1
00:00:00,000 --> 00:00:05,000
(soft bright music)
(logo whooshing)

2
00:00:07,170 --> 00:00:09,826
- [Narrator] Ground-level
ozone is a pollutant that forms

3
00:00:09,826 --> 00:00:12,630
when nitrogen oxides, or NOx,

4
00:00:12,630 --> 00:00:16,320
combined with volatile
organic compounds, or VOCs,

5
00:00:16,320 --> 00:00:18,540
in the presence of sunlight.

6
00:00:18,540 --> 00:00:20,616
Emissions from transportation play a role

7
00:00:20,616 --> 00:00:22,740
in ozone formation,

8
00:00:22,740 --> 00:00:25,980
but data gathered during
the COVID-19 lockdown

9
00:00:25,980 --> 00:00:28,650
has shown some unexpected findings.

10
00:00:28,650 --> 00:00:30,990
The Texas Department of Transportation

11
00:00:30,990 --> 00:00:35,100
and researchers with the Texas
A&M Transportation Institute

12
00:00:35,100 --> 00:00:38,610
have studied the data to better
understand the relationship

13
00:00:38,610 --> 00:00:41,610
between transportation and air quality.

14
00:00:41,610 --> 00:00:45,750
- When COVID happened,
we ended up seeing things

15
00:00:45,750 --> 00:00:48,180
that didn't make sense, so in particular,

16
00:00:48,180 --> 00:00:50,640
it was with ozone concentrations.

17
00:00:50,640 --> 00:00:52,770
They were showing that,

18
00:00:52,770 --> 00:00:55,410
even though traffic had
gone down significantly,

19
00:00:55,410 --> 00:00:58,830
we were still seeing ozone
on those same days go higher

20
00:00:58,830 --> 00:01:00,240
than we were expecting.

21
00:01:00,240 --> 00:01:03,210
- So this study used
diverse sources of data.

22
00:01:03,210 --> 00:01:04,530
For transportation side,

23
00:01:04,530 --> 00:01:08,160
we used TxDOT's vehicle detector data

24
00:01:08,160 --> 00:01:10,380
that collects volume and speed,

25
00:01:10,380 --> 00:01:11,940
hourly volume, and hourly speed,

26
00:01:11,940 --> 00:01:15,210
and we also used national-level
probe vehicle data

27
00:01:15,210 --> 00:01:19,020
to model the transportation
activities in Texas regions.

28
00:01:19,020 --> 00:01:20,400
For air quality side,

29
00:01:20,400 --> 00:01:24,000
we used multiple air quality
monitoring stations data,

30
00:01:24,000 --> 00:01:25,170
satellite images,

31
00:01:25,170 --> 00:01:28,230
and we also used national-level
emission inventory data.

32
00:01:28,230 --> 00:01:31,310
So we developed a modeling chain consist

33
00:01:31,310 --> 00:01:34,890
of transportation modeling,
emission estimation,

34
00:01:34,890 --> 00:01:38,760
and modeling air quality,
which is estimating origin

35
00:01:38,760 --> 00:01:41,070
and PM2.5 concentrations.

36
00:01:41,070 --> 00:01:44,340
For ozone concentration, we
used the chemical modeling,

37
00:01:44,340 --> 00:01:47,280
which requires huge computational power,

38
00:01:47,280 --> 00:01:49,920
so we used Texas A&M University's

39
00:01:49,920 --> 00:01:52,860
high-performance research
computing systems,

40
00:01:52,860 --> 00:01:57,860
and for PM2.5 concentrations,
we use air dispersion models.

41
00:01:58,050 --> 00:02:00,990
- First is figuring out what
was going on with ozone,

42
00:02:00,990 --> 00:02:05,990
and it's ozone titration, so basically,

43
00:02:06,390 --> 00:02:09,690
in certain VOC-limited areas,

44
00:02:09,690 --> 00:02:11,668
actually dropping the NOx concentration

45
00:02:11,668 --> 00:02:13,950
by reducing the number
of vehicles on the road

46
00:02:13,950 --> 00:02:16,830
can actually cause an increase in ozone.

47
00:02:16,830 --> 00:02:20,400
- Since ozone is a
combination of NOx and VOC,

48
00:02:20,400 --> 00:02:23,070
the level of VOC and
NOx is very important,

49
00:02:23,070 --> 00:02:27,090
so the urban area is usually
known as VOC-limited regimes,

50
00:02:27,090 --> 00:02:30,630
which means VOC is limited,
but there are plenty of NOx.

51
00:02:30,630 --> 00:02:32,760
But in the rural or suburban area,

52
00:02:32,760 --> 00:02:36,300
it's usually NOx-limited
regimes, so it is opposite,

53
00:02:36,300 --> 00:02:39,840
so that's why we observe
transportation decrease,

54
00:02:39,840 --> 00:02:42,780
but ozone increase in urban
area like Houston and Dallas,

55
00:02:42,780 --> 00:02:44,193
- We do research to try to understand

56
00:02:44,193 --> 00:02:48,420
how we impact the world
around us and the public,

57
00:02:48,420 --> 00:02:50,430
hopefully, an efficient
transportation system,

58
00:02:50,430 --> 00:02:53,610
but also in terms of how
that transportation system

59
00:02:53,610 --> 00:02:57,630
can otherwise affect the
public and how we can evaluate

60
00:02:57,630 --> 00:03:00,030
and potentially even mitigate for that.

61
00:03:00,030 --> 00:03:01,320
- [Narrator] For more information

62
00:03:01,320 --> 00:03:04,320
and to find the publications
for this project,

63
00:03:04,320 --> 00:03:06,373
please visit the TxDOT research library

64
00:03:06,373 --> 00:03:08,703
at the link shown below.