Application and Evaluation of a Low-cost PM Sensor and Data Fusion with CMAQ Simulations to Quantify the Impacts of Prescribed Burning on Air Quality in Southwestern Georgia, USA
Creators: name: Huang, Ran
name: Lal, Raj
name: Momei Qin
name: Yongtao Hu
name: Armistead G. Russell
name: M. Talat Odman
name: Afrin, Sadia
name: Garcia-Menendez, Fernando
name: O’Neill, Susan M.
Publisher: name: Taylor & Francis
Year: 2021
Subjects: subject: Biophysics
subject: Medicine
subject: Biotechnology
subject: 59999 Environmental Sciences not elsewhere classified
subject: FOS: Earth and related environmental sciences
subject: FOS: Earth and related environmental sciences
subject: 39999 Chemical Sciences not elsewhere classified
subject: FOS: Chemical sciences
subject: FOS: Chemical sciences
subject: 69999 Biological Sciences not elsewhere classified
subject: FOS: Biological sciences
subject: FOS: Biological sciences
subject: 80699 Information Systems not elsewhere classified
subject: FOS: Computer and information sciences
subject: FOS: Computer and information sciences
subject: Plant Biology

description: Prescribed burning (PB) is a prominent source of PM<sub>2.5</sub> in the southeastern US and exposure to PB smoke is a health risk. As demand for burning increases and stricter controls are implemented for other anthropogenic sources, PB emissions tend to be responsible for an increasing fraction of PM<sub>2.5</sub> concentrations. Here, to quantify the effect of PB on air quality, low-cost sensors are used to measure PM<sub>2.5</sub> concentrations in Southwestern Georgia. The feasibility of using low-cost sensors as a supplemental measurement tool is evaluated by comparing them with reference instruments. A chemical transport model, CMAQ, is also used to simulate the contribution of PB to PM<sub>2.5</sub> concentrations. Simulated PM<sub>2.5</sub> concentrations are compared to observations from both low-cost sensors and reference monitors. Finally, a data fusion method is applied to generate hourly spatiotemporal exposure fields by fusing PM<sub>2.5</sub> concentrations from the CMAQ model and all observations. The results show that the severe impact of PB on local air quality and public health may be missed due to the dearth of regulatory monitoring sites. In Southwestern Georgia PM<sub>2.5</sub> concentrations are highly non-homogeneous and the spatial variation is not captured even with a 4-km horizontal resolution in model simulations. Low-cost PM sensors can improve the detection of PB impacts and provide useful spatial and temporal information for integration with air quality models. R<sup>2</sup> of regression with observations increases from an average of 0.09 to 0.40 when data fusion is applied to model simulation withholding the observations at the evaluation site. Adding observations from low-cost sensors reduces the underestimation of nighttime PM<sub>2.5</sub> concentrations and reproduces the peaks that are missed by the simulations. In the future, observations from a dense network of low-cost sensors could be fused with the model simulated PM<sub>2.5</sub> fields to provide better estimates of hourly exposures to smoke from PB. Prescribed burning emissions are a major cause of elevated PM<sub>2.5</sub> concentrations, posing a risk to human health. However, their impact cannot be quantified properly due to a dearth of regulatory monitoring sites in certain regions of the United States such as Southwestern Georgia. Low-cost PM sensors can be used as a supplemental measurement tool and provide useful spatial and temporal information for integration with air quality model simulations. In the future, data from a dense network of low-cost sensors could be fused with model simulated PM<sub>2.5</sub> fields to provide improved estimates of hourly exposures to smoke from prescribed burning.Impliation statement Prescribed burning emissions are a major cause of elevated PM<sub>2.5</sub> concentrations, posing a risk to human health. However, their impact cannot be quantified properly due to a dearth of regulatory monitoring sites in certain regions of the United States such as Southwestern Georgia. Low-cost PM sensors can be used as a supplemental measurement tool and provide useful spatial and temporal information for integration with air quality model simulations. In the future, data from a dense network of low-cost sensors could be fused with model simulated PM<sub>2.5</sub> fields to provide improved estimates of hourly exposures to smoke from prescribed burning. Impliation statement