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Green Buildings Are Better – Financial Performance


A study by the Department of Energy found that in green buildings net operating income was 28.8% higher than in non-green buildings. Missouri has more green buildings than Tennessee, but far fewer than Maryland.


The residential and commercial buildings in the U.S. consume about 40% of the nation’s total energy consumption. Green buildings use less energy, improve occupant health and productivity, and lower ownership risk. However, until recently researchers have lacked sufficient historical data to analyze the link between energy efficiency and financial performance because the information has been proprietary.

A recent study by the U.S. Department of Energy addressed this question. The authors were able to identify a set of 131 buildings for which the necessary data were available. Only buildings that met the following criteria were accepted into the study:

  • Market value per square foot was greater than $400.
  • Rent concessions in the building were greater than $0, but less than $3 per square foot.
  • Monthly rent in the building was greater than $6 per square foot.
  • Occupancy in the building was greater than 50%.

The authors then divided the buildings into two groups: buildings were “green” if they had an Energy Star score of 75 or higher (a measure of energy efficiency compared to other buildings of the same type) or if they had achieved LEED Certification. A discussion of what these criteria mean is below. Buildings were “non-green” if they did not meet either criteria. The result was 2 groups of buildings, green and non-green, each with more than 60 buildings in it.

The authors then compared the buildings on the following metrics:

  • Market value per square foot;
  • Net operating Income per square foot;
  • Operating expenses per square foot;
  • Rental income per square foot;
  • Rental concessions per square foot;
  • Occupancy rate.

Table 1. Comparison of Green and Non-Green Buildings on 6 Financial Performance Metrics. Source: Department of Energy, 2017.

Table 1 gives the results. Green buildings had higher market value, higher net operating income, higher rent, lower rental concessions, lower operating expenses, and higher occupancy rates. The differences in operating expenses and net operating income achieved statistical significance (p = 0.0089 and 0.0015 respectively), and the difference in market value approached it (p = 0.094).

Looking at Table 1, what jumps out is that net operating income was 28.8% higher in green buildings. Most of the increase seems to have come from reduced expenses, with a smaller contribution coming from increased rents.

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Table 2. Source: Miller et al, 2008.

The Department of Energy study is not the only study to suggest better financial performance from green buildings. Table 2 summarizes results from 3 additional studies, all of which found that LEED and ENERGY STAR buildings generated higher rents, higher occupancy rates, and higher value per square foot.

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Figure 1. Data source: Green Building Information Gateway

So how many green buildings are there in Missouri? A database operated by the U.S. Green Building Council lists 389 LEED certifications in Missouri, covering 35.27 million square feet. Tennessee, Missouri, and Maryland are the 17th, 18th, and 19th most populous states in the country. Tennessee has 377 LEED certified activities (48.35 million square feet), and Maryland has 964 (11.4 million square feet). Figure 1 shows the data, with the number of LEED certified buildings in blue and the LEED certified square footage in red. Clearly, green building has caught on in Maryland to a much greater extent than it has here. It’s too bad – if you could deliver health benefits to those who live and work in a building, while at the same time improving its net operating income by 28.8%, you’d think that you’d want to do that, wouldn’t you?

Explanation of Energy Star and LEED Certification: ENERGY STAR is a building energy benchmarking program operated by the U.S. Department of Energy. Building owners enter their building’s energy consumption (from utility bills and similar sources) into a computer database. The database then compares the building’s energy consumption to that of other similar buildings. In other words, hospitals are compared to hospitals, schools to schools, office buildings to office buildings, etc. The program then gives each building a rating from 1-100, the higher the number the better the building’s energy performance. LEED is an acronym that stands for Leadership in Energy and Environmental Design. To achieve LEED certification, a building must incorporate a suite of technologies that improve the building’s environmental performance in a number of areas, from energy consumption to indoor air quality to water consumption, and others. The LEED system is administered by the U.S. Green Building Council.

MoGreenStats is now going on break for a few weeks. The next post will be scheduled for August 24, 2017. Happy trails ’til then.

Sources:

Department of Energy. 2017. Utilizing Commercial Real Estate Owner and Investor Data to Analyze the Financial Performance of Energy Efficient, High Performance Office Buildings. Downloaded 7/9/2017 from https://energy.gov/sites/prod/files/2017/05/f34/bto_PilotResearchStudy-DOEFinancialDataInitiative_5-8-17.pdf.

Miller, Norm, Jay Spivey, and Andy Florance. 2008. Does Green Pay Off? Published by U.S. Department of Energy. Downloaded 7/10/2017 from https://www.energystar.gov/sites/default/files/buildings/tools/DoesGreenPayOff.pdf.

The Green Building Information Gateway, an online database operated by the U.S. Green Building Council. Data accessed online 7/9/2017 at http://www.gbig.org.

Opinion: We Could Do It, If Only We Wanted

In the preceding posts, I have done some “back-of-the-envelope” calculations of how much land would be required to generate enough electricity using wind and solar energy to cover total energy consumption in the USA or in Missouri. I found that to cover total United States energy consumption would require wind farms on land equal to the size of South Carolina, or solar farms on land equal to almost the size of Texas. Alternatively, it you put solar panels on rooftops, it would require roughly six time as much roof space as exists in the entire country. To cover Missouri’s energy consumption would require wind farms on land equal to the size of Iron County, or solar farms on land equal to about 7% of the state.

I didn’t consider the need for storage, redundancy, peak demand, additional capacity to cover times when the wind wasn’t blowing or the sun wasn’t shining, or losses during delivery of the electricity to customers. All of this means that my estimates are bare minimums, and the actual land required would be larger. How much more? I don’t know.

The International Panel on Climate Change has estimated that we need to reduce GHG emissions 41-72% by 2050 in order to avoid the worst effects of climate change. If the United States were to attempt to meet that goal entirely through converting to renewable energy, then only 41-72% of the land I estimated would be required, plus the extra land required for the reasons cited above. Perhaps the end result would be in the rough vicinity of my estimates.

But the United States doesn’t have to make renewable energy the only possible way of reaching the goal. Other strategies might (and probably should) include reducing how much energy we consume and increasing the efficiency of the energy we do use. These are obvious strategies, they are far and away the most cost-effective ways of reducing GHG emissions, and there are no technological hurdles stopping us from getting started. The only thing stopping us is our refusal to do it. Like smokers with lung cancer who still smoke, we continue to emit GHGs despite their harmful effects.

Two other strategies are also possible, though significantly more controversial: nuclear power and population reduction. Nuclear power is one of the most efficient, most reliable forms of generating electricity that has been invented. It has virtually no GHG emissions. The problem is that, in its brief history, every 20-30 years something somewhere has gone spectacularly wrong, and the consequences have been devastating. Entire regions have been made uninhabitable, the costs have been in the hundreds of billions of dollars, and remediation has been virtually impossible. The Ukraine is still working to seal-off the Chernobyl Generating Station, and that accident was 30 years ago. Nuclear power seems to me something we can’t live without, but something we can’t live with, either.

The other strategy is population reduction. I personally believe that in 100 years human population will be significantly less than it is today. Whether that will come voluntarily or involuntarily, I don’t know. It is seems to be common wisdom these days that Malthus and Paul Ehrlich were completely wrong, and that Malthusian sorts of analyses are all off base. I don’t think so. Malthus and Ehrlich were spectacularly wrong in the specifics of their predictions; the dynamics of population and the world’s capacity to support life were influenced by factors they did not understand. The fundamental logic behind their analyses, however, is that you cannot infinitely increase population in a world with finite limits. Duh! That still seems cogent to me. People use resources and generate waste and pollution. It all puts the earth under stress, and the results show up in hundreds of ways that are plain to see if one only reads the newspapers. We have shown remarkable ingenuity in stringing this along for much longer than Malthus and Ehrlich thought we could. How long we can continue to do so, I don’t know. There are numerous important ecological systems that appear to be nearing tipping points, and unless we take the stress off them, sooner or later they are likely to start collapsing. Or so I believe.

Our population could be reduced through wars, famines, or plagues. These are the historical ways in which human population has been reduced, and these are the methods that nature uses to reduce population among other animals. These would all be terrible disasters, and any sane person would hate to see such a thing happen to the human race.

Planned population reduction has never been tried for an extended period on a global, or even a nation-wide basis. It comes with serious economic and demographic problems that people the world over have been unwilling to face. But they are better than population reduction through war, famine, or plague. I personally believe that if we don’t do this, then nature will do it to us. I don’t look forward to that time, either for myself, or for my child, or for my child’s children.

Climate change is just one of the stresses. Others could be named, such as changes to the ocean, desertification, water scarcity, or the mass extinction of species that is currently occurring. But the last few posts have been on renewable energy, so I’ll end with this:

Reducing GHG emissions through the use of renewable energy would be a big, expensive task. We would have to cover large areas of the country, and we would have to solve a number of thorny technical problems. But in terms of the land available, it is possible. We could do it, especially if we also used the other strategies like reducing consumption and increasing efficiency.

Addendum: This post was written in early August. On October 3, the New York Times published an article saying that  this year the carbon dioxide concentration of the atmosphere at Mauna Loa Observatory was measured at greater than 400 ppm., and is likely to remain above 400 ppm. for the immediate future. While 400 ppm. is not a catastrophic tipping point, it is a milestone. Those who had hoped to limit the effects of climate change had hoped to keep the carbon dioxide level below 400 ppm., or at least delay (by decades) the day it was exceeded. Well, we have blown by the milestone faster than almost anybody anticipated. It is not a tipping point, but it is a sign that the world has yet to take climate change seriously, and has yet to make the changes needed to head off its worst effects.

Source:

Chernobyl Disaster. Wikipedia. Viewed online 8/4/16 at https://en.wikipedia.org/wiki/Chernobyl_disaster#Economic_and_political_consequences.

Diamond, Jared. 2005. Collapse: How Societies Choose to Fail or Succeed. New York: Viking.

Ehrich, Paul. 1968. The Population Bomb. Sierra Club/Ballantine Books.

IPCC, 2014: Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Edenhofer, O., R. Pichs-Madruga, Y. Sokona, E. Farahani, S. Kadner, K. Seyboth, A. Adler, I. Baum, S. Brunner, P. Eickemeier, B. Kriemann, J. Savolainen, S. Schlömer, C. von Stechow, T. Zwickel and J.C. Minx (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA. Table SPM.1.

Malthus, Thomas. 1789. An Essay on the Principle of Population. Public domain, viewed 8/4/16 at the website of the Electronic Scholarly Publishing Project, http://www.esp.org/books/malthus/population/malthus.pdf.

A Wind Farm the Size of Iron County


To satisfy energy demand in Missouri would require a wind farm the size of Iron County, or a solar photovoltaic farm 7% the size of the state, or a combination of both.


In the past 3 posts I have constructed “back-of-the-envelope” estimates of how much land would be required in order to meet the USA’s energy needs from wind power and solar photovoltaic power. In this post I bring it back to Missouri: how big a wind farm, how big a solar photovoltaic farm, would you need to meet Missouri’s energy consumption?

I won’t go through all the calculations like I did in the previous posts. I’ll simply say that total energy consumption in Missouri was 557,946,666 MWh in 2014.

http://www.eia.gov/state/seds/data.cfm?incfile=/state/seds/sep_sum/html/rank_use.html&sid=US.

To satisfy this demand using wind farms would occupy 556 square miles. That’s a square less than 24 miles on each side. It is roughly the size of Iron County or St. Charles County. The largest county in Missouri, Texas County, is twice as large.

To satisfy the demand using solar photovoltaics would require solar farms occupying 4,819 square miles. That is a square 69 miles on each side. It is larger than any Missouri county, but only about 7% of the state.

As in previous posts, I must here caution that the examples I drew upon to construct my analyses, the Alta Wind Farm and the Topaz Solar Farm, are located in locations with strong wind and solar resources. Wind and solar farms elsewhere would be trying to reap lesser resources, and thus, would require more land to generate the same amount of power. Thus, my estimates represent the lower limit of the land that would be required. Still, they give some estimate of the size of the task involved.

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So what does all this rumination mean? First, let me reiterate that these are very rough “back-of-the-envelope” estimates. But they may be useful in demonstrating the size of the task required to convert to renewable energy.

Second, given current technology, it isn’t possible to cover the nation’s entire energy consumption using either wind power or solar photovoltaics. These technologies generate electricity, and a significant portion of the nations energy requires petroleum and natural gas. There are also engineering issues regarding the stability of the electrical grid that need to be solved

Third, it isn’t necessary to cover the nation’s entire energy consumption to have a significant effect. If we could derive 30%, 40%, 50% of the nations energy from renewables, it would make a significant impact on GHG emissions.

Fourth, converting to renewable energy would reduce air pollution, acid rain, and mercury poisoning, because all three come primarily from burning fossil fuel to create energy.

Fifth, it would also reduce our balance of payments deficit by reducing the amount of petroleum we have to buy from other nations. And it would enhance our energy security by making us less dependent on on foreign nations for our energy.

And sixth, it would take the money we currently send overseas to purchase oil and reinvest it here, in this country, possibly stimulating our own economy.

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My analysis suggests, that from a land coverage viewpoint, converting to renewable energy would require a lot of land, but not a prohibitive amount. Very large wind farms and solar farms have already been installed and are generating electricity. We would have to continue installing them, but the land exists.

We would have to have a national consensus that this is an appropriate way to use our land, however. And then the technological and economic issues would have to be resolved. Many of them already have been, but some remain, and those would be the issues that would make or break the project.

Too Little Real Estate on Rooftops?


To generate enough energy with rooftop solar panels to cover total energy consumption in the USA would require more than 6 times as much rooftop space as exists in the whole country.


In the previous two posts I have constructed “back-of-the-envelop” estimates of how much land you would have to use to satisfy the USA’s energy consumption with wind and solar power. I discovered that to do it with wind power would require at minimum wind farms occupying land the size of South Carolina. To do it with solar would require at minimum a solar farm at almost as big as the state of Texas.

What if solar was distributed around the country, on every building in the country? Obviously, not every building is suitable for solar power – they are shaded by trees or other buildings, they are oriented the wrong direction, or the slope of their roofs isn’t good for solar panels. Still, this is an interesting exercise to demonstrate the size of the requirement.

There are an estimated 113 million residential structures in the USA, totaling an estimated 180 billion square feet. There are an estimated 4.7 million commercial buildings totaling 68.5 billion square feet. Combined, they total 248.5 billion sq. ft.

https://www.aps.org/energyefficiencyreport/report/energy-bldgs.pdf.

The average new residence in the USA has 1.6 stories, and I will use that as my estimate for all housing. Thus, the average size of the roofs would be 180 billion / 1.6 = 112.5 billion = 112,500,000,000 sq.ft. This is probably an overestimate, because it does not account for multifamily buildings, but it will have to do.

https://www.census.gov/construction/chars/highlights.html.

I could find no data regarding the average number of stories for commercial buildings. However, there is data that buildings over 50,000 sq. ft. constitute half of the entire square footage, even though they represent only about 6% of all buildings. Obviously, some very large skyscrapers are going to account for a lot of internal square footage, but have comparatively small roofs. It’s just a guestimate, but I’m going to say that the square footage of commercial building roofs is only 1/4 that of their total square footage.

68.5 billion / 4 = 17.1 billion sq. ft. = 17,100,000,000 sq. ft.

https://www.eia.gov/consumption/commercial/reports/2012/buildstock/.

Thus, I estimate the total amount of roof space in the United States to be 112,500,000,000 + 17,125,000,000 = 129,625,000,000 sq.ft.

In 2014, total energy consumption in the United States was 98,385.2 trillion Btu. = 28,833,750,564 MWh.

http://www.eia.gov/state/seds/data.cfm?incfile=/state/seds/sep_sum/html/rank_use.html&sid=US.

The Desert Southwest has the strongest solar resource in the country, while northerly latitudes with lots of cloudy days have the weakest. The Wikipedia article on solar efficiency says that in Colorado, one could expect a solar panel to generate 440 kWh/sq.m./year, while in Michigan, one could expect 280 kWh/sq.m./year.

https://en.wikipedia.org/wiki/Solar_cell_efficiency.

The National Renewable Energy Laboratory provides a map of the solar resource across the country in kWh/sq.meter/day, but I could find no resource that gave a nationwide average. Since I am assuming solar panels installed on every building across the country, I must use a national average.

http://www.nrel.gov/gis/images/map_pv_national_lo-res.jpg.

“Eyeballing” the map, it is clear that Colorado does not represent the strongest solar resource in the country. On the other hand, the area that does have the strongest solar resource is relatively sparsely settled, meaning there are fewer buildings there than in, say, the Northeast. I will assume that these factors balance out, and that one may estimate the annual yield from solar panels by averaging the figures from Colorado and Michigan.

Thus, I estimate the average annual yield from a solar installations to be (440 + 280) / 2 = 360 kWh per square meter per year = 33.4 kWh per square foot per year.

Therefore, the total potential energy production that could be achieved by completely covering every roof in the country with solar panels would be 129,625,000,000 * 33.4 = 4,335,324,557,000 kWh, = 4,335,000,000 MWh.

The fraction of national consumption that could be met would be 28,833,750,564 / 4,335,324,557 = 15%. Put another way, we would need more than six times as much roof space as exists in the USA to meet our energy consumption using rooftop solar photovoltaic.

Some thoughts on where Missouri fits in all this and what it all means in the next post.

Cover Texas With Solar Panels?


To generate enough electricity with solar photovoltaics to cover total energy consumption in the USA, you would need land almost equal to the size of Texas.


My brother asked me how much land you would have to cover to satisfy the demand for energy in the USA using renewables. In the previous post I constructed a “back-of-the-envelope” estimate for wind power, finding that it would require a wind farms covering land roughly equal to the size of South Carolina. In this post, I construct a similar analysis for solar power.

The largest U.S. solar farm listed in Wikipedia is Solar Star, but it has not been operational long enough to have good generating statistics posted. I will use the Topaz Solar Farm, which Wikipedia lists as the second largest in the USA.

https://en.wikipedia.org/wiki/List_of_photovoltaic_power_stations#World.27s_largest_photovoltaic_power_stations.

Topaz is located in San Luis Obispo County, in California’s Central Valley. It is sited on 9.5 square miles, and its average annual generation is 1,100,000 MWh.

https://en.wikipedia.org/wiki/Topaz_Solar_Farm.

The amount of power generated per square mile is 1,100,000 / 9.5 = 115,789 MWh per square mile per year.

In 2014, total energy consumption in the United States was 98,385.2 trillion Btu. = 28,833,750,564 MWh.

http://www.eia.gov/state/seds/data.cfm?incfile=/state/seds/sep_sum/html/rank_use.html&sid=US.

To provide that much power would require 28,833,750,564 / 115,789 = 249,019 square miles.

How to put that in context? It is a square 499 miles on each side. It is just under the size of the state of Texas, it would occupy more than 90% of the state.

https://en.wikipedia.org/wiki/Texas.

Of course, Topaz is located in California’s Central Valley, which has a strong solar resource. The Desert Southwest has an even stronger one, however, and there is a great deal of land there. Still, some of the solar farms would be likely to be spread around the country. That would put some of them in areas with weaker solar resources. In addition, this analysis does not consider the need for excess capacity, redundancy, and storage, all of which would be required to cover times when the sun doesn’t shine, thus requiring even more land. Still, my estimate gives some idea of the size of the task.

Before you boggle at the size of the task, think of our current power generating infrastructure and how long it took us to create it. In 2014 there were an estimated 7,644 power plants in the USA.

https://www.eia.gov/tools/faqs/faq.cfm?id=65&t=2.

The first generating stations supplying power to the public were built in 1882, meaning that it took us 132 years to get to where we are now.

https://en.wikipedia.org/wiki/Power_station.

We have a big job in front of us, but if we give it our best effort, could we, would we, cover that much land with solar panels? I don’t know. But what if you relied on distributed solar photovoltaic power? What if you put solar panels on the roofs of buildings all across America? I will look at that next.

A Wind Farm the Size of South Carolina?


To satisfy demand for energy in the United States with wind power would require a wind farm the size of South Carolina.


My brother asked whether I had any idea how much ground would have to be covered with wind or solar farms to cover the energy consumption of the USA.

In reply, I produced the following analysis. This is obviously “back of the envelope” analysis, so be cautious how far you run with it. Still, I think it is interesting. Because some of the facts seem a bit counterintuitive, after each fact I’ve cited the source from which I got it. As you read, be sure to notice that wind power produces only electricity, yet I am comparing it to total energy consumption, which includes petroleum used in transportation.

According to Wikipedia, as of 2013 the largest wind farm in the world was the Alta Wind Energy Center, located on the eastern side of the Tehachapi Pass in the Mojave Desert. It is sited on 3,200 acres, has a rated capacity of 1,547 MW, and has a capacity factor of 30%.

https://en.wikipedia.org/wiki/Alta_Wind_Energy_Center.

A word here is needed to explain capacity factor. The rated capacity of a wind farm is its theoretical maximum generating power. However, because the wind doesn’t always blow, and turbines sometimes need maintenance, wind farms never generate their rated capacity. The average percentage of rated capacity that they actually generate is called their capacity factor. The Wikipedia article cites Alta’s capacity factor as 30%. The National Renewable Energy Laboratory says that the average capacity factor of onshore wind farms is 30-40%, with the best guess at about 37%. Capacity factor has been increasing due to improvements in turbine technology. I will use NREL’s figure.

http://www.nrel.gov/analysis/tech_cap_factor.html.

Thus, the actual capacity of Alta would be 1,547MW * 37% = 572 MW.

There are 8,760 hours in a year. Thus, the yearly production at Alta would be 572MW * 8,760 hours = 5,010,720 MWh.

Thus, production per acre would be 5,010,720 / 3,200 = 1,567 MWh per year per acre.

In 2014, total energy consumption in the United States was 98,385.2 trillion Btu. = 28,833,750,564 MWh.

http://www.eia.gov/state/seds/data.cfm?incfile=/state/seds/sep_sum/html/rank_use.html&sid=US.

Thus, the number of acres required to meet that consumption would be 28,833,750,564 / 1,567 = 18,401,574 acres = 28,752 square miles.

How to put that in context? It is a square 170 miles on each side, or approximately 40% the size of Missouri, or roughly equal to the size of West Virginia or South Carolina. You wouldn’t want to build one contiguous wind farm, but even if you did, it would fit in West Texas, the deserts of California, or the eastern plains of Montana with ease.

Now, Alta is located in the Tehachapi Pass, which has the strongest wind resource in the nation. Wind farms located elsewhere would be located in weaker wind resources. Further, because the wind does not always blow in a given location, you would have to build excess capacity elsewhere and power storage to cover those occasions, meaning that the actual land required would be somewhat larger than my estimate. Still, it is a starting point, and it gives some sense of the size of the task involved.

Before you boggle at the size of the task, think of our current power generating infrastructure and how long it took us to create it. In 2014 there were an estimated 7,644 power plants in the USA.

https://www.eia.gov/tools/faqs/faq.cfm?id=65&t=2.

The first generating stations supplying power to the public were built in 1882, meaning that it took us 132 years to get to where we are now.

https://en.wikipedia.org/wiki/Power_station.

We have a big job in front of us, but if we give it our best effort, what might we be able to accomplish?

In the next post, I will construct a similar analysis for solar photovoltaic.

Carbon Dioxide Emissions from Fossil Fuel – 2016

Figure 1. Source: U.S. Energy Information Agency.

Figure 1. Source: U.S. Energy Information Agency.

Climate change results from greenhouse gas (GHG) emissions. Inventories of U.S. GHG emissions consistently show that the majority of our emissions consist of carbon dioxide (CO2) from burning fossil fuel to create energy. This post looks at state emissions of CO2 from burning fossil fuel to create energy. Missouri did two GHG inventories in the early 1990s, but hasn’t done one since. Thus, this data is as close as we can come to assessing Missouri’s progress in reducing GHG emissions. The most recent data is through 2013.

Figure 1 shows that in Missouri CO2 emissions from burning fossil fuel to create energy grew 13% from 2000-2005, then began a decline through 2012 that reversed most of the growth. In 2013 they began increasing again. In 2013, CO2 emissions were 4.3% above the 2000 level.

 

Figure 2. Data source: U.S. Energy Information Administration.

Figure 2. Data source: U.S. Energy Information Administration.

Figure 2 shows similar data for Missouri and 4 neighboring states: Arkansas, Illinois, Iowa, and Kansas. Kansas and Illinois have reduced their emissions, though only by a small amount. The other states have increased emissions, Arkansas the most at 6.6%.

 

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Figure 3. Data source: U.S. Energy Information Administration.

Figure 3. Data source: U.S. Energy Information Administration.

Figure 3 shows change in CO2 emissions from 2000 to 2013 for all 50 states plus for the USA in total. Only 13 states have increased CO2 emissions over that period. The other 38 (list includes District of Columbia) have reduced CO2 emissions, in some instances by more than 25%. Nationwide, CO2 emissions are down 9.6%.

 

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Figure 4: Data source: U.S. Energy Information Administration (a and b).

Figure 4: Data source: U.S. Energy Information Administration (a and b).

Figure 4 shows 2013 CO2 emissions from Missouri by Sector. The blue columns show the raw data. CO2 emissions from generating electric power dwarf those from any other sector. Electric utilities, however, don’t generate electricity for their own consumption, they generate it for others to use. The EIA keeps data on the sectors into which utilities sell their electricity, and it can be used to distribute their CO2 emissions to their end use sectors. Almost all of it goes to the Commercial, Residential, and Industrial Sectors. The red columns show the results.

The data suggest that converting electricity generation to renewable sources would probably be the the single most effective way to reduce Missouri CO2 emissions. To reduce CO2 emissions by reducing energy consumption in end use sectors, the Residential, Transportation, and Commercial sectors would all be of similar importance.

The Intergovernmental Panel on Climate Change estimates that we need to make significant reductions in CO2 emissions – 50% or more – if we are to avoid the worst effects of climate change. All states have a long way to go; most appear to have made some progress. Not Missouri.

In the coming weeks, I’m going to offer some posts that suggest that completely converting to renewable energy would require covering huge amounts of the country with wind and solar farms, without even considering the need for redundancy, excess capacity, and storage, all of which would be required. It would be a huge task.

That notwithstanding, Missouri’s performance on this metric is shameful. The fact that it is a huge, difficult task means that we aren’t going to be able to accomplish this transition overnight. We need to get cracking, and there is no excuse for avoiding it. I fear we will pay a heavy price for our inaction.

Sources:

United States Energy Information Administration. 2016. Table 1: State Energy-Related Carbon Dioxide Emissions by Year (2000-2013). http://www.eia.gov/environment/emissions/state/analysis.

United States Energy Information Administration. “Sales and Revenue, 2013.” Form EIA 826 Detailed Data, Electricity. http://www.eig.gov/electricity/data/eia826/#salesrevenue.

Summary: Little Meaningful Progress on Energy in Missouri, 2016

In the previous three posts, I have analyzed energy consumption per capita, energy consumption per unit of State GDP, and consumption of energy produced from coal and from renewables. I have made this analysis for Missouri and for the surrounding states of Arkansas, Illinois, Iowa, and Kansas. As part of these posts, I have said that, because emissions from power plants burning fossil fuel to create energy are a principle cause of climate change, acid rain, air pollution, and mercury contamination, it is essential that we either reduce our consumption of energy, or we transition away from the use of fossil fuel, especially coal, to renewable energy.

I do not see signs that we are making good progress. Overall energy consumption has increased in all 5 states. Each individual’s consumption of energy (per capita basis) has significantly increased in some states, held roughly steady in some states, or slightly declined in some states. Considering the states as a group, there is NO strong trend towards decreasing per capita energy consumption!

Since 1997 the amount of energy required to produce a unit of State GDP has declined. That’s good, but the increase in GDP in all of the states has overwhelmed the effect of greater efficiency, resulting in increased consumption overall. This is like buying stuff on sale. The lower price is no doubt good, but we are buying so much more stuff that we are blowing our budget! And we will pay the price.

Four out of the five states have made progress transitioning from coal energy to renewable energy. But in only one, Iowa, is the progress really significant. In Iowa, the consumption of energy from renewables has soared: almost one unit of energy from renewables is consumed for every unit of energy from coal. But in each of the 4 other states, progress is slow; renewable energy consumption is still dwarfed by coal.

For Missouri, our per capita energy consumption has increased since 1980 from 289 to 314 trillion Btu per person. Energy consumption per dollar of State GDP has declined by 9.3% from 8.13 to 7.37 thousand Btu per dollar. However, our State GDP has increased, and total energy consumption has increased from 1,422.9 to 1,857 trillion Btu, a 30.5% increase. The ratio of energy from renewables to energy from coal almost tripled, from 4.7% to 11.7%. It is starting from such a small base, however, that the increase is not meaningful, and we still consume more than 7 units of coal energy for every unit of renewable energy. This is the worst ratio of any of the 5 states.

Sources:

In this 4-post series, data from the following data portals were used:

Missouri Energy Consumption, Clean Energy in My State, Energy Efficiency & Renewable Energy, Department of Energy, http://apps1.eere.energy.gov/states/consumption.cfm?state=MO&dollars=0#tecpd.

State Energy Data System (SEDS), U.S. Department of Energy. This is a data portal. Select Consumption Statistics, then Sector, Total end-use. Data downloaded 6/14/2016 from http://www.eia.gov/state/seds/seds-data-complete.cfm?sid=IL#Consumption.

Real GDP by State (millions of chained 2009 dollars), GDP & Personal Income, Regional Data, Bureau of Economic Analysis. Data downloaded 6/14/2016 from http://www.bea.gov/iTable/iTable.cfm?reqid=70&step=1&isuri=1&acrdn=2#reqid=70&step=10&isuri=1&7003=900&7035=-1&7004=naics&7005=-1&7006=05000,17000,19000,20000,29000&7036=-1&7001=1900&7002=1&7090=70&7007=-1&7093=levels.

Consumption of Energy from Coal and Renewables

Because the human contribution to climate change comes primarily from the burning of fossil fuel to create energy, it is essential that we do one of two things: reduce energy consumption, or switch to energy produced by renewable sources. It is especially important to get away from energy produced by burning coal, for it is the worst emitter of carbon dioxide and other pollutants.

Figure 1. Data source: Department of Energy.

Figure 1. Data source: Department of Energy.

In this post I will look at trends in consumption of energy produced from coal and from renewables. In the data from the U.S. Department of Energy, Renewable Energy includes Hydroelectric, Biomass, Geothermal, Solar, and Wind. Figure 1 shows consumption of energy produced from coal in Missouri and 4 surrounding states from 1960-2013.

(Click on chart for larger view.)

The first thing I notice is that until the mid-1970s and early-1980s, neither Arkansas nor Kansas show any appreciable consumption of energy from coal. I don’t believe it. I believe this is a problem with the data, perhaps related to delayed onset of reporting from these states. Missouri also shows a steep increase in consumption of energy from coal during the 1970s and 1980s, perhaps for the same reason.

During 1990s there was a significant increase in energy consumption from coal in all 5 states. Starting in the first decade of the 21st Century, consumption peaked and started to decline in 4 of them, but not in Arkansas. In 2013, however, energy from burning coal appears to have rebounded in 4 out of the 5 states (not Iowa).

Figure 2 shows the amount of energy consumed from renewables as a percentage of the energy consumed from coal. If this percentage is 50%, then half as much energy from renewables is consumed as energy from coal. If it is 100%, then equal amounts of each are consumed. If it is 200%, then twice as much energy from renewables is consumed as energy from coal. If we truly want to switch from coal to renewables, then we want this ratio to be well above 100%.

Figure 2. Data source: Department of Energy.

Figure 2. Data source: Department of Energy.

As noted above, there may be a problem with the coal energy reporting from Arkansas and Kansas. Thus, for Figure 2 I will only look at the years 2001-2013. All states have increased their consumption of renewable energy compared to coal energy, especially Iowa. In Iowa, the consumption of the two is approaching parity. Way to go, Iowa!

In Missouri, we have increased our consumption of renewable energy from 4.6% of coal energy to 11.7%. That’s a significant gain, but it still means that for every bit of renewable energy we consume, we consume more than 7 units of coal energy. Ugh, disgusting, the worst performance of any of the 5 states!

Sources:

State Energy Data System (SEDS), U.S. Department of Energy. This is a data portal. Select Consumption Statistics, then Sector, Total end-use. Data downloaded 6/14/2016 from http://www.eia.gov/state/seds/seds-data-complete.cfm?sid=IL#Consumption.

Energy Consumption per Unit of GDP Decreases in Missouri

In the previous post, I found that the amount of energy consumed per person per year grew until 2007, then decreased, and now has begun increasing again. Overall, there was no trend toward reduced energy consumption per person. This post looks at similar data, except instead of looking at energy consumption per person, I look at energy consumption per unit of GDP. A state’s GDP is the total amount of goods and services produced in the state during a given year.

Figure 1. Data source: U.S. Dept. of Energy and Bureau of Economic Analysis.

Figure 1. Data source: U.S. Dept. of Energy and Bureau of Economic Analysis.

Figure 1 at right shows how many thousands of British Thermal Units (Btus) of energy were consumed per dollar of Gross State Product for Missouri and four neighboring states: Arkansas, Iowa, Illinois, and Kansas. The data is for chained 2009 dollars; that is, it is adjusted for inflation, with 2009 being the baseline year. Notice that the data series begins in 1997, whereas the data series in the previous post begins in 1980. The Bureau of Economic Analysis changed its method for calculating state GDP in 1997.

(Click on chart for larger view.)

For all states, the number of 1000 Btus consumed per dollar of GDP has decreased over time. This means that we are consuming less energy per dollar of economic output: it is taking less energy to produce a unit of economic output. Compared to 1997, it declined most in Arkansas and Kansas, where it decline 25.13% and 22.32% respectively. It declined least in Missouri and Iowa, where it declined 9.32% and4.57% respectively.

Figure 2. Data source: Bureau of Economic Analysis.

Figure 2. Data source: Bureau of Economic Analysis.

Figure 2 shows the cumulative percent change in GDP from 1997 for the 5 states (cumulative means each year is compared to 1997). You can see that there has been a marked difference in economic growth between the states. Kansas, Arkansas, and Iowa have each grown their GDP by more than 30% since 1997, while Missouri and Illinois have been slower growers.

Cumulative change in State GDP was negatively correlated with change in energy consumption per capita in Arkansas, Missouri, Illinois, and Kansas, but positively correlated in Iowa. This means that in Arkansas, Missouri, Illinois, and Kansas, increased GDP was associated with lower per capita energy consumption, but not in Iowa. Why Iowa should differ from the other four is not immediately clear.

Well, this data set is small, and several of the correlations probably do not reach statistical significance. Thus, these analyses are interesting and suggestive, but far from conclusive. They suggest that economic growth may be associated with greater energy efficiency, both on a per capita and per unit of GDP basis. It would be a fascinating study for a university student.

Even if it is so, do not make the mistake of thinking that greater energy efficiency wipes out the increase in energy consumption that comes from increased population or increased economic activity. All 4 states showed increases in total energy consumption between 1997 and 2014. It is like buying stuff on sale: if you buy more stuff, it more than wipes out the savings you get from the sale.

It is an unfortunate fact that the very energy that enables our modern life style also creates many of our most serious problems.

Sources:

State Energy Data System (SEDS), U.S. Department of Energy. This is a data portal. Select Consumption Statistics, then Sector, Total end-use. Data downloaded 6/14/2016 from http://www.eia.gov/state/seds/seds-data-complete.cfm?sid=IL#Consumption.

Real GDP by State (millions of chained 2009 dollars), GDP & Personal Income, Regional Data, Bureau of Economic Analysis. Data downloaded 6/14/2016 from http://www.bea.gov/iTable/iTable.cfm?reqid=70&step=1&isuri=1&acrdn=2#reqid=70&step=10&isuri=1&7003=900&7035=-1&7004=naics&7005=-1&7006=05000,17000,19000,20000,29000&7036=-1&7001=1900&7002=1&7090=70&7007=-1&7093=levels.