Assessing the efficacy of dissolved air and flash-pressurized flotations using low energy for the removal of organic precursors and disinfection byproducts: a pilot-scale study

Environmental Science and Pollution Research - Dissolved air flotation (DAF) is a widely used treatment process in drinking water and wastewater treatment plants despite high energy cost associated...     

Pollutants and sperm quality: a systematic review and meta-analysis

Environmental Science and Pollution Research - Male fertility and semen quality have declined over recent decades. Among other causes, exposure to environmental and occupational pollution has been...     

Discovering meaningful information from large amounts of environment and health data to reduce uncertainties in formulating environmental policies

This study uses knowledge discovery concepts to analyze large amounts of data step by step for the purpose of assisting in the formulation of environmental policy. We performed data cleansing and extracting from existing nation-wide databases, and used regression and classification techniques to analyze the data. The current water hardness in Kaohsiung, Taiwan contributes to the prevention of cardiovascular disease (CVD) but exacerbates the development of renal stones (RS). However, to focus on water hardness alone to control RS would not be cost effective at all, because the existing database parameters do not adequately allow for a clear understanding of RS. Analysis of huge amounts of data can most often turn up the most reliable and convincing results and the use of existing databases can be cost-effective.     

Stable isotope on the evaluation of water quality in the presence of WWTPs in rivers

Environmental Science and Pollution Research - We investigated the distribution of nitrogen compounds in Han River as well as two tributaries of Tancheon and Jungrangcheon. Particularly, we...     

Enrichment of the metallic components from waste printed circuit boards by a mechanical separation process using a stamp mill

Printed circuit boards incorporated in most electrical and electronic equipment contain valuable metals such as Cu, Ni, Au, Ag, Pd, Fe, Sn, and Pb. In order to employ a hydrometallurgical route for the recycling of valuable metals from printed circuit boards, a mechanical pre-treatment step is needed. In this study, the metallic components from waste printed circuit boards have been enriched using a mechanical separation process. Waste printed circuit boards shredded to <10mm were milled using a stamp mill to liberate the various metallic components, and then the milled printed circuit boards were classified into fractions of <0.6, 0.6-1.2, 1.2-2.5, 2.5-5.0, and >5.0mm. The fractions of milled printed circuit boards of size <5.0mm were separated into a light fraction of mostly non-metallic components and a heavy fraction of the metallic components by gravity separation using a zig-zag classifier. The >5.0mm fraction and the heavy fraction were subjected to two-step magnetic separation. Through the first magnetic separation at 700 Gauss, 83% of the nickel and iron, based on the whole printed circuit boards, was recovered in the magnetic fraction, and 92% of the copper was recovered in the non-magnetic fraction. The cumulative recovery of nickel-iron concentrate was increased by a second magnetic separation at 3000 Gauss, but the grade of the concentrate decreased remarkably from 76% to 56%. The cumulative recovery of copper concentrate decreased, but the grade increased slightly from 71.6% to 75.4%. This study has demonstrated the feasibility of the mechanical separation process consisting of milling/size classification/gravity separation/two-step magnetic separation for enriching metallic components such as Cu, Ni, Al, and Fe from waste printed circuit boards.     

Characterizing Driving Patterns for Zhuhai for Traffic Emissions Estimation

Abstract

Zhuhai, a relatively less developed city on the western coast of the Pearl River Delta (PRD) of China, is planning to undergo major development in coming years. A Hong Kong-Zhuhai-Macao Bridge project has been approved by the Central Government of China. The project will have great impact on the driving pattern and vehicular emissions to the city. This baseline study collected speed-time data of two instrumented private cars in morning and evening periods, as well as a daytime nonpeak period of >10 consecutive days in the spring and winter of 2003. The authors used the microwave speed sensor and global positioning system installed in the instrumented cars and used car-chasing technique to perform the data collection. They used the statistical package SPSS to assess the consistency, as well as to evaluate the variability of the data. Nine parameters, namely, average speed, average running speed, average acceleration rate, average deceleration rate, mean length of a driving period, time proportions of driving modes, average number of acceleration-deceleration changes, root mean square acceleration, and positive acceleration kinetic energy are calculated to represent the driving characteristics. A driving cycle for private cars was developed. If emission tests were conducted using the Zhuhai driving cycle, the level of vehicle emissions measured is likely to be in between that of the Federal Test Procedure (FTP) cycle and the Melbourne Peak cycle.