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Process Data set: Groundwater remediation;In-situ remediation ; Adsorption ; Preparation of adsorbents ; Electrolysis (en) en zh

Key Data Set Information
Location ID
Reference year 2022
Name
Groundwater remediation;In-situ remediation ; Adsorption ; Preparation of adsorbents ; Electrolysis
Use advice for data set When utilizing the dataset for modeling and assessment purposes, ensure all methodology follows best practices for in-situ remediation lifecycle assessment. This includes proper accounting for the production and application of the AHNP2 nanoparticles and the associated energy and material inputs into the system. Attention should be paid to the impact of electrolysis conditions, such as current density and duration, on the properties of the nanoparticles. It is also essential to consider the removal efficiency of the nanoparticles and their fate post-treatment in the environmental impact assessment.
Technical purpose of product or process The process described is used for the production of aluminum hydroxide nanoparticles (AHNP2), which are intended for in-situ groundwater remediation applications. These nanoparticles are designed to adsorb contaminants from groundwater by being directly applied to the contaminated site, hence facilitating the removal of pollutants without the need for pumping out the water.
Classification
Class name : Hierarchy level
  • ILCD: Unit processes / Other Services / Repair and maintenance
General comment on data set The aluminum electrode was dissolved in distilled water with a current density of 195 A/m to prepare AHNP2. The electrolysis process lasted for 2 hours, after which it was stopped and the aluminum hydroxide nanoparticles were allowed to settle at the bottom of the electrochemical reactor. The settled particles (precipitate) were filtered and washed multiple times with distilled water to remove traces of sodium chloride used in the electrochemical cell, in order to increase the conductivity of the electrolyte solution.
Copyright No
Owner of data set
Quantitative reference
Reference flow(s)
Technological representativeness
Flow diagram(s) or picture(s)
  • V9NVbc0qRoz39Kxiu1JcNyiQnqh.png Image
LCI method and allocation
Type of data set Unit process, single operation
Deviation from LCI method principle / explanations None
Deviation from modelling constants / explanations None
Data sources, treatment and representativeness
Deviation from data cut-off and completeness principles / explanations None
Deviation from data selection and combination principles / explanations None
Deviation from data treatment and extrapolations principles / explanations None
Data source(s) used for this data set
Completeness
Completeness of product model No statement
Validation
Type of review
Dependent internal review
Reviewer name and institution
Data generator
Data set generator / modeller
Data entry by
Time stamp (last saved) 2024-03-25T14:10:16+08:00
Publication and ownership
UUID ff810493-2ebc-4ddc-a94d-99d2e113fa9b
Date of last revision 2024-04-20T15:00:55.245496+08:00
Data set version 00.01.005
Permanent data set URI https://lcadata.tiangong.world/showProcess.xhtml?uuid=ff810493-2ebc-4ddc-a94d-99d2e113fa9b&version=01.00.000&stock=TianGong
Owner of data set
Copyright No
License type Free of charge for all users and uses

Inputs

Type of flow Classification Flow Location Mean amount Resulting amount Minimum amount Maximum amount
Product flow Materials production / Metals and semimetals 1.05 m31.05 m3
Product flow Materials production / Water 0.015 kg0.015 kg
Product flow Materials production / Inorganic chemicals 0.17 kg0.17 kg
Product flow Energy carriers and technologies / Electricity 130.392 MJ130.392 MJ

Outputs

Type of flow Classification Flow Location Mean amount Resulting amount Minimum amount Maximum amount
Product flow
End-of-life treatment / Waste water treatment 0.006500000000000001 kg0.006500000000000001 kg
General comment Washed water
Product flow
Materials production / Other materials 8.5 kg8.5 kg
General comment Wet Adsorbent