Indian Super-Smog

We’ve poked a lot of fun at China and their serious smog problem. (Just this week, Beijing schools had their very first “smog day.” It’s just like a “snow day”, except you can’t go outside and write your name in it.) But, as it turns out, China is not the only country to produce super-thick smog. India does it, too. And, from the point of view of human health, India’s smog may actually be worse!

The World Health Organization just released a list of the Top 20 smoggiest cities, and 13 of them are in India (plus 1 in Bangladesh and 3 in Pakistan). Not a single Chinese city was anywhere in the Top 20! I’d consider taking back some of things I’ve said about China, except that 1) I never lied (although I did quote Brian Williams), and 2) the Chinese government is now instituting “smog days” because the smog is so bad. What I will do is stop comparing every type of air pollution to Chinese smog. From now on (at least until they start making some positive changes), India is the paragon of poor air quality on this blog.

Since VIIRS has no trouble seeing Chinese smog, it should have no problem seeing Indian smog. And it doesn’t:

VIIRS True Color RGB composite of channels M-4, M-4 and M-5 (07:14 UTC 18 November 2015)

VIIRS True Color RGB composite of channels M-4, M-4 and M-5 (07:14 UTC 18 November 2015).

You guessed it: all that gray area is optically thick smog! Let’s not forget, too, that India is the seventh largest country in world (2.4% of the Earth’s total surface area!), which is quite a large area to be covered by smog.

In the True Color image above from 18 November 2015, you can see that the people of Tibet are grateful for the Himalayas, which are an effective barrier to the smog. They may not get much air up there on the highest plateau in the world, but what little there is is much cleaner than what’s down below!

If your respiratory system is sensitive to this kind of thing, you might not want to read any further. Consider this your trigger warning. For those few brave enough to continue – prepare yourself, because it gets worse!

Here’s another VIIRS True Color image from 14 November 2015:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (06:50 UTC 14 November 2015)

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (06:50 UTC 14 November 2015).

Now it’s even harder to see the background surface along the base of the Himalayas. And, it’s easy to compare India’s pollution with Burma’s – I mean Myanmar’s – clean air.

VIIRS passed over the center of India on 11 November 2015 and saw that almost the entire country was covered by smog, with the thickest smog near Delhi:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (07:46 UTC 11 November 2015)

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (07:46 UTC 11 November 2015).

November 11th was the night of Diwali, the Hindu, Sikh and Jain “Festival of Lights” celebrating the “triumph of goodness over evil and knowledge over ignorance.” If you clicked that link and thought, “that doesn’t look so bad,” then note that the first few pictures were taken in England. In India, it was much smokier. I guess lighting all those fireworks in India comes with this “pro”: they can light the way through the thick smog; and this “con”: they give off smoke that adds to the thick smog. And, while the smog didn’t stop people from celebrating Diwali, it did affect people’s plans. It also caused a huge increase in the market for air purifiers.

The super-smog was not confined to November or Diwali. It’s still going on! Here’s a VIIRS image from 5 December 2015:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (06:56 UTC 5 December 2015)

VIIRS True Color RGB composite of channels M-3, M-4 and M-5 (06:56 UTC 5 December 2015).

I assure you that India and Bangladesh are under there somewhere beneath all that gray muck!

As I mentioned in the previous post, we now have access to data from the new Japanese satellite, Himawari, which can be thought of as a geostationary version of VIIRS. Himawari-8 hangs out over the Equator at a longitude of 140 °E and it takes images of the full disk every 10 minutes. From its perspective, India is right on the edge of the Earth (which, in satellite meteorology is called “the limb”). This means Himawari’s line-of-sight to India has an extra long path through the atmosphere, and that makes the smog look even worse. Here’s a True Color/Geocolor loop of Himawari images of India’s “Worse-than-China” Super-Smog. You can find this and other amazing loops on our new “Himawari Loop of the Day” webpage. We also produce a lot of other Himawari imagery products, which we post here.

Shameless plugs aside, don’t forget: India’s smog is actually worse than China’s. And, unless you live in India, you probably didn’t think that was possible! (If you do live in India, get them to clean up the air!)

The Great Indian Heat Wave of 2015

Have you ever slept in a really hot room?

Of course, if you clicked on that link, keep in mind two things: perjury is a crime, and extreme heat is no joke. It is number one on the list of causes of weather-related fatalities. It may not capture the attention of the media like tornadoes, typhoons and tiger sharks but, exposure to extreme heat and extreme cold are routinely found to be the top two killers worldwide. (Well, that depends on the source of your information and how deaths are or are not attributed to weather. Some say extreme droughts and floods kill more.)

And of course, video footage of tornadoes and typhoons is more dramatic than frying an egg on the sidewalk or watching someone sweat inside a car. But, a recent heat wave in India is actually grabbing some attention from the media. Is it because there have been more than 2,200 documented fatalities? Or, the fact that it has been hot enough to make the roads melt?

Take a look at this hi/lo temperature calendar produced by the Weather Underground for Delhi, India during May 2015. If you’re paying attention, you’ll notice that only 4 days during the month had high temperatures less than 100 °F (38 °C). What is more concerning is that 18 out of the 31 days had low temperatures in the 80s. Look at May 18, 25 and 31: the lowest temperature recorded on each of those days was 87 °F (31 °C)! And take a look at the 10-day period in Hyderabad, India (May 20-29): highs near 110 °F everyday, with lows in the mid- to upper-80s.

And, for those of you in Phoenix or Death Valley, it is not a dry heat. According to this website, the automated weather station in Tirumala, Andhra Pradesh state recorded a temperature of 50 °C (122 °F) on May 31st. The day before, the high was 49 °C (120 °F), with a dew point of 24 °C (75 °F), which yields a heat index (or “feels like”) temperature of 59 °C (139 °F)!

Whether you side with Newman or Kramer on wanting to kill yourself after sleeping in a really hot room, with temperatures like this, it might not be your choice. If your body can’t cool down, you’ll be in trouble – especially if you don’t have air conditioning, like a lot of people in India.

You’ve probably guessed by now that VIIRS is capable of telling us something about this heatwave. And, you’re right! (Otherwise I wouldn’t be writing this.)

You should all know by now that the amount of radiation in the longwave infrared (IR) “window” (10-11 µm) is a function of the temperature of the object you’re looking at. We often refer to an object’s “brightness temperature,” which is the temperature that a black body would have if it emitted the same amount of radiation. With that in mind, here is the VIIRS longwave IR (M-15) image from 18 May 2015:

VIIRS IR (M-15) image from 08:06 UTC 18 May 2015.

VIIRS IR (M-15) image from 08:06 UTC 18 May 2015. Colors correspond to brightness temperatures according to the scale at lower right.

The first thing to notice is: there aren’t many clouds out there to block out the sun. The second thing to notice is: that big, black area in west-central India is where the color-enhancement of the image has lead to “saturation”. The IR color table I like to use saturates at brightness temperatures of 330 K (57 °C), which isn’t usually a problem because most places around the globe don’t get that hot. Some pixels in this image reached 332 K (59 °C/139 °F)! (The detectors of M-15 don’t saturate unless the brightness temperature is higher than 380 K, so this is not a problem with VIIRS.)

To prove there weren’t many clouds, here’s the True Color RGB (M-3/M-4/M-5):

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 08:06 UTC 18 May 2015

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 08:06 UTC 18 May 2015.

There is some smog and dust, though, if you look close but, it’s not quite the same thing. And wait! The observed temperatures were only 40-45 °C, not 59 °C! What gives?

Aha! You are now aware of the difference between “air temperature” and “skin temperature”. The satellite observes “skin temperature” – the temperature of the surface of the objects it’s looking at*.  Thermometers measure the temperature of the air 2 m above the ground (assuming they follow the WMO standards [PDF]). As anyone who has ever tried to fry an egg on the sidewalk knows, the egg would never get cooked if you suspended it in the air 2 m above the ground. The ground heats up a lot more than the air does in this situation. One of the reasons is that the atmosphere doesn’t absorb radiation in this wavelength range*- and, if it did, it wouldn’t be an “atmospheric window”.

(* Not exactly. The atmosphere does have some effects in this wavelength range that have to be removed to get a true skin temperature. These effects increase with wavelength in the 11-12 µm range, which is why you may hear it called a “dirty window”.)

Another thing you should already know (even without cracking a few eggs) is that it’s much more comfortable to walk barefoot on grass in a park, than it is to walk barefoot in the parking lot (especially if it’s hot enough to make the asphalt melt). VIIRS can also tell you this.

Below, we’ve zoomed in on the area around Bombay (Mumbai) and the Gulf of Cambay. This is an image overlay that you might have to refresh your browser to see. Bombay is on the coast near the bottom of the images. As you drag the line back and forth, notice the areas with vegetation in the True Color image have a lower brightness temperature than the areas with bare ground.

beforeafter

Vegetation has the ability to keep itself cool (in a process similar to sweating), unlike the bare dirt. Of course, there may be some terrain effects and marine effects along the coastline that are keeping those areas cooler. Although, the terrain west of the Gulf is the hottest part of the scene (notice it has very little green vegetation). And, if you think the marine-influenced boundary layer moderates the temperatures, which it does, it greatly adds to the humidity. Bombay’s highs during the month of May were only in the 90s F (33-35 °C), but dew points were also 80-86 °F (27-30 °C). This gives a heat index of anywhere between 110-130 °F (45-54 °C). And, of course, with all that humidity, it never cooled off at night.

I mentioned smog and dust earlier. Well, the haze, smog and dust were even worse over northwestern India on 20 May 2015:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 07:28 UTC 20 May 2015

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken 07:28 UTC 20 May 2015.

If you click on the image to see it in full resolution, you can see that the smog is trapped by the Himalayas. That means the people of Tibet are not only at more comfortable temperatures, they can also breathe fresh air.

In case you’re wondering, the dust does show up in the IR as well:

VIIRS IR (M-15) image, taken 07:28 UTC 20 May 2015

VIIRS IR (M-15) image, taken 07:28 UTC 20 May 2015.

Haze, smog, dust, unbearable heat and humidity: it’s no wonder why the people of India pray for the monsoon.

When China Looks Like Canada

OK, so there probably aren’t any “Canadatowns” in China like there are Chinatowns in Canada. (Now you’re probably wondering what a Canadatown in China would look like. Maybe stores and restaurants selling poutine and maple syrup? Hockey rinks and curling sheets everywhere? A Tim Hortons on every street corner?) But this isn’t about that!

Last time I made the comparison between Canada and China, it was because there were numerous fires, particularly in the Northwest Territories, that produced so much smoke that it choked the air, making it difficult to breathe. This smoke was visible all the way down to the Lower 48 United States. These huge smoke plumes looked a lot like Chinese super-smog. Today, we’re talking not about the smoke and smog… well, actually, smoke and smog will be mentioned… hmm. Uh, what I mean is we’re focusing on the zillions of fires that VIIRS saw over Manchuria – just like the zillions of fires in the Northwest Territories. Well, OK, not “just like” – those fires were caused by Mother Nature. These fires appear to be intentionally set by human beings and are much smaller.

A CIRA colleague was checking out a real-time loop of MTSAT 3.75 µm imagery over northeastern China and reported seeing bright spots (which are typically hot spots from fires) throughout the area for most of the last month. So what is going on there?

MTSAT has ~4 km spatial resolution, so it’s not the best for fire detection. (At the time of this writing, CIRA has access to MTSAT-2, aka Himawari-7, which has 4 km spatial resolution in the infrared channels. The Advanced Himawari Imager {AHI} was successfully launched on Himawari-8 on 7 October 2014 and, when the operational imagery becomes available, it will have 2 km resolution in this channel [and it will have many of the channels that VIIRS has]. CIRA has plans to acquire this data when it becomes available. Until then, you’ll have to deal with coarse spatial resolution.) To really see what is going on, you need the spatial resolution of VIIRS.

Of course, spatial resolution is not the only thing you need. Check out the VIIRS M-13 (4.0 µm)  image below from 04:48 UTC 18 November 2014. How many hot spots can you see?

VIIRS M-13 image of northeastern China, taken 04:48 UTC 18 November 2014

VIIRS M-13 image of northeastern China, taken 04:48 UTC 18 November 2014.

This image uses a color table specifically designed to highlight hot spots from fires. Any pixel above 317 K (44 °C or 111 °F) is colored. (As always, click on the image to see it in full resolution.) There aren’t that many colored pixels, even though we’re using a relatively low temperature threshold for fire detection. There are, however, a lot of nearly black pixels, which means they are warmer than the background, but not warm enough to be highlighted. (In case you’re not sure, I’m talking about the area between 45° and 48°N, 123° and 128°E.) If we used this temperature threshold in a summer scene, there would be a lot false alarm fire detections.

A situation like this is when the Fire Temperature RGB composite comes in handy. It can detect the small (or low temperature) fires with no problem, particularly since the background isn’t very warm. Try to count up all the red pixels in this image from the same time:

VIIRS Fire Temperature RGB composite of channels M-10, M-11 and M-12, taken 04:48 UTC 18 November 2014

VIIRS Fire Temperature RGB composite of channels M-10, M-11 and M-12, taken 04:48 UTC 18 November 2014.

That’s a lot of fires! It’s probably because there are so many of them that they were visible in MTSAT. If you look closely at the full resolution image, there are two significant fires in North Korea, plus many more smaller fires/hot spots northwest and north of the Yellow Sea. Go back and compare the Fire Temperature RGB with the M-13 image. Admit it: fires in this scene are easier to see in the RGB composite.

If you don’t believe me, check out the M-13 and Fire Temperature RGB images that have been zoomed in on main concentration of fires. The Fire Temperature RGB has been lightened a little bit and the M-13 image has been darkened a little bit to highlight the hot spots better.

VIIRS M-13 image (as above) but zoomed in and slightly darkened

VIIRS M-13 image (as above) but zoomed in and slightly darkened.

VIIRS Fire Temperature RGB image (as above) but zoomed in and lightened slightly

VIIRS Fire Temperature RGB image (as above) but zoomed in and lightened slightly.

If you want to know why the Fire Temperature RGB composite works, go back and read this and this. Otherwise, stay put. If you’re familiar with the Fire Temperature RGB, because you are a loyal follower of this blog, you may be wondering why the overall image looks so dark.

All the previous cases where I’ve shown this RGB have been in the summer, typically under bright sunlight (since fires don’t tend to occur in winter). Here, it’s almost winter so there is less sunlight and the background surface is colder, which are going to make the image appear darker. Plus, there is some snow in the scene and snow appears black in this RGB composite. It’s not reflective at 1.61 µm (blue component) or 2.25 µm (green component) or at 3.74 µm (red component), plus it’s cold so it doesn’t emit much radiation at any of these wavelengths either.

The Natural Color RGB shows where the snow is. Look for the cyan signature of snow and ice here:

VIIRS Natural Color RGB composite of channels M-5, M-7, and M-10, taken 04:48 UTC 18 November 2014

VIIRS Natural Color RGB composite of channels M-5, M-7, and M-10, taken 04:48 UTC 18 November 2014.

The Natural Color RGB shows that the fires are occurring in an area with a lot of lakes. Also, there isn’t a very strong green signature from vegetation in this area. So what is burning? Your guess is as good as mine. (Unless your guess is a bunch of Chinese children using magnifying glasses to burn ants. That’s not a very good guess – particularly because, as I said, there is less sunlight in the winter and it’s colder so the ants wouldn’t ignite easily. Also, that’s a cruel thing to suggest and my reasoned account of why that wouldn’t work should not be taken as an implicit admission that I ever did such a thing as a kid.)

A quick perusal of Google Maps reveals that it is an area full of agricultural fields. So my guess is that it’s some sort of end-of-year burning of agricultural waste. They are all small or low temperature fires and they’re not anything that made the news (I checked), so it’s doubtful that it’s a zillion uncontrolled fires.

How do we even know they’re fires? Besides the fact that they show up in the Fire Temperature RGB, we can also see the smoke. Check out this True Color RGB image and focus on the area where the majority of the fires are occurring:

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken at 04:48 UTC 18 November 2014

VIIRS True Color RGB composite of channels M-3, M-4 and M-5, taken at 04:48 UTC 18 November 2014.

There are visible smoke plumes right where the greatest concentration of hot spots is located. There is also a long plume of gray along the base of the Changbai Mountains stretching southwest to the shores of the Yellow Sea, but it’s not clear if that is also smoke or simply smog. By the way, if you have respiratory ailments, don’t look at the southwest corner of the image (west of the Yellow Sea) because that’s definitely smog! The northern extent of that large area of smog is the Beijing metropolitan area.

What is most cough- and barf- inducing about that smog near Beijing is that it is thick enough to completely obscure the view of the surface. Last time we looked at that, it was record levels of smog that was receiving international attention. The thick, surface obscuring smog you see here isn’t record breaking or news-worthy – it’s simply a normal late fall day in eastern China!

If you can’t think of anything else to be thankful for on Thursday, you can be thankful that you don’t have to breathe air like that. Unless you live there. But, then, you wouldn’t be celebrating Thanksgiving anyway. And, if you live in Canada, you already had your Thanksgiving. You get to just sit back, relax, and watch Americans trample each other to death for discount electronics. Being able to avoid the Black Friday mob is something to be truly thankful for!

Chinese Super-Smog

No, not a Super-Smörg, super smog. Smog that is so thick, you can taste it. The smog in many parts of eastern China has been so bad this winter, it is literally “off-the-charts“. Based on our Environmental Protection Agency‘s not-very-intuitive Air Quality Index (see pages 13-16, in particular) any value above 300 is hazardous to everyone’s health. The scale doesn’t even go above 500 because the expectation is that the air could never get that polluted. Applying this scale to the air in Beijing, the local U.S. Embassy reported an Air Quality Index value of 755 on 13 January 2013. Visibility has been reduced to 100 m at times. This video (from 31 January 2013) gives a vivid description of the problems of the smog:

If that wasn’t bad enough, here’s video from NBC News where Brian Williams reveals a factory was on fire for three hours before anyone noticed because the smog was so thick!

Did you happen to notice in the beginning of the NBC video that the “air pollution is so bad that the thick smog can now be seen from space”? Of course, the satellite image shown in that clip came from MODIS. (It must have friends in high places. That, or people get the MODIS images out on their blogs less than two weeks after the event occurred, unlike this blog.) Needless to say, VIIRS has seen the smog, too, and it is terrible.

For comparison purposes, here’s what a clean air day looks like over eastern China:

VIIRS "true color" RGB composite of channels M-03, M-04 and M-05, taken 05:21 UTC 28 September 2012

VIIRS "true color" RGB composite of channels M-03, M-04 and M-05, taken 05:21 UTC 28 September 2012

This is a “true color” composite taken 05:21 UTC 28 September 2012. (As always, click on the image, then on the “2040×1552” link below the banner to see the full resolution image.) There appears to be some air pollution in that image (look near 33° N latitude between 112° and 116° E longitude), but it’s not that noticeable.

Here’s what it looks like when Beijing is reporting record levels of air pollution (04:56 UTC 14 January 2013):

VIIRS true color RGB composite of channels M-03, M-04 and M-05, taken 04:56 UTC 14 January 2013

VIIRS true color RGB composite of channels M-03, M-04 and M-05, taken 04:56 UTC 14 January 2013

You may have heard of a “brown cloud of pollution“. Here the clouds actually appear brown thanks to all that pollution. Notice the area around Shijiazhuang – the most polluted city in China – and how brown those clouds are in comparison to the clouds on the left and right edges of the image. Then look south from Shijiazhuang to where everything south and west of the cloud bank has a dull gray color. That is all smog! It’s enough to make anyone with a respiratory condition want to cough up a lung just from seeing this.

Now, this is a complicated scene with clouds, snow, ice and smog. So, to clear things up (in a manner of speaking), here is the same image with everything labelled:

VIIRS true color RGB composite of channels M-03, M-04, and M-05, taken 04:56 UTC 14 January 2013

VIIRS true color RGB composite of channels M-03, M-04, and M-05, taken 04:56 UTC 14 January 2013

The gray smog can be seen around Beijing as well, but it pales in comparison to the rest of eastern China. Think about that! Replay the videos above and consider that might not have even been the worst smog in China at the time!

Too bad there are a lot of clouds over the area. What does it look like on a “clearer” day? (“Clearer”, of course, refers to the amount of clouds, not air pollution.) It looks worse! The image below was taken at 04:32 UTC on 26 January 2013:

VIIRS true color RGB composite of VIIRS channels M-03, M-04, and M-05, taken 04:32 UTC 26 January 2013

VIIRS true color RGB composite of VIIRS channels M-03, M-04, and M-05, taken 04:32 UTC 26 January 2013

The area covered by smog rivals the area of South Korea, which is visible on the right side of the image. (One of the reports I linked to above put the figure at 1/7th of the land area of China covered by smog around this time, which is actually a lot bigger than South Korea!) I’m just counting the smog in the image that is thick enough to completely obscure the surface. There is likely smog that isn’t as obvious (and isn’t labelled) in that image. The snow between Shijiazhuang, Tianjin and Beijing is covered by smog that isn’t quite thick enough to totally obscure it. And the large area of snow south of Tianjin is likely covered with smog. (It sure is a lot dirtier in appearance than the snow near the top of the image.)

If you don’t believe my labels, the “pseudo-true color” or “natural color” RGB composite clearly identifies the low clouds (which usually appear a dirty, off-white color even without smog), ice clouds (pale cyan) and snow (vivid cyan):

VIIRS false color RGB composite of channels M-05, M-07 and M-10 (a.k.a. "natural color"), taken 04:32 UTC 26 January 2013

VIIRS false color RGB composite of channels M-05, M-07 and M-10 (a.k.a. "natural color"), taken 04:32 UTC 26 January 2013

Notice the smog in this image. It is an unholy grayish-greenish color with a value near 70-105-93 in R-G-B color space. The “natural color” composite is made from channels M-05 (0.67 µm, blue), M-07 (0.87 µm, green) and M-10 (1.61 µm, red), which are longer wavelengths than their “true color” counterparts. Longer wavelengths mean reduced scattering by atmospheric aerosols, so the higher green value may be due to the strong surface vegetation signal in M-07 being able to penetrate through the smog. (Either that or the smog is composed of some chemical compound that has a higher reflectivity value in M-07 than in the other two channels.)

I’ve looked at the EUMETSAT Dust, Daytime Microphysics and Nighttime Microphysics/Fog RGBs, which you might think would show super-thick smog and they don’t. At least, it’s not obvious.

The EUMESAT Dust RGB applied to VIIRS, valid 04:32 UTC 26 January 2013

The EUMESAT Dust RGB applied to VIIRS, valid 04:32 UTC 26 January 2013

The Dust RGB above uses M-14 (8.55 µm), M-15 (10.7 µm) and M-16 (12.0 µm) and requires there to be a large temperature contrast between the dust (cool) and the background surface (hot). Smog almost always occurs when there is a temperature inversion (the air at the ground is colder than the air above) so the necessary temperature contrast won’t exist.

The Daytime Microphysics RGB shows the smoggy areas are a slightly different color than other cloud-free surfaces, but that color can be confused with other non-smoggy surfaces. The clouds really stand out, though:

The EUMETSAT Daytime Microphysics RGB applied to VIIRS, valid 04:32 UTC 26 January 2013

The EUMETSAT Daytime Microphysics RGB applied to VIIRS, valid 04:32 UTC 26 January 2013

Perhaps, with a different scaling, the smog might stand out more.

The Nighttime Microphysics RGB from the night before (18:50 UTC 25 January 2013) is interesting. Notice the cloud identified by the letter “B” and the non-cloud next to it, “A”:

The EUMETSAT Nighttime Microphysics/Fog RGB applied to VIIRS, valid 18:50 UTC 25 January 2013

The EUMETSAT Nighttime Microphysics/Fog RGB applied to VIIRS, valid 18:50 UTC 25 January 2013

Now compare this with the Day/Night Band image from the same time:

VIIRS Day/Night Band image of eastern China, taken 18:50 UTC 25 January 2013

VIIRS Day/Night Band image of eastern China, taken 18:50 UTC 25 January 2013

This was a day before full moon. Thanks to the moon, clouds, snow and smog are visible in addition to the city lights. Points “A” and “B” have nearly identical brightness in the Day/Night Band, but only “B” shows up as a cloud in the Nighttime Microphysics RGB. These lighter areas around “A” and “B” are partially obscuring city lights, indicating “B” is a cloud, while “A” is smog. (If either was snow, you’d be able to see the city lights more clearly. See the lighter area northwest of Beijing, which is snow.)

Nothing sees super-smog like the true color composite, but the Day/Night Band will see it as long as there is enough moonlight. Smog as optically thick as a cloud… *hacking cough* … Yuck!