Is there a normal amount of Carbon Footprint?

What is the carbon footprint of a a single spam message?

• A friend of mine sent me a infograph about how much CO2 is produced from a single spam email. In the infograph it said, "The average GHG emission associated with a single spam message is 0.3 grams of CO2" I'm not sure the the claim is a valid one and would like to see some similar studies or links about the topic. Below is what the infograph was based on: "The “Carbon Footprint of Spam” study looked at global energy expended to create, store, view and filter spam across 11 countries, including Australia, Brazil, Canada, China, France, Germany, Japan, India, Mexico, Spain, the United States and the United Kingdom. It correlated the electricity spent on spam with its carbon footprint, since fossil fuels are by far the largest source of electricity in the world today. Since emissions cannot be isolated to one country, it averaged its findings to arrive at the global impact. Key findings of the “Carbon Footprint of Spam” study included: The average GHG emission associated with a single spam message is 0.3 grams of CO2. That's like driving three feet (one meter); but when multiplied by the yearly volume of spam, it is equivalent to driving around the earth 1.6 million times. Much of the energy consumption associated with spam (nearly 80 percent) comes from end-users deleting spam and searching for legitimate e-mail (false positives). Spam filtering accounts for just 16 percent of spam-related energy use. Spam filtering saves 135 TWh of electricity per year. That is equivalent to taking 13 million cars off the road. If every inbox were protected by a state-of-the-art spam filter, organizations and individuals could reduce today’s spam energy by 75 percent or 25 TWh per year, the equivalent of taking 2.3 million cars off the road. (my note seems like they are just trying to pitch a product) Countries with greater Internet connectivity and users, such as the United States and India, tended to have proportionately higher emissions per e-mail users. The United States for example, had emissions that were 38 times that of Spain. While Canada, China, Brazil, India, the United States and the United Kingdom had similar energy use for spam by country, Australia, Germany, France, Mexico and Spain tended to come in about 10 percent lower. Spain came in at the lowest, with both the smallest amount of e-mail that was received as spam and the smallest amount of energy use for spam per e-mail user."

• Answer:

  Hi, I'm a PhD student and I study this sort of stuff. I could point you to a half a dozen studies that make similar claims about the carbon footprint of downloading a music track, burning a CD, ordering a movie via Netflix, reading a journal article online, and so on. For what it's worth, 0.3g per spam message feels reasonable, in that it doesn't disagree wildly with similar studies. The way the measurements are conducted is something like this: Client side: 1. Estimate total life-cycle carbon footprint of the client computer and divide by computer lifespan (typically 4 years) to get a footprint-per-second-of-use 2. Estimate the amount of time spent doing activity X, e.g. "We estimate it takes the average user 3 seconds to view and delete a spam message" 3. Multiply these two figures together to get carbon footprint-per-activity 4. Multiply by the number of times the activity is performed to get overall carbon footprint. Server side: 5. Estimate carbon footprint of the internet and divide by total data traffic to get footprint-per-MB 6. Estimate data traffic per activity X 7. Multiply them together to get footprint-per-activity X 8. Multiply by the number of times the activity is performed to get overall carbon footprint. In my opinion, there are all kinds of problems with these studies. Even though I know and respect some of the people who are putting them out I think they are missing the mark, every single one of them. Let me rattle off some of the problems: - The estimate in part 2 is pulled out of the sky. Often it comes from surveys or questionnaires. But users multi-task and run background tasks and do all kinds of things that aren't picked up in questionnaires. What they should do is monitor users over a period of time and record the percentage of time which is actively spent on the activity, but this is rarely if ever done. - There is an assumption that user time scales linearly. If one person gets one spam message and spends 3 seconds on it, the person who gets 1000 messages spends 3000 seconds on it. I suspect, though don't know for sure, that these relationships are not linear, and that this might undermine the validity of step 4, the aggregation. - User time is treated as a conserved resource, where the removal of a 3-second activity means an energy savings of 300 Watt-seconds, assuming a 100W computer. But for most people, computer usage expands to fill the available or allotted time. If you were to study users who used anti-spam software and those who didn't, you should be able to see this claimed energy savings in their power bills, if the savings were real. Of course, it isn't real. - The estimates in step 1 and 5 are completely bogus to begin with. There is huge uncertainty about carbon footprints and I would trust it only within about an order of magnitude, and that's being generous. (The problem is mainly due to the manufacturing side of the product life cycle.) When it comes to quantifying the footprint of activities, things you do on a computer are the hardest to pin down and the exercise is probably the most useless. At the root there is an assumption that users are intentional about their tasks; that the personal tech-related footprint of a user is a function of the tasks they wish to perform, which means you can assign a percentage of their footprint to a specific task. The personal footprint is directly related to the number of hours spent in front of a computer and I suspect, but again don't know for sure, that you would never be able to establish a link between tasks and hours spent, and instead would find very strong associations with things like occupation, socioeconomic status, age, and so on. In other words, it's pretty much a marketing piece, which is unfortunate, but not really shocking.