Measuring residential PM2.5 concentrations using low-cost sensors in the Netherlands

Abstract

Accurate residential air quality assessment is crucial for studying health risks, evaluating local mitigation measures, and empowering citizens. Low-cost, easily operable sensors have gained popularity for enhancing monitoring coverage and providing individuals with air quality measurement tools. This study examines the validity of a low-cost sensor in estimating residential fine particulate matter (PM2.5) concentrations in the Netherlands. We employed a real-time Sensirion SPS30 dust sensor at a 1-minute sampling rate to monitor residential PM2.5 concentrations. 73 sensors were deployed outdoors at participants' residences for an average of 131 days each over fifteen months. Accuracy was assessed by comparing time series data from sensors with that of regulatory stations, using hourly and daily averages for comparison. Average and absolute differences were calculated for each comparison. After data cleaning, 95.7% of measurements were retained. Meteorological factors did not impact the sensor performance. The mean Pearson temporal correlation between the sensor and regulatory network was 0.75 for hourly and 0.88 for daily PM2.5 averages. The average difference ranged from -0.17 to 0.63 µg/m³, and the average absolute difference ranged from 2.42 to 4.50 µg/m³. Correlations remained consistent across various deployment conditions, including height and distance to the nearest regulatory station. This study demonstrates that PM2.5 can be accurately measured over extended periods using low-cost sensors, offering a dynamic, high-quality perspective on air quality, recording variations that regulatory stations and predictive air quality models may overlook. This demonstrates the value these sensors could have for epidemiological studies and evaluation of mitigation measures.