Tag: map

“How is waste in my area?” – a regional dashboard

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Introduction

Our aim in this piece of work is:

to surface facts of interest (maximums, minimums, trends, etc.) about waste in an area, to non-experts.

Towards that aim, we have built a prototype regional dashboard which is directly powered by our ‘easier datasets’ about waste.

The prototype is a webapp and it can be accessed here.

our prototype regional dashboard

Curiosities

Even this early prototype manages to surface some curiosities [1] …​

Inverclyde

Inverclyde is doing well.

Inverclyde’s household waste positions Inverclyde’s household waste generation Inverclyde’s household waste CO2e

In the latest data (2019), it generates the fewest tonnes of household waste (per citizen) of any of the council areas. And its same 1st position for CO2e indicates the close relation between the amount of waste generated and its carbon impact.

…​But why is Inverclyde doing so well?

Highland

Highland isn’t doing so well.

Highland’s household waste positions Highland’s household waste generation Highland’s household waste % recycled

In the latest data (2019), it generates the most (except for Argyll & Bute) tonnes of household waste (per citizen) of any of the council areas. And it has the worst trend for percentage recycled.

…​Why is Highland’s percentage recycled been getting worse since 2014?

Fife

Fife has the best trend for household waste generation. That said, it still has been generating an above the average amount of waste per citizen.

Fife’s household waste positions Fife’s household waste generation

The graphs for Fife business waste show that there was an acute reduction in combustion wastes in 2016.

Fife’s business waste

We investigated this anomaly before and discovered that it was caused by the closure of Fife’s coal fired power station (Longannet) on 24th March 2016.

Angus

In the latest two years of data (2018 & 2019), Angus has noticibly reduced the amount of household waste that it landfills.

Angus' household waste management

During the same period, Angus has increased the amount household waste that it processes as ‘other diversion’.

…​What underlies that difference in Angus’ waste processing?

Technologies

This prototype is built as a ‘static’ website with all content-dynamics occurring in the browser. This makes it simple and cheap to host, but results in heavier, more complex web pages.

  • The clickable map is implemented on Leaflet – with Open Street Map map tiles.
  • The charts are constructed using Vega-lite.
  • The content-dynamics are coded in ClojureScript – with Hiccup for HTML, and Reagent for events.
  • The website is hosted on GitHub.

Ideas for evolving this prototype

  1. Provide more qualitative information. This version is quite quantitative because, well, that is nature of the datasets that currently underlay it. So there’s a danger of straying into the “managment by KPI” approach when we should be supporting the “management by understanding” approach.
  2. Include more localised information, e.g. about an area’s re-use shops, or bin collection statistics.
  3. Support deeper dives, e.g. so that users can click on a CO2e trend to navigate to a choropleth map for CO2e.
  4. Allow users to download any of the displayed charts as (CSV) data or as (PNG) images.
  5. Enhance the support of comparisons by allowing users to multi-select regions and overlay their charts.
  6. Allow users to choose from a menu, what chart/data tiles to place on the page.
  7. Provide a what-if? tool. “What if every region reduced by 10% their landfilling of waste material xyz?” – where the tool has a good enough waste model to enable it to compute what-if? outcomes.
1. One of the original sources of data has been off-line due to a cyberattack so, at the time of writing, it has not been possible to double-check all figures from our prototype against original sources.

Waste sites and the quantities of incoming materials

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The dataset

SEPA publish a “Site returns” dataset (accessible via their Waste sites and capacity tool) that says…​

  • how many tonnes
  • of each (EWC coded) waste material
  • was moved in or out
  • of each authorised waste site in Scotland.

Here is an extract…​

SEPA Site returns sample

This is impressive, ongoing data collection and curation by SEPA.

But might some of its information be made more understandable to the general public by depicting it on a map?

Towards answering that, we built a prototype webapp. (For speed of development, we considered only the materials incoming to waste sites during the year 2019.)

Data mapping

To aid comprehension, SEPA often sorts waste materials into 33 categories. We do the same in our prototype, mapping each EWC coded waste material into 1 of the 33 categories…​

33 materials, categorised

The “Site returns” dataset identifies waste sites by their Permit/Licence code. We want our prototype to show additional information about each waste site. Specifically, its name, council area, waste processing activities, client types, and location – very important for our prototype’s map-based display!

SEPA holds that additional information about waste sites, in a 2nd dataset: “Waste sites and capacity summary” (also accessible via their Waste sites and capacity tool). Our prototype uses the Permit/Licence codes to cross-reference between the 2 SEPA datasets.

SEPA provides the waste site locations as National Grid eastings and northings. However, it is easier to use latitude & longitude coordinates in our chosen map display technology so, our prototype uses Colantoni’s library to perform the conversion.

The prototype webapp

A ‘live’ instance of the resulting prototype webapp can be accessed here.

Below is an animated image of it…​

our prototype webapp

UI & controls

  • Each pie chart depicts the amounts of materials incoming to a single waste site, or the aggregation of waste sites within a map area.
    • single waste site pie Depicts a single waste site.
    • multiple waste sites pie Depicts an aggregation of 26 waste sites.
  • no pie (I.e. a number without a surrounding pie chart) depicts a waste site with no incoming materials (probably because the site was not operational during 2019).
  • material details pop-up Hovering the cursor over a pie segment will pop-up details about incoming tonnes of the material depicted by the segment.
  • area highlighting Hovering the cursor over a pie that depicts an aggregation will highlight the map area in which the aggregated waste sites are located.
  • waste site pop-up Clicking on a single waste site will pop-up details about that waste site.
  • zoom control The webapp supports the usual zoom and pan controls. The user can also double-click on an aggregation pie to zoom into the area that it covers.
  • attributions Clicking on ‘attributions’ will display a page that credits:

Closing thoughts

But might some of its information be made more understandable to the general public by depicting it on a map?

For any good solution, the answer will be an obvious ‘yes’. But what about for our prototype webapp solution?…​

We think that it could help pique interest in the differences in the amounts & types of waste materials that are being disposed in different areas of the country. For example…​

splash view

Glancing at our prototype’s map (image left; at the default zoom level), the seemingly disproportionate amount of soils & stones coming into north west Scotland waste sites catches our attention.

So we zoom in (right image) to find that almost all of it is accounted for by one landfill site on the the Isle of Lewis.

 Bennadrove landfill site

Future work could increase the utility of this prototype webapp by:

  • allowing the user to browse over the time-series aspect of this dataset using a time slider control (like our through time on a map prototype)
  • providing a means to switch the focus of interest from incoming material to: outgoing material, processing activities (landfill, composting, metal recycling, etc.), or facilities offered (household, commercial, special disposals, etc.)
  • supporting filtering over the various dimensions
  • providing the means for a user to open their current data selection in a tool (like our data grid & graph prototype) that allows them to explore the data in more detail.

How I chanced on Longannet in the data

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I’ve added a “Household vs business waste” time-series to our map-oriented webapp from last week. The business data was parsed from SEPA’s Business Waste Data Tables.

When I watched the waste amounts change through time on this map, Fife’s amounts really stood out…​

Household vs business waste, thru time

Fife was generating so much more waste from business, than the other council areas. But why?

To look at the data in more detail, I loaded it into the data grid & graph tool that we built a couple of months ago.

First, I filtered the data grid to show me: Fife’s four largest, business wastes vs their averages link.

Fife’s four largest, business wastes vs their averages

Fife’s combustion waste stands out from the average.

Secondly, I filtered the data grid to show me: the business combustion waste quantities by sector link.

Business combustion wastes by sector

Unfortunately this data isn’t broken down by council area, but it clearly shows that most of the combustion wastes are generated by the power industry.

An internet search with this information – i.e. “Fife combustion power” – returns a page full of references to Longannet – the coal fuelled power station.

Longannet power station (courtesy of Scottish Power)

According to Wikipedia, Longannet power station was the 21st most polluting in Europe when it closed, so no wonder that its signature in the data is so obvious! It was closed on 24th March 2016, which correlates with the sharp return towards the average in 2016, of the combustion wastes graph line for Fife.

Of course this isn’t a real discovery – SEPA, Scottish Power and the people who lived around the power station will be very familiar with this data anomaly and its cause. But I think that its mildly interesting that a data lay person like me could discover this from looking at these simple data visualisations.

Waste quantities through time, on a map

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Preface

Shortly before the end of 2020, I attended the Code The City 21: Put Your City on the Map hack weekend which explored ideas for putting open data onto geographic maps.

It ran several interesting projects. There was one was especially inspiring to me: the Bioregion Dashboard. Its idea is to tell an evidence-backed story-through-the-years, involving interactive data displays against a map. James Littlejohn introduces it in this YouTube video.

This got me thinking about new ways to depict the information that is bound up in the data about waste…​

In particular, thinking about a means to convey at-a-glance, to the lay person, how councils areas compare through time in respect of the amounts of (household solid) waste that they process. Now, the grid & graph prototype that we built a couple of months back, conveys that same information very well (and with a greater fidelity than we will mange in this work) but, to the lay parson like me, it isn’t attention grabbing. I like seeing something with movement and with features that I can relate to, such as animated charts and a geographical map.

The prototype webapp

Leveraging what I learnt at the Code the City 21 hack weekend, I hacked together a prototype webapp that shows how waste quantities change through time, on a geographic map.

The below, animated image of the webapp, it conveys that landfilled-waste is reducing over time whilst total-waste is remaining fairly constant.

Managed solid waste, through time

UI controls

  • The dataset of interest is chosen through the dropdown control, either:
    1. Tonnes of managed solid household waste per person per year.
    2. Tonnes of C02 equivalent from household waste per person per year.
  • Use the slider control to travel through time.
  • Each pie chart depicts the waste-related quantities for a council area.
    • The sizes of its slices and its overall size, are related to the quantities that it depicts.
  • Hover over a council area to see detailed metrics in the detail panel.
  • The usual map zoom and pan controls are supported.

Software and datasets

CO2 equivalent

‘Live’ instance

A ‘live’ instance of this webapp can be accessed here .

Closing thoughts

I haven’t seen these datasets about waste shown in this way before, and I think that it usefully conveys aspects of the datasets in a catchy and easy to understand way. It is low fidelity when compared to a full data grid with graph solution, but the idea is to hold the attention of the average person in the street.

Future work could integrate additional waste-relevant datasets that have geography and time dimensions. Also we should consider alternative metrics (such as ratios), alternative charts (such as bar or polar) and alternative statistics (such as deviation or trend). I went with the ‘most straightforward’ but user-testing might indicate that an alternative is better.