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Friday, May 17, 2013

Global CO2 Summary -- The Keeling Curve, Seasonal CO2 Cycles, and Global CO2 Distribution


This blog post is a summary of several previous articles regarding atmospheric CO2.  This post consolidates and clarifies the previous posts.

Take a deep breath.   If you are about as old as me, that breath now contains about 25% more CO2 than your first breath when you were born, and about 42% more CO2 than when George Washington was president.  These numbers are changing rapidly, and have changed since I wrote my first post on this subject two years ago.

Abstract:
Atmospheric CO2 is rising globally, and has risen substantially in our lifetimes.  The CO2 content of the atmosphere is now higher than at any time in human history.    There is a seasonal cycle to CO2 concentration driven by growth and decay of plants in the Northern Hemisphere.  The CO2 cycle shows a strong fluctuation in the Northern Hemisphere and a very weak fluctuation of opposite polarity in the Southern Hemisphere.   Carbon isotopes show a similar global pattern of seasonal fluctuation and long-term change. 

A simple model can be constructed in an Excel spreadsheet using known volumes of agricultural production and fossil fuel consumption.  The model shows the global distribution of CO2, showing seasonal fluctuation and long-term increase identical to observed data.   The important thing is that the model was created using only data from human influences, although natural factors clearly exist and clearly affect atmospheric CO2.  The ease with which the model was generated, and the absence of quantifiable alternatives, clearly indicate that changes in atmospheric CO2 are primarily the result of human activities.

The Keeling Curve
The Keeling Curve is a set of CO2 measurements taken since 1958 on a mountaintop in Hawaii.  The measurements document seasonal CO2 change, and a long-term exponential rise in atmospheric CO2 concentration.   The Keeling curve at Mauna Loa fluctuates by about five ppm, peaking in the spring and reaching a minimum in the fall.  This week, the observatory announced that CO2 levels had exceeded 400 ppm for the first time at Mauna Loa. 
The Keeling Curve, as measured at Mauna Loa, has a seasonal cycle.  Atmospheric CO2 falls in the Northern Hemisphere summer, and rises during the Northern Hemisphere winter.  This is consistent with the absorption of CO2 by plants during the summer growing season, and the return of CO2 to the atmosphere through respiration or oxidation during the rest of the year.

Atmospheric CO2 has been measured at monitoring stations around the globe for a little over fifty years.
There is remarkable consistency of the long-term trend of CO2 across the globe, although details of the cycles differ.  The amplitude of the cycles varies dramatically by hemisphere and latitude.  The data on this chart are color-coded according to the monitoring stations shown above.

CO2 concentrations are rising everywhere on earth.   Superimposed on the rising curve is a cycle of seasonal fluctuation.  The fluctuation is strongest in the high latitudes of the Northern Hemisphere, and is weak in the Southern Hemisphere.  The following chart shows the seasonal CO2 cycle by latitude, with the long-term trend removed.

Long-Term CO2 Trends
Rising CO2 levels in the atmosphere are consistent with the volume of CO2 released by fossil fuels.  About 60%of the CO2 released by fossil fuels stays in the atmosphere; the remaining 40% is absorbed by earth systems acting as carbon reservoirs.  Examples include vegetation, the ocean, and precipitation of limestone.   We can compare the cumulative emissions to the observed change in atmospheric CO2, as seen in the following chart.
CO2 concentration in the Southern Hemisphere lags the rising concentration in the Northern Hemisphere.   The following chart shows the long-term trend at each CO2 monitoring station, with the seasonal cycle removed.



The average CO2 concentration in the Southern Hemisphere lags the Northern Hemisphere by about 2.7 ppm.  Looking at it another way, rising CO2 in the Southern Hemisphere lags the Northern Hemisphere by about 21 months.  
If we allocate fossil fuel emissions to each hemisphere by GDP, we see that 83% of CO2 emissions occur in the Northern Hemisphere.  Further, the 2.7 ppm difference in CO concentration between the hemispheres is a very close match to the annual excess CO2 emissions in the Northern Hemisphere.   The 21-month lag in the average CO2 level of the Southern Hemisphere represents the time required for atmospheric mixing of CO2 emitted in the Northern Hemisphere.

Pre-historic concentrations of CO2 are best known from air bubbles trapped in Antarctic ice.  Ice-cores have been recovered by drilling through the ice sheet.  The core was carefully dated by counting annual layers; by comparison with the deep-sea isotopic record; and by modeling the rate of ice accumulation.  Thousands of feet of core provide a continuous record going back 400,000 years.   Bubbles trapped in the ice are samples of the ancient atmosphere.   There is a small uncertainty regarding the time when the bubbles became permanently sealed, resulting in uncertainty of a few percent in the age of the trapped samples.   Current levels of atmospheric CO2, measured anywhere in the world, substantially exceed any sample recorded in ice cores for the past 400,000 to 800,000 years.
Pre-industrial levels of CO2 are estimated at about 280 ppm, based on ice-core data and a number  of 19th century chemical analyses.    An exponential function can be fitted to the data, beginning with 281 ppm CO2 in the year 1800, and fitting the modern data of the Keeling curve.   Atmospheric CO2 is growing exponentially for the simple reason that human population and the use of fossil fuels are growing exponentially.  The exponential growth of fossil fuels use was well documented by geologist M. King Hubbert in his classic paper on peak oil, gas, and coal, published in 1955.
The exponential function allows prediction of future levels of atmospheric CO2.   A global average of 400 ppm (seen at Mauna Loa this month) is expected to be reached in 2015.   According to the forecast, 450 ppm will be reached in the year 2031, and 500 ppm in the year 2042.
The Seasonal CO2 Cycle
We see some interesting features when we look at the seasonal cycle closely.  Northern Hemisphere cycles are high amplitude, while the Southern Hemisphere is very low amplitude.  The expected polarity reversal only occurs in high Southern latitudes (near the pole).  Readings from latitudes less than 30 degrees south (near the equator; Kermadec Islands and American Samoa) share the polarity of the Northern Hemisphere.

The seasonal cycle has an amplitude of 17 ppm at high latitudes in the Northern Hemisphere, and diminishes toward the equator.  Amplitude of the cycle in the entire southern hemisphere is much lower, about 1 to 2 ppm.  The following chart shows the seasonal CO2 cycle with the long-term trend removed.
The amplitude of the CO2 cycle at high latitudes has increased since 1975 by about 3 ppm, from about 14 ppm to about 17 ppm.  The increasing magnitude of the seasonal cycle probably represents increasing human agricultural activity, as human population increased from about 3.5 billion in 1970, to over 7 billion today.
Global cyclicity is dominated by seasons in the Northern Hemisphere.  Polarity of the cycle in low latitudes (near the equator) of the Southern Hemisphere follows the seasonal patterns of the Northern Hemisphere.   Polarity of the seasonal cycle is reversed near the pole in the Southern Hemisphere.

The seasonality and asymmetry of the cycles is quite apparent.  In the Northern Hemisphere, CO2 falls sharply in the three months of summer, followed by an increase during the fall, winter and spring.  The increase is initially sharp in the fall, then more gradual through winter and spring.

Southern hemisphere cycles are low amplitude and symmetrical.  Polarity of the cycles at low latitudes (near the equator) follows the polarity of the Northern Hemisphere.
The obvious question is what drives seasonal CO2 cycles, and why the Northern Hemisphere is dramatically different than the Southern Hemisphere.  The Northern Hemisphere contains only two-thirds of the earths landmass, but 88% of the human population, and produces 83% of the worlds GDP.   We will explore these factors by modeling the CO2 cycle, considering both fossil fuel consumption and the photosynthesis/oxidation cycle, but first we should look at changes in carbon isotopes in the atmosphere.

Seasonal Carbon Isotope Cycles
Carbon mostly occurs in two naturally occurring isotopes: C12 and C13.   C12 comprises about 99 percent of carbon in the world, while C13 comprises most of the other percent.*  

The light isotope, C12, is more easily taken up in plants during photosynthesis. Coal and oil, which are derived from wood and algae, are enriched lighter isotopes.  The light isotope is also more easily metabolized by bacteria, which produce natural gas.  CO2 produced by burning fossil fuel reflects the carbon composition of the fuel, and is isotopically lighter than CO2 in the atmosphere.

The ratio of C13 to C12 is expressed as a standard measure: dC13/C12 (usually pronounced "del-thirteen").  The measure represents the ratio of C13 to C12, as compared to a standard ratio, in tenths of a percent.  The isotopic record for CO2 since 1970 shows a steadily declining value of dC13/C12, showing progressively lighter isotopic CO2 in the atmosphere.  


This long-term observed trend of isotopically lighter CO2 is consistent with an increasing contribution of fossil fuels to atmospheric CO2.  A simple calculation combining the isotopic composition of fossil fuels and the atmosphere would predict an even larger decline in atmospheric dC13/C12.   The modest decline observed in the data shows involvement of other carbon sinks in the environment, exchanging carbon with the atmosphere and moderating the dC13/C12 decline in the atmosphere.

Carbon isotopes show a seasonal fluctuation very similar to the CO2 seasonal cycle.   Strong seasonal fluctuation is observed in the Northern Hemisphere, and weak seasonal fluctuation in the Southern Hemisphere.  

The Northern Hemisphere, with much greater fertile land area than the Southern Hemisphere, removes a significant volume of light carbon from the atmosphere during the growing season.   The isotope cycle shows an asymmetry similar to the asymmetry of the CO2 cycle.  The isotopic composition of the atmosphere in the Northern Hemisphere rises sharply in the summer, and then declines gradually as a result of atmospheric mixing and oxidation of the biomass following the growing season.
Additional modeling of the carbon isotope data would be valuable.  We can make a back-of-the-envelope calculation of the expected change in atmospheric  dC13/C12 based on fossil fuel combustion.  The calculation shows a larger expected change than observed in the atmosphere.  We know that atmospheric CO2 is moderated by the action of various carbon sinks, which exchange carbon with the atmosphere.  Assuming an average fossil fuel dC13/C12 of -25, and the atmospheric dC13/C12 of -7.5 (1977), would suggest a decrease in atmospheric dC13/C12 to -9.5, a change of -2.0.   The actual decrease observed is only to -8.2, a change of -0.7.  This suggests that the volume of the total carbon reservoir actively exchanging carbon with the atmosphere is about twice the size of the total carbon in the atmosphere.    A more detailed model would provide greater confidence in this conclusion.

*C14, an unstable radioactive isotope, occurs in trace amounts in nature.  The radioactive isotope is important for age-dating anything containing carbon, within about 10 half-lives of the isotope, or about 60,000 years before present.  C14 was also produced by nuclear weapons but has been rapidly decreasing in the environment since the cessation of above-ground nuclear testing. 

Modeling Atmospheric CO2
A simple but quantitative model can be constructed to show the global distribution of atmospheric CO2, using an Excel spreadsheet.  Inputs to the model include agricultural biomass, fossil fuel emissions, absorption of excess CO2 by carbon sinks, and atmospheric mixing between the Northern and Southern Hemispheres.  The final model begins in the year 1971, and yields a set of CO2 curves by latitude that closely matches the actual record.

Model inputs include known quantities of fossil-fuel consumption over several decades and known volumes of agricultural biomass.  The model allocates fossil fuel emissions and agriculture by hemisphere (N & S), and applies a simple mixing model to yield CO2 concentration at five latitude positions on the earth.  The annual oxidation of agricultural biomass is inferred and modeled to fit observations of the CO2 cycle.


From earlier observations, the model was constructed using the following parameters:
  • CO2 taken up by Plants during the growing season
  • Oxidation  of carbon in plants following the growing season
  • CO2 emissions from Fossil Fuels
  • Absorption of CO2 by carbon sinks (e.g. oceans)
  • Exchange of CO2 between Northern and Southern Hemispheres.

The CO2 seasonal cycle is dominated by the Northern Hemisphere, representing 67% of the earth's landmass, 90% of the human population (agriculture), and 83% of the industrial activity (GDP).  Modeling the cycle required consideration of fossil fuels and the photosynthesis/oxidation cycle.

Upon seeing the seasonal CO2 cycle in the Northern Hemisphere, my initial thought was that seasonal burning of fossil fuels accounted for much of the fluctuation.  Monthly consumption of oil, coal, and natural gas does show a seasonal fluctuation, with the correct polarity for the observed CO2 cycle.  However, fossil fuel consumption in the Northern Hemisphere produces only a 0.5 ppm seasonal cycle in atmospheric CO2, as compared to the 17 ppm cycle observed in actual data.  The following chart of seasonal CO2 emissions (with long-term growth of CO2 removed) was calculated from 2009-10 data from EIA and the BP Statistical Review of World Energy.  
The alternative consideration is that vegetation drives the seasonal CO2 cycle. In the summer, plants take up carbon through photosynthesis, and atmospheric CO2 declines.  Immediately following the growing season, plants give CO2 back to the atmosphere through oxidation, and CO2 rebounds sharply.

The model for seasonal CO2 uptake through photosynthesis was constructed beginning with the volume of biomass generated through agriculture.  Agriculture generates about 140 gigatonnes of biomass every year.
http://www.unep.or.jp/Ietc/Publications/spc/WasteAgriculturalBiomassEST_Compendium.pdf
After adjustments for the portion in the Northern Hemisphere (83%), moisture content (50%), carbon content (45%), and conversion to CO2 (3.67x) we can calculate about 96 gigatonnes of CO2 removed from the Northern Hemisphere atmosphere during the summer growing season.  Thus, during the growing season, CO2 in the Northern Hemisphere falls sharply.



The model distributed agricultural carbon and fossil fuel use according to economic output by hemisphere.  The Northern Hemisphere represents 83% of global economic output, and the Southern Hemisphere represents 17% of global economic output.
The following chart shows the monthly scheduling of photosynthesis, oxidation and fossil fuel consumption in the model for the Northern Hemisphere.


This model produced a surprisingly easy fit to the high latitude data of the Northern Hemisphere (see below).  There are no fossil fuel emissions in the model at this point, and the long-term trend of rising CO2 has been removed from the real-world data by subtracting an annual rolling average from the monthly data.

In modeling the Southern Hemisphere, I found that 17% of global agricultural biomass produced CO2 fluctuations that were far too large to match the data in the Southern Hemisphere. I found a good match by using only 5% of global agricultural biomass.   The chart below shows the model parameters.

Here is the modeled match to high-latitude Southern Hemisphere CO2, using 5% of global agricultural biomass.  It seems likely to me that the Southern Hemisphere photosynthesis/oxidation cycle is overwhelmed by CO2 mixing from the Northern Hemisphere, thus requiring a smaller volume to match the data.
A simple mixing model was generated to represent the cycles observed in intermediate latitudes.   The chart below shows a 50%-50% mixture at the equator, and 70% - 30% mixtures at intermediate latitudes.   As shown in the data above, the cycles of intermediate latitude (pink line) in the Southern Hemisphere follow the seasonal pattern of the Northern Hemisphere.
The final model runs from the year 1971 to 2009.  As a starting point, the model used values for the average CO2 concentration of the Northern and Southern Hemispheres in 1971, of 327 and 325 parts per million CO2, respectively.


The photosynthetic model, which was developed for the year 2009, was adjusted for earlier years as a function of global population. This resulted in cycles with increasing amplitude through the range of the model.  Agricultural production was assumed to vary directly as a function of population, but incremental agriculture was assumed to displace natural vegetation.  Growth of CO2 intake through photosynthesis was increased at a rate of 50% of incremental agricultural output (back-calculated from the 2009 model).


Although the fossil fuel input is much too small to account for the seasonal fluctuation in CO2, the long term effect is significant.  Carbon dioxide from fossil fuel emissions was added according to estimates from IEA and the BP statistical review of world energy.  Annual figures in these reports were scheduled on a monthly basis by analogy to US monthly consumption of coal, natural gas, and oil.  The volume of fossil fuel CO2 emissions was reduced by 40% to reflect the volume of CO2  absorbed by carbon sinks.

As previously noted, rising CO2 in the Southern Hemisphere lags CO2 in the Northern Hemisphere by a period of about 22 months.  The model was constructed to transfer half of the fossil fuel CO2 of the Northern Hemisphere to the Southern Hemisphere, using a lag of 22 months to represent the necessary mixing time.

Despite the general simplicity of the model, the resulting CO2 curve shows a reasonable correlation to actual data recorded across the global range of latitudes, and after 38 years of CO2 addition and subtraction, the model concludes at the appropriate concentrations of CO2 across the globe.

The most important conclusion from modeling global CO2 is that both long-term and seasonal change in atmospheric CO2 can be easily modeled using only inputs from human activities.
Other conclusions are as follows:

2)  Surprisingly, fossil fuel use does not have a significant effect on seasonal CO2 cycles.   Known volumes and timing of fossil-fuel emissions do not match the cyclicity in CO2 observations.
3)  Photosynthesis in the Northern Hemisphere dominates the seasonal CO2 cycle.  The model produced a good match to Northern Hemisphere seasonal CO2 using only agricultural biomass.  However, it is understood that natural biomass is also significant.  The agricultural volume is a proxy for the net volume of CO2 taken up and released by vegetation, in a more complex system.
 4)  Oxidation of vegetation occurs quickly.  Three quarters of the net seasonal biomass is oxidized in the first three months following the growing season.  Specifics on how and where this oxidation occurs would add confidence to the model.  Falling leaves and burning agricultural waste may account for some of the rapid oxidation following the growing season.
5)  The Northern Hemisphere dominates both seasonal and long-term trends in atmospheric CO2.  Global CO2 data and the model provide evidence for atmospheric mixing, to explain the 1) varying amplitude of seasonal CO2 cycles by latitude, 2) the lag of rising CO2 in the Southern Hemisphere, and 3) the gradation in phase of the cycles observed at intermediate latitudes.  The evidence of the degree and timing of atmospheric mixing may be useful in other areas of climate research.
6)  Calculations comparing isotope changes from fossil fuel emissions to the observed carbon isotope record suggest that the total reservoir of environmental carbon (including the atmosphere) is about three times the volume of carbon in the atmosphere.
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This post is a summary of previous posts about atmospheric CO2.  Additional details about the work can be found in these posts.

1)  The Keeling Curve
2)  The Keeling Curve and Seasonal Carbon Cycles
3)   Seasonal Carbon Isotope Cycles
4)   Long-Term Trends in Atmospheric CO2
5)   Modeling Global CO2 Cycles



References:


Global CO2 concentration data in this report is credited to C. Keeling and others at the Scripps Institute of Oceanography, also Gaudry et al, Ciattaglia et al, Columbo and Santaguida, and Manning et al.  The data can be found on the Carbon Dioxide Information Analysis Center.
Data for CO2 released by fossil fuels is available from EIA CO2 Emissions from Fuel Consumption,
http://www.iea.org/co2highlights/co2highlights.pdf
And the BP Statistical Review of World Energy:
http://www.bp.com/sectionbodycopy.do?categoryId=7500&contentId=7068481

Monthly data for US fossil fuel consumption were taken from the EIA website:


Global population figures from 1970 - 2010 were taken from Wikipedia.
The estimate for annual global biomass, circa 2009 was taken from a UN report:
http://www.unep.or.jp/Ietc/Publications/spc/WasteAgriculturalBiomassEST_Compendium.pdf

Wednesday, February 20, 2013

Wealth Inequality in America: Young versus Old


We have a problem of inequality of wealth distribution in America, and the problem is increasing.  The issue is not simply that the wealthiest 1% control too much wealth; rather, the problem is the distribution of wealth between the young and the old.   In a variety of ways, the young are suffering financially compared to previous generations.  Young people have less wealth, earn lower wages, pay higher taxes, and face higher education costs and higher unemployment than the previous generation.  Furthermore, the young will inherit the government debt incurred by their parents.  In this context, 22 percent of American children are growing up in poverty, defined as family income providing less than half of basic necessities.  Forty-five percent of American children are growing up in low-income households.

In America, it has always been expected that each generation would provide a better life for the next generation.  In our time, we have failed.
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Let’s look at the distribution of household wealth in America. 
Wealth in America is concentrated among the middle-aged and elderly.  Eighty-nine percent of national wealth is held in families aged 45 and over.  Families under the age of 35, raising young children, hold less than 3% of American wealth.  
Young families did not begin the decade with a lot of wealth.   Median family wealth for families under 35 hit a peak at $16,000 in 2004, but declined to $9300 by the end of the decade.
Most of America suffered financial losses through the Great Recession.  But young families suffered the most severe decline in net worth.  Changes in Median household wealth, representing typical families, are shown in the chart below.  Household wealth was reported in constant 2010 dollars, adjusted for inflation.

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Wages and salaries have been in a relative decline since the 1960s, as a greater share of GDP has accrued to owners of capital, and a smaller share accrued to workers.   As we saw earlier, financial assets are concentrated in the middle-aged and elderly, who are receiving a larger share of GDP, while the working youth are receiving a smaller share.  The following chart shows wages and salaries as a percentage of GDP, in constant 2005 dollars.
Wages and salaries also declined disproportionately for the young in the last decade.


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I hope to add to this post in the coming days and weeks.
Further considerations are the distribution of income, payroll taxes supporting the elderly, unemployment and the cost of education.
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References:
Survey of Household Net Worth


US Census Statistical Abstract

US Census Bureau Publication:  Income, Expenditures, Poverty and Wealth

22 percent of children are in households beneath the poverty level, defined as $23,000 income for a family of four, or less than half of what is needed to meet basic expenses.   45 percent of children are living in low-income households.

Monday, February 11, 2013

Vladimir Putin and Julius Caesar


Here is something of a slightly lighter character for this blog.

A number of years ago, a traveling exhibit of Roman statuary came to one of the major museums in Houston.   Among many other beautiful statues, there was a long line of busts; the head and shoulders of many of the Roman emperors.  At the beginning of the line was Julius Caesar.

As I stared at the head of Julius Caesar, I had a strange feeling of familiarity about the face.  It was the face of someone contemporary, someone famous.  Finally I had it!  Julius Caesar resembles Vladimir Putin!  Or, alternatively, Vladimir Putin resembles Julius Caesar.

Take a look.
Vladimir Putin                       Julius Caesar
To me, there's a resemblance:  the high forehead, the slight hollow in the cheeks, the slight twist to the mouth, as if he is waiting for the right moment to say something.

The resemblance raises another question; whether people come in archetypes.  To me, it seems that certain patterns among people recur, perhaps controlled by groups of genes which are inherited together.  Sometimes, physical appearance, abilities, personality, attitudes and gestures occur as a correlated set.  We recognize these archetypes in our humor, in our dramas, in our cartoons.   We look at a new colleague and say silently to ourselves, "Oh, no, not again.  One of THOSE."

Perhaps evolution selected certain patterns which persist in populations today.  A small, near-sighted man, introverted, patient and clever with his hands, might have been a flint-knapper, making arrowheads and spear points for the clan.  Large and strong men, courageous and far-sighted, might have been the hunters.  A woman with sharp mind and memory, and fascinated with plants might have been a healer.  And ambitious, authoritarian leaders have been a part of mankind as long as people have organized themselves in groups.


Tuesday, February 5, 2013

The Net Worth of America


Total personal wealth in the United States in 2010 was about 58 trillion dollars.  That is our net worth.  That’s everything:  houses, farms, real estate, bank accounts, stocks and bonds, mutual funds, cars; net of all liabilities, debts and mortgages.   This number is important, because it gives us a relative measure to other big numbers, for example, the national debt, or the unfunded liabilities of the Social Security system.   Incomprehensibly big numbers become comprehensible when we can compare them to other big numbers of the same order of magnitude.   And our net worth is a useful yardstick for recognizing when other big numbers are absurd.

Our total net worth is fairly easy to calculate.   I took the number of households according to the age of the Head of Household from the 2010 Census.  I found the mean and median net worth according to the age of the Head of Household from survey data published by the Federal Reserve.  From the mean figures, we can see the total wealth by the age group, and from the median figure, we see the wealth of a typical family.  My estimate of the $ 58 trillion total net worth of the United States compares favorably to the $50 trillion  published by Harvard in 2004, and $ 54 trillion published for 2009 in Wikipedia (but unreferenced).   By comparison, global household net worth in 2000 was estimated at $ 125 trillion, adjusted for purchasing power (calculated from data in Davies, et al, 2007). 

The household net worth figure includes the value of most of American businesses, through ownership of stock and mutual funds by individuals, including 401k and other retirement plans.  It does not include the value of trusts, churches, non-profit organizations, co-operatives, and pension funds; or the net worth of local, state and federal governments; or of publically owned infrastructure.   But for this discussion, let’s consider that household wealth represents the net worth of the United States, and disregard the possibility of selling Alaska back to Russia, or Louisiana back to France.

Distribution of Wealth by Age
Wealth in America is concentrated in middle-aged and elderly households.  About ninety percent of the wealth in America is held by people over 45 years old.   About sixty-five percent of the wealth is held by people over 55, and thirty-three percent by people over 65 years old.  A chart shows the mean and median distribution of net worth by age of household; the wide separation between the mean and median lines indicates the skewness of the distribution of wealth in America.

The median net worth for young families (< 35 years old) is $9,300, less than one-third of the global average household wealth ($33,800, Davies et al, 2007).    The deteriorating economic condition of many families can be seen by comparing the median net worth by age across through the first decade of the century.  The 2008 recession had a significant impact on family wealth in all households except the most elderly.


The concentration of wealth in older households has consequences for children in America.  Households headed by people under the age of 35 have the lowest net worth, and of course, these are the households raising small children.  Twenty-two percent of American children are living in households below the poverty line, which is defined as having less than half of the income needed to cover basic expenses.  Forty-five percent of American children live in low-income households.

Net Worth of America, by Comparison to Other Big Numbers
We can compare a few other economic numbers to the $ 58 trillion in household wealth, which provides a yardstick for seeing the significance of other big numbers.
  • United States' externally held ("publicly held") debt is about 12 trillion dollars.   Including government debt held by other government agencies (representing the Social Security trust fund), the total US federal debt is about $ 16 trillion, or 27 percent of our total net worth.
  • The total value of publically traded stocks, representing the market value of all major companies in America, was about $ 12 trillion in 2010, or about 20% of household wealth.    Total market value of all stocks today is about $ 16 trillion.
  • The United States currently has a negative net international investment position.   Foreign interests hold a net $ 2 trillion dollars of American wealth, greater than the assets which Americans own overseas.
  • The United States money supply (M2) is about $ 10.4 trillion.   This measure of money supply has increased from about $ 7.7 trillion in late 2008, and increase of $ 2.7 trillion.  The increased money supply is largely a result of the Federal Reserve program termed “quantitative easing”.  
  • The Wall Street Journal recently published an article by Republicans Chris Cox and Bill Archer, which claimed that unfunded liabilities for Social Security and Medicare are accruing at a rate of $ 7 trillion per year.   According to Cox and Archer, unfunded liabilities for these programs now total about $ 87 trillion.  If correct, the unfunded liabilities of these programs befitting senior citizens greatly exceed the total net worth of all households in America.
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References:

Survey of Household Net Worth

US Census Statistical Abstract

US Census Bureau Publication:  Income, Expenditures, Poverty and Wealth

Wealth Inequality: Data and Models
Marco Cagetti, Federal Reserve Bank of Chicago; University of Virginia

World Distribution of Household Wealth, Davies, J.B., et al, University of California, Santa Cruz, 2007.
Year 2000 World Household Net Worth, 3.7 billion adults, average net worth $33,800, adjusted for purchasing power.   Calculation shows global net worth of 125 $ trillion, adjusted for purchasing power.

22 percent of children are in households beneath the poverty level, defined as $23,000 income for a family of four, or less than half of what is needed to meet basic expenses.   45 percent of children are living in low-income households.

Chris Cox and Bill Archer, WSJ, Nov. 28, 2012
The actual liabilities of the federal government—including Social Security, Medicare, and federal employees' future retirement benefits—already exceed $86.8 trillion, or 550% of GDP. For the year ending Dec. 31, 2011, the annual accrued expense of Medicare and Social Security was $7 trillion.


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Thursday, December 6, 2012

Job Recovery after the Great Recession: It's Different This Time


On the following unemployment chart, it appears that the 2008 recession was no different than earlier recessions.  There is the same saw-toothed pattern on the unemployment chart as seen in earlier recessions.   But a closer look at the data reveals some troubling issues with the recovery.    It is indeed different, this time.

In terms of job recovery and GDP growth, the “Great Recession” of 2008 was deeper and longer than any other recession since World War II.    Recovery from the 2008 recession continues to be weak, and is unlikely to restore either employment or GDP to pre-recession trends before the next recession.

The rate of job recovery after recent recessions has been weaker than following earlier recessions.   The weakness is seen clearly in three recessions since 1990, and may indicate structural changes in the economy.   A closer look shows that the recent weakness is part of a longer-term trend; job recovery following recessions has been declining since World War II.
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Let’s look at some graphs.

Employment Recovery from the 2008 Recession

The most striking thing about the current recovery is that employment has not recovered to pre-recession levels, even three and one-half years after the official end of the recession.    Another interesting observation form this chart is the progressive change in the shape of the recovery from the 1981 recession to the 2008 recession.   Employment recovery from each successive recession is slower, as indicated by flatter curves following the bottom of the recession.
Here is another chart showing the depth and duration of the 2008 employment recession.   Job losses and recovery are measured in percent of peak employment prior to the recession.    Recoveries from the 1990, 2001, and current recessions are flatter and broader than following earlier recessions.
A time-series chart also shows the depth and duration of employment recessions since 1959.  Recent recessions are broader, showing a slower recovery of jobs than after earlier recessions.
Long-term unemployment is dramatically higher than at any time since World War II. 
Not surprisingly, the quality of jobs has also deteriorated, with higher numbers of workers accepting part-time rather than full-time unemployment.

GDP

Persistent unemployment has been a drag on GDP.    Although GDP is now increasing at about the same rate as before the recession, there is a gap of about $1 trillion between actual GDP and potential GDP, as calculated by the Congressional Budget Office. 

 A graph presented by the Washington Post shows the growth rates required to restore GDP to the previous trend.  At growth rates of only 2%, the gap will not close.   Bill Gross, recognized as one of the brightest financial experts of our times, recently stated that he expects that 2% growth and persistent unemployment are the “New Normal” for the United States economy.
The entire WP slide show is worth seeing:  http://www.washingtonpost.com/wp-srv/business/the-output-gap/index.html

Structural Change in the Economy

We’ve seen how job recovery after recent recessions has been weaker than following previous recessions, indicated by flatter curves in figures 1 &2.    Let’s look at another presentation of figure 2, centering the curves on the bottom of the job recession.  
 All recessions prior to 1981 had full job recovery in less than 11 months; the latest three recessions have flatter recovery profiles, and require much longer to reach full recovery.    If we calculate the rate of job recovery (slope of the positive line) from the chart above, we see a long-term trend.    The rate of job recovery following recessions has been in a secular decline since World War II.  
 This trend would seem to indicate a progressive structural change in the economy since World War II.  Jobs which disappear during recessions are becoming harder to replace.  The manufacturing sector, the workhorse of the American economy is shrinking.  Manufacturing jobs are disappearing as work is outsourced overseas and American factories are increasingly automated.  New jobs are increasingly sophisticated, and time for workers to acquire specialized training and skills, leading to the progression we have seen in job recovery following recessions.
The Hamilton Project created a useful interactive graphic showing the jobs growth and time required to return the country to full employment.   The graphic allows the viewer to choose a rate of job growth, and see the time required to recover jobs lost in the recession.   Data from the most recent Dept. of Labor shows that employment growth averaged 153,000 jobs/month in 2011, and 157,000 jobs/month so far in 2012.   If we assume a long-term trend of 155,000 jobs/month, and place this data in the Hamilton Project calculator, we see that the jobs gap will not close before the year 2025.  I recommend trying a few scenarios on this interactive calculator (http://www.hamiltonproject.org/jobs_gap/).

The most recently reported jobs growth is 146,000, for November 2012; October jobs were revised downwards from 171,000 new jobs to 138,000 jobs.  It's clear we are falling short of the 220,000 jobs needed to restore jobs lost in the recession by the year 2020.
The average interval between recessions since WWII has been 5 years, 9 months; the maximum interval between recessions was 10 years, between 1990 and 2000.   We are already 3 years and 6 months past the official end of the Great Recession.  Considering the very real economic headwinds facing the nation, It is extremely unlikely that we will restore the jobs lost in the Great Recession before the beginning of the next recession.  The job recovery following the 2008 recession is indeed different, this time.
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References and Credits:

Charts prepared by the blogger at http://www.CalculatedRiskBlog.com were especially helpful in preparing this blog post.

Charts at these sites were also particularly useful in providing insights into the 2008 Recession recovery.:
    The Washington Post graphic "Why it doesn't feel like a recovery"
    Hamilton Project jobs creation graphic
    The Center for Policy Priorities, The Legacy of the 2008 Recession: Chartbook


2008 Recession recovery
GDP loss during the 2008 recession is deeper than previous recessions; recovery after recession slower than previous recessions.
“Why it doesn’t feel like a recovery”
Jobs Creation Interactive Graphic;  Most recent data:  October, 171,000 jobs added
 Women in Workforce

Recession unemployment rate by demographics; NYT interactive graphic
Unemployment graph by different recessions
US Labor Demographics and Forecast
Urbanomics Blog: Job Growth, charts, etc.
Bill Gross interview; the “New Normal” for the US economy is 2% growth and persistent unemployment.  Workers, already displaced by cheap Asian labor, are now being replaced by machines.
US GDP growth in 2012 Q3 was 1.9%, excluding Inventory growth.               
Employment growth averaged 153,000 jobs/month in 2011, and 157,000 jobs/month so far in 2012.


November job growth is 146,000; October jobs revised downward from 171,000 to 138,000.






Monday, October 1, 2012

Shale Gas Production, Resources, and Prices


Gas production from conventional reservoirs has been falling since 1973, exactly as predicted by M.K.Hubbert in his landmark “Peak Oil” paper published in 1956.   Offshore natural gas production (1970–2000) moderated the decline but did not reverse the trend. 

Unconventional gas reservoirs (“tight” sands and coal-bed methane) began to contribute significant production about 1980.   Significant volumes of shale gas production began in the early 2000s, and grew from 2 TCF in 2008 to over 4 TCF/year in 2010.   Some of the production growth was the result of the “land-rush” of lease acquisition.  Leasing terms often required immediate drilling to maintain the lease.  Many wells were drilled simply to satisfy leasing terms, without regard for the primary economics of the project. This created a supply bubble, driving prices below equilibrium for profitability.
The contribution of shale gas helped to push total gas production to about 25 TCF per year, well above the Hubbert Peak of 1973 (22.7 TCF/year).  (Note: EIA gas production volumes are somewhat higher than data from Jean Laherrier; probably due to different handling of volumes re-injected for gas storage and oil recovery.   EIA gives current production over 27 TCF per year.)

Production from unconventional sources is simply the continuation of the long-term trend of diminishing returns in producing oil and gas.  Technology and economics allow profitable production of low-productivity wells, and many more wells are needed to supply the market. 
The growth in supply caused a decline in average well-head prices from over $8 per mcf (thousand cubic feet)  to about $2.50 per mcf.   Current prices have recovered somewhat to about $3.00 per mcf.
The shale gas revolution is the product of two technologies.  The first is horizontal drilling, which was developed in the1980s, and the second was the ability to controllably fracture the rock surrounding the horizontal wellbore, which was developed in the early 2000s.   Hydrofracturing a well to stimulate production is an old technology, widely used since the 1970’s.   The innovation that allows commercial production of shale gas is technology to distribute the fractures evenly along the entire length of the wellbore.  Previously, fracturing only occurred at the weakest point, leaving 90% of the horizontal wellbore unproductive. 

The new technology opened up huge prospective areas in the United States.   Initial estimates of total potential were staggering.  In 2010, estimates from the EIA for technically recoverable resource from lower 48 shales were over 800 TCF (trillion cubic feet).  Of that volume, the EIA attributed 410 TCF to the Marcellus shale of the Appalachian states.

By 2011, however, some of the bloom was off the rose.  Every exploration play tends to go through phases.  It is almost a law of nature that the best wells are drilled first.   Geologists drill prospects with the best potential before drilling average prospects.   Predictably, engineers, management and financial analysts extrapolate the results of those early wells to the entire field or play.  No one pays attention to the warnings of the geologist until the disappointing wells are drilled.

Disappointing results from shale gas began to be documented in the financial media in 2011.

In 2012, two major studies by the USGS reduced expectations for shale gas
First, the USGS published the technically recoverable resources from the Marcellus shale, with a mean estimate of 84 TCF.   This was an increase from the estimate of 2 TCF published by the USGS in 2002, but substantially below the 410 TCF published by the EIA.  (This compares to about 22 TCF consumed annually in the United States.)  Conflict between the two agencies is almost palpable in the USGS press release, which noted testily:  “USGS is the only provider of publicly available estimates of undiscovered technically recoverable oil and gas resources of onshore lands and offshore state waters.”

USGS issues new estimate of technically recoverable reserves for Marcellus Shale
commentary:

Secondly, the USGS published a study of well productivity across all of the shale gas plays in the United States.  The USGS estimated the average EUR (Estimated Ultimate Recovery) per shale gas well at 1.1 BCF/well, substantially less than major operators, who published estimates of 4 to 5 BCF/well. 

USGS revised estimates of well production downwards, relative to claims my major producers:
commentary:

The major operators (e.g. Chesapeake) are probably doing better than average.   The leading companies are using the technology appropriately and have come up the learning curve on drilling and producing these wells.  By contrast, many of the inexperienced competitors who jumped into this play lack the engineering expertise to perform well.   The USGS “average” reflects the experience of both groups.  Still, the USGS numbers are sobering, and suggest that a slow-down in the growth of production is likely, until the issues of productivity are clearly settled.

Despite the downgrade in expectations, the EIA still expects shale gas production to expand to nearly one-half of U.S. gas production by 2035. 
The low gas prices that have hovered at or below $3/mcf have depressed exploration for gas in both conventional and unconventional plays.   Anecdotally, drillers in the Gulf of Mexico have stopped pursuing new gas, both in deep plays on the continental shelf and prospects in deep water.   Offshore gas is simply not profitable at $3/mcf.   However, I expect the current high production rates to keep prices in the range of $3 to $4 for one or two years, until excess production and excess gas in storage is depleted.   In a longer range outlook, I expect gas prices to rise to the $5 to $6 range in the medium term of 3 to 5 years. 

The energy equivalence of a unit of gas (mcf) to a barrel of oil is about 6 to 1.   In other words, 6 thousand cubic feet (mcf) of gas produces about 6 million Btu (British Thermal Units) of energy, which is roughly equivalent to the energy content of a barrel of oil.  By comparison to oil, energy from gas is incredibly cheap.  At today’s prices ($3.51/mcf gas, and $91.58/barrel oil), natural gas is only 23% of the cost of oil.  Natural gas prices could double, triple or quadruple and still represent a savings with respect to a barrel of oil.

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General Information

Shale Gas plays in the lower 48 (USGS)

Warnings on disappointing Shale Gas results:

USGS issues new estimate of technically recoverable reserves for Marcellus Shale
commentary:

USGS revised estimates of well production downwards, relative to claims my major producers:
commentary: