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Supply Shocks and Emissions When Firms Can Adapt

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Silke Forbes discusses the effects of a supply shock that affected some firms in the US airline industry

Image courtesy of interviewee. May 7, 2024

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This video video discusses a study on how airlines respond to supply shocks, particularly focusing on the grounding of Boeing 737 MAX planes following two fatal crashes in 2018 and 2019. This video video incident represented a significant negative shock to airlines' capital since planes are their most crucial asset. The study examines how the grounding affected airline operations and emissions, utilizing comprehensive data from the U.S. airline industry.

Key findings include:

1. **Adaptation to Supply Shock**: Airlines were able to adapt somewhat to the supply shock by changing schedules and reallocating planes to more valuable routes, indicating that while some adaptation occurred, it was imperfect.

2. **Emissions Impact**: The grounding led to a reduction in flights and overall emissions, aligned with expectations during a negative supply shock. However, specific routes that previously operated the 737 MAX experienced more significant reductions in both flights and emissions.

3. **Mechanisms of Adaptation**: The airlines struggled to expand their fleets quickly due to long production times for new planes and strict regulations affecting the leasing of older planes. Consequently, existing planes were used more intensively, but there were instances where total emissions increased locally due to the types of planes allocated to different routes.

4. **Social and Environmental Implications**: The study emphasizes the importance of understanding adaptation mechanisms across different contexts and assesses the uneven environmental impacts of airline operations on local emissions.

In summary, the research highlights the complexities of corporate responses to supply shocks in the airline industry, revealing challenges in adaptation and the resulting implications for emissions and environmental justice. Future research could explore different industries and contexts to further understand these dynamics.

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Here are some key quotes from the video discussing the impact of supply shocks on airlines, particularly focusing on the effects of the grounding of the Boeing 737 MAX:

1. **On the Importance of Aircraft:**
- "for airlines, the most important physical capital that they own are planes."

2. **On the Effects of Supply Shock:**
- "when they lose some of their planes, that's important, negative shock to their capital."

3. **Adaptation to Supply Shocks:**
- "how can firms adapt to a shock that they experience?"

4. **Discussion of Prior Research:**
- "There's been a relatively small literature on how companies respond to supply shocks."

5. **Characteristics of the Airline Industry:**
- "this is an industry that should be able to adapt relatively well to a supply shock."

6. **Methodology Focus:**
- "we look at adaptation within firms, and we can do that because we have very detailed slight level data."

7. **Specific Supply Shock Incident:**
- "after the second crash… regulators forced airlines to ground these planes to stop flying them."

8. **Duration of Impact:**
- "the grounding lasted for 18 months, until the FAA was confident that the plane was safe to fly again."

9. **Comparative Analysis:**
- "we can make comparisons between airlines that were impacted by these groundings and other airlines that were not impacted."

10. **Emissions and Adaptation:**
- "what we find is that the grounding reduced flights and therefore emissions, and that's what you would expect if there's a negative supply shock."

11. **Perfect vs. Imperfect Adaptation:**
- "this tells us that the adaptation is imperfect because airlines are losing relatively more flights on routes that are relatively more valuable."

12. **Mechanisms of Adaptation:**
- "airlines are not able to grow their fleets."

13. **Operational Changes:**
- "existing planes are used more intensively, more hours and longer distances."

14. **Conclusions on Future Research:**
- "we need to understand what are the mechanisms for adaptation."

15. **Environmental Impacts:**
- "the effects are uneven across locations... some locations seem to increase in local emissions, whereas other locations benefit from a reduction."

These quotes encapsulate the primary themes of the analysis, focusing on how airlines adapt to capital shocks, their impact on operations and emissions, and the complexities of these adaptations.

X-TIMESTAMP-MAP:LOCAL=00:00:00.000,MPEGTS=900000

00:00.095 --> 00:01.925
We're looking at, airlines

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and look at, how airlines respond to a supply shock.

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And for airlines, the most important physical capital

00:07.955 --> 00:09.525
that they own are planes.

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They use airports, but they own the planes.

00:12.625 --> 00:15.125
And so when they lose some of the, their planes,

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that's important, negative shock to their capital.

00:18.585 --> 00:19.685
And that's what we're studying.

00:20.105 --> 00:22.365
And we look at both how it impacts operations

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and also how it impacts the emissions

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because this is an important source

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of emissions around the world.

00:29.265 --> 00:32.565
Um, so specifically, you know,

00:32.635 --> 00:35.325
when we look at the airline industry, compared

00:35.325 --> 00:37.445
to other industries, planes are highly mobile.

00:37.665 --> 00:39.085
So we have an industry here

00:39.085 --> 00:41.645
where capital can actually be moved from one, one place

00:41.645 --> 00:44.685
to another because all that the airlines need to do is,

00:44.785 --> 00:47.685
you know, literally fly a plane to another place.

00:48.225 --> 00:51.405
And that means that this is an industry that should be able

00:51.405 --> 00:54.765
to adapt relatively well to a supply shock.

00:55.345 --> 00:58.485
Uh, there's been an interest in how will companies

00:58.485 --> 01:02.205
around the world adapt as we have more shocks,

01:02.275 --> 01:04.925
both in terms of, you know, the pandemic as we've seen,

01:05.265 --> 01:06.645
but also in terms of climate change.

01:06.705 --> 01:09.165
And so we are asking in this type of industry

01:09.495 --> 01:13.485
where capital is really quite mobile, how can firms adapt

01:13.865 --> 01:15.725
to a, shock that they experience?

01:16.065 --> 01:19.165
So there's been a relatively small literature on,

01:19.185 --> 01:21.925
how companies, respond to supply shocks.

01:22.235 --> 01:26.205
There's, work by Vasco cao, Marco Nire, like

01:27.395 --> 01:31.805
cyto and Alireza, that has looked at how,

01:32.185 --> 01:35.005
firms respond to natural disasters

01:35.465 --> 01:38.605
and how such shocks can propagate through the supply chain.

01:39.145 --> 01:41.725
Um, Eric Strobel has looked at,

01:41.745 --> 01:43.725
the impact on local growth when there have

01:43.725 --> 01:44.885
been natural disasters.

01:45.505 --> 01:48.485
Uh, and a more recent study by nor Nora Pancreat

01:48.485 --> 01:52.565
and Christoph Schiller investigates how the anticipation

01:52.565 --> 01:56.325
of future weather shocks from climate change affects the

01:56.325 --> 01:59.005
supply chain, that firms have.

01:59.985 --> 02:01.525
Um, we're a bit different from these papers

02:01.525 --> 02:03.965
because they mostly look at supply chain networks

02:04.255 --> 02:06.645
where there's adaptation between firms, where,

02:06.775 --> 02:09.765
where manufacturers have separate, supplier firms

02:10.235 --> 02:12.405
that they may or may not interact with anymore.

02:12.785 --> 02:15.805
And we look at adaptation within firms, and we can do that

02:15.805 --> 02:19.205
because we have very detailed slight level data.

02:19.305 --> 02:22.085
And so we can ask, how does an, a company

02:22.815 --> 02:26.525
adapt within its own production network when it's exposed

02:26.525 --> 02:28.285
to a, a negative capital shock?

02:28.515 --> 02:31.565
Yeah. So I'll speak to what exactly the,

02:31.565 --> 02:32.885
the events we're looking at.

02:33.145 --> 02:36.525
Uh, so, for the airline industry, the, as I said,

02:36.525 --> 02:38.445
the most important capitalist planes.

02:38.865 --> 02:41.565
And there are only two large,

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manufacturers in the whole world of,

02:43.865 --> 02:45.005
of commercial jet planes.

02:45.425 --> 02:47.325
Uh, and those are Airbus and Boeing.

02:47.765 --> 02:50.125
Boeing's most popular plane is the 7 3 7,

02:50.665 --> 02:54.045
and its most recent version of that plane is the 7 3 7 max.

02:54.545 --> 02:58.485
The 7 3 7 max first got into operations in the middle

02:58.485 --> 02:59.485
of 2017,

03:00.345 --> 03:03.685
and a little over a year later in October, 2018, one

03:03.685 --> 03:06.005
of these planes fatally crashed in Indonesia.

03:06.585 --> 03:10.965
And another few months later, in March, 2019,

03:11.125 --> 03:14.005
a second plane of this type, crashed in Egypt.

03:14.985 --> 03:16.685
Uh, so we had two fatal crashes.

03:16.745 --> 03:19.405
And after the second crash in the United States,

03:19.465 --> 03:22.765
the Federal Aviation Administration around the world,

03:22.825 --> 03:25.325
all regulators, forced airlines

03:25.385 --> 03:27.445
to ground these planes to stop flying them.

03:27.905 --> 03:29.605
Uh, and that meant that,

03:29.845 --> 03:31.245
airlines could no longer use these planes.

03:31.265 --> 03:35.165
And in the US the grounding lasted for 18 months,

03:35.415 --> 03:38.125
until the FAA was confident

03:38.125 --> 03:39.645
that the plane was safe to fly again.

03:39.905 --> 03:42.285
So for airlines, this was a negative supply shock.

03:42.585 --> 03:46.005
Uh, but not all airlines in the United States had operated

03:46.005 --> 03:48.125
these planes, and we were focusing on the US

03:48.555 --> 03:50.485
because, for one,

03:50.545 --> 03:53.085
we have very good data on the airline industry.

03:53.665 --> 03:56.645
And the second reason is that this is a very large market

03:56.895 --> 04:00.565
where we have many different routes where multiple,

04:00.765 --> 04:01.925
airlines compete against each other.

04:02.265 --> 04:04.725
So we can make comparisons between airlines

04:05.395 --> 04:07.285
that were impacted by these groundings

04:07.425 --> 04:09.005
and other airlines that were not impacted.

04:09.585 --> 04:13.605
Uh, and so specifically in the us, three large airlines,

04:14.085 --> 04:16.725
American, United and Southwest had operated the

04:16.725 --> 04:18.085
7 3 7 max planes.

04:18.625 --> 04:20.405
Uh, the fourth large airline,

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Delta had not operated this plane.

04:22.785 --> 04:24.965
And all the smaller airlines like JetBlue

04:24.965 --> 04:27.605
or Alaska also weren't operating these planes

04:27.735 --> 04:28.845
prior to the grounding.

04:28.845 --> 04:31.685
So that allows us, getting to methodology

04:32.585 --> 04:34.885
to do a difference in differences analysis,

04:34.885 --> 04:37.205
where we can look at airlines that were impacted

04:37.265 --> 04:40.085
by the shock and compare them to other airlines.

04:40.225 --> 04:43.285
And we're doing, you know, a a, a comparison where we assume

04:43.715 --> 04:46.445
that the impacted airlines would've behaved

04:46.585 --> 04:50.125
and grown the network in the same way,

04:50.305 --> 04:52.285
as the other airlines had they not

04:52.285 --> 04:53.485
been impacted by the shock.

04:53.485 --> 04:55.365
Yeah, I think you asked me to speak a bit

04:55.365 --> 04:56.445
to, to data as well.

04:56.445 --> 04:59.125
Yeah. So that briefly, address the data.

04:59.505 --> 05:03.085
Um, we're using data on, airline schedules

05:03.085 --> 05:05.325
and planes from the US Department of Transportation.

05:06.265 --> 05:09.365
Uh, and then we combine this with an emissions calculator

05:09.595 --> 05:12.805
that the European Environment Agency makes available.

05:13.425 --> 05:15.565
Um, we look at emissions,

05:15.845 --> 05:17.445
specifically from landing and takeoff.

05:17.985 --> 05:19.085
Um, and the seventh

05:19.145 --> 05:20.165
or seven max plane

05:20.165 --> 05:22.925
that was grounded had relatively lower emissions than the

05:22.925 --> 05:24.125
typical plane,

05:24.135 --> 05:26.485
especially if you look at it per passenger basis.

05:26.665 --> 05:30.205
So that's, motivated us to study the, the impact

05:30.225 --> 05:32.565
of this particular shock on emissions.

05:33.105 --> 05:37.285
So the, what we find is that the grounding reduced flights

05:37.285 --> 05:38.605
and therefore emissions, and that's

05:38.605 --> 05:40.685
what you would expect if there's a negative supply shock.

05:41.065 --> 05:42.965
Uh, and then we look in particular at

05:42.965 --> 05:44.725
how airlines adapt to the shock.

05:45.185 --> 05:47.405
So we see that over time they adapt

05:47.405 --> 05:48.645
by changing their schedules

05:48.645 --> 05:50.885
and reducing this number of scheduled flights.

05:51.265 --> 05:53.285
Uh, and then we see that airlines

05:53.805 --> 05:55.845
reallocate planes across their network

05:56.345 --> 05:57.965
to higher value routes.

05:58.225 --> 06:00.565
And the impact routes were particularly routes

06:00.565 --> 06:02.805
that were re relatively high value.

06:03.425 --> 06:07.325
Um, so we see reductions in flights

06:07.325 --> 06:09.925
and emissions on all routes, not just the routes

06:09.925 --> 06:12.165
that had been flying these 7, 3 7 max planes.

06:12.745 --> 06:16.485
Um, however, when we compare across routes, we see

06:16.485 --> 06:20.165
that the biggest impacts both in terms of number

06:20.165 --> 06:24.225
of flights, but also in terms of emissions are on the roots,

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that had been flying 77 max planes.

06:27.685 --> 06:30.625
So while there's some adaptation, this tells us

06:30.625 --> 06:32.505
that the adaptation is imperfect

06:32.735 --> 06:36.745
because airlines are losing relatively more flights on

06:36.745 --> 06:38.825
routes that are relatively more valuable,

06:38.825 --> 06:41.385
whereas the Econ 1 0 1 would tell you

06:41.535 --> 06:44.305
that you would reduce flights most on the routes

06:44.305 --> 06:45.465
that are the least valuable.

06:45.685 --> 06:48.025
So that tells us that there are frictions in the network.

06:48.095 --> 06:50.225
They cannot fully adapt to the shock,

06:50.405 --> 06:51.745
but they can partially adapt.

06:52.685 --> 06:56.385
Um, and so when you then look at, emissions,

06:56.385 --> 06:58.825
they very much are in line with, with number of flights.

06:58.825 --> 07:01.825
We look at the per seat emissions, right?

07:02.205 --> 07:05.425
So, so that's our proxy for per passenger emissions.

07:06.515 --> 07:08.785
There we've seen very interesting finding that

07:08.785 --> 07:12.105
because of the way that planes are reallocated,

07:12.415 --> 07:15.745
sometimes the older dirtier planes that are sent

07:15.745 --> 07:17.145
to certain routes and newer

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and cleanup planes are sent to others,

07:19.685 --> 07:23.305
we actually find some routes where total emissions increase

07:23.725 --> 07:26.025
and some airports where total emissions,

07:26.385 --> 07:30.665
increase locally, even though the overall emissions

07:30.665 --> 07:32.105
for the whole country decrease.

07:32.245 --> 07:34.665
So it's, there's reallocation,

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overall we see fewer emissions,

07:36.805 --> 07:40.265
but in some places we see an increase, and that's

07:40.265 --> 07:43.225
because of the types of planes that are moved

07:43.245 --> 07:44.545
to these, these airports.

07:44.925 --> 07:46.465
And then we look at the mechanisms,

07:46.575 --> 07:47.785
what are airlines actually doing?

07:48.285 --> 07:51.905
For one, we find that, airlines are not able

07:51.905 --> 07:54.145
to grow their, their, fleets.

07:54.645 --> 07:58.265
So, you know, you might expect that they lose some planes,

07:58.265 --> 08:00.065
they might try to replace 'em with others.

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It's very, it takes a very long time to produce new planes,

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and so they cannot quickly get new planes.

08:06.975 --> 08:11.075
And it's also difficult to lease or buy older planes

08:11.075 --> 08:12.635
and bring them maybe from other countries

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because they're very strict regulations, in,

08:16.125 --> 08:17.835
about bringing planes into service.

08:17.975 --> 08:21.155
So there's, a very strict limitation on expanding,

08:21.455 --> 08:22.755
the capital stock.

08:23.105 --> 08:24.755
However, we see that the

08:25.275 --> 08:27.115
existing plans are used more intensively,

08:27.495 --> 08:31.275
so capital stock is used more intensively, more hours

08:31.615 --> 08:33.235
and, longer distances.

08:33.495 --> 08:35.555
So those are the, the key findings that we have.

08:36.025 --> 08:38.155
Yeah, sweat the asset. Really good. Okay.

08:38.155 --> 08:39.995
What about the final question. What about your conclusions

08:39.995 --> 08:42.795
and implications and areas for future research? So,

08:43.655 --> 08:46.835
Yes, so the key impact is

08:46.835 --> 08:48.675
that when we study the impact

08:48.675 --> 08:51.115
of supply shocks on firms operations

08:51.415 --> 08:53.315
and their emissions, we have

08:53.315 --> 08:55.725
to think about adaptation responses of firms.

08:55.865 --> 08:57.765
And so we need to understand,

08:57.765 --> 08:59.685
what are the mechanisms for adaptation.

09:00.145 --> 09:01.485
For example, in our study,

09:01.825 --> 09:05.005
moving capital across the network in other contexts,

09:05.005 --> 09:07.325
these might be different adaptation mechanisms.

09:07.625 --> 09:08.725
We need to incorporate them

09:08.745 --> 09:12.125
to study the impact both on production,

09:12.125 --> 09:14.405
and the emissions that result from production.

09:15.425 --> 09:18.445
Um, because we're looking at an industry

09:18.445 --> 09:21.485
that is highly mobile, we think

09:21.485 --> 09:24.245
that this should be an industry where it's relatively easy

09:24.385 --> 09:25.845
to adapt to the supply shock.

09:25.845 --> 09:27.765
And we see there that there is adaptation,

09:28.025 --> 09:29.045
but it's imperfect.

09:29.225 --> 09:31.685
And so I think it will be really fascinating

09:32.225 --> 09:35.965
to study other contexts where it might be harder to adapt

09:36.065 --> 09:38.685
or the form of adaptation might be different.

09:39.385 --> 09:42.485
Um, and then finally, if we're,

09:42.485 --> 09:45.685
as we're thinking about the pollution impacts,

09:45.785 --> 09:48.085
and also, social justice relating

09:48.085 --> 09:51.685
to environmental impacts, it's important to consider

09:51.715 --> 09:55.525
that the, that the effects are uneven across locations.

09:55.755 --> 09:57.045
That there's some locations

09:57.045 --> 10:00.005
that actually seem increase in local emissions,

10:00.005 --> 10:03.085
whereas other locations benefit from a reduction.

Airlines' Adaptation to Supply Shocks and Emissions

00:00:00 - We're looking at, airlines and look at, how airlines respond to a supply shock. And for airlines, the most important physical capital that they own are planes. They use airports, but they own the planes. And so when they lose some of the, their planes, that's important, negative shock to their capital. And that's what we're studying. And we look at both how it impacts operations and also how it impacts the emissions because this is an important source of emissions around the world. so specifically, you know,
00:00:35 - to other industries, planes are highly mobile. So we have an industry here where capital can actually be moved from one, one place to another because all that the airlines need to do is, you know, literally fly a plane to another place. And that means that this is an industry that should be able to adapt relatively well to a supply shock. there's been an interest in how will companies around the world adapt as we have more shocks, both in terms of, you know, the pandemic as we've seen,
00:01:06 - And so we are asking in this type of industry where capital is really quite mobile, how can firms adapt to a, shock that they experience? So there's been a relatively small literature on, how companies, respond to supply shocks. There's, work by Vasco cao, Marco Nire, like cyto and Alireza, that has looked at how, firms respond to natural disasters
00:01:39 - Eric Strobel has looked at, the impact on local growth when there have been natural disasters. and a more recent study by nor Nora Pancreat and Christoph Schiller investigates how the anticipation of future weather shocks from climate change affects the supply chain, that firms have. we're a bit different from these papers because they mostly look at supply chain networks where there's adaptation between firms, where,
00:02:10 - that they may or may not interact with anymore. And we look at adaptation within firms, and we can do that because we have very detailed slight level data. And so we can ask, how does an, a company adapt within its own production network when it's exposed to a, a negative capital shock? Yeah. So I'll speak to what exactly the, the events we're looking at. so, for the airline industry, the, as I said, the most important capitalist planes.
00:02:41 - manufacturers in the whole world of, of commercial jet planes. and those are Airbus and Boeing. Boeing's most popular plane is the 7 3 7, and its most recent version of that plane is the 7 3 7 max. The 7 3 7 max first got into operations in the middle of 2017, and a little over a year later in October, 2018, one of these planes fatally crashed in Indonesia. And another few months later, in March, 2019,

Impact of 737 Max Grounding on Airlines

00:03:14 - so we had two fatal crashes. And after the second crash in the United States, the Federal Aviation Administration around the world, all regulators, forced airlines to ground these planes to stop flying them. and that meant that, airlines could no longer use these planes. And in the US the grounding lasted for 18 months, until the FAA was confident that the plane was safe to fly again. So for airlines, this was a negative supply shock.
00:03:46 - these planes, and we were focusing on the US because, for one, we have very good data on the airline industry. And the second reason is that this is a very large market where we have many different routes where multiple, airlines compete against each other. So we can make comparisons between airlines that were impacted by these groundings and other airlines that were not impacted. and so specifically in the us, three large airlines,
00:04:16 - 7 3 7 max planes. the fourth large airline, Delta had not operated this plane. And all the smaller airlines like JetBlue or Alaska also weren't operating these planes prior to the grounding. So that allows us, getting to methodology to do a difference in differences analysis, where we can look at airlines that were impacted by the shock and compare them to other airlines. And we're doing, you know, a a, a comparison where we assume that the impacted airlines would've behaved
00:04:50 - as the other airlines had they not been impacted by the shock. Yeah, I think you asked me to speak a bit to, to data as well. Yeah. So that briefly, address the data. we're using data on, airline schedules and planes from the US Department of Transportation. and then we combine this with an emissions calculator that the European Environment Agency makes available. we look at emissions, specifically from landing and takeoff.
00:05:19 - or seven max plane that was grounded had relatively lower emissions than the typical plane, especially if you look at it per passenger basis. So that's, motivated us to study the, the impact of this particular shock on emissions. So the, what we find is that the grounding reduced flights and therefore emissions, and that's what you would expect if there's a negative supply shock. and then we look in particular at how airlines adapt to the shock. So we see that over time they adapt by changing their schedules
00:05:51 - and then we see that airlines reallocate planes across their network to higher value routes. And the impact routes were particularly routes that were re relatively high value. so we see reductions in flights and emissions on all routes, not just the routes that had been flying these 7, 3 7 max planes. however, when we compare across routes, we see that the biggest impacts both in terms of number

Airline Adaptation to Supply Shock and Emissions

00:06:24 - that had been flying 77 max planes. So while there's some adaptation, this tells us that the adaptation is imperfect because airlines are losing relatively more flights on routes that are relatively more valuable, whereas the Econ 1 0 1 would tell you that you would reduce flights most on the routes that are the least valuable. So that tells us that there are frictions in the network. They cannot fully adapt to the shock,
00:06:52 - and so when you then look at, emissions, they very much are in line with, with number of flights. We look at the per seat emissions, right? So, so that's our proxy for per passenger emissions. There we've seen very interesting finding that because of the way that planes are reallocated, sometimes the older dirtier planes that are sent to certain routes and newer and cleanup planes are sent to others, we actually find some routes where total emissions increase
00:07:26 - increase locally, even though the overall emissions for the whole country decrease. So it's, there's reallocation, overall we see fewer emissions, but in some places we see an increase, and that's because of the types of planes that are moved to these, these airports. And then we look at the mechanisms, what are airlines actually doing? For one, we find that, airlines are not able to grow their, their, fleets.
00:07:58 - they might try to replace 'em with others. It's very, it takes a very long time to produce new planes, and so they cannot quickly get new planes. And it's also difficult to lease or buy older planes and bring them maybe from other countries because they're very strict regulations, in, about bringing planes into service. So there's, a very strict limitation on expanding, the capital stock. However, we see that the
00:08:27 - so capital stock is used more intensively, more hours and, longer distances. So those are the, the key findings that we have. Yeah, sweat the asset. Really good. Okay. What about the final question. What about your conclusions and implications and areas for future research? So, Yes, so the key impact is that when we study the impact of supply shocks on firms operations and their emissions, we have to think about adaptation responses of firms.
00:08:57 - what are the mechanisms for adaptation. For example, in our study, moving capital across the network in other contexts, these might be different adaptation mechanisms. We need to incorporate them to study the impact both on production, and the emissions that result from production. because we're looking at an industry that is highly mobile, we think that this should be an industry where it's relatively easy to adapt to the supply shock. And we see there that there is adaptation,

Exploring Environmental Adaptation and Inequities

00:09:29 - And so I think it will be really fascinating to study other contexts where it might be harder to adapt or the form of adaptation might be different. and then finally, if we're, as we're thinking about the pollution impacts, and also, social justice relating to environmental impacts, it's important to consider that the, that the effects are uneven across locations. That there's some locations that actually seem increase in local emissions,
00:10:00 -

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