Why I Have My Head In the Clouds

Last night I took the dog out just as an excuse to admire the sky. To fully appreciate it I didn’t immediately reach for the camera, I waited for my mind to clear, bent my neck back and the sky’s beauty sent my consciousness adrift with the clouds. To a passerby, it looked as if I was waiting for my dog to sniff out the scene while I was being temporarily distracted. I realize there are practical priorities in life, but it’s not as if in our leisure we don’t indulge in frivolous activities. Why then did I feel a need to camouflage my intentions from my neighbors? Is it more evidence that we are mostly psychologically disconnected from our natural surroundings?

 

The gap is indeed psychological since our lives heavily depend on clouds in ways that are less obvious than others. The amount of water that evaporates from lakes and oceans and which condenses into clouds does not entirely fall back over bodies of water when the clouds’ droplets get large enough. Some of the rainfall naturally irrigates farmlands or helps build up reservoirs, some of which are used for hydroelectricity. Clouds also sporadically dampen sunlight and contribute to temperature gradients over both land and water. The ensuing pressure gradients lead to wind which mixes water and distributes nutrients. By spreading pollen, wind also assists the reproduction of many trees. The main ingredient of clouds along with carbon dioxide absorb infrared, making the earth suitable for life.  It’s also why the dry, cloudless sky of deserts creates such a pronounced temperature gradient between night and day.

The clouds I saw, the ones portrayed above, are known as cumulus congestus. These sometimes grow into thunderclouds, which give clouds yet another important function. They fertilize the soil since lightning converts nitrogen into nitrate. Annually 1011 kg of nitrogen are naturally rendered useful, a figure that is coincidentally almost identical to the annual amount artificially produced for agriculture.

Clouds play an important role in the carbon cycle, converting some of the carbon dioxide released from volcanic activity, respiration, industry and transportation into carbonic acid. The acid then weathers rock, transforming silicates and releasing hydrogen carbonate. In oceans, organisms convert water-soluble hydrogen carbonate into insoluble carbonate which can be used for shells and exoskeletons.

Without impurities, clouds cannot form. They need dust from a variety of inanimate and living sources to act as condensation nuclei. But unfortunately they can also carry excessive impurities such as soot and sulfates that irritate lakes, trees, lungs and hearts. According to one hypothesis, particulate pollution increases the number of clouds formed. Since condensation does not affect the total amount of H2O present in the atmosphere, the presence of more clouds leads to a cooling effect from their ability to block sunlight. Having more clouds dampens but does not eliminate the degree of warming from greenhouse gas pollution. But in order to better predict increases in average global temperatures, clouds are currently included in climate models.

The one cloud-type that has not yet been included in models is the cumulus. It comes in several varieties at high, mid and low altitudes. Some of the mid-latitude cumulus evanesce; other types, as we mentioned, grow into cumulonimbus. And while we wait for climate scientists to optimize their models, the rest of us should continue to work at mitigating global pollution and at preparing our cities for the more intense or more common microstorms, hurricanes, and floods that will ensue for a while, regardless of our current actions.

But we should also contemplate clouds in idle moments. The positive experience provides us with one more reason why it’s worth the gargantuan effort to rescue ourselves not just from pollution but from the contemporary dissociation between sky and consciousness.

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Income Inequality: causes and mathematics

Whether you’re a researcher, programmer, doctor or professional athlete, most of the satisfaction you derive from work probably comes from uncovering some truth, problem-solving, treating the ill and mastering a sport, respectively. Money is not the main motivator as long as there’s enough to raise a family.  But here’s where things get complicated. If you live in a society where basic needs such as shelter, healthcare and education begin to get prohibitively expensive, people with highly specialized skills will demand much higher salaries and usually obtain them. But those whose skills are more commonplace are not in the same privileged position. They have to settle for less because it’s easier for someone else to come along and accept a compromised offer. The majority of people consequently have an increasingly difficult time coping if the daily essentials can only be attained by precariously accumulating personal debt.

Some governments are fully aware of this dilemma. It’s the reason they tax those with higher incomes. The revenues are used to provide the entire population with affordable education and health care. For the most disadvantaged, housing is also subsidized.  But most governments of the world are not committed to such a path. And even among those who are, the commitment has wavered, resulting in a widening gap between rich and poor and more poor people.  As mentioned by the Conference Board of Canada, some economists argue that institutions have blocked income-disparity mitigation by allowing lower unionization rates, low minimum wages, deregulation and national policies that favor the rich. This pattern is not only of concern from an ethical standpoint, but it’s also socially and economically destabilizing.

Income inequality in Canada has increased from 1990 to 2010. This reverses the trend experienced from 1970 to 1990. Although we are doing better than the United States where inequality has increased consistently since the 1970s, a minority of countries like Norway and Belgium have done better than Canada and bucked the common trend.

But just how is income inequality measured? We begin with an idealized situation of total equality where any percentage of the population equals the percentage of net income earned. In other words if you are looking at half the population, then they would earn half of all income. And in such a society if you considered only a tiny 2% slice, then they would be receiving only 2% of the money-pie. That one-to-one correspondence of income fraction on the y– axis and population fraction on the x -axis generates the simple identity function y = x.

On the other hand, the Lorenz function ( L(x) ) describes the actual distribution of income. For example in the United States in 2008, 80% of the population took home only half of all earnings. Only 3.4% of earnings went to a sizable chunk ( 20% ) of Americans. When several points are plotted, a curve is obtained  representing L(x). Gini-index-Lorenz-CurveA 20th century statistician named Corrado Gini decided to calculate the area between the two functions and divide it by the area under y = x. The result is called the Gini coefficient. The bigger the number, the more income disparity there is.

If you enjoy math, you are probably wondering how the area under the curve is calculated. A simple method lies in googling “power function fit” and an online java program will use the data points including the previously mentioned (0.2, 0.034) and (0.80, 0.50) to generate an equation of the form L(x) =axb . In general terms, the sandwiched area in between the two functions is found by integrating the difference between the identity function and the curve.

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The G coefficient according to its definition is:

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But since the region under y = x is just a triangle with an altitude of 1 and base of 1, its area = 0.5 units, so

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By replacing L(x) with the power function that was fit to the curve, and after evaluating the integral, we obtain a Gini coefficient for the United States in 2014 of 0.390. Among OECD (Organization for Economic Cooperation and Development) countries only Mexico, Chile and Turkey fared worse. Iceland was the fairest country with a Gini coefficient of 0.246. Canada was in the middle of the pack at 0.313. The OECD site also points out that the average Gini coefficient for its 35 countries is the highest on record since they started to measure it over 30 years ago.