This study aims to measures and develops emission factors of CO, HC, NOx, and soot from HDV trucks and buses using remote sensing technology. The device applies absorption spectroscopy to directly measure vehicle exhaust emissions from the roadside, allowing traffic to continue without interruption. It records emission data for each vehicle in less than one second. Testing was conducted at 19 highway and toll road locations in Jakarta over 58 days, using a 2020 M752 version 3.1 remote sensing device. From a valid sample of 4,774 HDV trucks and 2,029 buses, the median emission factors for CO, HC, NOx, and soot for diesel HDV trucks are 3.65, 0.24, 3.51 and 0.117 g/km, respectively; for diesel buses, 3.70, 0.23, 5.53 and 0.122 g/km; and for CNG buses, 5.90, 0.91, 1.10 and 0.005 g/km. Across all three vehicle types, median emission factors decreased with newer production years. Median soot emissions are zero for diesel buses produced after 2015 and CNG buses manufactured between 2007 and 2015 and after 2015. Diesel and CNG buses emit less CO than diesel HDVs, with Isuzu diesel buses recording the lowest at 0.8 g/km. Diesel buses also record the lowest HC emissions, with Isuzu and Mercedes-Benz buses at 0.06 g/km. The lowest NOx and soot emissions are also observed in Scania and Zhongtong CNG buses, with NOx around 0.3 g/km and soot at 0 g/km. The findings of this study can inform air quality regulations, support urban transportation planning, and raise awareness of the health impacts of pollution, particularly from the transport sector in Jakarta, Indonesia.
The rapid spread of highly contagious respiratory diseases overwhelmed healthcare systems worldwide, making home isolation a critical strategy for managing infected individuals. However, inadequate ventilation in home isolation settings may increase the risk of transmission within households. This study aims to evaluate aerosol dispersion under various ventilation strategies using computational fluid dynamics (CFD) simulations. An Eulerian–Langrangian approach was applied to predict airflow and aerosol transport. The simulation results were validated with optical particle counter (OPC) measurements and RT-PCR analysis of surface samples for SARS-CoV-2 detection. Good agreement was obtained between the simulations and experimental data, with a relative error of less than 5
Winter air pollution in Warsaw, Poland, was analyzed from 2016 to 2025 using hourly data from nine CIEP monitoring stations, meteorological observations from Okecie IMGW station, boundary layer heights from ERA5, and HYSPLIT backward trajectories. The study focused on PM10, PM2.5, NO2, and O3, with emphasis on black smog episodes. Air quality improved substantially over the decade: the frequency of good or very good (according to Polish air quality index thresholds) PM2.5 conditions increased from 10 to 12
AERONET Version 3 inversion products were used to classify optically defined aerosol regimes and examine their temporal distribution over Singapore during 2007–2023 using particle linear depolarization ratio (PLDR), dust ratio (Rd), fine-mode fraction (FMF), and single scattering albedo (SSA). Lower PLDR values were associated with fine-mode, relatively spherical particles characteristic of pollution-related aerosols, whereas higher PLDR values indicated non-spherical coarse particles associated with dust. The joint FMF-Rd distribution showed a predominance of fine-mode, low-dust aerosol conditions. Among the quality-assured AERONET inversion retrievals, dust-free pollution regimes, comprising strongly absorbing (SA), moderately absorbing (MA), weakly absorbing (WA), and non-absorbing (NA) regimes, accounted for 74
