Waiting in the heat: A low-cost data collection method to evaluate bus stop environmental exposure

Urban transit environments are critical sites of heat and air pollution exposure, yet lack continuous, high-resolution measurements. Designing an effective urban sensing campaign requires balancing device suitability, environmental threats, and location assessment in public spaces. This paper presents an active sensing framework for monitoring thermal and air quality conditions at bus shelters, combining controlled experimentation with in situ deployment. We combine the design and evaluation of a 3-D printed modification to low-cost PurpleAir sensors for installation in tamper-prone transit environments with assessment of sensor quality relative to reference monitoring equipment. Using a sequential field experiment, we quantify how configuration influences temperature and particulate matter (PM) measurements and demonstrate that biases introduced by sheltered deployment are systematic and correctable. A deployment-specific calibration model reduces mean absolute error in temperature measurements to 1.03°C under shaded, shelled conditions, without requiring sensor-specific refitting. For PM 2.5 , measurement error is primarily driven by relative humidity, and incorporating both sensor and reference humidity enables effective bias correction. This low-cost sensor approach enables scalable, exposure-relevant monitoring of transit environments and illustrates how active urban sensing can inform infrastructure design and support data-driven transit design.