MAQC

a toolkit to facilitate Measuring Air Quality from Construction

We are MADE MSc students at the AMS Institute in Amsterdam. In collaboration with the MIT Senseable City Lab, we experimented with low-cost sensors called City Scanners to measure air quality around construction sites. However, we encountered a number of practical hurdles that made it difficult to produce reliable results. As a result, we have created a guideline for other professionals and researchers who want to conduct similar experiments in the future, outlining the challenges we faced and offering suggestions for how to overcome them.

Our guidebook

Our code

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Why measure air quality?

Construction companies
Policymakers

“Meten is weten” (measuring = knowing)

Construction companies are increasingly aware of their social responsibility as well as economic incentives to minimize pollutants. However, prioritizing interventions when investment costs are high can be difficult. Implementing low-cost sensors on-site or on your machinery could inform sustainable investment decisions.

Healthy work environment

Creating a healthy work environment for construction workers is important. Measuring on-site, and especially on-person, allows workers to measure their direct exposure to pollutants. This information can be used to improve the working conditions.

Competitive advantage in tenders

There is increasing attention to sustainability measurements in the construction sector from the government and the media. Therefore, if you can demonstrate that you apply sustainable building practices, it will give you a comparative advantage over other contractors in tender processes.

What is the MAQC toolkit?

We developed the MAQC (“maxi”) toolkit was developed over the course of our research project, with the intent to make it easier for other researchers and professionals measure air quality around construction sites. The toolkit consists of two things: a guidebook and a code repository. The guidebook is a document with seven chapters, each containing tips for one step in the measurement process. The code repository contains functions and classes we used for data processing.

Curious? Check out the guidebook here.