Emission factors of air toxics from semiconductor manufacturing in Korea

The development of local, accurate emission factors is very important for the estimation of reliable national emissions and air quality management. For that, this study is performed for pollutants released to the atmosphere with source-specific emission tests from the semiconductor manufacturing industry. The semiconductor manufacturing industry is one of the major sources of air toxics or hazardous air pollutants (HAPs); thus, understanding the emission characteristics of the emission source is a very important factor in the development of a control strategy. However, in Korea, there is a general lack of information available on air emissions from the semiconductor industry. The major emission sources of air toxics examined from the semiconductor manufacturing industry were wet chemical stations, coating applications, gaseous operations, photolithography, and miscellaneous devices in the wafer fabrication and semiconductor packaging processes. In this study, analyses of emission characteristics, and the estimations of emission data and factors for air toxics, such as acids, bases, heavy metals, and volatile organic compounds from the semiconductor manufacturing process have been performed. The concentration of hydrogen chloride from the packaging process was the highest among all of the processes. In addition, the emission factor of total volatile organic compounds (TVOCs) for the packaging process was higher than that of the wafer fabrication process. Emission factors estimated in this study were compared with those of Taiwan for evaluation, and they were found to be of similar level in the case of TVOCs and fluorine compounds.     

The effect of overtaking behavior on unidirectional pedestrian flow

We present a model of overtaking behavior that can be used to simulate unidirectional pedestrian flow in routine. All pedestrians have the ability to determine whether or not to overtake other pedestrians according to their desired velocity and position. Although existing models such as cellular automata models, lattice gas models, social force models, etc., can be used to predict evacuation performance, most of these models are either computationally inefficient or do not account for some crucial elements of human behavior in a moving crowd. Furthermore, these models use either empirical equations developed from experiments or mechanical system analogies to determine movement decisions. The pedestrian flow patterns simulated by these models may deviate significantly from reality. In reality, pedestrians walk at different velocities and pedestrians with a higher walking velocity are accustomed to overtaking other pedestrians with a lower walking velocity and this paper aims to mimic this behavior as the original social force model developed by Helbing et al. does not reflect this pattern of collective pedestrian behavior. In this paper, we propose modifications of the social force model that reflects how overtaking behavior operates in routine. The comparison of the pedestrian flow pattern between the original social force model and the modified social force models with the real data collected by the camcorder is also performed in order to demonstrate our modified social force model can be used to achieve reasonable simulations of overtaking behavior among pedestrians.     

Potential CO2 intrusion in near-surface environments: a review of current research approaches to geochemical processes

Environmental Geochemistry and Health - Carbon dioxide (CO2) capture and storage (CCS) plays a crucial role in reducing carbon emissions to the atmosphere. However, gas leakage from deep storage...     

Long-run dynamics of renewable energy consumption on carbon emissions and economic growth in the European union

This paper examines long-run and short-run dynamics of renewable energy consumption on carbon dioxide (CO₂) emissions and economic growth in the European Union. This study employs cointegration tests, Granger causality tests and vector error correction estimates to examine the direction of Granger causality, the long-run dynamics of economic growth and energy variables on carbon emissions. This study analyses time series data from the World Development Indicators over the period from1961 to 2012. The results of this study support a link between renewable energy consumption, economic growth, industrialization, exports and CO₂ emissions in the long-run and short-run. The results support that the sign of the long-run dynamics from the endogenous variables to the CO₂ emissions variable is negative and significant, which implies that the energy and environmental policies of the European Union aimed at curbing CO₂ emissions must have been effective in the long-term. Furthermore, renewable energy consumption and exports have significant negative impact on CO₂ emissions in the short-run. However, industrialization and economic growth have positive impact on CO₂ emissions in the short-run. The results suggest that both economic growth and industrialization must have been achieved at the cost of harming the environment. The finding suggests that the increasing consumption of renewable energy tends to play an important role in curbing carbon emissions in the region.     

Compositional data analysis and geochemical modeling of CO2–water–rock interactions in three provinces of Korea

Environmental Geochemistry and Health - The CO2-rich spring water (CSW) occurring naturally in three provinces, Kangwon (KW), Chungbuk (CB), and Gyeongbuk (GB) of South Korea was classified based...     

Reductive dissolution and sequestration of arsenic by microbial iron and thiosulfate reduction

Environmental Geochemistry and Health - Iron oxide and oxy-hydroxide are commonly used for remediation and rehabilitation of arsenic (As)-contaminated soil and water. However, the stability of As...     

Colloid mobilization and heavy metal transport in the sampling of soil solution from Duckum soil in South Korea

Environmental Geochemistry and Health - Colloid mobilization is a significant process governing colloid-associated transport of heavy metals in subsurface environments. It has been studied for the...     

The potential implementation of green infrastructure assessment using high-resolution National Agriculture Imagery Program data for sustainable hazard mitigation

As green infrastructure gets its attention in hazard mitigation, it is necessary to improve general understanding on what makes green infrastructure important for hazard and resiliency research. To better understand how green infrastructure fits with more traditional notions of structural and nonstructural mitigation, this study examines the relationship between green infrastructure and ‘structural and nonstructural’ mitigation approaches for hazard mitigation. Also, this study discusses a new measurement of locational aspects and spatial patterns of green infrastructure by utilizing high-resolution data in urban areas, and its potential implementation in hazard mitigation. Compared to previous research using land-use land-cover datasets, the normalized difference vegetation index (NDVI) utilizing National Agriculture Imagery Program dataset provides an ability to capture green infrastructure in greater detail. A visual comparison suggests that the NDVI data are able to capture and identify more types of ‘green’ land uses in Harris County. The total green infrastructure percentages for Harris County, Texas, based on 1-m high resolution were found to be 61.5% of the area, compared to the 51.5% based on the National Land Cover Database. This study provides support for utilizing high-resolution data to establish guidelines for green infrastructure’s spatial characteristics and sustainable hazard mitigation. The outcomes of this study will be helpful in the strategic planning and implementation of green infrastructure in urban areas with hazard issues.