LOW-COST MONITORING OF AIR QUALITY IN HIGH-TRAFFIC URBAN AREAS OF PANAMA: A PRELIMINARY ASSESSMENT

Wed, 07 May 2025 00:00:00 +0000

This study presents the results of atmospheric pollutant monitoring for PM₁₀, PM2.5, NO₂, and O₃ in two of the most densely populated areas of Panama. Data were collected using a low-cost Aeroqual 500 series device, which, given the limited air quality monitoring infrastructure in the country, serves as a practical tool for generating valuable information to raise awareness among citizens and local authorities. The levels of PM₁₀, PM2.5, and NO₂ were relatively low, whereas O₃ concentrations exceeded the thresholds established by organizations such as the USEPA (for comparative purposes only). The most critical sites identified include the Gran Estación de San Miguelito, where PM₁₀ levels reached up to 34 µg/m³, likely influenced by its location at the intersection of major traffic arteries (Transístmica and Tocumen). The UTP-Site 2 Tocumen University Extension, situated near a highway, recorded the highest PM₂.₅ levels at 10 µg/m³. Regarding NO₂, the highest concentrations were observed in Plaza Princesa de Gales, Panama Norte, but remained relatively low (39 ppb). Similarly, O₃ levels were elevated in Plaza Princesa de Gales, with observed values ranging from 0.066 to 122 ppm. Standard deviations suggest moderate variability in PM₁₀, PM2.5, and O₃ measurements, whereas NO₂ levels exhibited significant fluctuations. These findings underscore the considerable contribution of vehicular emissions to urban air pollution in Panama, particularly concerning the high O₃ levels. Further in-depth studies are needed to better understand these trends and their implications for air quality management.

LIGHTNING–METEOROLOGY RELATIONSHIPS OVER SRI LANKA AND INDONESIA: A MACHINE LEARNING APPROACH

Wed, 07 May 2025 00:00:00 +0000

The relationship between lightning flashes (LF) and various meteorological parameters is analyzed using lightning data from 1995 to 2014. The meteorological parameters considered in this study include aerosol optical depth (AOD), precipitation (P), relative humidity (Rh), convective available potential energy (CAPE), effective cloud droplet size (CER), total precipitable water (TPW), cloud fraction (CF), cloud top temperature (CTT), Richardson number (RN), cloud ice water content (CIWC), and cloud liquid water content (CLWC). This study examines two regions with distinct climates: Sri Lanka (R1) and Indonesia (R2). Results show lower lightning activity in R1 (15.5 flashes/km²/year) than in R2 (21.8 flashes/km²/year), with both peaking in April. Furthermore, the study evaluates the effectiveness of different regression techniques in modeling lightning activity. The Support Vector (SV) regression model performs best for Sri Lanka, while the Random Forest (RF) regression model emerges as the most suitable approach for Indonesia.

International Journal of Engineering Science Technologies

LOW-COST MONITORING OF AIR QUALITY IN HIGH-TRAFFIC URBAN AREAS OF PANAMA: A PRELIMINARY ASSESSMENT

LIGHTNING–METEOROLOGY RELATIONSHIPS OVER SRI LANKA AND INDONESIA: A MACHINE LEARNING APPROACH