Periodic Reporting for period 3 - intelWATT (intelligent Water Treatment Technologies for water preservation combined with simultaneous energy production and material recovery in energy intensive industries)
Periodo di rendicontazione: 2023-04-01 al 2024-09-30
Unsustainable uses of water resources, population dynamics, along with climate change lead this critical resource to become scarce. The problem of water scarcity is very important for the society since clean and abundant supply of water is vital for supporting activities like food production, public health, industrial and energy conversion. More specific, industry is one of the main water users in Europe, accounting for about 30-40 % of total water abstractions. To mitigate these issues, sustainable water management approaches are needed. In that content, the general concept of intelWATT project is to introduce new innovative technological solutions towards the increase of water preservation and reuse in industrial environment. The main objective of the intelWATT project is to validate, at TRL7-8, innovative & intelligent water treatment technologies combining fresh water preservation with resources recovery and energy conversion based on the circular economy concept. This was demonstrated through three different case studies in representative energy intensive industrial activities (power generation, mining, manufacturing-electroplating): a) fresh water preservation through a >99% reduction of cooling tower blow down (CTBD) in a combined cycle natural gas power plant, b) energy conversion and water recovery from a symbiotic scheme exploiting mining and wastewater effluents and c) a closed loop for the simultaneous recovery of valuable metals and wastewater treatment to significantly reduce heavy loaded wastewater effluents & process costs in a plastic electroplating facility.
The targets and objectives of the project are implemented through ten Work Packages (WP) as described in brief:
1)In WP2: a) the identification of the basic water streams for each case study was performed, b) the potentials for water preservation were explored, c) an in-depth physicochemical characterization of the process streams d) the key quality parameters, units’ performance indexes and sensors’ requirements were specified and finally e) the inputs -outputs parameters / values of the Machine Learning system were defined.
2)In WP3: a) lab scale units were constructed for all intelWATT’s processes (UltraFiltration, NanoFiltration, Reverse Osmosis, Reverse ElectroDialysis and Membrane Distillation). Additionally the smart monitoring concept was implemented and optimized in a large scale format.
3)In WP4: a) Graphene based ion exchange membranes, Artificial Water Channels NF and RO membranes, Hollow Fibers NF membranes, PVDF based MD membranes and UF-Membranes for pre-treatment were developed, upscaled and characterized and b) new hollow fibers MD and UF modules were designed and constructed.
4)In WP5(CS1) following the detailed P&ID phase, the pilot construction was initiated and completed within the specifications described in the DoA. The pilot was design and constructed by NI and NCSRD and commissioned in the premises of PPC’s power plant. Evaluation results of the pilot operation confirmed that the concept of >99% recovery of the CTBD is feasible within the set energy consumption threshold of 5 KWhe/m3. AI assisted pilot operation was also established while real time monitoring and remote control was available to the operators of the unit.
5) WP6 (CS2) pilot plant focuses on the integration of UF, RED and solar assisted MD. As conclusions, UF proved to be an effective pretreatment method for removing turbidity and particles achieving all the estimated KPIs. RED briefly achieved the target to produce 3MJ of renewable energy per m3 of brine, reaching its most important project objective. The objective of MD for production of 1m3/h of distilled water is achievable under certain circumstances related to the feed salinity and availability of thermal energy. Moreover, the quality of permeate remained excellent below 1 μS cm even at high salinity feeds.
6) WP7 (CS3) The system assessment focused on the recirculation of the regenerate and the evaluation of the relevant parameters. The analyses of the influencing factors resulted in recovery rates for water of between 70.6 % and 88.1 %. The system was thus able to successfully recover the components and regenerate a permeate that can be reused as rinsing water. For the recirculation of the regenerate, 10% and 30% of the recovered concentrate were added to the Cr(III) electrolyte. Results showed that a ratio of 10% concentrate to 90% electrolyte can be used without reducing product quality. Overall, this case study was very successful and the technology can be fully industrialized.
7)In WP8: advanced development and integration of the Artificial Intelligence system like the dashboard, the data lake, the AI algorithms, the sensors ingestion mechanism and the communication protocols were established and tested for the interconnectivity, smart monitoring and optimization of energy consumption and water production of the demo units.
8)In WP9: a) the Life Cycle Assessment Analysis referring to all CS was completed. A study focusing on industrial wastewater processing in water stressed areas proved the replicability of the proposed technologies. Finally, a health and safety assessment were conducted ensuring the harm-free nature of the intelWATT approaches for both humans and environment.
9) WP10 included: a) the set-up and constant update of project’s website and social media platforms, b) the preparation of the exploitation and dissemination registries, c) the preparation of the Plan for the Exploitation and Dissemination of the project’s results and d) networking and clustering actions, strong presence in workshops, conferences and trades as well as 20 journal publications. The exploitation potential of the R&I advancements during the project’s duration is strongly reflected in the Innovation Radar initiative where seven technologies are included, with two considered as market ready.
10)The development of a Quality assurance plan for the management and control of projects’ administrative and financial aspects as well as a constantly updated Data Management strategy. A risk monitoring registry has been the cornerstone for the progress monitoring and mitigation actions ensuring the best possible implementation of the project’s technical timeframe.
1)In WP2: a) the identification of the basic water streams for each case study was performed, b) the potentials for water preservation were explored, c) an in-depth physicochemical characterization of the process streams d) the key quality parameters, units’ performance indexes and sensors’ requirements were specified and finally e) the inputs -outputs parameters / values of the Machine Learning system were defined.
2)In WP3: a) lab scale units were constructed for all intelWATT’s processes (UltraFiltration, NanoFiltration, Reverse Osmosis, Reverse ElectroDialysis and Membrane Distillation). Additionally the smart monitoring concept was implemented and optimized in a large scale format.
3)In WP4: a) Graphene based ion exchange membranes, Artificial Water Channels NF and RO membranes, Hollow Fibers NF membranes, PVDF based MD membranes and UF-Membranes for pre-treatment were developed, upscaled and characterized and b) new hollow fibers MD and UF modules were designed and constructed.
4)In WP5(CS1) following the detailed P&ID phase, the pilot construction was initiated and completed within the specifications described in the DoA. The pilot was design and constructed by NI and NCSRD and commissioned in the premises of PPC’s power plant. Evaluation results of the pilot operation confirmed that the concept of >99% recovery of the CTBD is feasible within the set energy consumption threshold of 5 KWhe/m3. AI assisted pilot operation was also established while real time monitoring and remote control was available to the operators of the unit.
5) WP6 (CS2) pilot plant focuses on the integration of UF, RED and solar assisted MD. As conclusions, UF proved to be an effective pretreatment method for removing turbidity and particles achieving all the estimated KPIs. RED briefly achieved the target to produce 3MJ of renewable energy per m3 of brine, reaching its most important project objective. The objective of MD for production of 1m3/h of distilled water is achievable under certain circumstances related to the feed salinity and availability of thermal energy. Moreover, the quality of permeate remained excellent below 1 μS cm even at high salinity feeds.
6) WP7 (CS3) The system assessment focused on the recirculation of the regenerate and the evaluation of the relevant parameters. The analyses of the influencing factors resulted in recovery rates for water of between 70.6 % and 88.1 %. The system was thus able to successfully recover the components and regenerate a permeate that can be reused as rinsing water. For the recirculation of the regenerate, 10% and 30% of the recovered concentrate were added to the Cr(III) electrolyte. Results showed that a ratio of 10% concentrate to 90% electrolyte can be used without reducing product quality. Overall, this case study was very successful and the technology can be fully industrialized.
7)In WP8: advanced development and integration of the Artificial Intelligence system like the dashboard, the data lake, the AI algorithms, the sensors ingestion mechanism and the communication protocols were established and tested for the interconnectivity, smart monitoring and optimization of energy consumption and water production of the demo units.
8)In WP9: a) the Life Cycle Assessment Analysis referring to all CS was completed. A study focusing on industrial wastewater processing in water stressed areas proved the replicability of the proposed technologies. Finally, a health and safety assessment were conducted ensuring the harm-free nature of the intelWATT approaches for both humans and environment.
9) WP10 included: a) the set-up and constant update of project’s website and social media platforms, b) the preparation of the exploitation and dissemination registries, c) the preparation of the Plan for the Exploitation and Dissemination of the project’s results and d) networking and clustering actions, strong presence in workshops, conferences and trades as well as 20 journal publications. The exploitation potential of the R&I advancements during the project’s duration is strongly reflected in the Innovation Radar initiative where seven technologies are included, with two considered as market ready.
10)The development of a Quality assurance plan for the management and control of projects’ administrative and financial aspects as well as a constantly updated Data Management strategy. A risk monitoring registry has been the cornerstone for the progress monitoring and mitigation actions ensuring the best possible implementation of the project’s technical timeframe.
During the project implementation considerable progress was achieved in a wide spectrum of areas which will be continually improved and optimized to meet the objectives and ambition of this interdisciplinary project.
In brief, achievements that have been reached to this stage include
a)The implementation of smart monitoring design to all the processes aiming at a 30% reduction in energy demands.
b) Next generation of separation elements.
c) Novel approaches for the integration of machine learning in wastewater treatment
d)Development of smart sensors capable of detecting elements of interest
e)Development of cloud infrastructure and real time sensor data transmission
The adoption of intelWATT’s solutions is expected to tackle the water scarcity issue having obvious technological, social and environmental impacts. The increase of water reuse, the recovery of materials and the energy generation will have also a positive effect on the reduction of greenhouse gases emissions. Finally, the cutting edge breakthroughs introduced by the project regarding the water treatment processes will improve the competitive of the relevant European industrial sectors.
In brief, achievements that have been reached to this stage include
a)The implementation of smart monitoring design to all the processes aiming at a 30% reduction in energy demands.
b) Next generation of separation elements.
c) Novel approaches for the integration of machine learning in wastewater treatment
d)Development of smart sensors capable of detecting elements of interest
e)Development of cloud infrastructure and real time sensor data transmission
The adoption of intelWATT’s solutions is expected to tackle the water scarcity issue having obvious technological, social and environmental impacts. The increase of water reuse, the recovery of materials and the energy generation will have also a positive effect on the reduction of greenhouse gases emissions. Finally, the cutting edge breakthroughs introduced by the project regarding the water treatment processes will improve the competitive of the relevant European industrial sectors.