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Declining Snowpack in the American West


The snowpack over the western United States has declined about 23% since 1981. It is projected to decline more in the future.


I have written a number of posts about the looming water deficit in California due to a projected decline in the snowpack on the Sierra Nevada mountains. Is something similar projected to occur throughout the entire western United States?

Figure 1. Change in Snow Water Equivalent at SNOTEL Stations, 1955-2016. Source: Mote and Sharp 2016, in Environmental Protection Agency, 2016.

Yes. Studies find that the water content of the snowpack throughout the West has already declined 23%, and it is expected to decline more, perhaps up to 30% by 2038.

This decline is not occurring via a decrease in precipitation. Indeed, to date precipitation across the West has actually increased slightly. The decline is occurring due to increased temperature. Some precipitation that used to fall as snow now falls as rain, and the snow that does fall melts more quickly.

Mote and Sharp studied the snow water equivalent* of the snowpack in April from 1955-2016 at SNOWTEL measuring stations operated by the U.S. Natural Resource Conservation Service. Figure 1 shows a map of the stations, with blue dots representing stations where the snowpack increased and orange dots representing stations where the snowpack declined. The size of the dots represent the magnitude of change.

It is easy to see that the vast majority showed declines in the snowpack, in many cases by as much as 80%. Overall, Mote and Sharp computed that there had been an average 23% decline in the western snowpack since 1955.

 

Figure 2. Observed and Modeled Change in Snowpack. Source: Fyfe, et al, 2017.

Fyfe and his colleagues conducted climate modeling to try to determine whether the decline in the snowpack was due to natural causes or human causes. Figure 2 shows the results in a rather complicated graph. Let’s unpack it. The computer models ran from 1950 to 2010. The dashed black line shows the observed trend in the snow water content. The solid blue line shows the projected snow water content if only natural climate causes are included in the model. It doesn’t fit the observed trend very well. The solid black line shows the projected snow water content if both natural and human climate causes are included in the model. It fits the observed data quite closely. (The pink and green lines show data from analyses using other sets of data and need not concern us here. The gray band and blue dotted lines show statistical confidence levels for the computer simulations, and also need not concern us here.)

The simulation that included both natural and human causes agreed with the observed data, but the one that included only natural causes did not. The authors concluded that natural causes could not explain the loss of snowpack in the West. A combination of human and natural causes could explain it.

Figure 3. Projected Short-Term Change in Snowpack. Source: Fyfe, et al, 2017.

Fyfe and his colleagues also conducted a suite of climate models to project snowpack loss into the future. The results are shown in Figure 3. In this graph, the y-axis represents the actual snow water content of the snowpack, not the change. The blue line represents the computer model that projected the least snowpack loss in 2030, and the red line represents the computer model that projected the most loss. It is common practice among climate modelers to run a suite of projections, and when this is done, the average of them is often also presented, and it is often taken as likely to be the most accurate. In Figure 3, the average of the projections is represented by the black line.

It is easy to see that the trend in all of the lines is down. There is considerable variation from point-to-point in the red and blue lines, indicating that the projections expect there to be considerable variability in the snowpack from year-to-year. The black line is pretty smooth, however, as might be expected from an average of several analyses, and it has a consistent downward trend. The losses in snowpack in some of the projections ran as high as 60%, though average loss across the suite of projections was about 30%.

A 30% decline in the snowpack does not sound so dire; after all the projections are for a 60% loss of snowpack in California (see here). However, that projection was for the end of the century. This projection is for 2038; that’s only 20 years from now.

Some may wonder about how little snow water equivalent is shown on the y-axis of Figure 3. In the 1990s, the snowpack maxed-out each year at only 6+ cm. of snow water equivalent. In thinking about this number, remember two things: first, a centimeter of water represents somewhere between 3 and 20 centimeters of snow, with an average value being somewhere around 10 cm. Thus, 6 cm. of snow water equivalent would roughly equal 60 cm. of snow, or 23.6 inches. Thus, the average depth of the snowpack was about 2 feet. Second, remember that the measurements were averaged across hundreds of locations; some were high and received a great deal of snow, but some were relatively low (low altitude means more rain, less snow), or were located in areas that don’t receive much precipitation of any kind.

Much of Missouri depends on the Missouri River as a water supply, including both Kansas City and St. Louis. The Missouri River gets much of its water from the western snowpack. A declining snowpack may, or may not, have implications for our water supply, depending on whether the reservoirs along the Missouri River can accommodate the shift toward earlier snowmelt and increased rain. I will look at this issue in the next post.

*   Snow water equivalent: Different types of snow hold different amounts of water. Thus, scientists don’t just measure how deep the snow is. Rather, at a given location they take a representative sample of the snowpack and melt it, thereby determining how much water it holds. This is the snowpack’s snow water equivalent at that given location. April is generally when the snowpack is at its maximum.

Sources:

Environmental Protection Agency. 2016. Climate Change Indicators in the United States: Snowpack. Retrieved online 5/22/2017 at https://www.epa.gov/sites/production/files/2016-08/documents/print_snowpack-2016.pdf.

Fyfe, John, Chris Kerksen, Lawrence Mudryk, Gregory Flato, Benjamin Santer, Neil Swart, Noah Molotch, Xuebin Zhang, Hui Wan, Vivek Arora, John Scinocca, and Yanjun Jiao. 2017. “Large Near-Term Projected Snowpack Loss Over the Western United States.” Nature Communications, DOI: 10.1038/ncomms14996. Retrieved online 5/14/2017 at https://www.nature.com/articles/ncomms14996.

California Continues to Face Future Water Supply Challenges


Despite the wet winter in 2017, climate change will pose severe challenges to California’s future water supply.


In the last post I reported that Gov. Brown has declared California’s drought emergency officially over. The state has plenty of water for the next year. This post explores the implications of this wet winter for California’s long-term water status.

I first looked at this topic in a 13-post series that ran during the summer of 2015. The series starts here. It contains a lot of information about California’s water supply and consumption. I concluded that at some point in the not-too-distant future California would experience a significant permanent water deficit. The #1 cause of the deficit would be climate change, which is projected to result in a significant reduction in the size of California’s snowcap. The #2 cause would be population increase. I performed the analysis myself because I could find no sources that did anything similar. I’m not going to repeat that analysis in this post. Rather, I’m going to report a couple of new reports that confirm the concerns I had in 2015.

Figure 1. Source: California Dept. of Water Resources.

Figure 1 illustrates the problem California faces. Almost all of California’s precipitation falls during the winter. Some of it gets temporarily “locked up” as snowpack on the Sierra Nevada mountains. Demand for water, however, peaks during the summer. California has many man-made reservoirs that release water during the summer and fall, and the state depends on the melting snowpack to recharge the man-made reservoirs as water is drawn from them. In Figure 1, the blue line represents runoff and the red line represents water demand. You can see that moving the date of maximum runoff earlier in the year increases the amount of water that cannot be captured into storage (yellow area). It has to be dumped; see the post on Oroville Dam to see what happens if the volume of water being dumped gets too high. It increases the amount of water that must be released from storage in the summer and fall. The amount released is now larger than the amount of inflow the reservoir receives, resulting in an increased water deficit (the blue area represents water received, the green area represents water discharged equal to the size of the blue area, and the red area represents the deficit). There is a water deficit in average years, but it is small, and a winter with slightly above average precipitation can make up the deficit. Moving maximum runoff earlier in the year increases the size of the deficit; now only a much wetter year can recharge the reservoirs.

Figure 2. Source: California Dept. of Water Resources.

Figure 2 includes two charts. The first chart shows the percentage of precipitation in California that occurred as rain from 1948-2012. If precipitation occurs as rain, it is not snow and can’t add to the snowpack. On the chart, the black horizontal line is the mean percentage across all years. Red columns represent years with above average percentage of rain, the blue columns below average. There is variation between years, but you can see that the red columns cluster to the right while blue columns cluster to the left. That means that on average an increasing percentage of precipitation is falling as rain. Thus, on average, unless annual precipitation undergoes a sustained increase (which hasn’t happened and is not projected), California’s snowpack will shrink, because what once was snow is now rain.

The second chart in Figure 2 shows runoff measured on the Sacramento River. The red line represents the 50-year period from 1906-1955, while the blue line represents the 52-year period from 1956-2007. This is the specific problem that was discussed conceptually in Figure 1. You can see that runoff has moved earlier in the year by about a month.

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Figure 3. Source: National Centers for Environmental Information.

Why is more precipitation falling as rain rather than snow, and why is melt occurring earlier? Because of increased temperature. Winter is when the snow falls in California, and it is when the state receives the bulk of its precipitation. Figure 3 shows that the average winter temperature (December – March) has increased more than 2°F. In addition, if you look at Figure 3 carefully, you can see that the rate of temperature increase accelerated somewhere around 1980. The runoff chart in Figure 2 chunks the data into only 2 groups, each about 50 years long. Because of the acceleration in the increase in temperature, I believe that if they had chunked the data into 3 groups, each about 33 years long, the change towards earlier snowmelt would have been even greater than the one shown.

How dire is the threat is to California’s snowpack? It depends on which climate projection is used. The projected effects of climate change depend very much on how humankind responds to the threat. If we greatly reduce our GHG emissions immediately, the climate will warm less; if we don’t, it will warm more.

Figure 4. Source: California Dept. of Water Resources.

Figure 4 shows the historical size of the California snowpack plus 2 projections. The middle map show the projected size of the snow pack if warming is less. The map on the right shows its size if warming is more. You can see that, even under the low warming scenario, a loss of 48% of the snowpack is projected. Under the high warming scenario, a 65% loss of the snowpack is projected. These projections are for the end of the century. In my original series, I estimated the loss of snowpack at 40% by mid-century. That is not too far off from the high warming scenario. And I have to say, the evidence suggests that so far the world is operating under the high warming scenario, possibly, even worse.

Surface water is not the only source on which California depends. California withdraws significant amounts of water from underground aquifers, especially in (but not limited to) the agricultural areas of the Central Valley. Aquifers can be compared to underground lakes, but don’t think of them as being like a big, hollow cave in which there is a concentrated, pure body of water. Rather, think of them as regions of porous ground, such as gravel or sand. In between the pieces of gravel or sand is space, and that space can hold water. Below and on the sides are rocks or clay that are impervious to water, which allow the water to be held in the aquifer.

So long as the aquifer is charged with water, this is a situation that can last for thousands of years. If, however, water is pumped out without being replaced, then nothing occupies the spaces between the pieces of gravel or sand. If that occurs, the weight of the ground over the aquifer can compress the aquifer, reducing the amount of space available between the pieces of sand and gravel, reducing the capacity of the aquifer to hold water. When this occurs, it sometimes shows up as subsidence on the surface. In California, it is primarily the snowpack that feeds the aquifers. If a significant amount of the snowpack is lost, it will be less able to recharge the aquifers, and they will undergo increased compaction.

Figure 5. Map of Permanent Subsidence. Source: Smith et al, 2016.

As noted in my original series, significant subsidence has already occurred over California’s aquifers. More seems to be occurring every year. A recent study attempted to quantify the amount of water storage capacity being lost to compaction. The study covered the years 2007-2010, so it didn’t even include the recent severe drought (2007, 2008, and 2009 were dry years, but 2010 was 9th wettest in the record). The study covered only a small portion of the south end of the Central Valley Aquifer, yet it found that during those 4 years significant permanent subsidence had occurred (see Figure 5), resulting in a total loss of 748 million cubic meters of water storage, an amount roughly equal to 9% of the groundwater pumping that occurs in the study area. If this ratio held going forward, it would mean that for every 44.4 gallons of water pumped out each year, about 1 gallon of aquifer storage would be lost.

During the recent drought many newspaper articles reported that there had been a sharp increase in the number of wells being drilled in the Central Valley, and that the depth of the wells had also significantly increased. This suggests an increase in the rate at which the water table is being lowered, which would lead to an increased rate of compaction. As the study notes, this is a loss that cannot be replenished; aquifer storage lost to compaction is gone forever.

Dry periods become more devastating when they occur during hot periods. One reason the recent drought in California was so devastating was because it was a hot drought. A recent study found that climate change has already raised the temperature in the state (as in Figure 3 above), and will continue to raise it further, to the point that every dry year is likely to be a hot drought. The report concludes that anthropogenic warming has substantially increased the risk of severe impacts on human and natural systems, such as reduced snowpack, increased wildfire risk, acute water shortages, critical groundwater overdraft, and species extinction.

The bottom line here is that we are talking about the effects of climate change. Climate means average patterns over long periods of time – 30 years at minimum. The current wet period represents only 1 winter. Just as one swallow doesn’t make a summer, so one wet winter doesn’t make a climate trend. For that matter, neither do 5 dry years. However, California’s increase in temperature is a long-term change that does make a climate trend, and every indication suggests it will only increase more.

My conclusion is that this wet winter not withstanding, the concerns I voiced in 2015 over California’s water supply remain valid. As time passes, California will face increasing challenges meeting the demand for water (see here). The state will be unable to secure large new sources of surface water or ground water (see here), and will have to construct large, expensive desalination plants (see here). There will be sufficient water to supply human consumption if it is properly allocated (see here), but water available to agriculture will be reduced, resulting in a decline in California’s agricultural economy (see here). That loss, plus the cost of the desalination plants, will impact California’s economy (see here), as well as the food supply for the entire country.

[In the above paragraph I have referenced several of the posts in my 2015 series Drought in California. If you are interested in the topic, you should read the series sequentially, beginning with Drought in California Part 1: Introduction.]

Sources:

California Department of Water Resources. 2015. California Climate Science and Data for Water Resources Management. Downloaded 4/6/2017 from http://www.water.ca.gov/climatechange/docs/CA_Climate_Science_and_Data_Final_Release_June_2015.pdf.

Diffenbaugh, Noah, Daniel Swain, and Danielle Touma. 2015. “Anthropogenic Warming Has Increased Drought Risk in California.” Proceedings of the National Academy of Sciences. Downloaded 3/30/2017 from http://www.pnas.org/content/112/13/3931.

National Centers for Environmental Information. “California, Average Temperature, December-March, 1896-2016” Graph generated and downloaded 4/13/2017 at https://www.ncdc.noaa.gov/cag/time-series/us.

Smith, R.G., R. Kinght, J. Chen, J.A. Reeves, H.A. Zebker, T. Farr, and Z. Liu. 2016. “Estimating the Permanent Loss of Groundwater Storage in the Southern San Joaquin Valley, California.” Water Resources Research, American Geophysical Union. 10.1002/2016WRO19861. Downloaded 3/30/2017 from http://onlinelibrary.wiley.com/doi/10.1002/2016WR019861/full.

California Drought Emergency Officially Over

Gov. Jerry Brown officially declared California’s drought emergency over on Friday, April 7. It was a fitting ending to one of the worst episodes in California’s drought-laden history.

Or was it? The next two posts update California’s water situation. This one focuses on the current short-term situation. The next one focuses on the future, with an eye toward the future impact of climate change. I have personal reasons for following California’s water situation – I have family living there. But in addition, California is the most populous state in the Union, it has the largest economy of any state, and the state grows a ridiculously large fraction of our food. What happens in California affects us here in Missouri.

Figure 1. California Snowpack, 3/31/2017. Source: California Department of Water Resources.

Is the short-term drought truly over? Yes, I think so. The vast majority of California’s precipitation falls during the winter, and the snowpack that builds up in the Sierra Nevada Mountains serves as California’s largest “reservoir.” As it melts, it not only releases water that represents about 30% of the state’s water supply, but it also feeds water into the underground aquifers that provide groundwater to much of the state. Thus, the size of the snowpack is the most important factor in determining California’s water status. California measures the water content of the snowpack electronically and manually. The measurements around April 1 are considered the most important, as that is when the snowpack is typically at its largest. Figure 1 shows the report for this year. Statewide, the water content of the snowpack was 164% of average for the date, almost 2/3 larger than average. The water content was significantly above average in all three regions of the snowpack, North, Central, and South.

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I follow the snow report at Mammoth Mountain Ski Resort to provide a specific example of the snow conditions. Figure 2 shows that through March, Mammoth received over 500 inches of snow, one of the highest totals in the record going back to 1969-70. The column for 2016-17 has very large blue and orange sections, indicating that the majority of the snow fell in January and February. Figure 3 confirms the impression. It charts the amount of snowfall at Mammoth during each month of the 2016-17 snow season, and compares it to the average for that month across all years. You can see that both January and February were monster snow months, especially January. By March, snowfall had already fallen below average. I wouldn’t make too much of this fact, one month doesn’t make a trend.

Figure 2. Source: Mammoth Mountain Ski Resort.

Figure 3. Data source: Mammoth Mountain Ski Resort.

 

 

 

 

 

 

 

 

 

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Figure 4. Source: California Data Exchange Center.

California also stores water in man-made reservoirs. Figure 4 show the condition of 12 especially important ones on March 31. Most were above their historical average for that date, and many were approaching their maximum capacity. Those who follow this blog know that the Oroville Reservoir actually received so much water that it damaged both the main and emergency spillways, threatening collapse of the dam and requiring evacuation of thousands of people down stream. (See here.)

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Figure 5. Elevation of the Surface of Lake Mead. Source: water-data.com.

In addition, Southern California receives the lion’s share of water drawn from the Colorado River, thus the status of Lake Mead, the largest reservoir on the Colorado, is important to the state. A study in 2008 found that there was a 50% chance the reservoir would go dry by 2021. On March 31, Lake Mead was at 1088.26 feet above sea level. (This doesn’t mean there were that many feet of water in the reservoir, Hoover Dam isn’t that tall. Rather, it represents how many feet above sea level the surface of the water was. Lake Mead’s maximum depth is 532 feet.) The current level represents 41.38% of capacity. Figure 5 shows the level of the lake over time. You can see that the line tends to go up with the spring snowmelt, and down during the rest of the year. This year it is up very slightly year-over-year, but the trend has been relentlessly down since 2000.

The conclusion seems inescapable: for this year at least, California has plenty of water. The short-term drought is over. One year doesn’t make a climate trend, however. In the next post I will consider the implications of this wet winter for California’s water situation going into the future.

Sources

Barnett, Tim, and David Pierce. 2008. “When Will Lake Mead Go Dry?” Water Resources Research, 44, W03201. Retrieved online at http://www.image.ucar.edu/idag/Papers/PapersIDAGsubtask2.4/Barnett1.pdf.

CA.GOV. Governor Brown Lifts Drought Emergency, Retains Prohibition on Wasteful Practices. Viewed online 4/10/2017 at https://www.gov.ca.gov/home.php.

California Data Exchange Center. Conditions for Major Reservoirs: 31-Mar-2017. Viewed online at http://cdec.water.ca.gov/cdecapp/resapp/getResGraphsMain.action.

California Department of Water Resources. Snow Water Equivalents (inches) for 3/30/2017. Viewed online 3/31/2017 at http://cdec.water.ca.gov/cgi-progs/snowsurvey_sno/DLYSWEQ.

Mammoth Mountain Ski Resort. Snow Conditions and Weather, Extended Snow History. Data downloaded 4/2/2017 from http://www.mammothmountain.com/winter/mountain-information/mountain-information/snow-conditions-and-weather.

water-data.com. “Lake Mead Daily Lake Levels.” Downloaded 4/5/2017 from http://graphs.water-data.com/lakemead/.

Above Average Precipitation in 2016


2016 was an above average year for precipitation in Missouri and across the United States.


Source: NOAA Centers for Environmental Information.

Source: NOAA Centers for Environmental Information.

In 2016, precipitation across the Continental United States averaged 31.70 inches. That is above average, but not a record. Figure 1 shows the precipitation trend over time. The green line represents measured precipitation, the blue line represents the linear trend over time, and the black line represents the average yearly precipitation over the reference period (1901-2000). The trend suggests that precipitation is increasing, and that the United States receives, on average, about 2 inches more precipitation per year than it did in 1895.

Some parts of the country receive more precipitation, others less. In addition to the trend, we want to see is how various regions of the country fared compared to usual. Figure 2 shows 2016 precipitation anomalies for climate divisions across the Continental United States. On the map, green represents above average precipitation, while yellow, red, and purple represent below average.

Figure 2. Source: NOAA Centers for Environmental Information.

Figure 2. Source: NOAA Centers for Environmental Information.

Regions of the Pacific Northwest, Texas/Louisiana, Minnesota/Wisconsin, and the Mid-Atlantic Coast received rainfall much above average. The Mid-Atlantic Coast was impacted by 7 tropical storms (!), but none of the other regions were. Louisiana was the site of massive flooding in August that was related to an extraordinary heavy rainfall event, but not a tropical storm. (See here for my post on heavy rainfall events.)

Dry areas included Oklahoma, portions of the Northeast, and a large area centered near Atlanta, GA. This last area received as much as 18 inches of precipitation less than normal, and it has entered a drought that is graded as “Extreme” by the U.S. Drought Monitor.

Meanwhile, precipitation in the Pacific Northwest has brought much of that area out of short-term drought, and a recent set of storms hold promise for the California snowpack. Mammoth Mountain (a ski resort in the Central Sierra Nevadas) is running about 4% ahead of the October-January total for last year, and there are still 2+ weeks left in January.

Parts of California, however, were so far behind that they haven’t yet resolved the long-term drought situation. This is particularly true for a region of mid-coastal California, from about Big Sur down to Santa Barbara. This area remains in an “Exceptional” drought, and as of 12/20/2016, the Gibralter Reservoir was completely empty, and the Cachuma Reservoir was down to 8% of capacity. San Diego relies on these two reservoirs for 82% of its water supply. As I write, it is raining today in Santa Barbara, and since January 1, it has rained about 2.1 inches more than average. Hopefully, even this most stubborn remnant of the drought will finally break.

Figure 3. Source: NOAA Centers for Environmental Information.

Figure 3. Source: NOAA Centers for Environmental Information.

Figure 3 shows annual precipitation in Missouri over time. Statewide, Missouri received 0.55 inches less precipitation than average, basically an average year. The trend, however, suggests that over time precipitation is increasing across the state at the rate of 0.24 inches per decade.

Looking at Figure 2 shows that precipitation varied by region of the state. The northwestern and southeastern portions of the state received above average precipitation, while the rest of the state received below average. In particular, Southwest Missouri, the area around Springfield, Branson, and Joplin, was on the edge of the dry region centered on Oklahoma, and it received 4.3 inches less than average.

For the period 1895-2016, no region of the country shows a strong trend toward decreased precipitation. The Northeast, the Ohio Valley, the Upper Midwest, and the South all show significant trends towards increased precipitation.

Sources:

City of Santa Barbara. Drought Information. Viewed online 1/10/2017 at http://www.santabarbaraca.gov/gov/depts/pw/resources/system/docs/default.asp
utm_source=WaterConservation&utm_medium=Drought&utm_campaign=QuickLink.

National Drought Mitigation Center. U.S. Drought Monitor for 1/3/2017. Viewed online 1/10/2017 at http://droughtmonitor.unl.edu.

NOAA Los Angeles/Oxnard Weather Forecast Office. Climatological Report (Daily) for January 11, 2017. Viewed online 1/12/2017 at http://w2.weather.gov/climate/index.php?wfo=lox.

NOAA National Centers for Environmental information, Climate at a Glance: U.S. Time Series, Average Temperature, published January 2017, retrieved on January 9, 2017 from http://www.ncdc.noaa.gov/cag.

2016 Second Hottest Year in United States


In the United States, 2016 was the second hottest year on record, replacing 2015, which is now the third hottest.


Data source: NOAA National Centers for Environmental Information.

Data source: NOAA National Centers for Environmental Information.

Weather data for 2016 has been posted on the Climate at a Glance data portal operated by the National Centers for Environmental Information. Figure 1 shows average temperature trend for the contiguous 48 states. The purple line represents the yearly average, the blue line represents the trend over time, and the black line represents the average temperature over the entire reference period (1901-2000).

The average temperature for 2016 was 54.91°F, some 2.89°F above the mean, the second warmest year in the record. The warmest year was 2012 at 55.28°F. The third warmest was 2015 at 54.40°F. There is a lot of variability from year-to-year, but the trend is clearly upward, especially since about 1980.

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Data source: NOAA National Centers for Environmental Information.

Data source: NOAA National Centers for Environmental Information.

Figure 2 shows the trend in the average daily maximum temperature (red line), the average daily minimum temperature (blue line), and the average daily average temperature (orange line). I have dropped a dashed linear trend line on each.

If you look at the trend lines carefully, you can see that, while all three are increasing, the trend for minimum daily temperature is steepest, followed by daily average temperature, with the trend for daily maximum being least steep. Though they are not shown on the chart, the equations for the trend lines confirms the visual impression: the average daily minimum temperature is increasing faster than the daily maximum temperature. This finding is consistent with projections for climate change: as the temperature warms, the atmosphere can hold more humidity. The humidity reduces the amount of cooling that occurs at night.

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Data source: NOAA National Centers for Environmental Information.

Data source: NOAA National Centers for Environmental Information.

In Missouri, the average temperature was 57.4°F, the fifth highest reading in the record. The highest reading occurred in 2012. Figure 3 shows the Missouri temperature trends. The red line at the top shows the average daily maximum temperature, the orange line in the middle shows the average daily average temperature, and the blue line at the bottom shows the average daily minimum temperature. The dashed lines show the trends.

The trend lines show that the national pattern applies in Missouri: minimum daily temperature is increasing most rapidly, followed by daily average temperature, then daily maximum temperature. The change in Missouri is less than the average nationwide change, and the reason is, again, humidity. Missouri is a humid state, and it takes more energy to change the temperature here than it does in a dry state.

Because I have been following the water situation in California, I will note that the average temperature there in 2016 was 60.2°F, the third highest since record keeping began. The highest on record occurred in 2014, and the second highest in 2015. Thus, it has been a really warm 3 years in California.

To summarize, 2016 was warmer than average. Across the entire contiguous United States, it was the second warmest year in the record, while in Missouri it was the fifth warmest.

I’ll look at precipitation during 2016 in the next post.

Sources:

NOAA National Centers for Environmental information, Climate at a Glance: U.S. Time Series, Average Temperature, published January 2017, retrieved on January 9, 2017 from http://www.ncdc.noaa.gov/cag.

Oroville Dam: When It Rains, It Pours

If you have been watching the national news, you know that California has had record precipitation for the winter so far. There has been so much rain that one of the state’s biggest reservoirs, Lake Oroville, has exceeded its capacity. Water flowing through the emergency spillway has eroded portions of the dam, threatening a dam collapse that would kill thousands and wipe out communities below the dam. Emergency efforts are underway to repair the dam.

Following are two photos that show just how badly the dam has been damaged. The photos are a bit hard to interpret, but here’s what I think they show: water overtopped the dam into the emergency spillway in amounts that the spillway was not designed to handle. In Figure 1, the water is no longer overtopping the dam, but a huge section of the dam face has been badly damaged. Several channels have been carved down the face of the dam. Figure 2 shows water surging down the damaged main spillway. The spillway is the concrete structure at left. You can see that the water isn’t flowing in it, but rather down a rogue channel that the water has cut in the face of the dam. This actually occurred 2 days after the photo in Figure 1, as the California Department of Water Resources dumped water out of the lake in anticipation of large inflows from a new storm.

Figure 1: Damage on the face of the Oroville Dam. Source: Kolke 2017.

Figure 1: Damage on the face of the Oroville Dam. Source: Kolke 2017.

Figure 2: Water Damaging the Face of Oroville Dam. Source: Grow, 2017.

Figure 2: Water Damaging the Face of Oroville Dam. Source: Grow, 2017.

 

 

 

 

 

 

 

 

 

It sure seems like the surface water drought in California has been broken. The most important snow survey of the year (and often the final one) occurs on or about April 1. So I’m going to wait for that date before I do an analysis of how the wet winter has changed their water situation. Hopefully, at that point there will be enough data to allow an analysis that goes beyond the headlines and looks at long-term implications.

Source:

Kolke, Dale. 2017. DK_Oro_Spillway_damage-4109_02_15_2017.jpg. California Department of Water Resources > Galleries > Dams > Oroville Dam > Oroville Spillway Damage. Downloaded 2/21/17 from http://pixel-ca-dwr.photoshelter.com/galleries/C0000OxvlgXg3yfg/G00003YCcmDTx48Y/Oroville-Spillway-Damage.

Grow, Kelly. 2017. KG_oroville_damage-1 2868_02_20_2017.jpg. California Department of Water Resources > Galleries > Dams > Oroville Dam > Oroville Spillway Damage. Downloaded 2/21/17 from http://pixel-ca-dwr.photoshelter.com/galleries/C0000OxvlgXg3yfg/G00003YCcmDTx48Y/Oroville-Spillway-Damage.

And Now, Three Consecutive Record Warm Years


2016 was even hotter than 2015!


Figure 1. Source: NASA Goddard Institute for Space Studies.

Figure 1. Graph of Global Average Temperature. Source: NASA Goddard Institute for Space Studies.

Data released by NASA reveals that the average global temperature in 2016 was even hotter than in 2015, and by a substantial margin. The data is shown in Figure 1. 2014 was a record, then 2015 was a new record, and now 2016 is a new record: this marks the first time in the data maintained by NASA that the world has set three consecutive records. The data indicates that the temperature was at record highs during every month of the year.

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In 2016, global surface temperature was 0.12°C warmer than in 2015. In 2016, the temperature was .99°C warmer than during the reference period, from 1951-1980, and about 2.0°C warmer than the late 19th Century.

Figure 2. Map of Annual Temperature Anomaly, 2016. Source: NASA Goddard Institute for Space Studies.

Figure 2. Map of Annual Temperature Anomaly, 2016. Source: NASA Goddard Institute for Space Studies.

Figure 2 shows a map of global temperature anomalies. In terms of heavily populated areas, portions of the United States, Canada, Russia, and Brazil were especially warm. But in truth, the real pattern here is that the farther north you go, the more severe the warming.

The NASA report is based on satellite measurements of temperature over both land and sea. In general, satellite measurement is quite accurate. The report does not address the many other climate variables that are addressed in the State of the Climate report published by the American Meteorological Association. That report, however, takes many months to prepare. In the previous post, I reported on the most recent State of the Climate report, which concerns 2015, not 2016.

Sources:

NASA Goddard Institute for Space Studies. GISS Surface Temperature Analysis: Global Maps from GHCN v3 Data. Downloaded 1/18/2017 from https://data.giss.nasa.gov/gistemp/maps.

NASA Goddard Institute for Space Studies. GISS Surface Temperature Analysis: Analysis Graphs and Plots. Downloaded 1/19/2017 from https://data.giss.nasa.gov/gistemp/graphs.

The Temperature Keeps on Rising


2015 was the hottest year worldwide since record-keeping began. The previous hottest year was 2014.


Figure 1. Map of Average Temperature Anomalies, 2015. Source: Blunden and Arndt 2016.

Figure 1. Map of Average Temperature Anomalies, 2015. Source: Blunden and Arndt 2016.

2015 was the hottest year worldwide since record-keeping began in 1900, according to the State of the Climate in 2015 report by the American Meteorological Society. This is a report that came out in August, 2016, and I’m just catching up to it now. I will summarize a few of the many findings.

Figure 1 shows how much 2015 temperatures around the globe varied from the average temperature for that location (reference years 1981-2010). The yellow and red areas were warmer than average, the blue areas cooler. White represents areas for which there is not enough data to make a characterization. You can see that the map has many more yellow and red areas than blue. The previous record was set the year before, and 2015 was 0.13 – 0.18°C warmer. That is a large jump.

Figure 2. Global Temperature Trends. Source: Blunden and Arndt 2016.

Figure 2. Global Temperature Trends. Source: Blunden and Arndt 2016.

Figure 2 shows the trend in global temperatures from 1880 to 2015. The top two graphs represent different analyses of temperature over both land and ocean, the middle two graphs represent different analyses of temperature over land only, and the bottom two represent different analyses of temperature over ocean only. An inspection of the charts shows considerable year-to-year variation, but all of them show a continuing trend towards warmer temperature. Climate change deniers have been making much of a multi-year pause in the increase in surface temperature at the beginning of the 21st Century. Climate scientist have pointed out that this pause was illusory, as it represented a period during which heat was being shunted from the surface to the depths of the ocean faster than usual, not an actual pause in warming. It now seems that surface temperature has resumed its upward march: 2014 and 2015 show up on the charts as a quite large spike upward.

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Figure 3. Warm Day Anomalies, 2015. Source: Blunden and Arndt 2016.

Figure 3. Warm Day Anomalies, 2015. Source: Blunden and Arndt 2016.

One of the ways global warming has its effect is by increasing the number of warm days, defined as “number of days above the seasonal 90th percentile of daily maximum temperatures over the 1961-1990 base period.” (Blunden and Arndt, 2016, p. S19) Figure 3 shows the map. You can see that there are large blobs of red over Australia, Southeast Asia, China, Siberia, Europe, South Africa, eastern Greenland, and most of North America. That means that all these regions had an above average number of warm days, in most cases by a lot (+30 days or more).

Extreme days are important. In the summer a “warm” day might indicate that it was extremely hot, which is hazardous. During the winter, on the other hand, it might indicate that the day was above freezing.

The map of warm days for 2015 looks quite similar to the map for 2014 (here): many of the same areas were involved.

There is a great deal more information in the report that is beyond the scope of this blog. For those interested in meteorology and climatology, it would make interesting reading.

I’m writing this post in early January, 2017. United States climate data for 2016 should post-up on Climate at a Glance during January, so hopefully by the time this post goes live, I’ll be able to follow up with information about the USA and Missouri.

Source:

Blunden, Jessica and Derek Arndt (eds.) 2016. “State of the Climate in 2015.” Bulletin of the American Meteorological Society, 97 (8) Special Supplement. Downloaded 1/8/17 from https://www.ametsoc.org/ams/index.cfm/publications/bulletin-of-the-american-meteorological-society-bams/state-of-the-climate.

Invisible Pollution


You can’t always see air pollution in a photograph.


In the previous post I counted down the industrial facilities that are the 10 largest GHG emitters in Missouri, providing photos. Carbon dioxide, the main greenhouse gas, is colorless and odorless: you can’t see it. What, then, do the photos I posted show? Here are a few more photos and a discussion of what can and can’t be seen in them.

The Clean Air Act requires the EPA to set standards for atmospheric concentrations of 6 common air pollutants (aka criteria air pollutants). They are ozone, sulfur dioxide, nitrous oxide, carbon monoxide, and two classes of particulates: particulates less than 2.5 micrometers in size (PM2.5), and those between 2.5 and 10 micrometers (PM10). (See here.) They are by no means the only air pollutants emitted by large industrial plants. Among the 10 largest GHG emitters in Missouri, other pollutants include carbon dioxide (of course!) plus as many as 15-20 toxic compounds, most commonly heavy metals like lead and mercury (EPA TRI Explorer). Heavy metals are contained in coal and released when it is burned, and are toxic even in small amounts.

At least 5 of these pollutants are colorless gases: ozone, sulfur dioxide, nitrous oxide, carbon monoxide, and carbon dioxide. You can’t see them in the plume emitted by an industrial facility (or by your car, for that matter), they are invisible. The remaining compounds are contained in escaping particulates.

So, several of the pollutants can’t be readily seen in the plume of an industrial plant, but they are dangerous none-the-less. Generally, only escaping particulates are readily seen. Lets look at some examples:

(Click on photos for a larger view.)

Figure 1. The Sioux Energy Center Before Dawn on a Winter Day. Photo by John May.

Figure 1. The Sioux Energy Center Before Dawn on a Winter Day. Photo by John May.

Figure 2. Mississippi Lime Co. Ste. Genevieve Plant on a Winter Morning. Photo by John May.

Figure 2. Mississippi Lime Co. Ste. Genevieve Plant on a Winter Morning. Photo by John May.

 

 

 

 

 

 

 

 

Figure 1 and Figure 2 show the Sioux Energy Center and the Mississippi Lime Company Ste. Genevieve Plant. The photos show dramatic white plumes belching from the chimneys of these two plants. Those white plumes sure are dramatic, but they are not the problem. They are mostly steam – water vapor. It condenses when it hits the air on a cold morning, forming dramatic white clouds. The dark parts of the cloud are simply shadow where the cloud has become thick enough to block the sun.

The problem is what is hidden inside the white plume. That is where the air pollutants are. In addition, if you look at the buildings in Figure 2, you can see a gray haze. Those are particulates. I don’t know if they are PM2.5, PM10, or even larger particles, or perhaps a combination of all 3. While taking the photo in Figure 2, I noticed a definite rotten-egg smell. That is usually caused by sulfur dioxide, and it suggests that sulfur dioxide was being emitted by the plant. You can’t see it, however, it is colorless.

The Labadie Energy Center on a Spring Morning. Photo by John May.

Figure 3. The Labadie Energy Center on a Spring Morning. Photo by John May.

The Labadie Energy Center at Dawn on a Fall Morning. Photo by John May.

Figure 4. The Labadie Energy Center at Dawn on a Fall Morning. Photo by John May.

 

 

 

 

 

 

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Figure 3 shows the Labadie Energy Center on a warm day in May. No billowing clouds of steam are visible, it wasn’t cold enough to condense them. With the naked eye you could barely make out a slight plume coming from the chimneys. By using a polarizing filter, I could make it just a bit more obvious. Here we have a photo of the real pollution being emitted by this power plant. I think it is probably fly ash – those PM2.5 and PM10 particles the EPA tracks. Figure 4 is a photo of the Labadie Energy Center on an October morning. If you look very hard, you can see a slight discoloration above the stacks, but man, is it hard to see! Unless the emissions are backlighted, or unless the photo is enhanced, it is very, very difficult to see the pollution that belches forth from these facilities.

Figure 4. The Thomas Hill Energy Center at Dusk on a Fall Day. Photo by John May.

Figure 5. The Thomas Hill Energy Center at Dusk on a Fall Day. Photo by John May.

Figure 6. The Hawthorn Plant on a Fall Day. Photo by John May.

Figure 6. The Hawthorn Plant on a Fall Day. Photo by John May.

 

 

 

 

 

 

 

 

Figure 5 shows the Thomas Hill Power Plant and Figure 6 shows the Hawthorne Plant. The plants were pumping out electricity, which means the boilers were burning, but no plume is visible above the chimneys. The conditions just weren’t right to be able to see it.

If you look at all the photos of power plants, you can see that they share one characteristic: a tall chimney. The one at New Madrid is 800 ft. tall, Iatan, Rush Island, and Labadie have stacks that are 700 ft. tall, Thomas Hill’s stack is 620 ft. tall, the Sioux Energy Center stack is 603 ft. tall, and so forth. Tall chimneys like this are expensive, so there is a reason for them. Most of the pollutants emitted out of the chimneys are poisonous. If they were emitted at ground level, they would blow with the wind and cause harm. In addition, almost all of them are regulated by the EPA. If the chimneys were less tall, there is a chance that the pollution could reach the ground at concentrations still high enough to put the plant in violation. By building very tall chimneys, the company ensures that by the time any of the pollutants reach the ground, they have been diluted sufficiently so that they don’t create a violation. If you look at the photo of the Mississippi Lime Co. Ste. Genevieve Plant, you can see that its chimneys are much shorter, and perhaps that is why I could smell the sulfur dioxide.

In one sense, this is a good strategy: people and property in close proximity aren’t exposed to high concentrations of the pollutants. In another sense, it is a bad strategy: it puts pollutants into the environment, where they accumulate and cause widespread damage. Thus, pollution from facilities here in the Midwest contributes to smog, acid rain, mercury accumulation in fish, and GHG build-up in the atmosphere.

Figure 7. The Labadie Energy Center Seen From Midtown St. Louis at Dusk on a Winter Day. Photo by John May.

Figure 7. The Labadie Energy Center Seen From Midtown St. Louis at Dusk on a Winter Day. Photo by John May.

One final photo: Figure 7 is a photo of the Labadie Energy Center taken on a winter day from the top of a building opposite Forest Park in St. Louis. Expand the photo and you can see the chimneys on the horizon. The plant is some 30 miles away from the camera. The plume rises more than 2,000 feet into the air before the steam evaporates. How much higher than that does the column of polluted hot air rise? I don’t know, but I would expect quite a bit. Even this visible plume dominates the otherwise empty sky and horizon.

These plants come with important economic benefits, which I reviewed in the first post of this series, and we couldn’t do without them. But their pollution is also a big deal.

So, the point is that you can’t necessarily see the pollution being emitted by a large industrial emitter. If the sun is in just the right spot, you might be able to barely make out some particulates. But the other pollutants are all invisible. On a cold day, the plant will emit billowing clouds of water vapor. Water vapor itself is mostly harmless, but it stands as a reminder of the invisible pollution hidden within.

Sources:

Environmental Protection Agency. TRI Explorer, Release Facility Report. Data accessed 12/21/2016 at https://iaspub.epa.gov/triexplorer/tri_release.facility.

May, John. 2015. “Air Quality Update 2014.” Mogreenstats.com. Viewed online 12/21/2016 at https://mogreenstats.com/2015/11/06/air-quality-update-2014.

Wikipedia. List of Tallest Buildings in Missouri. Viewed online 12/21/2016 at https://en.wikipedia.org/wiki/List_of_tallest_buildings_in_Missouri#Missouri.27s_tallest_structures.

Countdown of the Top 10 GHG Emitting Facilities in Missouri


In the previous post, I summarized information about the 10 GHG emitting facilities in Missouri. In this post, I will count them down and profile them.


When possible, for each facility I will give the date the plant entered service, the amount of GHG emitted, some of the economic benefit derived from the plant’s products, and closing plans that have been announced by the plant’s owner. Typically, closing plans for industrial facilities are not publicly discussed, but they are required by Integrated Resource Plans that public electric utilities must file. They often extend a decade or two into the future and have been formulated partially in response to EPA clean air regulations. Thus, as economic and regulatory environments change, and as technological alternatives become more or less feasible, I would expect closure plans to change with them.

And now, the countdown:

(Click on photos for a larger view.)

10. Meramec Energy Center. GHG emissions 2015: 2,324,558 MTCO2e.

Figure 1. The Meramec Engergy Center. Photo by John May.

Figure 1. The Meramec Engergy Center. Photo by John May.

The Meramec Energy Center is located in southeastern St. Louis County, at the confluence of the Meramec and Mississippi Rivers. It is a coal-burning electricity generating station with a nameplate capacity of 831 MW. In 2009, it generated 5,362,000 MWh (data from CARMA, www.carma.com). If the average home in the United States consumes 10.8 MWh per year (Energy Information Administration), then the Meramec Plant produces enough electricity to power 496,481 homes. It is owned by Union Electric Co., a subsidiary of Ameren Missouri.

It began operation in 1953, and according to an article 7/12/2014 in the St. Louis Post-Dispatch, Ameren announced plans to close the Meramec Energy Center in 2022. If emissions remain at the current level, by then it will have emitted an additional 13,947,348 MTCO2e into the atmosphere.

In 2015, the Meramec Energy Center emitted 2,324,558 million MTCO2e (EPA Facility Level Information on Greenhouse Gases Tool).

9. Mississippi Lime Company. GHG emissions 2015: 2,430,415 MTCO2e

Figure 2. The Mississippi Lime Co. Ste. Genevieve Plant. Photo by John May.

Figure 2. The Mississippi Lime Co. Ste. Genevieve Plant. Photo by John May.

The Mississippi Lime Company is located just west of the city boundary of the City of Ste. Genevieve. It produces a variety of calcium products that are related to cement, but not equivalent, such as quicklime and hydrated lime. The output of this plant is unknown. It is a privately held company with headquarters in St. Louis.

Specific information about the plant is in short supply, but the history of the company on the company’s website indicates that the site was purchased and the kilns constructed during the 1920s. Future plans for the plant are unknown.

Greenhouse gases are emitted in 2 ways during calcium processing. To produce quicklime, for instance,
quarried limestone is crushed, and then heated at about 825°C in a kiln. Fossil fuel, most often coal, is burned to heat the kiln, releasing carbon dioxide. In addition, in the kiln, the limestone undergoes a chemical change that converts it to quicklime. This reaction releases carbon dioxide. The Mississippi Lime plant released 2,430,415 MTCO2e in 2015.

A footnote on the EPA website says that some of the CO2 emitted by the plant is captured and reused, not released into the atmosphere, but the amount is not specified.

8. Holcim Ste. Genevieve Plant. GHG emissions 2015: 2,598,048 MTCO2e.

Figure 3. The Holcim Ste. Genevieve Plant. Source: Holcim USA publicity photo.

Figure 3. The Holcim Ste. Genevieve Plant. Source: Thanks to Holcim (US) Inc. for supplying this photo, as I was unable to take one myself.

The Holcim Ste. Genevieve Plant is located on the Mississippi River at the northeastern corner of Ste. Geneieve County. Though across the county line, it is physically adjacent to the Rush Island Energy Center (see below). It is a cement manufacturing plant, and claims to have the largest single kiln line in the world. It is claimed to have the capacity to produce 4 million metric tons of cement per year. The U.S. Geological Survey estimates that the Interstate Highway System contains 48 million metric tons of cement, so the Ste. Genevieve Plant turns out about 1/12th of that amount each year (USGS 2006). The plant is owned by Holcim US, a subsidiary of Holcim Ltd. of Switzerland.

The plant entered service in 2010, and future plans for the plant are not known. The Ste. Genevieve Plant received the EPA Energy Star Award for energy efficiency in each year from 2010-2015. It has also received Gold Certification from the Wildlife Habitat Council for its wildlife conservation efforts.

Greenhouse gases are emitted in 2 ways during cement production. Cement is produced by quarrying limestone, crushing it, and then heating it at about 1,500°C in a kiln. Fossil fuel, most often coal, is burned to heat the kiln, releasing carbon dioxide. In addition, in the kiln, the limestone undergoes a chemical change that converts it to cement. This reaction releases carbon dioxide.

The Holcim Ste. Genevieve Plant emitted 2,598,048 MTCO2e in 2015.

7. Hawthorn Plant. GHG emissions 2015: 3,145,642 MTCO2e.\

Figure 4. The Hawthorn Plant. Photo by John May.

Figure 4. The Hawthorn Plant. Photo by John May.

The Hawthorn Plant is located along the banks of the Missouri River in northeastern Kansas City. It is a coal-burning electricity generating station with a nameplate capacity of 565 MW. In 2009, it generated 4,174,900 MWh (data from CARMA, www.carma.com). If the average home in the United States consumes 10.8 MWh per year (Energy Information Administration), then the Hawthorn Plant produces enough electricity to power 386,565 homes. It is owned by Kansas City Power and Light, a subsidiary of Great Plains Energy.

In the photo, to the right of the main structure stand several small boxy structures. Those are natural gas peaking generators. Though they still emit GHGs, they are cleaner than the coal-burning main plant. In addition, they can be started when electricity demand is peaking and turned off when it is slackening, compared to the coal-burning main plant, which cannot.

The Hawthorn Plant was built in stages between 1951 and 1969. The peaking generators entered service between 2000 and 2003. Regarding future plans for the station, in reply to a request for information, the company referred me to their website, where I could find none. (The company does not publish its Integrated Resource Plan, deeming it to be confidential.)

In 2015, the Hawthorn Plant emitted 3,145,642 million MTCO2e (EPA Facility Level Information on Greenhouse Gases Tool).

6. Sioux Energy Center. GHG emissions 2015: 4,314,760 MTCO2e.

Figure 5. The Sioux Energy Center. Photo by John May.

Figure 5. The Sioux Energy Center. Photo by John May.

The Sioux Energy Center is located in northern St. Charles County, along the banks of the Mississippi River. It is a coal-burning electricity generating station with a nameplate capacity of 970 MW. In 2009, it generated 5,760,500 MWh (data from CARMA, www.carma.com). If the average home in the United States consumes 10.8 MWh per year (Energy Information Administration), then the Sioux Plant produces enough electricity to power 533,379 homes. It is owned by Union Electric Co., a subsidiary of Ameren Missouri.

It began operation in 1967, and Ameren filed a plan indicating it would be closed no later than 2033. If emissions remain at the current level, by then it will have emitted an additional 73.4 million MTCO2e.

In 2015, the Sioux Energy Center emitted 4,314,760 million MTCO2e (EPA Facility Level Information on Greenhouse Gases Tool).

5. New Madrid Power Station. GHG emissions 2015: 5,815,694 MTCO2e.

Figure 6. The New Madrid Power Station. Photo by John May.

Figure 6. The New Madrid Power Station. Photo by John May.

The New Madrid Power Station is located along the banks of the Mississippi River six miles southwest of New Madrid, Mo. It is a coal-burning electricity generating station with a nameplate capacity of 1,200 MW. In 2009 it generated 7,246,800 MWh of electricity. If the average home in the United States consumes 10.8 MWh per year (Energy Information Administration), then the New Madrid Plant produces enough electricity to power 671,000 homes. It is owned by the Associated Electric Cooperative. AEC provides electricity to 51 local electricity cooperatives throughout Missouri and in parts of Oklahoma, and Iowa.

It’s two units entered service in 1972 and 1977. Regarding future plans for the station: in reply to a request for information, the company stated that it had no plans to close or convert the fuel source for the plant (Viquet 2016).

In 2015, the New Madrid Power Station emitted 5,815,694 million MTCO2e (EPA Facility Level Information on Greenhouse Gases Tool).

4. Rush Island Energy Center. GHG emissions 2015: 6,833,938 MTCO2e.

Figure 7. The Rush Island Energy Center. Photo by John May.

Figure 7. The Rush Island Energy Center. Photo by John May.

The Rush Island Energy Center is located at the southeastern corner of Jefferson County along the banks of the Mississippi River, adjacent to the Holcim St. Genevieve plant (see above). It is a coal-burning electricity generating station with a nameplate capacity of 1,180 MW. In 2009, it generated 8,017,200 MWh (data from CARMA, www.carma.com). If the average home in the United States consumes 10.8 MWh per year (Energy Information Administration), then the Sioux Plant produces enough electricity to power 742,333 homes. It is owned by Union Electric Co., a subsidiary of Ameren Missouri.

It began operation in 1976, and Ameren’s 2014 Integrated Resource Plan stated that the company had “developed assumptions for an evaluation of retirements of Labadie and Rush Island Energy Centers.” (Ameren Missouri 2016) I don’t understand this statement to indicate that Ameren is considering closing the facility, only that they have developed a set of assumptions that will be used in an ongoing fashion to monitor its viability.

In 2015, the Rush Island Energy Center emitted 6,833,938 million MTCO2e (EPA Facility Level Information on Greenhouse Gases Tool).

Note: On 1/23/17 the U.S. District Court for Eastern Missouri found the Rush Island Energy Center in violation of the Clean Air Act because Ameren Missouri had performed major modifications to the facility without installing required pollution control equipment. Ameren had tried avoid its obligation by characterizing the work as routine maintenance.

3. Thomas Hill Energy Center. GHG emissions 2015: 7,506,076 MTCO2e

Figure 8. The Thomas Hill Energy Center. Photo by John May.

Figure 8. The Thomas Hill Energy Center. Photo by John May.

The Thomas Hill Energy Center is located on the banks of the Thomas Hill Reservoir, about 12 miles northwest of Moberly. It is a coal-burning electricity generating station with a nameplate capacity of 1,135 MW. In 2009 it generated 7,379,800 MWh of electricity. If the average home in the United States consumes 10.8 MWh per year (Energy Information Administration), then the Thomas Hill Energy Center produces enough electricity to power 683,315 homes. It is owned by the Associated Electric Cooperative. AEC provides electricity to 51 local electricity cooperatives throughout Missouri and in parts of Okalahoma, and Iowa.

Thomas Hill’s three generating units entered service in 1966, 1969, and 1982. Regarding future plans for the station: in reply to a request for information, the company stated that it had no plans to close or convert the fuel source for the plant (Viquet 2016).

In 2015, the Thomas Hill Energy Center emitted 7,506,076 million MTCO2e (EPA Facility Level Information on Greenhouse Gases Tool).

2. Iatan Generating Station. GHG emissions 2015: 8,911,498 MTCO2e.

Figure 9. The Iatan Generating Station. Photo by John May.

Figure 9. The Iatan Generating Station. Photo by John May.

The Iatan Generating Station is located in northwestern Platte County, along the banks of the Missouri River, between Kansas City and St. Joseph. It is a coal-burning electricity generating station with a nameplate capacity of 1,576 MW. It is the second largest generating station in Missouri, and the state’s second largest GHG emitter. The second unit at Iatan entered service after 2010, so generating statistics for 2009 are irrelevant. It is owned by Kansas City Power and Light, a subsidiary of Great Plains Energy.

Iatan’s 2 generating units entered service in 1980 and 2010. Regarding future plans for the station, in reply to a request for information, the company referred me to their website, where I could find none. Given that the second unit was completed only 6 years ago, I would expect the company plans to continue to operate the plant for the foreseeable future.

In 2015, the Iatan Generating Station emitted 8,911,498 million MTCO2e (EPA Facility Level Information on Greenhouse Gases Tool).

1. Labadie Energy Center. GHG emissions 2015: 14,754,371 MTCO2e.

Figure 10. The Labadie Energy Center. Photo by John May.

Figure 10. The Labadie Energy Center. Photo by John May.

The Labadie Energy Center is located in Franklin County along the banks of the Missouri River east of Washington. It is Missouri’s largest coal-burning electricity generating station, with a nameplate capacity of 2,372 MW, about half-again as large as the Iatan Station. In 2009, it generated 17,238,000 MWh (data from CARMA, www.carma.com). If the average home in the United States consumes 10.8 MWh per year (Energy Information Administration), then the Labadie Energy Center produced enough electricity to power 1,596,111 homes. It is owned by Union Electric Co., a subsidiary of Ameren.

It began operation in 1976, and Ameren’s 2014 Integrated Resource Plan stated that the company had “developed assumptions for an evaluation of retirements of Labadie and Rush Island Energy Centers.” (Ameren Missouri 2016) I don’t understand this statement to indicate that Ameren is considering closing the facility, only that they have developed a set of assumptions that will be used in an ongoing fashion to monitor its viability.

In 2015, the Labadie Energy Center emitted 14,754,371 million MTCO2e (EPA Facility Level Information on Greenhouse Gases Tool).

As you have read this post, you probably noticed that some of the photos showed billowing white clouds gushing out of a chimney, some showed a thin plume, and some showed no plume at all. I think the differences make for an interesting discussion, and they will be the focus of the next post.

Sources:

Ameren Missouri. 2016. Integrated Resource Plan. Viewed online 12/10/2016 at https://www.ameren.com/missouri/environment/renewables/ameren-missouri-irp.

Energy Information Administration. Frequently Asked Questions: How much electricity does an American home use? Accessed 10/20/2016 at https://www.eia.gov/tools/faqs/faq.cfm?id=97&t=3.

EPA. Facility Level Information on Greenhouse Gases Tool. http://ghgdata.epa.gov/ghgp/main.do. Data downloaded 10/20/2016.

EPA. 2015. EPA Fact Sheet: Social Cost of Carbon. Downloaded 12/10/2016 from https://www3.epa.gov/climatechange/Downloads/EPAactivities/social-cost-carbon.pdf.

EPA. 2015. Facility Profile Report: Ameren Missouri Labadie Energy Center. Retrieved online 12/10/2016 at https://iaspub.epa.gov/triexplorer/release_fac_profile?TRI=63055LBDPWNO10L&year=2011&trilib=TRIQ1&FLD=&FLD=RELLBY&FLD=TSFDSP&OFFDISPD=&OTHDISPD=&ONDISPD=&OTHOFFD=.

Genova, Marcus, Area Environmental and Public Affairs Manager, Holcim (US) Inc. Email message to John May 1/10/2017.

United States v. Ameren Missouri. Case 4:11-cv-00077-RWS, U.S. District Court for Eastern District of Missouri. Viewed online 1/25/2017 at http://www.moed.uscourts.gov/sites/default/files/Ameren%20Memorandum%20and%20Order.pdf.

U.S. Census Bureau. Quick Facts: Missouri. Viewed online 12/10/2016 at http://www.census.gov/quickfacts/table/PST045215/29.

U.S. Geological Survey. 2006. Materials in Use in the U.S. Interstate Highways. Viewed online 12/10/2016 at https://pubs.usgs.gov/fs/2006/3127/2006-3127.pdf.

Viquet, Mark, email message to author, 12/12/2016.