Sustainability Math A Quantitative Literacy and Mathematics Resource for Instructors

The Pew article Most in the U.S. say young adults today face more challenges than their parents’ generation in some key areas by Stella Sechopoulos (2/28/20220) provides the survey response graph copied here. There are generational difference in these responses:

While majorities across all age groups say young adults have it harder when it comes to buying a home, saving for the future and paying for college, Americans ages 18 to 29 are more likely than older age groups to say this. More than eight-in-ten adults younger than 30 (84%) say buying a home is harder for young adults today, while 80% say the same about saving for the future and paying for college. Among those ages 30 to 49, 72% say buying a home and paying for college is harder for young adults today, and 74% say this about saving for the future. Those 50 and older are the least likely to say these measures are harder for younger generations to reach, with 63% saying this about buying a home, 67% saying this about saving for the future, and 66% saying this about paying for college.

A nice addition to this article would be data to back up the opinions. For example, are young adults saving less for the future than other generations and if so by how much?

There is another graph as well as questions used with the data and a methodology section.

The iea has a Methane Tracker Data Explorer which has information of methane emissions by country or for the world.  In 2021 the U.S. emitted 31,460 kt of methane which is 8.8% of the global emissions.  There are various graphs, such as the one copied here, and links to download the data.

The World Inequality Database  summarize the paper by Bonneau and Grobon in the article Unequal Access to Higher Education (2/7/2022).

In this paper, Cécile Bonneau and Sébastien Grobon provide new stylized facts on inequalities in access to higher education by parental income in France. At the bottom of the income distribution, 35% of individuals have access to higher education compared to 90% at the top of the distribution. This overall level of inequality is surprisingly close to that observed in the United States. The authors then document how these inequalities in access to higher education by parental income combine with inequalities related to parental occupation or degree. Finally, they assess the redistributivity of public spending on higher education, and present a new accounting method to take into account the tax contribution of parents in our redistributivity analysis.

The article lists 11 key findings such as:

Inequalities in access to higher education create large inequalities in public spending on higher education: Those in the bottom 30 percent of the income distribution receive between 7,000 and 8,000 euros of investment in higher education between the ages of 18 and 24, compared to about 27,000 euros –of which 18,000 euros correspond to public spending and 9,000 to private spending through tuitions paid by parents– for those in the top 10 percent of the income distribution (Figure 5a);

The paper (link in the first quote) has numerous graphs and the details of the modeling.

The Antarctic has broken the record low for sea ice extent and doesn’t appear to be done. The chart here is from the National Snow and Ice Data Center’s Charctic Interactive Sea Ice Graph page. Data is available from the Sea Ice Data and Analysis Tools page.

From NOAA’s Global Climate Report – January 2022:

The global surface temperature for January 2022 was 0.89°C (1.60°F) above the 20th century average and the sixth highest for January since global records began in 1880. The last eight Januarys (2015–2022) rank among the 10 warmest Januarys on record.

Similar to 2021, the year 2022 began with an episode of a La Niña in the tropical Pacific Ocean. The El Niño-Southern Oscillation (ENSO) can affect global temperatures. La Niña tends to cool global temperatures slightly, while El Niño tends to boost global temperatures. With a slightly cool start to the year, there is only a 10% chance of 2022 ending as the warmest year on record. However, there is over 99% chance of the year ranking among the 10 warmest years on record.

Time series data available at the top of the page.

NCICS (North Carolina Institute for Climate Studies) hosts the State Climate Summaries page. On this page you can select a state to arrive at a climate summary for the state. For example, the NYS page has ten graphs, including the one copied here, and summaries such as

Since the beginning of the 20th century, temperatures in New York have risen almost 2.5°F, and temperatures in the 2000s have been higher than in any other historical period (Figure 1). As of 2020, the hottest year on record for New York was 2012, with a statewide average temperature of 48.8°F, more than 4°F above the long-term average (44.5°F). This warming has been concentrated in the winter and spring, while summers have not warmed as much (Figures 2a and 2b). Summer warming is more influenced by the number of warm nights than by the occurrence of very hot days (Figures 2c and 2d). The state has experienced an increase in the number of warm nights and a decrease in the number of very cold nights (Figure 3). The increase in winter temperatures has had an identifiable effect on Great Lakes ice cover. Since 1998, there have been several years when Lakes Erie and Ontario were mostly ice-free (Figure 4).

A great site that allows educators to plan lessons around their state.

The Pew article Increasing Public Criticism, Confusion Over COVID-19 Response in U.S. by Alec Tyson and Cary Funk (2/9/2022) has the graph copied here, which seems unrelated to the title but is interesting. I’ll leave you to decide what is surprising and what isn’t. Further:

Some demographic differences in vaccination status are more pronounced within one partisan group than another. For instance, 80% of Republicans ages 65 and older say they have received a COVID-19 vaccine, compared with far fewer Republicans 18 to 29 (52%). There is a much more modest gap between the shares of Democrats 65 and older and those 18 to 29 who say they’ve received a vaccine (94% vs. 88%). See the Appendix for more details on vaccination status within partisan groups.

This all seems like good data for statistical tests. There are more  graphs, a methodology section, and more data.

The graph here from Our Word in Data’s Cancer page  is a tutorial in quantitative literacy.  From 1990 to 2019 the total number of cancer death’s in the U.S. increases 43.5%. So, cancer deaths are up. But the overall population is growing so we need to normalize and we need to  look at the death rate, which increased only 11% over the same time period.  The death rate is an obvious metric, but still really not correct.

Cancer kills mostly older people – as the death rate by age shows, of those who are 70 years and older, 1% die from cancer every year. For people who are younger than 50, the cancer death rate is more than 40-times lower (more detail here).

We would therefore expect that many more people die from cancer in an old population than in a young population. Because health is improving and fertility rates are falling, the world is aging rapidly. This impacts the change over time that we are interested in: historically, fewer died from cancer because larger parts of the population died before they reached the age when cancer becomes a common cause of death.

Epidemiologists correct for changes in age-profile over time by relying on the so called ‘age-standardized death rate’. This metric tells us what the death rate would be if the age structure of the population had stayed the same over time and would be the same across countries.⁴

If we look at the age-standardized death rate we see a decline of 18.7% in cancer death rates. Knowing what metrics to view to understand trends is a critical quantitative literacy skill and necessary in understanding the world.

The data is available by clicking on download under the chart.

The abstract from The recent normalization of historical marine heat extremes by Kisei R. Tanaka and Kyle S. Van Houtan (2/1/2022) in PLOS Climate:

Climate change exposes marine ecosystems to extreme conditions with increasing frequency. Capitalizing on the global reconstruction of sea surface temperature (SST) records from 1870-present, we present a centennial-scale index of extreme marine heat within a coherent and comparable statistical framework. A spatially (1° × 1°) and temporally (monthly) resolved index of the normalized historical extreme marine heat events was expressed as a fraction of a year that exceeds a locally determined, monthly varying 98^th percentile of SST gradients derived from the first 50 years of climatological records (1870–1919). For the year 2019, our index reports that 57% of the global ocean surface recorded extreme heat, which was comparatively rare (approximately 2%) during the period of the second industrial revolution. Significant increases in the extent of extreme marine events over the past century resulted in many local climates to have shifted out of their historical SST bounds across many economically and ecologically important marine regions. For the global ocean, 2014 was the first year to exceed the 50% threshold of extreme heat thereby becoming “normal”, with the South Atlantic (1998) and Indian (2007) basins crossing this barrier earlier. By focusing on heat extremes, we provide an alternative framework that may help better contextualize the dramatic changes currently occurring in marine systems.

The paper includes a link to the data (so you can reproduce the cool ridge plot here) and there are three other graph.

Curious about current wind patterns around the globe? Check out Windy.com. This is one of those posts that I’m not sure how to use it in a math class, but the website is so cool I’m posting about it. The graph here is a still image but the wind currents are shown moving in real time on the webpage. NOAA’s Climage.gov page Windy has suggestions on how to use the page in classrooms. Take a look, really, and leave a comment if you have a thought on how to use this in a math classroom.