An Approach to Monitoring Particulate Matter Based Pollution Using Low-Cost Sensing

Particulate matter based pollution has a health impact on ‘at-risk’ individuals requiring monitoring to reduce and inform the population of exposure. These ‘at-risk’ individuals are those with respiratory and pulmonary illnesses. Currently pollution is monitored by High-Cost pollution sensors (HCPS) which can be deployed in limited fashion due to expense. A low-cost alternative can be used to provide greater sensor density for the same budget there-by better informing the ‘at-risk’ population. This study compares the accuracy of low-cost particulate matter sensors as an alternative to a HCPS that are generally used for this purpose. In our evaluation a low-cost sensor was co-located with a HCPS for a period of one month. Data was collected from both sensors in order to enable a comparison. Raw data comparison showed that readings generated from our low-cost sensor fell within the same Air Quality Index (AQI) banding as data from the HCPS. Although the data produced by the low-cost sensor is functionally accurate (classification of pollution within the AQI bands), accuracy could be improved using an algorithmic calibration curve. This could allow for many low-cost systems to be deployed across a wider geographical city area, improving coverage. Helping in-forming the general public of risks and measure to reduce exposure.