Input-dependent life-cycle inventory model of industrial wastewater-treatment processes in the chemical sector.

Environ Sci Technol

Empa, Technology and Society Laboratory, Uberlandstrasse 129, CH-8600 Diibendorf, Switzerland.

Published: August 2007

Industrial wastewater-treatment systems need to ensure a high level of protection for the environment as a whole. Life-cycle assessment (LCA) comprehensively evaluates the environmental impacts of complex treatment systems, taking into account impacts from auxiliaries and energy consumption as well as emissions. However, the application of LCA is limited by a scarcity of wastewater-specific life-cycle inventory (LCI) data. This study presents a modular gate-to-gate inventory model for industrial wastewater purification in the chemical and related sectors. It enables the calculation of inventory parameters as a function of the wastewater composition and the technologies applied. Forthis purpose, data on energy and auxiliaries' consumption, wastewater composition, and process parameters was collected from chemical industry. On this basis, causal relationships between wastewater input, emissions, and technical inputs were identified. These causal relationships were translated into a generic inventory model. Generic and site-specific data ranges for LCI parameters are provided for the following processes: mechanical-biological treatment, high-pressure wet-air oxidation, nanofiltration, and extraction. The input- and technology-dependent process inventories help to bridge data gaps where primary data are not available. Thus, they substantially help to perform an environmental assessment of industrial wastewater purification in the chemical and associated industries, which may be used, for instance, for technology choices.

Download full-text PDF

Source
http://dx.doi.org/10.1021/es0617284DOI Listing

Publication Analysis

Top Keywords

inventory model
12
life-cycle inventory
8
model industrial
8
industrial wastewater-treatment
8
industrial wastewater
8
wastewater purification
8
purification chemical
8
wastewater composition
8
causal relationships
8
inventory
5

Similar Publications

Background: Ventricular arrhythmias (VAs) frequently occur in the acute phase of myocarditis. Possible arrhythmic recurrences and the risk of sudden cardiac death (SCD) in this setting are reasons for concern, and limited data have been published to guide clinical management of these patients. The aim of the present paper is to report the incidence of major arrhythmic events, defined as sustained VA, SCD and appropriate implantable cardiac-defibrillator (ICD) treatment, in patients with acute myocarditis and ventricular arrhythmic phenotype.

View Article and Find Full Text PDF

Accurate estimates of forest dynamics and above-ground forest biomass for the topographically challenging Himalaya are crucial for understanding carbon storage potential, assessing ecosystem services, and guiding conservation efforts in response to climate change. This dataset provides a manually delineated multi-temporal forest inventory and a comprehensive record of above-ground biomass (AGB) across the Kashmir Himalaya, generated from field observations, advanced remote sensing and machine learning. Data were collected and generated through remote sensing techniques and extensive in-situ measurements of 6220 trees (n=275 plots), including tree diameter at breast height, species composition, and tree density to map forest area and model AGB across varied terrain.

View Article and Find Full Text PDF

Introduction: The full-scale Russian war has caused Ukrainian female refugees to experience many stressful events which may have an adverse impact on their mental health. Understanding the prevalence and determinants associated with anxiety is essential for psychosocial support. The study aimed: to evaluate the psychometric validity of the Ukrainian version of the Beck Anxiety Inventory (BAI) among Ukrainian female refugees in the Czech Republic, to determine the prevalence of anxiety, and to identify key determinants for anxiety in this population.

View Article and Find Full Text PDF

Biokinetic soft-sensing using Thiothrix and Ca. Microthrix bacteria to calibrate secondary settling, aeration and NO emission digital twins.

Water Res

January 2025

Department of Chemical Engineering, University of Bath, Claverton Down, Bath BA2 7AY, UK; SWING - Department of Built Environment, Oslo Metropolitan University, St Olavs plass 0130, Oslo, Norway. Electronic address:

Climate resilience in water resource recovery facilities (WRRFs) necessitates improved adaptation to shock-loading conditions and mitigating greenhouse gas emission. Data-driven learning methods are widely utilised in soft-sensors for decision support and process optimization due to their simplicity and high predictive accuracy. However, unlike for mechanistic models, transferring machine-learning-based insights across systems is largely infeasible, which limits communication and knowledge sharing.

View Article and Find Full Text PDF

Background: Wearable sensor technologies, often referred to as "wearables," have seen a rapid rise in consumer interest in recent years. Initially often seen as "activity trackers," wearables have gradually expanded to also estimate sleep, stress, and physiological recovery. In occupational settings, there is a growing interest in applying this technology to promote health and well-being, especially in professions with highly demanding working conditions such as first responders.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!