• Title, Summary, Keyword: Particulate matter

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Analysis of 119 dispatch for patients with cardio-cerebrovascular and respiratory diseases according to particulate matter (미세먼지 농도에 따른 심·뇌혈관계 및 호흡기계 환자의 119 구급 출동 분석)

  • Koo, Ji-Yeon;Cho, Keun-Ja
    • The Korean Journal of Emergency Medical Services
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    • v.24 no.1
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    • pp.37-55
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    • 2020
  • Purpose: The purpose of this study was to provide basic data for improving the response capacity of 119 EMS systems by analyzing the effects of particulate matter on cardio-cerebrovascular and respiratory symptoms in the pre-hospital stage. Methods: We examined 46,389 patients who transferred to the hospital with complaints of cardiopulmonary arrest and cardio-cerebrovascular and respiratory symptoms by 119 ambulances in Incheon from 2016 to 2018. Results: The probability of 119 emergency dispatch for patients with cardiopulmonary arrest increased 2.8-4.0% from the day of symptom onset until two days before hospital presentation as particulate matter 10㎛ or less in diameter(PM10) increased by 10㎍/㎥ (OR=1.028; 95% CI=1.014-1.041, p=0.000, lag 0), (OR=1.040; 95% CI=1.024-1.056, p=0.000, lag 1), (OR=1.032; 95% CI=1.016-1.049, p=0.000, lag 2). Meanwhile, emergency dispatch increased 3.6-6.1% for PM2.5 in creased by 10㎍/㎥ (OR=1.046; 95% CI=1.024-1.068, p=0.000, lag 0), (OR=1.061; 95% CI=1.035-1.088, p=.000, lag 1), and (OR=1.036; 95% CI=1.010-1.063, p=0.006, lag 2). Conclusion: Emergency medical technicians (EMTs) who respond to 119 calls should rapidly and accurately evaluate patients and provide professional emergency care by identifying the characteristics of the vulnerable groups relative to particulate matter size. To prevent the occurrence and exacerbation of symptoms caused by particulate matter, EMTs should be prepared and equipped with a response system for high particulate matter in the EMS system.

The Relationship between Particular Matter Reduction and Space Shielding Rate in Urban Neighborhood Park (도시근린공원 미세먼지(PM)저감과 공간차폐율과의 관계 - 대구광역시 수성구 근린공원을 중심으로 -)

  • Koo, Min-Ah
    • Journal of the Korean Institute of Landscape Architecture
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    • v.47 no.6
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    • pp.67-77
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    • 2019
  • The purpose of this study is to analyze how much particulate matter at the center of the urban park is reduced compared to the entrance of the park, where the particulate matter problem is serious. It also endeavored to analyze the relationship between the space closure rate and particulate matter reduction rate in the center of the park through the collection and analysis of experimental data. Seven flat land type urban neighborhood parks in Suseong-gu, Daegu were measured at the same place for three days. The research results are as follows. First, the center of the urban neighborhood park had an average temperature 1.05℃ lower than at the entrance and an average humidity of 2.57% higher. Second, the rate of fine dust reduction was PM1- 17.09%, PM2.5- 17.65%, PM10- 14.99%. As for the reduction rate of particulate matter, the smaller the size of the park, the greater the reduction rate. In addition, the reduction rate at the center of the park was lower on days when particulate matter concentration based on the weather reports was low. The higher the concentration at the park entrance, the higher the reduction rate was. Third, a higher the rate of space closures at the center of the park resulted in a higher effect of particulate matter reduction. Noting this, the relationship between particulate matter reduction and the space closure rate in urban neighborhood parks was clearly shown. We hope to be the basis for more extensive experimental data collection.

Suspended Particulate Matter of the Surface Water in Relation to the Hydrography in the South Sea of Korea in Early Winter (한국 남해의 초겨울 해황과 관련한 표층 부유물질의 분포)

  • Choi Yong-Kyu
    • Journal of Environmental Science International
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    • v.14 no.11
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    • pp.1063-1069
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    • 2005
  • In order to investigate the distribution of suspended particulate matter of the surface water in the South Sea of Korea in early winter, the cruise results during 2 to 8 December 2004 were analyzed in relation to the hydrography. The front was formed along the line connecting between Tsushima and Cheju Islands, which divided the water into two water masses; the coastal water with for temperature and for salinity, and the Tsushima Warm Current Water with high temperature and high salinity. In the coastal water the suspended particulte matter was 5.0-6.5 mg/l, while in the oceanic water suspended particulate matter was 4.5-5.0 mg/l. The coastal water showed higher mixing effects, compared to the oceanic area where vertical stratification was clearly formed. These indicate that the distribution of suspended particulate matter was affected by the stratification or mixing of the water column. Also it is suggested that the mixing effects of sea surface cooling and rind play an important role on the distribution of suspended particulate matter in the South Sea of Korea in winter time.

Prediction of Particulate Matter AQI using Recurrent Neural Networks (순환 신경망을 이용한 미세먼지 AQI 지수 예측)

  • Jung, Yong-jin;Lee, Jong-sung;Oh, Chang-heon
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • pp.543-545
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    • 2019
  • The AQI index has been developed and used to guide the action of particulate matter. Information on the AQI index can be easily provided to the general public, and various services are provided based on the AQI index. As services are provided, accurate AQI index prediction is needed. In this paper, we design the classification model using the circular neural network to predict the AQI index of particulate matter. For the evaluation of the designed model, compare the AQI index of the actual particulate matter with the predicted value.

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Machine Learning-based Estimation of the Concentration of Fine Particulate Matter Using Domain Adaptation Method (Domain Adaptation 방법을 이용한 기계학습 기반의 미세먼지 농도 예측)

  • Kang, Tae-Cheon;Kang, Hang-Bong
    • Journal of Korea Multimedia Society
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    • v.20 no.8
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    • pp.1208-1215
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    • 2017
  • Recently, people's attention and worries about fine particulate matter have been increasing. Due to the construction and maintenance costs, there are insufficient air quality monitoring stations. As a result, people have limited information about the concentration of fine particulate matter, depending on the location. Studies have been undertaken to estimate the fine particle concentrations in areas without a measurement station. Yet there are limitations in that the estimate cannot take account of other factors that affect the concentration of fine particle. In order to solve these problems, we propose a framework for estimating the concentration of fine particulate matter of a specific area using meteorological data and traffic data. Since there are more grids without a monitor station than grids with a monitor station, we used a domain adversarial neural network based on the domain adaptation method. The features extracted from meteorological data and traffic data are learned in the network, and the air quality index of the corresponding area is then predicted by the generated model. Experimental results demonstrate that the proposed method performs better as the number of source data increases than the method using conditional random fields.

A Novel Approach for the Particulate Matter(PM) Reduction in the Industrial Complex using Integrated Data Platform (통합데이터 플랫폼을 활용한 산업단지 미세먼지 저감 방안)

  • Chung, Seokjin;Jung, Seok
    • Journal of the Korean Institute of Resources Recycling
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    • v.29 no.1
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    • pp.62-69
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    • 2020
  • Manufacturing processes in industrial complexes produce NOx, SOx, VOCs, which cause particulate matter (PM). Therefore, this study analyzed the characteristics of each industrial complex by using scattered public data, matched the existing particulate matter(PM) reduction technology, and proposed an optimized reduction plan. The application of matching technologies and facilities by industrial complexes based on data is able to mitigate NOx, SOx, and VOCs which cause particulate matter in the process in advance. This way can be an effective alternative in order to reduce PM in the manufacturing processes as well as industrial complexes.

Characteristics of Nano-Particles Exhausted from Diesel Passenger Vehicle with DPF

  • Park, Yong-Hee;Shin, Dae-Yewn
    • Journal of Environmental Health Sciences
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    • v.32 no.6
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    • pp.533-538
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    • 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.

Evaluation of genotoxic potentials in diesel exhaust particulate matter with the Ames test, the comet assay and the micronucleus assay

  • Kim, Soung-Ho;Lee, Do-Han;Han, Kyu-Tae;Oh, Seung-Min;Chung, Kyu-Hyuck
    • Proceedings of the PSK Conference
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    • pp.165.1-165
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    • 2003
  • This research was designed to examine the presence of mutagenic/carcinogenic compounds in airborne pollutants in diesel particulate matter using an integrated biological approach. Respirable air borne particulate matter (PM2.5: <2.5mm) was collected from diesel engine exhaust using a high-volume sampler equipped with a cascade impactor. (omitted)

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Estrouenic/antiestrogenic potencies in crude and fractionated extracts of diesel exhaust particulate matter(PM) on human breast cancer cell

  • Ryu, Byung-Taek;Kim, Yun-Hee;Han, Kyu-Tae;Oh, Seung-Min;Chung, Kyu-Hyuck
    • Proceedings of the PSK Conference
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    • pp.165.2-166
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    • 2003
  • Diesel exhaust is suspected to cause acute and chronic adverse effects on health. In recent. the effect of estrogenic endocrine disruptor in diesel particulate matter was little studied. Therefore, we examined the estrogenic activity of respirable diesel exhaust particulate matter derived from diesel engine motor. PM2.5 diesel exhaust of vehicle was collected using a high volume samples equipped with a cascade impactor. (omitted)

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Investigating the underlying structure of particulate matter concentrations: a functional exploratory data analysis study using California monitoring data

  • Montoya, Eduardo L.
    • Communications for Statistical Applications and Methods
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    • v.25 no.6
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    • pp.619-631
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    • 2018
  • Functional data analysis continues to attract interest because advances in technology across many fields have increasingly permitted measurements to be made from continuous processes on a discretized scale. Particulate matter is among the most harmful air pollutants affecting public health and the environment, and levels of PM10 (particles less than 10 micrometers in diameter) for regions of California remain among the highest in the United States. The relatively high frequency of particulate matter sampling enables us to regard the data as functional data. In this work, we investigate the dominant modes of variation of PM10 using functional data analysis methodologies. Our analysis provides insight into the underlying data structure of PM10, and it captures the size and temporal variation of this underlying data structure. In addition, our study shows that certain aspects of size and temporal variation of the underlying PM10 structure are associated with changes in large-scale climate indices that quantify variations of sea surface temperature and atmospheric circulation patterns.