Date of Publication

8-2025

Document Type

Master's Thesis

Degree Name

Master of Science in Applied Physics

Subject Categories

Physics

College

College of Science

Department/Unit

Physics

Thesis Advisor

Maria Cecilia D. Galvez

Defense Panel Chair

Edgar A. Vallar

Defense Panel Member

Tatsuo Shiina
Prane Mariel B. Ong

Abstract/Summary

In the context of urban aerosol monitoring, advancements in monitoring techniques rely on the accurate and efficient evaluation of urban atmospheres. A Mie LIDAR system offers high sensitivity to fine particulate matter in the atmospheric layer. However, the post-processing of data delays the interpretation of information to the public. This study developed a 405-nm LD Near-Range LIDAR (NRL) system designed and calibrated to directly translate the range-corrected signals RCS) into particulate matter (PM) concentrations (µg/m³) (i.e., PM2.5, PM10). The system was configured in a horizontal orientation with the assumption of a homogeneous atmospheric layer. A series of chamber-based experiments were conducted to simulate varying aerosol concentrations using powder (i.e., 50 mg, 100 mg, 200 mg, 300 mg, 400 mg). The co-located low-cost optical particle counters (OPCs) (Temtop M2000 2nd gen and BLATN BR-Smart126s) were deployed and validated against a DustTrak™ DRX Aerosol Monitor 8533 as a reference-grade instrument. The chamber experiments revealed a power-law relationship between the RCS and the PM concentrations through regression analysis using a log-log scale plot. The resulting correction factor reflects strong agreement observed across trials with R² = 0.94 for PM2.5 and R² = 0.95 for PM10. Trial-to-trial consistency was verified to account for experimental variability and to derive the average correction factor translating the RCS to PM concentration. The correction model was applied to the nighttime field measurements. The NRL system was deployed in the De La Salle University–Manila campus. The translated RCS-derived PM values showed strong agreement with the OPC-derived PM values. The time-series plots revealed similarly significant trends under field conditions. This confirms the reliability of the NRL system in translating the received signal intensity. Furthermore, the inverse slope method was utilized to derive the extinction and backscatter coefficients from the atmosphere, resulting in α = 0.0034 m⁻¹, and β = 6.8 × 10⁻⁵ m⁻¹ sr⁻¹, respectively. Additionally, consistent and uniform atmospheric layers can be observed, especially in the < 30 m range. This chamber-based calibration approach demonstrates the potential of the NRL system for real-time PM estimation. This addresses the gap in promoting low-cost LiDAR-based systems for localized near-ground and near-range air quality monitoring. This study further supports the advancements of the atmospheric LIDAR for early-warning systems and public health management.

Abstract Format

html

Language

English

Format

Electronic

Keywords

Atmospheric aerosols—Measurement; Optical radar

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Embargo Period

8-19-2028

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Available for download on Saturday, August 19, 2028

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