• Title/Summary/Keyword: air monitoring

Search Result 1,512, Processing Time 0.034 seconds

DENTAL TREATMENT OF A PATIENT WITH SWYER JAMES UNDER GENERAL ANESTHESIA: A CASE REPORT (Swyer James syndrome환아의 전신마취 하 치아우식 치료: 증례보고)

  • Sung, Young Jae;Song, Ji Soo;Hyun, Hong-Keun;Kim, Young-Jae;Kim, Jung-Wook;Jang, Ki-Taeg;Lee, Sang-Hoon;Shin, Teo Jeon
    • The Journal of Korea Assosiation for Disability and Oral Health
    • /
    • v.15 no.1
    • /
    • pp.60-64
    • /
    • 2019
  • Swyer-James syndrome (SJS), also known as Swyer-James-MacLeod syndrome and unilateral hyperlucent lung syndrome, is rare acquired pulmonary disorder develops secondary to infectious etiologies in early childhood. Viral respiratory infection such as adenoviruses or Mycoplasma pneumoniae in infancy or early childhood rarely cause Swyer-James syndrome. It is generally characterized on radiographs by a unilateral small lung with hyperlucency and air trapping on expiration. In many cases unaffected lung tissue functions normally, compensating for affected lung portion. Preoperative assessment is needed to determinate individual's pulmonary function. A 4-year-old boy with Swyer-James syndrome visited Seoul National University Dental Hospital Department of pediatric dentistry for caries treatment. Clinical and radiographic examinations revealed multiple carious lesions on deciduous teeth. Considering patient's underling disease, age, and level of cooperation, dental treatment under general anesthesia was scheduled. Dental treatment was done with composite resin and stainless-steel crown. Since ventilation of Swyer-James syndrome patients was diminished because of airway obstruction, close monitoring of ventilation is necessary during dental treatment. Considering pulmonary pathology, general anesthesia rather than sedation is recommended when special behavior management is required for dental treatment. Swyer-James syndrome patients can tolerate general anesthesia and surgery well, according to several reports.

Exposure to Particles and Nitrogen Dioxide Among Workers in the Stockholm Underground Train System

  • Plato, N.;Bigert, C.;Larsson, B.M.;Alderling, M.;Svartengren, M.;Gustavsson, P.
    • Safety and Health at Work
    • /
    • v.10 no.3
    • /
    • pp.377-383
    • /
    • 2019
  • Objectives: Exposure to fine particles in urban air has been associated with a number of negative health effects. High levels of fine particles have been detected at underground stations in big cities. We investigated the exposure conditions in four occupational groups in the Stockholm underground train system to identify high-exposed groups and study variations in exposure. Methods: $PM_1$ and $PM_{2.5}$ were measured during three full work shifts on 44 underground workers. Fluctuations in exposure were monitored by a real-time particle monitoring instrument, pDR, DataRAM. Qualitative analysis of particle content was performed using inductively coupled plasma mass spectrometry. Nitrogen dioxide was measured using passive monitors. Results: For all underground workers, the geometric mean (GM) of $PM_1$ was $18{\mu}g/m^3$ and of $PM_{2.5}$ was $37{\mu}g/m^3$. The particle exposure was highest for cleaners/platform workers, and the GM of $PM_1$ was $31.6{\mu}g/m^3$ [geometric standard deviation (GSD), 1.6] and of $PM_{2.5}$ was $76.5{\mu}g/m^3$ (GSD, 1.3); the particle exposure was lowest for ticket sellers, and the GM of $PM_1$ was $4.9{\mu}g/m^3$ (GSD, 2.1) and of $PM_{2.5}$ was $9.3{\mu}g/m^3$ (GSD, 1.5). The $PM_1$ and $PM_{2.5}$ levels were five times higher in the underground system than at the street level, and the particles in the underground had high iron content. The train driver's nitrogen dioxide exposure level was $64.1{\mu}g/m^3$ (GSD, 1.5). Conclusions: Cleaners and other platform workers were statistically significantly more exposed to particles than train drivers or ticket sellers. Particle concentrations ($PM_{2.5}$) in the Stockholm underground system were within the same range as in the New York underground system but were much lower than in several older underground systems around the world.

Contamination Characteristics of Hazardous Air Pollutants in Particulate Matter in the Atmosphere of Ulsan, Korea (울산시 미세먼지의 유해대기오염물질 오염 특성)

  • Lee, Sang-Jin;Kim, Seong-Joon;Park, Min-Kyu;Cho, In-Gyu;Lee, Ho-Young;Choi, Sung-Deuk
    • Journal of Environmental Analysis, Health and Toxicology
    • /
    • v.21 no.4
    • /
    • pp.281-291
    • /
    • 2018
  • Recently, long-range atmospheric transport (LRAT) from China is regarded as a major reason for elevated levels of particulate matter (PM) in Korea. However, local emissions also play an important role in PM pollution, especially in large-scale industrial cities. In this study, PM samples were collected at suburban, residential, and industrial sites in Ulsan, Korea. Polycyclic aromatic hydrocarbons (PAHs) and heavy metals were analyzed, and a potential human health risk assessment was conducted. The concentrations of PAHs and heavy metals in total suspended particles (TSP) increased during high $PM_{10}$ episodes, and backward trajectory analysis verified the influence of LRAT from China during the high episodes. Furthermore, the concentrations of PAHs and heavy metals in $PM_{2.5}$ and $PM_{10}$ at the industrial site were higher than those at the residential site. The risk assessment of PAHs and heavy metals in $PM_{2.5}$ suggested no significant health effects. The highest levels of PAHs were measured in the particle size of $0.32{\sim}0.56{\mu}m$ at the residential site, and those of heavy metals were detected in the particle size of 1.8~5.6 and $>18{\mu}m$, reflecting different major emissions sources for both groups. On the basis of this preliminary study, we are planning long-term monitoring and modeling studies to quantitatively evaluate the influence of industrial activities on the PM pollution in Ulsan.

Fault Classification Model Based on Time Domain Feature Extraction of Vibration Data (진동 데이터의 시간영역 특징 추출에 기반한 고장 분류 모델)

  • Kim, Seung-il;Noh, Yoojeong;Kang, Young-jin;Park, Sunhwa;Ahn, Byungha
    • Journal of the Computational Structural Engineering Institute of Korea
    • /
    • v.34 no.1
    • /
    • pp.25-33
    • /
    • 2021
  • With the development of machine learning techniques, various types of data such as vibration, temperature, and flow rate can be used to detect and diagnose abnormalities in machine conditions. In particular, in the field of the state monitoring of rotating machines, the fault diagnosis of machines using vibration data has long been carried out, and the methods are also very diverse. In this study, an experiment was conducted to collect vibration data from normal and abnormal compressors by installing accelerometers directly on rotary compressors used in household air conditioners. Data segmentation was performed to solve the data shortage problem, and the main features for the fault classification model were extracted through the chi-square test after statistical and physical features were extracted from the vibration data in the time domain. The support vector machine (SVM) model was developed to classify the normal or abnormal conditions of compressors and improve the classification accuracy through the hyperparameter optimization of the SVM.

An Experimental Study on the Applicability of UAV for the Analysis of Factors Influencing Rural Environment - Focusing on Photovoltaic Facilities and Vacant House in Galsan-Myeon, Hongseong-gun - (농촌 공간 환경영향요인 분석을 위한 무인항공기 적용 가능성에 관한 실험적 연구 - 홍성군 갈산면의 태양광 발전시설과 빈집을 중심으로 -)

  • An, Phil-Gyun;Eom, Seong-Jun;Kim, Su-Yeon;Kim, Young-Gyun
    • Journal of the Korean Institute of Rural Architecture
    • /
    • v.24 no.1
    • /
    • pp.9-17
    • /
    • 2022
  • Rural spaces are increasingly valuable as areas for introducing renewable energy infrastructure to achieve carbon neutrality. Rural areas are the living grounds of rural residents, and the balance of conservation and development for rural areas is important for the introduction of reasonable facilities. In order to maintain a balance between development and preservation and to introduce reasonable renewable energy facilities, it is necessary to develop a current status survey and an effective survey method to utilize a space capable of introducing renewable energy facilities such as idle land and vacant houses. Therefore, this study was conducted to verify the readability using an unmanned aerial vehicle, and the main results are as follows. The detection of photovoltaic power generation facilities using unmanned aerial vehicles was effective in analyzing the location and area of photovoltaic panels located on the roofs of buildings, and it was possible to calculate the expected power generation by region through the area calculation of photovoltaic panels. The vacant house detection can be used to select an investigation target for an vacant house condition survey as it can identify damage to buildings that are expected to be empty houses, management status, and electricity supply facilities through aerial photos. It is judged that the unmanned aerial vehicle detection capability can be utilized as a method to improve the efficiency of investigation and supplement the data related to solar power generation facilities and vacant houses provided by public institutions. Although this study detected the status of solar power generation facilities and vacant houses through high-resolution aerial image analysis, as a follow-up study, automatic measurement methods using the temperature difference of solar power generation facilities and general characteristics of vacant houses that can be read from the air were investigated. If the deriving research is carried out, it is judged that it will be possible to contribute to the improvement of the accuracy of the detection result using the unmanned aerial vehicle and the expansion of the application range.

Prediction and Analysis of PM2.5 Concentration in Seoul Using Ensemble-based Model (앙상블 기반 모델을 이용한 서울시 PM2.5 농도 예측 및 분석)

  • Ryu, Minji;Son, Sanghun;Kim, Jinsoo
    • Korean Journal of Remote Sensing
    • /
    • v.38 no.6_1
    • /
    • pp.1191-1205
    • /
    • 2022
  • Particulate matter(PM) among air pollutants with complex and widespread causes is classified according to particle size. Among them, PM2.5 is very small in size and can cause diseases in the human respiratory tract or cardiovascular system if inhaled by humans. In order to prepare for these risks, state-centered management and preventable monitoring and forecasting are important. This study tried to predict PM2.5 in Seoul, where high concentrations of fine dust occur frequently, using two ensemble models, random forest (RF) and extreme gradient boosting (XGB) using 15 local data assimilation and prediction system (LDAPS) weather-related factors, aerosol optical depth (AOD) and 4 chemical factors as independent variables. Performance evaluation and factor importance evaluation of the two models used for prediction were performed, and seasonal model analysis was also performed. As a result of prediction accuracy, RF showed high prediction accuracy of R2 = 0.85 and XGB R2 = 0.91, and it was confirmed that XGB was a more suitable model for PM2.5 prediction than RF. As a result of the seasonal model analysis, it can be said that the prediction performance was good compared to the observed values with high concentrations in spring. In this study, PM2.5 of Seoul was predicted using various factors, and an ensemble-based PM2.5 prediction model showing good performance was constructed.

Challenges of Medical Waste Treatment in Fiji (피지국에서의 의료폐기물 처리현황과 문제점)

  • Kim, Daeseon;Bolaqace, Josefa;Rafai, Eric;Lee, Chulwoo
    • Journal of Appropriate Technology
    • /
    • v.6 no.1
    • /
    • pp.37-44
    • /
    • 2020
  • Medical waste is any kind of waste that contains infectious material and recommended not to be transferred for infection control. As a means of disposal, incineration has better points than dumping or landfill in the quantity reduction, odorless and nonhazardous. However, open burning and incineration of health care wastes under bad circumstances, can result in the emission of environmental pollutants to air. A burial of biological waste brings pollution of soil and water. Most of sub divisional hospitals in Fiji transfer their medical wastes to divisional hospitals for incineration. In 2011, 62,518 kg of medical waste was incinerated in the three divisional hospitals. However, some medical wastes are considered as general waste and burnt or sent to landfill site, some are buried on site in some sub-divisional hospitals. In this regards, urgent education is necessary for awareness promotion to relevant personnel in medical waste treatment. On site incineration using small scale incinerator is more recommended than transportation of medical wastes treatment in Fiji. Moreover, remotely controllable and fixable small scale of incinerator is more desirable in sub-divisional hospitals. It is recommended that Fiji government to set up a legal framework for medical waste management (MWM), to develop specific guidelines for MWM, to set up a training system for MWM to ensure that all relevant personnel are trained, to develop a monitoring and supervision system for MWM, to clarify the future financing of MWM activities, and to improve the MWM infrastructure.

Comparison of Detection Rate of Salmonella spp. in Environment Sampling of Conventional and Welfare Chicken Farms (양계 일반농장과 동물복지농장에서의 환경 샘플링을 통한 살모넬라 검출율 비교)

  • Deok-Hwan, Kim;Kyu-Jik, Kim;Yun-Jeong, Choi;Heesu, Lee;Ji-Yeon, Hyeon;Chang-Seon, Song
    • Korean Journal of Poultry Science
    • /
    • v.49 no.4
    • /
    • pp.281-286
    • /
    • 2022
  • This study was conducted to investigate the detection rate and serotypes of Salmonella spp. in conventional and welfare poultry farms. Ten welfare (five layer and five broiler) and 15 conventional farms (five layer and ten broiler farms) were visited to collect environmental samples for identification and serotyping of Salmonella spp. The detection rate of Salmonella spp. was higher in the welfare farms than in conventional farms in both layer and broiler farms. In layer farms, Salmonella spp. was detected in 0.76% (1 out of 130) of samples from one of five welfare layer farms, but was not detected in the five in conventional layer farms. No significan ifference (P>0.05) was observed between the welfare and conventional layer farms. In broiler farms, Salmonella spp. was detected in 10.5% (21 out of 200) of samples from four of five welfare broiler farms and 3.5% (7 out of 200) of samples from five of ten conventional broiler farms, and a significant difference (p <0.05) was observed between the welfare and conventional broiler farms. Among 29 Salmonella spp. isolates, five isolates were serotyped to Salmonella enterica subsp. Enteritidis (n=2), Salmonella enterica subsp. Grampian (n=1), Salmonella enterica subsp. Virchow (n=1), and Salmonella enterica subsp. Senftenberg (n=1). These results suggest that microbial risks could be higher in welfare farms than in conventional farms due to easy access to open-air areas, environmental enrichment, and reduced use of antibiotics. Therefore, continuous monitoring and surveillance for Salmonella spp. is necessary to improve the microbiological safety of poultry meat.

Health Risk Assessment by Exposure to Heavy Metals in PM2.5 in Ulsan Industrial Complex Area (울산 산단지역 PM2.5 중 중금속 노출에 의한 건강위해성평가)

  • Ji-Yun Jung;Hye-Won Lee;Si-Hyun Park;Jeong-Il Lee;Dan-Ki Yoon;Cheol-Min Lee
    • Journal of Environmental Health Sciences
    • /
    • v.49 no.2
    • /
    • pp.108-117
    • /
    • 2023
  • Background: When particles are absorbed into the human body, they penetrate deep into the lungs and interact with the tissues of the body. Heavy metals in PM2.5 can cause various diseases. The main source of PM2.5 emissions in South Korea's atmosphere has been surveyed to be places of business. Objectives: The concentration of heavy metals in PM2.5 near the Ulsan Industrial Complex was measured and a health risk assessment was performed for residents near the industrial complex for exposure to heavy metals in PM2.5. Methods: Concentrations of heavy metals in PM2.5 were measured at four measurement sites (Ulsan, Mipo, Onsan, Maegok) near the industrial complexes. Heavy metals were analyzed according to the Air Pollution Monitoring Network Installation and Operation Guidelines presented by the National Institute of Environmental Research. Among them, only five substances (Mn, Ni, As, Cd, Cr6+) were targeted. The risk assessment was conducted on inhalation exposure for five age groups, and the excess cancer risk and hazard quotient were calculated. Results: In the risk assessment of exposure to heavy metals in PM2.5, As, Cd, and Cr6+ exceeded the risk tolerance standard of 10-6 for carcinogenic hazards. The highest hazard levels were observed in Onsan and Mipo industrial complexes. In the case of non-carcinogenic hazards, Mn was identified as exceeding the hazard tolerance of 1, and it showed the highest hazard in the Ulsan Industrial Complex. Conclusions: This study presented a detailed health risk from exposure to heavy metals in PM2.5 by industrial complexes located in Ulsan among five age groups. It is expected to be utilized as the basis for preparing damage control and industrial emission reduction measures against PM2.5 exposure at the Ulsan Industrial Complex.

Prioritizing for Selection of New High-heat Risk Industries and Thermal Risk Assessment (신규 고열 위험 업종 선정을 위한 우선순위 및 온열 위험 평가)

  • Saemi Shin;Hea Min Lee;Nosung Ki;Jeongmin Park;Sang-Hoon Byeon;Sungho Kim
    • Journal of Korean Society of Occupational and Environmental Hygiene
    • /
    • v.33 no.2
    • /
    • pp.230-246
    • /
    • 2023
  • Objectives: The climate crisis has arrived and heat-related illnesses are increasing. It is necessary to discover new high-heat risk industries and understand the environment . It is also necessary to prioritize risks of industries that have not been included in the management target to date. The study was intended to monitor and evaluate the thermal risk of high-priority workplaces. Methods: A prioritization method was developed based on five factors: occurrence of and death due to heat-related illnesses, work environment monitoring, indoor work rate, small heat source, and limited heat dissipation. it, was applied to industrial accidents caused by heat-related illnesses. Wet bulb temperature index and apparent temperature were measured in July and August at 24 workplaces in seven industries and assessed for thermal risk. Results: The wet bulb temperature index was in the range of 23.8~31.9℃, and exposure limits were exceeded in the growing of crops, food services activities and accommodation, and building construction. The apparent temperature was in the range of 26.8~36.7℃, and exceeded the temperature standard for issuing heatwave warnings in growing of crops, food services activities and accommodation, warehousing, welding, and building construction. Both temperature index in growing of crops and building construction were higher than the outside air temperature. Conclusions: In the workplace, risks in industries that have not be controlled and recognized through existing systems was identified. it is necessary to provide break times according to the work-rest time ratio required during dangerous time period.