• 한국환경과학회지
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• 제12권9호
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• pp.987-996
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• 2003

In this study, we analyzed the relationship between the time-variation trend of air pollution concentration index and the meteorological conditions with CO(carbon monoxide) concentration and meteorological observation data in high-CO episode days. CO is a representative automobile air pollutant. The results are as follows; 1. Most of the high-CO episode days within 30 classes appeared in winter season. 2. Most of them appeared under the surface weather conditions with east-west high-pressure system. The surface winds in this high-pressure area were very light. 3. The high-CO episode days were due to unusual accumulation within urban atmosphere in the morning. 4. The Atmospheric stabilities were more stable, and then the wind-ventilation conditions were worse than yearly mean atmospheric condition in Daegu.

• Asian Journal of Atmospheric Environment
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• 제9권1호
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• pp.12-21
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• 2015

Air pollution is a challenging issue in some of the large cities in developing countries. In this regard, data interpretation is one of the most important parts of air quality management. Several methods exist to analyze air quality; among these, we applied the Multilayer Perceptron (MLP) and Radial Basis Function (RBF) methods to predict the hourly air concentration of benzene in 14 districts in the municipality of Tehran. Input data were hourly temperature, wind speed and relative humidity. Both methods determined reliable results. However, the RBF neural network performance was much closer to observed benzene data than the MLP neural network. The correlation determination resulted in 0.868 for MLP and 0.907 for RBF, while the Index of Agreement (IA) was 0.889 for MLP and 0.937 for RBF. The sensitivity analysis related to the MLP neural network indicated that the temperature had the greatest effect on prediction of benzene in comparison with the wind speed and humidity in the study area. The temperature was the most significant factor in benzene production because benzene is a volatile liquid.

• Asian Journal of Atmospheric Environment
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• 제10권2호
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• pp.67-79
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• 2016

The forecasting of air pollution is an important and popular topic in environmental engineering. Due to health impacts caused by unacceptable particulate matter (PM) levels, it has become one of the greatest concerns in metropolitan cities like Karaj City in Iran. In this study, the concentration of $PM_{2.5}$ was predicted by applying a multilayer percepteron (MLP) neural network, a radial basis function (RBF) neural network and a Markov chain model. Two months of hourly data including temperature, NO, $NO_2$, $NO_x$, CO, $SO_2$ and $PM_{10}$ were used as inputs to the artificial neural networks. From 1,488 data, 1,300 of data was used to train the models and the rest of the data were applied to test the models. The results of using artificial neural networks indicated that the models performed well in predicting $PM_{2.5}$ concentrations. The application of a Markov chain described the probable occurrences of unhealthy hours. The MLP neural network with two hidden layers including 19 neurons in the first layer and 16 neurons in the second layer provided the best results. The coefficient of determination ($R^2$), Index of Agreement (IA) and Efficiency (E) between the observed and the predicted data using an MLP neural network were 0.92, 0.93 and 0.981, respectively. In the MLP neural network, the MBE was 0.0546 which indicates the adequacy of the model. In the RBF neural network, increasing the number of neurons to 1,488 caused the RMSE to decline from 7.88 to 0.00 and caused $R^2$ to reach 0.93. In the Markov chain model the absolute error was 0.014 which indicated an acceptable accuracy and precision. We concluded the probability of occurrence state duration and transition of $PM_{2.5}$ pollution is predictable using a Markov chain method.

• Advances in environmental research
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• 제4권4호
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• pp.219-231
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• 2015

In recent years, raising air pollutants has become as a big concern, especially in metropolitan cities such as Tehran. Therefore, forecasting the level of pollutants plays a significant role in air quality management. One of the forecasting tools that can be used is an artificial neural network which is able to model the complicated process of air pollution. In this study, we applied two different methods of artificial neural networks, the Multilayer Perceptron (MLP) and Radial Basis Function (RBF), to predict the hourly air concentrations of toluene in Tehran. Hourly temperature, wind speed, humidity and $NO_x$ were selected as inputs. Both methods had acceptable results; however, the RBF neural network produced better results. The coefficient of determination ($R^2$) between the observed and predicted data was 0.9642 and 0.99 for MLP and RBF neural networks, respectively. The results of the mean bias errors (MBE) were 0.00 and -0.014 for RBF and MLP, respectively which indicate the adequacy of the models. The index of agreement (IA) between the observed and predicted data was 0.999 and 0.994 in the RBF and the MLP, respectively which indicates the efficiency of the models. Finally, sensitivity analysis related to the MLP neural network determined that temperature was the most significant factor in air concentration of toluene in Tehran which may be due to the volatile nature of toluene.

• 대기
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• 제30권4호
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• pp.439-454
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• 2020

This study investigates the change in the fine particulate matter (PM2.5) concentration and World Health Organization (WHO) air quality index (AQI) in East Asia (EA) under Shared Socioeconomic Pathways (SSPs). AQI is an indicator of increasing levels about health concern, divided into six categories based on PM2.5 annual concentrations. Here, we utilized the ensemble results of UKESM1, the climate model operated in Met Office, UK, for the analysis of long-term variation during the historical (1950~2014) and future (2015~2100) period. The results show that the spatial distributions of simulated PM2.5 concentrations in present-day (1995~2014) are comparable to observations. It is found that most regions in EA exceeded the WHO air quality guideline except for Japan, Mongolia regions, and the far seas during the historical period. In future scenarios containing strong air quality (SSP1-2.6, SSP5-8.5) and medium air quality (SSP2-4.5) controls, PM2.5 concentrations are substantially reduced, resulting in significant improvement in AQI until the mid-21st century. On the other hand, the mild air pollution controls in SSP3-7.0 tend to lead poor AQI in China and Korea. This study also examines impact of increased in PM2.5 concentrations on downward shortwave energy at the surface. As a result, strong air pollution controls can improve air quality through reduced PM2.5 concentrations, but lead to an additional warming in both the near and mid-term future climate over EA.

• Advances in environmental research
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• 제3권3호
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• pp.207-216
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• 2014

A study was conducted to determine the phytotoxic effect of mercury on seed germination and seedling growth of an important arid legume tree Albizia lebbeck. The seeds germination and seedling growth performance of A. lebbeck responded differently to mercuric chloride treatment (1 mM, 3 mM, 5 mM and 7 mM) as compared to control. Seed germination of A. lebbeck was significantly (p < 0.05) affected by mercury treatment at 1 mM. Root growth of A. lebbeck was not significantly affected by mercury treatment at 1 mM, and 3 mM. Shoot and root length of A. lebbeck were significantly (p < 0.05) affected by 5 mM concentration of mercury treatment. Increase in concentration of mercury treatment at 5 mM and 7 mM significantly (p < 0.05) reduced seedling dry weight of A. lebbeck. The treatment of mercury at 1 mM decreased high percentage of seed germination (22%), seedling length (10%), root length (21.85%) and seedling dry weight (9%). Highest decrease in seed germination (51%), seedling (34%), root length (48%) and seedling dry weight (41%) of A. lebbeck occurred at 7 mM mercury treatment. A. lebbeck showed high percentage of tolerance (78.14%) to mercury at 1 mM. However, 7 mM concentration of mercury produced lowest percentage of tolerance (51.65%) in A. lebbeck. The seed germination potential and seedling vigor index (SVI) clearly decreased with the higher level of mercury. Plantation of A. lebbeck in mercury-polluted area will help in reducing the burden of mercury pollution. A. lebbeck can serve better in coordinating in land management programs in metal contaminated areas. The identification of the toxic concentration of metals and tolerance indices of A. lebbeck would also be helpful for the establishment of air quality standard.

• 한국조경학회지
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• 제49권5호
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• pp.1-11
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• 2021

본 연구는 도시의 표면을 구성하는 물리적 공간요소 가운데 대기질에 영향을 미치는 주요 요인을 찾아 환경개선을 위한 단서를 제공하는 것이 목적이다. 중국의 산업도시인 창춘의 9개 측정소에서 2018년 1월 1일부터 2019년 12월 31일까지의 AQI 농도 자료를 수집하였다. 측정소를 중심으로 반경 300m 내의 지역을 구성하는 도시의 물리적 시설에 대한 유형과 분포 특징을 분석하였다. 측정소를 3개 그룹으로 나눠 계절별로 미세먼지 농도 차이를 분석한 결과, 봄과 겨울에 AQI 농도가 가장 높고, 다음으로 여름, 가장 낮은 계절은 가을이었다. 봄의 AQI 농도가 가장 높은 곳은 F(93.00)·D(91.10)·I(89.20), 여름 농도가 가장 높은 곳은 D(69.05)·A(67.89)·B(84.44), 가을 농도가 가장 높은 곳은 I(62.80)·G(60.84)·D(53.27), 겨울은 I(95.82)·H(95.60)·F(94.04)이었다. SPSS를 이용한 계열분석을 통해 직경 600m인 공간내의 대기지수는 임야, 초지, 나지, 수공간, 수고, 건축면적(평균치), 건물 체적(평균치)과 상관성이 있는 것으로 나타났다. 오염이 심한 봄과 겨울의 수치자료를 통계분석한 결과, 임야면적(43,637m², 15.44%)과 수면적(18,736m², 6.63%)이 큰 비율을 차지하고, 건축평균면적(448m², 0.17%)과 건축평균부피(10,201m³)가 가장 적은 그룹 1(A, B, C)구역의 오염 농도가 가장 낮았다. 반대로 그룹 2(D, E, F)구역은 AQI 농도가 가장 높은 구역으로 임야(1,917m², 0.68%)와 수면적(0m², 0%)이 적거나 없고 건축평균면적(1,056m², 0.37%)과 건축평균부피(17,470m³)가 가장 높았다. AQI 농도가 가장 높은 지역의 특징은 가로수의 수고가 12m 이상인 경우가 다수 확인되었고, 나지면적의 비율이 적을수록 오염도가 낮은 것으로 나타났다. 동일한 방법으로 창춘의 9개 공간의 특징을 분석한 결과, 도시 공간의 물리적 특성에 따른 대기질은 위의 요인들과 밀접한 관련이 있음을 알 수 있었다.

• Journal of Advanced Marine Engineering and Technology
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• 제23권4호
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• pp.543-551
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• 1999

Diesel engine is a major source of the air pollution. In general the concentrations of these pollu-tants in diesel engine exhaust differ from values calculated assuming chemical equibrium. Thus the detailed chemical mechanisms by which these pollutions form and the kinetic of these process-es are important in determining emission levels. In this study the computer program has been developed to calculate the required thermodynam-ic properties of combustion products(10 spacies) for both equilibrium and non-equilibrium in cylin-der for diesel engines. Nitric oxide emissions are calculated by using the extended Zeldovich Kinet-ic mechanism with a steady state assumption for the N concentration and equilibrium values used for H, O, $O_2$ and OH concentrations. By the results it is confirmed that developed simulations program with the NO prediction model is validated against residual mass fraction combustion index of Wiebe's functions pre-mixed com-bustion ration fuel injection timing.

• 한국대기환경학회지
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• 제21권5호
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• pp.495-505
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• 2005

This study is to estimate source contribution by air pollutantion types (point, area, line) over Seoul metropolitan area. The Air Pollution Model (TAPM) and the highly resolved anthropogenic and biogenic gridded emissions ($1km{\times}1km$) were applied to simulate $SO_2,\;NO_2,\;O_3\;and\;PM_{10}$ concentrations by seasons and contribution was estimated by their source types (point, area, line). The results showed that the simulated concentrations of secondary pollutant agreed well with observed values with an index of agreement (IOA) over 0.4, whereas IOAs over 0.3 were observed for most primary pollutants. The contributions of each source types by seasons were similar. The point source contribution was the highest for $SO_2$ at medium level ranged from $55.1\%\;to\;61.5\%$. But the contribution from area source during for the spring and summer increased as the concentration level increased. The line source contribution was the highest for $NO_2$ at all levels ranged from $68.3\%\;to\;93.1\%$. The results indicate that $SO_2$ emissions should be mainly controlled from point source, as well as area source at higher level concentration. Also, $NO_2\;and\;PM_{10}$ to from line source should be controlled.

• 한국산림과학회지
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• 제87권3호
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• pp.404-414
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• 1998

대기오염이 심한 것으로 판단되는 울산지역의 석유화학공단과 온산공단을 중심으로 수목착생지의류를 이용한 대기환경의 오염정도를 평가하기 위하여 공단 주변의 산림에서 지의류의 출현종수와 피도, 생육한계분포농도에 따른 분포특성과 대기청정도지수(IAP)를 조사한 결과, 조사지점에서 출현한 지의류는 총 16종류였으며, 그중 Lepraria sp.(30.85%)과 Lecanora strobilina(26.18%), Parmelia austrosinensis(13.42%) 등이 우점하고 있었다. 석유화학공단과 온산공단 주변 조사지점에서는 지의사막대(地衣砂漠帶)의 형성과 더불어 공단으로부터 멀어질수록 출현종수가 증가했다. 조사지점별 평균피도는 I-V계급으로 오염물질이 공단이 위치하는 해안가로부터 내륙으로 유입됨을 추측할 수 있으며, 공단으로부터 멀어질수록 평균피도계급도 증가하였다. $SO_2$ 농도에 대한 지의류의 종별 생육한계분포농도에 따른 분포특성을 Cladonia sp.과 Dirinaria applanata, Parmelia austrosinensis, Lepraia sp., Lecanora strobilina를 대상으로 살펴 본 결과, 오염에 대한 민감정도에 따라 분포형태가 다르게 나타났다. 특히, 대기오염에 내성 종인 Lepraria sp.과 Lecanora strobilina는 I부터 V의 피도계급으로 가장 폭넓게 분포하였으며, 분포형태가 비슷한 Lecanora strobilina도 대기오염에 강한 종임을 추측할 수 있었다. 대기청정도지수(IAP)는 0-64.3으로 6계급으로 구분하여 조사한 결과, 조사지점별 IAP 등치선도는 피도 등치선도와 비슷한 형태로 공단으로부터 멀어질수록 IAP가 높아졌다. IAP와 지의류 출현종의 분포는 IAP가 5-10으로 낮은 부분에서는 대기에 저항성 종으로 알려진 Lepraria sp.과 Lecanora strobilina가 출현하고 있었으며, IAP 5-10 사이부터는 Parmelia austrosinensis와 Dirinaria applanata가 IAP 10이상부터 오염에 비교적 약한 종으로 말려진 Cladonia sp.를 비롯하여 Candelaria concolar와 Parmelia borreri 등이 출현하였고, 조사지점의 IAP와 지의류의 출현종수는 정의 상관관계 (r=0.9308)를 나타내었다.