• Journal of The Korean Society of Agricultural Engineers
• /
• v.46 no.1
• /
• pp.107-117
• /
• 2004

Hourly monitoring data from Saemangeum estuary, which is expected to become freshwater, was analyzed to evaluate the water quality characteristics. Higher algal growth at spring season than winter influenced the high ratio of organic nitrogen to total nitrogen and concentration of chemical oxygen demand (COD). About 87.9％ and 59.7％ of organic nitrogen was observed at winter season and spring season, respectively. Daily salinity analysis at the mouth of two main rivers demonstrated that the Dongjin in river was more influenced by tidal effect and showed higher variation than the Mankyung river. The ratio of nitrogen to phosphorus (N/P ratio) was different with site (estuary versus sea area) and season (winter versus spring) remarkably. The N/P ratio was highest (32.74 ∼ 43.93) at estuary in winter and was lowest (1.78 ∼ 3.06) at sea in spring. The high N/P ratio at estuary area implies that phosphorus can be the limiting nutrient factor for algal growth as in general freshwater river, therefore, water quality management practice considering river characteristics rather might be needed in the Saemangeum estuary. The Saemangeum project is nationally recognized for its environmental issues, and especially water quality concern is a critical factor to make policy decision and further assessment with continued monitoring is strongly recommended.

• New & Renewable Energy
• /
• v.20 no.1
• /
• pp.79-87
• /
• 2024

This study introduces a method for estimating Aerosol Optical Depth (AOD) using Broadband Aerosol Optical Depth (BAOD) derived from direct normal irradiance and meteorological factors observed between 2016 and 2017. Through correlation analyses between BAOD and atmospheric components such as Rayleigh scattering, water vapor, and tropospheric nitrogen dioxide, significant relationships were identified, enabling accurate AOD estimation. The methodology demonstrated high correlation coefficients and low Root Mean Square Errors (RMSE) compared to actual AOD₅₀₀ measurements, indicating that the attenuation effects of water vapor and the direct impact of tropospheric nitrogen dioxide concentration are crucial for precise aerosol optical depth estimation. The application of BAOD for estimating AOD₅₀₀ across various time scales-hourly, daily, and monthly-showed the approach's robustness in understanding aerosol distributions and their optical properties, with a high coefficient of determination (0.96) for monthly average AOD₅₀₀ estimates. This study simplifies the aerosol monitoring process and enhances the accuracy and reliability of AOD estimations, offering valuable insights into aerosol research and its implications for climate modeling and air quality assessment. The findings underscore the viability of using BAOD as a surrogate for direct AOD₅₀₀ measurements, presenting a promising avenue for more accessible and accurate aerosol monitoring practices, crucial for improving our understanding of aerosol dynamics and their environmental impacts.

• Asian Journal of Atmospheric Environment
• /
• v.10 no.2
• /
• pp.67-79
• /
• 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.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
• /
• v.4 no.3
• /
• pp.127-137
• /
• 2000

This study presents an analysis of the characteristics of vertical ozone distribution near the surface using ozonesonde data(l995 to 1998), plus surface ozone and meteorological data from the Pohang region. These features were examined in detail using three case studies. The first related to episodes of high surface ozone concentrations during the Spring season when the frontogenesis between the high and low pressure associated with the upper-level jet stream was found to be located near the surface. The second was a 5-day winter period(l3 -17 December, 1997) in the Pohang province when the hourly concentrations exceeded 90 ppb on several occasions owing to low-level jets(LLJs) induced by a nocturnal stable layer. Accordingly, this explains why the high surface ozone concentrations occurred at night as the ozone was transported across the zone by a strong wind speed( over 12.5 ms .1). The third case study was ozone enhancement due to photochemical reactions. In this case, the maximum concentration of ozone exceeded 60 ppb in the summer(23 -28 August, 1997). When an ozone peak appeared within the boundary layer, the occurrence frequency of a low-level jet due to the nocturnal stable layer was about 77%, similarly the occurrence frequency of a near-surface ozone peak relative to the appearance of an LLJ was about 76%. Accordingly, there is clearly a close correlation between the occurrence of LLJs and near-surface ozone peaks.

• Journal of Korean Society for Atmospheric Environment
• /
• v.23 no.5
• /
• pp.612-624
• /
• 2007

The real-time monitoring of radon ($^{222}Rn$) concentrations has been carried out to evaluate its ambient background concentration levels in Gosan site, Jeju Island between January 2001 and December 2004. In addition, the atmospheric TSP aerosols have been sampled, and their ionic and metallic components were analyzed to understand the characteristics of air pollution. The mean concentration of radon was $3,121{\pm}1,627\;mBq/m^3$, and the seasonal mean concentrations for spring, summer, fall and winter seasons were 2,898, 2,398, 3,571 and $3,646\;mBq/m^3$, respectively, The hourly concentrations have shown the highest value at 7 a.m. and the lowest value at 2 p.m. From the backward trajectory analyses, the radon concentrations have increased, when the air parcels were moved from the Chinese continent to Jeju area. On the other hand, they have decreased, when the air parcels from the North Pacific Ocean. In the analytical results of ionic species and metal elements of TSP aerosols, the concentrations of $nss-{SO_4}^{2-}$ and S were higher in June and March. Meanwhile, the concentrations of other anthropogenic species as well as soil components were mostly higher in March and April. On the basis of factor analysis, the TSP aerosols at Gosan area were largely influenced by soil sources, followed by anthropogenic sources and marine sources. From the result of backward trajectory analyses, the concentrations of $nss-{SO_4}^{2-},\;{NO_3}^-$, Al and Ca were mostly higher, when the air parcels moved from Chinese continent to Jeju area. On the other hand, their concentrations were lower, when the air parcels drifted from the North Pacific Ocean.

• Analytical Science and Technology
• /
• v.25 no.1
• /
• pp.7-13
• /
• 2012

The real-time monitoring of radon ($^{222}Rn$) concentrations has been carried out to evaluate the background concentration level of atmospheric radon in Gosan site, Jeju Island. The mean concentration of radon for the recent 10 years was 2831 $mBq/m^3$ (0.077 pCi/L), which was 19.5 time lower than that of indoor radon in Korea. The seasonal concentrations were 2657, 2071, 3249, 3384 $mBq/m^3$ respectively for spring, summer, fall, and winter seasons. In monthly comparison, the radon concentrations were high in October and low in July. The hourly concentrations have increased during the nighttime, showing 3666 $mBq/m^3$ at 7 a.m., and decreased relatively during the daytime, showing 2755 $mBq/m^3$ at 2~3 p.m. From the back trajectory analysis, the radon concentrations showed higher values when the air mass was moved from the Asia continent to Jeju area, on the other hand, it showed low values when it was moved from the North Pacific Ocean.

• Journal of Radiation Protection and Research
• /
• v.25 no.4
• /
• pp.207-216
• /
• 2000

Continuous measurements of radon progeny concentrations in the open atmosphere and measurements of meteorological parameters were performed in Tajeon, using a continuous gross alpha/beta aerosol monitor and a weather measuring equipment between July 1999 and July 2000. These data were analyzed for half-hourly, daily, and seasonal variations. The distribution of daily averaged equilibrium equivalent radon concentration$(EEC_{Rn})$ had an arithmetic mean value of $11.3{\pm}5.86Bqm^{-3}$ with the coefficient of variation of about 50% and the geometric mean was $10.3Bqm^{-3}$. The $EEC_{Rn}$ varies between 0.83 and $43.3Bqm^{-3}$, depending on time of day and weather conditions. Half-hourly averaged data indicated a diurnal pattern with the outdoor $EEC_{Rn}$ reaching a maximum at sunrise and a minimum at sunset. The pattern of the seasonal variation of the $EEC_{Rn}$ in Taejon had a tendency of minimum concentration occurring in the summer(July) and maximum concentration occurring in the late autumn(November). But the seasonal variation of the $EEC_{Rn}$ is expect to vary greatly from place to place. The outdoor $EEC_{Rn}$ was highly dependent on the local climate features. Particularly the $EEC_{Rn}$an rapidly drops less than $5Bqm^{-3}$ in case of blowing heavily higher than wind speed of $6msec^{-1}$, reversely the days with more than $30Bqm^{-3}$ were at a calm weather condition with the wind speed of lower than $1msec^{-1}$.

• Journal of Korean Society for Atmospheric Environment
• /
• v.33 no.1
• /
• pp.31-44
• /
• 2017

The aim of this study is to evaluate the accuracy and variability of the oak pollen concentrations over the Seoul metropolitan region (SMR) simulated by the Community Multiscale Air Quality (CMAQ)-based pollen dispersion model, which is the CMAQ-pollen model integrated with the improved oak pollen emission model(PEM-oak). The PEM-oak model developed is based on hourly emission flux parameterization that includes the effects of plant-specific release, meteorological adjustment, and diurnal variations of oak pollen concentrations. A 33 day-run for oak pollen simulation was conducted by the CMAQ-pollen model with a 3 km spatial resolution for the SMR during the 2014 spring pollen season. Modeled concentrations were evaluated against the hourly measurements at three Burkard sampling sites. Temporal variations of oak concentrations were largely well represented by the model, but the quantitative difference between simulations and measurements was found to be significant in some periods. The model results also showed that large variations in oak pollen concentrations existed in time and space and high concentrations in the SMR were closely associated with the regional transport under strong wind condition. This study showed the effective application of the CMAQ-pollen modeling system to simulate oak pollen concentration in the SMR. Our results could be helpful in providing information on allergenic pollen exposure. Further efforts are needed to further understand the oak pollen release characteristics such as interannual variation of the oak pollen productivity and its spatio-temporal flowering timing.

• Journal of Environmental Health Sciences
• /
• v.47 no.6
• /
• pp.521-529
• /
• 2021

Background: The coronavirus disease (COVID-19) has caused changes in human activity, and these changes may possibly increase or decrease exposure to fine dust (PM_2.5). Therefore, it is necessary to evaluate the exposure to PM_2.5 in relation to the outbreak of COVID-19. Objectives: The purpose of this study was to compare and evaluate the exposure to PM_2.5 concentrations by the variation of dynamic populations before and after the outbreak of COVID-19. Methods: This study evaluated exposure to PM_2.5 concentrations by changes in the dynamic population distribution in Guro-gu, Seoul, before and after the outbreak of COVID-19 between Jan and Feb, 2020. Gurogu was divided into 2,204 scale standard grids of 100 m×100 m. Hourly PM_2.5 concentrations were modeled by the inverse distance weight method using 24 sensor-based air monitoring instruments. Hourly dynamic population distribution was evaluated according to gender and age using mobile phone network data and time-activity patterns. Results: Compared to before, the population exposure to PM_2.5 decreased after the outbreak of COVID-19. The concentration of PM_2.5 after the outbreak of COVID-19 decreased by about 41% on average. The variation of dynamic population before and after the outbreak of COVID-19 decreased by about 18% on average. Conclusions: Comparing before and after the outbreak of COVID-19, the population exposures to PM_2.5 decreased by about 40%. This can be explained to suggest that changes in people's activity patterns due to the outbreak of COVID-19 resulted in a decrease in exposure to PM_2.5.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.25 no.3
• /
• pp.74-99
• /
• 2022

Surface ozone is produced by photochemical reactions of nitrogen oxides(NOx) and volatile organic compounds(VOCs) emitted from vehicles and industrial sites, adversely affecting vegetation and the human body. In South Korea, ozone is monitored in real-time at stations(i.e., point measurements), but it is difficult to monitor and analyze its continuous spatial distribution. In this study, surface ozone concentrations were interpolated to have a spatial resolution of 1.5km every hour using the stacking ensemble technique, followed by a 5-fold cross-validation. Base models for the stacking ensemble were cokriging, multi-linear regression(MLR), random forest(RF), and support vector regression(SVR), while MLR was used as the meta model, having all base model results as additional input variables. The results showed that the stacking ensemble model yielded the better performance than the individual base models, resulting in an averaged R of 0.76 and RMSE of 0.0065ppm during the study period of 2020. The surface ozone concentration distribution generated by the stacking ensemble model had a wider range with a spatial pattern similar with terrain and urbanization variables, compared to those by the base models. Not only should the proposed model be capable of producing the hourly spatial distribution of ozone, but it should also be highly applicable for calculating the daily maximum 8-hour ozone concentrations.