Critical analysis of a data-driven news story

For this post I will be analyzing a piece of data-driven science journalism by Alister Doyle for Reuters with the headline "China to surpass U.S. as top cause of modern global warming".

The top line for this story is that if you add up all the CO2 emissions for each country from 1990 until now, China has caught up to the US in cumulative emissions and is projected to exceed it by the end of this year or sometime next year. Or as Mr Doyle put it in his article:

"China is poised to overtake the United States as the main cause of man-made global warming since 1990, the benchmark year for U.N.-led action, in a historic shift that may raise pressure on Beijing to act.

China's cumulative greenhouse gas emissions since 1990, when governments were becoming aware of climate change, will outstrip those of the United States in 2015 or 2016, according to separate estimates by experts in Norway and the United States."

I think that both my summation and Mr Doyle's descriptions are a bit wordy and could be aided by the use of a chart or visualization. Mr Doyle uses carbon dioxide emissions data from two independent sources for this story; The Center for International Climate and Environmental Research, Oslo (CICERO) in Norway, and the World Resources Institute (WRI), a US-based think-tank. The main point of the story is supported by just two numbers referenced, 151 and 147 billion tonnes, which correspond to the cumulative CO2 emissions between 1990-2016 for China and the US respectively. I think that using a bar chart (similar to the one I made in a previous post on CO2 emissions) would be a really nice way to break up all the text in the original article and provide some sense of scale for the reader.

I played around a bit with CO2 emissions data I got from The World Bank, since there is no link in the article to the data mentioned, and came up with a pretty simple and straightforward visualization that I think would strengthen the article without distracting from the story told in the text.

The article does an excellent job of contextualizing the carbon emissions data with regards to the consequences of increased CO2 levels and international efforts to control them. It also has a good diversity of relevant and useful quotes from experts on the topic.

"A few years ago China's per capita emissions were low, its historical responsibility was low. That's changing fast," said Glen Peters of CICERO.

The rise of cumulative emissions "obviously does open China up to claims of responsibility from other developing countries," said Daniel Farber, a professor of law at the University of California, Berkeley. 

"All countries now have responsibility. It's not just a story about China -- it's a story about the whole world," said Ottmar Edenhofer of the Potsdam Institute for Climate Impact Research and co-chair of a U.N. climate report last year.

"China is acting. It has acknowledged its position as a key polluter," said Saleemel Huq, of the International Institute for Environment and Development in London. 

Any fair formula for sharing out that trillion tonnes, or roughly 30 years of emissions at current rates, inevitably has to consider what each country has done in the past, said Myles Allen, a scientist at Oxford University. 

My only criticisms are the lack of a chart or some kind of visualization to really emphasize the numbers and how they relate, and that the data used for the story is not provided, nor linked to anywhere in the article.