SlideShare a Scribd company logo
D1.2 Operational demo cases
CS7 Tain
UCRAN, Aquabio
2
The project leading to this application has received funding from the European Union’s
Horizon 2020 research and innovation programme under grant agreement No 869318
CS7: Tain
Lead partner:
Other partner:
With support of:
3
The project leading to this application has received funding from the European Union’s
Horizon 2020 research and innovation programme under grant agreement No 869318
CS7: Situation before Ultimate
4
The project leading to this application has received funding from the European Union’s
Horizon 2020 research and innovation programme under grant agreement No 869318
CS7: Objectives of the Ultimate solutions
5
The project leading to this application has received funding from the European Union’s
Horizon 2020 research and innovation programme under grant agreement No 869318
CS7: Subtask 1.2.6 status/progress
Subtask: 1.2.6 RO treatment of distillery wastewater after AnMBR for internal water reuse
Baseline technology: no water reuse so far (discharge of AnMBR effluent to Dornoch Firth)
TRL: 5  7
Ultimate solution to foster circular economy: RO system for distillery wastewater (AnMBR effluent)
Capacity of demo plant: 1 m³/d
Quantifiable target: At full scale, potential for the production of 58,000 m³/a for internal water reuse; >40 % reduction of freshwater
through reuse of treated water
Status/progress:
• System operational and initial trials conducted
6
The project leading to this application has received funding from the European Union’s
Horizon 2020 research and innovation programme under grant agreement No 869318
CS7: Results of the laboratory experiments
Subtask: 1.2.6 RO treatment of distillery wastewater after AnMBR for internal water reuse
Lab-scale trials were carried out to evaluate the impact of the reverse osmosis
membranes position in the treatment train. Experiments with the different waters
(anaerobically treated = raw, after precipitation and after stripping) were
performed in a Sterlitech HP4750 lab-scale dead-end filtration cell using Trisep
X201 RO flat sheet membranes to achieve 50% permeate recovery.
Anaerobic MBR effluent
Reverse osmosis permeate Reverse osmosis concentrate
The RO permeate obtained from the water pre-treated through precipitation and stripping delivers the best quality for reuse.
However, the RO concentrate obtained directly from the treatment of the anaerobic MBR effluent provides a more concentrated
source of nutrients in a smaller volume which would make the nutrients recovery step more sustainable.
7
The project leading to this application has received funding from the European Union’s
Horizon 2020 research and innovation programme under grant agreement No 869318
CS7: Results of the laboratory experiments
Subtask: 1.2.6 RO treatment of distillery wastewater after AnMBR for internal water reuse
Experimental trials on different feed waters in a Sterlitech HP4750 lab-scale dead-end filtration cell using Trisep X201 RO flat sheet
membranes to achieve 50% permeate recovery.
Overall, pH adjustment (increase for the precipitation and stripping steps and decrease for the RO filtration) significantly
increases the salt concentration in the water.
The sequence of the technologies in the treatment train can be adpated but it will lead to trade-offs between membrane fouling,
resource recovery potential and quality of water for reuse.
Interestingly, the fouling resistance in the
RO membranes was found to be slightly
higher with the water which went through
stripping first due to the increase in salts
after pH adjustment.
However, due to the nature of the water,
the effluent from the anaerobic MBR
(labelled raw here) produced a more
complex fouling with struvite crystals
identified on the surface of the
membrane.
8
The project leading to this application has received funding from the European Union’s
Horizon 2020 research and innovation programme under grant agreement No 869318
CS7: Pictures and initial results of the technology
Subtask: 1.2.6 RO treatment of distillery wastewater after AnMBR for internal water reuse
The RO unit is designed to achieve high quality water for reuse from the distillery wastewater after treatment through a pre-
precipitation stage and ammonia stripping. The system is fitted with TriSep 1812 X20 membrane elements. Trials were so far
conducted in batch to evaluate the operability of the unit to meet a water recovery of 50%.
9
The project leading to this application has received funding from the European Union’s
Horizon 2020 research and innovation programme under grant agreement No 869318
CS7: Task 1.2.6 - Timeline
 Pilot scale experiments started in August 2022 (M27)
 Additional lab scale experiments will continue to be carried out in parallel to
the operation of the pilot unit to help further support the evaluation
Subtask: 1.2.6 RO treatment of distillery wastewater after AnMBR for internal water reuse
Legend
Task/Subtask
Activity as planned
Postponed activity
Delay of activity
Extension of activity
M1
M2
M3
M4
M5
M6
M7
M8
M9
M10
M11
M12
M1
M2
M3
M4
M5
M6
M7
M8
M9
M10
M11
M12
M1
M2
M3
M4
M5
M6
M7
M8
M9
M10
M11
M12
M1
M2
M3
M4
M5
M6
M7
M8
M9
M10
M11
M12
M1
M2
M3
M4
M5
YEAR 5
YEAR 4
YEAR 1 YEAR 2 YEAR 3
T1.2.6 - RO treatment of distillery wastewater after AnMBR for
internal water reuse in Tain
Baseline conditions assessed MS05 D1.1
Design of pilot system MS09
Laboratory scale experiments MS15 + 9M
Pilot system operational MS15 + 9M D1.2 + 3M
Start-up & results MS19 D1.9
Best practices for water recycling D1.3
10
The project leading to this application has received funding from the European Union’s
Horizon 2020 research and innovation programme under grant agreement No 869318
CS7: Subtask 1.3.5 status/progress
Subtask: 1.3.5 Heat recovery from treated (AnMBR) distillery wastewater
Baseline technology: Biogas production via existing AnMBR; no heat recovery before Ultimate
TRL: 5  7
Ultimate solutions to foster circular economy: heat from the AnMBR effluent utilized in subsequent treatment steps
Capacity of demo plant: heat utilization will be tested in all systems at 1 m3/d for the RO and 12 m³/d for the nutrients recovery
system and 14 kW of heat recovery can be expected
Quantifiable targets: At full scale, >15 % reduction of energy demand from biogas and 60 % heat recovery within stripping column unit
Status/progress:
• System operational and initial trials conducted
11
The project leading to this application has received funding from the European Union’s
Horizon 2020 research and innovation programme under grant agreement No 869318
CS7: First results of the new technologies
Subtask: 1.3.5 Heat recovery from treated (AnMBR) distillery wastewater
The biogas produced in the AnMBR first goes through a scrubber for H2S removal and is then converted to steam in a boiler.
The steam produced is reused to heat the stills in the distillery and contribute to reduce its dependence on fossil fuel by 15%.
https://www.forbesgroup.co.uk/envir
onmental-technologies/packed-
tower/
12
The project leading to this application has received funding from the European Union’s
Horizon 2020 research and innovation programme under grant agreement No 869318
CS7: Task 1.3.5 - Timeline
 Residual heat utilisation trials were started in August 2022 (M27) to
evaluate the impact of temperature in the reverse osmosis membrane
and further trials will be carried out in the nutrients recovery steps.
 Monitoring of the biogas and steam productions from the full scale
AnMBR continues
Subtask: 1.3.5 Heat recovery from treated (AnMBR) distillery wastewater
Legend
Task/Subtask
Activity as planned
Postponed activity
Delay of activity
Extension of activity
M1
M2
M3
M4
M5
M6
M7
M8
M9
M10
M11
M12
M1
M2
M3
M4
M5
M6
M7
M8
M9
M10
M11
M12
M1
M2
M3
M4
M5
M6
M7
M8
M9
M10
M11
M12
M1
M2
M3
M4
M5
M6
M7
M8
M9
M10
M11
M12
M1
M2
M3
M4
M5
YEAR 5
YEAR 4
YEAR 1 YEAR 2 YEAR 3
T1.3.5 - Heat recovery from treated (AnMBR) distillery wastewater
in Tain
Baseline conditions assessed MS05 D1.1
Design of pilot system MS09
Pilot system operational MS15 +9M D1.2 + 3M
Start-up & results MS19 D1.9
Best practices for energy recovery D1.4
13
The project leading to this application has received funding from the European Union’s
Horizon 2020 research and innovation programme under grant agreement No 869318
CS7: Subtask 1.4.6 status/progress
Subtask: 1.4.6 Recovery of ammonia from distillery wastewater via IEX/packed columns after AnMBR
Baseline technology: reuse of digestate on the barley fields
TRL: 5  7 (air stripping column & scrubber); 5  7 (struvite precipitation)
Ultimate solution to foster circular economy: air stripping column & scrubber; struvite precipitation
Capacity of demo plants:12-24 m³/d
Quantifiable target: At full scale, potential for the production of 122 t struvite/a from the pre-precipitation stage and 47 t nitrogen/a from
ammonia stripping, corresponding to about 80% P recovery and 80% N recovery in total
Status/progress:
• System operational and initial trials conducted
14
The project leading to this application has received funding from the European Union’s
Horizon 2020 research and innovation programme under grant agreement No 869318
Subtask: 1.4.6 Recovery of ammonia from distillery wastewater via IEX/packed columns after AnMBR
CS7: Results of the preliminary evaluation
The evaluation of current knowledge and performance of ion
exchange, stripping and precipitation based systems for ammonia
recovery form industrial wastewaters and the measured
characteristics of the anaerobically treated distillery wastewater
led to the selection of a two-stage system comprising pre-
precipitation (struvite) followed ammonia stripping to maximize the
recovery of nutrients.
15
The project leading to this application has received funding from the European Union’s
Horizon 2020 research and innovation programme under grant agreement No 869318
CS7: Pictures of the struvite precipitator and
ammonia stripping unit
Subtask: 1.4.6 Recovery of ammonia from distillery wastewater after AnMBR
16
The project leading to this application has received funding from the European Union’s
Horizon 2020 research and innovation programme under grant agreement No 869318
CS7: Task 1.4.6 - Timeline
 Nutrients recovery systems were commissioned in September 2022 (M28).
 The pilot and lab scale experiments will continue in parallel
until the end of the project
Subtask: 1.4.6 Recovery of ammonia from distillery wastewater after AnMBR
Legend
Task/Subtask
Activity as planned
Postponed activity
Delay of activity
Extension of activity
M1
M2
M3
M4
M5
M6
M7
M8
M9
M10
M11
M12
M1
M2
M3
M4
M5
M6
M7
M8
M9
M10
M11
M12
M1
M2
M3
M4
M5
M6
M7
M8
M9
M10
M11
M12
M1
M2
M3
M4
M5
M6
M7
M8
M9
M10
M11
M12
M1
M2
M3
M4
M5
YEAR 5
YEAR 4
YEAR 1 YEAR 2 YEAR 3
T1.4.6 - Recovery of ammonia from distillery wastewater by
IEX/packed columns after AnMBR in Tain
Baseline conditions assessed MS05 D1.1
Design of pilot system MS09
Laboratory scale experiments MS15 +10M
Pilot system operational MS15 +10M D1.2 + 4M
Start-up & results MS19 D1.9
Best practices for material recovery D1.5
The project leading to this application has received funding from the European Union’s
Horizon 2020 research and innovation programme under grant agreement No 869318
m.pidou@cranfield.ac.uk
CS7 Contacts
M.M.Gritti@cranfield.ac.uk

More Related Content

Similar to D1.2-Demonstrator Case Study Tain

D1.2-Demonstrator Case Study Nafplio
D1.2-Demonstrator Case Study NafplioD1.2-Demonstrator Case Study Nafplio
D1.2-Demonstrator Case Study Nafplio
DrKristineJung
 
D1.2-Demonstrator Case Study Kalundborg
D1.2-Demonstrator Case Study KalundborgD1.2-Demonstrator Case Study Kalundborg
D1.2-Demonstrator Case Study Kalundborg
DrKristineJung
 
D1.2-Demonstrator Case Study Nieuw Prinsenland
D1.2-Demonstrator Case Study Nieuw PrinsenlandD1.2-Demonstrator Case Study Nieuw Prinsenland
D1.2-Demonstrator Case Study Nieuw Prinsenland
DrKristineJung
 
D1.2-Demonstrator Case Study Nieuw Prinsenland
D1.2-Demonstrator Case Study Nieuw PrinsenlandD1.2-Demonstrator Case Study Nieuw Prinsenland
D1.2-Demonstrator Case Study Nieuw Prinsenland
DrKristineJung
 
D1.2-Demonstrator Case Study Nieuw Prinsenland
D1.2-Demonstrator Case Study Nieuw PrinsenlandD1.2-Demonstrator Case Study Nieuw Prinsenland
D1.2-Demonstrator Case Study Nieuw Prinsenland
DrKristineJung
 
D1.2-Demonstrator Case Study Kalundborg
D1.2-Demonstrator Case Study KalundborgD1.2-Demonstrator Case Study Kalundborg
D1.2-Demonstrator Case Study Kalundborg
DrKristineJung
 
D1.2-Demonstrator Case Study Karmiel/Shafdan
D1.2-Demonstrator Case Study Karmiel/ShafdanD1.2-Demonstrator Case Study Karmiel/Shafdan
D1.2-Demonstrator Case Study Karmiel/Shafdan
DrKristineJung
 
D1.2 operational demo cases
D1.2 operational demo casesD1.2 operational demo cases
D1.2 operational demo cases
NextGen Water Solutions
 
D1.2-Demonstrator Case Study Saint-Maurice l´Exil
D1.2-Demonstrator Case Study Saint-Maurice l´ExilD1.2-Demonstrator Case Study Saint-Maurice l´Exil
D1.2-Demonstrator Case Study Saint-Maurice l´Exil
DrKristineJung
 
D1.2-Demonstrator Case Study Saint-Maurice l´Exil
D1.2-Demonstrator Case Study Saint-Maurice l´ExilD1.2-Demonstrator Case Study Saint-Maurice l´Exil
D1.2-Demonstrator Case Study Saint-Maurice l´Exil
DrKristineJung
 
D1.2-Demonstrator Case Study Karmiel/Shafdan
D1.2-Demonstrator Case Study Karmiel/ShafdanD1.2-Demonstrator Case Study Karmiel/Shafdan
D1.2-Demonstrator Case Study Karmiel/Shafdan
DrKristineJung
 
D1.2-Demonstrator Case Study Karmiel/Shafdan
D1.2-Demonstrator Case Study Karmiel/ShafdanD1.2-Demonstrator Case Study Karmiel/Shafdan
D1.2-Demonstrator Case Study Karmiel/Shafdan
DrKristineJung
 
D1.2-Demonstrator Case Study Rosignano
D1.2-Demonstrator Case Study RosignanoD1.2-Demonstrator Case Study Rosignano
D1.2-Demonstrator Case Study Rosignano
DrKristineJung
 
D1.2-Demonstrator Case Study Karmiel/Shafdan
D1.2-Demonstrator Case Study Karmiel/ShafdanD1.2-Demonstrator Case Study Karmiel/Shafdan
D1.2-Demonstrator Case Study Karmiel/Shafdan
DrKristineJung
 
D1.2-Demonstrator Case Study Tarragona
D1.2-Demonstrator Case Study TarragonaD1.2-Demonstrator Case Study Tarragona
D1.2-Demonstrator Case Study Tarragona
DrKristineJung
 
D1.2-Demonstrator Case Study Tarragona
D1.2-Demonstrator Case Study TarragonaD1.2-Demonstrator Case Study Tarragona
D1.2-Demonstrator Case Study Tarragona
DrKristineJung
 
D1.2-Demonstrator Case Study Rosignano
D1.2-Demonstrator Case Study RosignanoD1.2-Demonstrator Case Study Rosignano
D1.2-Demonstrator Case Study Rosignano
DrKristineJung
 
NextGen Athens, Greece
NextGen Athens, GreeceNextGen Athens, Greece
NextGen Athens, Greece
NextGen Water Solutions
 
D1.2-Demonstrator Case Study Rosignano
D1.2-Demonstrator Case Study RosignanoD1.2-Demonstrator Case Study Rosignano
D1.2-Demonstrator Case Study Rosignano
DrKristineJung
 
D1.2-Demonstrator Case Study Tarragona
D1.2-Demonstrator Case Study TarragonaD1.2-Demonstrator Case Study Tarragona
D1.2-Demonstrator Case Study Tarragona
DrKristineJung
 

Similar to D1.2-Demonstrator Case Study Tain (20)

D1.2-Demonstrator Case Study Nafplio
D1.2-Demonstrator Case Study NafplioD1.2-Demonstrator Case Study Nafplio
D1.2-Demonstrator Case Study Nafplio
 
D1.2-Demonstrator Case Study Kalundborg
D1.2-Demonstrator Case Study KalundborgD1.2-Demonstrator Case Study Kalundborg
D1.2-Demonstrator Case Study Kalundborg
 
D1.2-Demonstrator Case Study Nieuw Prinsenland
D1.2-Demonstrator Case Study Nieuw PrinsenlandD1.2-Demonstrator Case Study Nieuw Prinsenland
D1.2-Demonstrator Case Study Nieuw Prinsenland
 
D1.2-Demonstrator Case Study Nieuw Prinsenland
D1.2-Demonstrator Case Study Nieuw PrinsenlandD1.2-Demonstrator Case Study Nieuw Prinsenland
D1.2-Demonstrator Case Study Nieuw Prinsenland
 
D1.2-Demonstrator Case Study Nieuw Prinsenland
D1.2-Demonstrator Case Study Nieuw PrinsenlandD1.2-Demonstrator Case Study Nieuw Prinsenland
D1.2-Demonstrator Case Study Nieuw Prinsenland
 
D1.2-Demonstrator Case Study Kalundborg
D1.2-Demonstrator Case Study KalundborgD1.2-Demonstrator Case Study Kalundborg
D1.2-Demonstrator Case Study Kalundborg
 
D1.2-Demonstrator Case Study Karmiel/Shafdan
D1.2-Demonstrator Case Study Karmiel/ShafdanD1.2-Demonstrator Case Study Karmiel/Shafdan
D1.2-Demonstrator Case Study Karmiel/Shafdan
 
D1.2 operational demo cases
D1.2 operational demo casesD1.2 operational demo cases
D1.2 operational demo cases
 
D1.2-Demonstrator Case Study Saint-Maurice l´Exil
D1.2-Demonstrator Case Study Saint-Maurice l´ExilD1.2-Demonstrator Case Study Saint-Maurice l´Exil
D1.2-Demonstrator Case Study Saint-Maurice l´Exil
 
D1.2-Demonstrator Case Study Saint-Maurice l´Exil
D1.2-Demonstrator Case Study Saint-Maurice l´ExilD1.2-Demonstrator Case Study Saint-Maurice l´Exil
D1.2-Demonstrator Case Study Saint-Maurice l´Exil
 
D1.2-Demonstrator Case Study Karmiel/Shafdan
D1.2-Demonstrator Case Study Karmiel/ShafdanD1.2-Demonstrator Case Study Karmiel/Shafdan
D1.2-Demonstrator Case Study Karmiel/Shafdan
 
D1.2-Demonstrator Case Study Karmiel/Shafdan
D1.2-Demonstrator Case Study Karmiel/ShafdanD1.2-Demonstrator Case Study Karmiel/Shafdan
D1.2-Demonstrator Case Study Karmiel/Shafdan
 
D1.2-Demonstrator Case Study Rosignano
D1.2-Demonstrator Case Study RosignanoD1.2-Demonstrator Case Study Rosignano
D1.2-Demonstrator Case Study Rosignano
 
D1.2-Demonstrator Case Study Karmiel/Shafdan
D1.2-Demonstrator Case Study Karmiel/ShafdanD1.2-Demonstrator Case Study Karmiel/Shafdan
D1.2-Demonstrator Case Study Karmiel/Shafdan
 
D1.2-Demonstrator Case Study Tarragona
D1.2-Demonstrator Case Study TarragonaD1.2-Demonstrator Case Study Tarragona
D1.2-Demonstrator Case Study Tarragona
 
D1.2-Demonstrator Case Study Tarragona
D1.2-Demonstrator Case Study TarragonaD1.2-Demonstrator Case Study Tarragona
D1.2-Demonstrator Case Study Tarragona
 
D1.2-Demonstrator Case Study Rosignano
D1.2-Demonstrator Case Study RosignanoD1.2-Demonstrator Case Study Rosignano
D1.2-Demonstrator Case Study Rosignano
 
NextGen Athens, Greece
NextGen Athens, GreeceNextGen Athens, Greece
NextGen Athens, Greece
 
D1.2-Demonstrator Case Study Rosignano
D1.2-Demonstrator Case Study RosignanoD1.2-Demonstrator Case Study Rosignano
D1.2-Demonstrator Case Study Rosignano
 
D1.2-Demonstrator Case Study Tarragona
D1.2-Demonstrator Case Study TarragonaD1.2-Demonstrator Case Study Tarragona
D1.2-Demonstrator Case Study Tarragona
 

Recently uploaded

spirit beverages ppt without graphics.pptx
spirit beverages ppt without graphics.pptxspirit beverages ppt without graphics.pptx
spirit beverages ppt without graphics.pptx
Madan Karki
 
Generative AI leverages algorithms to create various forms of content
Generative AI leverages algorithms to create various forms of contentGenerative AI leverages algorithms to create various forms of content
Generative AI leverages algorithms to create various forms of content
Hitesh Mohapatra
 
bank management system in java and mysql report1.pdf
bank management system in java and mysql report1.pdfbank management system in java and mysql report1.pdf
bank management system in java and mysql report1.pdf
Divyam548318
 
Properties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptxProperties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptx
MDSABBIROJJAMANPAYEL
 
2. Operations Strategy in a Global Environment.ppt
2. Operations Strategy in a Global Environment.ppt2. Operations Strategy in a Global Environment.ppt
2. Operations Strategy in a Global Environment.ppt
PuktoonEngr
 
sieving analysis and results interpretation
sieving analysis and results interpretationsieving analysis and results interpretation
sieving analysis and results interpretation
ssuser36d3051
 
Literature Review Basics and Understanding Reference Management.pptx
Literature Review Basics and Understanding Reference Management.pptxLiterature Review Basics and Understanding Reference Management.pptx
Literature Review Basics and Understanding Reference Management.pptx
Dr Ramhari Poudyal
 
6th International Conference on Machine Learning & Applications (CMLA 2024)
6th International Conference on Machine Learning & Applications (CMLA 2024)6th International Conference on Machine Learning & Applications (CMLA 2024)
6th International Conference on Machine Learning & Applications (CMLA 2024)
ClaraZara1
 
Manufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptxManufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptx
Madan Karki
 
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTCHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
jpsjournal1
 
digital fundamental by Thomas L.floydl.pdf
digital fundamental by Thomas L.floydl.pdfdigital fundamental by Thomas L.floydl.pdf
digital fundamental by Thomas L.floydl.pdf
drwaing
 
Swimming pool mechanical components design.pptx
Swimming pool  mechanical components design.pptxSwimming pool  mechanical components design.pptx
Swimming pool mechanical components design.pptx
yokeleetan1
 
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsKuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
Victor Morales
 
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...Electric vehicle and photovoltaic advanced roles in enhancing the financial p...
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...
IJECEIAES
 
A review on techniques and modelling methodologies used for checking electrom...
A review on techniques and modelling methodologies used for checking electrom...A review on techniques and modelling methodologies used for checking electrom...
A review on techniques and modelling methodologies used for checking electrom...
nooriasukmaningtyas
 
132/33KV substation case study Presentation
132/33KV substation case study Presentation132/33KV substation case study Presentation
132/33KV substation case study Presentation
kandramariana6
 
Embedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoringEmbedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoring
IJECEIAES
 
Series of visio cisco devices Cisco_Icons.ppt
Series of visio cisco devices Cisco_Icons.pptSeries of visio cisco devices Cisco_Icons.ppt
Series of visio cisco devices Cisco_Icons.ppt
PauloRodrigues104553
 
Advanced control scheme of doubly fed induction generator for wind turbine us...
Advanced control scheme of doubly fed induction generator for wind turbine us...Advanced control scheme of doubly fed induction generator for wind turbine us...
Advanced control scheme of doubly fed induction generator for wind turbine us...
IJECEIAES
 
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdfBPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
MIGUELANGEL966976
 

Recently uploaded (20)

spirit beverages ppt without graphics.pptx
spirit beverages ppt without graphics.pptxspirit beverages ppt without graphics.pptx
spirit beverages ppt without graphics.pptx
 
Generative AI leverages algorithms to create various forms of content
Generative AI leverages algorithms to create various forms of contentGenerative AI leverages algorithms to create various forms of content
Generative AI leverages algorithms to create various forms of content
 
bank management system in java and mysql report1.pdf
bank management system in java and mysql report1.pdfbank management system in java and mysql report1.pdf
bank management system in java and mysql report1.pdf
 
Properties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptxProperties Railway Sleepers and Test.pptx
Properties Railway Sleepers and Test.pptx
 
2. Operations Strategy in a Global Environment.ppt
2. Operations Strategy in a Global Environment.ppt2. Operations Strategy in a Global Environment.ppt
2. Operations Strategy in a Global Environment.ppt
 
sieving analysis and results interpretation
sieving analysis and results interpretationsieving analysis and results interpretation
sieving analysis and results interpretation
 
Literature Review Basics and Understanding Reference Management.pptx
Literature Review Basics and Understanding Reference Management.pptxLiterature Review Basics and Understanding Reference Management.pptx
Literature Review Basics and Understanding Reference Management.pptx
 
6th International Conference on Machine Learning & Applications (CMLA 2024)
6th International Conference on Machine Learning & Applications (CMLA 2024)6th International Conference on Machine Learning & Applications (CMLA 2024)
6th International Conference on Machine Learning & Applications (CMLA 2024)
 
Manufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptxManufacturing Process of molasses based distillery ppt.pptx
Manufacturing Process of molasses based distillery ppt.pptx
 
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTCHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECT
 
digital fundamental by Thomas L.floydl.pdf
digital fundamental by Thomas L.floydl.pdfdigital fundamental by Thomas L.floydl.pdf
digital fundamental by Thomas L.floydl.pdf
 
Swimming pool mechanical components design.pptx
Swimming pool  mechanical components design.pptxSwimming pool  mechanical components design.pptx
Swimming pool mechanical components design.pptx
 
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsKuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressions
 
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...Electric vehicle and photovoltaic advanced roles in enhancing the financial p...
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...
 
A review on techniques and modelling methodologies used for checking electrom...
A review on techniques and modelling methodologies used for checking electrom...A review on techniques and modelling methodologies used for checking electrom...
A review on techniques and modelling methodologies used for checking electrom...
 
132/33KV substation case study Presentation
132/33KV substation case study Presentation132/33KV substation case study Presentation
132/33KV substation case study Presentation
 
Embedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoringEmbedded machine learning-based road conditions and driving behavior monitoring
Embedded machine learning-based road conditions and driving behavior monitoring
 
Series of visio cisco devices Cisco_Icons.ppt
Series of visio cisco devices Cisco_Icons.pptSeries of visio cisco devices Cisco_Icons.ppt
Series of visio cisco devices Cisco_Icons.ppt
 
Advanced control scheme of doubly fed induction generator for wind turbine us...
Advanced control scheme of doubly fed induction generator for wind turbine us...Advanced control scheme of doubly fed induction generator for wind turbine us...
Advanced control scheme of doubly fed induction generator for wind turbine us...
 
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdfBPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
BPV-GUI-01-Guide-for-ASME-Review-Teams-(General)-10-10-2023.pdf
 

D1.2-Demonstrator Case Study Tain

  • 1. D1.2 Operational demo cases CS7 Tain UCRAN, Aquabio
  • 2. 2 The project leading to this application has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 869318 CS7: Tain Lead partner: Other partner: With support of:
  • 3. 3 The project leading to this application has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 869318 CS7: Situation before Ultimate
  • 4. 4 The project leading to this application has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 869318 CS7: Objectives of the Ultimate solutions
  • 5. 5 The project leading to this application has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 869318 CS7: Subtask 1.2.6 status/progress Subtask: 1.2.6 RO treatment of distillery wastewater after AnMBR for internal water reuse Baseline technology: no water reuse so far (discharge of AnMBR effluent to Dornoch Firth) TRL: 5  7 Ultimate solution to foster circular economy: RO system for distillery wastewater (AnMBR effluent) Capacity of demo plant: 1 m³/d Quantifiable target: At full scale, potential for the production of 58,000 m³/a for internal water reuse; >40 % reduction of freshwater through reuse of treated water Status/progress: • System operational and initial trials conducted
  • 6. 6 The project leading to this application has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 869318 CS7: Results of the laboratory experiments Subtask: 1.2.6 RO treatment of distillery wastewater after AnMBR for internal water reuse Lab-scale trials were carried out to evaluate the impact of the reverse osmosis membranes position in the treatment train. Experiments with the different waters (anaerobically treated = raw, after precipitation and after stripping) were performed in a Sterlitech HP4750 lab-scale dead-end filtration cell using Trisep X201 RO flat sheet membranes to achieve 50% permeate recovery. Anaerobic MBR effluent Reverse osmosis permeate Reverse osmosis concentrate The RO permeate obtained from the water pre-treated through precipitation and stripping delivers the best quality for reuse. However, the RO concentrate obtained directly from the treatment of the anaerobic MBR effluent provides a more concentrated source of nutrients in a smaller volume which would make the nutrients recovery step more sustainable.
  • 7. 7 The project leading to this application has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 869318 CS7: Results of the laboratory experiments Subtask: 1.2.6 RO treatment of distillery wastewater after AnMBR for internal water reuse Experimental trials on different feed waters in a Sterlitech HP4750 lab-scale dead-end filtration cell using Trisep X201 RO flat sheet membranes to achieve 50% permeate recovery. Overall, pH adjustment (increase for the precipitation and stripping steps and decrease for the RO filtration) significantly increases the salt concentration in the water. The sequence of the technologies in the treatment train can be adpated but it will lead to trade-offs between membrane fouling, resource recovery potential and quality of water for reuse. Interestingly, the fouling resistance in the RO membranes was found to be slightly higher with the water which went through stripping first due to the increase in salts after pH adjustment. However, due to the nature of the water, the effluent from the anaerobic MBR (labelled raw here) produced a more complex fouling with struvite crystals identified on the surface of the membrane.
  • 8. 8 The project leading to this application has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 869318 CS7: Pictures and initial results of the technology Subtask: 1.2.6 RO treatment of distillery wastewater after AnMBR for internal water reuse The RO unit is designed to achieve high quality water for reuse from the distillery wastewater after treatment through a pre- precipitation stage and ammonia stripping. The system is fitted with TriSep 1812 X20 membrane elements. Trials were so far conducted in batch to evaluate the operability of the unit to meet a water recovery of 50%.
  • 9. 9 The project leading to this application has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 869318 CS7: Task 1.2.6 - Timeline  Pilot scale experiments started in August 2022 (M27)  Additional lab scale experiments will continue to be carried out in parallel to the operation of the pilot unit to help further support the evaluation Subtask: 1.2.6 RO treatment of distillery wastewater after AnMBR for internal water reuse Legend Task/Subtask Activity as planned Postponed activity Delay of activity Extension of activity M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 M12 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 M12 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 M12 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 M12 M1 M2 M3 M4 M5 YEAR 5 YEAR 4 YEAR 1 YEAR 2 YEAR 3 T1.2.6 - RO treatment of distillery wastewater after AnMBR for internal water reuse in Tain Baseline conditions assessed MS05 D1.1 Design of pilot system MS09 Laboratory scale experiments MS15 + 9M Pilot system operational MS15 + 9M D1.2 + 3M Start-up & results MS19 D1.9 Best practices for water recycling D1.3
  • 10. 10 The project leading to this application has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 869318 CS7: Subtask 1.3.5 status/progress Subtask: 1.3.5 Heat recovery from treated (AnMBR) distillery wastewater Baseline technology: Biogas production via existing AnMBR; no heat recovery before Ultimate TRL: 5  7 Ultimate solutions to foster circular economy: heat from the AnMBR effluent utilized in subsequent treatment steps Capacity of demo plant: heat utilization will be tested in all systems at 1 m3/d for the RO and 12 m³/d for the nutrients recovery system and 14 kW of heat recovery can be expected Quantifiable targets: At full scale, >15 % reduction of energy demand from biogas and 60 % heat recovery within stripping column unit Status/progress: • System operational and initial trials conducted
  • 11. 11 The project leading to this application has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 869318 CS7: First results of the new technologies Subtask: 1.3.5 Heat recovery from treated (AnMBR) distillery wastewater The biogas produced in the AnMBR first goes through a scrubber for H2S removal and is then converted to steam in a boiler. The steam produced is reused to heat the stills in the distillery and contribute to reduce its dependence on fossil fuel by 15%. https://www.forbesgroup.co.uk/envir onmental-technologies/packed- tower/
  • 12. 12 The project leading to this application has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 869318 CS7: Task 1.3.5 - Timeline  Residual heat utilisation trials were started in August 2022 (M27) to evaluate the impact of temperature in the reverse osmosis membrane and further trials will be carried out in the nutrients recovery steps.  Monitoring of the biogas and steam productions from the full scale AnMBR continues Subtask: 1.3.5 Heat recovery from treated (AnMBR) distillery wastewater Legend Task/Subtask Activity as planned Postponed activity Delay of activity Extension of activity M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 M12 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 M12 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 M12 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 M12 M1 M2 M3 M4 M5 YEAR 5 YEAR 4 YEAR 1 YEAR 2 YEAR 3 T1.3.5 - Heat recovery from treated (AnMBR) distillery wastewater in Tain Baseline conditions assessed MS05 D1.1 Design of pilot system MS09 Pilot system operational MS15 +9M D1.2 + 3M Start-up & results MS19 D1.9 Best practices for energy recovery D1.4
  • 13. 13 The project leading to this application has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 869318 CS7: Subtask 1.4.6 status/progress Subtask: 1.4.6 Recovery of ammonia from distillery wastewater via IEX/packed columns after AnMBR Baseline technology: reuse of digestate on the barley fields TRL: 5  7 (air stripping column & scrubber); 5  7 (struvite precipitation) Ultimate solution to foster circular economy: air stripping column & scrubber; struvite precipitation Capacity of demo plants:12-24 m³/d Quantifiable target: At full scale, potential for the production of 122 t struvite/a from the pre-precipitation stage and 47 t nitrogen/a from ammonia stripping, corresponding to about 80% P recovery and 80% N recovery in total Status/progress: • System operational and initial trials conducted
  • 14. 14 The project leading to this application has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 869318 Subtask: 1.4.6 Recovery of ammonia from distillery wastewater via IEX/packed columns after AnMBR CS7: Results of the preliminary evaluation The evaluation of current knowledge and performance of ion exchange, stripping and precipitation based systems for ammonia recovery form industrial wastewaters and the measured characteristics of the anaerobically treated distillery wastewater led to the selection of a two-stage system comprising pre- precipitation (struvite) followed ammonia stripping to maximize the recovery of nutrients.
  • 15. 15 The project leading to this application has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 869318 CS7: Pictures of the struvite precipitator and ammonia stripping unit Subtask: 1.4.6 Recovery of ammonia from distillery wastewater after AnMBR
  • 16. 16 The project leading to this application has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 869318 CS7: Task 1.4.6 - Timeline  Nutrients recovery systems were commissioned in September 2022 (M28).  The pilot and lab scale experiments will continue in parallel until the end of the project Subtask: 1.4.6 Recovery of ammonia from distillery wastewater after AnMBR Legend Task/Subtask Activity as planned Postponed activity Delay of activity Extension of activity M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 M12 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 M12 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 M12 M1 M2 M3 M4 M5 M6 M7 M8 M9 M10 M11 M12 M1 M2 M3 M4 M5 YEAR 5 YEAR 4 YEAR 1 YEAR 2 YEAR 3 T1.4.6 - Recovery of ammonia from distillery wastewater by IEX/packed columns after AnMBR in Tain Baseline conditions assessed MS05 D1.1 Design of pilot system MS09 Laboratory scale experiments MS15 +10M Pilot system operational MS15 +10M D1.2 + 4M Start-up & results MS19 D1.9 Best practices for material recovery D1.5
  • 17. The project leading to this application has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 869318 m.pidou@cranfield.ac.uk CS7 Contacts M.M.Gritti@cranfield.ac.uk