Author: levyba

The Road to Paris

Ashley Wang, Brandon Levy, Kevin Zhang, Nina Lutz, & Nikki Waghani

Link to slides:  https://docs.google.com/presentation/d/1Sp6JdnGYlVR9WkvcqhJF0UFnQwkcecgn1MKCsIqrOy4/edit#slide=id.p

Link to web site: http://the-road-to-paris.kevz.me/?campaign=cms.631

Impact

Transportation is currently the second largest contributor to emissions, just behind electricity generation. Our primary goal is to reduce emissions by targeting commuters, and specifically those who drive to work. We want to show them the impact they can have by choosing a greener ride to work. We specifically sent out our web page to communities on Facebook and Reddit that are already inclined to care about climate change but might not be convinced that they can help. We aim to help them better understand the magnitude of the problem, convince them their actions can make a difference, and then show them how they can reasonably adjust their commute to contribute to our goal. In addition, we assume they are busy people so we aim to provide them with practical solutions they can actually implement. To do this we look at each individual’s commute and give concrete, specific options on how they can make it greener.

We would also like to inspire a grassroots effort to combat climate change in the face of lacking government leadership. Progress was made when the United Nations came together to draft the Paris Agreement in 2016 and it looked like the world had stepped up to the challenge of fighting climate change. However, with the recent administration change in the United States, it is possible that America will pull out of the Paris Agreement, making it important to educate and inspire Americans to act green regardless of what the government decides to do.

To evaluate how well our webpage accomplished our goals, we tracked how many users clicked on the petition link at the end. This data was collected from posting on the March for Science facebook page, reddit (r/climate and r/environment), and sending out the link to friends and family.

In total, 92 individuals accessed our web page and 13 of them (14%) clicked on the petition link at the end. Seeing as our target audience is already primed to care about this issue, this result could be viewed in one of two ways. It’s possible they already signed this petition or a similar one and so did not feel the need to sign this petition. Alternatively, it might suggest that our site was not effective in discussing the importance of the Paris Agreement, although user responses to other questions would suggest this isn’t the case.

We also asked users to complete a short post-survey. 31 users (34%) completed the post-survey. 13% of these individuals said our page made them “much more concerned” about climate change and 20% said that our page made them “slightly more concerned,” whereas 67% were “equally concerned” afterwards. The fact that our site was able to increase users’ concern at all is a solid accomplishment given that this audience is already primed to care about the issue.

Moreover, 13% said that they are “very likely” to change the way they commute after going through our web page, compared to 33% who said they are “slightly likely” and 54% who said they are “not at all likely.” Given that altering one’s commute can be a significant change to an ingrained routine and some of our respondents likely already take public transportation, bike, or walk to work, these results are encouraging.

85% of respondents said we should stay in the Paris Agreement, 10% said they weren’t sure, and 5% said we should not. Since our audience is already primed to care about global climate change, this is a bit disappointing. We seem to not have made a strong enough case for the importance of the US keeping its Paris commitments, since doing so should have been a really easy sell to our target audience. On the other hand, in reality, very few people said “not sure” or “no,” so perhaps these were people were outliers.

Finally, 52% of respondents said they think individual transportation choices can have a “big impact” on US greenhouse gas emissions, while 45% said “some impact” and 3% said “no impact.” Although it’s unclear whether our site caused these feelings of personal power, the numbers are still a great sign, since encouraging people to think their individual actions matter was the primary goal of our site. Even if they don’t change their commute, these people may institute other changes that help reduce greenhouse gas emissions.

Methodology

The arc of our story begins with an introduction that establishes the planet is warming and quantifies how much warming has occurred over the past 130 years using data from NASA’s Goddard Institution for Space Studies. Next, we have an interactive that asks the user to project how much the Earth will warm if we continue emitting greenhouse gases at our current rate. After they make their guess, we show scientists’ actual prediction under the business-as-usual scenario and detail some of the effects of such a large amount of warming, including rising sea levels and more severe storms. Then on the same graph where users make their predictions, we display what will happen to temperatures if the Paris Climate goals are met. The numbers for both scenarios are drawn from global temperature projections supplied by the UN’s Intergovernmental Panel on Climate Change. This portion of our web page concludes with a brief explanation of the Paris agreement.

The second part of our web page begins with a bubble chart that shows the carbon footprint of the United States in 2005 and what the US’s footprint will need to shrink to by 2025 in order to meet its commitment under the Paris agreement. Next to this chart, we display the five sectors of the economy that contribute to American greenhouse emissions and invite the user to increase or decrease them to see how much a change to each sector would affect US emissions. Data concerning the United States’ annual greenhouse gas emissions came from the World Bank, and numbers for the contribution of various sectors of the economy to US emissions came from the US Environmental Protection Agency. We conclude this section by informing the user that transportation is the second largest contributor to emissions in the US economy, just behind electricity generation.

The third section of our web page begins with an invitation to help the US meet its Paris commitment by changing the way the user commutes. This section features an interactive that informs the user about how fuel efficient their car is. Our page displays five cars, one in each quintile of fuel efficiency. We then ask the user what kind of car they drive and ask him or her to drag their car to a place on the scale from most fuel-efficient to least fuel-efficient. To do this, we utilize data on the fuel efficiencies of different passenger vehicles from the US Department of Energy.

The final section features an interactive that recommends changes to the user’s commute based on its length and how they currently get to and from work (by car, bus, or bike). We utilize the Google Maps API to calculate the length of the user’s commute, which is then used to determine the amount of carbon the user would produce by commuting by car, bus, and bike using numbers from the European Cyclists’ Federation. We also used that API to determine whether taking the bus or biking is an option for the user. We only recommend taking the bus as an option if it there is a bus route and it would reduce the carbon footprint of the user’s commute (since the bus route may be significantly longer than a direct route via car). Similarly, biking is only recommended if the user’s commuting distance is less than two kilmometers. In all cases, we also recommend carpooling or purchasing a more fuel efficient car as ways to “green” the user’s commute.

What’s (Not) for Dinner?

Brandon Levy, Sean Soni, Mikayla Murphy, Meghan Kokoski

The data say that 700,000 children and adults in Massachusetts don’t have enough food to eat and 40 percent of the food produced in the US each year is wasted. MIT’s dining halls donate excess food to Food for Free, so when MIT students waste food at dining halls, that wasted food could have provided meals to food-insecure individuals via Food for Free’s Family Meals program. We want to tell this story because we think it will encourage MIT students to take smaller portions and reduce food waste, thereby helping both the environment and Food for Free.

Our audience is MIT students who eat in MIT’s dining halls (although our installation could be implemented at any dining hall that donates extra food to Food for Free).

Our goal is to encourage MIT students to waste less food, which not only helps the environment but also helps to feed the hungry by increasing the amount of food MIT’s dining halls can donate to Food for Free.


 

Our installation shows the number of food-insecure individuals Food for Free’s Family Meals program could feed with the food wasted in MIT dining halls, which donate excess food to Food for Free. Our project uses several sources of data, one of which currently exists and some that we would find or generate ourselves if we implemented this idea. We pulled positive quotes about Food for Free from a database of feedback provided by the organization’s recipients. If we went ahead with this project, we would ask Food for Free to provide data on approximately how much food (by weight) goes into each Family Meal they prepare, so as to accurately calculate how many people Food for Free could feed with the food wasted in MIT’s dining halls. We might also run a short experiment to calculate roughly how much of the food wasted in MIT dining halls could be used instead by Food for Free – specifically, cases where a student could have taken a smaller portion of food, since food refuse like apple cores and discrete food items like burgers and bread that have bites taken out of them would not be useable by Food for Free if they were saved.

MIT students often take excessively large portions given the chance and throw away the uneaten food. Our installation would confront students with the consequences of those actions by displaying the amount of wasted food that an MIT dining hall could have donated to Food for Free and how many people could have been fed with that food. The idea that someone might go hungry because of wasted food at an MIT dining hall provides an emotional punch to our call-to-action (reducing food waste) and, in our opinion, makes it more likely that our message will stick with students and influence their future behavior. The use of photos from Food for Free and quotes from organizations that receive rescued food from the organization also helps to humanize the food-insecure individuals who would benefit if MIT students reduced their food waste, adding additional emotional weight to our message. Finally, the practical tips we provide for reducing food waste will help students take the action we want them to.

Grey Skies Black Clouds (Hui Tian Hei Yun)

 

 

 

 

Team names: Brandon Levy, Margaret Yu, Lawrence Sun, Ashley Yang

Summary sentence: The data say that the average concentration of small particulate matter (PM2.5) in Beijing’s air in January 2017 was 121.96 µg/m³, much higher than both the World Health Organization’s safe standard of 35 µg/m³ and the more lenient Chinese safe standard of 75 µg/m³. We want to tell this story because the air quality in Chinese cities is not even close to meeting the lax standards of the Chinese government, let alone the stricter WHO standard. Our target audience is Chinese politicians attending environmental conferences who have the power to reduce air pollution in their nation’s cities.

Our data come from the U.S. State Department’s “Mission China” air quality monitoring program. Specifically, we examined data from the years 2017 and 2016 that show the concentration of small particulate matter (PM2.5) air pollution each hour of each day in those years in Beijing. We ultimately settled on showing the monthly average across January 2017 (121.96 µg/m³) and decided to compare it to the standards established by the Chinese government (75 µg/m³) and the WHO (35 µg/m³), which we found in the WHO’s Air Quality Guidelines for Particular Matter, Ozone, Nitrogen Dioxide and Sulfur Dioxide: Global Update 2005.

In our prototype, we are physically representing the data as balls of newspaper suspended by string from a canopy. The idea for the final piece would be to set up a series of these canopies leading up to the doors of the building where the Chinese politicians are gathering for their environment-related conference. The politicians would have to walk underneath these canopies – and through these “blown up” PM2.5 particulates – in order to get into the conference. In front of each canopy it would say what that canopy represents (WHO standard, Chinese standard, January 2017 average, etc.). In our mock-up, each newspaper ball represents 4 µg/m³ of PM2.5. In a scaled up version, each canopy would be one meter by one meter and each string would hang down one meter from the canopy, thereby representing one cubic meter of space, and each hanging ball would represent 1 µg/m³ of PM2.5.

This is an effective way to tell the story of our data because it turns PM2.5 pollution into something that is not only easy to see but also something that can be physically felt. We hope that walking through these hanging bundles of newspaper balls will be a sobering experience for the politicians, making them think about how problematic air pollution is and how PM2.5 pollution in Bejing far exceeds even the Chinese government’s lax standard. Hopefully, this will encourage them to pass legislation to curb air pollution and/or enforce existing laws to bring pollution levels down to their government’s safe limit.

Introducing the Hubway Class of 2013!

Team Members: Brandon Levy, Tina Quach, Mikayla Murphy, Lisa Woo

Link to presentation:
https://docs.google.com/presentation/d/1yDLBzar1jGO5Fz6SXmD9QTVfEKjNu1borJMKfu3pJFY/edit#slide=id.p

 

Summary statement: The data show that Hubway bike B00490 (“Queen Bee Bike”) was used more times than any other bike from Hubway’s launch in 2011 through the end of the 2013 regular season, and bike B00552 (“Night Owl Bike”) was used between the hours of 11 pm and 2 am more often than any other bike. We want to tell the stories of these two bikes because each Hubway bike has its own story, formed by a variety of Hubway bike users, and highlighting interesting, data-based facts about certain bikes via high-school-esque superlatives and creative bike designs encourages potential users to contribute to these stories by riding Hubway bikes.

For our sketch, we used data provided by Hubway that included every trip taken by a Hubway bike between July 28, 2011, and July 24, 2013. We first calculated the total number of uses for each bike and designated the bike with the most uses as “Queen Bee Bike” due to its popularity. To represent the story of Queen Bee Bike, we constructed a chart in which the horizontal positions of Queen Bee Bike and the average bike represent the total number of uses for each. We chose this type of chart because we wanted to make a visualization that looked like a race between the two bikes, with Queen Bee Bike way ahead of the average bike.

We also determined the number of uses for each bike between 11 pm and 2 am and named the bike with the most uses in this time span “Night Owl Bike.”  To tell the story of Night Owl Bike, we constructed a graphic in which the amount of moon visible represents the number of trips taken in that late-night time span by Night Owl Bike compared to the average bike. We designed the chart in this way because we thought it was a fun and easily understood way to represent this piece of data, especially since the average number of late-night uses was roughly half the number of late-night uses for Night Owl Bike, so we could easily represent the former with a half-moon and the latter with a full moon.

Ultimately, we envision the end product of our data visualization to be a yearbook for the “Hubway Class of 2013” in which specific bikes are highlighted and given superlatives that relate to some interesting factoid about them, and in which a creative chart is used to compare each highlighted bike to the average bike on the relevant metric. We envision having several additional bikes featured in this “yearbook” in addition to the ones used in this sketch. Some of our ideas include Lothario Bike (highest proportion of female users), Bombshell Bike (highest proportion of male users), Adventure Bike (most unique Hubway stations visited), Marathon Bike (longest single trip over the course of one day), and Hardworking Bike (longest streak of consecutive days used).

 

Hubway data source: http://hubwaydatachallenge.org/

Brandon Levy’s Data Log for February 9, 2017

On Thursday, February 9, I produced the following digital data:

  • Played Pokemon Go – hit the pokestop at my apartment building a bunch of times and caught a few pokemon
  • Fitbit – got 10,549 steps (met my step goal for the day despite the weather!)
  • Surfed the Internet – among many other things, I checked my email and Facebook, watched an episode of “Santa Clarita Diet” on Netflix, watched Wednesday night’s episodes of “The Daily Show” and “Full Frontal With Samantha Bee,” and used the WatchESPN app to watch the Duke vs UNC basketball game
  • Text messages – texted with a classmate about a group project and a friend about the Duke vs UNC basketball game
  • Swiped my MIT ID at a Pharos printer to print the readings for next week’s classes
  • Used my credit card to buy an external hard drive on Best Buy’s website

 

Data Presentation Description – American Sugar Consumption

This infographic presents data related to American sugar consumption and its health consequences. The original can be found at http://www.coolinfographics.com/blog/2012/8/29/american-sugar-consumption.html.

Brandon Levy

Given my interest in nutrition, I often come across data presentations that address Americans’ consumption of various sorts of food, many of which focus on sugar. This infographic, titled “Nursing Your Sweet Tooth,” includes multiple data presentations that display information about Americans’ sugar consumption. Given the shocking nature of some of the images in the infographic, its intended audience appears to be Americans who either are not aware of the incredible quantity of sugar consumed in the US and the associated health effects or don’t really care about these issues. The shocking images – such as one showing a mouth eating ten strips of bacon, the caloric equivalent of the average American’s daily sugar consumption – are probably intended to persuade people who are not particularly health-conscious that consuming lots of sugar is unhealthy and that they should cut back on their sugar intake.

The infographic shows a variety of data, including how much sugar the average American consumes each year and every five days; how many 12-ounce sodas that equates to; how much sugar people should be consuming compared to what they actually consume; what kinds of foods provide Americans’ with most of their sugar intake; and how many calories from sugar the average American consumes daily. As I said before, the shocking nature of some of the images strikes me as very convincing, although they may turn off some people who don’t want to acknowledge the reality of their sugar consumption. In addition, some of the data presentations are a bit arbitrary, such as the one that compares 5-day average sugar consumption in the modern day with (for some unclear reason) the year 1812. But I do think the use of familiar food items like 12-ounce sodas, pop tarts, and Twinkies to represent certain quantities of sugar, along with bacon to represent the calories in sugar, makes the infographic much more accessible and intelligible to a lay audience than it otherwise would be.