Precipitation of heavy metals from wastewater using simulated flue gas: sequent additions of fly ash, lime and carbon dioxide

Lime is a preferred precipitant for the removal of heavy metals from industrial wastewater due to its relatively low cost. To reduce heavy metal concentration to an acceptable level for discharge, in this work, fly ash was added as a seed material to enhance lime precipitation and the suspension was exposed to CO2 gas. The fly ash-lime-carbonation treatment increased the particle size of the precipitate and significantly improved sedimentation of sludge and the efficiency of heavy metal removal. The residual concentrations of chromium, copper, lead and zinc in effluents can be reduced to (mg L-1) 0.08, 0.14, 0.03 and 0.45, respectively. Examination of the precipitates by XRD and thermal analysis techniques showed that calcium-heavy metal double hydroxides and carbonates were present. The precipitate agglomerated and hardened naturally, facilitating disposal without the need for additional solidification/stabilization measures prior to landfill. It is suggested that fly ash, lime and CO2, captured directly from flue gas, may have potential as a method for wastewater treatment. This method could allow the ex-situ sequestration of CO2, particularly where flue-gas derived CO2 is available near wastewater treatment facilities. (C) 2009 Elsevier Ltd. All rights reserved.

Human respiration rate estimation using ultra-wideband distributed cognitive radar system

It has been shown that remote monitoring of pulmonary activity can be achieved using ultra-wideband (UWB) systems, which shows promise in home healthcare, rescue, and security applications. In this paper, we first present a multi-ray propagation model for UWB signal, which is traveling through the human thorax and is reflected on the air/dry-skin/fat/muscle interfaces. A geometry-based statistical channel model is then developed for simulating the reception of UWB signals in the indoor propagation environment. This model enables replication of time-varying multipath profiles due to the displacement of a human chest. Subsequently, a UWB distributed cognitive radar system (UWB-DCRS) is developed for the robust detection of chest cavity motion and the accurate estimation of respiration rate. The analytical framework can serve as a basis in the planning and evaluation of future measurement programs. We also provide a case study on how the antenna beamwidth affects the estimation of respiration rate based on the proposed propagation models and system architecture