tend to be much shorter on average,
so they provide much more diminished

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ecosystem services beyond just the clear
cooling properties that trees provide,

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but also the potential links to
mental health, and well-being

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as well as their management of
storm water and air quality impacts,

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we'll, get to that in just a little bit.

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And then the impact of these policies
potentially on the health outcomes

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in these neighborhoods were
investigated by the NCRC in their

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redlining and neighborhood health report
which was also released in 2020

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showing systematically that comparing the
formerly red lines to non-red line neighborhoods

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there are higher levels of things like
poor health outcomes related to

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diabetes and obesity, respiratory
health issues cholesterol,

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and then overall the most harrowing of these
conclusions was the lowering of life expectancy

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in these formerly red-lined areas
versus their non-redline neighbors.

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And I think that really to me
drives home the importance

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of centering these communities in
any sort of decision-making that's made

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as we move forward towards
ameliorating these differences.

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So, I think we can go to the next slide.

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And get to one of the kind of
other cascading impacts here,

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so we you've heard from us that
there's this more impervious surfaces

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and we know due to climate change that
it's not only heat that's getting worse,

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but it's also extreme weather events
like extreme precipitation events

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that may overwhelm our city's aging
storm water infrastructure

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and in areas that are low-lying in flood
plains of river systems that provide aquatic

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environmental tourism
and things in different cities.

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Well, the website Redfin collaborated
with the flood factor score folks

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at the First Street Foundation.

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And what they were able to show is that
predominantly in the cities that were redlined

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we see a higher proportion of properties
and parcels with higher relative flood risks

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that may actually be underestimated by FEMA
maps in American cities that were redlined.

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So not only are we seeing these
disproportionate health impacts

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that are easily correlated with things
like health inequality or heat inequity,

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 but we're also seeing these other
climate change exacerbated stressors

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like extreme precipitation and the effects
that it might have on our neighborhoods

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being worse in these
formerly redline neighborhoods.

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So this ties together the environmental
justice issue that we've identified in heat

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to the underlying structural
issues with things like urban flooding

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and really shows that regardless of the
stressor we're starting to emerge

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from the literature a consistent picture
of a climate change in equity brought on

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at least in part by the long-term
decision making that started over

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almost a century ago and is now echoing in
the present day as environmental inequity.

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So, I think this well-- I'm gonna
pass it back over to Vivek to tell you

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a little bit about the work that we've
been doing around community-centered

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participatory research campaigns and how
that's helped us evolve a changing view

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of how we can actually engage communities in
this discovery of thermal inequity. Vivek?

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Vivek Shandas: Thank you, Jeremy,
So I want to just talk a little bit about

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the "so what" question and
where do we go from here,

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and I think the rest of our conversation
here, including a moderated discussion

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by Charles will
help us kind of situate this,

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but before we do that just a couple
of words on the where do we go

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and part of what you're hearing
now is a very analytical approach

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and Jeremy and I have been spending a lot
of time on analysis and trying to

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unpack some of these historic policies in
relation to redlining in relation to heat

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and what we wanted to do though and both of us
have a real interest in engaging communities.

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And so what we have here is a quadrant
system where we have ABCD

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and I don't want to belabor this
too much though I do want to suggest

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as a way of thinking about going forward
that we may have a lot of data

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in this case robustness of data
access from low to high in this D quadrant

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we may have a lot of
data that we're working with

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and we may have a lot of really specialized
knowledge about this particular issue

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and we can kind of serve up these data
through publications through presentations

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and the like though that really doesn't
get us very deep into the community

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and what we might want to do to activate
the community which we can talk about

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in a moderated discussion coming up.

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There's another option here where
there might be both not much data or not

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much community engagement in this.

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And we're what we end up
there is just really status quo

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and not really being able to make move-- much
move the needle much on this particular issue

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and people aren't involved, they're
apathetic and we don't really know

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what exactly the patterns are, because we
don't have much data in this other quadrant,

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but if we go up to the B quadrant where
we have a high level of engagement people are

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very involved and there
although there's not much data

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to be able to underscore and support the
actions to go forward and decision making

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that can often lead to
confrontational debates or some

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aspects of not really being able to identify
where we invest for improving the quality

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of communities health and well-being
and what we would argue

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and where we want to go with some of this
work is towards this quadrant A ultimately

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where we have really robust
really rich data sets like this

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like the digitized red line maps in relation
to the granular level of understanding of heat

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and flooding and other climate induced
environmental injustices with a high level

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of community engagement, and so to
move in that direction is really what we're

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aspiring to do, and if you go to the next
slide, I just want to close this out

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with a suggestion that we've been doing
a series of these heat watch campaigns

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where we're essentially outfitting cars and
bicycles and even pedestrians with little sensors

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that enable them to be able to go out and
collect hundreds of thousands of temperature

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and humidity measurements in a specific
city, and when we're able to do that

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we're actually able to involve the
community in understanding their place

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drawing on local knowledge about that
place, understanding how there's

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differences from one place to another and then
identify where in-- what types of interventions

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and where those interventions might go.

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And so we actually are not just serving
up the data in a sense, we're actually

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involving the communities in the collection
of the data and the interpretation of it

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and then the actual activation of it as well.

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And so that's kind of where we'd
like to take this work and I want to

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really give a shout out to Charles and
EPA for lifting up many of these topics

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over the last several
decades and if you haven't seen

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the front page of the Washington post today,
I would really encourage you to look at

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the piece on the heroes of environmental
justice and what environmental racism

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looks like today and several of the folks
including our moderator Charles Lee,

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who was prominently featured in that article.

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And so this is a movement that we're just
really have had going for quite some time

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communities have been hard at work,
what we're trying to do is create a means

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for systematically analyzing it,
being able to offer these campaigns

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as a way to really ground this in
local knowledge and local activity.

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And then provide the technical
expertise where it might be sought

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and where it might be helpful for really
addressing this issue at the systemic level.

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So for with that let me pause
and turn it back over to our

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environmental justice hero
Charles Lee to moderate.

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Charles Lee: Thank you, both,
Jeremy and Vivek for great presentations.

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I want to dig in into a few of
the topics a little bit deeper,

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so I will start with Jeremy and so Jeremy you
start-- you work in the science museum

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which is a kind of like a new setting for
empiric-- rigorous empirical scientific research,

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however you are
consciously seeking to develop

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and these are in your own words a
"community science model",

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so can you describe that more and give
examples of such-- of them from your work?

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00:25:22,559 --> 00:25:27,360
Jeremy Hoffman: Sure, and thank
you, Charles for the question about

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science centers and I think I have to lift up
the work of many science center institutions

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that have been funded by the National
Oceanic and Atmospheric Administration's

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Environmental Literacy Program which
has really focused on expanding

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environmental literacy into and--
what through the information

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and community engagement
that science centers have.

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So I wanted to start by saying
the idea of community science,

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I know a lot of people have heard
probably the idea of citizen science,

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and I think that there's a really
important distinction in many ways by

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and how those kind of systems operate.

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Citizen science tends to be more designed
entirely by the experts like scientific experts

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that are running the research and recruiting
volunteers to make standardized measurements

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that may or may not necessarily they have any
sort of input into how they're interpreted

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what they're used for long term and so it's
kind of a an expert model that we're working

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with traditionally citizen
science types of campaigns.

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It doesn't mean that they're wrong, in fact one
of the most famous citizen science campaigns

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has produced thousands of measurements
of bird migrations and distributions

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that have significantly improved
our understanding of how human

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environments are interfering or actually improving
the lives and distribution of bird species,

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but what I'm-- the community science
model is more something that is designed by

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and community that is seeking scientific
information to improve the understanding of their

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neighborhood around them.

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And so the American Geophysical
Unions Thriving Earth Exchange program

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as well as the associated-- Association
of Science and Technology Centers

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a community science initiative, really work
with a community defined problem

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and then linking up with an expert
that then uses their talents to amplify

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the voice and vision of that
neighborhood in designing

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and then actually executing
that type of research.

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Now, in my direct experience when we worked
with Vivek in 2017 in the city of Richmond,

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we actively recruited members of the
community alongside nonprofits

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that were actually already working in greening
initiatives and expanding green space access

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in the city of Richmond to go out and
actually design the campaign around

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assessing urban heat in the city of Richmond
and that has kind of spawned a lot

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of the work that has come out of
Vivek and I's collaboration over the years.

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Now, what we're also doing at
the Science Museum of Virginia

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funded through the Institute of Museum and
Library Services is known as RV Air,

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we're basically outfitting individuals
both neighborhood associations

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and groundwork RVA, a key
workforce skills development nonprofit

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with handheld air quality sensors to go
around and walk around their neighborhood

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at repeatable times throughout
the summer and into the fall

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and determine an area where they want to
provide some sort of intervention

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whether that's a public education,
talking about the history of

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roadways design, urban planning in
their neighborhood or doing something

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like a green space intervention.

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What the key thing about community
science and that community science model

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that you asked me about Charles, is
really the scientific experts seeding

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the power in the exchange of that scientific
endeavor to allow for the community to decide

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how are we gonna collect the information,
what are we gonna do with it.

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And I think that that's really what can inspire
a lot of climate-related action

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in the near-term across the United
States and especially with science centers

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and their high level of
trust in their communities.

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So that's kind of what I mean by the
community science model Charles, thank you.

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Charles Lee: Great, and so I'm going to move
on from that question or build on that question

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to Vivek and talk about that
approach and how that relates to areas

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which you are very interested in such
as a better understanding of vulnerability

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climate adaptation, and most
importantly, urban governance.

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Vivek Shandas: Yeah, so this is one of those
areas that I think we are really starting

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to scratch the surface on, we've been
understanding at the very national scales

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even international scales aspects of
climate and even through the COP summits

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we're understanding governance and some of the
bottlenecks we're finding around governance.

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At the local level there's a lot of
idiosyncratic actions histories culture

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that often plays out and it's probably
no surprise to anyone on this webinar

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that the way in which specific policies
get rolled out implemented

388
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and then ultimately evaluated by
folks like us in the research community

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00:30:36,964 --> 00:30:42,688
is really interesting, because we do
see so many idiosyncratic approaches.

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For example, when we look at the redlining
maps one of the things that comes up is this

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very distinct, there's some cities where
there's very distinct individual

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roadways that are called out
as hazardous or as redlined

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and it required a great deal of local knowledge
to be able to identify those specific roads

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as being, in this case, category as the D grade
and part of what comes up there is just an

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00:31:09,279 --> 00:31:13,948
indication or a suggestion as to the fact that
local consulting companies

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00:31:13,972 --> 00:31:18,399
or local planning agencies were very involved
in the construction of some of these maps

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00:31:18,399 --> 00:31:22,080
and what ends up happening
as a result is that governance

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creates some real challenges in terms of how
much trust local communities

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00:31:26,679 --> 00:31:31,655
then have for the kinds of policies that
are promulgated at the local level.

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What we have now as a result of a lot of
these particular policies needless to say

401
00:31:36,612 --> 00:31:43,519
is a great deal of a great challenge and just
to be real about it a great deal of distrust

402
00:31:43,519 --> 00:31:49,467
of local planning agencies in terms
of being able to roll out specific policies

403
00:31:49,491 --> 00:31:54,399
that might in the ult-- might in their view or
at least the planning agencies planners view

404
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be beneficial for a community.

405
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I see this often with tree plantings and
things like that, we're showing redlining

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00:32:00,653 --> 00:32:04,139
or we're showing heat maps and the
immediate planning response is

407
00:32:04,163 --> 00:32:06,788
let's put a bunch of trees
in that neighborhood.

408
00:32:06,812 --> 00:32:10,799
And what happens as a result is
not only has that neighborhood been

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00:32:10,799 --> 00:32:14,559
disinvested over time, then all of a
sudden this knee-jerk reaction

410
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of going in and starting to plant a
bunch of trees in that neighborhood without

411
00:32:18,240 --> 00:32:23,200
engaging the communities in any
kind of meaningful place-based way

412
00:32:23,200 --> 00:32:28,320
further creates-- further I think activates some
of the trauma that communities have experienced

413
00:32:28,320 --> 00:32:30,740
and could further
increase distrust.

414
00:32:30,764 --> 00:32:33,600
So what we've been
really thinking about

415
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is a co-produced governance model that
allows communities to actively participate

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00:32:38,640 --> 00:32:47,955
in the creation of those spaces through a, for
example, an identification of a collaborative

417
00:32:47,979 --> 00:32:51,149
greening campaign that could
happen at a neighborhood scale

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00:32:51,273 --> 00:32:55,997
so what would it look like for local community
local neighborhood rep-- participants

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to be actively involved in the
process of greening that neighborhood.

420
00:33:00,159 --> 00:33:07,440
So those kinds of approaches I think are just
really-- have been done, there's many examples

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00:33:07,440 --> 00:33:10,799
examples of those around the
country and I'd really encourage

422
00:33:10,799 --> 00:33:14,080
EPA as well as other
federal agencies to think about

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00:33:14,080 --> 00:33:19,421
how to engage the local communities in a
way of creating those local co-produced

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00:33:19,445 --> 00:33:24,921
climate and governance plans that
would allow the strategies to come

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00:33:24,945 --> 00:33:30,344
from the communities that are often
the folks who have been hardest hit

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00:33:30,368 --> 00:33:32,721
by some of the policies in the past.

427
00:33:32,745 --> 00:33:37,821
So I want to just start there and provoke
you a little bit, hopefully that did it.

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00:33:37,945 --> 00:33:41,734
Charles Lee: Great, thanks for Vivek, I'm
going to switch gears a little bit

429
00:33:41,858 --> 00:33:51,279
I have said earlier that about use of EJSCREEN
and to help display the relationship between

430
00:33:51,279 --> 00:33:56,880
redlining and environmental disparities,
and we in fact have like I said before

431
00:33:56,880 --> 00:33:59,155
a person that's pretty adept at this.

432
00:33:59,179 --> 00:34:04,621
So Jeremy, how-- what
advice would you provide to others

433
00:34:04,645 --> 00:34:11,679
both inside and outside of government agencies
that's interested in doing something like that.

434
00:34:11,918 --> 00:34:21,839
Yeah, so the-- I think one of the key aspects is
knowing that for any city that has this history

435
00:34:21,839 --> 00:34:27,688
of redlining, the maps and the shape files
themselves are available for download

436
00:34:27,712 --> 00:34:34,159
via the Mapping Inequality website, so
that's if you have experience

437
00:34:34,159 --> 00:34:39,359
incorporating those sorts of data sets into
a mapping software both open source something

438
00:34:39,359 --> 00:34:48,079
like QGIS or ArcGIS or ArcGIS online
actually now the folks at Esri have

439
00:34:48,079 --> 00:34:55,355
made that entire HOLC mapping
package, the entire database available

440
00:34:55,379 --> 00:35:01,520
for people to use on ArcGIS on-- ArcGIS
online, and I actually made a version of this,

441
00:35:01,520 --> 00:35:05,839
Charles I think it's two-- the
next slide perhaps,

442
00:35:05,839 --> 00:35:10,655
Charles Lee: Right two, slides
next two slide is-- yeah.

443
00:35:10,679 --> 00:35:11,055
Jeremy Hoffman: Yeah,
Charles Lee: So after.

444
00:35:11,079 --> 00:35:16,400
Jeremy Hoffman: Yeah, one
more, yeah, so if you use ArcGIS online,

445
00:35:16,400 --> 00:35:21,855
you can actually access both the Homeowners'
Loan Corporation neighborhood redlining

446
00:35:21,879 --> 00:35:31,119
grade database which will overlay all of the
HOLC polygons in the Mapping Inequality database

447
00:35:31,119 --> 00:35:39,520
as well as the EJSCREEN data
sets available via the ArcGIS online

448
00:35:39,520 --> 00:35:44,720
living atlas of the world, so these are totally
available, you can make a free online account

449
00:35:44,720 --> 00:35:48,400
and begin to overlay the individual
aspects of the EJSCREEN

450
00:35:48,400 --> 00:35:52,880
indices, something like here I'm looking
at that the traffic volume

451
00:35:52,880 --> 00:36:03,221
in the darker colors being more traffic
proximity and then the redlining polygons.

452
00:36:03,345 --> 00:36:08,240
And just like Vivek mentioned, it's very clear
when you start to look at several cities

453
00:36:08,240 --> 00:36:14,000
where the interstates go and that dark
swath through the north side of the city

454
00:36:14,000 --> 00:36:18,488
of Richmond Virginia, is exactly what
Vivek was talking about earlier

455
00:36:18,512 --> 00:36:26,255
that is where the interstate 95 and 64 was
bulldozed the Jackson Ward neighborhood

456
00:36:26,279 --> 00:36:32,480
or portions of it, and those are the red
polygons right in the middle of the screen there.

457
00:36:32,480 --> 00:36:36,988
And so you can actually look at these patterns
not only with using the EJSCREEN data,

458
00:36:37,012 --> 00:36:41,200
but other sorts of data that
might be interesting to look at,

459
00:36:41,200 --> 00:36:44,980
so you can kind of replicate
the analysis that the NCRA did

460
00:36:45,080 --> 00:36:50,140
by incorporating the CDC's 500 cities data
and looking at patterns of things like

461
00:36:50,140 --> 00:36:54,921
what might underlie this would be
patterns of asthma which it turns out

462
00:36:54,945 --> 00:37:01,599
looks exactly kind of like this map, so
it's really an interesting way to explore

463
00:37:01,599 --> 00:37:06,368
this historical lens of this planning decisions
that were made a hundred years ago

464
00:37:06,392 --> 00:37:11,680
by a very small a powerful
mostly white kind of decision maker

465
00:37:11,680 --> 00:37:17,440
group just as Vivek said, this
generations of these neighborhoods being

466
00:37:17,440 --> 00:37:22,548
left out of the decision-making process that
these sorts of lenses can help shape your

467
00:37:22,672 --> 00:37:27,360
climate adaptation or action plan to really
center these communities in the decision making

468
00:37:27,484 --> 00:37:31,680
and get them around the table,
compensate them for their participation

469
00:37:31,680 --> 00:37:36,774
and get them talking about these sorts of
environmental issues alongside

470
00:37:36,798 --> 00:37:43,760
the plans and sorts of implement or mitigation
and intervention things that might be

471
00:37:43,760 --> 00:37:46,455
available to these neighborhoods.

472
00:37:46,479 --> 00:37:54,021
And so, I would say again the Mapping Inequality
database is available for free download,

473
00:37:54,045 --> 00:37:58,555
but you can go to ArcGIS online make a free
account and begin to explore these using

474
00:37:58,579 --> 00:38:03,755
the living atlas data sets
that are available there.

475
00:38:03,779 --> 00:38:08,020
So, Charles do you want me to go
into any more detail about this?

476
00:38:08,120 --> 00:38:13,308
Charles Lee: No no, not right now, but
we can probably figure out ways for us

477
00:38:13,332 --> 00:38:20,400
to have you talk with people interested
because there's a huge amount of interest

478
00:38:20,400 --> 00:38:26,555
in trying to do this, but let me move on
to Vivek because I really want to get

479
00:38:26,579 --> 00:38:33,680
his thoughts about his advice
for our research agendas on the part of EPA

480
00:38:33,680 --> 00:38:41,440
and other federal agencies in the areas
of EJ, our urban sustainability and climate.

481
00:38:43,280 --> 00:38:45,839
Vivek Shandas: Yeah, so to
build on some of what Jeremy

482
00:38:45,839 --> 00:38:52,320
was describing is really thinking about this
from the perspective of centering historically

483
00:38:52,320 --> 00:38:56,880
disinvested communities, like-- that's
that's where I begin with this work

484
00:38:56,880 --> 00:39:04,728
how do we really enable communities
that have been historically marginalized

485
00:39:04,752 --> 00:39:10,720
from decision-making processes, from
participating in even local governance,

486
00:39:10,720 --> 00:39:17,440
how do we find ways that would
meaningfully and equitably involve

487
00:39:17,440 --> 00:39:19,886
the communities that
have been left out?

488
00:39:19,910 --> 00:39:25,599
And not only from decision making, also from an
outcomes, the distribution of benefits and burdens.

489
00:39:25,599 --> 00:39:30,320
What we're able to do with this particular
paper and some of the other studies that we--

490
00:39:30,320 --> 00:39:36,960
I've been working on is reveal a little bit
through an analytical platform, reveal some

491
00:39:36,960 --> 00:39:41,188
of these things that are just underneath
the surface of what we experience every day.

492
00:39:41,212 --> 00:39:46,880
We don't-- when we see actions happening around
our neighborhoods or we see actions happening

493
00:39:46,880 --> 00:39:52,480
at the city scale, we're not really able
to see how these particular actions add up

494
00:39:52,480 --> 00:39:58,079
across the entire country and the fact that
these are systemic patterns that we're seeing.

495
00:39:58,079 --> 00:40:01,920
And once we are able to actually see
these systemic patterns like we're

496
00:40:01,920 --> 00:40:05,520
doing with the redlining and the heat
study, we're able to actually see that

497
00:40:05,520 --> 00:40:08,880
this isn't some idiosyncratic thing
happening at the local community level,

498
00:40:08,880 --> 00:40:13,839
because of a set of policies that were passed
recently around racial covenants or the like,

499
00:40:13,839 --> 00:40:18,480
it's actually something that's been happening
through support from a variety of different

500
00:40:18,480 --> 00:40:22,828
systems that are in place that have
enabled this to happen and what we're doing

501
00:40:22,852 --> 00:40:28,386
is creating an analytical platform to
show that these disparities are consistent

502
00:40:28,410 --> 00:40:32,288
across the entire country
regardless of where you live.

503
00:40:32,312 --> 00:40:36,746
And so that's one piece I feel like EPA would
be really interesting to conduct more

504
00:40:36,870 --> 00:40:42,160
of these national scale studies to reveal
what are some of the systemic issues

505
00:40:42,160 --> 00:40:46,400
that are persistent across the country
and that may have their own

506
00:40:46,400 --> 00:40:50,988
kind of local flavor to them if you will, whether
that's geographic in terms of region,

507
00:40:51,112 --> 00:40:55,440
EPA region or whether that's even
geographic in terms of neighborhood

508
00:40:55,440 --> 00:41:00,079
regardless of scale, I think that national--
national reviewing national patterns

509
00:41:00,079 --> 00:41:03,755
like this is really one of the
first things that needs to be done,

510
00:41:03,779 --> 00:41:07,221
because we're just really starting to
take environmental justice

511
00:41:07,245 --> 00:41:12,316
from the local community that and
the advocacy work that's happened

512
00:41:12,440 --> 00:41:15,760
in so many local communities and
start adding that up to a national agenda

513
00:41:15,760 --> 00:41:20,720
which I really congratulate
EPA on moving forward.

514
00:41:20,720 --> 00:41:27,200
I also think just two quick other things,
one is to really think about

515
00:41:27,200 --> 00:41:31,680
how do we integrate that analysis
that we do with community action

516
00:41:31,680 --> 00:41:35,680
and to really re-examine
the notion of expertise.

517
00:41:35,680 --> 00:41:40,807
We've often-- especially in the scientific
fields like environmental science

518
00:41:40,831 --> 00:41:45,535
we've often thought about this as the expert
knows, and I really think we're at a stage

519
00:41:45,559 --> 00:41:50,466
where we're really expanding the kind of
knowledges that are necessary

520
00:41:50,490 --> 00:41:54,480
for solving for addressing some of these wicked
problems like climate or environmental justice.

521
00:41:54,480 --> 00:42:02,240
And that we need a real plurality of knowledge
to be able to effectively address these issues.

522
00:42:02,240 --> 00:42:10,960
And so these ways of engaging communities
directly and affected communities as well as

523
00:42:10,960 --> 00:42:16,688
indirectly affected communities and
bringing the necessary data to bear

524
00:42:16,812 --> 00:42:23,021
I think those are the ways-- we really start
to expose what kind of local issues are at play

525
00:42:23,145 --> 00:42:26,521
what kind of local knowledge might
be needed to be brought forward

526
00:42:26,545 --> 00:42:30,365
and how do we do that in a way that centers
communities that haven't been

527
00:42:30,389 --> 00:42:31,021
part of this process.

528
00:42:31,145 --> 00:42:36,454
And then of course my last bit would of course
be, let's get some more funding on

529
00:42:36,478 --> 00:42:41,173
the table for this issue and that is
not only through individual EPA,

530
00:42:41,197 --> 00:42:45,760
but I think collaboratively across
multiple federal bureaus to be able

531
00:42:45,760 --> 00:42:49,888
to bring more resources to the table to
address this issue both for local communities

532
00:42:49,912 --> 00:42:55,040
as well as these kind of analysis
that we were that we've been talking about.

533
00:42:55,040 --> 00:42:57,008
Charles Lee: Great, thanks, thanks for that.

534
00:42:57,032 --> 00:43:03,280
So one last question before we move out
quickly and I want to make sure we covered this

535
00:43:03,280 --> 00:43:09,755
one of the more important things from the
surveyor's descriptions of the red line areas

536
00:43:09,779 --> 00:43:15,760
from the 1930s are the kind of
descriptions they provide,

537
00:43:15,760 --> 00:43:21,200
and one on Jeremy to talk about
that in terms of the kind of

538
00:43:21,200 --> 00:43:24,560
work clouds that you guys
have been able to create

539
00:43:24,560 --> 00:43:29,048
that really show some really
important relationships.

540
00:43:29,072 --> 00:43:33,421
Jeremy Hoffman: Yeah, thank you, Charles, so
if we go to the-- yeah this slide right here,

541
00:43:33,445 --> 00:43:36,800
I think goes to deepen
this story a little bit more,

542
00:43:36,800 --> 00:43:42,160
so we took a look at these patterns of
inequitable heat distribution in our city

543
00:43:42,160 --> 00:43:47,280
in cities that were redlined and
several of these follow-up studies

544
00:43:47,280 --> 00:43:54,400
kind of replicated our results in at least
the underlying land use types that were there

545
00:43:54,400 --> 00:43:59,208
and what I want to highlight is that we
have notes about not only the folks

546
00:43:59,232 --> 00:44:01,839
that were living in these
neighborhoods when they were

547
00:44:01,839 --> 00:44:06,588
redlined or given their grade
designation, but we also have descriptions

548
00:44:06,712 --> 00:44:09,007
of the neighborhoods themselves.

549
00:44:09,031 --> 00:44:13,200
What the kind of neighborhood land
use choices were already there.

550
00:44:13,200 --> 00:44:18,329
This is done with help from with Rob Nelson at
the University of Richmond's Mapping

551
00:44:18,353 --> 00:44:23,320
Inequality project and on the left on this
slide we have the environmental descriptor words

552
00:44:23,520 --> 00:44:26,575
that were used to describe the
neighborhoods that were given

553
00:44:26,599 --> 00:44:29,586
A and B ratings across the country.

554
00:44:29,610 --> 00:44:34,331
So and then the size of the word is
scaled to how many times it appears

555
00:44:34,455 --> 00:44:36,889
in the description database.

556
00:44:36,912 --> 00:44:38,880
So what you can see is that the
A and B neighborhoods

557
00:44:38,880 --> 00:44:44,521
were already described as having
extremely wooded conditions, shade--

558
00:44:44,545 --> 00:44:49,400
I mean this gets to the core
of it, is the availability of shade

559
00:44:49,500 --> 00:44:53,755
was already one of the dominant descriptors
of the environment of these neighborhoods.

560
00:44:53,779 --> 00:44:58,574
But then you can see some other things that
also correlate to present-day distributions

561
00:44:58,598 --> 00:45:02,355
of trees and vegetation indices.

562
00:45:02,479 --> 00:45:05,888
Things like shrubbery, they also
have things like rolling and golf,

563
00:45:05,912 --> 00:45:11,040
so you can think of these green islands
that these landscapes already represented

564
00:45:11,040 --> 00:45:13,221
back in the 1930s.

565
00:45:13,245 --> 00:45:16,969
Then on the right side we see instead the
descriptors that were used

566
00:45:17,093 --> 00:45:21,820
to describe the C and D neighborhoods, and
Charles I think this also echoes that

567
00:45:22,020 --> 00:45:27,821
what we see in the EJSCREEN data
sewers, manufacturing, odors, pave

568
00:45:27,845 --> 00:45:33,599
they were even described as hot, so in
many ways what I what I hope that you

569
00:45:33,599 --> 00:45:39,955
get from this is maybe not so much that
redlining caused these environmental disparities

570
00:45:39,979 --> 00:45:45,839
but they locked them in, they made them
lawful for multiple generations

571
00:45:45,839 --> 00:45:50,079
and we've seen this in the socioeconomic
outcomes in the economic literature

572
00:45:50,079 --> 00:45:55,481
where these redlining maps were an economic
treatment for the people that lived there

573
00:45:55,505 --> 00:45:59,323
where now decades later
we see that they have lasting

574
00:45:59,447 --> 00:46:02,821
and long-term socioeconomic
implications for the folks that live there,

575
00:46:02,845 --> 00:46:10,319
but also it's very clear that it's also a
long-term impact and in locking in the kinds of

576
00:46:10,319 --> 00:46:14,188
land uses that were already
existent and then as Vivek mentioned

577
00:46:14,212 --> 00:46:19,119
then these redlined maps served
as a way to figure out where or

578
00:46:19,119 --> 00:46:22,880
where the administrations
put the federal highway system.

579
00:46:22,880 --> 00:46:27,755
And then even before this, you might
ask what came even before redlining,

580
00:46:27,779 --> 00:46:31,760
well there's actually a really
interesting TED talk by Stephen DeBerry

581
00:46:31,760 --> 00:46:36,720
called Why the East Side of the City--
or Why the Wrong Side of the Tracks

582
00:46:36,720 --> 00:46:41,920
Tends to be the East Side of Cities, and
has to do with the spin of the earth

583
00:46:41,920 --> 00:46:47,521
that deflects winds predominantly
from a west to east or westerly winds

584
00:46:47,545 --> 00:46:52,727
in both hemispheres, push historical pollution
from the west side to the east side of the city.

585
00:46:52,751 --> 00:46:56,240
We have an example of that here
in Richmond,Virginia where there's a

586
00:46:56,240 --> 00:47:00,755
small community named Bon Air on
the west side of the city that was used

587
00:47:00,879 --> 00:47:04,288
as an escape for wealthy white
communities to get out of the industrial

588
00:47:04,312 --> 00:47:06,422
pollution of the 19th century.

589
00:47:06,545 --> 00:47:13,119
So in many ways, we had generations of
disproportionate exposure to different forms

590
00:47:13,119 --> 00:47:18,621
of environmental inequity that these redlining
maps may have locked into place into law.

591
00:47:18,645 --> 00:47:21,616
So I just wanted to thank you for
giving me a chance to talk about this,

592
00:47:21,640 --> 00:47:26,319
because I think it really deepens the appreciation
that these environmental justice issues

593
00:47:26,319 --> 00:47:31,588
have been around potentially for hundreds
of years much like sytemic forms of racism

594
00:47:31,612 --> 00:47:35,421
that have existed in this country
as well. So thank you, Charles.

595
00:47:35,545 --> 00:47:40,221
Charles Lee: Thank you, so we're going
to move on now to the question and answer

596
00:47:40,245 --> 00:47:46,720
audience questions and before we do that I--
Sabrina Johnson who's going to lead that section

597
00:47:46,720 --> 00:47:51,555
that portion of the session today
has a question of her own to pose

598
00:47:51,579 --> 00:47:58,421
and then we'll go on Sabrina to a couple
of questions from the audience.

599
00:47:58,445 --> 00:48:02,088
Sabrina Johnson: Yes,
thank you, good afternoon.

600
00:48:02,112 --> 00:48:07,200
My question is going to
be directed to Vivek, please,

601
00:48:07,200 --> 00:48:12,960
we are rightly focused on urban on the
urban landscape and conditions in the US,

602
00:48:12,960 --> 00:48:16,960
but are there interesting insights
approaches and developments

603
00:48:16,960 --> 00:48:24,800
in how urban heat island challenges are
being addressed in international locations?

604
00:48:25,040 --> 00:48:28,188
Vivek Shandas: Yeah, thank you,
Sabrina a very interesting question.

605
00:48:28,312 --> 00:48:31,680
I spent a lot of time talking to folks
in different parts of the world,

606
00:48:31,680 --> 00:48:35,680
I am a big fan of trying to
learn about what's happening

607
00:48:35,680 --> 00:48:41,288
with these specific interventions from different
parts of the world being from South Asia myself

608
00:48:41,312 --> 00:48:49,090
I tend to have a sensitivity to just looking
really broadly for some of the solutions for this.

609
00:48:49,114 --> 00:48:53,272
I will say that in terms of redlining
and heat just kind of context this

610
00:48:53,296 --> 00:48:58,521
is not something that's unique just to the US,
this is something that is-- I've been hearing

611
00:48:58,545 --> 00:49:03,221
working with some folks in South Africa and
during apartheid there was a lot of segregation

612
00:49:03,245 --> 00:49:06,480
that is happening and what
we're seeing is very similar patterns

613
00:49:06,480 --> 00:49:12,028
that's also occurring in parts of South Africa
in terms of disinvested areas

614
00:49:12,052 --> 00:49:15,486
of cities being hotter than the
invested areas of cities.

615
00:49:15,510 --> 00:49:21,888
So this is not a pattern unique to the United
States, at least so far is what we're noticing.

616
00:49:21,912 --> 00:49:25,732
And in terms of the actual mitigation
and activities that are happening

617
00:49:25,756 --> 00:49:27,921
there's been a great
deal of work happening

618
00:49:27,945 --> 00:49:32,079
in various parts of western Europe, great deal
of work happening in parts of Asia as well.

619
00:49:32,079 --> 00:49:37,788
And one of the big things that's coming up is
in terms of green spaces and cooling spaces.

620
00:49:37,812 --> 00:49:42,588
The pandemic has made cooling spaces very
challenging for anywhere in the world,

621
00:49:42,612 --> 00:49:49,288
because of the indoor environment being
inhospitable given the transmission of COVID,

622
00:49:49,312 --> 00:49:54,000
and so what has been really happening is a lot
of folks have been looking to outdoor spaces

623
00:49:54,000 --> 00:50:00,319
and creating ways in which you can move
air and provide cooling spaces in outdoor

624
00:50:00,319 --> 00:50:07,040
environments and so there have been these
pop-up cooling spaces in different parts

625
00:50:07,040 --> 00:50:12,000
of France, there's been oases like
resilience hubs and oases that have been

626
00:50:12,000 --> 00:50:16,559
developed in different cities where
during a heat wave,

627
00:50:16,559 --> 00:50:21,888
particularly in places like France and Western
Europe where almost 30,000 people died

628
00:50:21,912 --> 00:50:28,640
in 2003 due to a heat wave, that these specific
preemptive measures are taken where you can

629
00:50:28,640 --> 00:50:32,355
actually create space
cool spaces for communities to go.

630
00:50:32,379 --> 00:50:38,079
And it really varies by context, because
one of the biggest and least costly

631
00:50:38,079 --> 00:50:42,567
strategies that was taken for example in
South Asia was the opening up of parks.

632
00:50:42,591 --> 00:50:49,721
Parks were gated off during the night
and when people die of heat exhaustion

633
00:50:49,845 --> 00:50:53,689
it's usually the epidemiologists tell us that
it's usually during the evening hours

634
00:50:53,913 --> 00:50:56,306
when the body is not
thermoregulating and overheats,

635
00:50:56,330 --> 00:51:00,755
and so what people were doing were
essentially opening up the gates to parks

636
00:51:00,779 --> 00:51:06,410
in Delhi, for example, and that reduced the
number of excess mortality and morbidity

637
00:51:06,534 --> 00:51:11,612
from heat waves overnight dramatically and so
what we were seeing is a very low cost

638
00:51:11,636 --> 00:51:16,559
very effective solution that was
locally tailored for an environment that

639
00:51:16,559 --> 00:51:20,988
was pushing upwards of 120 degrees
Fahrenheit overnight temperatures

640
00:51:21,012 --> 00:51:26,400
which for many communities would be
very-- would be a big burden on health

641
00:51:26,400 --> 00:51:27,948
and may cause fatalities.

642
00:51:27,972 --> 00:51:31,920
And so those are just a couple
of examples of pop-ups or oasis

643
00:51:31,920 --> 00:51:38,088
that are being created outdoors as well
as enabling communities to access parks

644
00:51:38,112 --> 00:51:39,221
and different environments.

645
00:51:39,245 --> 00:51:44,242
Of course there's the contentious
discussion about air conditioners

646
00:51:44,266 --> 00:51:48,721
and the fact that many cities have
been giving air conditioners a way

647
00:51:48,745 --> 00:51:51,421
to reduce mortality from heat waves.

648
00:51:51,445 --> 00:51:56,720
And of course also trying to balance that
with the fact that air conditioners are

649
00:51:56,720 --> 00:52:00,319
often also drawing and generating more
greenhouse gases and the energy

650
00:52:00,319 --> 00:52:04,480
that they demand, and so really
thinking about passive cooling

651
00:52:04,480 --> 00:52:09,721
as well as renewable energy cooling and
various other strategies that are popping up

652
00:52:09,745 --> 00:52:12,319
in various places around the world.

653
00:52:12,880 --> 00:52:18,240
Sabrina Johnson: Thank you, and systemic racism
is global, so it's not surprising that we

654
00:52:18,240 --> 00:52:22,608
would hear that there are similar kinds of
conditions concerning redlining

655
00:52:22,632 --> 00:52:24,800
and the climate crisis elsewhere.

656
00:52:24,800 --> 00:52:30,421
Thank you, so our next question
we're going to direct to Jeremy,

657
00:52:30,445 --> 00:52:35,599
and it really ties in with your
earlier comments on Jeremy about

658
00:52:35,599 --> 00:52:43,280
how these land use issues are really
locked in by the decision making--

659
00:52:43,280 --> 00:52:49,307
decision makers and actions historically
that we're discussing here.

660
00:52:49,331 --> 00:52:56,151
So the question is, do designated
degrade areas that have gentrified

661
00:52:56,275 --> 00:53:01,155
in the past approximately
20 years, currently experience

662
00:53:01,179 --> 00:53:07,888
the same environmental disadvantages
as degrade areas that have not gentrified?

663
00:53:08,012 --> 00:53:11,839
Jeremy Hoffman: That's a fascinating question,
and one that we have had the opportunity

664
00:53:11,839 --> 00:53:18,240
to look at in a few different cities, and
while we haven't published on this idea yet,

665
00:53:18,240 --> 00:53:23,155
I think Vivek might actually be
working with his lab about that

666
00:53:23,179 --> 00:53:28,559
in a few particular large cities,
places like Denver or Minneapolis

667
00:53:28,559 --> 00:53:33,755
that have experienced a
significant gentrification,

668
00:53:33,779 --> 00:53:40,000
in particular-- I think of one particular
neighborhood in Denver which went from a former

669
00:53:40,000 --> 00:53:45,760
factory district to now the baseball stadium
and luxury apartments around it

670
00:53:45,760 --> 00:53:48,880
that did not see as far as
we could tell any meaningful

671
00:53:48,880 --> 00:53:54,319
land surface temperature change,
from one land use to another.

672
00:53:54,319 --> 00:53:58,640
Now that's just one example
and a very small population size,

673
00:53:58,640 --> 00:54:05,200
but in many ways if there's not a
substantial change to the overall

674
00:54:05,200 --> 00:54:11,520
intensity of the imperviousness
of that formerly redlined area

675
00:54:11,520 --> 00:54:17,320
there's not going to be a substantial shift
in the surface energy balance that creates

676
00:54:17,420 --> 00:54:22,559
that skin temperature urban heat
island or the surface urban heat island.

677
00:54:22,559 --> 00:54:26,240
Now, what we can see though
is based on Vivek's work is that

678
00:54:26,240 --> 00:54:30,855
if that changes the potential building
height variation in that neighborhood

679
00:54:30,879 --> 00:54:35,973
you might get more turbulence of air
kind of moving air around in those areas

680
00:54:36,097 --> 00:54:39,879
a bit better than it was before.

681
00:54:40,079 --> 00:54:46,000
Now in the short time that we have
left I would like to invite Vivek to add

682
00:54:46,000 --> 00:54:50,720
anything that he might be working
on to this discussion since I know

683
00:54:50,720 --> 00:54:53,407
this is something that he
and I have talked about before.

684
00:54:53,431 --> 00:54:57,839
Vivek do you have something to
add to that gentrification question.

685
00:54:57,839 --> 00:55:00,155
Vivek Shandas: Sure, and not
to get into this in too much detail,

686
00:55:00,179 --> 00:55:05,760
but we do have a paper that's about to go out
looking at a series of cities that essentially

687
00:55:05,760 --> 00:55:11,680
we're looking at what happened since, so
we've looked from 1970s all the way up

688
00:55:11,680 --> 00:55:18,221
until 2017 to see what's happening in these
ABCD areas in terms of population change

689
00:55:18,245 --> 00:55:21,359
and what we've noticed is a
consistent pattern across the country

690
00:55:21,359 --> 00:55:27,839
is that the D and C areas, the grade D and
the grade C areas of the HOLC maps have seen

691
00:55:27,839 --> 00:55:34,720
the highest proportion of population change
of any of the neighborhoods in these cities,

692
00:55:34,720 --> 00:55:39,599
and that to us has been really an interesting
observation because what we're seeing is

693
00:55:39,599 --> 00:55:42,968
the residual effects of
redlining still playing out today,

694
00:55:42,992 --> 00:55:46,640
because we're essentially locking
in a particular land use system.

695
00:55:46,640 --> 00:55:53,040
And what that ends up creating is
a real increase and while we do need

696
00:55:53,040 --> 00:55:58,321
more housing where that housing
and where the large blocks of housing

697
00:55:58,345 --> 00:56:01,521
is largely going are C and
D neighborhoods right now.

698
00:56:01,545 --> 00:56:08,621
So what that might end up doing is
further expanding the actual footprint

699
00:56:08,645 --> 00:56:14,055
of the buildings which then reduces the
likelihood of any forms of, for example, greening

700
00:56:14,079 --> 00:56:17,040
of those neighborhoods, which
becomes then really challenging.

701
00:56:17,040 --> 00:56:21,921
So this has been something that we're
tracking now very closely because these patterns

702
00:56:21,945 --> 00:56:25,655
although they were abolished
in 1968 with a Fair Housing Act

703
00:56:25,679 --> 00:56:30,721
with redlining it-- these are patterns
that were built in and baked in as

704
00:56:30,745 --> 00:56:36,160
I was as we saying earlier to the kinds of
development processes that are playing in today.

705
00:56:36,160 --> 00:56:42,255
And yeah let me pause there.

706
00:56:42,279 --> 00:56:47,717
Sabrina Johnson: Okay, thanks,
this next question comes from Marina,

707
00:56:47,841 --> 00:56:56,319
I think we'll have time for at least one more,
and I'll direct this one to Vivek, please,

708
00:56:56,319 --> 00:57:03,488
her question is, why aren't there more cities
in the southwest and west included in this?

709
00:57:03,512 --> 00:57:08,720
Vivek Shandas: Jeremy we
might go back and forth on that.

710
00:57:08,720 --> 00:57:15,521
It's really drawing from what data
are available in the Mapping Inequality

711
00:57:15,545 --> 00:57:20,119
website like they are constantly as I
understand and Jeremy can speak to this

712
00:57:20,143 --> 00:57:23,024
updating the website with
digitizing these maps over time

713
00:57:23,048 --> 00:57:26,079
and getting more and more
of these maps over time

714
00:57:26,079 --> 00:57:28,887
which allows us to kind of bring in more
and more of the data sets,

715
00:57:28,911 --> 00:57:32,880
but Jeremy you
want to speak to that briefly?

716
00:57:35,119 --> 00:57:38,475
Oops you're muted.

717
00:57:38,499 --> 00:57:43,760
Jeremy Hoffman: Sorry about that, so the
interesting thing about that is that the

718
00:57:43,760 --> 00:57:50,721
redlining maps were basically constrained
to cities that had over 40,000 residents

719
00:57:50,745 --> 00:57:51,988
at the time of their drawing.

720
00:57:52,012 --> 00:57:57,921
So there were some many cities
that were just below that threshold

721
00:57:57,945 --> 00:58:03,200
so unfortunately unless they had more
than 40,000 people they weren't

722
00:58:03,200 --> 00:58:05,527
given this redlining treatment.

723
00:58:05,551 --> 00:58:14,720
But that doesn't mean that there weren't other
de facto segregation techniques that were used

724
00:58:14,720 --> 00:58:20,454
in the housing and development of those
cities, so in many ways you hear about cities

725
00:58:20,478 --> 00:58:25,760
that had real racialized housing covenants
where individuals-- individual properties

726
00:58:25,760 --> 00:58:31,468
were written into their deeds that
individuals families of color could

727
00:58:31,492 --> 00:58:34,788
not physically own that property.

728
00:58:34,812 --> 00:58:39,920
So many smaller cities actually
had these kind of similar races planning

729
00:58:39,920 --> 00:58:45,421
in the form of zoning categories and housing
covenants for individual neighborhoods

730
00:58:45,445 --> 00:58:50,907
which restricted ownership to only
wealthy white privileged individuals.

731
00:58:50,931 --> 00:58:55,200
So while they might not have been included
in our study in the formal sense,

732
00:58:55,200 --> 00:58:59,708
because they were not given an HOLC redlining
map as Vivek mentioned, the University

733
00:58:59,832 --> 00:59:05,839
of Richmond's team is expanding
the availability of smaller cities.

734
00:59:05,839 --> 00:59:10,720
The state of Colorado did their own
program that was kind of like redlining

735
00:59:10,720 --> 00:59:13,488
that was based on the same kind of
rating system.

736
00:59:13,512 --> 00:59:20,720
So while it seems like they were-- it wasn't 
intentional cities in the west and the southwest

737
00:59:20,720 --> 00:59:26,708
being left out, it's just based on
the availability of these HOLC maps

738
00:59:26,732 --> 00:59:29,839
and the way that they were drawn.

739
00:59:29,839 --> 00:59:36,821
Charles Lee: Okay, okay, well, thank you,
all and we're closing in on one o'clock,

740
00:59:36,845 --> 00:59:39,821
I'm just gonna close begin to close out.

741
00:59:39,845 --> 00:59:46,640
I want to thank, really thank Jeremy and
Vivek for their great presentations

742
00:59:46,640 --> 00:59:49,920
wonderful insights, there's so many
things to follow up on,

743
00:59:49,920 --> 00:59:52,661
and we are intended to do so.

744
00:59:52,685 --> 00:59:57,040
I want also thank the
production team at OEJ,

745
00:59:57,040 --> 01:00:03,155
that's Sabrina Johnson, Mat Tejada, Maria
Wallace, Rebecca Huff, Christina Motilau

746
01:00:03,179 --> 01:00:09,280
and Erica Ferro for all their hard
work and kind of putting this together.

747
01:00:09,280 --> 01:00:14,028
And of course thank you for your
participation and you're helping us share

748
01:00:14,052 --> 01:00:16,655
the word about this series.

749
01:00:16,679 --> 01:00:24,000
Our next session which is scheduled for May
5th, will focus on how this information is used,

750
01:00:24,000 --> 01:00:29,760
specifically through the eyes of youth leaders,
who are engaged in communities to secure

751
01:00:29,760 --> 01:00:32,355
meaningful public policy change.

752
01:00:32,379 --> 01:00:37,760
It will focus on groundwork USA
climate safe neighborhoods partnership,

753
01:00:37,760 --> 01:00:43,760
and our guest will be Cate Mingoya,
Melissa Guevara and Victor Medina,

754
01:00:43,760 --> 01:00:50,000
they registration information for that
session is on the slide and we will also email

755
01:00:50,000 --> 01:00:52,548
it to each and every one of you.

756
01:00:52,572 --> 01:00:55,119
Along with that, we will also email

757
01:00:55,119 --> 01:00:59,920
you an evaluation form, I
would appreciate your filling it out.

758
01:00:59,920 --> 01:01:06,755
Last thing I want to say is that we
are-- we have recorded this session

759
01:01:06,779 --> 01:01:10,788
and we are working to post the
recording of the last session.

760
01:01:10,812 --> 01:01:15,621
This is taking a little bit longer than
expected as we are trying to make sure

761
01:01:15,645 --> 01:01:21,920
that it is accessible to persons with
limited English proficiency and disabilities.

762
01:01:21,920 --> 01:01:30,319
But these will be posted and it should become
a library of great resources for all of you.

763
01:01:30,319 --> 01:01:35,040
So with that I want to close and
thank you again for participating,

764
01:01:35,040 --> 01:01:41,314
I always say that this is really a dialogue
that's very important to the future

765
01:01:41,438 --> 01:01:47,355
of our nation and so we are very
grateful, appreciative that you are paying

766
01:01:47,379 --> 01:01:50,064
so much close attention.

767
01:01:50,088 --> 01:01:56,480
With that, thank you and take
care, have a great afternoon.