From Farm to Table. How much Greenhouse Gas does each food, and/or process contribute, and what you can do to curb it.

There’s quite a process for the food we eat. There is food being planted now that we will not consume till much later. In all of that time, different parts of the process are contribution to greenhouse gas (GHG) emissions. The original article from MakeOverMondays mentions that eating locally is something we hear to try and reduce emissions. But it’s probably not the most effective way to curb results. I agree, however, there may be something else we can do that would be more effective, yet it appears to be the one we would be least likely to give up. We are going to break down this info into more digestible chunks, and recommend something clearer.

The original graph shows a lot of information to analyze (left). It shows processes that food goes through from start to finish. It shows different types of food and how they fit in to the process. The original suggestion was to not focus on eating locally, but focus on what you eat instead. Agreed, but let’s dive deeper and see if we can get more specific.

Which process contributes the most to GHG?

The most visible processes of getting food from farm to table would be:

  • Farming

There are more processes, but these just seemed the most obvious and evident. Other processes include, land-use-change, livestock feed (though this was partially included in our analyses), retail, and packaging.

Data Source: Poore and Nemecek #MakeOverMonday. Tablaeu Data Story


In the graphic (left)(full data story available here), it shows GHG emissions by food product. In farming, notice how many of the small contributors are non-animal products. Those top 6 were outliers in the dataset. Beef was STILL and outlier within the outliers. An outlier is a data point that is excessively far from its next closest data point. Outlier max would be 29.75kg/kg (kg CO2/kg food product). Beef came in at 39.4kg/kg. In the bottom center graph, cow products contributions are larger than that of non-animal products combined. Livestock feed for cows was the highest (bottom right).

Data Source: Poore and Nemecek #MakeOverMonday. Tablaeu Data Story


There were outliers again. These 5 food products (shown above). Beef is tied for 1st (1.3kg/kg), and 3 out of the 5 are animal products. Comparing it back to farming, beef is high on both measures, farming and processing. However, 1.3kg/kg is a significant decrease from 39.4kg/kg.

Data Source: Poore and Nemecek #MakeOverMonday. Tablaeu Data Story


Once again there are outliers. Beef appears on low end of the outliers, but an appearance nonetheless. The top 3 were non-animal products. The GHG contributions are also much lower, even on the high end, coming in at about 0.8 kg/kg.

If we look at the contributions by process, farming has the highest average, followed by processing and transport. Transport was the lowest of these three. It seems safe to say that transport plays a small roll in overall GHG contributions, so eating locally may not be the most effective way to curb GHG emissions.

Which food product contributes the most to GHG?

The data suggest with a fair amount of certainty that livestock is a large contributor. Partly due to it being a simultaneous double contributor. Animals contribute while they are alive, but also growing food for them. The demand for it seems extremely high given that they were outliers, and some on multiple occasions.

Biases and Limitations in the data

The info on this only contains kg/kg. This is an average, and does not show total contributions by category. This doesn’t tell us how many of each category there are, therefore not getting a total contribution.

We focused on the highest contributors, in one mentioning that beef is bigger than the others combined. There could be more non-animal products that were not counted in this data set, so it is possible that they could be equal, or more.

In transport, it doesn’t account for distance. The original article mentions maybe eating locally may not be the best way, which may be true, but it doesn’t account for distance traveled. Olive oil was one of the higher contributors in transport, and could be due to the distance traveled, not the quantity, if it is primarily coming from one location.

Having several sections with outliers on the high end means these are heavy contributors. Especially outliers within outliers.

There were other contributor stages that were not explored in this data story. The info is there but these were chosen because they are more “visible” to everybody. From the original graph, the green section is land-use-change. This was one of the next biggest sections. Maybe some awareness needs to be brought to this. People do mention how forest or other land masses are being cut down and “changing the land” to farm. Maybe people aren’t aware as to how much this is occurring. That is why I didn’t include it. It doesn’t occur to the majority as a natural logical process of acquiring food. Most of us assume the same land is being used over and over, and don’t realize the demand and the need for expansion. Or perhaps climate is forcing some to find new locations for the same products. The data does not include what the new land is being used for, or why new land is needed. These are other hypotheses. The new land could be for low contributors and/or high contributors. If demand is that great for the outliers, we could be looking at having those numbers increase even more.

So what can you do about it?

Eating locally to reduce transport, therefore curbing GHG emissions from transport? From the data that was analyzed, we came to a fairly certain conclusion that transport is a small fraction of GHG emissions. Their recommendation was to not focus on eating locally, but watching what you eat altogether. That is a good suggestion but I think we can get more specific. The largest contributors were livestock. They were a double contributor because we are growing their food at the same time we are maintaining them. And this is why I think the most actionable thing we can do is the most difficult. Consume less livestock. If livestock is an outlier, it is likely demand is very high. By reducing demand, it will reduce contributions. It doesn’t have to be “cold turkey” (pun intended), but baby steps, and slowly through time we can adapt. Some have mentioned cutting it out of your diet for one day out of the week. Then perhaps slowly increasing to 2 days a week.

If we want to get a little more specific, cut back on beef products. Several companies have started making imitation meats, that taste and feel like beef, but are plant-based. We saw the impact non-animal products have on emissions. Some of these plant-based products have passed blind taste tests. I myself don’t mind them. Again, they are not beef, and get pretty close to taste and texture, but the effect GHG are much better, if that is the goal. Some of these are more expensive, probably because of the processing. Could the processing of these products equal up to the same amount go GHG that livestock contributes? If demand increases and supply does too, it may be able to bring down prices.

If you want to try and spread it out, then start cutting out all other animal products, including cheese, milk, eggs, etc. Rome wasn’t built in a day. Our culture needs to change a lot to facilitate this transition. But starting small would be a good first step. After all, (another pun) how would you eat a whole cow? One bite at a time.



Tableau Data Story

Google Slides Data Story