The use of the word 'data' to describe this report is complete B.S. . This is not objective scientific data, it is in fact social models base on various algorithms and social assumptions.

What it is good for is to analyze and envision social relationships, for example growing emissions of China, and slight decrease of emissions from the United States. In other words, production and consumption. Using GDP could also suffice.

But it is not objectively scientific. It is social models and assumptions. Calling oneself a 'climate change data scientist' is also B.S. as it implies one's data is objective, based on physical reality. A more accurate description would be a climate change sociologist.

Not saying this information is not valuable, but by confusing objective scientific information with social/economic/ production and consumption information you destroy the credibility of 'science' to gauge climate change.

Popper talked about science vs pseudo-science, with the difference being falsability. There is no way to falsify a social model because the data is not objective, but social. Some climate models are even copyrighted by the creators. The problem as I see it is a growing 'postmodern science' that replaces objective data with social consensus.

So, again, not saying what you are doing is not valuable and with great merit, but it is social models, not objective data.