Peak Streamflow Increasing in Missouri

Missouri and other parts of the Midwest are experiencing severe flooding, perhaps historic flooding. The record flood in this part of the country occurred in 1993. According to Chris Boerm, transportation manager for Archer Daniels Midland, the 1993 flood was concentrated in Iowa and the upper Midwest. This one is more expansive, affecting the entire Mississippi River, the Arkansas River, the Illinois River, the Ohio River, and the Missouri River. (quoted in Sullivan, Singh, and Bloomberg, 2019). Some 203 river gages along U.S. rivers are at or above flood stage.

With every flood, it seems, we hear a chorus complaining that flooding is getting more severe, and that our efforts to manage our major rivers have actually made things worse. Flood plains upstream act as sponges, absorbing flood water and then releasing it slowly over time, thus reducing the severity of flooding downstream. But levees along the river prevent this from happening, funneling all of the water downstream, worsening flooding there.

I thought I would look and see if, indeed, there is a trend towards increased flooding, and if so, how severe it was.

First I decided that I would focus only on Missouri. Then I decided that I would focus only on select rivers that represented diverse geographical areas of the state. Then I decided I would focus only on rivers that were relatively major rivers. And finally, I decided that I would eliminate rivers that I felt were almost entirely controlled by dams. The White River, for instance, is one our longer rivers, though it only flows through Missouri for part of its length. While in Missouri, it is impounded by 3 reservoirs: Table Rock Lake, Lake Tanneycomo, and Bull Shoals Lake. So, I eliminated it, and other similar rivers. I did not, however, eliminate the Missouri and the Mississippi. Though those rivers are regulated by dams and impounded into reservoirs, their many floods indicate that they are not almost entirely controlled by anything.

Figure 1. Location of USGS river gages. Source: USGS Mapper.

But how to measure flooding? I decided to use two measurements routinely made by the United States Geological Survey at thousands of river gages, which cover every major river in the country: peak streamflow, and peak gage height. Peak streamflow is the highest amount of water flowing down the river at any given time during a water year (water years begin in the summer). Peak gage height represents the highest the river is during a water year. These two measurements are not specific indicators of flooding. However, high readings go along with flooding, and if these two measurements are increasing, it would provide support for the idea that floods are getting worse.

Figure 1 shows a map of the river gages I selected for my study. They included gages on the Mississippi River at Grafton and at Thebes, a gage on the Missouri River at Kansas City, gages on the Meramec River near Steelville and near Eureka, a gage on the Gasconade River at Jerome, a gage on the Grand River at Sumner, a gage on the Pomme de Terre River at Polk, and a gage on the Current River at Van Buren.

Each gage has historical data for peak streamflow and peak gage height for each water year. How far back the data goes varies between gages. I turned this data into graphs, shown as Figures 2-10. For each graph, streamflow is shown in orange, and should be read against the left vertical axis. Gage hight is shown in blue, and should be read against the right vertical axis. I had Excel drop linear regressions on each of the lines, to show the trend over time. They are shown as dotted lines. I will discuss the results after sharing the charts.

(To view a chart, click on it. Once a chart is open, you may cycle through the charts by using the buttons below the charts. To return to this post from the charts, click on the name of the post under the chart.)

As one considers the charts as a group, the most obvious thing that jumps out is the large variation in streamflow from year-to-year. This is particularly evident on smaller streams that don’t gather precipitation from large drainage areas. The Grand River, for instance, had a minimum streamflow of 6,320 cfs in 2003, but a maximum streamflow of 180,000 cfs in 1947. The maximum streamflow was more than 28 times the minimum. However, even on the big rivers the yearly variation was large: on the Mississippi River at Thebes, the minimum was 140,000 cfs in 1934, while the maximum was 1,050,000 in 2016 (7.6 times the minimum).

There are 18 trend lines: 2 lines for each of 9 gage locations. All but 1 show an increasing trend over time. The only trend that isn’t upward is streamflow on the Meramec River near Steelville. I’m not sure what this means, as the gage height there does trend up, and both streamflow and gage height on the Meramec near Eureka also trend up. Eureka is downriver from Steelville. This one finding notwithstanding, with 17 out of 18 trending upward, I think it is safe to say that both streamflow and gage height have been increasing over time in Missouri.

Don’t read too much into the steepness of the different trendlines, they are determined by the scales Excel chose for the vertical axes.

At each location peak streamflow and peak gage height tend to vary within a limited range, but this range is broken in some years by extremes. Even high values in the normal range may go along with flooding in some locations, but the extremes probably indicate more severe flooding. If there is an upward trend in the normal range, it may indicate a trend toward increased minor flooding. But if there is an increase in the extremes, it may indicate that extreme flooding is getting even more extreme. And that is what we find. On most of the charts, the extreme peaks on the right are taller than the extremes on the left.

Put this together with increased development in flood plains, and yikes! The levees better hold!

The trend is not universal, however, and one of the locations that turned out to be more complex was the Missouri River at Kansas City. The highest streamflow there occurred in 1951, and streamflows since then (even in 1993) were lower. Gage height, however, peaked in 1993. The series of dams on the Missouri River were completed in 1962, and they may have moderated streamflow since then. (Although when flooding is extreme, the dams have to dump water to prevent themselves from being overtopped, and that can make things worse. See my posts on Oroville Dam.)

(Added note 6/27/19: This may actually be an effect of levee building. Levees constrict the width of the river during high water. If the river width is sufficiently narrowed, the gage level might be considerably higher, but the river might still be carrying less water.)

So, it was a lot of work to find this data and put these charts together. But they do tend to support the notion that the peak streamflow and the peak level of Missouri’s rivers are increasing over time, and that the severity of especially severe events is, too. I have heard this trend attributed to both levee building and climate change, but this data does not speak to causation.


Sullivan, Brian K., Shruti Date Singh, and Mario Parker Bloomberg. 2019. “Hundreds of Barges Stalled as Floods Hider Midwest Supplies.” St. Louis Post Dispatch, 6/10/2019. Viewed online 6/10/2019 at

United States Geological Survey. National Water Information System: Mapper. I used the map to select the river gages for this article 6/10/2019 at

United States Geological Survey. Peak Streamflow for the Nation. This is a data portal. I downloaded the data for the 9 river gages in this article on 6/10/2019 from

Births and Birth Rate Decline in 2018

Figure 1. Source: Hamilton, Martin, Osterman, and Rossen, 2019.

In 2018, 3,788,235 live births occurred in the United States, according to the Bureau of Vital Statistics. That is down from 3,855,500 in 2017, a decline of 2%. Figure 1 shows the trend in the data from 1990 to 2018. The number of births is the blue line, and it should be read against the left vertical axis. The fertility rate (the number of births per 1,000 women of child-bearing age) is shown as a green line, and it should be read against the right vertical axis.

The chart shows that both declined through 1997, then rose from 1997 to 2008, then began declining again. Overall, births have declined a little more than 10% since 1990. The fertility rate has declined by about 15% since then.

Every person in this world has an environmental footprint; we consume resources and create pollution. You can reduce the average environmental footprint, but you can’t eliminate it. The United States has the 7th highest per capita environmental footprint in the world, outranked only by Qatar, Luxembourg, the United Arab Emirates, Bahrain, Kuwait, and Trinidad and Tobago. Thus, the population of the United States is very important environmentally.

Figure 2. Data source: Missouri Information for Community Assessment.

According to the report, the number of births in Missouri in 2018 was 73,222. The report does not contain historical data for individual states, but data for 1990-2017 can be found on MICA, the Missouri Information for Community Assessment database. In Figure 2, the blue line represents the number of births, and it should be read against the left vertical axis. The MICA data does not include 2018, that has been added from the CDC report. The red line represents the fertility rate, and should be read against the right vertical axis.

The series are very similar, and they parallel the general shape of the data for the whole United States: the number of births and birth rate fell during the 1990s, then rose until around 2007, and have fallen since then.

Comparing the national fertility rate to that in Missouri, it appears that in 2017, the last year for which data was available in both jurisdictions, the national birth rate was just over 60 births per 1,000, while in Missouri it was 62. That doesn’t seem like a big difference, but multiplied over millions of people, it is substantial.

The report contains additional data regarding the race and ethnicity of the mothers giving birth, their age (teen births are a particular concern) and other characteristics.


Global Footprint Network. Compare Countries. Data portal. Data for  2016 for “ecological footprint (gha per person).” Viewed online 6/7/2019 at

Hamilton BE, Martin JA, Osterman MJK, Rossen LM. Births: Provisional data for 2018. Vital Statistics Rapid Release; no 7. Hyattsville, MD: National Center for Health Statistics. May 2019.

Missouri data generated 5/18/2019 on the Missouri Information for Community Assessment database (MICA):

Fire and the Regeneration of Aspen Trees

Figure 1. Regeneration after the Red Eagle Fire in Glacier National Park. Photo: John May.

After returning from a trip to several national parks in 2016, I wrote a series of posts on wildfire, and the role wildfire has in keeping forests healthy. (See here.) In those posts, I reported that wildfire was essential for regenerating species of conifer that have serotenous cones. The cones of these species are coated with a waxy resin that prevents them from opening and releasing their seeds. Fire must melt the resin, and only then are the seeds released – millions of them. Thus, after a fire, the forest regenerates with thousands-upon-thousands of saplings, all the same age. Figure 1 shows the forest regenerating after the Red Eagle Fire near Glacier National Park. These are lodgepole pine, the dominant species in the forests of that area.

I also wrote that aspen trees require fire to regenerate. After a few decades, stands of aspen are invaded by conifers. Aspens are not shade tolerant, and they are not long-lived. Because the conifers create too much shade, the aspens cannot regenerate, and the stand dies out. Fire clears away the shade, and the aspen rhizomes, which remain beneath the ground, send up new shoots, and the aspen stand can be regenerated.

Figure 1. Effects of the Warm Fire (2006) in Kaibab National Forest. Photo by John May.

I just returned from the North Rim of the Grand Canyon. In 2006, the Warm Fire (what a name for a wildfire!) burned across Arizona Hwy. 67, the route to the North Rim. Figures 2, 3, and 4 show the scene. The Red Eagle Fire and the Warm Fire both occurred in 2006, but what has happened since is very different. The scene of the Red Eagle Fire is covered in thousands of small lodgepole pines, all the same age. The scene of the Warm Fire has nary a conifer to be seen. These are all aspens. They haven’t leafed-out yet, so they are a little difficult to see. Aspens turn brilliant colors in the fall – imagine what this area will look like when these trees are mature.




Figure 2. Effects of the Warm Fire (2006) in Kaibab National Forest. Photo by John May.

To my eye, the area burned by the Warm Fire looks blasted in a way that the area burned by the Red Eagle Fire does not. The reasons might include higher altitude, a more arid climate, and a hotter fire that sterilized the ground. But in addition, this is usually a mixed conifer forest. These species are less tolerant of full sunlight than are the aspens. Thus, the aspens recolonize the burned areas more quickly.







Figure 3. Effects of the Warm Fire (2006) in Kaibab National Forest. Photo by John May.

Eventually, an interesting thing will occur: the aspens will provide the light shade that the conifers need, and they will be able to start growing. In time, they will begin to shade out the aspens, which will die out, and there will be no more aspens until once again the area burns in a fire. Nature has her ways.







Figure 5. Warm Fire Progression Map. Source: United States Forest Service, 2006.

The Warm Fire was started in the Kaibab National Forest by lightning on 6/6/2006. At first, it was judged to be a small fire of low intensity that could be allowed to burn and would help renew the forest. In its first 10 days, it burned 1,049 acres.

After 2-1/2 weeks, however, suddenly it blew up into a very hot, rapidly-spreading fire. Between 6/23 and 7/4 it burned about 43,000 acres. Figure 5 shows the fire map through 6/27, but the fire wasn’t contained until 7/4.


United States Forest Service. Warm Fire Recovery Project. Viewed online 5/27/2019 at

United States Forest Service. Warm Fire Progression Map. Downloaded 5/27/2019 from

On a Break

Though I didn’t originally want to, I’m going to have to put MoGreenStats on a break until mid-June. I’m traveling, and while I hoped to be able to write as I travelled, I’m moving each day. I don’t have the chance to research an environmental report and write a post on it.

I will return home in June, and I should be able to have a new post prepared shortly after. Until then, be well.


No Decline in Missouri Crop Yields (Yet)

There have been some recent articles about how climate change is harming agriculture. One by Kim Severson in the New York Times (here) says “Drop a pin anywhere on a map of the United States and you’ll find disruption in the fields.” It goes on to discuss the impacts on “11 everyday foods”: tart cherries (Michigan), organic raspberries (New York), watermelons (Florida), chickpeas (Montana), wild blueberries (Maine), organic heirloom popcorn (Iowa), peaches (Georgia and South Carolina), organic apples (Washington), golden kiwi fruit (Texas), artichokes (California), and rice (Arkansas).

Well, that is a sampling of foods from around the country. I’m not so sure how “everyday” many of them are, but rice is certainly one of the basic grains.

A somewhat more convincing article by Chris McGreal in The Guardian interviewed farmers in valley of the Missouri River near Langdon, in northwestern Missouri. These are corn and soybean farmers. Their problem has been moisture: they have had too much rain. In many years, the ground has been so muddy that crops were ruined or not planted at all. In other years, the rain has caused the water table to rise so much that the ground looks dry on top, but is mucky mud just a few inches down. This is something, of course, that would affect river valleys the most, and the big river valleys in Missouri are some of the richest farmland the state has.

Figure 1. Data source: National Agriculture Statistics Service, USDA.

Most climate change studies project that climate change will impact agriculture negatively. Given this blog’s focus on the large statistical perspective, I thought it might be interesting to see how crop yields are doing in Missouri. The United States Department of Agriculture publishes the data. This data is a statistical average of yields across Missouri. Results in any one location may be different.

Figure 1 shows the per-acre yield for corn. The data shows that corn yields vary significantly from year-to-year, and that some years are really terrible, with yields being roughly half of what they are in good years. That said, there is a clear trend toward increased yields from 1957 right through 2014. Yields since then have been lower, and it is possible that we are looking at the start of a downward trend, but 4 years is not sufficient to tell.

Figure 2. Data source: National Agricultural Statistics Service, USDA.

Figure 2 shows the per-acre yield for soybeans. The yearly variation here may be somewhat less, but the overall pattern is much the same. With soybeans, however, yields increased right through 2017.

This data doesn’t tell us why crop yields are rising. Perhaps they are due to improved farming practices and better seed stock. It is possible that warmer temperatures, an increase in carbon dioxide, and more rain have benefitted crop yields overall, even if they have hurt some farmers in some locations. We just don’t know, at least not from this data.

What we do know is that, overall, the predicted negative effects of climate change do not yet seem to be reducing yields in these two important crops.


McGreal, Chris. 2018. “As Climate Change Bites in America’s Midwest, Farmers Are Desperate to Ring the Alarm.” The Guardian,” 12/12/2018. Viewed online 5/1/2018 at

Severson, Kim. 2019. “From Apples to Popcorn, Climate Change Is Altering the Foods America Grows.” The New York Times, 4/30/2019. Viewed online 5/1/2019 at

National Agriculture Statistics Service, United States Department of Agriculture. Quick Stats. This is a data portal that can be used to build a customized report. I focused on yield, in bushels per acre, for corn and soybeans from 1957-2018. Data downloaded 5/1/2019 from

Missouri Has A Big, Unused Wind Resource

Figure 1. Source: Department of Energy.

Missouri is blessed with a significant wind energy resource, less than 1% of which is being exploited, according to data from the United States Department of Energy. In all of the following data, the speed of the wind has been measured at 80 meters above the ground, the typical tower height of a wind turbine.

Figure 1 shows the potential wind capacity of the United States by state. Texas has more wind potential than any other state, at 1.3 million megawatts. Missouri ranks 16th in most potential, with 279,000 megawatts.





Figure 2. The map shows the estimated mean annual wind speeds at an 80-m height (262 feet). Source: Department of Energy.

Figure 2 shows where Missouri’s wind resource is located. According to the Department of Energy, an average annual wind speed of 6.0 meters per second is required to constitute a viable wind resource. On the map at right red represents average annual wind speeds of 7 – 7.5 meters/second, or about 16 mph, while orange represents average annual wind speeds of 6.5 – 7 meters/second. Missouri’s wind resource is located in a broad arc across the northern and western portions of the state.







Figure 3. Source: Department of Energy.

Figure 3 shows installed wind power capacity by state. Texas again leads the way, with 24,899 megawatts of installed capacity. Iowa is second with 8,422 megawatts, and California is third with 5,885 megawatts. Missouri has 959 megawatts of installed capacity; that equals about 0.3% of our wind power potential.








Figure 4. Source: United States Geological Survey.

Figure 4 shows the location of wind turbines installed in Missouri. You can see that they are all located in the northwest quadrant of the state.











Figure 5. Source: Department of Energy.

Figure 5 shows the energy mix on the electrical grid in Missouri. About 73% of our electricity is generated by burning coal, about 13% is generated in a nuclear plant, only 8% is generated from natural gas, and only 3.58% from wind power. Given that wind power represents 3+% of our energy mix, but only 0.3% of our wind power potential, Missouri could generate much more of its electricity using wind power.

Figure 5 also shows the amount of electricity generated by wind power in Missouri by year. You can see that between 2008 and 2012 it grew, but then it plateaued until 2016, and has grown since then.

Climate change presents many challenges. Among the largest is transitioning to energy resources that don’t release carbon dioxide. The data above shows that Missouri has significant potential, but we have only begun to exploit it.


United States Department of Energy. 2019. Wind Energy in Missouri. Downloaded 4/22/2019 from

United States Geological Service. 2018. The U.S. Wind Turbine Database. Downloaded 4/22/2019 from

Missouri Weather-Related Deaths, Injuries, and Damages in 2017

Figure 1. Data source: Office of Climate, Water, and Weather Services, National Weather Service.

Damage from severe weather in Missouri shows a different pattern than does damage nationwide. As Figure 1 shows, the cost of damage from hazardous weather events in Missouri spiked in 2007, then spiked even higher in 2011. Since then, it has returned to a comparatively low level. The bulk of the damage in 2011 was from 2 tornado outbreaks. One hit the St. Louis area, damaging Lambert Field. The second devastated Joplin, killing 158, injuring 1,150, and causing damage estimated at $2.8 billion. The damages in 2007 came primarily from two winter storms, one early in the year, one late. In both cases, hundreds of thousands were without power, and traffic accidents spiked.



Office of Climate, Water, and Weather Services, National Weather Service.

Figure 2 shows deaths and injuries in Missouri from hazardous weather. Deaths are in blue and should be read on the left vertical axis. Injuries are in red and should be read on the right vertical axis. The large number of injuries and deaths in 2011 were primarily from the Joplin tornado. In 2006 and 2007, injuries spiked, but fatalities did not. The injuries mostly represented non-fatal auto accidents from winter ice storms. The fatalities in 1999 resulted from a tornado outbreak.

I understand the trends in both figures this way: once in a while, Missouri has been struck with catastrophic weather events. They cause lots of deaths and a lot of damage, at a whole different scale from years with no catastrophic weather event. In years with no such event, weather-related deaths in Missouri have been around 40 or fewer, and injuries have been roughly 400 or fewer. Damages in such years have been about $150 million or less. In years with catastrophic weather events, the totals can be much higher.

2017 was a year in which Missouri saw no weather disasters that caused such high damages, or killed or injured so many people. That does not mean that Missouri was unaffected, however. The state was included in several billion-dollar weather disasters, the most costly of which was probably the flood of April 25-May 7. That was a historic flood for many of the communities that were affected.

The Missouri data covers fewer years than the national data discussed in my previous post. It also covers all hazardous weather, in contrast to the national data, which covered billion dollar weather disasters only. In addition, for some reason the Missouri data for 2018 has not yet been posted.

While the national data shows a clear trend towards more big weather disasters, Missouri’s data does not. The Missouri data seems to reflect the kind of disaster and where it occurred. Tornadoes, if they hit developed areas, cause injuries, deaths, and lots of damage. Floods cause fewer injuries and deaths; damage can be significant, but it is limited to the floodplain of the river that flooded. Ice storms affect widespread areas; damages come mostly through loss of the electrical grid, which can cause widespread economic loss and from car crashes, which cause many injuries but fewer deaths.


Office of Climate, Water, and Weather Services, National Weather Service. 2016. Natural Hazard Statistics. Data for Missouri downloaded at various dates from

CPI inflation Calculator. 2019. 2017 CPI and Inflation Rate for the United States. Data downloaded 4/6/2019 from
National Centers for Environmental Information. 2019. Billion-Dollar Weather and Climate Disasters: Table of Events. Viewed online 4/6/2019 at

Descriptions of specific weather events, if they are large and significant, can be found on the websites of the Federal Emergency Management Administration, the Missouri State Emergency Management Agency, and local weather forecast offices. However, in my experience, the best descriptions are often on Wikipedia.

Natural Disasters Down in USA in 2018

The number of natural disasters in the USA in 2018 declined from 2017, and the amount of damage they did also declined.

Figure 1. Source: National Centers for Environmental Information, 2019.

Since 1980, there have been 241 severe weather and/or climate events in the USA that have caused damages exceeding $1.6 trillion dollars. The most important of these are the “billion-dollar disasters,” events that caused damages in excess of $1 billion. Figure 1 shows the data. The columns represent the number of events, with each color representing a different type of event. The black line represents a moving 5-year average number of events. They gray line represents the cost of damages, in billions of dollars.

In 2018, there were 14 billion-dollar disasters. That is more than double the long-term average. The 4 years with the most billion dollar disasters have all occurred in the last 8 years, and the last 3 years have ranked #1 (tie), #3, and #4. The last 3 years have been significantly higher than any other years except 2011. The increase comes primarily from severe storms, a category that excludes hurricanes and tropical cyclones, flooding and winter storms. These are tornadoes, thunderstorms, hail, and similar kinds of storms.

The estimated CPI-adjusted losses in 2018 were $91 billion. That’s quite a chunk of change, but it much less than the costs in 2017 ($312.7 billion), 2005 ($220.8 billion), or 2012 ($128.6 billion). 2017 was a terrible year (see here): Hurricanes Harvey, Irma, and Maria struck in 2017, and not only was it far-and-away the most costly year, it also tied for the highest number of disasters. Hurricane Katrina struck in 2005, and Hurricane Sandy struck in 2012. Hurricane Katrina is still the single event that caused more damage than any other, followed by Hurricanes Harvey and Maria. Last year, the most costly natural disaster was the series of wildfires in California, especially the Camp Fire. The fires caused an estimated $24 billion in damage.

Looking at Figure 1, starting somewhere around 2005, the number of billion-dollar disasters starts to trend upward. The amount of damage does, too, though the variation from year-to-year is much greater. The National Centers for Environmental Information, which keeps this data, factors the Consumer Price Index into it, so the change is probably not due to inflation.

Three factors probably account for most of the increase. First, climate change has caused an increase in the amount of energy in the atmosphere, energy that is available to power more and bigger storms. I once calculated that the increased radiative forcing from climate change was equal to the energy output of 1.6 million nuclear power plants. (See here) That’s a lot of energy available to power storms. Second, climate change has caused an increase in droughts throughout the western United States. Even in years like this one, when there has been an abundance of winter snow, the warm temperatures cause the snow to melt earlier in the spring, and they dry out the land faster during the summer. The result is a tinder box, perfect conditions for huge wildfires. And finally, we keep putting ourselves in harm’s way. Development has increased along the Atlantic and Gulf Coasts, where it is in the path of any hurricane that comes ashore. Development has also increased along the fringes of forests, where it is vulnerable to wildfire. And even in the middle of the country, sprawl has increased the built-up area, making tornadoes more likely to grind over it, as opposed to farmland.

Missouri was in the region damaged by some of the big weather events of 2018, so the next post will look at how we fared here in the Show Me State.


The National Centers for Environmental Information Billion-Dollar Weather and Climate Disasters portal has 5 pages available, and I used them all for this post: Overview, Mapping, Time Series, Summary Stats, and Table of Events. Downloaded and viewed online 4/3/2019 at

Americans Still Think the Environment Is Worth Saving

If you listen to the national media, especially the conservative media, you might think that interest in environmental protection has gone the way of the dinosaur, swept away by a national consensus to focus on economic growth at all costs.


Figure 1. Source: Gallup Inc.

Gallup Inc. is a global analytics and analysis organization that conducts what we all know as Gallup Polls. One of the questions they regularly include in their polls is “With which one of these statements do you most agree – protection of the environment should be given priority, even at the risk of curbing economic growth (or) economic growth should be given priority, even if the environment suffers to some extent?” The results are shown in Figure 1. It is a chart from Gallup showing the percent of respondents choosing the environment over the economy, and vice-versa. To it I have added a line showing republican and democratic presidencies (red and blue, respectively).

In 1990, people chose environmental protection over economic growth 71% to 19%. That is a huge majority! Support for the environment weakened starting in 2000. By 2010, respondents chose the economy over the environment 53% to 38%. Since then, support for the environment has rebounded, with the most recent figures showing respondents picking the environment over the economy by 57% to 35%. (The percentages don’t sum to 100% because some people answer that they don’t have a preference, or they decline to answer the question.)

Even 57% to 35% is a large majority – a difference of 32%: for every 10 people who chose the economy, 17 chose the environment. No American president has ever been elected by such a margin. Warren Harding comes closest (!), with a margin of 26%. Some recent “landslides” involved margins of 23% (Nixon over McGovern, 1972, and Johnson over Goldwater, 1964). Even the famous Reagan “landslide” of 1984 (Reagan over Mondale) was only 18%. The current Tweeter-in-Chief, due to a quirk in the electoral college system, was elected with a minority of the vote (-3%).

Figure 2. Source: Gallup, Inc.

Since 1998, Gallup has also asked respondents “Is the seriousness of global warming generally exaggerated, generally correct, or is it generally underestimated?” Figure 2 shows the results. The dark green line shows the number of people who think the seriousness of global warming is exaggerated. The dark black line shows the number of people who think its seriousness is generally correctly portrayed. The gray line shows the percent of people who think it is underestimated.

A minority of people think that the seriousness of global warming is correctly represented – that is constant across the whole time period. For much of the period, more people thought its seriousness was exaggerated than thought it was underestimated. In recent years, that has shifted, and now more people think it is underestimated (41%) than think it is exaggerated (33%).

Where would I fit on that last question? I think I would refuse to answer it. I feel that global warming is one of the most significant challenges facing humanity. But I feel that it is a slow-motion catastrophe. Just as a simple example: if you go to Miami Beach or Lower Manhattan in 100 years, you are likely to find they are very different places, struggling to cope with flooding, sometimes more severe, sometimes milder. However, that is a change that will unfold over the entire coming century, giving people lots of time to adapt and adjust. Thus, those who say the danger is fabricated are underestimating it. On the other hand, those who say an existential catastrophe is imminent are exaggerating.

What is true is that the carbon that goes into the atmosphere stays there for nearly a century. Thus, if we don’t act quickly, we most likely doom ourselves to a change that will unfold over decades, and which we will be impotent to prevent.

As the two figures above illustrate, environmental concerns have NOT been swept away our current president. Rather, he is acting to prevent Americans from addressing problems that they feel are important, even if it involves some economic sacrifice.


Gallup Inc. 2018. In Depth: Topics A to Z: Environment. Downloaded 3/27/2019 from

Trends Over Time

The last 2 posts have reported specifics on some of the toxic chemicals released into the environment in Missouri in 2017. This post will broaden the view and discuss trends in toxic releases over time.

Figure 1. Source: Environmental Protection Agency, 2019b.

To some extent it is difficult to follow trends over time because of changes in the TRI program. Figure 1 shows the national trend in chemicals reported to the EPA over time, and it labels the years in which major changes have occurred in the program. The light blue and sandy yellow show the total amount of toxic chemicals reported, the dark blue and orange show the amount disposed of and released. The total amount of toxic chemicals reported to EPA peaked in 2000 and decreased until 2009, the bottom of a recession. Over that period, the amount decreased by more than 40%. Since 2009, however, the amount has increased by about 50%. The chart shows that most toxic chemicals reported to the EPA are used in manufacturing (light blue).

(Click on chart for larger view.)

It is beyond the scope of this blog to explore why toxic chemicals reported to EPA should drop so significantly, then rebound so significantly. If you know the answer, please comment on this post and let us all know.

The increase concerns me. This series of posts started with a review of several catastrophic releases of toxic chemicals that killed people and poisoned the land, in some cases permanently. Preventing the release of toxic chemicals means that no mistakes can ever be made, and that is simply not within human capability. I view toxic chemicals as similar to time bombs. Sooner or later, one will go off.

Figure 2. Source: Environmental Protection Agency, 2018.

Of course, chemicals reported to the EPA are different from releases: what about releases? Figure 2 shows on-site toxic releases in Missouri over time. Because on-site releases represent about 93% of toxic releases in Missouri, I will let this chart represent the trend in total releases. You can see that releases peaked in 2004-2005, and have been trending downward since then. In 2017 they were about 47% of those in 2005, slightly less than half.


Figure 3. Source: Environmental Protection Agency, 2019b.

Figure 3 shows the trend nationwide. The chart I have goes back only to 2007. Since then, the total amount of releases has decreased from just 4.13 billion lb. to 3.85 billion lb., a decrease of 7%.


Because Missouri has been losing manufacturing over time, the possibility exists that the decline in toxic releases comes from the decline in manufacturing. To look at this possibility, one would want to plot toxic releases against the amount of manufacturing in the state. But what is “the total amount of manufacturing” in a state? Is it the tonnage of goods produced? The economic value produced? The number of factories, or their total square footage? The number of people employed in manufacturing? I can find statistics for manufacturing employment in Missouri, so I will use it.

Figure 4. Data sources: Environmental Protection Agency, 2018; Federal Reserve Bank of St. Louis, 2019.

Figure 4 shows the trend over time for toxic releases in Missouri (the blue line, which should be read against the left vertical axis) and manufacturing employment (the red line, which should be read against the right vertical axis). The chart considers toxic releases, not toxics managed. The chart shows that toxic releases and manufacturing employment follow similar trajectories. The correlation between the 2 data series is 0.75, which is fairly high as correlations go.

Correlation, of course, proves nothing. There is a wonderful website dedicated to spurious and absurd correlations (For instance, per capita cheese consumption correlates with the number of people who die by becoming tangled in their bedsheets at 0.95. Check out But it seems logical that the decline in toxic releases could be at least partially related to the amount of manufacturing. It would be a wonderful study for some enterprising student.

As I noted in the first post in this series, interpreting data in the TRI is complex. The most serious exposures to toxic chemicals probably happen to people who work with them regularly. You can’t assume that releases translate to public exposure. But you probably can infer the inverse: unless there is a release, the public can’t be exposed. These are poisonous chemicals. Lead, the most released chemical in Missouri, persists and accumulates in the environment and in the human body. I’m thankful that toxic releases have declined in Missouri, and I hope they continue to do so.


Environmental Protection Agency. 2018. 2017 TRI Factsheet: State – Missouri. Downloaded 3/7/2019 from

Environmental Protection Agency. 2019a. Factors to Consider When Using Toxics Release Inventory Data. Downloaded 3/20/2019 from

Environmental Protection Agency. 2019b. Toxic Release Inventory: TRI National Analysis 2017. Downloaded 3/20/2019 from

Financial Reserve Bank of St. Louis. FRED Economic Data: Manufacturing Employment in Missouri. FRED is a data portal accessed 3/7/2019 at[1][id]=MOMFGN.