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一种用于模拟痕量元素在厌氧消化环境中命运的通用框架。

A general framework to model the fate of trace elements in anaerobic digestion environments.

机构信息

Department of Civil and Mechanical Engineering, University of Cassino and the Southern Lazio, Via di Biasio 43, 03043, Cassino, FR, Italy.

Department of Mathematics and Applications "Renato Caccioppoli", University of Naples Federico II, Naples, Italy.

出版信息

Sci Rep. 2021 Apr 5;11(1):7476. doi: 10.1038/s41598-021-85403-2.

Abstract

Due to the multiplicity of biogeochemical processes taking place in anaerobic digestion (AD) systems and limitations of the available analytical techniques, assessing the bioavailability of trace elements (TEs) is challenging. Determination of TE speciation can be facilitated by developing a mathematical model able to consider the physicochemical processes affecting TEs dynamics. A modeling framework based on anaerobic digestion model no 1 (ADM1) has been proposed to predict the biogeochemical fate TEs in AD environments. In particular, the model considers the TE adsorption-desorption reactions with biomass, inerts and mineral precipitates, as well as TE precipitation/dissolution, complexation reactions and biodegradation processes. The developed model was integrated numerically, and numerical simulations have been run to investigate the model behavior. The simulation scenarios predicted the effect of (i) organic matter concentration, (ii) initial TEs concentrations, (iii) initial Ca-Mg concentrations, (iv) initial EDTA concentration, and (v) change in TE binding site density, on cumulative methane production and TE speciation. Finally, experimental data from a real case continuous AD system have been compared to the model predictions. The results prove that this modelling framework can be applied to various AD operations and may also serve as a basis to develop a model-predictive TE dosing strategy.

摘要

由于厌氧消化(AD)系统中发生的生物地球化学过程的多样性和可用分析技术的局限性,评估痕量元素(TE)的生物可利用性具有挑战性。通过开发能够考虑影响 TE 动态的物理化学过程的数学模型,可以促进 TE 形态的测定。已经提出了基于厌氧消化模型 1(ADM1)的建模框架,以预测 AD 环境中 TE 的生物地球化学命运。具体而言,该模型考虑了 TE 与生物质、惰性物质和矿物沉淀物的吸附-解吸反应,以及 TE 的沉淀/溶解、络合反应和生物降解过程。开发的模型进行了数值集成,并运行了数值模拟来研究模型的行为。模拟场景预测了(i)有机物浓度、(ii)初始 TE 浓度、(iii)初始 Ca-Mg 浓度、(iv)初始 EDTA 浓度以及(v)TE 结合位点密度变化对累积甲烷产量和 TE 形态的影响。最后,将实际连续 AD 系统的实验数据与模型预测进行了比较。结果证明,该建模框架可应用于各种 AD 操作,也可作为开发模型预测 TE 投加策略的基础。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2314/8021560/a14d3b0c55a4/41598_2021_85403_Fig1_HTML.jpg

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