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.     

Absorption characteristics of new solvent based on a blend of AMP and 1,8-diamino-p-menthane for CO2 absorption

Aqueous 1,8-diamino-p-menthane (KIER-C3) and commercially available amine solutions were tested for CO₂ absorption. A 2-amino- 2-methyl-1-propanol (AMP) solution with an addition of KIER-C3 showed 9.3% and 31.6% higher absorption rate for CO₂ than the AMP solution with an addition of monoethanolamine (MEA) and ammonia (NH₃), respectively. The reaction rate constant for CO₂ absorption by the AMP/KIER-C3 solution was determined by the following equation: k_2,AMP/C3 = 7.702×10⁶ exp (-2248.03/T). A CO₂ loading ratio of the AMP/KIER-C3 solution was also 2 and 3.4-times higher than that of the AMP/NH3 solution and the AMP/MEA solution, respectively. Based on the experimental results, KIER-C3 may be used as an excellent additive to increase CO₂ absorption capability of AMP.     

Quality control for coal combustion products in South Korea through assessed pozzolanic-activity index with long-term property tests

In South Korea, nine million tons of fly ash (FA) are annually produced and approximately 70 % is reutilized for industrial demand. For the prompt reuse and insufficient reclamation site, quality control of FA which is main productive construction material from coal ash is very important. Assessed Pozzolanic-activity Index (API) test which needs only 2 days for evaluation of pozzolanic reaction is currently considered as an alternative of activity index measurement. This paper aims for an applicability of API test for prompt quality control and investigation of domestic FA properties. For the work, FAs from two different power plant types are prepared, and quality tests are carried out based on Korean Standards (KS) methods and API method. Lots of test results are compared with those from API and K-value test for FA with age of 7 days–1 year. From the test results for FA aged 1 year, API results are evaluated to be closely related with those from activity index and K-value, and the correlations are improved with increasing ages regardless of plant types. The applicability of API test is verified and the reduced period of FA quality evaluation can accelerate prompt use and the related process of FA.     

Distribution features of biological hazardous pollutants in residential environments in Korea

This research has been conducted continuously since 2009 as part of a cohort of studies examining relationships between asthma and genetic factors, dietary habits, and environmental factors. Based on data from environmental research on house dust mites and endotoxins, which are widely known as pollutants in bedding that cause asthma in pregnant women and children, this work was conducted to obtain basic data that can be used in future cohort studies that analyze links between distribution of biological hazards and physical features of residential environments. The detection rates of house dust mite allergens, Der p1 and Der f1, were 52.7 and 86.5 %, respectively, indicating that Der f1 is a dominant species in domestic indoor environments. According to comparisons between concentrations of house dust mites and endotoxins in bedding of pregnant women and children, Der p1 and endotoxins showed significantly lower concentrations in bedding of pregnant women compared with those in bedding of children, whereas Der f1 showed no significant difference in concentration according to bedding.     

Formic acid as an alternative reducing agent for the catalytic nitrate reduction in aqueous media

Formic acid was used for the nitrate reduction as a reductant in the presence of Pd:Cu/γ-alumina catalysts. The surface characteristics of the bimetallic catalyst synthesized by wet impregnation were investigated by SEM, TEM-EDS. The metals were not distributed homogeneously on the surface of catalyst, although the total contents of both metals in particles agreed well with the theoretical values. Formic acid decomposition on the catalyst surface, its influence on solution pH and nitrate removal efficacy was investigated. The best removal of nitrate (50 ppm) was obtained under the condition of 0.75 g/L catalyst with Pd:Cu ratio (4:1) and two fold excess of formic acid. Formic acid decay patterns resembled those of nitrate removal, showing a linear relationship between kf (formic acid decay) and k (nitrate removal). Negligible amount of ammonia was detected, and no nitrite was detected, possibly due to buffering effect of bicarbonate that is in situ produced by the decomposition of formic acid, and due to the sustained release of H2 gas.     

Prediction of effluent concentration in a wastewater treatment plant using machine learning models

Of growing amount of food waste, the integrated food waste and waste water treatment was regarded as one of the efficient modeling method. However, the load of food waste to the conventional waste treatment process might lead to the high concentration of total nitrogen(T-N) impact on the effluent water quality. The objective of this study is to establish two machine learning models—artificial neural networks(ANNs) and support vector machines(SVMs), in order to predict 1-day interval T-N concentration of effluent from a wastewater treatment plant in Ulsan, Korea. Daily water quality data and meteorological data were used and the performance of both models was evaluated in terms of the coefficient of determination(R~2), Nash–Sutcliff efficiency(NSE), relative efficiency criteria(d rel). Additionally, Latin-Hypercube one-factor-at-a-time(LH-OAT) and a pattern search algorithm were applied to sensitivity analysis and model parameter optimization, respectively. Results showed that both models could be effectively applied to the 1-day interval prediction of T-N concentration of effluent. SVM model showed a higher prediction accuracy in the training stage and similar result in the validation stage.However, the sensitivity analysis demonstrated that the ANN model was a superior model for 1-day interval T-N concentration prediction in terms of the cause-and-effect relationship between T-N concentration and modeling input values to integrated food waste and waste water treatment. This study suggested the efficient and robust nonlinear time-series modeling method for an early prediction of the water quality of integrated food waste and waste water treatment process.     

Sensitivity of veliger larvae of Mytilus edulis and mussel of various sizes to chlorination

The blue mussel Mytilus edulis is one of the dominant fouling organisms in cooling water systems. In this work, how veliger larvae and different size groups of the mussels responded against chlorine dosage was examined. Veliger larvae mortality was studied at different residual chlorine concentrations (0.05–0.5 mg L^?1), and it was found that a chlorine dose of 0.5 mg L^?1 is 4 times as effective as 0.05 mg L^?1 and twice as effective as 0.1 mg L^?1. Mortality of 100% for three size groups (1.4, 14, and 25 mm) and relative physiological activities of two size groups (14 and 25 mm) were observed. The exposure duration for 100% mortality of mussels decreased with the increasing residual chlorine concentration (0.1–4.0 mg L^?1). Mussel size was also found to be an important factor, considering that the continuation times for mussel mortality were 28 h for the 1.4 mm and 410 h for the 25 mm size groups. All size groups showed progressive reduction in physiological activities, such as oxygen consumption, foot activity, and byssus thread production with increasing chlorine dose (0.05–1.0 mg L^?1); the two data-sets were strongly correlated with each other. The results of this study should be of significance for optimizing the chlorine content, and minimize the environmental threat to industries where mussels are the dominant fouling organisms.