| dc.description.abstract | Air pollution resulting from industrial activities—particularly Coal-Fired
Power Plants (CFPPs)—has become a critical issue affecting environmental quality
and public health. Fine particulate matter (PM₂.₅) and sulfur dioxide (SO₂) are two
principal pollutants that can degrade water quality through acidification mechanisms.
This study aims to design and implement a real-time air-quality monitoring system
based on Internet of Things (IoT) technology, employing low-cost sensors to detect
PM₂.₅ and SO₂ concentrations and to analyze their relationship with variations in
water pH. Research was conducted in two villages in North Sumatra, Indonesia:
Tanjung Pasir, located near a CFPP, and Lubuk Kasih, situated farther from emission
sources. PM₂.₅ and SO₂ were measured hourly using GP2Y1010AU0F and MQ-136
sensors, while water pH was recorded every three hours with a DfRobot pH sensor.
Results revealed consistently higher PM₂.₅ and SO₂ concentrations in Tanjung Pasir,
with peak values reaching 180 µg m⁻³ and > 4 ppm at night, accompanied by water
pH decreases to below 5.5. Conversely, Lubuk Kasih displayed more stable conditions
with near-neutral pH. Correlation analysis indicated a significant negative
relationship between pollutant levels and pH in the village proximate to the CFPP. The
developed system proved effective, economical, and responsive for monitoring air
pollution and its environmental impacts, and thus holds promise as a data-driven tool
to support sustainable ecosystem protection policies. | en_US |
