# 100-Year Flood, 500-Year Flood: Real Risk Probabilities

When the Army Corp of Engineers and NFIP came up with the 100-Year Flood and 500-Year Flood designations, it’s almost as though they wanted to confuse the public. With Hurricane Harvey, much has been written on the meaning of the terms 100-year flood (it means a 1% chance of flooding in a single year), and the term 500-year flood (a 0.2% chance of flooding in a single year). While these basic definitions are correct, they don’t really help homeowners, whose question is: what’s the chance that my house will flood while I own it?

In the case of the 100-year flood zone, this means that the chance of flooding is at least 1% in a single year. But what if you plan to own your home for 30 years? In this case, you have a 99% of NOT flooding each year, but you’ve got to NOT flood for all 30 years. The probability of NOT flooding over 2 years is 0.99 * 0.99, and thus the probability of not flooding over 30 years is 0.99^30, or 74%. This means that the home has a 26% of flooding over the 30 years in question.

Of course, that doesn’t take into account the change in probabilities resulting from a combination of climate change and reckless development in most American cities. According to Kenneth Trenbeth, a scientist at the National Center for Atmospheric Research, “What used to be a 500-year event has become a 50- or 100-year event.” With this in mind, we can lay out the following table of homeowners’ flood risks:

 Flood Probability Over 10 Years Flood Probability Over 30 Years 100-year flood zone 10% 26% 100-year flood zone, climate-change adjusted (to 10-year flood) 65% 96% 500-year flood zone 2% 6% 500-year flood zone, climate-change adjusted (to 50-year flood) 18% 45%

The flood risks over 30 years likely exceed many homeowners’ assumptions even before accounting for climate change – the climate-change adjusted risks make flooding within flood zones a virtual certainty! Homeowners in these areas are well advised to buy flood insurance, which is an incredible value as it is priced by the government below fair value. Homeowners not in, but simply near the 100-year floodplain, should realize that THEY are now likely in the true 100-year flood risk area, while their neighbors in the floodplain are likely at much greater risk.

Think that the probabilities can’t possibly have shifted that much? Consider that parts of Houston have had 3 500-year flood events since 2001 – Harvey, the 2016 Tax Day Flood, and Hurricane Allison. The chance of having one such “500-year” flood in 16 years is around 3.2%, but three such events? It’s less than 0.15% if these are really 500 year floods! [1] The reality is that 500-year floods are likely more than 10 times more common than the old statistics indicate, and homeowners should plan accordingly.

[1] The chance of 3 or more 500 year floods is equal to 100% minus the chance of 0, 1, or 2 such floods. The chance of 0 floods is 96.85%, and the chance of exactly 1 flood is roughly 3%, leaving less than 0.15% for the other potential outcomes (which drop off very rapidly because of the 0.2% chance happening multiple times).

# List of Warmest Years on Record Globally

9 of the top 10 hottest years globally have occurred over the past decade, when measured using three different global temperature data sets. The top 20 warmest years have all occurred during the last 24 years.

How do the record high temperatures over the spring and summer in the US compare on a global basis? While numerous articles on global temperature trends exist [1], I decided to go to the primary temperature data sources to find out. Below I have created a list of the 20 warmest years on record globally, using three data sets: NASA GISS, the UK Meteorogical Office, and NOAA / UAH [2]. While the three data sets vary in length from 40 to 150 years, the 20 warmest years turn out to have all occurred in the last 24, making it possible to construct an average temperature for the hottest 20 years.

Rank Year Global Avg Temp (F) [3]
1 2010 58.28
2 1998 58.22
3 2005 58.15
4 2007 58.06
5 2002 58.05
6 2009 58.04
7 2003 58.03
8 2006 58.02
9 2011 57.98
10 2004 57.90
11 2001 57.89
12 2008 57.75
13 1995 57.70
14 1997 57.68
15 1999 57.65
16 1990 57.64
17 1991 57.64
18 2000 57.64
19 1988 57.59
20 1987 57.54

Since this is a divisive topic prone to political obfuscation, it’s worth noting that both the NASA Goddard Institute and the UK Meteorological Office officially support the theory of anthropogenic global-warming, while the research scientist responsible for the University of Alabama-Huntsville data set does not support this theory.

[1] This has been a popular topic: Economist, Live Science, ArsTechnica, Science Daily, and Wikipedia

[2] Here are the original data sets:

Hadley Meteorological Centre UK: http://www.metoffice.gov.uk/hadobs/hadcrut4/data/download.html#regional_series

[3] The data in this blog post was constructed by averaging data from the three underlying data series. The NASA GISS estimate of global mean baseline temperature of 14 degrees Celsius was used to adjust the temperature deltas provided by the original data series in order to show global mean temperature in Fahrenheit terms here.

Here is my excel spreadsheet with data and calculations.

# Will Solar Power Meet World Electricity Demands?

Proponents have looked to solar power as a potential panacea to the world’s current and future energy needs, while critics note that solar power still provides less than 1% of the world’s electricity. While wind power has grown to scale much faster, conventional wind technology has much less capacity to scale than solar power, and the theoretical limits on solar power are significantly higher [1]. When might solar power fulfill the hype and generate much of our electricity? Solar energy has grown at a rapid clip since its infancy in the 1970’s, from 0 to 20GW (nameplate capacity) in 2009. How much of worldwide electricity demand will solar be able to fulfill if it maintains this growth rate?

Total solar power capacity continues to grow at 20-25% per year, a rate of growth it has maintained for decades. It’s not surprising that solar photovoltaic technology is advancing rapidly, as it is a cousin of traditional semiconductor technology. For almost four decades semiconductor technology advanced according to Moore’s Law, with chips roughly doubling in transistor density (and speed) every 18 months. At a 20% annual rate of growth, installed solar capacity would rise from 21 GW in 2009 to almost 6000 GW by 2040. This install base could generate 12 trillion kilowatt-hours of electricity per year, or two-thirds of today’s worldwide electricity consumption [2]. However, the EIA estimates that by 2040 worldwide electricity demand will hit 35 trillion kilowatt-hours!

Even assuming that solar energy installations grow at a 20% clip for three decades, the total install base will not be sufficient to meet world energy demands. Despite the industry’s rapid growth, replacing a hundred years of fossil-fuel based generation capacity by mid-century may be close to impossible. Nonetheless, if solar energy manages to scale on this trajectory, its contribution would still be enormous, and would likely bring total renewable generation to over 50% of all electricity.

Can it be done? Did anyone in the 1960’s believe that a 2010 phone would have more processing capacity than all the world’s computers combined?

[1] From Without The Hot Air – all wind power resources worldwide could supply a significant fraction of total power needs, while solar energy in the Sahara alone could theoretically supply all world energy needs.

[2] The EIA International Energy Outlook shows current worldwide electrical demand of roughly 18 trillion kilowatt-hours, with this figure growing to 35 trillion kWh by 2035 by www.usbgeeks.net.

# Hybrid Economics Part II

In part I of this post, I outlined a number of variables that impact the cost-benefit of buying a hybrid-electric vehicle.

First, the spreadsheet model.

To recap, here are the variables included in the model, with the default assumptions made:

• Price of gasoline = \$3/gallon
• Annual mileage driven = 12k/year
• Standard-car MPG (mileage of the same car or similar car without hybrid technology) = 20mpg
• Hybrid MPG / electric MPGe = 100 mpge
• Risk-free discount rate = 3%
• Projected annual increase in gasoline prices = 5%
• Hybrid price premium = \$18k
• Length of car ownership = 8 years

There’s one more important variable to add to this list:

• Time savings from reducing gas station stops = 300 minutes, or 5 hours per year

Time savings can be a huge hidden savings for upper-middle class and wealthy Americans (those able to afford a car like the Chevy Volt). If the value of a Volt driver’s time is \$50/hour (equivalent to a 100k/yr salary), then eliminating a single gas station stop of 10 minutes is worth over \$8. Ten minutes may sound long for a stop at the gas station, but is not unrealistic when considering total time lost leaving and re-entering a normal commute.

Using the assumptions provided above, we find that the total fuel and time cost savings of driving a Chevy Volt for eight years are around \$9000. Since the Chevy Volt costs \$18,000 more than a comparable loaded Chevy Cruze, it’s not yet cost competitive, even with government tax credits and with time savings taken into account.

Key Conclusions:

• Gas prices of \$7 per gallon are required to make the Chevy Volt cost-effective at current prices (without the government tax credit)
• Once plugin hybrid premiums drop to \$9000, they will be cost-competitive.
• The Nissan Leaf currently offers buyers significant savings WITH the \$7500 tax credit according to frontier high speed internet, as the total savings of \$16,500 exceeds the \$12,000 price premium. Even without the tax credit, the Leaf is very close to being cost-competitive at current pricing.

# Hybrid Economics Part I

With the arrival of the Chevy Volt and Nissan Leaf, and plans for many more hybrid and electric vehicles in the works, I’d like to revisit the cost-benefit of purchasing a hybrid (or electric) vehicle. Externalities* (pollution) and cool-factor aside, a hybrid vehicle is a cost-effective purchase only if the total present value of gasoline savings equals the price premium paid for hybrid technology. A number of factors impact the calculation:

• Price of gasoline
• Annual mileage driven
• Standard-car MPG (mileage of the same car or similar car without hybrid technology)
• Hybrid MPG / electric MPGe
• Risk-free discount rate
• Projected annual increase in gasoline prices
• Hybrid price premium
• Length of car ownership

In part II of this post, I’ll attach a detailed spreadsheet to analyze this problem. But it’s possible to come up with a quick best-case estimate without a whole lot of math. Assume that gas costs \$3 a gallon, that we drive 15,000 miles per year, that a comparable non-hybrid gets 30 MPG, and that the risk-free discount rate (currently in the 3% range) and gas price inflation roughly cancel out. In a year we’ll have to buy 500 gallons of gas for \$1500. If we own the car for eight years, that makes \$12,000 in maximum possible gas savings – if the hybrid were to use no fuel at all!

The Chevy Volt and Nissan Leaf both appear to cost significantly more than \$12,000 above vanilla gasoline competitors. At \$40,280, the Chevy Volt is more than 18k more than a loaded Chevy Cruze, and that’s with GM selling at a loss! The Nissan Leaf is similarly 15k more than a maxed-out Nissan Versa. Perhaps this is not surprising, as new technology often commands a price premium, and early adopters may be happy to pay that premium.

In Part II I’ll introduce the complete model, and add one more variable that may tip the balance back in hybrids’ favor. Stay tuned…

*Why leave out externalities like pollution from the analysis? True externalities are outside the traditional economic transaction, and so a car buyer doesn’t take them into account when making a purchasing decision. In reality, a large number of hybrid buyers purchase the vehicles precisely because they value the environmental benefits of the vehicle. But in order to scale past that crowd, hybrids will have to be cost-effective for the rest of consumers – so it makes sense to leave this out environmental benefits here.

# Fuel Efficiency: Modes of Transportation Ranked By MPG

Building on a previous post on the energy efficiency of various foods, I decided to create a list of transportation modes by fuel efficiency.  In order to compare vehicles with different passenger capacities and average utilization, I included both average efficiency and maximum efficiency, at average and maximum passenger loads.

The calculations and source data are explained in detail in the footnotes. For human-powered activities, the mpg ratings might appear high, but many calculations omit the fact that a human’s baseline calorie consumption must be subtracted to find the efficiency of human-powered transportation. I have subtracted out baseline metabolism, showing the true efficiencies for walking, running, and biking.

For vehicles like trucks and large ships which primarily carry cargo, I count 4000 pounds of cargo as equivalent to one person. This is roughly the weight of an average American automobile (cars, minivans, SUVs, and trucks).

The pmpg ratings of cars, trucks, and motorcycles are also higher than traditional mpg estimates, since pmpg accounts for the average number of occupants in a vehicle, which according to the Bureau of Transportation Statistics is 1.58 for cars, 1.73 for SUVs, minivans, and trucks, and 1.27 for motorcycles.

List of Transportation Modes By Person-Miles Per Gallon (PMPG)

 Transport Average PMPG Max PMPG Bicycle [3] 984 984 Walking [1] 700 700 Freight Ship [10] 340 570 Running [2] 315 315 Freight Train [7] 190.5 190.5 Plugin Hybrid [5] 110.6 350 Motorcycle [4] 71.8 113 Passenger Train [7] 71.6 189.7 Airplane [9] 42.6 53.6 Bus [8] 38.3 330 Car [4] 35.7 113 18-Wheeler (Truck) [5] 32.2 64.4 Light Truck, SUV, Minivan [4] 31.4 91

[0] I used these conversion factors for all calculations.

[1] Walking: A typical person expends roughly 75 calories to walk a mile in 20 minutes. An American burns about 30 calories just to exist for 20 minutes, so the net expenditure for walking is 45 calories per mile. One gallon of gasoline contains roughly 31,500 kcal, so 45 calories is 0.0014 gallons of gas. Thus the average American has a walking efficiency of 700mpg. This estimate is higher than that given elsewhere – the crucial difference is that you have to subtract out baseline metabolism, since an American consumes over 2100 calories a day just to stay alive.

[2] Running: The calculation is similar to [1]. Here we assume a 6 minute/mile pace, which burns 1088 calories per hour, or 109 calories per mile, and 100 net calories per mile. 100 calories is 0.003 gallons of gas, for a fuel efficiency of 315mpg.

[3] Bicycles: Bicycling at 10mph requires 408 calories per hour, or 40.8 calories per mile, which is 32 net calories per mile. This yield an mpg rating of 984, higher even than walking!

[4] Automobiles: The Bureau of Transportation Statistics has done the heavy lifting for us, calculating BTU per passenger-mile for cars, light trucks, and motorcycles. For cars, the latest (2008) data point is 3501 BTU / passenger-mile, or 0.028 gallons per passenger-mile, which equals 35.7 pmpg (BTS assumes 1.58 passengers on average, so this equates to 22.6 mpg). Using the same BTS data, average pmpg for light trucks is 31.4, and for motorcycles is 71.76. For max pmpg, we use a max passengers of 5 for cars and trucks, and 2 for motorcycles. To do this calculation from the BTS data, we first divide the avg. pmpg by the avg. passenger count, and then multiply by the max in each case.

[5] 18-Wheelers: For 18-wheel rigs, BTS data shows an average diesel mpg of 5.1. This equates to a gasoline mpg of 4.6, using 125,000 btu / 138,700 btu as the gas / diesel energy ratio. The weight limit for trucks on most roads is 80,000 lbs, of which 55,000 might be the max load given a truck weight of 25,000 lbs. To convert load to passengers, I assume 4000 lbs per passenger, since that’s roughly the weight of a passenger vehicle. A 50% (average) loaded truck counts for roughly 7 passengers, and a full load counts for 14. Using these factors, average pmpg is 32.2 and max pmpg is 64.4.

[6] Plugin-Hybrids: With the exception of the Prius Hymotion conversion, plugin hybrids like the Chevy Volt have yet to reach market, and have not yet had a final mpg designation. Consumer Reports achieved 67 mpg with the Hymotion Prius, though Hymotion and many owners claim 100 mpg is possible. Using 70 mpg, and adjusting this by the 1.58 average passenger count, the Hymotion Prius has an average pmpg of 110.6, and a maximum pmpg of 350.

[7] Trains: While all trains have similar underlying efficiencies, passenger trains in the US are much less efficient in practice because of poor utilization. BTS calculates Amtrak efficiency at 1745 BTU per passenger-mile, which equates to 71.6 pmpg. Amtrak traveled 267 million car-miles in 2007, which equals to 16 billion potential passenger miles if the average car holds 60 passengers. In 2007 Amtrak consumed 10.5 trillion BTU of fuel, or 659 BTU per available passenger mile. Amtrak’s max pmpg is therefore 189.7 (if somebody would just ride it).

Freight trains consume 328 BTU to move a ton one mile. Using 4000 lbs of freight equals one passenger, this equals 656 BTU per passenger-mile, or 190.5 pmpg.

[8] Buses: At average passenger loads, buses achieve 3262 BTU per passenger-mile, or 38.3 pmpg. Per BTS data, buses average 6.1 diesel mpg, or 5.5 gas mpg. With a full load of roughly 60 passengers, a max pmpg of 330 is possible. The huge difference in average and max pmpg implies that buses are usually almost empty – perhaps smaller mini-buses should be used by more fleets.

[9] Airplanes: Airplanes flying domestic routes average 2931 BTU per passenger-mile, or 42.6 pmpg. The overall domestic load factor in 2008 was 79.6%, so at max capacity a plane might achieve 53.6 pmpg.

[10] Ships: In a previous post I found that shipping over water (by barge) costs one-third of shipping by rail. This implies that water based shipping is also roughly triple the efficiency in energy terms, since energy is one of the key cost drivers in transportation. This provides a rough estimate of 570 pmpg. According to this post, the world’s largest container ship travels 28 feet on a gallon of residual fuel oil (149,690 BTU or 1.2 gallons of gas). This equals 0.004 mpg. Per Wikipedia, the ship can carry 11,000 14-ton containers, or 77,000 passenger-equivalents using our 4000 lb conversion rate. Thus pmpg is 340 for this ship.

# The ROI Payback of Tossing Incandescents For CFLs

After moving into my current home, I discovered that the previous owners had left dozens of light bulbs for the various fixtures in the house. I was happy to know that I wouldn’t have to restock for a while. In the interim, compact fluorescent light bulbs have become inexpensive, and LED bulbs have begun to become economical as well. While I have realized for some time that CFLs are a good investment with a short payback period, I have yet to replace my bulbs. At some level, it feels wrong to throw out all those light bulbs. What is the real return on throwing out a working bulb and replacing it with a CFL?

I calculated the payback period in days when replacing a 60W bulb with a CFL, assuming \$0.1 per kWh electricity and \$0.97 per CFL, which is what I paid at Home Depot last weekend [1]. I performed the calculation for a variety of usage assumptions, and this graph shows the results:

The payback on moving to CFLs is quite fast, a few weeks for high usage bulbs, and several months for bulbs used only one hour per day.

The first graph begs the question – how frequently does a light bulb need to be used to justify replacing it with an incandescent? Assuming that a 10% return on investment is desired, that the CFL will last 5 years [2], and that electricity costs \$0.10 per kWh, I calculate that you should replace any bulb used more than 9 minutes per day [3].

That’s a pretty low bar, lower than I expected. As CFL prices have dropped, and light quality has improved [4], there aren’t many arguments left for sticking with incandescents. And for the lazy, switching to CFLs will decrease the frequency of light bulb changes, resulting in lower effort as well.

Conclusion: Throw out your light bulbs and replace them with CFLs today. The quality of CFL light output is now pretty close to incandescent, and you are burning money every day you wait!

I replaced roughly 40 light bulbs last weekend, in the middle of writing this post. For the most part it’s worked out – the light quality is decent, but the CFLs still take some time to get to full intensity, and I may have to replace a few that flicker due to dimmers on the switches.

[1] While this was a sale price, CFL prices have been falling steadily and the standard price at HomeDepot.com is still only \$1.25 per bulb (see the 12 pack of 60W-equivalent TCP brand bulbs available at this writing).

[2] Many CFLs are warrantied for 7-9 years, and claim 8000-12,000 hours of working life. Five years is thus a conservative estimate, but takes into account the fact that CFL quality control is still an issue, so that some percentage of bulbs will be defective.

[3] The calculations in my spreadsheet are linear with respect to purchase price – if you pay \$2 for a CFL instead of \$1, then you should replace all bulbs used for more than 18 minutes a day, and so on.

[4] That CFL light quality has improved is my personal opinion – look around on the web, and you will find hundreds of articles disparaging CFL light quality. I think they’ve come a long way, however, and the soft-white (2700K) bulbs available now do an acceptable job imitating incandescent soft-white bulbs.

# List of Foods By Environmental Impact and Energy Efficiency

Which foods have the smallest (and largest) energy footprint, thereby having the most environmental impact? While most people probably realize that meat products have a larger energy and environmental impact, the degree of difference isn’t immediately clear. How much difference does it make if you’re a vegetarian, or if you’re almost entirely carnivorous? The following list provides a rough estimate of the energy required to produce different kinds of foods, in order from least to most energy intensive. Forever body transformation is a source for many of the numbers below:

Table 1: List of Foods By Energy Required to Produce One Pound

 Food Energy (kWh) to Produce 1 Lb Corn [1] 0.43 Milk [2] 0.75 Apples [3] 1.67 Eggs [4] 4 Chicken [5] 4.4 Cheese [2] 6.75 Pork [6] 12.6 Beef [7] 31.5

Table 2: Energy Efficiency of Various Foods (Measured as Food Calories / Energy Used in Production) [8]

 Food Calories / Lb Energy Efficiency Corn 390 102% Milk 291 45% Cheese 1824 31% Eggs 650 19% Apples 216 15% Chicken 573 15% Pork 480 8.5% Beef 1176 4.3%

The data above indicate the huge difference in energy required from one end of the food spectrum to the other. Roughly twenty-five times more energy is required to produce one calorie of beef than to produce one calorie of corn for human consumption. Dairy products are actually fairly energy efficient, as they are very dense in calories. Vegans may indeed be able to boast that their diets use 90% less energy than the average American’s, and even those who eat only eggs and dairy can lay claim to significant energy efficiency.

At the same time, food production and consumption amounts to only about 10% of first-world energy consumption, so even the most parsimonious eater can reduce their total energy footprint by around 9% through diet alone. The big culprits remain transportation, heating, and cooling, and while diet modification can help, energy conservation efforts should focus most heavily on these areas.

[1] It’s possible to estimate the energy involved in corn production very accurately, since corn energy intensity has been closely scrutinized by both proponents and critics of the corn ethanol industry. This Berkeley study compares energy intensity estimates from two sources, one pro and one anti-ethanol. Using an average of the two studies’ data yields an estimate of 30,000 BTU energy consumed per gallon of ethanol produced. From the same study, about 2.75 gallons of ethanol are produced per bushel of corn, which means that one bushel of corn required 82,500 BTU. One bushel of corn is 56 pounds of corn kernels, so one pound of corn kernels requires 1473 BTU for production. This is equivalent to 0.43 kWh.

[2] For milk, the estimates provided in Without The Hot Air Chapter 13 are utilized, with this conversion used for fluid ounces of milk to weight. The estimates for cheese are also taken from the above chapter, with the numbers simply proportionally adjusted from kg to pounds.

[3] From Table 3 in this study in Nature, we see that the annual energy input for a hectare of apple trees is 500,000 MJ, or 56,230 kWh at 3.6 MJ per kWh and 2.47 acres per hectare. According to this article, 800 bushels of apples per acre appears normal, which is 33600 lb of apples at 42 lb of apples per bushel. This equals 1.67 kWh per pound of apples.

[4] Here are the estimates for eggs, taken from Without The Hot Air page 77. Using a standard of eight eggs to a pound, convert from metric to English measures and arrive at the 4kWh estimate.

[5] Chicken is examined in detail on Without The Hot Air page 79, and I use that estimate, converted to kWh per pound.

[6] For Pork, I use McKay’s estimates from page 77, and convert them for each animal. McKay estimates that a 65kg human burns 3kWh per day, or 0.0462 kWh / kg / day = 0.021 kWh / pound / day. McKay uses a pig lifespan of 400 days, and thus notes that if you want to eat a pound of pork every day, 400 lb of pig must be alive at any given time (one pound for each day, so that the rate of pig production matches the rate of consumption). McKay further estimates that only two-thirds of an animal can be used for meat, so we actually need 600 lb of pig to generate one pound of meat per day. 600lb * 1 day * 0.021 kWh / pound /day = 12.6 kWh for a pound of pork.

[7] Beef is calculated exactly as for Pork above, except that a cow lives for 1000 days instead of 400 days. 1000 lb / 0.66 (wastage factor) * 1 day * 0.021 kWh / pound / day = 31.5 kWh for a pound of beef.

[8] Calorie data was taken from caloriecount.about.com, and kcal (food calories) were converted to kWh for energy efficiency calcs. We simply convert the calories in one pound of each food into kWh, and then divide that number by the energy required for production of one pound of that food.

[9] How can corn have an energy efficiency higher than 100%? This means that the energy that human beings put into the process of growing, distributing, and eating corn is less than theenergy provided to the human body by the corn. The hidden factor here is sunlight – corn plants are drawing energy from the sun for free, and storing that energy, which humans later consume.

# US Economic Energy Efficiency 1950-2008

How is energy related to economic output? Energy is the underpinning of all modern society, as our economy and society would grind to a halt without gasoline, electricity, and other similar forms of energy [1]. Since energy plays such an important role in the nation’s economic health, the Energy Information Administration (EIA) has been measuring energy inputs into the economy for decades, and uses this data to calculate the economic energy efficiency (energy intensity) of the economy. The EIA measures the BTU used to produce one dollar of GDP over time. By this measure the US economy has become significantly more efficient over the last six decades, using half the energy to produce a dollar of output today than it did in the 1950’s:

As the above graph illustrates, the amount of energy (in BTU) required to produce a dollar of GDP has been dropping steadily, from close to 20,000 BTU in 1949 to 8,500 BTU in 2008. Just how fast has that drop been occurring?

This graph illustrates the rate of annual efficiency gains from 1950 onward, measured as the increase in dollars of GDP per thousand BTU [2]. During and after periods of high energy prices, energy efficiency rose quickly, as in the late 70’s and early 80’s, and again from 2002 until today. Overall, the mean rate of annual energy efficiency gains in the economy is 1.44%. At this rate, the energy required to produce a dollar of GDP drops in half every 50 years [3]. Can the US do better? At its peak in 1981, annual energy efficiency rose by 5 percent. Sustained annual increases of 5% would halve the energy intensity of the economy in less than 15 years! In other words, the US could maintain its current \$14 trillion dollar economy while using half the coal, oil, and natural gas that it uses today.

More realistically, the US might attempt to match the efficiency gains it racked up from 1978 to 1985, when annual efficiency increases averaged 3.3%. Sustaining this pace would halve energy intensity every 20 years. With even the more optimistic predictions of the EIA and IEA indicating a potential oil supply crunch in the next few decades, reducing energy intensity is key to maintaining and improving world prosperity. For the US, many of the easy gains are gone, as outsourcing manufacturing improved US efficiency by moving energy intensive industries overseas. Further decreases in energy intensity will have to come from actual increases in energy efficiency, and from an increase in the quantity and relative value of low-energy products like online services and media [4].

What about a pessimistic scenario like peak oil? How much impact can energy efficiency have in this scenario? Assume that the US can halve BTUs per dollar of GDP again by 2050, through a combination of increases in thermodynamic efficiency and increases in low-energy goods and services [4]. This would only require a 1.75% annual increase in efficiency, not far above the historical average of 1.44%. A number of peak oil predictions indicate that oil production will be roughly half what it is today by mid-century. But energy efficiency increases alone could enable the US to sustain its current GDP at mid-century on half the oil! While a world of zero economic growth is alien today, it’s a far cry from the end of civilization as we know it. As long as renewable energy growth exceeds population growth, continued economic growth may even be possible in this worst of cases.

[1] When thinking about how a lack of energy would affect US life, imagine America without electricity, gasoline, and natural gas. The US as we know it would cease to exist. Also, strictly speaking, gasoline is not energy, but it and other fuels are often measured in terms of the BTU of combustion energy they contain.

[2] Here’s the spreadsheet with data. It makes more sense to look at the percentage rate of increase in dollars per BTU, instead of looking at the rate of decline in BTU per dollar. People can interpret positive growth rates more easily than negative decline rates, and so the data was graphed in this way. To do so, I inverted the data from the first graph (from BTU/dollar to dollar/BTU), and then measured the rate of change of the resulting data.

[3] At a compound annual growth rate 0f 1.44%, in 50 years the number of dollars per BTU will roughly double, which is the same as halving the number of BTU required to produce a dollar of GDP. 1.44^50 ~= 2. Similarly, an annual growth rate of 5% doubles efficiency in 15 years.

[4] The energy efficiency of an economy can be improved in two ways. First, the thermodynamic efficiency of energy production, conversion, and distribution can be improved, as discussed in this blog post. Thermodynamic energy efficiency can only be improved so much, as hard physical limits exist. But an economy’s energy intensity also decreases when goods and services that use energy less intensively become more common. For instance, email is much less energy intense than physical mail, and has in fact replaced a large percentage of physical mail. The entire media industry is much less energy intense than it was in the 19th century, when all media had to be consumed in person (at a concert/theater) or on paper. Consider also the difference in energy content between two different services: a \$200 flight, and a \$200 salon visit. If the US economy evolves in a way that makes it less energy-intense while still providing benefit to its citizens, this will generate substantial “economic” energy efficiency.

# Is Local Really Greener Than Global?

Environmentalists have decried the long supply chains of the globalized world, asserting that they are responsible for significant excess pollution and waste when products could be produced locally instead. With the recession and rising unemployment, support for buying domestic also takes on a political slant, as cries for protecting local jobs mount. But when it comes to the environment and emissions, which is really worse? Is the simple assumption that buying local is always better correct?

Cost of Shipping by Land, Air, and Sea [1]

 Transport Mode Cost (Cents Per Ton-Mile) Emissions (CO2 Grams Per Ton-Km) Airplane 81 570 Truck 27 252 Railroad 2.24 200 Barge/Ship 0.72 52

Shipping goods by plane is obviously most expensive, but it’s the difference between shipping by truck, rail, and ship that stand out. Shipping a ton of freight by truck is 35 times more expensive than shipping it over water. While railroads are much more efficient than trucks, shipping by rail is still three times as expensive as barge shipping. Goods from China travel roughly 7000 miles on ship to reach California, but that distance can be covered at the same cost as only 200 miles by truck! Since most store-bound products in the US travel via truck, it’s clear that the ocean voyage is a smaller part of globalization’s environmental impact than is commonly suspected.

In calculating the environmental footprint of wine, National Geographic and LiveScience have both noted a study on the same phenomenon: a New Yorker causes less environmental impact by drinking a bottle of wine from Bordeaux than by drinking a bottle of California wine!

These calculations don’t take into account the environmental impact of production, which varies by product and country of origin. A worker in the US uses far more energy (and creates more pollution) than a worker in China, simply because his standard of living is higher. Even if a US factory is run more efficiently, a US worker owns more cars, a larger home, and drives longer distances to work than a Chinese worker who lives in a dormitory at her factory. While an exact calculation of emissions by product is laborious, it’s easy to see that the cut-and-dry notion that local goods are more environmentally friendly is questionable at best.

[1] Data for the table were source from the  US Bureau of Transportation Statistics. Since shipping cost data were not available for all transportation modes after 2001, 2001 data were used. The emissions data comes from Dr. Vino’s wine study, which in turn sourced these figures primarily from the Greenhouse Gas Protocol.