Definition of a Sankey Diagram
A Sankey diagram is a specialized type of flow diagram where the width of the arrows is directly proportional to the quantity of the flow they represent. These diagrams are designed to visualize transfers and distributions of various quantities, such as energy, materials, money, or information, from one set of states or processes to another. They are particularly useful for illustrating complex systems with multiple inputs, outputs, and intermediate stages, making magnitudes and inefficiencies immediately apparent.
Key Principles and Components
The fundamental principle governing a Sankey diagram is the conservation of flow: the sum of the widths of the input arrows must always equal the sum of the widths of the output arrows. Key components include nodes (rectangles or blocks) that represent processes, states, or categories, and links (arrows) that depict the flow between these nodes. The precise thickness of each link visually communicates the quantitative value of that specific flow, allowing for intuitive comparison of different pathways and contributions.
Practical Example: Global Carbon Emissions
Imagine a Sankey diagram illustrating global carbon emissions. Major sources like fossil fuel combustion, industrial processes, and land-use change would be represented by thick input arrows. These flows would then branch into various sinks, such as oceanic absorption, terrestrial uptake, and atmospheric accumulation. The varying widths of these arrows would visually demonstrate which sources contribute most to emissions and how carbon is distributed among different environmental reservoirs.
Importance and Applications
Sankey diagrams are powerful analytical and communication tools across numerous STEM fields. In engineering, they help optimize material and energy use; in environmental science, they clarify resource flows and waste generation; and in economics, they illustrate financial transactions and trade balances. Their ability to succinctly highlight dominant flows, inefficiencies, and system dynamics makes them indispensable for decision-making, process improvement, and effective data storytelling.