Air quality data for all: The case for air quality research in the Philippines

Air pollution accounts for 2.2 million premature deaths in the Western Pacific Region. In the Philippines, mortality rates related to poor air quality reached 45.3 deaths for every 100,000 people in 2018. Apart from the cost to lives, pollution has cost the country US$ 1B in 2015, which accounts for 0.3% to 0.4% of the country’s gross domestic product.

Despite the cost to life and associated economic burden, the current system for sampling air pollution data - both indoor and outdoor in urban areas - has not provided dense spatiotemporal distribution information to identify air pollution hotspots.

While the sensor installations of the government and private sector in some parts of the country provide data on the current status of air pollution, one air quality sensor system per city - the average in the Philippines - provides very little information on how pollution is distributed and may not be able to identify hotspots that increase the exposure of the general public.

To close the gap in the strategic installation of air quality sensor systems and the availability of actionable data on air quality status, the University of the Philippines’ College of Engineering proposed the UP Center on Air Quality Research in Urban Environments (UP CARE) research program for government funding. This program provides a venue for engineers, scientists, health professionals and other domain experts to solve this collective challenge on air pollution.

 Our talk will focus on UP CARE’s efforts to study how pollutants, both gaseous and particulate matter, are dispersed in urban environments. One key component in this program is the development of an IoT infrastructure and its online platform that connects various locally-developed wireless sensor nodes to measure air pollutants generated by vehicles traversing the streets of central business districts and determine how much of these pollutants enter homes, schools, and offices. In addition, the online platform would include mobile sensing modalities in our trains, buses, and cars plus personal measurements through wearables to complete the cycle of exposure to air pollution parameters one encounters daily. The goal is to integrate these measurements into a resilient and scalable IoT platform that will enable the development of applications that the general public could use to mitigate their personal exposure to air pollution and allow the local agencies to devise a more reliable approach/plans to decrease the risk of their constituents and stakeholders. The ever-expanding database of measurements will provide datapoints for researchers to improve dispersion and forecasting models and improve our understanding of the long-term effects of air pollution to one’s health.