Category: Samples

Circular Zinc Flows

While some were indulging in an extended spring cleaning (this year labeled ‘quarantine cleaning’) I decided to take on some of the hard disks sitting on my desk.

These circular zinc flow diagrams from 2011 survived the cleaning and are getting a new life here on the blog. They are more or less two versions of the same diagram, apparently with a Sankey diagram in mind.

The first is a top view and shows zinc flows in the economy (U.S. or world? … sorry, but I don’t have the accompanying text any more). Flows are in millions of tonnes (Mt) in 1996. The second one has the same numbers, but adds a 3D perspective…

Some tricky issues here: The ‘zinc in products’ stream of 8.1 Mt narrows down to zero, as the zinc sits in products, from where it later might be released into the cycle again. This does not help the attempt to draw them in a circle (to associate circularity of zinc flows). As a consequence the streams are not to scale (compare, for example the 0,8 Mt scrap feed flow right next to the 6,6 Mt flow for zinc from mines). The 3D perspective and the shadow effect don’t help in any way here…

Check out some more Sankey diagrams with the tag ‘circular’ and this post on radial Sankey diagrams.

Sankey Diagrams for Expressing Relevance

SaraVaca is a specialist on evaluation and data visualization. She runs the VisualBrains blog (check out the visuals CVs section!).

In a 2016 post she discussed using Sankey diagrams to express “Relevance” in evaluation. Having in mind a quantifiable flow perspective in Sankey diagrams, I was not sure how relevance could be translated. “Relevance in Evaluation is understood as the extent to which the aid activity is suited to the priorities and policies of the target group, recipient and donor”, she explains. So for a Sankey diagram that would mean expressing the “extent” or “suitability” in numbers. Which can of course be done either by assigning weight criteria or doing an ABC analysis.

Here is Sara’s sample:

We can see bands of four different widths. Additionally there is a color-coding for different categories for which the relevance is measured. Interesting approach. In 2017 she followed up with a post on ‘More inclusive (Sankey) diagrams to analyze Relevance’.

Textile Flows in the United States

RRS, a consulting firm with expertise in waste reduction, life cycle management and applied sustainable design has this Sankey diagram on textile streams in the US garment industry.


While the figure doesn’t show any numbers explicitly (which I am sure exist, and were used to set up this schematic Sankey diagram), the idea is to show existing alternative paths for post-consumer textile use. Green flows are recycle, reuse and repurpose, while red streams are to incineration. The largest stream is to landfills. RRS is developing ideas and helping to change the material flows in the textile sector to be more environmentally friendly.

Greenhouse Gas Emissions Mexico 2015

Here is a great Sankey diagram visualizing the greenhouse gas emissions of Mexico in 2015. This graphic comes from the ‘Sexta Comunicación Nacional y Segundo Informe Bienal de Actualización ante la Convención Marco de las Naciones Unidas sobre el Cambio Climático’ published by Secretaría de Medio Ambiente y Recursos Naturales (SEMARNAT) and Instituto Nacional de Ecología y Cambio Climático (INECC).

The Mexican national inventory of emissions of gases and composites withe greenhouse effect (Inventario Nacional de Emisiones de Gases y Compuestos de Efecto Invernadero) is compiled by INECC on a regular basis as part of its reporting as a signatory to the United Nations Framework Convention on Climate Change (UNFCCC). The report is here, you can find the graphic on pages 110/111.

On the left side we see the different sectors of the country and their contribution to the emission of the 665 Mt (megatonnes) of GHG gases in 2015. The unit of measure is Mt CO2 equivalents. For each of the sectors this is further broken down to the activities causing the emissions. Further to the right these emissions are split to the individual underlying gases,. We see a large share (75%) caused by carbon dioxide (bióxido de carbono), methane and nitrous oxides. 492 Mt CO2eq were released to the atmosphere, while 173 Mt CO2eq were sequestered (absorbed by plants and soil).

1913 public transport 3D map

Leafing through Brinton’s 1914 book ‘Graphic methods for presenting facts’ I found this example of a 3D map that has elements of a Sankey diagram.

This map (photo taken from an exhibit at a 1913 exhibition) shows passenger numbers on the Frankfurt streetcar lines (back then when trams were still called streetcars!)


Brinton explains that “we have a map presentation in which quantities are represented by building vertically above the various routes laid out on the map … made by strips of wood, alternately black and white, glued carefully above each one of the street-car routes. Each of the strips of wood represents 4,000 passengers carried on the street-car lines in 24 hours” (page 224).

The built up flows showing passenger numbers would, if laid sideways, indeed make a Sankey diagram. Building them up using the third map dimension avoids the issue of dealing with wide Sankey arrows in a dense city center, where passenger numbers are highest.

Brinton’s book, although over 105 years from its publication still makes for a great read (as does his 1939 book on ‘Graphic Presentation’, which is basically a sample book for doing infographics).

LatAm BEN – Peru

Here is another post in my loose mini-series featuring energy balances of Latin American countries. I had shown Peru energy flows for 2009 in this post, but here is a more recent one for 2017.


This is from page 122 of the official ‘Balance Nacional de Energía 2017’ report published by Ministro de Energía y Minas (MINEM) of Peru. PDF here.

Flows are in terajoules (TJ). Natural gas and hydro energy are the two largest sources. Transformation losses (pérdidas de transformación) amount to 45%. The split on the consumption side separates mining from industry, and we can see that this sector is the largest energy consumers.

Energy Use per Industrial Sector, Indonesia

The article ‘Tracing the energy footprints of Indonesian manufacturing industry’ by Yales Vivadinar, Widodo W. Purwanto & Asep H. Saputra from Department of Chemical Engineering, Universitas Indonesia, Depok, Indonesia (published as Open Access in: Energy Science and Engineering 2016; 4(6): 394–405) looks at typical energy usage in different industrial manufacturing sectors in Indonesia.

There are Sankey diagrams representing “energy maps” for basic chemicals, cement, pulp, paper, spinning, weaving and textile finishing. I am showing two of them below. The first one is for the basic chemical industry.

Flows are in kboe (thousand barrels oil equivalent) for the year 2013. Losses are shown as grey arrows. The second one is for textile finishing:


For those of you interested, please read the full paper here.