Bibliographic Details
| Title: |
Spatiotemporal variability of benzene in a petrochemical industrial complex: insights from repeated mobile SIFT-MS monitoring and comparison with Me-DOAS. |
| Authors: |
Jung, Joon-sig1 (AUTHOR) jsjung080@korea.kr, Choi, Su-jin2 (AUTHOR) tnwls0263@korea.kr, Lee, Dong-keun1 (AUTHOR) ldk0225@korea.kr, Kim, Seon-woo2 (AUTHOR) seonu92@korea.kr, Jung, Dae-kwan2 (AUTHOR) hiandgoo@korea.kr, Park, Jung-min1 (AUTHOR) anspark011@korea.kr, Lee, So-young1 (AUTHOR) lsyoung09@korea.kr, Ko, Min-jeong1 (AUTHOR) komj95@korea.kr, Jang, Jong-hee1 (AUTHOR) jhjang1013@korea.kr |
| Source: |
Environmental Monitoring & Assessment. Jun2026, Vol. 198 Issue 6, p1-20. 20p. |
| Subject Terms: |
*Spatiotemporal processes, *Air quality monitoring, *Emissions (Air pollution), *Mass spectrometry, *Seasonal temperature variations, *Petroleum chemicals industry, *Air quality management |
| Abstract: |
This study investigated the spatiotemporal characteristics of benzene concentrations in a petrochemical industrial complex using integrated mobile monitoring techniques. Real-time measurements were conducted using vehicle-mounted Selected Ion Flow Tube–Mass Spectrometry (SIFT-MS), with Mobile-extraction Differential Optical Absorption Spectroscopy (Me-DOAS) applied as a complementary approach to assess spatial consistency and seasonal patterns. Benzene concentrations showed clear seasonal and diurnal variability, with higher levels and more frequent high-concentration events in winter and consistently elevated concentrations during nighttime (22:00–03:00) under stable atmospheric conditions. Spatial analysis revealed that exceedance events were concentrated within specific industrial blocks associated with benzene-handling and emission-intensive processes, indicating persistent localized hotspots. Although absolute concentration levels differed between SIFT-MS and Me-DOAS, both techniques reproduced consistent temporal patterns. Agreement was weak under background conditions but strengthened during high-concentration events, suggesting convergence under source-dominated conditions. Me-DOAS effectively represents spatially averaged concentrations, whereas SIFT-MS captures short-term variability and localized high-concentration events. Overall, the results demonstrate that high-resolution mobile monitoring can resolve short-term benzene peaks and identify spatially persistent hotspots, providing practical information for targeted air quality management. [ABSTRACT FROM AUTHOR] |
| Database: |
Energy & Power Source |