• 제목/요약/키워드: PM(particulate matter)

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제철제강시설의 대기오염물질 배출특성 및 배출계수 산정 (Emission Characteristics and Coefficients of Air Pollutants in Iron and Steel Manufacturing Facilities)

  • 김병욱;홍영균;이영섭;양승표;현근우;이건호
    • 한국환경보건학회지
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    • 제47권3호
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    • pp.259-266
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    • 2021
  • Objectives: This study was conducted to identify the emissions characteristics of total particulate matter (TPM), fine dust (PM10, PM2.5), and gaseous pollutants (SOx, NOx) in iron and steel manufacturing facilities in order to investigate emissions factors suitable for domestic conditions. Methods: Total particulate matter (TPM), fine dust (PM10, PM2.5), and gas phase materials were investigated at the outlet of electric arc furnace facilities using a cyclone sampling machine and a gas analyzer. Results: The concentrations of TPM ranged from 1.64 to 3.14 mg/Sm3 and the average was 2.47 mg/Sm3. Particulate matter 10 (PM10) averaged 1.49 mg/Sm3 with a range of 0.92 to 1.99 mg/Sm3, and the resulting ratio of PM10 to TPM was around 60 percent. PM2.5/PM10 ranged from 33.7 to 47.9% and averaged 41.6%. Sulfur oxides (SOx) were not detected, and nitrogen oxides (NOx) averaged 6.8 ppm in the range of 5.50 to 8.67 ppm. TPM emission coefficients per product output were in the range of 0.60 to 1.26 g/kg, 0.13 to 0.79 g/kg for PM10 and 0.12 to 0.36 g/kg for PM2.5, and showed many differences from the emissions coefficients previously announced. An emissions coefficient for NOx is not currently included in the domestic notices, but the results were calculated to be 0.42 g/kg per product output. Conclusions: Investigation and research on emissions coefficients that can reflect the characteristics of various facilities in Korea should be conducted continuously, and the determination and application of unique emissions coefficients that are more suitable for domestic conditions are needed.

Increase of Cardiometabolic Biomarkers Among Vehicle Inspectors Exposed to PM0.25 and Compositions

  • Ramdhan, Doni Hikmat;Kurniasari, Fitri;Tejamaya, Mila;Fitri, Aidila;Indriani, Aisyah;Kusumawardhani, Adinda;Santoso, Muhayatun
    • Safety and Health at Work
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    • 제12권1호
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    • pp.114-118
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    • 2021
  • Background: Exposure to particulate matter (PM) emitted from vehicle exhaust might disrupt systemic function and elevate the risk of cardiovascular disease. In this study, we examined the changes of cardiometabolic biomarkers among vehicle inspectors exposed daily to PM0.25 and components. Methods: This cross-sectional study was conducted at two vehicle inspection centers, Pulogadung and Ujung Menteng, located in East Jakarta, Indonesia. The exposed respondents were 43 workers from vehicle inspection centers, and the unexposed group consisted of 22 staff officers working in the same locations. Vehicle exhaust particulate matter was measured for eight hours using a Leland Legacy personal pump attached to a Sioutas Cascade Impactor. The used filters were 25 and 37-mm quartz filters. The particulate matter concentration was analyzed using a gravimetric method, whereas trace elements were analyzed using energy dispersive X-ray fluorescence. An EEL Smoke Stain Reflectometer analyzed black carbon. Results: The personal exposure concentrations of PM0.25 were 10.4-fold higher than those in unexposed groups. Calcium and sulfur were the major components in the obtained dust, and their levels were 3.3- and 7.2-fold higher, respectively, in the exposed group. Based on an independent-samples t-test, high-density lipoprotein, triglyceride, HbA1c, total immunoglobulin E, high-sensitivity C-reactive protein, tumor necrosis factor-alpha, and nitric oxide levels were significantly different between the groups. Conclusions: In summary, it was suggested that PM0.25 exposure from vehicle exhaust might affect cardiometabolic biomarkers change.

Ceramic Diesel Particulate Filter Structure with Inclined Gas Paths

  • Hwang, Yeon;Kang, Dae-Sik;Choi, Hyoung-Gwon;Lee, Choong-Hoon
    • 한국세라믹학회지
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    • 제49권3호
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    • pp.226-230
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    • 2012
  • This paper presents a novel structure for a diesel particulate filter (DPF) with inclined gas paths, which was designed so that the gas paths offered a fluent flow of exhaust gases, and particulate matter (PM) was collected at pores formed in the body. The alumina porous filter was prepared by a conventional sintering process at $1200^{\circ}C$ for 2 h. Straight gas paths with $30^{\circ}$ of inclination from the gas flow direction were formed in the filter body. It is shown that this filter structure worked as a PM filter, in which 90.2% of soot filtration efficiency and 59.6 mbar of pressure drop were achieved.

미세먼지 저감을 위한 정책 선정 연구 (Making Primary Policies for Reducing Particulate Matter)

  • 김봉균;이원상;조혜인;이봉규
    • 한국전자거래학회지
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    • 제25권1호
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    • pp.109-121
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    • 2020
  • 본 연구의 목적은 미세먼지를 줄이고 국민 삶의 질을 개선하기 위해 정부와 지방자치단체간의 역할분담과 협업을 하는 정책수립과정에서 도입하려는 정책의 우선순위를 도출하는 것이다. 심각한 미세먼지 문제는 건강뿐만 아니라 경제 특히 상거래에도 많은 영향을 미치고 있으나, 아직 미세먼지 저감 정책 선정에 관한 연구는 많지 않은 실정이다. 본 연구에서는 환경부와 지자체의 환경정책전문가, 학계 및 환경업계 전문가 25명을 대상으로 AHP 방법론을 사용하여 조사 및 분석하였다. 상위계층은 교통, 생산시설, 생활환경 및 도시계획 관리 분야의 4개로 나누고 각 분야는 다시 3개씩 세분화하여 12개의 정책을 선별하였고, 생산업의 대기오염 감축 의무화 및 공장가동 중단이 가장 우선시되는 정책으로 분석되었다. 본 연구결과는 향후 미세먼지와 관련된 정책 수립 시 가이드라인으로 활용할 수 있다.

다중 선형 회귀에 의한 광산란 초미세먼지 측정기의 황사 보정 기법 (An Asian Dust Compensation Scheme of Light-Scattering Fine Particulate Matter Monitors by Multiple Linear Regression)

  • 백승훈
    • 융합정보논문지
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    • 제11권8호
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    • pp.92-99
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    • 2021
  • 광산란법을 이용한 초미세먼지 측정기는 초 단위의 측정이 가능하고 휴대할 수 있는 크기로 설계될 수 있다. 또한 하나의 센서로 여러 크기별 (PM1.0, PM2.5, PM4.0, 및 PM10) 농도를 측정할 수 있다. 이 방식은 입자의 개수와 크기를 측정하고 이를 단위 부피당 무게인 농도로 변환하는 과정 때문에 큰 밀도를 가지는 황사에 대해서는 큰 오차를 나타낸다. 본 논문은 광산란 초미세먼지 측정기가 여러 크기별 PM 농도를 이용하여 황사 발생 시 초미세먼지(PM2.5)의 농도의 오차를 정확히 보정할 수 있고, 황사가 발생하지 않을 때도 영향을 받지 않는, 다중 선형외기 기법의 기계학습에 의한 보정 기법을 제시한다. 두 가지 또는 세 가지의 PM 크기 입력만으로도 광산란 미세먼지 측정 장치의 황사 오류를 크게 보정할 수 있음을 보인다. 한 달 동안 중부권대기환경연구소의 베타레이 측정기와 광산란 측정기의 측정값을 비교·분석하였다. 황사가 없는 구간에서 이 두 장비의 상관계수(R2)는 0.927이었고, 황사를 포함한 전 구간에서 상관계수는 0.763이었지만, 기계학습을 통하여 상관계수가 0.944로 향상되었다.

소형 직화식 커피 로스터 이용 시 발생하는 미세먼지 특성 연구 (Characteristics of Particulate Matter Generated during the Operation of a Small Directly Fired Coffee Roaster)

  • 유다은;김승원
    • 한국산업보건학회지
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    • 제30권2호
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    • pp.236-248
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    • 2020
  • Objectives: The purpose of this study was to evaluate the concentrations of particulate matter generated during coffee roasting and to study various factors affecting the concentrations. Methods: Differences in concentration levels were investigated based on various factors to understand the emission rates of particulate matter over time and to compare the mass and number concentrations according to their size. Sampling was performed in closed laboratories without the operation of air conditioning or ventilation. Optical Particle Sizer(OPS) was used as a measuring device. An OPS measures using a light-scattering method. Sampling was performed for sixty minutes at one-minute intervals. The background concentration was measured for about 30 minutes before starting of coffee roasting. The concentrations of particulate matter generated during coffee roasting were monitored until roasted coffee beans were removed from the roaster and cooled down. Several factors affecting the concentrations of particulate matter were investigated, which includes the origins of green beans, the roasting level, and the input amount of green beans. Results: The results of this study may be summarized as follows: 1) There was no difference in particulate matter concentration levels by the origin of the green beans, but a statistically significant difference in concentration levels by roasting level and the input amount of green beans; The higher the roasting level, the higher was the particulate matter concentration. The more green beans we put in the roaster, the higher were the concentrations; 2) The PM10 mass concentrations increased over time. The average concentration after roasting was higher than the average concentration during roasting; 3) In the distribution of mass and number concentration by particle diameter, the majority of particles was below 2.5 ㎛. Conclusions: Persons who work in roastery cafes can be exposed to high concentrations of particulate matter. Therefore, personal exposure and risk assessment should be conducted for roastery cafe workers.

Overview of the Effect of Catalyst Formulation and Exhaust Gas Compositions on Soot Oxidation In DPF

  • Choi Byung Chul;FOSTER D.E.
    • Journal of Mechanical Science and Technology
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    • 제20권1호
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    • pp.1-12
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    • 2006
  • This work reviews the effects of catalyst formulation and exhaust gas composition on soot oxidation in CDPF (Catalytic Diesel Particulate Filter). DOC's (Diesel Oxidation Catalysts) have been loaded with Pt catalyst (Pt/$Al_{2}O_3$) for reduction of HC and CO. Recent CDPF's are coated with the Pt catalyst as well as additives like Mo, V, Ce, Co, Fe, La, Au, or Zr for the promotion of soot oxidation. Alkali (K, Na, Cs, Li) doping of metal catalyst tends to increase the activity of the catalysts in soot combustion. Effects of coexistence components are very important in the catalytic reaction of the soot. The soot oxidation rate of a few catalysts are improved by water vapor and NOx in the ambient. There are only a few reports available on the mechanism of the PM (particulate matter) oxidation on the catalysts. The mechanism of PM oxidation in the catalytic systems that meet new emission regulations of diesel engines has yet to be investigated. Future research will focus on catalysts that can not only oxidize PM at low temperature, but also reduce NOx, continuously self-cleaning diesel particulate filters, and selective catalysts for NOx reduction.

Comparative Analysis of PM10 Prediction Performance between Neural Network Models

  • Jung, Yong-Jin;Oh, Chang-Heon
    • Journal of information and communication convergence engineering
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    • 제19권4호
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    • pp.241-247
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    • 2021
  • Particulate matter has emerged as a serious global problem, necessitating highly reliable information on the matter. Therefore, various algorithms have been used in studies to predict particulate matter. In this study, we compared the prediction performance of neural network models that have been actively studied for particulate matter prediction. Among the neural network algorithms, a deep neural network (DNN), a recurrent neural network, and long short-term memory were used to design the optimal prediction model using a hyper-parameter search. In the comparative analysis of the prediction performance of each model, the DNN model showed a lower root mean square error (RMSE) than the other algorithms in the performance comparison using the RMSE and the level of accuracy as metrics for evaluation. The stability of the recurrent neural network was slightly lower than that of the other algorithms, although the accuracy was higher.

Seasonal impact to air qualities in industrial areas of the Arabian Gulf region

  • Al-Taani, Ahmed A.;Howari, Fares M.;Nazzal, Yousef;Yousef, Ahmad
    • Environmental Engineering Research
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    • 제23권2호
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    • pp.143-149
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    • 2018
  • Air quality conditions and pollution status have been evaluated in the industrial area between Sharjah and Ajman border in UAE. Daily concentrations of $O_3$, CO, $NO_2$, $SO_2$, $PM_{2.5}$, $PM_{10}$, Total Volatile Organic Compounds (TVOC) and Total Suspended Particulate (TSP) have been monitored from Sept. 2015 to April 2016. The monthly average concentrations of $O_3$, CO, $NO_2$, $SO_2$, TVOC were within the UAE ambient air quality standards during the survey period. However, $PM_{10}$ and TSP levels exceeded the recommended limits in Sept. 2015, Oct. 2015 and March 2016. Temporal variations in air quality parameters showed highest levels in March 2016 for $PM_{2.5}$, $PM_{10}$, $NO_2$, TVOC and TSP, whereas $O_3$, $SO_2$ and CO showed relatively low values in this month. $PM_{2.5}$ levels in ambient air were above the EPA guideline of $35{\mu}g/m^3$ in all months. $PM_{2.5}$ was the critical ambient air pollutant with Index for Pollutant ($I_p$) values varying from 103-209, indicating Air Quality Index categories of unhealthy for sensitive groups (62.5%) to unhealthy (25%) to very unhealthy (12.5%). The $I_p$ average values of $PM_{2.5}$ decreased from Sept. 2015 to reach lowest value in Dec. 2015 before increasing gradually, peaking in March 2016. These results suggest the potential health risks associated with $PM_{2.5}$ is low in winter, where the prevailing meteorological conditions of lower temperatures, higher humidity, higher wind speed reduced particulate matter. The results revealed the industrial area is impacted by anthropogenic and natural sources of particulate matter.

Influence of Blending Method on the Generation of Wear Particulate Matters and Physical Properties in TBR Tire Tread Compounds

  • Sanghoon Song;Junhwan Jeong;Jin Uk Ha;Daedong Park;Gyeongchan Ryu;Donghyuk Kim;Kiwon Hwang;Sungwook Chung;Wonho Kim
    • Elastomers and Composites
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    • 제58권4호
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    • pp.161-172
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    • 2023
  • Because particulate matter has emerged as a major contributor to air pollution, the tire industry has conducted studies to reduce particulate matters from tires by improving tire performance. In this study, we compared the conventional blending method, in which rubber, filler, and additives are mixed simultaneously, to the Y-blending method, in which masterbatches are blended. We manufactured carbon black (CB)-filled natural rubber (NR)/butadiene rubber (BR) blend and silica-filled epoxidized NR/BR blend compounds to compare the effects of the two blending methods on the physical properties of the compounds and the amount of particulate matter generated. The Y-blending method provided uniform filler distribution in the heterogeneous rubber matrix, improved processability, and exhibited low rolling resistance. This method also improved physical properties owing to the excellent filler-rubber interaction. The results obtained from measuring the generation of particulate matter indicated that, the Y-blending method reduced PM2.5 particulate matter generation from the CB-filled and silica-filled compounds by 38% and 60%, and that of PM10 by 29% and 67%, respectively. This confirmed the excellence of the Y-blending method regarding the physical properties of truck bus radial tire tread compounds and reduced particulate matter generated.