Monitoring Technology

Hailing from Greece, Sotirios Papathanasiou is an air quality expert. His blog, See The Air, focuses on air quality monitoring, pollution analysis, and activism pushing cities around the world to concentrate on clean air.

The Pearson squared correlation coefficient (R²) is calculated to determine how measurements from a device under analysis correlate with measurements of a reference instrument, or in other words, how well the device under analysis measures changes in pollutant concentration compared to the reference instrument.

Mean Absolute Error (MAE) is calculated to determine the absolute difference between the measurements of a device under analysis and the measurements of a reference instrument. It is the average of the absolute value of the deviations between measurements of the two devices. In other words, it shows how different measurements from the two devices are in value.

The wide acceptance and adoption of indicative monitoring technologies in air quality management practices are enabling new insights and actions at lower costs, higher data resolutions, and with less maintenance. For these benefits to truly shine through, we must first address the most important question when it comes to taking air quality readings as truth - how accurate is the sensor?

As we post this blog, most of our daily lives have been disrupted by the coronavirus COVID-19 outbreak. During a time of uncertainty shrouded by fear, we are grateful for first responders, medical staff, and scientists everywhere at the frontline of this pandemic.

The rising number of chronic diseases linked to poor air quality has brought to light the severity and urgency of air pollution — the cause of 8 million early deaths worldwide each year.

Cities around the world are spending billions of dollars to address urban pollution. London alone has pledged to spend over $1.1 billion over the next five years.