1 00:00:05,670 --> 00:00:03,110 computer models of earth's atmosphere 2 00:00:08,390 --> 00:00:05,680 can tell us a lot trained on how the 3 00:00:10,549 --> 00:00:08,400 atmosphere typically operates the models 4 00:00:12,870 --> 00:00:10,559 take in data about temperature wind 5 00:00:14,910 --> 00:00:12,880 speed humidity and more to give us 6 00:00:17,750 --> 00:00:14,920 important insights into the world around 7 00:00:19,910 --> 00:00:17,760 us computer models like nasa's geos 8 00:00:21,670 --> 00:00:19,920 model can help us study how chemicals 9 00:00:24,150 --> 00:00:21,680 move through the atmosphere how the 10 00:00:27,269 --> 00:00:24,160 oceans circulate and where air quality 11 00:00:29,429 --> 00:00:27,279 might be affected by fires and pollution 12 00:00:31,429 --> 00:00:29,439 these models can also provide a look at 13 00:00:33,750 --> 00:00:31,439 what might have been if circumstances 14 00:00:35,670 --> 00:00:33,760 were different for instance climate 15 00:00:37,430 --> 00:00:35,680 models can forecast how temperatures 16 00:00:39,590 --> 00:00:37,440 might change with different levels of 17 00:00:42,069 --> 00:00:39,600 carbon emissions 18 00:00:44,950 --> 00:00:42,079 in 2020 the world through the models a 19 00:00:48,069 --> 00:00:44,960 new test when people began behaving very 20 00:00:50,630 --> 00:00:48,079 very differently with almost no warning 21 00:00:52,950 --> 00:00:50,640 a global pandemic set in 22 00:00:55,350 --> 00:00:52,960 around the globe people stopped driving 23 00:00:57,350 --> 00:00:55,360 and flying in large numbers started 24 00:00:59,830 --> 00:00:57,360 staying home and completely changed 25 00:01:02,549 --> 00:00:59,840 their pollution patterns in particular 26 00:01:04,950 --> 00:01:02,559 emissions of nitrogen dioxide a common 27 00:01:07,030 --> 00:01:04,960 air pollutant released by cars airplanes 28 00:01:08,550 --> 00:01:07,040 and many factories declined 29 00:01:10,870 --> 00:01:08,560 significantly 30 00:01:12,870 --> 00:01:10,880 but just how much did the shutdown 31 00:01:15,270 --> 00:01:12,880 change our emissions 32 00:01:17,670 --> 00:01:15,280 nasa's geos atmospheric composition 33 00:01:19,990 --> 00:01:17,680 model offers an answer 34 00:01:22,710 --> 00:01:20,000 the model run functions by assuming that 35 00:01:24,630 --> 00:01:22,720 nothing was different in 2020 the people 36 00:01:26,149 --> 00:01:24,640 continued behaving roughly the same as 37 00:01:28,149 --> 00:01:26,159 they would have with no activity 38 00:01:30,710 --> 00:01:28,159 shutdowns adding the same number of 39 00:01:33,590 --> 00:01:30,720 atmospheric pollutants to the air 40 00:01:35,990 --> 00:01:33,600 it's then a matter of subtraction 41 00:01:37,990 --> 00:01:36,000 comparing those models to real-world 42 00:01:40,310 --> 00:01:38,000 observations made by satellites during 43 00:01:42,310 --> 00:01:40,320 the shutdowns shows how significant the 44 00:01:43,670 --> 00:01:42,320 decrease in pollution was in various 45 00:01:46,069 --> 00:01:43,680 cities 46 00:01:49,350 --> 00:01:46,079 activity shutdowns started in wuhan 47 00:01:51,749 --> 00:01:49,360 china and in january observed emissions 48 00:01:54,230 --> 00:01:51,759 of nitrogen dioxide began to diverge 49 00:01:57,030 --> 00:01:54,240 from what models predicted about 60 50 00:01:59,109 --> 00:01:57,040 percent less than predicted that is as 51 00:02:01,590 --> 00:01:59,119 the virus and the associated shutdowns 52 00:02:03,670 --> 00:02:01,600 moved west european cities began to 53 00:02:05,830 --> 00:02:03,680 experience decreased levels of nitrogen 54 00:02:07,429 --> 00:02:05,840 dioxide emissions as well 55 00:02:10,150 --> 00:02:07,439 in madrid spain 56 00:02:13,430 --> 00:02:10,160 nitrogen dioxide emissions were also 60 57 00:02:15,589 --> 00:02:13,440 percent less than modeled 58 00:02:18,150 --> 00:02:15,599 shortly after cities in the united 59 00:02:20,949 --> 00:02:18,160 states began to follow suit 60 00:02:22,949 --> 00:02:20,959 in march new york city shut down all but 61 00:02:25,670 --> 00:02:22,959 essential activities and emissions 62 00:02:28,949 --> 00:02:25,680 dropped by 45 63 00:02:31,509 --> 00:02:28,959 50 of the 61 analyzed cities show 64 00:02:33,110 --> 00:02:31,519 nitrogen dioxide reductions between 20 65 00:02:35,589 --> 00:02:33,120 and 50 percent 66 00:02:37,910 --> 00:02:35,599 clearly linking lower no2 emissions to 67 00:02:39,910 --> 00:02:37,920 pandemic-related restrictions and 68 00:02:42,309 --> 00:02:39,920 therefore human activity 69 00:02:43,990 --> 00:02:42,319 this sudden change in human behavior 70 00:02:45,990 --> 00:02:44,000 gives us new insights into the 71 00:02:47,430 --> 00:02:46,000 relationship between human activities 72 00:02:49,589 --> 00:02:47,440 and air pollution 73 00:02:51,750 --> 00:02:49,599 which still has many unanswered 74 00:02:53,990 --> 00:02:51,760 scientific questions 75 00:02:56,229 --> 00:02:54,000 the only way we can fully understand air 76 00:02:58,790 --> 00:02:56,239 pollution is by combining surface 77 00:02:59,830 --> 00:02:58,800 observations satellite data and computer 78 00:03:02,149 --> 00:02:59,840 models 79 00:03:04,869 --> 00:03:02,159 with nasa's satellite monitoring system 80 00:03:06,470 --> 00:03:04,879 and computing capabilities it's uniquely 81 00:03:08,869 --> 00:03:06,480 positioned to provide detailed 82 00:03:10,310 --> 00:03:08,879 information about air quality everywhere