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. 2024 Dec 7;24(23):7836.
doi: 10.3390/s24237836.

Air Pollution Measurement and Dispersion Simulation Using Remote and In Situ Monitoring Technologies in an Industrial Complex in Busan, South Korea

Naghmeh Dehkhoda  1 , Juhyeon Sim  1 , Juseon Shin  1 , Sohee Joo  1 , Sung Hwan Cho  2 , Jeong Hun Kim  2 , Youngmin Noh  3
Affiliations

Air Pollution Measurement and Dispersion Simulation Using Remote and In Situ Monitoring Technologies in an Industrial Complex in Busan, South Korea

Naghmeh Dehkhoda et al. Sensors (Basel). .

Abstract

Rapid industrialization and the influx of human resources have led to the establishment of industrial complexes near urban areas, exposing residents to various air pollutants. This has led to a decline in air quality, impacting neighboring residential areas adversely, which highlights the urgent need to monitor air pollution in these areas. Recent advancements in technology, such as Solar Occultation Flux (SOF) and Sky Differential Optical Absorption Spectroscopy (SkyDOAS) used as remote sensing techniques and mobile extraction Fourier Transform Infrared Spectrometry (MeFTIR) used as an in situ technique, now offer enhanced precision in estimating the pollutant emission flux and identifying primary sources. In a comprehensive study conducted in 2020 in the Sinpyeong Jangrim Industrial Complex in Busan City, South Korea, a mobile laboratory equipped with SOF, SkyDOAS, and MeFTIR technologies was employed to approximate the emission flux of total alkanes, sulfur dioxide (SO2), nitrogen dioxide (NO2), formaldehyde (HCHO), and methane (CH4). Using the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) diffusion model, pollutant dispersion to residential areas was simulated. The highest average daily emission flux was observed for total alkanes, with values of 69.9 ± 71.6 kg/h and 84.1 ± 85.8 kg/h in zones S1 and S2 of the Sinpyeong Jangrim Industrial Complex, respectively. This is primarily due to the prevalence of metal manufacturing and mechanical equipment industries in the area. The HYSPLIT diffusion model confirmed elevated pollution levels in residential areas located southeast of the industrial complex, underscoring the influence of the dominant northwesterly wind direction and wind speed on pollutant dispersion. This highlights the urgent need for targeted interventions to address and mitigate air pollution in downwind residential areas. The total annual emission fluxes were estimated at 399,984 kg/yr and 398,944 kg/yr for zones S1 and S2, respectively. A comparison with the Pollutant Release and Transfer Registers (PRTRs) survey system revealed that the total annual emission fluxes in this study were approximately 24.3 and 4.9 times higher than those reported by PRTRs. This indicates a significant underestimation of the impact of small businesses on local air quality, which was not accounted for in the PRTR survey system.

Keywords: formaldehyde (HCHO); hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) diffusion model; methane (CH4); mobile extraction Fourier transform infrared spectrometry (MeFTIR); nitrogen dioxide (NO2); sky differential optical absorption spectroscopy (SkyDOAS); solar occultation flux (SOF); sulfur dioxide (SO2); total alkanes.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
The industrial operating divisions located in the Sinpyeong Jangrim Industrial Complex.
Figure 2
Figure 2
Location of Busan City in South Korea and the Sinpyeong Jangrim Industrial Complex (S1 and S2), residential areas (R1–R5), and installed anemometers (W1 and W2). The purple spots indicate other industrial areas near the observation site.
Figure 3
Figure 3
The measurement vehicle diagram.
Figure 4
Figure 4
Comparison of the measured wind speed by the two anemometers (black dots), the reference relationship between the wind speeds measured by the two anemometers (red line), and the confidence intervals (blue dotted line).
Figure 5
Figure 5
The measurement principle and the defined fence line for CH4 measurement in zone S2 (the red circle defines the expected source of CH4 emission).
Figure 6
Figure 6
The main wind direction for zones S1 (on the top) and S2 (on the bottom) (northwesterly for both zones), and the wind speed for zones S1 (~2.1 m/s) and S2 (~3.6 m/s) during the measurement period.
Figure 7
Figure 7
Daily average emission flux of the measured gasses for zones S1 (on the top) and S2 (on the bottom) (unit: kg/h).
Figure 8
Figure 8
The average emission flux during the entire period of measurement in zone S1 (the white arrow indicates the dominant wind direction during the observation).
Figure 9
Figure 9
The results of whole days of measurement based on the substances in zone S2 (the white arrow indicates the dominant wind direction during the observation).
Figure 10
Figure 10
Total alkane dispersion estimation based on the HYSPLIT diffusion model in zone S1 (5 November 2020, at 1:57 p.m., 2:17 p.m., and 2:42 p.m.). (a) Expected emission source according to the observed peak, (b) wind speed and direction data, and (c) the HYSPLIT diffusion model results.
Figure 11
Figure 11
NO2 dispersion estimation based on the HYSPLIT diffusion model in zone S2 (16 November, at 10:41 a.m. and 12:00 p.m.). (a) Expected emission source according to the observed peak, (b) wind speed and direction data, and (c) the HYSPLIT diffusion model results.
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