Who are the low-wage workers?

The Brookings report Meet the low-wage workforce by Martha Ross and Nicole Bateman (11/7/19) provides demographics of the low-work force by category. The nine categories they use are represented in their chart copied here.  For example, cluster 1 are ages 18-24 are not in school and don’t have a college degree. They are 13% of the low-wage workforce. The post has links to the full report where we learn that this cohort is 51% White, 16% Black, 27% Latino or Hispanic, 2% Asian American, and 4% Other. Of this group, 14% didn’t graduate from high school.

There are regional differences:

Across more than 350 metro areas, the share of workers earning low wages ranges from 30% to 62% of the overall workforce. Low-wage workers are particularly concentrated in smaller places in the southern and western parts of the United States. They make up larger shares of the workforce in places with lower employment rates and that concentrate in agriculture, real estate, and hospitality.

The full report contains a number of data tables.

What are college persistence rates?

The St. Louis Fed post Staff Pick: College Education Persists Less for Blacks and Hispanics by Ana Kent (11/12/19 – reposted from Feb) explains:

Educational attainment tells us quite a bit about the types of financial outcomes we should expect a family to have. So does the education of the family’s parents. Unsurprisingly, most people tend to achieve the same level of education as their parents, with college “persisters” (college graduates for whom at least one parent was also a college grad) having the best financial outcomes.

There are racial differences, for example (note: the chart here is population composition – see the table in the article for persistence rates by race):

Blacks had the lowest intergenerational college persistence. If at least one parent had a degree, only 1 in 3 continued to get a college degree themselves.

Intergenerational no-college persistence also showed marked racial differences. Hispanics had the highest no-college persistence, with just under 9 in 10 not achieving a four-year degree if neither parent did.

The post has two graphs and one table.

How does food move around the U.S.?

An article by Fast Company, The first map of America’s food supply chain is mind-boggling by Megan Konar (10/28/19), reports on the paper Food flows between counties in the United States by Xiaowen Lin, et. el. The author of the paper created the network graph of food flow copied here.  From the article:

Overall, there are 9.5 million links between counties on our map.

At 22 million tons of food, Los Angeles County received more food than any other county in 2012, our study year. It also shipped out the most of any county: almost 17 million tons.

Some of the other largest links were inside the counties themselves. This is because of moving food items around for manufacturing within a county—for example, milk gets off a truck at a large depot and is then shipped to a yogurt facility, then the yogurt is moved to a grocery distribution warehouse, all within the same county.

The article has a link to data that created the map. There must be a good graph theory project here.

How has income changed in the U.S.?

From the Census Bureau report New Data Show Income Increased in 14 State and 10 of the Largest Metros by Gloria Guzman (9/26/19)

Median household income for the United States and 14 states increased significantly in 2018 from the previous year, according to U.S. Census Bureau data released today.

But,

However, the Gini index of income inequality was significantly higher during the same period for the nation and nine states.

The report has six charts or tables. The full Household Income: 2018 report has tables of data. Historical data including household gini index (table H-4 which includes data by race) is on the Historical Income Tables: Income Inequality page.

Where can we find regional weather data?

Go to the NOAA Climate at a Glance Divisional Mapping page. From the first drop down menu choose a state. Below that a state map appears and now click on a region. If time series data is desired click on the second tab along the top that says time series.  At this point the first drop down menu is to choose a parameter. There are seven choices including average, max, and min temperature as well as precipitation. A time scale can be chosen such as a single month or annual. For example, the graph here created from the site is average annual temperature for the finger lakes region in NYS. Along with a graph, a spreadsheet of the data can be downloaded.

What is the status of the ozone hole?

According to the NOAA article Five questions about 2019’s record-small ozone hole by Rebecca Lindsey (10/21/2019):

In 2019, the hole that developed in the ozone layer over Antarctica was the smallest on record since 1982, according to the NASA/NOAA press release. In an average spring, the hole expands throughout September and early October to a maximum extent of about 8 million square miles (21 million square kilometers), an area larger than the United States and Canada combined. In 2019, the hole reached 6.3 million square miles (16.4 million square kilometers) on September 8, but then shrank to less than 3.9 million square miles (10 million square kilometers) for the remainder of September and the first half of October.

Why so small?

An uncommon weather event—a sudden stratospheric warming—disrupted the circulation in the polar stratosphere in early September, just as the ozone hole was beginning to form.

What about the future?

No, this year’s small ozone hole was simply the result of an isolated weather event, not part of a trend. Thanks to the international treaty banning the production and use of CFCs (short for chlorofluorocarbons), levels of these compounds have been declining since about 2000. But because CFCs are so long-lived, concentrations remain high enough to cause significant ozone loss each spring. With continued declines in CFCs, experts project the ozone layer will recover to its 1980 conditions around 2070.

There are three other graphics and the article is worth reading. If you are looking for classroom materials related to the ozone hole consider the Near-Ground Level Ozone Pollution Lab posted by NOAA and designed by SERC. Also note the Ozone project in the Calculus Projects page.

Who produces the most air travel CO2 emissions?

The statista post The Worst Offenders For Air Travel Emissions by Niall McCarthy (10/22/2019) produced the chart here. The post notes

The 12 percent of Americans who make more than six round trips by air each year are actually responsible for two-thirds of all U.S. air travel and therefore two-thirds of all its emissions. Each of those travelers emits over 3 tons of CO2 per year and if everyone else in the world flew like them, global oil consumption would rise 150 percent while CO2 from fossil fuel use would go up 60 percent. As over half of the population does not generally fly, the U.S. ranks 11th in emissions per capita from flying.

The post references the icct report CO2 emission from commercial aviation, 2018. It notes

CO2 emissions from all commercial operations in 2018 totaled 918 million metric tons—2.4% of global CO2 emissions from fossil fuel use. Using aviation industry values, there has been a 32% increase in emissions over the past five years.

At the bottom of the icct report there is a link to spreadsheet data with air travel emissions data by country.

 

What’s the difference between consumption and production CO2 emissions?

The Our World in Data article How do CO2 emissions compare when adjusted for trade by Hannah Ritchie (10/7/2019) answers the question.

To calculate consumption-based emissions we need to track which goods are traded across the world, and whenever a good was imported we need to include all CO2 emissions that were emitted in the production of that good, and vice versa to subtract all CO2 emissions that were emitted in the production of goods that were exported.

Consumption-based emissions reflect the consumption and lifestyle choices of a country’s citizens.

The map copied here show consumption CO2 emissions per capita. As some countries consume more than they produce this this may be a more accurate way to compare CO2 emissions.

We see that the consumption-based emissions of the US are higher than production: In 2016 the two values were 5.7 billion versus 5.3 billion tonnes – a difference of 8%. This tells us that more CO2 is emitted in the production of the goods that Americans import than in those products Americans export.

The opposite is true for China: its consumption-based emissions are 14% lower than its production-based emissions. On a per capita basis, the respective measures are 6.9 and 6.2 tonnes per person in 2016. A difference, but smaller than what many expect.

The article has seven charts with data including time series data.

How hot was September 2019?

From the NOAA Global Climate Report – September 2019:

The average global land and ocean surface temperature for September 2019 was 0.95°C (1.71°F) above the 20th century average and tied 2015 as the highest September temperature departure from average since global records began in 1880.

The Northern Hemisphere, as a whole, also had its warmest September on record at +1.24°C (2.23°F) above the 20th century average, surpassing the previous record set in 2016 by +0.03°C (+0.05°F). The five warmest Northern Hemisphere land and ocean surface temperature have occurred since 2015.

So far for 2019:

Each of the first nine months of the year had a global land and ocean temperature departure from average that ranked among the five warmest for their respective months. This gave way to the second warmest January–September in the 140-year record at 0.94°C (1.69°F) above the 20th century average.

Global time series data for September.

Northern Hemisphere time series data for September.

 

How do food systems differ between rich and poor countries?

The World Bank post The high price of healthy food and the low price of unhealthy food by Derke Headey and Harold Alderman (7/23/19) explores the connection between food systems and wealth in a country, along with the impacts. For example, their graph here show a correlation between stunting in children and the caloric price of milk.

The metric we use to analyze the global food system from a consumer perspective is the “relative caloric price” of a given food. Take eggs, for example: how expensive is an egg calorie in Niger compared to the most important staple foods in that country? Egg calories in Niger are 23.3 times as expensive as a calorie from a staple food, such as rice or corn. In contrast, egg calories in the US are just 1.6 times as expensive as staple food calories.

The big picture:

Hence the problem in less developed countries is that poor people also live in poor food systems: nutrient-dense foods like eggs, milk, fruits and vegetables can be very expensive in these countries, making it much harder to diversify away from nutrient-sparse staple foods like rice, corn and bread. The problem in more developed countries is rather different: unhealthy calories have simply become a very affordable option. In the US, for example, calories from soft drinks are just 1.9 times as expensive as staple food calories and require no preparation time.