4.7 Article

Quantifying gel properties of industrial waste-based geopolymers and their application in Pb2+ and Cu2+ removal

Journal

JOURNAL OF CLEANER PRODUCTION
Volume 315, Issue -, Pages -

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2021.128203

Keywords

Geopolymer; Red mud; Coal gangue; Adsorption; Heavy metal; Industrial wastewater

Funding

  1. Natural Science Fund of Guangdong Province [2021A1515010558]

Ask authors/readers for more resources

The study found a positive correlation between geopolymer gel and heavy metal adsorption capacity, with external sources of silicon and aluminum affecting the specific surface area and dissolution which further impacted the adsorption performance. All tested geopolymers exhibited heavy metal adsorption based on the Langmuir isotherm and the pseudo-second-order kinetic model.
In this study, novel geopolymers based on solid wastes (coal gangue and red mud) were used in the adsorption of heavy metals (Pb2+ and Cu2+) from solution. The correlations between the composition and quantity of the geopolymer gels and heavy metal adsorption were investigated under various conditions using hydrochloric acid dissolution and spectroscopic techniques. The results showed that the geopolymer gel positively correlated with the Pb2+ and Cu2+ adsorption capacities in the absence of external silica and aluminum. Moreover, external silica and aluminum sources promoted Al2O3 and SiO2 dissolution in the raw materials, which increased and decreased the specific surface areas, respectively. All of the tested geopolymers exhibited Pb2+ and Cu(2+ )adsorption based on the Langmuir isotherm and the pseudo-second-order kinetic model, with adsorption maxima of 137.7 and 90 mg g(-1), respectively. This research first determined the correlation between the geopolymer gel and its heavy metal adsorption performance, and demonstrated industrial waste-based geopolymers could be effectively applied for the removal of heavy metal which can help reduce the burden of waste management and provide new insights about the resource recovery of solid wastes.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

Article Environmental Sciences

An environmental-friendly magnetic bio-adsorbent for high-efficiency Pb (II) removal: Preparation, characterization and its adsorption performance

Jiaying Feng, Jun Zhang, Weifeng Song, Jianguo Liu, Zhicheng Hu, Bingqin Bao

ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY (2020)

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)