• Advances in Energy Research
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• v.8 no.2
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• pp.111-123
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• 2022

Solar Energy is the energy of solar radiation carried by them in the form of heat and light. It can be converted into electricity. Solar potential depends on the site's atmosphere; the solar energy distribution depends on many factors, e.g., turbidity, cloud types, pollution levels, solar altitude, etc. We estimated solar radiation with the help of the Ashrae clear-sky model for three locations in Pakistan, namely Pasni, Gwadar, and Jiwani. As these locations are close to each other as compared to the distance between the sun and earth, therefore a slight change of latitude and longitude does not make any difference in the calculation of direct beam solar radiation (BSR), diffuse solar radiation (DSR), and global solar radiation (GSR). A modified formula for declination angle is also developed and presented. We also created two different models for Ashrae constants. The values of these constants are compared with the standard Ashrae Model. A good agreement is observed when we used these constants to calculate BSR, DSR, GSR, the Root mean square error (RMSE), Mean Absolute error (MABE), Mean Absolute percent error (MAPE), and chisquare (χ²) values are in acceptance range, indicating the validity of the models.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.47-53
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• 2021

The article deals with the problems of application of microwave methods in systems of geoecological monitoring of natural environments and resources of the agro-industrial complex. It is noted that the methods of microwave radiometry make it possible, by the power of the measured intrinsic radio-thermal radiation of the atmosphere, when solving inverse problems using empirical and semi-empirical models, to determine such parameters of the atmosphere as thermodynamic temperature, humidity, water content, moisture content, precipitation intensity, and the presence of different fractions of clouds.In addition to assessing the meteorological parameters of the atmosphere and the geophysical parameters of the underlying surface based on the data of microwave radiometric measurements, it is possible to promptly detect and study pollution of both the atmosphere and the earth's surface. A technique has been developed for the analysis of sources of measurement error and their numerical evaluation, because they have a significant effect on the accuracy of solving inverse problems of reconstructing the values of the physical parameters of the probed media.To analyze the degree of influence of the limited spatial selectivity of the antenna of the microwave radiometric system on the measurement error, we calculated the relative measurement error of the ratio of radio brightness contrasts in two angular directions. It has been determined that in the system of geoecological monitoring of natural environments, the effect of background noise is maximal with small changes in the radiobrightness temperature during angular scanning and high sensitivity of the receiving equipment.

• Journal of Environmental Health Sciences
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• v.32 no.4 s.91
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• pp.304-315
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• 2006

This study is performed to reexamine the association between ambient air pollution and daily mortality in seven major cities of Korea using a method of meta-analysis with the data filed for the period 1998-2001. These cities account for half of the Korean population (about 23 million). The observed concentrations of carbon monoxide (CO, mean=1.08 ppm), ozone ($O_3$, mean=33.97 ppb), particulate matter less than 10 ${\mu}m$ ($PM_{10},\;mean=57.11\;{\mu}g/m^3$), nitrogen dioxide ($NO_2$, mean=25.09 ppb), and sulfur dioxide ($SO_2$, mean=9.14 ppb) during the study period were at levels below Korea's current ambient air quality standards. Generalized additive models were applied to allow for the highly flexible fitting of seasonal and long-term time trends in air pollution as well as nonlinear associations with weather variables, such as air temperature and relative humidity. Also, we calculated a weighted mean as a meta-analysis summary of the estimates and its standard error. In city-specific analyses, an increase of $41.17{\mu}g/m^3(IQR)\;of\;PM_{10}$ corresponded to $1{\sim}12%$ more deaths, given constant weather conditions. Like most of air pollution epidemiologic studies, this meta-analysis cannot avoid fleeing from measurement misclassification since no personal measurement was taken. However, we can expect that a measurement bias be reduced in district-specific estimate since a monitoring station is better representative of air quality of the matched district. Significant heterogeneity was found for the effect of all pollutants. The estimated relative risks from meta-like analysis increased compared to those relative risks from pooled analysis. The similar results to those from the previous studies indicated existence of health effect of air pollution at current levels in many industrialized countries, including Korea.

• Journal of Environmental Health Sciences
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• v.28 no.1
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• pp.31-39
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• 2002

Generally, inaccurate reports on environmental issues occur due to various factors. The purpose of this study was to find out a way to enhance accuracy of environmental reporting. So the reporters' career and college major had been compared to the accuracy of their articles. The by-lined environmental articles in nine dailies published in 1991 were checked. Results of this study were as follows. (I) Inaccuracy rate in environmental articles was 54.2%. Inaccuracies appeared 1.7 times per an article, while the average frequency of inaccuracies in overall articles was 0.9 time. (2) Errors in the articles consist of 65.8% of subjective inaccuracies and 34.2% of subjective inaccuracies. They derive from the false usage of terminology(15.8% ),misquotation(14.5%), incorrect statistics(13%), exaggeration(13%), inaccurate title(7.9%), and false comparison(5%). (3) Inaccuracy rate by the type of articles was 66.7% in columns, 60% in feature stories, 54.5% in-depth stories, 40.9% in straight news, respectively. (4) Inaccuracy rate by the specific field was shown 71.4% in environmental impacts assessment, 52.5% in water pollution, 37.5% in waste management, and 35.7% in air pollution. (5) According to the result of chi-square test analysis, there were no statistically significant differences of inaccuracy rate and of subjective, and objective inaccuracies relevant to the period of reporters' career covering environmental reporting and the nature of articles, and college major.

• Journal of the Korean Solar Energy Society
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• v.39 no.4
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• pp.55-67
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• 2019

Recently, as the amount of particulate matter blowing from China increases, the domestic air environment is rapidly deteriorating. This pollution of the atmosphere greatly affects the light energy reaching the ground. Particularly, since the light enters the solar cell module in various forms, the amount of input energy of the solar power generation system may be changed depending on the ratio of direct beam irradiation and diffused horizontal irradiation. In this paper, we analyze how the ratio of direct beam component and diffused component on global horizontal irradiation varies with the atmospheric conditions. In addition, the reliability of the regression equation, designed to decompose the global horizontal irradiation into horizontal direct beam irradiation and diffused horizontal irradiation, was verified according to the level of air pollution. So, we derive the most suitable decomposition model for use in domestic climatic conditions in Korea by comparing the ratio of direct and diffuse component on the horizontal which is calculated with Perez model and Watanabe model using the meteorological weather data observed for 14 months. Finally, to reduce the error of the transposition result, we verified the reliability of the decomposition which depends on the atmospheric environment.

• Proceedings of KOSOMES biannual meeting
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• 2007.05a
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• pp.21-26
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• 2007

The Protocol adopted in Sep. 1997 included the new Annex VI of MARPOL 73/78, which entered into force on 19 May 2005. Revision for the accept MARPOL Annex VI with make public on 29 Dec. 2005 and enforce on 29 Jun. 2006. For all that not installation at oil terminal or if installed do not used. The purpose of this study is to research and evaluate the methods of sampling and analysis, and the pollution measure of existed VOCs during the bulk liquid cargo operation at vessels. As the sampling instrument of VOCs, Tedlar bag has the effect of decrease in concentration by the chemical reaction and absorption, and the method using the solvent extraction has error cause because of the extraction, the absorption tube has error by the breakthrough. But canister is the best sampling instrument because of having no sampling mistake. The study on VOCs emission is not sufficient for the research on the pollution cause and the analysis data on the HAP during the bulk liquid cargo operation at vessels. Hence, monitoring on the management hazardous VOCs need to be continued during the cargo operation at vessels and VOCs management field must be study for the make progress at a good pace for reason of crew's health.

• Asian Journal of Atmospheric Environment
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• v.10 no.2
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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.

• Journal of Korean Society for Atmospheric Environment
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• v.19 no.6
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• pp.789-803
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• 2003

The purpose of this study is to compare the usefulness between Gaussian dispersion model and receptor model with the experimental result of the dispersion tracing of the particulate pollutants from Taean coal-fired power plants. For this purpose, the component analysis of the collected PM 10 samples was performed. In order to trace the pollution sources, factor analysis was done with the result of the component analysis. As a result of the correlativity analysis of the fifteen power plants' profiles offered by US EPA, the correlativity of No.11202 source profile showed highest rate up to 84.5%. Thus it was adopted as proper one and the contribution rate by each pollution source was calculated by Chemical Mass Balance (CMB)-8 model. The contribution rate, which was the effect rate of the power plants on each measuring point, were calculated with a range of 24∼52％ and the standard error was below 0.9 $\mu\textrm{g}$/㎥. This indicates the selection of the source profile was appropriate. Also, the concentrations of each point were calculated by the ISCST3 which is suggested by US EPA as one of the regulatory Gaussian dispersion model. The calculation result showed that the predicted concentration was 50∼58 $\mu\textrm{g}$/㎥, comparing with the measured result of 9∼65 $\mu\textrm{g}$/㎥. It was found that the concentration calculated by ISCST3 was underpredicted. It was thought that the receptor model was more favorable than the Gaussian dispersion model in estimating the effect of the particulate matter on a certain receptive point.

• Journal of Environmental Impact Assessment
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• v.10 no.2
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• pp.123-133
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• 2001

Gaussian dispersion model is the most widely used tool for the ground level air pollution simulation. Though in spite of the convenience there are important problems on the Pasquill- Gifford' stability classification scheme which was used to define the turbulent state of the atmosphere or to describe the dispersion capabilities of the atmosphere which was each covers a broad range of stability conditions, and that they were very site specific, and the vertical dispersion calculation formula on the case of the unstable atmospheric condition. This paper was carried out to revise the Gaussian dispension model for the purposed of increase the modeling performance and propose the revised model, which was composed of the turbulent characteristics in the unstable atmospheric conditions. The proposed models in this study were composed of the profile method, Monin-Obukhove length, the probability density function model and the lateral dispersion function which was composed of the turbulent parameters, $u_*$(friction velocity), $w_*$(convective velocity scale), $T_L$(lagrangian time scale) for the model specific. There were very good performance results compare with the tracer experiment result on the case of the short distance (<1415m) from the source, but increase the simulation error(%) to stand off the source in the all models. In conclusion, the revised Gaussian dispersion model using the turbulent characteristics may be a good contribution for the development of the air pollution simulation model.

• Journal of Environmental Science International
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• v.12 no.3
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• pp.265-274
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• 2003

The Pasquill-Gifford stability category is a very important scheme of the Gaussian type dispersion model defined the complex turbulence state of the atmosphere by A grade(very unstable) to F grade(very stable). But there has been made a point out that this stability category might decrease the predictability of the model because it was each covers a broad range of stability conditions, and that they were very site specific. The APSM (Air Pollution Simulation Model) was composed of the turbulent parameters, i.e. friction velocity(${\mu}$$\_$*/), convective velocity scale($\omega$$\_$*/) and Monin-Obukhov length scale(Ｌ) for the purpose of the performance increasing on the case of the unstable atmospheric conditions. And the PDF (Probability Density Function)model was used to express the vertical dispersion characteristics and the profile method was used to calculate the turbulent characteristics. And the performance assessment was validated between APSM and EPA regulatory models(TEM, ISCST), tracer experiment results. There were very good performance results simulated by APSM than that of TEM, ISCST in the short distance (<1415 m) from the source, but increase the simulation error(%) to stand off the source in others. And there were differences in comparison with the lateral dispersion coefficient($\sigma$$\_$y/) which was represent the horizontal dispersion characteristics of a air pollutant in the atmosphere. So the different calculation method of $\sigma$$\_$y/ which was extrapolated from a different tracer experiment data might decrease the simulation performance capability. In conclusion, the air pollution simulation model showed a good capability of predict the air pollution which was composed of the turbulent parameters compared with the results of TEM and ISCST for the unstable atmospheric conditions.