1350
00:00:01,731 --> 00:00:06,521
All right, So maybe
let's get started.

1351
00:00:07,341 --> 00:00:09,256
Hello everybody.

1352
00:00:09,256 --> 00:00:11,191
Welcome to today's seminar.

1353
00:00:11,191 --> 00:00:15,525
This is a joint event
between USF and CTECH.

1354
00:00:15,525 --> 00:00:17,610
So at USF, we do have

1355
00:00:17,610 --> 00:00:20,116
the Friday transportation seminar

1356
00:00:20,116 --> 00:00:24,811
organized each Friday
during the semester.

1357
00:00:24,811 --> 00:00:26,550
And it's sponsored by

1358
00:00:26,550 --> 00:00:29,476
the Department of Civil and
Environmental Engineering

1359
00:00:29,476 --> 00:00:32,521
and also Center for Urban
Transportation Research (CUTR).

1360
00:00:32,521 --> 00:00:36,240
It's also sponsored by
three Tier One UTCs

1361
00:00:39,091 --> 00:00:43,306
at USF and also the National Center of
Congestion Reduction at USF.

1362
00:00:43,306 --> 00:00:45,750
This is a joint
event together with CTECH.

1363
00:00:45,750 --> 00:00:48,391
CTECH is a Tier One

1364
00:00:48,391 --> 00:00:52,156
UTC sponsored by USDOT,
with four partner universities,

1365
00:00:52,156 --> 00:00:55,410
Cornell University,
UT El Paso,

1366
00:00:55,410 --> 00:00:58,546
UC Davis, and 
University of South Florida.

1367
00:00:58,546 --> 00:01:02,611
My name is Yu Zhang and I'm

1368
00:01:02,611 --> 00:01:04,740
a professor in the
CEE Department

1369
00:01:04,740 --> 00:01:07,365
at USF and also with CUTR.

1370
00:01:07,365 --> 00:01:11,911
So today it's our pleasure
to have Dr. Oliver Gao

1371
00:01:11,911 --> 00:01:14,160
from Cornell University to

1372
00:01:14,160 --> 00:01:17,100
deliver a talk on 
Smart and Healthy Cities.

1373
00:01:17,100 --> 00:01:21,661
Oliver is the director of CTECH 
and he's

1374
00:01:21,661 --> 00:01:24,421
a professor with

1375
00:01:24,421 --> 00:01:27,301
the School of Civil and
Environmental Engineering

1376
00:01:27,301 --> 00:01:29,250
at Cornell University.

1377
00:01:29,250 --> 00:01:31,650
I have known Oliver
for a long time.

1378
00:01:31,650 --> 00:01:35,910
He focuses his
research on the

1379
00:01:35,910 --> 00:01:38,100
environmental issues
in transportation,

1380
00:01:38,100 --> 00:01:40,141
sustainability issues
in transportation.

1381
00:01:40,141 --> 00:01:43,365
And his research focuses on
modeling and

1382
00:01:43,365 --> 00:01:46,681
development of
systems solutions for

1383
00:01:46,681 --> 00:01:50,280
sustainable and intelligent
infrastructure systems.

1384
00:01:53,925 --> 00:01:57,660
You can see that he's a very
productive researcher and

1385
00:01:57,660 --> 00:01:59,955
has published many papers in

1386
00:01:59,955 --> 00:02:05,010
very prestigious 
transportation journals and beyond.

1387
00:02:05,010 --> 00:02:06,900
And he also served as

1388
00:02:06,900 --> 00:02:10,920
the editor in chief for
Transportation Research Part D,

1389
00:02:10,920 --> 00:02:13,606
Transport and Environment before.

1390
00:02:13,606 --> 00:02:16,620
So, without further
introduction,

1391
00:02:16,620 --> 00:02:18,886
I will give the floor to Oliver

1392
00:02:18,886 --> 00:02:21,180
and thank you for accepting

1393
00:02:21,180 --> 00:02:25,800
the invitation and thank you
for delivering this talk.

1394
00:02:25,800 --> 00:02:28,091
Looking forward to it.

1395
00:02:28,161 --> 00:02:29,610
Wonderful.

1396
00:02:29,610 --> 00:02:33,031
Thank you Yu and
thank you all for having me.

1397
00:02:33,031 --> 00:02:36,706
It's a great pleasure to
join your seminar series.

1398
00:02:36,706 --> 00:02:40,575
Good afternoon everyone.

1399
00:02:40,575 --> 00:02:41,851
It's a Friday afternoon.

1400
00:02:41,851 --> 00:02:45,211
So I will try my best to make

1401
00:02:45,211 --> 00:02:50,505
this talk as informative as possible 
and also in the meantime,

1402
00:02:50,505 --> 00:02:52,981
I want you to really
enjoy this process.

1403
00:02:52,981 --> 00:02:54,750
I would like to go
ahead and get started

1404
00:02:54,750 --> 00:02:57,376
right away. Let me see.

1405
00:02:58,891 --> 00:03:00,841
I'm going to start
with two questions.

1406
00:03:00,841 --> 00:03:03,270
Maybe someone can
help me get started.

1407
00:03:03,270 --> 00:03:07,621
Saeid, I saw you
were here earlier.

1408
00:03:07,621 --> 00:03:10,200
So if I may ask you
the first question.

1409
00:03:10,200 --> 00:03:12,855
So as an individual,

1410
00:03:12,855 --> 00:03:18,091
what is your most
valuable asset?

1411
00:03:18,091 --> 00:03:20,115
Are you there? Can you help
me answer this question?

1412
00:03:24,030 --> 00:03:25,110
Just you as an individual,

1413
00:03:25,110 --> 00:03:28,361
what is your most
valuable asset?

1414
00:03:29,181 --> 00:03:31,630
I guess?

1415
00:03:32,391 --> 00:03:35,490
The knowledge that you can gain

1416
00:03:35,490 --> 00:03:39,540
and use it in our area,
in our field.

1417
00:03:39,540 --> 00:03:42,661
Great, thank you for helping.

1418
00:03:42,661 --> 00:03:44,671
When we think
about our assets,

1419
00:03:46,021 --> 00:03:48,181
of course, when you are
working hard to get

1420
00:03:48,181 --> 00:03:50,940
your degree and 
after you graduate,

1421
00:03:50,940 --> 00:03:52,710
you are going to
make some money and

1422
00:03:52,710 --> 00:03:54,211
you're going to put
some of the money in

1423
00:03:54,211 --> 00:03:58,381
the bank. That becomes
one part of your assets.

1424
00:03:58,381 --> 00:04:00,150
Of course, you'll
make more money.

1425
00:04:00,150 --> 00:04:01,561
You're going to buy a car.

1426
00:04:01,561 --> 00:04:04,965
You're also going to
probably buy a house with a car.

1427
00:04:04,965 --> 00:04:08,055
These are all very
important assets.

1428
00:04:08,055 --> 00:04:10,155
But now Saeid, 
let me ask you again.

1429
00:04:10,155 --> 00:04:11,476
There is one asset,

1430
00:04:11,476 --> 00:04:14,310
that if you don't have,
all these other things that I listed here

1431
00:04:14,310 --> 00:04:20,415
mean nothing to you. 
Can you think of that asset?
My job?

1432
00:04:26,520 --> 00:04:28,905
What else? Anyone else would like
to give it a try?

1433
00:04:30,285 --> 00:04:31,711
Of course you have many assets,

1434
00:04:31,711 --> 00:04:34,276
but there's one asset 
which if you don't have,

1435
00:04:34,276 --> 00:04:37,420
all the other things mean
nothing to you.

1436
00:04:37,881 --> 00:04:43,231
Health.
Thank you Yu.

1437
00:04:43,231 --> 00:04:44,566
Saeid, does that make sense to you?

1438
00:04:44,566 --> 00:04:46,171
Yes.

1439
00:04:46,171 --> 00:04:52,546
That's right. You can see
that because we really work hard.

1440
00:04:52,546 --> 00:04:55,425
You work on your homework,
on your project.

1441
00:04:55,425 --> 00:04:56,761
But from time to time,

1442
00:04:56,761 --> 00:04:58,891
we have to pause and
think about what is

1443
00:04:58,891 --> 00:05:01,606
most important to
us, which is health.

1444
00:05:01,606 --> 00:05:05,715
Now, if you look at health

1445
00:05:05,715 --> 00:05:08,791
in this nation, US,
you can see that

1446
00:05:08,791 --> 00:05:10,546
we actually now spend about

1447
00:05:10,546 --> 00:05:16,066
18 percent of the
national GDP on healthcare.

1448
00:05:16,066 --> 00:05:17,941
So what is healthcare?

1449
00:05:17,941 --> 00:05:21,710
Healthcare is
essentially taking

1450
00:05:21,710 --> 00:05:25,460
care of people after
people get sick.

1451
00:05:25,460 --> 00:05:28,101
And now I just wanted to
throw one question to you

1452
00:05:28,101 --> 00:05:30,890
so that you can keep thinking
throughout this discussion.

1453
00:05:30,890 --> 00:05:33,260
So we are spending 18 percent

1454
00:05:33,260 --> 00:05:36,621
of our GDP on healthcare.

1455
00:05:36,621 --> 00:05:38,960
But health care is only

1456
00:05:38,960 --> 00:05:42,201
taking care of people
after people get sick.

1457
00:05:42,201 --> 00:05:44,046
But how often

1458
00:05:44,046 --> 00:05:46,581
have we asked or has our

1459
00:05:46,581 --> 00:05:50,481
healthcare system asked 
how did people get sick?

1460
00:05:50,481 --> 00:05:53,586
And we always know that,
we are told to

1461
00:05:53,586 --> 00:05:57,936
preventive measures can be
much more cost effective.

1462
00:05:57,936 --> 00:06:01,916
But how often do we take
preventive measures?

1463
00:06:01,916 --> 00:06:05,371
So now, this is the first 
question regarding health.

1464
00:06:05,371 --> 00:06:10,200
Now, let me ask you
a second question.

1465
00:06:10,200 --> 00:06:13,111
For the state of Florida,

1466
00:06:13,111 --> 00:06:15,301
for the city of Tampa,

1467
00:06:15,301 --> 00:06:20,731
and also for a nation
like US, India, or China,

1468
00:06:20,731 --> 00:06:25,306
what is the most important
asset for a county,

1469
00:06:25,306 --> 00:06:29,230
for a city, for a
municipality, for a country?

1470
00:06:29,931 --> 00:06:35,171
Can you think of any assets for
a country, for a state?

1471
00:06:35,241 --> 00:06:37,965
Anyone? 
Christina, are you there?

1472
00:06:37,965 --> 00:06:40,726
I'm just trying to ask

1473
00:06:40,726 --> 00:06:44,621
names that I can see
on the Zoom panel.

1474
00:06:48,521 --> 00:06:51,710
I would say, people.

1475
00:06:51,710 --> 00:06:56,280
I think that is a very important asset.
Absolutely. What else?

1476
00:07:00,281 --> 00:07:03,200
We have people answering
in the chat box.

1477
00:07:03,200 --> 00:07:06,216
Infrastructure,
natural resources.

1478
00:07:06,216 --> 00:07:08,090
Beautiful, beautiful.

1479
00:07:08,090 --> 00:07:11,105
So you can see that in the
natural resources that

1480
00:07:11,105 --> 00:07:14,961
it is a very important asset
and infrastructure.

1481
00:07:14,961 --> 00:07:18,215
We have smart people
in our chat box.

1482
00:07:18,215 --> 00:07:20,181
And also, Saeid

1483
00:07:20,181 --> 00:07:21,920
as you mentioned, people, right?

1484
00:07:23,405 --> 00:07:25,910
I bet you did not
see my slide before,

1485
00:07:25,910 --> 00:07:28,626
but you can see you have
answered this correctly.

1486
00:07:28,626 --> 00:07:30,951
These are all very
important assets.

1487
00:07:30,951 --> 00:07:33,831
So let's look at infrastructure.

1488
00:07:33,831 --> 00:07:35,481
In terms of the infrastructure,

1489
00:07:35,481 --> 00:07:37,985
what is now going on
in Washington DC?

1490
00:07:37,985 --> 00:07:40,521
What is the big thing now
going on in Washington DC?

1491
00:07:40,521 --> 00:07:44,481
What is the big thing now
many UTCs are concerned about?

1492
00:07:44,481 --> 00:07:47,841
It's about our next
infrastructure bill.

1493
00:07:47,841 --> 00:07:50,795
If you look at these
infrastructure investments

1494
00:07:50,795 --> 00:07:54,516
from developing countries
to developed countries,

1495
00:07:54,516 --> 00:07:57,815
a large proportion of our GDP,

1496
00:07:57,815 --> 00:07:59,421
a significant amount of money,

1497
00:07:59,421 --> 00:08:02,420
is invested in our
infrastructure, right?

1498
00:08:02,420 --> 00:08:07,145
So here in this talk
today, actually,

1499
00:08:07,145 --> 00:08:12,031
we're going to focus on
how our individual

1500
00:08:12,031 --> 00:08:16,590
most valuable asset and a
nation's most valuable asset,

1501
00:08:16,590 --> 00:08:21,376
how are these two sets
of assets related?

1502
00:08:21,376 --> 00:08:22,936
How are they connected?

1503
00:08:22,936 --> 00:08:26,505
They're actually
very closely related.

1504
00:08:36,780 --> 00:08:38,971
You can see that
most of the time for

1505
00:08:38,971 --> 00:08:41,730
an individual, it's
hard to figure

1506
00:08:41,730 --> 00:08:44,565
why infrastructure is
related to one's health.

1507
00:08:44,565 --> 00:08:45,931
So let's look at this.

1508
00:08:45,931 --> 00:08:47,011
How are they related?

1509
00:08:47,011 --> 00:08:49,305
So speaking of our health,

1510
00:08:49,305 --> 00:08:52,411
based on health researchers,

1511
00:08:52,411 --> 00:08:57,136
there are three major factors
that affect our health.

1512
00:08:57,136 --> 00:08:59,731
Genome, phenome,

1513
00:08:59,731 --> 00:09:03,360
and the third factor
is actually exposome.

1514
00:09:03,360 --> 00:09:05,880
Exposome, genome, phenome.

1515
00:09:05,880 --> 00:09:07,650
Of course, nowadays
people are talking a lot

1516
00:09:07,650 --> 00:09:10,516
about working on the genetics.

1517
00:09:10,516 --> 00:09:13,710
But that is
really a two-sided coin.

1518
00:09:13,710 --> 00:09:15,810
We don't know really know how like

1519
00:09:15,810 --> 00:09:18,090
when people talk about
CRISPR or

1520
00:09:18,090 --> 00:09:21,046
gene editing.

1521
00:09:21,046 --> 00:09:24,390
But let's be practical
and realistic.

1522
00:09:24,390 --> 00:09:28,456
Among the three factors
that affect our health,

1523
00:09:28,456 --> 00:09:31,621
you can see that it's
really exposome

1524
00:09:31,621 --> 00:09:34,205
that especially for civil engineers,

1525
00:09:34,205 --> 00:09:36,916
is so close to us, right?

1526
00:09:36,916 --> 00:09:40,755
So speaking of exposome
related to health,

1527
00:09:40,755 --> 00:09:43,501
we have to look at our cities.

1528
00:09:43,501 --> 00:09:45,616
We know that there's a whole world,

1529
00:09:45,616 --> 00:09:48,451
we have been
talking for more than

1530
00:09:48,451 --> 00:09:51,346
a decade about
urbanization.

1531
00:09:51,346 --> 00:09:53,176
Now, more than half of

1532
00:09:53,176 --> 00:09:55,800
all the population is
living in urban areas,

1533
00:09:55,800 --> 00:09:57,331
in the city areas.

1534
00:09:57,331 --> 00:10:00,840
So any city you go to, 
if you're flying to any city,

1535
00:10:00,840 --> 00:10:02,221
this is going to be a

1536
00:10:02,221 --> 00:10:04,381
typical picture you
are going to see.

1537
00:10:04,381 --> 00:10:06,901
Of course this is a
picture of New York City,

1538
00:10:06,901 --> 00:10:10,576
but I can imagine if
you're flying to

1539
00:10:10,576 --> 00:10:16,066
say Beijing, New
Delhi, or São Paulo,

1540
00:10:16,066 --> 00:10:18,405
this is a typical
picture you see here.

1541
00:10:18,405 --> 00:10:22,321
So in this picture,
what do we see?

1542
00:10:22,321 --> 00:10:26,086
And also if you ask
a deeper question,

1543
00:10:26,086 --> 00:10:28,605
why do we build these cities?

1544
00:10:28,605 --> 00:10:30,780
We build all these cities,

1545
00:10:30,780 --> 00:10:33,571
we build our towns
to serve people.

1546
00:10:33,571 --> 00:10:36,705
But now in this
picture of a typical city,

1547
00:10:36,705 --> 00:10:38,371
what do you see in
this picture?

1548
00:10:38,371 --> 00:10:40,126
You don't see people at all.

1549
00:10:40,126 --> 00:10:45,151
All you see is essentially
infrastructure.

1550
00:10:45,151 --> 00:10:47,416
I can give you a statistic.

1551
00:10:47,416 --> 00:10:53,885
Imagine that if you collect
all the human bodies in

1552
00:10:53,885 --> 00:10:56,750
this city and if you look
at either the mass or

1553
00:10:56,750 --> 00:11:00,171
the volume of the human
bodies versus the whole size,

1554
00:11:00,171 --> 00:11:02,150
the whole mass of the city,

1555
00:11:02,150 --> 00:11:05,961
the total volume of human
bodies accounts for less than

1556
00:11:05,961 --> 00:11:10,790
0.01% of the whole
volume of the city,

1557
00:11:10,790 --> 00:11:13,580
which consists
mostly of infrastructure.

1558
00:11:13,580 --> 00:11:16,010
We are building all
these huge cities

1559
00:11:16,010 --> 00:11:19,890
to serve less than 0.01%,

1560
00:11:20,291 --> 00:11:25,971
that is the body or the
mass of human beings.

1561
00:11:25,971 --> 00:11:29,165
And don't forget how
we build the cities.

1562
00:11:29,165 --> 00:11:32,256
We move concrete.

1563
00:11:32,256 --> 00:11:34,745
We move cement from

1564
00:11:34,745 --> 00:11:40,370
mountains to cities and we
build these concrete jungles.

1565
00:11:40,370 --> 00:11:44,885
And of course, you can
imagine one pound of

1566
00:11:44,885 --> 00:11:47,435
cement from the production

1567
00:11:47,435 --> 00:11:50,780
all the way to the
usage in the building.

1568
00:11:50,780 --> 00:11:53,661
One ton of cement
corresponds to

1569
00:11:53,661 --> 00:11:57,275
one ton of carbon
dioxide emissions.

1570
00:11:57,275 --> 00:11:59,045
So what are we doing here?

1571
00:11:59,045 --> 00:11:59,390
Right?

1572
00:12:01,751 --> 00:12:04,731
Now imagine that
you are

1573
00:12:04,731 --> 00:12:06,981
taking an airplane and you
get closer to the city.

1574
00:12:06,981 --> 00:12:08,631
You check in to a hotel,
you look out of

1575
00:12:08,631 --> 00:12:10,836
the hotel room, now
you see people.

1576
00:12:10,836 --> 00:12:13,476
Now when you see all these
people in the street,

1577
00:12:13,476 --> 00:12:15,651
you can see all the people

1578
00:12:15,651 --> 00:12:18,670
having to do with transportation. 
Either walking,

1579
00:12:18,670 --> 00:12:20,685
or taking the taxi,
taking the bus,

1580
00:12:20,685 --> 00:12:23,280
or taking the 
subway train, right?

1581
00:12:23,280 --> 00:12:27,641
So let me show you
another picture here.

1582
00:12:28,371 --> 00:12:30,631
Among those in the audience,

1583
00:12:30,631 --> 00:12:32,715
you either have children or adolescents,

1584
00:12:32,715 --> 00:12:34,771
and you were once children.

1585
00:12:34,771 --> 00:12:38,191
Can you imagine what these
children are doing here?

1586
00:12:38,191 --> 00:12:43,186
They are actually
playing with the ants.

1587
00:12:43,186 --> 00:12:47,656
They are moving the rocks
along the path of the ants.

1588
00:12:47,656 --> 00:12:50,145
Now can you imagine if one of the kids

1589
00:12:50,145 --> 00:12:54,255
puts a rock on the
path of the ants,

1590
00:12:54,255 --> 00:12:56,506
what would the ants do?

1591
00:12:56,506 --> 00:13:00,405
The ants will adjust
their behavior

1592
00:13:00,405 --> 00:13:03,151
and adapt to the
new environment.

1593
00:13:03,151 --> 00:13:05,956
So this is why I actually say that

1594
00:13:05,956 --> 00:13:09,946
these kids here are building the
urban infrastructure for ants.

1595
00:13:09,946 --> 00:13:12,585
And also the ants will
adjust their behavior.

1596
00:13:12,585 --> 00:13:17,041
So now you look 
at this picture again, Saeid.

1597
00:13:17,041 --> 00:13:18,631
Imagine if you're 
in the hotel room

1598
00:13:18,631 --> 00:13:20,056
looking out from the
hotel window.

1599
00:13:20,056 --> 00:13:22,570
Now what do we see on the street?

1600
00:13:22,731 --> 00:13:30,210
I see people using infrastructure
for their daily needs.

1601
00:13:30,210 --> 00:13:33,256
And then from the
previous slide here,

1602
00:13:33,256 --> 00:13:37,590
now you look at this, 
do you see any analogy?

1603
00:13:37,590 --> 00:13:39,090
You know like people moving,

1604
00:13:39,090 --> 00:13:41,925
people living in this
infrastructure,

1605
00:13:41,925 --> 00:13:44,911
do they seem like
ants, you know,

1606
00:13:44,911 --> 00:13:49,950
kind of facing those rocks
in this picture?

1607
00:13:49,950 --> 00:13:50,836
Yes.

1608
00:13:50,836 --> 00:13:53,265
So my point is that.

1609
00:13:53,265 --> 00:13:56,911
I'm going to say that
human activities,

1610
00:13:56,911 --> 00:14:00,330
our daily life, our behavior.

1611
00:14:00,330 --> 00:14:02,686
Of course, most of us,

1612
00:14:02,686 --> 00:14:04,141
a lot of us think that

1613
00:14:04,141 --> 00:14:06,046
we are in a graduate program

1614
00:14:06,046 --> 00:14:08,205
in a very good
university, right?

1615
00:14:08,205 --> 00:14:10,170
We feel we've
been very successful,

1616
00:14:10,170 --> 00:14:13,335
we feel that we are in
control of our life.

1617
00:14:13,335 --> 00:14:15,135
But look at this picture,

1618
00:14:15,135 --> 00:14:16,755
I can tell you actually,

1619
00:14:16,755 --> 00:14:18,331
you are in control of

1620
00:14:18,331 --> 00:14:22,126
no more than 10 percent of
your life,

1621
00:14:22,126 --> 00:14:25,231
your lifestyle,
the way you move.

1622
00:14:25,231 --> 00:14:26,581
For example, this morning,

1623
00:14:26,581 --> 00:14:29,370
when you went from

1624
00:14:29,370 --> 00:14:33,510
your apartment to your
classroom to take the courses,

1625
00:14:33,510 --> 00:14:35,190
your behavior,

1626
00:14:35,190 --> 00:14:36,300
you saw that okay

1627
00:14:36,300 --> 00:14:38,161
I'm moving, I was walking by

1628
00:14:38,161 --> 00:14:40,921
but you were following certain
paths. Those certain paths

1629
00:14:40,921 --> 00:14:44,310
were defined by the existing
urban infrastructure.

1630
00:14:44,310 --> 00:14:49,005
So urban infrastructure
defines your behavior.

1631
00:14:49,005 --> 00:14:51,015
And more importantly,

1632
00:14:51,015 --> 00:14:53,415
the urban infrastructure
investment

1633
00:14:53,415 --> 00:14:56,505
is one, irreversible.

1634
00:14:56,505 --> 00:14:58,891
Once it's invested,
when it's built,

1635
00:14:58,891 --> 00:15:01,441
it's very hard 
to reverse it.

1636
00:15:01,441 --> 00:15:04,201
And the second, as soon as

1637
00:15:04,201 --> 00:15:05,970
infrastructure is
done, it will

1638
00:15:05,970 --> 00:15:07,776
start shaping your behavior.

1639
00:15:09,420 --> 00:15:12,270
Just look at, of
course, the US.

1640
00:15:12,270 --> 00:15:13,831
We have been very successful.

1641
00:15:13,831 --> 00:15:16,935
Especially Hollywood
has been very successful.

1642
00:15:16,935 --> 00:15:21,031
All the Hollywood movies,
the American dreams,

1643
00:15:21,031 --> 00:15:22,830
the lifestyle that

1644
00:15:22,830 --> 00:15:25,410
many developing countries
have picked up.

1645
00:15:25,410 --> 00:15:26,596
That dream.

1646
00:15:26,596 --> 00:15:28,500
Look at what happened in

1647
00:15:28,500 --> 00:15:30,960
the past few decades in
developing countries.

1648
00:15:30,960 --> 00:15:33,690
Even successful developing
countries like India and China,

1649
00:15:33,690 --> 00:15:35,715
their economy has
developed so much.

1650
00:15:35,715 --> 00:15:38,101
Their urban infrastructure.

1651
00:15:38,101 --> 00:15:39,435
Look at the roads,

1652
00:15:39,435 --> 00:15:41,235
look at the buildings.

1653
00:15:41,235 --> 00:15:44,535
And then you look at what is
happening to those children.

1654
00:15:44,535 --> 00:15:47,521
Before, when I was young,

1655
00:15:47,521 --> 00:15:52,321
I went to school riding
a bicycle or walking.

1656
00:15:52,321 --> 00:15:53,956
And now all the kids,

1657
00:15:53,956 --> 00:15:55,681
most of the time, they are

1658
00:15:55,681 --> 00:15:57,346
in the backseat of  cars.

1659
00:15:57,346 --> 00:16:03,765
So when they grow up, 
cars are like their legs.

1660
00:16:03,765 --> 00:16:07,336
The future generations

1661
00:16:07,336 --> 00:16:09,586
of the current generation in the US,

1662
00:16:09,586 --> 00:16:12,046
they will be so used to

1663
00:16:12,046 --> 00:16:15,181
the ride-on-the-wheel 
lifestyle.

1664
00:16:15,181 --> 00:16:16,921
And then in the future
we will realize, oh,

1665
00:16:16,921 --> 00:16:18,421
actually we should not do that.

1666
00:16:18,421 --> 00:16:20,300
We want to change
our infrastructure.

1667
00:16:20,300 --> 00:16:24,436
You realize that
the difficulty is,

1668
00:16:26,555 --> 00:16:29,131
reversing the infrastructure.

1669
00:16:29,131 --> 00:16:32,550
Those kids, 
those future generations

1670
00:16:32,550 --> 00:16:34,096
are used to cars.

1671
00:16:34,096 --> 00:16:36,061
They don't want you to change.

1672
00:16:36,061 --> 00:16:38,221
You can see
the cycle here.

1673
00:16:38,221 --> 00:16:42,661
So how is our built environment,
including transportation, how are they

1674
00:16:42,661 --> 00:16:45,721
shaping our lives and health?

1675
00:16:45,721 --> 00:16:48,226
Just going to give you some
quick statistics.

1676
00:16:48,226 --> 00:16:49,980
Traffic safety. 
Many of you have

1677
00:16:49,980 --> 00:16:52,366
probably conducted
research in traffic safety.

1678
00:16:52,366 --> 00:16:54,285
Just look at these statistics.

1679
00:16:54,285 --> 00:16:57,330
All these
yellow car crashes,

1680
00:16:57,330 --> 00:17:00,766
car accidents, and also
the injuries,

1681
00:17:00,766 --> 00:17:08,116
they all translate
into big bills of health cost.

1682
00:17:08,116 --> 00:17:09,570
So now what do we do?

1683
00:17:09,570 --> 00:17:12,811
Let's do our best to make 
our transportation safe.

1684
00:17:12,811 --> 00:17:17,565
But even if we make our
transportation safe, are we okay?

1685
00:17:17,565 --> 00:17:21,616
I'm not sure if any of you
have seen such a picture.

1686
00:17:21,616 --> 00:17:24,961
Standing behind this bus
could be more dangerous

1687
00:17:24,961 --> 00:17:26,535
than standing in front of it.

1688
00:17:26,535 --> 00:17:28,260
Standing in front of the bus could be

1689
00:17:28,260 --> 00:17:29,521
dangerous because you can see

1690
00:17:29,521 --> 00:17:32,820
that the bus could hit you
and it could be an accident.

1691
00:17:32,820 --> 00:17:35,521
But even when you are
standing behind the bus,

1692
00:17:35,521 --> 00:17:39,616
most of our buses nowadays
are powered by diesel.

1693
00:17:39,616 --> 00:17:43,471
Diesel fumes, diesel
emissions, can cause cancer.

1694
00:17:43,471 --> 00:17:45,466
They can kill.
Actually you can see that

1695
00:17:45,466 --> 00:17:48,466
based on the paper published
in 2000 in Lancet.

1696
00:17:48,466 --> 00:17:51,826
More people are killed
by vehicle emissions

1697
00:17:51,826 --> 00:17:54,421
than by traffic accidents.

1698
00:17:54,421 --> 00:17:57,705
Let's say, if we make
our transportation

1699
00:17:57,705 --> 00:18:03,040
safe and clean, are
we going to be okay?

1700
00:18:03,831 --> 00:18:07,516
Unfortunately, look
at the obesity rate

1701
00:18:07,516 --> 00:18:10,741
from 1996 to 2016.

1702
00:18:10,741 --> 00:18:13,421
Look what's happening.

1703
00:18:13,761 --> 00:18:15,960
Now I hope you

1704
00:18:15,960 --> 00:18:17,820
agree with me that

1705
00:18:17,820 --> 00:18:23,745
infrastructure does
significantly affect our health.

1706
00:18:23,745 --> 00:18:26,101
So in a brief summary,

1707
00:18:26,101 --> 00:18:27,631
you can see that while we are

1708
00:18:27,631 --> 00:18:30,676
enjoying the mobility service,

1709
00:18:30,676 --> 00:18:34,066
enjoying the goods coming
from all the different places,

1710
00:18:34,066 --> 00:18:37,185
all enabled by transportation.

1711
00:18:37,185 --> 00:18:39,136
But not many of us

1712
00:18:39,136 --> 00:18:44,026
realize this huge
cost, this externality.

1713
00:18:44,026 --> 00:18:49,441
Sorry, this is a beautiful
Friday afternoon

1714
00:18:49,441 --> 00:18:51,331
and I kind of

1715
00:18:51,331 --> 00:18:54,001
painted such a gloomy
picture in front of you.

1716
00:18:54,001 --> 00:18:57,315
We cannot help asking
ourselves what's wrong,

1717
00:18:57,315 --> 00:18:59,200
what's the problem?

1718
00:18:59,200 --> 00:19:02,161
As researchers, as
future leaders

1719
00:19:02,161 --> 00:19:04,861
when you see 
all these issues,

1720
00:19:04,861 --> 00:19:07,156
you will ask 
"What is going wrong?

1721
00:19:07,156 --> 00:19:08,685
What's the problem?"

1722
00:19:08,685 --> 00:19:12,600
Since most people

1723
00:19:12,600 --> 00:19:14,550
are probably either studying

1724
00:19:14,550 --> 00:19:17,236
or are in the profession of
transportation,

1725
00:19:17,236 --> 00:19:19,231
you may be very familiar with

1726
00:19:19,231 --> 00:19:22,081
this picture. 
From the left to the right,

1727
00:19:22,081 --> 00:19:24,886
this is essentially
the evolution

1728
00:19:24,886 --> 00:19:27,480
of our human transportation.

1729
00:19:27,480 --> 00:19:30,046
What did we gain?

1730
00:19:30,046 --> 00:19:33,840
We got faster,
faster and faster.

1731
00:19:33,840 --> 00:19:37,561
We gained a lot of
physical efficiency.

1732
00:19:37,561 --> 00:19:40,965
You can see that
throughout this process,

1733
00:19:40,965 --> 00:19:43,396
there were a lot of
innovations, right?

1734
00:19:43,396 --> 00:19:44,986
But it was along the lines

1735
00:19:44,986 --> 00:19:46,981
of improvement in the
physical efficiency.

1736
00:19:46,981 --> 00:19:49,156
And in addition, human beings,

1737
00:19:49,156 --> 00:19:51,105
we are not only smart,

1738
00:19:51,105 --> 00:19:53,400
human beings are also greedy.

1739
00:19:53,400 --> 00:19:55,291
We wanted to achieve

1740
00:19:55,291 --> 00:19:57,870
all this physical efficiency

1741
00:19:57,870 --> 00:19:59,940
through economic efficiency.

1742
00:19:59,940 --> 00:20:03,120
We want to spend the least
money to do all these things.

1743
00:20:03,120 --> 00:20:05,221
If you look at the decision-making,

1744
00:20:05,221 --> 00:20:08,746
either yourself as an individual

1745
00:20:08,746 --> 00:20:11,896
or group decisions
in Washington DC

1746
00:20:11,896 --> 00:20:14,085
for our infrastructure bills,

1747
00:20:14,085 --> 00:20:15,480
you're going to see that
mostly they are

1748
00:20:15,480 --> 00:20:17,100
looking at these dimensions,

1749
00:20:17,100 --> 00:20:20,401
physical efficiency,
economic efficiency.

1750
00:20:20,401 --> 00:20:21,841
But how often

1751
00:20:21,841 --> 00:20:23,025
can you see that these kinds of

1752
00:20:23,025 --> 00:20:26,685
tailpipe emissions would
come into the equation?

1753
00:20:26,685 --> 00:20:27,931
No.

1754
00:20:27,931 --> 00:20:29,401
They were not in the equation.

1755
00:20:29,401 --> 00:20:32,011
But if such kind of issues

1756
00:20:32,011 --> 00:20:34,201
are not even in the equation,

1757
00:20:34,201 --> 00:20:37,621
how can you expect
that the cities

1758
00:20:37,621 --> 00:20:41,581
would put your health
as a priority?

1759
00:20:41,581 --> 00:20:44,581
That's why you can see last
year when we were in

1760
00:20:44,581 --> 00:20:47,040
the pandemic and people

1761
00:20:47,040 --> 00:20:49,200
started thinking
about cities again,

1762
00:20:49,200 --> 00:20:52,081
many people fled away
from the cities.

1763
00:20:52,081 --> 00:20:53,685
And you can ask

1764
00:20:53,685 --> 00:20:56,116
why we are building these cities.

1765
00:20:56,116 --> 00:20:59,446
What criteria should we
follow in building our cities?

1766
00:20:59,446 --> 00:21:03,600
I think nowadays it's really
a good time for all of us,

1767
00:21:03,600 --> 00:21:06,391
from individual citizens
to the decision-makers,

1768
00:21:06,391 --> 00:21:07,996
to academics,

1769
00:21:07,996 --> 00:21:10,650
it really gives us the
opportunity to think about

1770
00:21:10,650 --> 00:21:12,646
what we have been

1771
00:21:12,646 --> 00:21:15,721
pursuing in our city 
and regional planning,

1772
00:21:15,721 --> 00:21:19,366
and in our transportation.

1773
00:21:19,366 --> 00:21:23,385
Well, our education system,
universities,

1774
00:21:23,385 --> 00:21:27,631
have also been problematic.

1775
00:21:27,631 --> 00:21:30,645
Look at USF, look at Cornell.

1776
00:21:30,645 --> 00:21:32,596
Here at the bottom

1777
00:21:32,596 --> 00:21:35,250
we have this infrastructure.

1778
00:21:35,250 --> 00:21:38,040
Civil engineers contributed
a lot to this.

1779
00:21:38,040 --> 00:21:41,026
So civil engineers,
mechanical engineers,

1780
00:21:41,026 --> 00:21:42,961
or even operations researchers,

1781
00:21:42,961 --> 00:21:44,535
they are trained to

1782
00:21:44,535 --> 00:21:46,501
optimize how we

1783
00:21:46,501 --> 00:21:48,960
can make this whole
system more efficient.

1784
00:21:48,960 --> 00:21:52,335
But while they're building
these things,

1785
00:21:52,335 --> 00:21:55,141
they do not realize that
emissions that come into

1786
00:21:55,141 --> 00:21:58,321
the air will pollute
the air that we breathe.

1787
00:21:58,321 --> 00:22:01,771
However, civil engineers,
we seldom know that.

1788
00:22:01,771 --> 00:22:04,260
And plus, this air pollution

1789
00:22:04,260 --> 00:22:07,560
will in the end
impact public health.

1790
00:22:07,560 --> 00:22:12,330
So let me just ask
all of you in this audience.

1791
00:22:12,330 --> 00:22:15,360
How often have you been in

1792
00:22:15,360 --> 00:22:17,700
the same classroom or in

1793
00:22:17,700 --> 00:22:21,166
the same conference where
you have civil engineers,

1794
00:22:21,166 --> 00:22:23,626
mechanical engineers,
environmental scientists,

1795
00:22:23,626 --> 00:22:25,846
and health researchers together

1796
00:22:25,846 --> 00:22:28,320
talking about urban design,

1797
00:22:28,320 --> 00:22:30,421
talking about new technologies?

1798
00:22:30,421 --> 00:22:36,781
Unfortunately, our education
system has also been siloed.

1799
00:22:36,781 --> 00:22:39,691
Each department has

1800
00:22:39,691 --> 00:22:41,101
their individual silos.

1801
00:22:41,101 --> 00:22:45,421
So imagine that if we're
producing these silos,

1802
00:22:45,421 --> 00:22:47,280
a student who will end up in

1803
00:22:47,280 --> 00:22:50,655
the siloed government
departments.

1804
00:22:50,655 --> 00:22:54,106
So how can we imagine that we can,

1805
00:22:54,106 --> 00:22:56,221
we will be able to view

1806
00:22:56,221 --> 00:22:59,911
this whole system and see
all these problems? Because look,

1807
00:22:59,911 --> 00:23:03,361
the root of the problem, for example,
from transportation emission

1808
00:23:03,361 --> 00:23:05,191
is really related
to transportation

1809
00:23:05,191 --> 00:23:06,301
which is in the hands of

1810
00:23:06,301 --> 00:23:08,461
civil engineers or
transportation engineers.

1811
00:23:08,461 --> 00:23:10,636
But the problem
is up in the air.

1812
00:23:10,636 --> 00:23:12,151
We have never met a scientist

1813
00:23:12,151 --> 00:23:14,131
who published science papers,

1814
00:23:14,131 --> 00:23:17,476
major papers to call out
all these problems.

1815
00:23:17,476 --> 00:23:20,085
But civil engineers,
transportation engineers,

1816
00:23:20,085 --> 00:23:22,015
they probably don't know that.

1817
00:23:22,015 --> 00:23:25,686
So that's why you can see that.

1818
00:23:25,686 --> 00:23:27,035
What can we do?

1819
00:23:27,035 --> 00:23:30,500
What must we do to
overcome all these issues?

1820
00:23:30,500 --> 00:23:33,471
That's why the Center
for Transportation,

1821
00:23:33,471 --> 00:23:35,526
Environment, and
Community Health,

1822
00:23:35,526 --> 00:23:37,220
this USDOT center,

1823
00:23:37,220 --> 00:23:40,520
a very unique center,
we are promoting,

1824
00:23:40,520 --> 00:23:44,225
we're advocating the system
integrative approach

1825
00:23:44,225 --> 00:23:45,606
to infrastructure,

1826
00:23:45,606 --> 00:23:48,215
transportation,
environment, and health,

1827
00:23:48,215 --> 00:23:52,640
from planning to the design
and operations management.

1828
00:23:52,640 --> 00:23:54,231
How can we do that?

1829
00:23:54,231 --> 00:23:56,976
So you can see now

1830
00:23:56,976 --> 00:23:58,296
for most of urban planning,

1831
00:23:58,296 --> 00:23:59,585
this is separated.

1832
00:23:59,585 --> 00:24:01,685
First, we want to build

1833
00:24:01,685 --> 00:24:04,676
quantitative
models to translate

1834
00:24:04,676 --> 00:24:08,521
all the infrastructure
policies and plans and designs

1835
00:24:08,521 --> 00:24:13,096
into the impacts on the
environment and on health.

1836
00:24:13,096 --> 00:24:15,301
First you need to be
able to quantify that

1837
00:24:15,301 --> 00:24:17,956
because the other
story I told you so far,

1838
00:24:17,956 --> 00:24:20,160
if you tell the
same story to the

1839
00:24:20,160 --> 00:24:22,816
mayors, to the governors,

1840
00:24:22,816 --> 00:24:25,110
they'll say, "Oh, Oliver,
I want to do something,

1841
00:24:25,110 --> 00:24:26,461
but I don't know how,

1842
00:24:26,461 --> 00:24:27,840
what will be the
effective way?"

1843
00:24:27,840 --> 00:24:30,511
So as researchers,
as educators,

1844
00:24:30,511 --> 00:24:34,110
we have the responsibility
to develop new knowledge,

1845
00:24:34,110 --> 00:24:35,731
develop signs, and develop

1846
00:24:35,731 --> 00:24:38,731
tools to support
the practitioners.

1847
00:24:38,731 --> 00:24:41,086
So first we quantify the impact.

1848
00:24:41,086 --> 00:24:45,525
And in addition, we
want to proactively

1849
00:24:45,525 --> 00:24:51,630
fit all these impacts back
into the planning, design

1850
00:24:51,630 --> 00:24:56,445
and decision process such
that we avoid mistakes.

1851
00:24:56,445 --> 00:24:58,020
As I mentioned earlier,

1852
00:24:58,020 --> 00:25:01,155
infrastructure investment
is irreversible.

1853
00:25:01,155 --> 00:25:03,870
So now with this
system approach,

1854
00:25:03,870 --> 00:25:07,170
which is better with today's
modeling capabilities,

1855
00:25:07,170 --> 00:25:08,911
we can help the decision-makers

1856
00:25:08,911 --> 00:25:12,871
avoid those deep hole mistakes.

1857
00:25:12,871 --> 00:25:15,015
How do we do that?

1858
00:25:15,015 --> 00:25:21,301
Alright, so here I show
a simplified flow chart.

1859
00:25:21,301 --> 00:25:24,330
Sorry this might be a
very busy chart for you.

1860
00:25:24,330 --> 00:25:27,331
But of course you can see
that as I mentioned earlier,

1861
00:25:27,331 --> 00:25:29,371
since one of the roots of our problem

1862
00:25:29,371 --> 00:25:33,406
is this siloed education,
siloed training,

1863
00:25:33,406 --> 00:25:35,731
that's why you can see
from the training,

1864
00:25:35,731 --> 00:25:39,586
we want to have more engineers,

1865
00:25:39,586 --> 00:25:44,610
planners to be equipped with
infrastructure systems,

1866
00:25:44,610 --> 00:25:47,250
analytical views, and tools.

1867
00:25:47,250 --> 00:25:49,560
We don't have many
people like that

1868
00:25:49,560 --> 00:25:51,780
so far,  but I have
been very fortunate.

1869
00:25:51,780 --> 00:25:53,880
It's interesting that when I
was doing my undergrad

1870
00:25:53,880 --> 00:25:56,851
I got my undergrad
degree in civil engineering.

1871
00:25:56,851 --> 00:25:58,891
But in the meantime, I got to do

1872
00:25:58,891 --> 00:26:02,596
a degree in environmental
science.

1873
00:26:02,596 --> 00:26:05,640
When I was doing my senior
thesis at that time,

1874
00:26:05,640 --> 00:26:07,680
my senior thesis topic was

1875
00:26:07,680 --> 00:26:10,216
transportation and air
quality in Beijing.

1876
00:26:10,216 --> 00:26:11,956
That was back in 1996.

1877
00:26:11,956 --> 00:26:14,370
I can tell you the
air quality back in

1878
00:26:14,370 --> 00:26:19,351
1996 was much better than
what Beijing has nowadays.

1879
00:26:19,351 --> 00:26:21,871
So anyway, and then when I was

1880
00:26:21,871 --> 00:26:24,541
doing my PhD, my PhD advisor,

1881
00:26:24,541 --> 00:26:27,301
she is a transportation
emission modeler

1882
00:26:27,301 --> 00:26:30,196
and the other two committee
members on my committee,

1883
00:26:30,196 --> 00:26:33,151
they are what people

1884
00:26:33,151 --> 00:26:37,231
jokingly call the Caltech
mafia of air quality modeling.

1885
00:26:37,231 --> 00:26:39,270
So I had two committee members

1886
00:26:39,270 --> 00:26:41,460
with expertise in
air quality modeling.

1887
00:26:41,460 --> 00:26:42,990
So I have been fortunate to be

1888
00:26:42,990 --> 00:26:45,810
trained in this
cross-disciplinary way.

1889
00:26:45,810 --> 00:26:47,370
So you can see

1890
00:26:47,370 --> 00:26:48,631
now we look back to

1891
00:26:48,631 --> 00:26:51,420
these models from economic
development,

1892
00:26:51,420 --> 00:26:53,775
energy systems, policy,
technology, behavior

1893
00:26:53,775 --> 00:26:56,116
and then through all
these transportation models,

1894
00:26:56,116 --> 00:26:57,405
emissions models,

1895
00:26:57,405 --> 00:27:00,165
air quality models, BenMAP,

1896
00:27:00,165 --> 00:27:02,341
exposure models, and then together

1897
00:27:02,341 --> 00:27:04,891
you can see that here
at CTECH we have

1898
00:27:04,891 --> 00:27:07,861
integrated all these
models together into

1899
00:27:07,861 --> 00:27:12,660
an integrated analytical
tool for us to analyze

1900
00:27:12,660 --> 00:27:15,661
different policies from
economic development to

1901
00:27:15,661 --> 00:27:18,645
behavior change, to
technology adoption.

1902
00:27:18,645 --> 00:27:20,071
You can see that of course, we have

1903
00:27:20,071 --> 00:27:23,310
all this feedback from
the transportation, right,

1904
00:27:23,310 --> 00:27:25,816
the traffic, emissions, and then

1905
00:27:25,816 --> 00:27:28,966
toxic air pollutants,

1906
00:27:28,966 --> 00:27:31,156
greenhouse gas
emissions, all this and

1907
00:27:31,156 --> 00:27:33,661
feedback on the top
to the land use.

1908
00:27:33,661 --> 00:27:35,056
And also you can see in

1909
00:27:35,056 --> 00:27:37,951
travel demand model
we have activity-based,

1910
00:27:37,951 --> 00:27:39,376
the travel demand model,

1911
00:27:39,376 --> 00:27:43,126
US EPA's MOVES model
for emissions modeling,

1912
00:27:43,126 --> 00:27:46,231
and then AERMOD and also
the exporter model.

1913
00:27:46,231 --> 00:27:48,165
All these things
can be integrated.

1914
00:27:48,165 --> 00:27:51,976
So here, I just want to give
you some specific examples.

1915
00:27:51,976 --> 00:27:57,286
As I claimed before, I
said that infrastructure

1916
00:27:57,286 --> 00:27:59,280
impacts our health.

1917
00:27:59,280 --> 00:28:00,841
Is that true?

1918
00:28:00,841 --> 00:28:04,200
Right, so this is a
study where we looked at

1919
00:28:04,200 --> 00:28:07,216
about 13,000
heart failure patients

1920
00:28:07,216 --> 00:28:11,146
in New York City
from 2012 to 2017.

1921
00:28:11,146 --> 00:28:14,176
Of course, we also
definitely control

1922
00:28:14,176 --> 00:28:16,981
the individual
covariates like their age,

1923
00:28:16,981 --> 00:28:19,951
gender, BMI, education, income.

1924
00:28:19,951 --> 00:28:23,820
After all those variables
had been controlled,

1925
00:28:23,820 --> 00:28:27,510
we looked at the impact
of the built environment.

1926
00:28:27,510 --> 00:28:29,131
For example, 
the walkability of

1927
00:28:29,131 --> 00:28:31,636
the neighborhood, air
pollution, traffic exposure,

1928
00:28:31,636 --> 00:28:33,375
and all these

1929
00:28:33,375 --> 00:28:35,685
different individual
components, right?

1930
00:28:35,685 --> 00:28:38,401
So this is the
result of our model.

1931
00:28:38,401 --> 00:28:43,125
So this x-axis shows
the odds ratio,

1932
00:28:43,125 --> 00:28:47,686
the odds ratio of a patient
dying due to heart failure.

1933
00:28:47,686 --> 00:28:50,161
You can see that after we have

1934
00:28:50,161 --> 00:28:52,230
controlled all the
individual variables,

1935
00:28:52,230 --> 00:28:54,885
all these built
environment variables,

1936
00:28:54,885 --> 00:29:00,046
they all have odds ratios
significantly above one.

1937
00:29:00,046 --> 00:29:02,280
Which means that they
all significantly

1938
00:29:02,280 --> 00:29:05,236
impact our physical health.

1939
00:29:05,236 --> 00:29:07,305
How about mental health?

1940
00:29:07,305 --> 00:29:08,986
How about mental health?

1941
00:29:08,986 --> 00:29:15,271
So we look at the incidence of postpartum depression.

1942
00:29:15,271 --> 00:29:19,261
Basically, baby blue,

1943
00:29:19,261 --> 00:29:23,490
that occurs in some women after they give birth.

1944
00:29:23,490 --> 00:29:27,330
There is a high tendency
that they could develop

1945
00:29:27,330 --> 00:29:31,441
this postpartum
depression, or baby blue.

1946
00:29:31,441 --> 00:29:34,620
So we again look at this
data about

1947
00:29:34,620 --> 00:29:36,766
10,000 individuals,

1948
00:29:36,766 --> 00:29:38,866
control their individual covariates,

1949
00:29:38,866 --> 00:29:42,125
and look at how the built
environment impacts

1950
00:29:42,125 --> 00:29:45,410
the rate of
developing depression

1951
00:29:45,410 --> 00:29:47,331
after giving birth to babies.

1952
00:29:47,331 --> 00:29:48,890
Again, you can see that all

1953
00:29:48,890 --> 00:29:50,706
these built environment factors,

1954
00:29:50,706 --> 00:29:54,501
they turn out to be
very significant

1955
00:29:54,501 --> 00:29:56,405
in affecting the odds

1956
00:29:56,405 --> 00:29:59,616
of women developing
postpartum depression.

1957
00:29:59,616 --> 00:30:02,241
So here, this is
another example where

1958
00:30:02,241 --> 00:30:05,440
we developed a 
software tool that

1959
00:30:05,440 --> 00:30:09,461
combines the activity-based
travel demand model

1960
00:30:09,461 --> 00:30:11,185
of New York City with

1961
00:30:11,185 --> 00:30:16,450
EPA's MOVES emission
factor model to support

1962
00:30:16,450 --> 00:30:22,121
the transportation conformity
requirement by EPA and the DOT.

1963
00:30:22,121 --> 00:30:26,335
So we can see that for any
future scenarios in New York City,

1964
00:30:26,335 --> 00:30:29,891
any transportation or 
infrastructure investment,

1965
00:30:29,891 --> 00:30:33,640
can be modeled through
first the travel demand model,

1966
00:30:33,640 --> 00:30:36,056
and then this post-processing

1967
00:30:36,056 --> 00:30:39,281
software to give the
decision-maker as well

1968
00:30:39,281 --> 00:30:43,150
as the general public how
all the future transportation

1969
00:30:43,150 --> 00:30:47,965
plan's are going to impact the
emissions and air quality

1970
00:30:47,965 --> 00:30:49,181
in the New York City area.

1971
00:30:49,181 --> 00:30:51,220
So this software
has been used as

1972
00:30:51,220 --> 00:30:54,161
the official software
since 2012 for

1973
00:30:54,161 --> 00:30:56,306
transportation conformity for

1974
00:30:56,306 --> 00:30:58,960
New York City.  By the way,
New York City is so far

1975
00:30:58,960 --> 00:31:01,361
the only city that
has been equipped

1976
00:31:01,361 --> 00:31:04,705
with this web-based software.

1977
00:31:04,705 --> 00:31:09,565
Here you can see that we also
have very finely resolved

1978
00:31:11,561 --> 00:31:14,126
hour by hour, and link by link emissions,

1979
00:31:14,126 --> 00:31:15,775
that can be used further for

1980
00:31:15,775 --> 00:31:18,416
exposure assessment.

1981
00:31:18,416 --> 00:31:22,090
And then of course, when
emissions come out in the air,

1982
00:31:22,090 --> 00:31:24,716
it will be transported
to the downwind.

1983
00:31:24,716 --> 00:31:27,401
The tricky thing
is that, you know,

1984
00:31:27,401 --> 00:31:32,065
the atmospheric system
is not only non-linear,

1985
00:31:32,065 --> 00:31:35,710
it also has so many different
photochemical reactions.

1986
00:31:35,710 --> 00:31:38,050
That's mainly what many

1987
00:31:38,050 --> 00:31:40,991
atmospheric scientists 
today do to develop

1988
00:31:40,991 --> 00:31:43,721
all these non-linear
complicated models to

1989
00:31:43,721 --> 00:31:45,491
simulate what is happening

1990
00:31:45,491 --> 00:31:47,861
physically and chemically
in the atmosphere.

1991
00:31:47,861 --> 00:31:51,971
So this is the result showing
the ozone concentration

1992
00:31:51,971 --> 00:31:53,891
and PM2.5 concentration after

1993
00:31:53,891 --> 00:31:56,741
considering all those
photochemical reactions.

1994
00:31:56,741 --> 00:31:58,840
So again in our group,
we have integrated

1995
00:31:58,840 --> 00:32:00,685
all these things together
and then we apply,

1996
00:32:00,685 --> 00:32:03,746
for example, that
software to look at

1997
00:32:03,746 --> 00:32:05,636
now a very hot topic,

1998
00:32:05,636 --> 00:32:08,801
congestion pricing
in New York City, right?

1999
00:32:08,801 --> 00:32:11,770
Cordon pricing.
They're talking about people entering

2000
00:32:11,770 --> 00:32:15,820
into lower Manhattan,
beneath 60th street.

2001
00:32:15,820 --> 00:32:20,380
They're talking about charging
a cordon pricing fee.

2002
00:32:20,380 --> 00:32:23,531
So we looked at how

2003
00:32:23,531 --> 00:32:28,346
the different tolling rate
would impact the emissions.

2004
00:32:28,346 --> 00:32:30,521
The good news is that we

2005
00:32:30,521 --> 00:32:33,145
show that actually this
congestion pricing,

2006
00:32:33,145 --> 00:32:34,871
of course, for the
decision-maker,

2007
00:32:34,871 --> 00:32:37,555
they care a
lot about the revenue.

2008
00:32:37,555 --> 00:32:40,076
But our study shows that actually,

2009
00:32:40,076 --> 00:32:46,121
if you charge a toll of $20
for that cordon pricing,

2010
00:32:46,121 --> 00:32:49,301
you can reduce greenhouse
gas emissions as well as

2011
00:32:49,301 --> 00:32:53,620
PM2.5 emissions by about
15 percent.

2012
00:32:53,620 --> 00:32:57,281
So that is really a good
thing for the general public.

2013
00:32:57,281 --> 00:33:00,100
You're not only enjoying
reduced congestion,

2014
00:33:00,100 --> 00:33:03,565
but you also
enjoy reduced emissions.

2015
00:33:03,565 --> 00:33:08,935
Also, we applied our model
to look at another scenario.

2016
00:33:08,935 --> 00:33:12,030
What if we electrify
our transportation systems?

2017
00:33:12,030 --> 00:33:13,585
Of course, now post pandemic,

2018
00:33:13,585 --> 00:33:16,601
you look at the success
of Tesla, right?

2019
00:33:16,601 --> 00:33:19,870
And now I think
for many decision

2020
00:33:19,870 --> 00:33:22,931
agencies, including the
federal government,

2021
00:33:22,931 --> 00:33:24,656
we are talking so much about

2022
00:33:24,656 --> 00:33:27,220
transportation
electrification and what

2023
00:33:27,220 --> 00:33:28,930
would be the air quality and

2024
00:33:28,930 --> 00:33:31,660
health benefit of
such strategies?

2025
00:33:31,660 --> 00:33:33,956
So we conducted a study using

2026
00:33:33,956 --> 00:33:35,966
our integrated modelling system

2027
00:33:35,966 --> 00:33:38,801
and using Houston
as an example.

2028
00:33:38,801 --> 00:33:41,561
And our results
show that actually,

2029
00:33:41,561 --> 00:33:44,020
if you completely electrify

2030
00:33:44,020 --> 00:33:47,845
the transportation system
by 2040 for Houston,

2031
00:33:47,845 --> 00:33:50,081
each year, you'll
be able to save

2032
00:33:50,081 --> 00:33:54,266
about $2 billion of health cost.

2033
00:33:54,266 --> 00:33:58,600
So we also looked at the
freight transportation.

2034
00:33:58,600 --> 00:34:02,096
If you clean up the freight
sector because freight,

2035
00:34:02,096 --> 00:34:05,110
diesel trucks,
so that has

2036
00:34:05,110 --> 00:34:07,991
a lot of diesel PM
that can cause cancer.

2037
00:34:07,991 --> 00:34:09,956
So we look at a
different climate

2038
00:34:09,956 --> 00:34:12,685
and clean-up policies
for the freight sector

2039
00:34:12,685 --> 00:34:16,586
and we show again the air
quality and health benefit.

2040
00:34:16,586 --> 00:34:18,881
So essentially you
can see that

2041
00:34:18,881 --> 00:34:22,781
using an integrated
systems approach,

2042
00:34:22,781 --> 00:34:28,705
we can proactively quantify
the potential impact of

2043
00:34:28,705 --> 00:34:31,751
any of our infrastructure
from policy

2044
00:34:31,751 --> 00:34:34,900
to technology adoption,
to congestion pricing.

2045
00:34:34,900 --> 00:34:37,001
And we can find out

2046
00:34:37,001 --> 00:34:39,701
what that would imply
for the general public.

2047
00:34:39,701 --> 00:34:41,771
And then we can
inform the public,

2048
00:34:41,771 --> 00:34:43,315
we can inform the decision makers.

2049
00:34:43,315 --> 00:34:45,690
And also we can fit all these

2050
00:34:45,690 --> 00:34:48,825
back to optimize our
investment policies.

2051
00:34:48,825 --> 00:34:51,285
So we have done it for New
York City and for Houston,

2052
00:34:51,285 --> 00:34:54,300
we can certainly do it
for any other city.

2053
00:34:54,300 --> 00:34:59,710
So this is my second
to last topic.

2054
00:35:01,011 --> 00:35:04,215
I described
all those problems

2055
00:35:04,215 --> 00:35:06,931
and we had certain
policy solutions,

2056
00:35:06,931 --> 00:35:08,431
but we all know that

2057
00:35:08,431 --> 00:35:11,611
transportation is

2058
00:35:11,611 --> 00:35:15,586
a demand driven service
sector, that's nature.

2059
00:35:15,586 --> 00:35:19,306
So we have to think also about
demand, the behavior.

2060
00:35:19,306 --> 00:35:21,270
So how can we take advantage of

2061
00:35:21,270 --> 00:35:23,925
information technology
for behavior change?

2062
00:35:23,925 --> 00:35:26,840
I just want to give you a quick
example.

2063
00:35:26,840 --> 00:35:29,711
How can we use information
to change human behavior?

2064
00:35:29,711 --> 00:35:32,155
So for example,
imagine if you have

2065
00:35:32,155 --> 00:35:34,885
a Google Map in the GPS.

2066
00:35:34,885 --> 00:35:37,781
It's not only telling
you the shortest path

2067
00:35:37,781 --> 00:35:40,285
in terms of time.

2068
00:35:40,285 --> 00:35:42,656
What if we can also tell people

2069
00:35:42,656 --> 00:35:44,621
the emissions along
different paths

2070
00:35:44,621 --> 00:35:46,196
your vehicle will generate.

2071
00:35:46,196 --> 00:35:49,465
And more importantly,
what could be

2072
00:35:49,465 --> 00:35:55,360
your personal exposure to
particulate matter, pollution?

2073
00:35:55,360 --> 00:35:57,536
Imagine that on one route,

2074
00:35:57,536 --> 00:36:00,520
it's like you're exposed
to two cigarettes.

2075
00:36:00,520 --> 00:36:04,466
And second is about
equivalent to three cigarettes.

2076
00:36:04,466 --> 00:36:06,955
Would that possibly
change your behavior?

2077
00:36:06,955 --> 00:36:07,601
Right?

2078
00:36:07,601 --> 00:36:10,000
Of course,

2079
00:36:10,000 --> 00:36:11,231
for us to be able to tell

2080
00:36:11,231 --> 00:36:13,436
the exposure we need
to be able to model

2081
00:36:13,436 --> 00:36:18,191
and monitor the air pollutant
information ubiquitously.

2082
00:36:18,191 --> 00:36:22,015
So actually we find out that the
cellular service network,

2083
00:36:22,015 --> 00:36:24,641
the wireless transfer network,

2084
00:36:24,641 --> 00:36:26,995
those signals are
affected by weather and

2085
00:36:26,995 --> 00:36:29,410
weather in turn affects air
pollution.

2086
00:36:29,410 --> 00:36:31,601
We develop algorithms to

2087
00:36:31,601 --> 00:36:33,911
make inferences about
air quality using

2088
00:36:33,911 --> 00:36:35,876
this ubiquitously distributed

2089
00:36:35,876 --> 00:36:38,635
wireless communication network.

2090
00:36:38,635 --> 00:36:42,326
And then we
inform the travelers.

2091
00:36:42,326 --> 00:36:45,370
So this is a
picture where we

2092
00:36:45,370 --> 00:36:48,461
did a simulation for Fresno,
California network.

2093
00:36:48,461 --> 00:36:51,521
This is when people are
just using regular GPS,

2094
00:36:51,521 --> 00:36:53,425
no air quality information.

2095
00:36:53,425 --> 00:36:55,871
And you can see how
congested things are

2096
00:36:55,871 --> 00:36:58,466
because everyone is trying
to take the shortest paths.

2097
00:36:58,466 --> 00:36:59,800
Right? We all know that.

2098
00:36:59,800 --> 00:37:02,711
And now this one
nothing has  changed

2099
00:37:02,711 --> 00:37:04,990
but in addition to telling
them the shortest path,

2100
00:37:04,990 --> 00:37:08,440
we also tell them the air
pollution information.

2101
00:37:08,440 --> 00:37:10,466
And then of course,

2102
00:37:10,466 --> 00:37:12,775
all those behavior
parameters were based on

2103
00:37:12,775 --> 00:37:15,251
econometric studies,
willingness to pay,

2104
00:37:15,251 --> 00:37:18,971
how you are willing
to pay for reducing,

2105
00:37:18,971 --> 00:37:21,430
for example, 10 percent
of the air pollution.

2106
00:37:21,430 --> 00:37:24,671
All those behavior parameters
are used in the simulation.

2107
00:37:24,671 --> 00:37:25,960
So what difference did you see

2108
00:37:25,960 --> 00:37:30,140
from the previous slide?

2109
00:37:30,631 --> 00:37:34,135
The beauty you see here.

2110
00:37:34,135 --> 00:37:38,261
It's very intriguing because

2111
00:37:38,261 --> 00:37:41,081
for many cities when we are
dealing with congestion,

2112
00:37:41,081 --> 00:37:42,940
we're talking about
congestion pricing.

2113
00:37:42,940 --> 00:37:44,290
We're talking about

2114
00:37:44,290 --> 00:37:46,000
tolling people.

2115
00:37:46,000 --> 00:37:50,351
But we all know that congestion
pricing is regressive,

2116
00:37:50,351 --> 00:37:53,726
right, there are very
serious equity issues.

2117
00:37:53,726 --> 00:37:56,290
But now if you look
at this picture here,

2118
00:37:56,290 --> 00:37:58,151
what we did is that we just tell

2119
00:37:58,151 --> 00:38:01,870
people the air pollution
information and people adjust

2120
00:38:01,870 --> 00:38:05,890
their behavior voluntarily
and the outcome is

2121
00:38:05,890 --> 00:38:10,361
that it not only helps reduce
exposure of these travelers,

2122
00:38:10,361 --> 00:38:14,351
it also magically
reduces congestion.

2123
00:38:14,351 --> 00:38:19,061
So you don't have to toll
people to reduce congestion.

2124
00:38:19,061 --> 00:38:20,770
All we need to do is to tell

2125
00:38:20,770 --> 00:38:23,005
people the air
pollution information.

2126
00:38:23,005 --> 00:38:25,151
So this is just an
example showing

2127
00:38:25,151 --> 00:38:27,595
you how powerful
information could be.

2128
00:38:27,595 --> 00:38:29,531
My final points.

2129
00:38:29,531 --> 00:38:31,511
If you agree with me that

2130
00:38:31,511 --> 00:38:34,721
our infrastructure is so
important to our health,

2131
00:38:34,721 --> 00:38:38,815
and then we have to ask what
determines infrastructure?

2132
00:38:38,815 --> 00:38:42,521
That actually brings us to
a higher level question.

2133
00:38:42,521 --> 00:38:44,621
It's called
infrastructure finance

2134
00:38:44,621 --> 00:38:45,955
because we all know that,

2135
00:38:45,955 --> 00:38:48,446
who pays for infrastructure

2136
00:38:48,446 --> 00:38:50,861
has a better say about
how infrastructure

2137
00:38:50,861 --> 00:38:53,426
will be built. 
So far,

2138
00:38:53,426 --> 00:38:55,766
you know that for our
transportation infrastructure,

2139
00:38:55,766 --> 00:38:57,251
some of you,
you know that we

2140
00:38:57,251 --> 00:38:59,125
have the highway bill, right?

2141
00:38:59,125 --> 00:39:01,151
We have the highways
superfund,

2142
00:39:01,151 --> 00:39:04,975
which is based on the federal
gasoline tax.

2143
00:39:04,975 --> 00:39:08,021
For the states or for
the municipality,

2144
00:39:08,021 --> 00:39:09,985
they want to build
new roads or something,

2145
00:39:09,985 --> 00:39:13,540
they apply for funding
from the federal highway superfund.

2146
00:39:13,540 --> 00:39:15,550
But now you see we are trying

2147
00:39:15,550 --> 00:39:17,500
to promote cleaner vehicles.

2148
00:39:17,500 --> 00:39:20,171
We want to vehicles
to burn less gasoline

2149
00:39:20,171 --> 00:39:24,161
that means that the gasoline
tax will go down.

2150
00:39:24,161 --> 00:39:25,496
But on the other hand,

2151
00:39:25,496 --> 00:39:28,525
we all know that the US
infrastructure,

2152
00:39:28,525 --> 00:39:32,636
as the ASCE has evaluated it
is at a level D. Very bad.

2153
00:39:32,636 --> 00:39:36,131
On one hand, we are having
a reduction in revenue.

2154
00:39:36,131 --> 00:39:37,480
On the other hand,
we need a lot of

2155
00:39:37,480 --> 00:39:40,076
money to fix our roads.

2156
00:39:40,076 --> 00:39:42,806
So where do we get the money?

2157
00:39:42,806 --> 00:39:45,955
So that's why now a lot of
people are talking about

2158
00:39:45,955 --> 00:39:50,410
public private
partnership, PPP, right?

2159
00:39:50,410 --> 00:39:53,080
So basically the idea
is that, you know,

2160
00:39:53,080 --> 00:39:55,330
introducing the private
sector to come into

2161
00:39:55,330 --> 00:39:57,760
the investment of our
future infrastructure.

2162
00:39:57,760 --> 00:40:00,550
Of course, when the
private sector comes in.

2163
00:40:00,550 --> 00:40:02,725
They don't come in,

2164
00:40:02,725 --> 00:40:06,115
just invest for the good
of the general public.

2165
00:40:06,115 --> 00:40:07,556
They want profit.

2166
00:40:07,556 --> 00:40:10,045
So anyway, this is essentially

2167
00:40:10,045 --> 00:40:11,546
going to be a game.

2168
00:40:11,546 --> 00:40:14,036
It's going to be a game
between the government,

2169
00:40:14,036 --> 00:40:19,180
the private parties, and the
general public - us.

2170
00:40:19,180 --> 00:40:23,815
And also this game is
different from the game

2171
00:40:23,815 --> 00:40:26,230
you play overnight
in Las Vegas.

2172
00:40:26,230 --> 00:40:27,970
In Las Vegas if you lose
$200 overnight,

2173
00:40:27,970 --> 00:40:31,405
you come back
home, your life goes on.

2174
00:40:31,405 --> 00:40:33,986
But these infrastructure games

2175
00:40:33,986 --> 00:40:36,445
are decades long.

2176
00:40:36,445 --> 00:40:39,206
And through the process, 
the contracting processes.

2177
00:40:39,206 --> 00:40:40,690
There are different stages.

2178
00:40:40,690 --> 00:40:43,391
So, while so many people,

2179
00:40:43,391 --> 00:40:47,575
including many 
politicians in Washington DC,

2180
00:40:47,575 --> 00:40:51,926
talk a lot about PPP,
public-private partnership.

2181
00:40:51,926 --> 00:40:55,015
But not many people
really understand

2182
00:40:55,015 --> 00:40:59,710
the intricacy of this PPP game.

2183
00:40:59,710 --> 00:41:02,245
Because how is this game

2184
00:41:02,245 --> 00:41:04,705
going to have equilibrium?

2185
00:41:04,705 --> 00:41:07,855
How are you going to be able to
maximize the social welfare

2186
00:41:07,855 --> 00:41:11,785
while satisfying the Bayesian
incentive compatibility

2187
00:41:11,785 --> 00:41:15,701
and also thinking about the
interim individual rationality.

2188
00:41:15,701 --> 00:41:18,415
So this is another study
that my group looked at.

2189
00:41:18,415 --> 00:41:20,411
But you can just go
back very quickly.

2190
00:41:20,411 --> 00:41:23,125
In this one, look at
the bottom right.

2191
00:41:23,125 --> 00:41:26,711
We wanted to incorporate
the emissions

2192
00:41:26,711 --> 00:41:28,871
directly into

2193
00:41:28,871 --> 00:41:32,831
the mechanism design of
infrastructure finance,

2194
00:41:32,831 --> 00:41:35,681
such that emissions are early on

2195
00:41:35,681 --> 00:41:37,421
already in the equation

2196
00:41:37,421 --> 00:41:39,355
because if it's not
in the equation,

2197
00:41:39,355 --> 00:41:41,455
they are not going to
be considered, right?

2198
00:41:41,455 --> 00:41:44,350
So this is basically another
thing we're trying to do.

2199
00:41:44,350 --> 00:41:48,326
So you can see that all of us,

2200
00:41:48,326 --> 00:41:50,741
we are facing a megaton problem

2201
00:41:50,741 --> 00:41:52,931
which requires a megaton solution.

2202
00:41:52,931 --> 00:41:57,430
That requires a multidisciplinary
system approach.

2203
00:41:57,430 --> 00:41:59,440
It's not just civil engineers,

2204
00:41:59,440 --> 00:42:02,800
mechanical engineers, environmental scientists
or health researchers.

2205
00:42:02,800 --> 00:42:05,890
We need all of us
working together from

2206
00:42:05,890 --> 00:42:09,836
engineering and natural science to
social science and technology, right?

2207
00:42:09,836 --> 00:42:12,130
So also in practice,

2208
00:42:12,130 --> 00:42:15,011
we need multi-sector,

2209
00:42:15,011 --> 00:42:18,760
trans-sector collaboration
in planning, designing,

2210
00:42:18,760 --> 00:42:23,966
and managing our future
infrastructure systems.

2211
00:42:23,966 --> 00:42:27,461
Look, this is the community.

2212
00:42:27,461 --> 00:42:28,991
This is a community,

2213
00:42:28,991 --> 00:42:31,850
this is the city
we're living in today.

2214
00:42:32,191 --> 00:42:36,506
Look at this child.

2215
00:42:36,506 --> 00:42:39,190
Look at what is surrounding her.

2216
00:42:39,190 --> 00:42:40,721
That could be your child,

2217
00:42:40,721 --> 00:42:42,666
it could be my child.

2218
00:42:42,666 --> 00:42:45,750
And she could be
hit by a car while

2219
00:42:45,750 --> 00:42:48,420
she's breathing all
this polluted air.

2220
00:42:48,420 --> 00:42:51,450
We certainly don't want
our future generations

2221
00:42:51,450 --> 00:42:54,631
to live in such a
miserable environment.

2222
00:42:54,631 --> 00:42:57,181
We want to build the
cities of tomorrow.

2223
00:42:57,181 --> 00:43:00,555
We want our cities of tomorrow
not only to be smart,

2224
00:43:00,555 --> 00:43:02,926
but also to be healthy.

2225
00:43:02,926 --> 00:43:06,120
That's why I feel that it
really calls for all of us

2226
00:43:06,120 --> 00:43:09,541
to work together
and first of all,

2227
00:43:09,541 --> 00:43:13,830
change our view,
change our paradigm

2228
00:43:13,830 --> 00:43:16,531
and take a system
integration and

2229
00:43:16,531 --> 00:43:18,106
innovation approach

2230
00:43:18,106 --> 00:43:20,910
towards the future
of our communities.

2231
00:43:20,910 --> 00:43:24,195
I believe this is my last
slide. I will stop here.

2232
00:43:24,195 --> 00:43:25,840
Thank you.

2233
00:43:26,671 --> 00:43:29,860
Great presentation.
Very visionary.

2234
00:43:29,860 --> 00:43:31,660
Thank you so much Oliver.

2235
00:43:31,660 --> 00:43:34,301
And I didn't mention that

2236
00:43:34,301 --> 00:43:36,356
our seminar is actually hybrid

2237
00:43:36,356 --> 00:43:38,381
which means that we
have the online session

2238
00:43:38,381 --> 00:43:41,800
and we also have USF
students actually

2239
00:43:41,800 --> 00:43:46,480
in the classroom also listening
to Oliver's presentation.

2240
00:43:46,480 --> 00:43:49,420
So now we open the
floor to questions.

2241
00:43:49,420 --> 00:43:52,735
Please feel free to
unmute yourself,

2242
00:43:52,735 --> 00:43:58,940
or you can put your questions
in the Q&A of Zoom.

2243
00:43:59,011 --> 00:44:01,451
And Oliver, 
when you asked

2244
00:44:01,451 --> 00:44:03,806
the questions at the
beginning about what is important,

2245
00:44:03,806 --> 00:44:05,650
we actually had a
lot of answers in

2246
00:44:05,650 --> 00:44:08,036
the meeting chat as
well as in the Q&A.

2247
00:44:08,036 --> 00:44:10,946
And I think many of them
got the answers right.

2248
00:44:10,946 --> 00:44:11,560
That's right.

2249
00:44:11,560 --> 00:44:13,945
I saw Amy's answer - 
your health.

2250
00:44:13,945 --> 00:44:17,751
That's wonderful.

2251
00:44:21,271 --> 00:44:25,220
Okay. Questions
from our audience?

2252
00:44:25,561 --> 00:44:27,820
I know it's
a lot of information.

2253
00:44:27,820 --> 00:44:29,710
It's very, very
comprehensive,

2254
00:44:29,710 --> 00:44:33,025
lot of information in many
different areas. Saeid?

2255
00:44:33,025 --> 00:44:34,165
Yes.

2256
00:44:34,165 --> 00:44:36,700
It was a really
interesting presentation.

2257
00:44:36,700 --> 00:44:37,750
Thank you, Dr. Gao

2258
00:44:37,750 --> 00:44:40,480
for that. It made me think
about so many things.

2259
00:44:40,480 --> 00:44:43,481
You gave us an example
that when you were a kid,

2260
00:44:43,481 --> 00:44:45,791
you used to ride
a bike to school.

2261
00:44:45,791 --> 00:44:48,161
Nowadays with
advanced technology,

2262
00:44:48,161 --> 00:44:51,956
I think all the kids are using
public transportation and buses.

2263
00:44:51,956 --> 00:44:53,590
Aside from

2264
00:44:53,590 --> 00:44:57,821
all those physical health
problems that

2265
00:44:57,821 --> 00:44:59,936
the new technology might cause,

2266
00:44:59,936 --> 00:45:03,356
I'm thinking about the
mental problem.

2267
00:45:03,356 --> 00:45:06,070
Do you think
that people that lived

2268
00:45:06,070 --> 00:45:07,675
at the time

2269
00:45:07,675 --> 00:45:10,435
when technology was not
as advanced as now,

2270
00:45:10,435 --> 00:45:12,405
lived  happier than we are?

2271
00:45:12,405 --> 00:45:14,816
As you said, we are making
everything efficient.

2272
00:45:14,816 --> 00:45:17,231
More efficient. We are
trying to decrease the cost,

2273
00:45:17,231 --> 00:45:19,871
but are we making
people happier?

2274
00:45:19,871 --> 00:45:22,091
And if not, how should we change

2275
00:45:22,091 --> 00:45:27,351
our perspective to
make that happen?

2276
00:45:27,351 --> 00:45:34,140
That's a beautiful question.

2277
00:45:34,140 --> 00:45:38,416
You can see that
I turned back to this slide.

2278
00:45:38,416 --> 00:45:40,080
I mentioned earlier, right?

2279
00:45:40,080 --> 00:45:43,816
I think our cities are
like concrete jungles.

2280
00:45:43,816 --> 00:45:47,296
And I mentioned that in
concrete we use cement.

2281
00:45:47,296 --> 00:45:50,671
And you know that
cement is produced by

2282
00:45:50,671 --> 00:45:53,896
processing the
rocks from caves

2283
00:45:53,896 --> 00:45:56,040
in the mountains.

2284
00:45:56,040 --> 00:45:58,530
And Saeid, your question
reminded me of course,

2285
00:45:58,530 --> 00:45:59,805
if you think about

2286
00:45:59,805 --> 00:46:03,735
our ancestors, 
where did they live?

2287
00:46:03,735 --> 00:46:05,985
They lived in caves.

2288
00:46:05,985 --> 00:46:08,295
And in the daytime they went out

2289
00:46:08,295 --> 00:46:10,776
to pickup fruits or vegetables.

2290
00:46:10,776 --> 00:46:13,346
Then at night  they
came back to the cave.

2291
00:46:14,516 --> 00:46:19,510
So to expand your question,

2292
00:46:19,510 --> 00:46:22,001
are people nowadays
living in New York City,

2293
00:46:22,001 --> 00:46:25,270
are they happier than our
ancestors living in the cave,

2294
00:46:25,270 --> 00:46:29,096
picking up apples and
pears and eating?

2295
00:46:29,096 --> 00:46:30,865
So which lifestyle is better?

2296
00:46:30,865 --> 00:46:32,381
Exactly, that's my question.

2297
00:46:32,381 --> 00:46:36,640
Technology always makes
worry about that,

2298
00:46:36,640 --> 00:46:38,291
that we are making
everything efficient

2299
00:46:38,291 --> 00:46:39,880
but we're creating a lot of

2300
00:46:39,880 --> 00:46:42,341
mental health
problems for people.

2301
00:46:42,341 --> 00:46:43,570
That's right.

2302
00:46:43,570 --> 00:46:45,460
So that's why

2303
00:46:45,460 --> 00:46:48,431
I'm calling for a
paradigm shift from

2304
00:46:48,431 --> 00:46:52,910
individual level to 
a collective level.

2305
00:46:52,910 --> 00:46:55,651
Right? What is the purpose?

2306
00:46:55,651 --> 00:46:59,370
So for systems engineering,

2307
00:46:59,370 --> 00:47:02,206
whenever you start something,

2308
00:47:02,206 --> 00:47:04,726
system engineering prompts people to ask the questions,

2309
00:47:04,726 --> 00:47:07,320
"What is our goal?"
"What is my objective?"

2310
00:47:07,320 --> 00:47:10,620
But somehow, you can see that in

2311
00:47:10,620 --> 00:47:13,770
our daily life, politicians,

2312
00:47:13,770 --> 00:47:16,155
our students,

2313
00:47:16,155 --> 00:47:19,576
we are kept so busy 
to be efficient,

2314
00:47:19,576 --> 00:47:21,240
such that we seldom

2315
00:47:21,240 --> 00:47:25,755
pause and think
about the purpose.

2316
00:47:25,755 --> 00:47:28,215
And the "why". 
That's why Saeid,

2317
00:47:28,215 --> 00:47:30,540
I was just joking when
I first asked you what is

2318
00:47:30,540 --> 00:47:33,226
your most important/valuable asset,

2319
00:47:33,226 --> 00:47:35,761
you did not know.

2320
00:47:35,761 --> 00:47:40,005
Yeah. Yeah. Great.

2321
00:47:40,005 --> 00:47:44,070
We have questions from
the meeting chat and also Q&A so

2322
00:47:44,070 --> 00:47:46,051
one question from 
the meeting chat is

2323
00:47:46,051 --> 00:47:48,481
from Jennifer Brown and she asked,

2324
00:47:48,481 --> 00:47:50,791
"Could you please
expand on how to tell

2325
00:47:50,791 --> 00:47:53,521
people about emissions to
effect the change it needs?"

2326
00:47:53,521 --> 00:47:56,310
So basically how to
improve the awareness

2327
00:47:56,310 --> 00:48:00,461
of the environmental impacts
from transportation?

2328
00:48:00,741 --> 00:48:03,076
That's a very good question.

2329
00:48:03,076 --> 00:48:05,161
So maybe let's see

2330
00:48:05,161 --> 00:48:11,056
this slide.

2331
00:48:15,046 --> 00:48:17,484
So it's really emissions.

2332
00:48:19,921 --> 00:48:22,230
You can see that when you
look at the statistics,

2333
00:48:22,230 --> 00:48:24,480
wow, more people are killed by

2334
00:48:24,480 --> 00:48:26,896
vehicle emissions.
But in our daily lives,

2335
00:48:26,896 --> 00:48:28,170
if you think about,

2336
00:48:28,170 --> 00:48:29,730
when you think
of a car accident,

2337
00:48:29,730 --> 00:48:31,711
you think about that
bloody thing and

2338
00:48:31,711 --> 00:48:35,130
the person being injured
or killed in that.

2339
00:48:35,130 --> 00:48:37,680
That would make
an impact on you

2340
00:48:37,680 --> 00:48:40,906
and you will either tell
yourself or tell your children

2341
00:48:40,906 --> 00:48:43,426
that traffic safety is the most
important, definitely.

2342
00:48:43,426 --> 00:48:46,170
However, emissions
are killing people.

2343
00:48:46,170 --> 00:48:49,050
Can you imagine a
picture in your mind?

2344
00:48:49,050 --> 00:48:51,105
It's very hard. You
cannot even imagine

2345
00:48:51,105 --> 00:48:55,425
how emissions kill people.

2346
00:48:55,425 --> 00:48:58,635
But now, Jennifer, let   
me try to give you a

2347
00:48:58,635 --> 00:49:00,570
another scenario or
picture that will

2348
00:49:00,570 --> 00:49:03,416
get you to probably
realize the importance.

2349
00:49:03,416 --> 00:49:06,881
We all know this story.

2350
00:49:06,881 --> 00:49:13,946
Right? If you put a frog in
gradually warmed up water,

2351
00:49:13,946 --> 00:49:15,940
like in a bottle of
water and you put

2352
00:49:15,940 --> 00:49:20,531
a frog in the water and you 
just heat that water gradually

2353
00:49:20,531 --> 00:49:23,245
in the winter time,

2354
00:49:23,245 --> 00:49:25,075
for example.

2355
00:49:25,075 --> 00:49:28,061
What would
the frog feel

2356
00:49:28,061 --> 00:49:30,671
in the very beginning?
Very comfortable.

2357
00:49:30,671 --> 00:49:33,175
"Wow, the water is becoming
very comfortable."

2358
00:49:33,175 --> 00:49:36,806
But then gradually

2359
00:49:36,806 --> 00:49:39,536
it gets so used to
this warm water.

2360
00:49:40,421 --> 00:49:42,640
And at a certain point,

2361
00:49:42,640 --> 00:49:45,820
it realizes that 
"Oh, the water is too hot."

2362
00:49:45,820 --> 00:49:47,651
But what does that mean?

2363
00:49:47,651 --> 00:49:50,665
It's already too late.

2364
00:49:50,665 --> 00:49:52,600
So I want to use

2365
00:49:52,600 --> 00:49:55,720
that analogy to tell you that
vehicle emissions kill people

2366
00:49:55,720 --> 00:50:00,956
like you kill a frog in
the gradually warmed up water.

2367
00:50:00,956 --> 00:50:04,241
So if you can, I hope if you
tell this story to people,

2368
00:50:04,241 --> 00:50:06,011
they will see that.

2369
00:50:06,011 --> 00:50:08,140
But I think you did bring up

2370
00:50:08,140 --> 00:50:10,946
a very important aspect
for our researchers.

2371
00:50:10,946 --> 00:50:12,971
It's really, you know,

2372
00:50:12,971 --> 00:50:14,831
we have all these
scientific knowledge.

2373
00:50:14,831 --> 00:50:17,080
We have all these discoveries.

2374
00:50:17,080 --> 00:50:18,910
But communication. 
How can we

2375
00:50:18,910 --> 00:50:22,601
communicate all these
things effectively

2376
00:50:22,601 --> 00:50:24,175
to the general public, right?

2377
00:50:24,175 --> 00:50:25,946
That is so important.

2378
00:50:25,946 --> 00:50:28,271
That's why, actually, Cornell,

2379
00:50:28,271 --> 00:50:33,746
in collaboration with USF, 
some professors at USF,

2380
00:50:33,746 --> 00:50:36,671
are having this community buddy program [Healthy Buddy Program https://www.hbuddy.org/]

2381
00:50:36,671 --> 00:50:38,290
to help with seniors.

2382
00:50:38,290 --> 00:50:39,460
So what I'm trying to say

2383
00:50:39,460 --> 00:50:46,736
is that engineering is not
simply just math or equations.

2384
00:50:46,736 --> 00:50:50,606
Now if you look at
today's talk, look beyond it.

2385
00:50:50,606 --> 00:50:53,830
Engineering is actually 
everything from

2386
00:50:53,830 --> 00:50:57,581
communication all the way
to mathematic model making.

2387
00:50:57,581 --> 00:51:00,416
Thank you, Jennifer, for
that great question.

2388
00:51:00,416 --> 00:51:05,726
Thanks Oliver and another
question from Shanjun Li says,

2389
00:51:05,726 --> 00:51:07,166
"Could you please
talk a little bit

2390
00:51:07,166 --> 00:51:09,566
more about this
study on depression?

2391
00:51:09,566 --> 00:51:11,291
For example, the data and the

2392
00:51:11,291 --> 00:51:14,380
method used and the
policy implications.

2393
00:51:14,380 --> 00:51:17,081
If green space or proximity to

2394
00:51:17,081 --> 00:51:20,140
public transit
helps mental health,

2395
00:51:20,140 --> 00:51:23,666
could you put a dollar
value on that benefit?"

2396
00:51:23,666 --> 00:51:25,931
And I think you did mention

2397
00:51:25,931 --> 00:51:28,600
how much it can
save the health

2398
00:51:28,600 --> 00:51:35,800
costs if the emissions are
considered in equations.

2399
00:51:35,800 --> 00:51:38,140
So can you elaborate on that?

2400
00:51:38,140 --> 00:51:40,931
Yes, sure,

2401
00:51:40,931 --> 00:51:43,691
one clarification and then the
answer to Shanjun's question.

2402
00:51:43,691 --> 00:51:49,645
So I did mention 
that the health savings

2403
00:51:49,645 --> 00:51:52,450
but that was a
case study looking

2404
00:51:52,450 --> 00:51:56,155
at what if we electrify
transportation in Houston?

2405
00:51:56,155 --> 00:51:59,021
And we used
BenMAP, exposure,

2406
00:51:59,021 --> 00:52:03,620
health risk, and also translated
into statistic value.

2407
00:52:04,891 --> 00:52:07,480
Yeah, so that was
basically about,

2408
00:52:07,480 --> 00:52:09,311
that was for
electrification.

2409
00:52:09,311 --> 00:52:11,380
But this one, Shanjun,

2410
00:52:11,380 --> 00:52:14,920
this was an empirical study

2411
00:52:14,920 --> 00:52:17,681
looking at the data.

2412
00:52:17,681 --> 00:52:18,881
Actually, this is your area.

2413
00:52:18,881 --> 00:52:22,726
It was statistic modeling
after controlling the

2414
00:52:22,726 --> 00:52:24,910
individuals' variables.

2415
00:52:24,910 --> 00:52:26,711
We controlled those.

2416
00:52:27,955 --> 00:52:29,980
It was more of a hypothesis
test and we wanted

2417
00:52:29,980 --> 00:52:32,035
to find out whether or

2418
00:52:32,035 --> 00:52:35,800
what built environment factors

2419
00:52:35,800 --> 00:52:38,156
are associated
with the incidence

2420
00:52:38,156 --> 00:52:40,120
of this postpartum depression?

2421
00:52:40,120 --> 00:52:42,820
And we have found out that
you can see, even distance to

2422
00:52:42,820 --> 00:52:46,751
the bike path, or distance to the green space,

2423
00:52:46,751 --> 00:52:50,470
accessibility to the green space,
they all play a role.

2424
00:52:50,470 --> 00:52:51,790
Towards the end of our paper,

2425
00:52:51,790 --> 00:52:53,755
we did make some
recommendations.

2426
00:52:53,755 --> 00:52:55,795
For example, of
course, in the green space,

2427
00:52:55,795 --> 00:52:59,935
which is always a very
important thing.

2428
00:52:59,935 --> 00:53:03,610
But we did not do

2429
00:53:03,610 --> 00:53:06,760
any quantification because at

2430
00:53:06,760 --> 00:53:08,530
this point, we're
not able to yet.

2431
00:53:08,530 --> 00:53:10,661
So for example, if you invest

2432
00:53:10,661 --> 00:53:14,291
this much money in building
some more green space,

2433
00:53:14,291 --> 00:53:16,660
then what would be

2434
00:53:16,660 --> 00:53:19,181
the coefficient corresponding to

2435
00:53:19,181 --> 00:53:21,821
the improvement 
in mental health?

2436
00:53:21,821 --> 00:53:24,640
That part is really very tricky.

2437
00:53:24,640 --> 00:53:26,741
And of course, this
was a collaboration

2438
00:53:26,741 --> 00:53:30,701
between engineering and also
Cornell Weill Medical.

2439
00:53:30,701 --> 00:53:32,140
So we were working
with them because

2440
00:53:32,140 --> 00:53:33,370
they had the health data.

2441
00:53:33,370 --> 00:53:34,991
But I think probably
in the future,

2442
00:53:34,991 --> 00:53:37,826
if we can also work with
economists like you,

2443
00:53:37,826 --> 00:53:39,760
we can probably add

2444
00:53:39,760 --> 00:53:41,320
some more dimensions in terms

2445
00:53:41,320 --> 00:53:44,271
of cost effectiveness
assessment.

2446
00:53:44,521 --> 00:53:47,111
Thanks Professor Li for the question,

2447
00:53:47,111 --> 00:53:49,165
and thanks Oliver for the answer.

2448
00:53:49,165 --> 00:53:51,341
Do we have more questions?

2449
00:53:51,341 --> 00:53:53,171
Do we have questions
from the students

2450
00:53:53,171 --> 00:53:56,510
in the classroom, Christina?

2451
00:54:01,855 --> 00:54:03,325
Yes.

2452
00:54:03,325 --> 00:54:04,751
I saw one attendee,

2453
00:54:04,751 --> 00:54:07,241
so maybe we should
go there. Christina,

2454
00:54:07,241 --> 00:54:08,890
please let me know
if we have questions

2455
00:54:08,890 --> 00:54:12,416
from the classroom.

2456
00:54:12,416 --> 00:54:16,331
We have no questions [from the 
classroom] right now,

2457
00:54:16,331 --> 00:54:19,841
we increased our attendance
in classroom a little bit

2458
00:54:19,841 --> 00:54:21,800
so they're still 
thinking about it.

2459
00:54:22,381 --> 00:54:25,196
I saw that Sean has a question

2460
00:54:25,196 --> 00:54:27,625
about using vehicles
as probe sensors.

2461
00:54:27,625 --> 00:54:30,580
Absolutely.

2462
00:54:30,580 --> 00:54:32,305
Because the thing is 
that nowadays,

2463
00:54:32,305 --> 00:54:36,205
the cost of sensors is
coming down significantly.

2464
00:54:36,205 --> 00:54:39,715
So think about Tesla.

2465
00:54:39,715 --> 00:54:43,181
Tesla is essentially
a moving sensor,

2466
00:54:43,181 --> 00:54:45,731
a moving set of sensors, right?

2467
00:54:45,731 --> 00:54:48,401
I think it's kind of if
we can take advantage of

2468
00:54:48,401 --> 00:54:52,061
the vehicle technologies to
monitor this air quality.

2469
00:54:52,061 --> 00:54:54,236
But you can see that
monitoring air quality

2470
00:54:54,236 --> 00:54:56,365
is not the 
ultimate goal.

2471
00:54:56,365 --> 00:54:59,591
It's really through the monitoring
of this information and

2472
00:54:59,591 --> 00:55:01,600
distributing that information to

2473
00:55:01,600 --> 00:55:03,865
the travelers to
change their behavior,

2474
00:55:03,865 --> 00:55:05,785
that if we can
make that happen,

2475
00:55:05,785 --> 00:55:07,821
I think that will be great.

2476
00:55:09,751 --> 00:55:14,261
And in the meeting
chat also,

2477
00:55:14,261 --> 00:55:15,311
someone asked

2478
00:55:15,311 --> 00:55:16,691
if a link to the recorded

2479
00:55:16,691 --> 00:55:18,670
session could be sent to the
attendees by email.

2480
00:55:18,670 --> 00:55:24,910
So this is a joint event
between USF and CTECH.

2481
00:55:24,910 --> 00:55:26,291
Actually, we will work on

2482
00:55:26,291 --> 00:55:29,651
this recorded presentation and

2483
00:55:29,651 --> 00:55:33,041
put the captions on it. 
In about two weeks we

2484
00:55:33,041 --> 00:55:36,926
will post it on the CTECH 
website [https://ctech.cee.cornell.edu/].

2485
00:55:36,926 --> 00:55:38,740
So I will put the
website here

2486
00:55:38,740 --> 00:55:41,381
and then maybe after
two weeks you can

2487
00:55:41,381 --> 00:55:46,255
go directly to the website and
you can see the recorded seminar

2488
00:55:46,255 --> 00:55:48,071
https://ctech.cee.cornell.edu/events-2/impacts-of-transportation-and-urban-systems-on-health-and-the-environment-webinar-series/

2489
00:55:48,071 --> 00:55:52,181
So another question, coming
from Gina Park, says,

2490
00:55:52,181 --> 00:55:55,255
"How can we factor in
a structural problem?

2491
00:55:55,255 --> 00:55:57,641
For example, lower-income
households in

2492
00:55:57,641 --> 00:55:59,875
the less clean 
environments in the

2493
00:55:59,875 --> 00:56:02,006
integrative model
of transportation,

2494
00:56:02,006 --> 00:56:04,481
health and infrastructure."

2495
00:56:04,481 --> 00:56:11,321
Wonderful question, Gina.

2496
00:56:11,321 --> 00:56:14,921
We are currently finishing
up two papers

2497
00:56:14,921 --> 00:56:17,770
related to environmental
justice and equity.

2498
00:56:17,770 --> 00:56:19,511
Essentially,
you are bringing up

2499
00:56:19,511 --> 00:56:20,861
this very important dimension

2500
00:56:20,861 --> 00:56:22,511
of the environmental injustice,

2501
00:56:22,511 --> 00:56:25,406
lower income people or

2502
00:56:25,406 --> 00:56:29,050
certain ethnic groups or

2503
00:56:29,050 --> 00:56:32,636
racial groups that live
closer to the road.

2504
00:56:32,636 --> 00:56:35,020
So currently,

2505
00:56:35,020 --> 00:56:37,166
we have two ongoing studies.

2506
00:56:37,166 --> 00:56:41,650
One study is that we are
looking at the quantification

2507
00:56:41,650 --> 00:56:43,075
of the disparity in

2508
00:56:43,075 --> 00:56:46,361
exposure to these transportation
related emissions.

2509
00:56:46,361 --> 00:56:49,061
The second one
is even more interesting.

2510
00:56:49,061 --> 00:56:51,820
We are looking at,

2511
00:56:51,820 --> 00:56:56,290
if we electrify the
transportation system,

2512
00:56:56,290 --> 00:57:00,041
how would that impact
this disparity?

2513
00:57:00,041 --> 00:57:01,810
We have an existing hypothesis.

2514
00:57:01,810 --> 00:57:04,646
My hypothesis is that,

2515
00:57:04,646 --> 00:57:07,930
adopting cleaner
vehicle technology will

2516
00:57:07,930 --> 00:57:11,441
help reduce the disparity.

2517
00:57:11,441 --> 00:57:13,481
Here is the rationale.

2518
00:57:13,481 --> 00:57:16,661
Because so far a lot of
people, when they talk about,

2519
00:57:16,661 --> 00:57:18,415
when they think about

2520
00:57:18,415 --> 00:57:21,235
equity issue in adopting
electric vehicles,

2521
00:57:21,235 --> 00:57:23,126
they are mostly
looking at okay,

2522
00:57:23,126 --> 00:57:26,260
rich people tend to
be more able to

2523
00:57:26,260 --> 00:57:30,296
afford or adopt a
cleaner vehicle.

2524
00:57:30,296 --> 00:57:32,650
But think about New York
City as an example.

2525
00:57:32,650 --> 00:57:35,665
Many rich people, they
live on Long Island.

2526
00:57:35,665 --> 00:57:39,491
They commute every day from
Long Island to Manhattan.

2527
00:57:39,491 --> 00:57:42,895
And if they're driving
a conventional car,

2528
00:57:42,895 --> 00:57:45,895
they are going to emit
along the way in Queens,

2529
00:57:45,895 --> 00:57:49,661
where relatively poor people

2530
00:57:49,661 --> 00:57:51,011
are living in the Queens area.

2531
00:57:51,011 --> 00:57:54,730
Now imagine that if those rich people,

2532
00:57:54,730 --> 00:57:56,966
they adopt electric vehicles,

2533
00:57:56,966 --> 00:57:59,560
they buy electric vehicles.

2534
00:57:59,560 --> 00:58:01,375
And then when they
drive actually,

2535
00:58:01,375 --> 00:58:04,751
that's why I'm
hypothesizing that

2536
00:58:04,751 --> 00:58:11,590
electrification could be one of the 
really good technological solutions,

2537
00:58:11,590 --> 00:58:14,411
not only reducing the
overall emissions,

2538
00:58:14,411 --> 00:58:17,231
but could mitigate
the disparity.

2539
00:58:17,231 --> 00:58:18,326
This is our hypotheses.

2540
00:58:18,326 --> 00:58:22,271
We're doing modelling
to verify this.

2541
00:58:22,271 --> 00:58:25,961
And another thing we're looking
at is also like the rural

2542
00:58:25,961 --> 00:58:30,535
versus urban differences in
terms of this disparity.

2543
00:58:30,535 --> 00:58:32,590
Because we recently
finished a paper looking

2544
00:58:32,590 --> 00:58:34,630
at the future three revolutions,

2545
00:58:34,630 --> 00:58:37,331
how they impact air
quality and health.

2546
00:58:37,331 --> 00:58:38,980
We have already done
that, and now we

2547
00:58:38,980 --> 00:58:40,750
are looking further to

2548
00:58:40,750 --> 00:58:43,825
study the equity implications

2549
00:58:43,825 --> 00:58:46,046
of the future three revolutions,

2550
00:58:46,046 --> 00:58:52,370
which are shared use of
electrified autonomous vehicles.

2551
00:58:52,801 --> 00:58:56,650
Thanks Oliver. So you talked
about electrification in

2552
00:58:56,650 --> 00:59:00,640
transportation. There is one question
from the audience.

2553
00:59:00,640 --> 00:59:02,591
And the question is,

2554
00:59:02,591 --> 00:59:04,870
"Electrification
transportation is crucial

2555
00:59:04,870 --> 00:59:07,015
for global
climate stability

2556
00:59:07,015 --> 00:59:09,040
but the electrification
transition is very

2557
00:59:09,040 --> 00:59:11,575
slow due to to a
number of factors.

2558
00:59:11,575 --> 00:59:13,151
So how do you entertain

2559
00:59:13,151 --> 00:59:16,285
this disparity between
the demand for

2560
00:59:16,285 --> 00:59:18,730
electrification and
the lack of technology

2561
00:59:18,730 --> 00:59:22,221
and money for
developing countries?"

2562
00:59:22,861 --> 00:59:28,821
I think first of all,
it's interesting, right?

2563
00:59:29,461 --> 00:59:33,160
I would like to answer your
question from two aspects.

2564
00:59:33,160 --> 00:59:35,201
The first aspect, again,

2565
00:59:35,201 --> 00:59:37,676
looking at what is
happening in Washington DC.

2566
00:59:37,676 --> 00:59:40,870
The Biden administration
is trying hard,

2567
00:59:40,870 --> 00:59:44,936
it's trying hard to get
that $3.5 trillion bill.

2568
00:59:44,936 --> 00:59:47,230
In that, and I know Shanjun is also aware,

2569
00:59:47,230 --> 00:59:49,481
that there is going to be

2570
00:59:49,481 --> 00:59:50,920
a huge amount of

2571
00:59:50,920 --> 00:59:55,165
money targeting transportation
electrification.

2572
00:59:55,165 --> 00:59:57,221
Because of course
in this country,

2573
00:59:57,221 --> 01:00:00,221
if human
behavior changes,

2574
01:00:00,221 --> 01:00:01,556
there is momentum, right?

2575
01:00:01,556 --> 01:00:02,890
It's a habit.

2576
01:00:02,890 --> 01:00:04,331
It's probably very hard for people,

2577
01:00:04,331 --> 01:00:06,431
for you to change human
behavior all of a sudden.

2578
01:00:06,431 --> 01:00:08,245
Many people are
going to switch to

2579
01:00:08,245 --> 01:00:11,860
electric vehicles. It
is a gradual process.

2580
01:00:11,860 --> 01:00:14,966
But what I can see is that
at least in this country,

2581
01:00:14,966 --> 01:00:18,116
that process is now much more

2582
01:00:18,116 --> 01:00:22,421
promising from the
national policy level

2583
01:00:22,421 --> 01:00:24,955
to the technology level, right?

2584
01:00:24,955 --> 01:00:26,290
I think technology is, in

2585
01:00:26,290 --> 01:00:28,030
the past couple of years,

2586
01:00:28,030 --> 01:00:29,321
a few years, technology,

2587
01:00:29,321 --> 01:00:32,666
this mileage, this range anxiety

2588
01:00:32,666 --> 01:00:35,200
has been mostly addressed

2589
01:00:35,200 --> 01:00:37,720
by the battery technologies.

2590
01:00:37,720 --> 01:00:40,061
I feel positive about

2591
01:00:40,061 --> 01:00:43,001
at least the near term trend

2592
01:00:43,001 --> 01:00:44,830
of transportation electrification.

2593
01:00:44,830 --> 01:00:47,050
And you also probably
realize that many studies

2594
01:00:47,050 --> 01:00:49,270
now are being conducted.

2595
01:00:49,270 --> 01:00:51,655
For the developing countries,

2596
01:00:51,655 --> 01:00:55,301
while you might

2597
01:00:55,301 --> 01:00:57,700
think that developing countries

2598
01:00:57,700 --> 01:00:59,756
might be at a disadvantage.

2599
01:00:59,756 --> 01:01:03,416
But if you look at that 
from another perspective,

2600
01:01:03,416 --> 01:01:10,000
I see it as an opportunity
for leap-frog.

2601
01:01:10,191 --> 01:01:12,690
The reason is this. Just look

2602
01:01:12,690 --> 01:01:14,205
at the example of
China,

2603
01:01:14,205 --> 01:01:17,400
and I think in DC,

2604
01:01:17,400 --> 01:01:19,801
the Biden administration
and other politicians,

2605
01:01:19,801 --> 01:01:21,870
they're talking about
what has happened in

2606
01:01:21,870 --> 01:01:24,961
China in terms of 
transportation electrification.

2607
01:01:24,961 --> 01:01:27,495
So that's not necessarily,

2608
01:01:27,495 --> 01:01:29,205
I think, a disadvantage.

2609
01:01:29,205 --> 01:01:31,755
And also what is
happening in India,

2610
01:01:31,755 --> 01:01:33,871
like in the Tata company.

2611
01:01:33,871 --> 01:01:39,210
Of course, in a lot of
other developing countries,

2612
01:01:39,210 --> 01:01:40,875
while in the near term,

2613
01:01:40,875 --> 01:01:42,946
they might not be able to adopt

2614
01:01:42,946 --> 01:01:47,705
electric vehicles as fast
as the developed countries.

2615
01:01:47,705 --> 01:01:52,225
But if you look at the
overall life cycle,

2616
01:01:52,225 --> 01:01:54,611
development cost of

2617
01:01:54,611 --> 01:01:56,560
transportation electrification technologies,

2618
01:01:56,560 --> 01:01:58,481
and the adoption cost,

2619
01:01:58,481 --> 01:02:01,165
I still believe

2620
01:02:01,165 --> 01:02:04,256
that the developing countries

2621
01:02:04,256 --> 01:02:11,450
without the initial
investment in the technologies,

2622
01:02:11,731 --> 01:02:15,400
they might be able to enjoy

2623
01:02:15,400 --> 01:02:18,326
more mature and less

2624
01:02:18,326 --> 01:02:21,265
expensive and
cleaner technologies.

2625
01:02:26,851 --> 01:02:29,740
Alright, thank you
so much Oliver.

2626
01:02:29,740 --> 01:02:32,080
And I think your talk

2627
01:02:32,080 --> 01:02:35,440
definitely gave the audience
lots of new thoughts.

2628
01:02:35,440 --> 01:02:37,840
And also you gave some kind of

2629
01:02:37,840 --> 01:02:41,980
direction to the students
for their future research.

2630
01:02:41,980 --> 01:02:44,456
And you have demonstrated

2631
01:02:44,456 --> 01:02:46,615
how the interdisciplinary
research is

2632
01:02:46,615 --> 01:02:48,370
so important to connect

2633
01:02:48,370 --> 01:02:51,371
transportation environments
and public health.

2634
01:02:51,371 --> 01:02:53,605
So this is great and

2635
01:02:53,605 --> 01:02:56,786
thank you again for
delivering this talk.

2636
01:02:56,786 --> 01:02:58,166
Thank you all.

2637
01:02:58,166 --> 01:03:01,045
It was a great pleasure
to talk to you

2638
01:03:01,045 --> 01:03:02,771
I hope you'll find some of

2639
01:03:02,771 --> 01:03:06,460
the views helpful for
your future development.

2640
01:03:06,460 --> 01:03:09,010
Of course, if you have any
questions please do

2641
01:03:09,010 --> 01:03:11,710
reach out to Yu
or directly to us.

2642
01:03:11,710 --> 01:03:14,875
We'd be very happy
to answer.

2643
01:03:14,875 --> 01:03:18,431
I put the link of the CTECH
website in the chat,

2644
01:03:18,431 --> 01:03:20,740
so please write that

2645
01:03:20,740 --> 01:03:22,330
down if you want to visit

2646
01:03:22,330 --> 01:03:24,731
it later for the
recorded seminar.

2647
01:03:24,731 --> 01:03:27,775
And I want to thank Dr. Gao

2648
01:03:27,775 --> 01:03:29,320
again and also thank

2649
01:03:29,320 --> 01:03:32,891
the audience for attending
today's seminar.

2650
01:03:32,891 --> 01:03:35,081
Thank you so much.

2651
01:03:35,081 --> 01:03:37,481
Thank you. Great.

2652
01:03:37,481 --> 01:03:38,365
Bye-bye.

2653
01:03:38,365 --> 01:03:40,101
Bye.

2654