The applications of chlorine have been broadly used in many industrial products, such as bleaching agents, synthetic rubbers, plastics, disinfectants, iron chlorides, fire refractory materials, insecticides, and anti-freezers, etc. According to the Taiwan Environmental Protection Administration (TEPA), more than 30 thousand tons were used in the year 2000. In addition, there were more than 12 reported incidents from 2000 to 2003—mostly on using chlorine as disinfectants (five) and as process agents (four).
This study investigated 15 chlorine operation plants in central Taiwan. These chlorine usages included bleaching agents, disinfectants, iron chloride, synthesizing rubber plastics, and others. Thirteen plants were located in the industrial parks and two were in or near residential zones. The consequence analysis were used three different methods to analyze the worst-case scenarios (WCSs) and alternative release case scenarios (ACSs) in order to compare impact zones for applying various active and passive mitigation systems, such as confined space, scrubber, water-spray, and so no. For two plants in or near residential zones, multi-layers mitigation systems and operation limits should be implemented in order to enforce more stringent protection measures. However, there was no specific regulation for chlorine plants operated at different locations, such as industrial parks or residential zones. In order to reduce chemical accidents and their impacts on public safety, our results suggest that source mitigation/management and warning systems should be adopted simultaneously. 相似文献
This study develops a stratified conditional Latin hypercube sampling (scLHS) approach for multiple, remotely sensed, normalized difference vegetation index (NDVI) images. The objective is to sample, monitor, and delineate spatiotemporal landscape changes, including spatial heterogeneity and variability, in a given area. The scLHS approach, which is based on the variance quadtree technique (VQT) and the conditional Latin hypercube sampling (cLHS) method, selects samples in order to delineate landscape changes from multiple NDVI images. The images are then mapped for calibration and validation by using sequential Gaussian simulation (SGS) with the scLHS selected samples. Spatial statistical results indicate that in terms of their statistical distribution, spatial distribution, and spatial variation, the statistics and variograms of the scLHS samples resemble those of multiple NDVI images more closely than those of cLHS and VQT samples. Moreover, the accuracy of simulated NDVI images based on SGS with scLHS samples is significantly better than that of simulated NDVI images based on SGS with cLHS samples and VQT samples, respectively. However, the proposed approach efficiently monitors the spatial characteristics of landscape changes, including the statistics, spatial variability, and heterogeneity of NDVI images. In addition, SGS with the scLHS samples effectively reproduces spatial patterns and landscape changes in multiple NDVI images. 相似文献