• Food Science and Industry
• /
• v.54 no.1
• /
• pp.29-33
• /
• 2021

Particulate matter (PM) is an air pollutant that causes serious environmental problems in Korea and other countries. The annual average PM10 concentration in Korea is around 40 ㎛/㎥, which is more than twice as high as the WHO recommended standard. When consumed with food, fine PM can pose a risk to humans. However, the risk of fine PM has been focused on the risk of fine PM introduced through the respiratory system. We investigated the quantitative measuring methods of PM10 on food surface to identify possible risk analysis of fine PM. The surfaces of food with artificially contaminated PM10 were observed with a scanning electron microscope(SEM). An automatic object-based image analysis was used to analyze the amount and size distribution of particulate matter contained in SEM micrographs.

• ETRI Journal
• /
• v.43 no.3
• /
• pp.511-523
• /
• 2021

The World Health Organization provides guidelines for managing the particulate matter (PM) level because a higher PM level represents a threat to human health. To manage the PM level, a procedure for measuring the PM value is first needed. We use a PM sensor that collects the PM level by laser-based light scattering (LLS) method because it is more cost effective than a beta attenuation monitor-based sensor or tapered element oscillating microbalance-based sensor. However, an LLS-based sensor has a higher probability of malfunctioning than the higher cost sensors. In this paper, we regard the overall malfunctioning, including strange value collection or missing collection data as anomalies, and we aim to detect anomalies for the maintenance of PM measuring sensors. We propose a novel architecture for solving the above aim that we call the hypothesis pruning generative adversarial network (HP-GAN). Through comparative experiments, we achieve AUROC and AUPRC values of 0.948 and 0.967, respectively, in the detection of anomalies in LLS-based PM measuring sensors. We conclude that our HP-GAN is a cutting-edge model for anomaly detection.

• Economic and Environmental Geology
• /
• v.55 no.6
• /
• pp.701-716
• /
• 2022

This study investigated the distribution behaviors of PM2.5 and PM10 at two air quality monitoring sites, Go-eup (GO) and Backseokeup (BS), located in Yangju City, South Korea. The amounts of emissions sources of pollutants were analyzed based on the Clean Air Policy Support System (CAPSS), and the contribution rates of neighboring cities were enumerated in Yangju. Yangju has a geological basin structure, and it is a city with mixed urban and rural characteristics. The emission concentration of particulate matter was affected by geological and seasonal factors for all sites observed in this study. Therefore, these factors should be considered when establishing policies related to particulate matter. Because the official GO and BS station sites in Yangju are both situated in the southern part of the city, the representativeness of both stations was checked using correlation analysis for the measurement of PM2.5 and PM10 by considering two more sites-those of Bongyang-dong (BY) and the Gumjun (GJ) industrial complex. The data included discharge amounts for business types 4 and 5, which were not sufficiently considered in the CAPSS estimates. Because the 4 and 5 types of businesses represent over 92.6% of businesses in this city, they are workplaces in Yangju that have a significant effect on the total air pollutant emission. These types of businesses should be re-inspected as the main discharge sources in industry, and basic data accumulation should be carried out. Moreover, to manage the emission of particulate matter, attainable countermeasures for the main sources of these emissions should be prepared in a prioritized fashion; such countermeasures include prohibition of backyard burning, supervision of charcoal kilns, and management of livestock excretions and fugitive dust in construction sites and on roads. The contribution rates by neighboring cities was enumerated between 6.3% and 10.9% for PM2.5. Cooperation policies are thought to be required with neighboring cites to reduce particulate matter.

• Journal of odor and indoor environment
• /
• v.17 no.4
• /
• pp.303-314
• /
• 2018

The urban railway system is a convenient public transportation system, as it carries many people without increasing traffic congestion. However, air quality in urban railway environments is worse than ambient air quality due to the internal location of the source of air pollutants and the isolated space. In this paper, characteristics of particulate matter (PM) pollution in urban railway environments are described from the perspective of diurnal variation, chemical composition and source apportionment of PM. PM concentrations in concourse, platform, passenger cabin, and tunnel are summarized through an analysis of 34 journal articles published in Korea and overseas. This information will be helpful in developing effective policies to reduce PM pollution in urban railway environments.

• Journal of Environmental Health Sciences
• /
• v.32 no.6
• /
• pp.533-538
• /
• 2006

The nano-particles are known to influence the environmental protection and human health. The relationships between transient vehicle operation and nano-particle emissions are not well-known, especially for diesel passenger vehicles with DPF(Diesel Particulate Filter). In this study, two diesel passenger vehicles were measured on a chassis dynamometer test bench. The particulate matter (PM) emission of these vehicles was investigated by number and mass measurement. The mass of the total PM was evaluated using the standard gravimetric measurement method, and the total number concentrations were measured on a ECE15+EUDC driving cycle using Condensation Particle Counter (CPC). According to the investigation results, total number concentration was $1.14{\times}10^{11}$M and mass concentration was 0.71mg/km. About 99% of total number concentration was emitted during the $0{\sim}400s$ because of engine cold condition. In high temperature and high speed duration, the particulate matter was increased but particle concentration was emitted not yet except initial engine cold condition According to DPF performance deterioration, the particulate matter was emitted 2 times and particle concentration was emitted 32 times. Thus DPF performance deterioration affects particle concentration more than PM.

• Communications for Statistical Applications and Methods
• /
• v.30 no.3
• /
• pp.259-272
• /
• 2023

In this paper, we suggest a new method for the prediction of sharp changes in particulate matter (PM₁₀) using quantile mapping. To predict the current PM₁₀ density in Seoul, we consider PM₁₀ and precipitation in Baengnyeong and Ganghwa monitoring stations observed a few hours before. For the PM₁₀ distribution estimation, we use the extreme value mixture model, which is a combination of conventional probability distributions and the generalized Pareto distribution. Furthermore, we also consider a quantile generalized additive model (QGAM) for the relationship modeling between precipitation and PM₁₀. To prove the validity of our proposed model, we conducted a simulation study and showed that the proposed method gives lower mean absolute differences. Real data analysis shows that the proposed method could give a more accurate prediction when there are sharp changes in PM₁₀ in Seoul.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2021.11a
• /
• pp.40-41
• /
• 2021

Recently, particulate matter(PM) caused by internal factors such as industrialization and urbanization as well as external factors such as Asian dust is a serious problem in Korea. In particular, while the emission due to construction appears to be very serious among the internal factors, it is necessary to manage PM in consideration of the characteristics of construction sites. Accordingly, in this study, a PM management system suitable for construction sites was developed to reduce civil complaints caused by PM and to minimize damage to field workers and nearby residents by supporting the fine dust management system of the state and local governments. The factors to be considered when measuring PM due to the specificity of construction sites were considered, and the system components were developed based on the considerations. As a result, an IoT based construction site PM monitoring system (CPMS) that integrates each component was established.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.21 no.2
• /
• pp.98-103
• /
• 2013

Conventional method to estimate mass of particulate matter accumulated in diesel particulate filter is to use pressure difference between upstream and downstream of the filter. Then measured pressure difference should be compared that of clean condition which is no particulate matter accumulated in DPF. During regeneration soot oxidation is also estimated by same method. This methodology, however, has demerit on accuracy because of pressure difference deviation of clean DPFs and pressure difference caused by non-carbon based PM which is different from that of caused by carbon based PM. This study suggests new methodology to estimate accumulated soot oxidation rate through exhaust gas characteristics during regeneration. Results, more high accuracy of soot oxidation was obtained by analysis of relationship between fuel mass and concentration of carbon dioxide and oxygen.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.17 no.3
• /
• pp.29-34
• /
• 2009

Diesel particulate filter (DPF) has been developed to optimize engine out emission, especially particulate matter (PM). One of the main important factors for developing the DPF is estimation of soot mass being accumulated inside the DPF. Evaluation of pressure drop over the DPF is a simple way to estimate the accumulated soot mass but its accuracy is known to be limited to certain vehicle operating conditions. The method to compensate drawback is adoption of integrating time history of the engine out PM and burning soot. Present study demonstrates current status of the soot estimation methods including the results from the engine test benches and vehicles.

• Clinical and Experimental Pediatrics
• /
• v.62 no.1
• /
• pp.22-29
• /
• 2019

Particulate matter (PM) is a ubiquitous air pollutant that is a growing public health concern. Previous studies have suggested that PM is associated with asthma development and exacerbation of asthma symptoms. Although several studies have suggested increased risks of atopic dermatitis, allergic rhinitis, and allergic sensitization in relation to PM exposure, the evidence remains inconsistent. The plausible mechanisms underlying these effects are related to oxidative stress, enhancement of sensitization to allergens, inflammatory and immunological responses, and epigenetics. This review discusses the effect of PM on childhood allergic diseases, along with plausible mechanisms. Further studies are required to understand the role of PM exposure on childhood allergic diseases, to reduce these diseases in children.