期刊
JOURNAL OF CLEANER PRODUCTION
卷 218, 期 -, 页码 335-346出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2019.01.326
关键词
Electroflotation; Automotive paint; Wastewater treatment; Modelling; Energy efficiency; Continuous-flow reactor
资金
- University of Western Ontario
- Natural Sciences and Engineering Research Council of Canada (NSERC)
With painting operations as a major origin of environmental concerns in automotive industry, novel and effective technologies are required for treatment of automotive paint wastewater. In this experimental study, a continuous-flow electroflotation reactor with effective volume of 38.4 L and stainless-steel electrodes were designed and implemented for treatment of this industrial wastewater. The system performance, namely the total suspended solids removal, was investigated with operational parameters including the hydraulic retention time, current density and influent total solids concentration. The removal rate ranged between 57 +/- 1% and 95 +/- 7% under initial total solids concentration 3000 mg/L, current density 50 A/m(2), retention time 4 min, and initial total solids concentration 500 mg/L, current density 100 A/m(2), retention time 8 min conditions, respectively. It was found that the removal rate decreases with the increase of influent total solids concentration. The results revealed that the suspended solids removal rate is directly related to the applied current density and hydraulic retention time. The electroflotation system showed to be energy-efficient compared to the commercial systems. Further, an empirical equation for the total suspended solids removal rate was established with the R-2 value of 92.74%. The independent variables were the retention time, influent suspended solids concentration and applied current density. (C) 2019 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
Article
Green & Sustainable Science & Technology
Relative evaluation of probabilistic methods for spatio-temporal wind forecasting
Lars odegaard Bentsen, Narada Dilp Warakagoda, Roy Stenbro, Paal Engelstad
Summary: This study investigates uncertainty modeling in wind power forecasting using different parametric and non-parametric methods. Johnson's SU distribution is found to outperform Gaussian distributions in predicting wind power. This research contributes to the literature by introducing Johnson's SU distribution as a candidate for probabilistic wind forecasting.
JOURNAL OF CLEANER PRODUCTION (2024)
Article
Green & Sustainable Science & Technology
Comparison of ethane recovery processes for lean gas based on a coupled model
Xing Liu, Qiuchen Wang, Yunhao Wen, Long Li, Xinfang Zhang, Yi Wang
Summary: This study analyzes the characteristics of process parameters in three lean gas ethane recovery processes and establishes a prediction and multiobjective optimization model for ethane recovery and system energy consumption. A new method for comparing ethane recovery processes for lean gas is proposed, and the addition of extra coolers improves the ethane recovery. The support vector regression model based on grey wolf optimization demonstrates the highest prediction accuracy, and the multiobjective multiverse optimization algorithm shows the best optimization performance and diversity in the solutions.
JOURNAL OF CLEANER PRODUCTION (2024)
Article
Green & Sustainable Science & Technology
A novel deep-learning framework for short-term prediction of cooling load in public buildings
Cairong Song, Haidong Yang, Xian-Bing Meng, Pan Yang, Jianyang Cai, Hao Bao, Kangkang Xu
Summary: The paper proposes a novel deep learning-based prediction framework, aTCN-LSTM, for accurate cooling load predictions. The framework utilizes a gate-controlled multi-head temporal convolutional network and a sparse probabilistic self-attention mechanism with a bidirectional long short-term memory network to capture both temporal and long-term dependencies in the cooling load sequences. Experimental results demonstrate the effectiveness and superiority of the proposed method, which can serve as an effective guide for HVAC chiller scheduling and demand management initiatives.
JOURNAL OF CLEANER PRODUCTION (2024)
Article
Green & Sustainable Science & Technology
The impact of social interaction and information acquisition on the adoption of soil and water conservation technology by farmers: Evidence from the Loess Plateau, China
Zhe Chen, Xiaojing Li, Xianli Xia, Jizhou Zhang
Summary: This study uses survey data from the Loess Plateau in China to evaluate the impact of social interaction on the adoption of soil and water conservation (SWC) technology by farmers. The study finds that social interaction increases the likelihood of farmers adopting SWC, and internet use moderates this effect. The positive impact of social interaction on SWC adoption is more pronounced for farmers in larger villages and those who join cooperative societies.
JOURNAL OF CLEANER PRODUCTION (2024)
Article
Green & Sustainable Science & Technology
Study on synergistic heat transfer enhancement and adaptive control behavior of baffle under sudden change of inlet velocity in a micro combustor
Chenghua Zhang, Yunfei Yan, Kaiming Shen, Zongguo Xue, Jingxiang You, Yonghong Wu, Ziqiang He
Summary: This paper reports a novel method that significantly improves combustion performance, including heat transfer enhancement under steady-state conditions and adaptive stable flame regulation under velocity sudden increase.
JOURNAL OF CLEANER PRODUCTION (2024)
分享论文
