In 2015, the winner is Norway by producing 97.7% of their electricity needs through renewable energy. The top 3 is completed with New Zealand (80.1%) and Columbia (77.7%). The U.S. produces only 13.6% of their electricity with renewable energy. You can learn more from the Global Energy Statistics Yearbook 2017. The data on renewable energy production dates back to 1990. You can download graphs like the one here and the data sets (after registering).
Kevin Drum answers the question in his post A Little Bit of Chart History for Wednesday. The phase out started in 1975. Why?
According to Nussbaum, EPA wanted places like California to reduce smog, and that meant cars would have to be fitted with catalytic converters. However, since gasoline lead ruins catalytic converters, refineries needed to produced unleaded gasoline. This was the initial impetus behind unleaded gasoline. The fact that it also reduced atmospheric lead was basically a happy accident.
Once that was done, however, EPA started looking more closely at the health effects of lead. It was no secret that high levels of lead poisoning were dangerous, but new research was showing that even moderate levels could be dangerous, especially in young children. So now EPA had two reasons to phase out leaded gasoline.
Drum’s post provides nice historical context on leaded gas, including this graph that may be the first graph produced showing a correlation between lead in blood and lead in gas (excellent artifact for use in a classroom). Read the article to find out about President Carter’s connection in all of this.
For further information read Drum’s essay Lead: America’s Real Criminal Element, published in Feb 2016. The lead crime connection has an element of environmental racism, which is not often discussed. In Statistics Materials you’ll find lead and crime data for linear regression and further information.
Climate Central has your answer with its post The First Frost is Coming Later. They provide graphs, like the one here for NYC (about 20 days later since 1970), for most major cities in the U.S. They don’t provide the data, but you can try and send them an email and they may send it to you. Alternatively, this could be a great stats project where students get the data themselves for a city of their choice and create the chart. You can get weather data from NOAA Climate Data Online.
There is a lot of information in the Climate Science Special Report, but you can read the Executive Summary, or this shorter summary from the Wunderground post Blockbuster Assessment: Humans Likely Responsible For Virtually All Global Warming Since 1950s. Posted here is a graph about global mean sea level (GMSL) rise from the executive summary. Yes, 8ft of sea level rise is a possibility by 2100.
Emerging science regarding Antarctic ice sheet stability suggests that, for higher scenarios, a GMSL rise exceeding 8 feet (2.4 m) by 2100 is physically possible, although the probability of such an extreme outcome cannot currently be assessed. Regardless of emission pathway, it is extremely likely that GMSL rise will continue beyond 2100 (high confidence). (Ch. 12)
Relative sea level rise in this century will vary along U.S. coastlines due, in part, to changes in Earth’s gravitational field and rotation from melting of land ice, changes in ocean circulation, and vertical land motion (very high confidence). For almost all future GMSL rise scenarios, relative sea level rise is likely to be greater than the global average in the U.S. Northeast and the western Gulf of Mexico. In intermediate and low GMSL rise scenarios, relative sea level rise is likely to be less than the global average in much of the Pacific Northwest and Alaska. For high GMSL rise scenarios, relative sea level rise is likely to be higher than the global average along all U.S. coastlines outside Alaska. Almost all U.S. coastlines experience more than global mean sea level rise in response to Antarctic ice loss, and thus would be particularly affected under extreme GMSL rise scenarios involving substantial Antarctic mass loss (high confidence). (Ch. 12)
Plenty of graphs in the executive summary and the Wundergraound post of any QL course and much of the data is available.
The Nenets are reindeer herders in Russia’s Arctic that migrate 800 miles each year. The National Geographic Article, They Migrate 800 Miles a Year. Now It’s Getting Tougher, tells their story.
The Nenets have undertaken this annual migration for centuries, and at 800 miles round-trip, it’s one of the longest in the world. Yuri’s group, called Brigade 4, is a relic of a Soviet collective—under Soviet rule the Nenets endured decades of forced collectivization and religious persecution. They survived centuries of Russian rule before that. Through it all, they’ve managed to sustain their language, their animist worldview, and their nomadic traditions.
The Nenets are facing challenges.
As I talk to Yuri, the region is suffering another record-hot summer; the thermometer has already hit 94°F. It hasn’t rained for weeks, and it’s hard for reindeer to pull the loaded sleighs across the dry tundra. Before the summer is out, a boy and more than 2,300 reindeer will die from anthrax on southern Yamal, and dozens of people will get sick—a direct result of thawing permafrost, which allowed animal carcasses buried during an outbreak in the 1940s to reemerge, still bearing infectious microbes.
And it isn’t just climate related challenges.
Yet climate change isn’t even the greatest threat to the Nenets. Development is. Russia’s quest for new sources of hydrocarbons has encroached on pastures that were already tight for the estimated 255,000 reindeer and the 6,000 nomadic herders that live on Yamal.
Read the article, which includes a video and a number of great photos and maps: They Migrate 800 Miles a Year. Now It’s Getting Tougher.
Related permafrost articles from this blog: Climate Change, Melting Permafrost, and Disease, Melting Permafrost and a Feedback Loop, Climate Change – Impacts on People, and Methane Bubbles – A Feedback Loop.
The Tropical Meteorology Project at CSU posts data on hurricanes (and tropical storms). From their data we created this bar chart that shows the top 21 years of hurricanes based on the number of storms. Of the top 21, eleven have occurred since 2000, and 2017 will already be in the top 21 with 16 storms. This will make it twelve of the top 21 since 2000 at years end. The posted data set at the Tropical Meteorology Project includes named storm days, hurricanes, hurricane days, major hurricanes, major hurricane days, and accumulated cyclone energy.
Climate Central has your answer by providing graphs of the number of above average warm days in the fall since 1970, for most major cities in the U.S. Here is their graph for Duluth MN from their article More Warm Fall Days Across the U.S. In 2016 Duluth had over 70 days in the fall of above average temperatures, almost the entire fall. They don’t provide the data, but you can contact them and they might provide it to you. Alternatively, their methodology is listed and so you can create a graph for your town with some effort (maybe a student project?). There are potential linear regression assignments waiting to be created here that could include comparing cities.
Our World in Data’s latest visualization is this graph of CO2 emissions by world region. If you go to the page you will find the usual high quality interactive graph with data in a excel file. You can read off the graph that in 2015 China emitted 10.23 Gt of CO2 while the U.S. emitted 5.1 Gt. On the other hand, while China emitted about twice as much CO2 their population is about four times the size of the U.S.
NOAA has a page, Sea Ice and Snow Cover Extent, where you can create graphs for snow cover by four regions (Northern Hemisphere, North America and Greenland, Eurasia, and North America) for each month of the year. For example the graph here is for North America in March. The green line is the average and the red the trend. For each graph you can download the associated data or simply download the graph.
Our World in Data has the answer in their post, 50% of the world’s habitable land is used for agriculture. If we all ate like New Zealanders we would need 200% of habitable land, which is supplied in the chart. Simply put, the world all can’t eat like the U.S. The world can’t eat like the countries colored in orange but can with those colored in green. Why?
Livestock takes up nearly 80% of global agricultural land, yet produces less than 20% of the world’s supply of calories. This means that what we eat is more important than how much we eat in determining the amount of land required to produce our food.
There is an association between wealth and diet as can be seen in the chart below, but there are variations.
Nonetheless, there are still large differences in dietary land requirements between countries of a similar income-level. Why, for example, is the requirement for a New Zealander more than double that of a UK citizen, despite them having similar levels of prosperity?
As always Our World in Data includes the data for each of their charts and there are more than the two here. They also allow you to download the graphics which was done for this post.