Are we making our days shorter with artificial lighting?

Developing countries are good at doing just that, developing. What they can fail to do, however, is recognize when their development may be more detrimental than helpful to its’ residents.

A recent article by The Washington Post highlights a new, growing problem the world may come to face as we continue to develop and grow our infrastructures. The study  found that the area of artificially lit area of the Earth’s surface grew by 2.2%** per year from 2012-2016. Which is a pretty big amount of land.

** 2.2% of the Earth’s land is roughly 3,000,000km^2. The majority of results online estimated that the amount of habitable land on Earth is about 150,000,000km^2.

Scientists in this study examined high resolution satellite images from country to country (excluding regions along a similar latitude to Iceland, because their data was not accurate beyond a certain latitude) to measure just how much the artificial lighting was growing and affecting the light in our atmosphere at night. They compared measurements from 2012 (NOTE: taken with a DIFFERENT satelite imaging technology than 2016 images), then compared them to an image from 2016. The growth they observed startled them.

This figure illustrates the lighting change between 2012 and 2016. The blue indicates decreases in light, and the red indicates an increase in light.

What concerned the scientists even more is that the satellite images were not sensitive to blue LED lights, which have recently become more commonplace in work and home spaces. These blue LED lights have been linked to sleep disorders and linked to sleep deficiencies and other health issues. Because the satellites do not pick this kind of  light up, scientists fear the numbers produced from their study may be underestimates of the actual levels of light in the atmosphere. Furthermore, while the LED may reduce the overall “brightness” of a city, the health impacts mentioned before could still be amplified as the LEDs are more readily available and encouraged. The bottom line is no one knows what the effects could be once applied to a global scale.

The results of this study could have wide ranging implications. Literally globe-spanning implications. Exposure to artificial light is being blamed for numerous sleep disorders. The blue LED lights emitted from our phone and computer screens have been proven to keep our brains awake longer if we use them before bed. I am questioning if the obscenely bright lights out on the village green are having an impact on my sleep.

If this 2.2% per year trend continues, within the next 50 years we could, in theory, illuminate all of Earth’s atmosphere with artificial light. What would this look like? They don’t offer a picture, but could we truly ever get rid of night time altogether? I’m not sure, and the article does not really state any negative implications other than the possibility of an increase in sleep disorders.

The study, though widely mentioned, was not actually linked by this article. I had to Google it to find the published study.

It is interesting to me, that there still would be a 2.2% increase, even when there are such large areas of land, possibly uninhabited or more rural areas, where there is little to no light. It seems like a significant number to obtain.

While this is interesting data, I find it all to be pretty logical, and easy to explain. An increase in population will  lead to an increase in the demand for energy/electricity, therefore leading to more lights and more light pollution. This data would be more compelling if it included some possible implications of smaller increases in light in the atmosphere to compare against some of the more prominent research dealing with direct exposure to intense LED lights before bed. Furthermore, they never actually reference how much night time we are losing because of this increase in artificial light. I would be interested to see how much night we lose with every percent increase.

Nevertheless, if more studies similar to this one come out, perhaps it will make us think twice about our energy consumption, and turn out the lights at night.


Men Eat More In Front Of Women?

An article written by Julie Beck of The Atlantic on November 19, 2017, outlines a study that claims “Men Overeat to Impress Women”. The article explains how the study, by Cornell University, recorded observations of men and women at an all you can eat pizza buffet, and measured how much food they ate. The study found that men ate “93 percent more pizza and 86 percent more salad” when they were with women compared to when they were with other men. The study cited that they were probably doing it to impress women, “Our observation of men ‘eating heavily’ is sensibly viewed in an evolutionary perspective as men ‘showing off’”.

The entire article makes this study seem like it was very sound and that the results were clear. It also made it seem like the reasoning for it was clear. In an interview with Kevin Griffin, the lead author of the study, he said “overeating might function as a comparable kind of signal that a person is healthy enough that they can engage in unhealthful behavior of excessive eating (and still end up okay).” The thing about this statement is it’s a hypothesis. The article makes it seem like it’s a fact, based on the fact that that quote is written in it twice, but it doesn’t talk anywhere about any other possibilities besides impressing women or trying to signal to women that they are strong.

When I went through and read the study, I got a lot more information from it than I got from the article. For example, the article made it seem like they just creepily watched people what pizza, never taking surveys from them or even letting them know they were being surveyed. However, in the abstract, it states “Additionally, while women do not eat significantly differently as a function of the sex of their dining partners, women eating with men tended to estimate themselves to have eaten more and reported feeling like they were rushed and overate.” It’s actually interesting to me that the article does not talk about this, because it seems like a pretty major finding for the study, but I guess the Atlantic just wanted to focus on men overeating. However, this quote brings up an important point that the article did not – the people were all surveyed as follows: “When participants had finished with their meals, a research assistant met them at the cash register to ask them to complete a survey that asked each of them to estimate the number of calories of pizza they consumed as well as their level of (dis)agreement on a nine-point scale with the statements “I overate,” “I felt rushed,” and “I am physically uncomfortable.” A picture of some of the graphs they used can be found below.

Screen Shot 2017-12-03 at 5.27.01 PMScreen Shot 2017-12-03 at 5.27.52 PM

I personally feel that this study was much more interesting than the article made it out to be, particularly with how people predicted how many calories they ate. When women ate with women, they predicted they ate an average of about 350 less calories compared to when they ate with men, even though they only ate slightly less with women. In addition, when women ate with men, they felt much fuller than if they ate with women, probably having to do with the perceived calorie intake thing. According to their study, men also ate about twice as much with women than when they ate with men.

This study, in my opinion, has some holes. For example, this is not a representative population at all. They did this study at one pizza buffet at lunch time over the course of two weeks. How do we know that maybe men in this area don’t eat breakfast as much as women, so maybe that’s why they ate more or something? The sample size was just 133 people. As someone whose worked in resturaunts, either that not everyone who went into the pizza buffet at lunch was surveyed, or maybe it was a really slow resturaunt. Maybe they had really bad pizza, so that’s why so few people were surveyed in the teo weeks, and maybe men don’t complain about gross pizza in front of women but they would in front of men. I know I’m being quite skeptical about this, but I guess I just don’t agree with how the data was collected and for them to be making as profound statements such as the article makes. The conclusion stated that:

“Future research into “eating heavily” among males should examine the relative importance of female mate choice and intrasexual competition and consider whether this pattern holds in societies where relative thinness is not prized (e.g., Tovee et al. 2006); however, our behavioral findings drawn from a naturalistic field study introduce an important pattern through its rejection of the hypothesis that men tend to eat more in the company of other men.”

The study accepts and acknowledges that more research should be done and proposes more things it could be gone on, and says that they have “introduced an important pattern”. The article written by the Atlantic made it seem like such more sound research compared to “introduced an important pattern”. Honestly, I have nothing against the study, because they definitely aren’t saying their research is more important or has more gravity than it has. However, the article by the Atlantic about the study, is a bit of an exaggeration.

More Women in Education Means that More Women With B.A.’s Are Marrying Men Without (Shocking!)

In Alfred Lubrano’s article “More women with college degrees are marrying men without B.A.’s,” the author details a few heterosexual couples where the wives have bachelor’s degrees and the husbands do not.

The author uses U.S. Census data for the Education Gender Gap to show that “since 1990, the percentage of young women with a college degree has grown faster than the percentage of young men.” The data visualization appears accurate, except that it goes from 0% to 50%, rather than 0% to 100%. Because of this, the gap between women at 46% and men at 37% looks significantly larger than 9%.Screen Shot 2017-12-03 at 10.15.57 PM.png

The author then uses U.S. Census data for the Education Gender Gap in Local Counties, but I’m not from Philadelphia, so I don’t know where these counties are, and I don’t know how applicable this data is beyond those select counties.

Screen Shot 2017-12-03 at 10.16.06 PM.pngLater on in the article, the author references race/ethnicity and says that “[a]ctually, while more black women than black men aged 25 to 34 have a bachelor’s degree or higher, according to 2016 Census statistics, the nearly four-percentage-point difference (26.5 to 22.6) is half the size of the figure for all of the United States, said Temple sociologist Judith Levine. What’s different is that black women have always been more likely to get a college degree than black men, as far back as the 1940s, Levine said. Racism and high incarceration rates are among the reasons, she said.” These two sentences are the only sentences about race and it feels like this idea was just interjected and not well thought out.

After race/ethnicity is brought up (and then not evaluated), the piece immediately ends with an interviewee’s take on education: “Whether a man has a degree is not one of my first questions. At this point, life-education outweighs a degree.” I think that this conclusion for that specific person, but it is not an all-encompassing conclusion that is applicable to anyone even beyond the counties of Philadelphia.

This article has the cultural implication that while it is good that women are receiving more bachelor’s degrees than men that there is going to be even more of an intellectual disparity from now on.

Panda Sex!


Through the stress of upcoming finals, I figured we  could all use a little cute, and what better than pandas?

Now of course, I did actually do some research for this one, but you bet your ass I am going to present it in a visually cuddly way (especially since some of the stuff isn’t super cuddly).

Pictured above is Pan Pan, which loosely means ‘Hope’ which I learned after reading all about his legacy in this article on FiveThirtyEight. Pan Pan passed last year, but not before leaving 130 panda descendants in his stead.

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Pan Pan is credited with being one of the most successful sexual pandas. He helped panda researchers in breeding programs that natural breeding is more successful than insemination or more pressured or forced couplings. He’s a stud, and studs apparently make a lot of babies. His studly genes were even passed on. Some of his descendants are known for being successful breeders. Unfortunately, there are problems that arose once the hurdle of endangerment was crossed.


Pandas like Pan Pan that were raised in captivity are often more domesticated and lose the abilities they need to survive in the while after a few generations of breeding. Very few pandas are released into the wild. After that, there is still an issue that unless groups of wild pandas cross paths and mate, inbreeding can affect and destroy the group.

On the flip side,  a similar issue is already happening in captivity. Researchers are scrambling to increase gene variability by increasing the number of successful mating pandas.

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Fortunately, other endangered species have gone through similar experiences when raised and bred in zoos and conservation sites. That information is now in the researcher’s hands to translate into panda terms and hopefully rebuild the strength of the species.


Hopefully in the next decade of panda research and captive breeding, we will see more pandas successfully entering the wild and increasing the gene pool.

Here are more pictures of pandas.

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The Making of a Data Visualization

I was inspired by the blustery weather outside to write a weather related blog post today. In searching for interesting weather data, I stumbled upon this beautiful infographic created by Nicholas Rougeux, which can be found on his blog.


The poster shows weather data from 2014 in 50 major US cities. Each city is represented by a circle. Each circle is composed of 365 days worth of weather data from the Quality Controlled Local Climatological Data, represented by a circle on a line. Each circle on a line shows five measurements for the day: highest temperature, lowest temperature, range of temperatures, wind direction, and wind speed. Check out the image below to learn more about how to read each data point:


Here’s a close up of some of the cities on the infographic:


This infographic first stood out to me because of how pretty it is to look at. Each city is a unique explosion of color, and made the weather for the year in that city look exciting. I also appreciated how informative the image is. For example, by quickly looking at the images above you can learn the Las Vegas had the hottest temperatures of the three cities and tends to have wind from the the southwest. Chicago had the most varied wind scores, and Fargo had the strongest winds. Both Chicago and Fargo had a mix of warm and cold temperatures during the year. The image is an interesting and fun way to compare and contrast weather in different places across the US.

I was interested in how Rougeux created this image, so I checked out his page on the making of the infographic. First, Rougeux talks about how he was inspired to create a image about weather because it’s something that everyone, everywhere experiences everyday. Rougeux wrote about how it was challenging to create a design where each data point remained relatively equal… he didn’t want the days with warmer temperatures to visually overpower the colder days due to brighter colors or larger sizes. His solution to this problem was having the size of the temperature circles reflect the range of temperatures on that day. This would give the warm and cool days equal visual presence. I thought it was interesting how the choices Rougeux made about how to present the information visually changed both the aesthetic appeal of the image and the way viewers perceive the information.

I also thought Rougeux’s rough drafts of the image were fascinating.I highly suggest checking out his site to see them all. One I found interesting was the 8th version Rougeux tried for visualizing the Chicago data. The triangles pointing upwards are the highs for each day, and the triangles pointing downwards are the lows. The pairs are plotted horizontally from largest to smallest range of temperature, and smaller triangles are placed in front of larger ones. I think this image does a good job of showing the range, but makes it hard to see individual data points, and makes it seem that Chicago was hotter than it really was since the cooler colors tend to blend into the middle.


I think Rougeux’s work is a great example of how data, technology, and art can work together. If I had just looked at the weather data presented in a table of list, I probably wouldn’t have been very interested. However, seeing the infographic made me want to look closer to analyze weather trends, or maybe even hang the image up on my wall as a poster. I also appreciated that Rougeux showed some of his drafts. It helped me understand that data visualizations can emphasize different aspects of the data depending on how it is presented.

Are Your Christmas Lights Burning Your Cash?


With the exception of eager retailers, December 1 and the passing of Thanksgiving mark the beginning of the Christmas season for most. We play Christmas songs on the radio, decorate Christmas trees, go Christmas shopping, and bake Christmas cookies. We foresee the potential financial setbacks of Christmas presents, but might neglect to acknowledge another Christmas tradition that hits our bank statement as well –  Christmas lights!

Christmas lights become so abundant this time of year that NASA claims their effect is recognizable from space! An article from The Washington Post states that “the light intensity in American suburbs increases by thirty to fifty percent” until the start of the new year. This luminous form of Christmas cheer doesn’t come cheap, however. The same article approximated the cost of running Christmas lights for 12 hours a day for 45 days at a rate of 12 cents per kilowatt hour. (Energy use calculations were made according to manufacturer power use approximations.)

The choice between LED and incandescent bulbs makes a huge difference! Let’s say that an average family uses two mini strings of 100 bulbs for a tree and other interior decorations in addition to three C9 strings of 25 bulbs on a house exterior. If all of these bulbs were incandescent, the total cost according to the above constraints and power use estimates would be $52.42. However if all of these bulbs were LED, the total cost would amount to $1.45. That difference could go back into your pocket or towards a nice gift. Furthermore that cost difference represents an energy difference of approximately 425 kilowatt hours. Imagine the difference that an entire community or city could make on energy usage if they opted to use LED lights rather than incandescents! Unfortunately according to another article by The Washington Post these savings might encourage consumers to simply buy more lights (see here). This Christmas consider your wallet and your planet while choosing Christmas lights!


Are Americans Less Neighborly?

This week, I was reading through The Washington Post when I found an article called “It’s not just Rand Paul’s street: Americans are a lot less neighborly than they used to be.” Christopher Ingraham wrote the article after U.S. Senator Rand Paul was attacked by one of his neighbors. Ingraham argues that this type of behavior isn’t isolated, but part of a trend in America—people are becoming less neighborly.

The writer’s main support for this argument is data from the General Social Survey (GSS). The GSS is a nationwide sociological survey which has been administered since 1972 by the National Opinion Research Center at the University of Chicago. The data from this survey is often used by journalists, politicians, and policymakers.

The article says that “In 2016, the share of Americans who say they ‘never’ socialize with their neighbors hit an all-time high of 34 percent, according to the General Social Survey.” Below this statement was the following graph:

WP Graph

This is the claim that I am specifically interested in—whether or not America has actually become less neighborly. The article includes no link to the GSS data, so I had to find the GSS website by myself (you can find it here). The GSS has a search function where you can enter a search word and find all the data connected to that word. For example, if you type in the word neighbor, the GSS will show you all the surveys which include the word neighbor. You can then click on each question and find the response breakdown for each year that the question was included in the survey.

I went through this process, and I was a little confused because none of the questions asked “How often do you socialize with your neighbor,” or some close variant (here are my search results). I thought that maybe I just didn’t know how to use the search function properly, but then I stumbled across the following question: “How often do you spend a social evening with someone who lives in your neighborhood.” Out of all the questions in the database, this was really the only one dealing with neighbors and social behaviors. However, I didn’t really think that this could be the question that Ingraham was referring to. After all, “How often do you spend an evening with your neighbor,” and “How often do you socialize with your neighbor” are different questions. Someone might rarely, or even never, spend a social evening with their neighbor. They might, however, socialize with their neighbor at church or PTA meetings, or play pickleball with them on a Saturday morning.

I thought that The Washington Post article couldn’t possibly be based on the GSS question, until I looked at the data. The graph from above shows that 21% of people in 1974 never socialize with their neighbor. This matches exactly the breakdown for the question that I found on the GSS website—of the 1,484 people surveyed in 1974, 322 said they never spend a social evening with someone who lives in their neighborhood (or, 21.7%). The breakdown of the question from 1974 is below.

GSS 1974

So what about the 2016 data for this question? Of the 2,867 surveyed, 611 said they never spend a social evening with someone who lives in their neighborhood, or, 21.3%. Below is a breakdown of the question for 2016 (you’ll have to ignore all the years in between), as well as the percentages provided by the GSS codebook.1

 GSS 2016GSS Codebook

21.3% is far from the 34% of Americans that The Washington Post claimed weren’t socializing with neighbors. However, I also noticed that if you take all those that responded “Not Applicable”2 out of the 2016 sample, you get 611 out of 1888 that never spend a social evening with their neighbor—which ends up being about 32.4%. While The Washington Post graph claimed 34% in 2016, I still think this is a solid piece of evidence to suggest that the Ingraham was looking at this question and just didn’t include the full sample.

So is The Washington Post’s claim completely bogus? I can’t say for certain, but I think so. Because Ingraham didn’t provide links and I couldn’t follow his path, I suppose it is possible that he was looking at data I couldn’t find. However, I think it is probable that Ingraham took the question about spending a social evening with a neighbor and generalized it to all socialization with neighbors.

In response to my title— “Are Americans less neighborly?”—I think I would say, “I don’t know.” The Washington Post article wasn’t all that helpful, and I don’t think that the GSS question I found is that representative of “neighborliness.” Also, this blog doesn’t address issues of survey methodology such as sample size, the wording of questions, and changes in the survey over the years. I guess what I learned from writing this blog post is to be careful with data collected from surveys, and even more careful with articles based on survey data.



1 There is no codebook for 1974, or I would have provided that information as well.

2 The “Not Applicable” option was not offered in the 1974 GSS.