The geoFluxus manifesto

We determine the areas of greatest impact by first gathering as much information as possible about the area in question. Then we estimate how much we know, and how much we don't know. We communicate the uncertainty between known and unknown to our clients, because identifying data gaps is a good way to determine practical next steps. We place all figures in the larger context by comparing them with each other and selecting the largest ones based on size or environmental impact.

Reducing household waste is high on the agenda of many governments. Although households and individuals are also responsible for reducing the impact of their consumption, their relative share of total waste in the Amsterdam Metropolitan Area is barely 11% compared to the 89% of commercial waste. The unique combination of data allowed us to accurately track this ratio for the first time for the Amsterdam municipality. This creates perspective on the relative contribution of household waste to the total amount of waste in the area. This leads to increasingly informed decision-making.

We provide not only numbers, but also knowledge. We put our numerical findings in the right (human) context. This means we communicate what we think the numbers mean, what they don't mean, and where to start digging if we want to know more.

To give an example: through our reclassification algorithm, we found that 19.6% of all commercial waste in the Amsterdam Metropolitan Area was directly reusable. This was the first time such a summary statistic was calculated. Yet it also turned out that only a few economic sectors provided sufficient additional data to make the calculation possible, leading to the identification of sector-specific data gaps.

However, this did not mean that these materials were immediately reused. In some cases, they were simply stored, without knowing if and when they would be reused or disposed of. In some cases, we saw such streams going to incineration. It seems plausible that they could have been processed by a method that retains a higher value. The reasons for not doing so can be varied, from legal to economic. The difference between streams that were labeled as directly reusable and their final processing option allowed us to identify specific material streams that consistently lost value, such as A-rated wood from construction that was burned or composted.

These important lessons provided the municipality with new insights, statistics, and starting points for policy development.

Clearly, not all discarded products and materials can fall under the same objectives and policies. Organic waste obviously cannot be "refurbished" or "repaired," scrap from the production process cannot be "reused," and renewable energy sources cannot be "rejected" if they replace critical raw materials. This calls for the distinction of targets - and thus metrics - at least by material group and economic sector.

Although this seems a rather obvious example, we see that the unexpected effects and mismatches occur in every dimension analyzed. Therefore, we approach the problem with five lenses and their combinations for providing metrics. The lenses allow us to view each data point in its specific context, minimize generalization, and keep the focus on the big picture.

1. The geospatial lens allows metrics to be viewed according to different administrative units and compared with other administratively available data, particularly social and environmental quality. Since waste generation and treatment often do not occur within the same administrative units, the flows and relationships between them also become important.

2. The Temporal Lense allows tracking changes over time, observing seasonal patterns, relating changes to other large-scale events, determining cause-and-effect relationships between policies and effective changes.

3. The Economic Sector Lense enables targeted policy design, identification of opportunities for industrial symbiosis, and differentiation of the environmental impacts of economic activities themselves from the impacts of their materials. Economic sectors can be explored using internationally recognized NACE codes or special groupings, e.g., based on position in the value chain.

4. The material lens distinguishes streams based on their content: original raw material, product, composition, waste classification-taxonomy are all different parameters that can be explored through the lens.

5. The process lens focuses primarily on the end-of-life products that undergo a particular treatment. This lens allows to see potential value retention and assess the effects of material disposal.

We integrate the principle of identifying truly circular resource flows by engaging in networking. We literally map resource flows to understand which resources, in which context, can be considered circular. We convert all the data, using geospatial algorithms and specially developed correspondence tables, into a format that can tell us more about the content of the flows and spatial movements.

First, we break down the content of the streams into materials and conditions for high-value applications to reverse the process; from end-of-life to cradle. The material content helps us understand whether the material can make a full circle and be reused in the same product or process. Sometimes such a cycle is possible only at the substance level (e.g., phosphorus can be recovered from wastewater and reused for food production), sometimes at the material level (e.g., using recycled glass to produce bottles over and over again), rarely at the product level. By assigning labels to material streams such as pure/mixed, compound/raw, product/material, etc., we can see if the given stream can find its way back to its source.

The spatial context is important to follow the stream's journey back to its origin, to truly understand whether or not its use can be made geographically circular. Resources leaving a country's borders do not necessarily indicate resource loss or less sustainable use. At the same time, imported resources are not necessarily less sustainable than locally produced ones. Only by tracking global reach is it possible to make reliable assessments.

When it comes to resource flows, we gather as much information as possible to see the big picture. We combine knowledge and methods from different disciplines into one platform. At the same time, we ensure that our findings can be reused by other organizations and combined in the broader knowledge network.

Currently, in our platform we combine traditional Material Flow Analysis (which answers the question, "How many resources are there in a system?") with Geographic Information Systems ("Where do these flows go?), Input Output Analysis ("Which economic activities consume which resources?"), Life Cycle Assessment ("What is the environmental impact of these flows?") and data visualization ("How can we understand the patterns?").

The road network on the left represents the amount of carbon emissions produced in 2019 on each road segment from waste transport alone. Producing such a picture from the underlying data requires integrating all the analysis methods mentioned earlier.

The road network, metadata and all related data can be downloaded for each visualization, and the calculation methods are freely accessible in our code repository. Therefore, our approach is scalable, open-source and multidisciplinary.