Lactate production from lactose-rich wastewater: A comparative study on reactor configurations to maximize conversion rates and efficiencies

IF 11.4 1区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL
Monika Temovska , Richard Hegner , Andrés E. Ortiz-Ardila , Joseph G. Usack , Largus T. Angenent
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Abstract

About 90 % of global lactate production is derived from bacterial fermentation of sugars via pure homofermentative cultures in batch mode. Acid whey, which is a lactose-rich wastewater from the yogurt industry, can be used as an alternative substrate for commercial lactate production. Operating reactor microbiomes reduces the lactate production costs by circumventing sterilization, while continuous operation with biomass retention achieves higher productivity at shorter production times. To find the best reactor configuration with biomass retention for lactate production from acid whey, we operated three different reactor configurations: (1) an upflow anaerobic sludge blanket (UASB) reactor; (2) an anaerobic filter reactor (AFR); and (3) an anaerobic continuously stirred tank reactor (CSTR) with a hollow-fiber membrane module. We operated at different hydraulic retention times (HRTs) to find the optimum production parameters at a temperature of 50 °C and a pH of 5.0. We did not use an inoculum but enriched the endogenous D-lactate-producing Lactobacillus spp. that later dominated the reactor microbiomes (> 90 % relative abundance). Undissociated lactic acid concentrations of more than 60 mmol C L−1 inhibited the microbiomes. We alleviated the inhibition effect by shortening the HRT to 0.6 days and using diluted acid-whey substrate (1.67-fold dilution) to achieve almost complete conversion of the acid-whey sugars to lactate. At the 0.6-day HRT, the AFR and CSTR performed better than the UASB reactor due to their better cell retention abilities. During the period between Day 365–384, we experienced an error in the pH control of the CSTR system during which the pH value dropped to 4.3. After this pH-error period, the lactose and galactose-into-lactate (LG-into-LA) conversion efficiency for the CSTR considerably improved and surpassed the AFR. We achieved the highest lactate conversion rate of 1256 ± 46.3 mmol C L−1 d−1 (1.57 ± 0.06 g L−1 h−1) at a LG-into-LA conversion efficiency of 82.2 ± 3.4 % (in mmol C), with a yield of 0.85 ± 0.02 mmol C mmol C−1 (product per consumed substrate) for the CSTR.

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来源期刊
Water Research
Water Research 环境科学-工程:环境
CiteScore
20.80
自引率
9.40%
发文量
1307
审稿时长
38 days
期刊介绍: Water Research, along with its open access companion journal Water Research X, serves as a platform for publishing original research papers covering various aspects of the science and technology related to the anthropogenic water cycle, water quality, and its management worldwide. The audience targeted by the journal comprises biologists, chemical engineers, chemists, civil engineers, environmental engineers, limnologists, and microbiologists. The scope of the journal include: •Treatment processes for water and wastewaters (municipal, agricultural, industrial, and on-site treatment), including resource recovery and residuals management; •Urban hydrology including sewer systems, stormwater management, and green infrastructure; •Drinking water treatment and distribution; •Potable and non-potable water reuse; •Sanitation, public health, and risk assessment; •Anaerobic digestion, solid and hazardous waste management, including source characterization and the effects and control of leachates and gaseous emissions; •Contaminants (chemical, microbial, anthropogenic particles such as nanoparticles or microplastics) and related water quality sensing, monitoring, fate, and assessment; •Anthropogenic impacts on inland, tidal, coastal and urban waters, focusing on surface and ground waters, and point and non-point sources of pollution; •Environmental restoration, linked to surface water, groundwater and groundwater remediation; •Analysis of the interfaces between sediments and water, and between water and atmosphere, focusing specifically on anthropogenic impacts; •Mathematical modelling, systems analysis, machine learning, and beneficial use of big data related to the anthropogenic water cycle; •Socio-economic, policy, and regulations studies.
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