Brendan Walsh discusses its criticality, the water-energy nexus and the requirement for a value-added system, demonstrated using a manufacturing factory
Chem

Author: Brendan Walsh, chartered engineer and PhD candidate, under the tutorship of Dr Dominic O’Sullivan, UCC School of Engineering, http://www.ucc.ie/en/ierg/

Abstract


In order to further the progress towards industrial sustainability, a focus on improving critical areas has identified that water demand-side management and, by association, energy, requires attention.

The world’s current utilisation of water, allied to the forecasted increase in our dependence on it, has led to the realisation that water as a resource needs to be managed. The heavy dependence of energy generation on water and the similar dependence of water treatment and distribution on energy – collectively termed the water-energy nexus – is also critical.

While it is generally accepted that enhancements in water management are required worldwide, the relatively low apparent financial cost of water is inhibiting the essential changes. Motivating factors are necessary to enable the transformation and even though standards provide a framework to allow companies fulfil their corporate and social responsibilities, the cost savings associated with the necessary modifications do not alone provide adequate justification. The reason for this is that the true cost or true value of the water being used is not known.

In order to remedy this situation within industry, a novel framework for establishing the true cost of water, by analysing and simulating the value added, has been developed and is presently being applied to a typical manufacturing factory.

Background


Global water demand (in terms of water withdrawals), illustrated in Fig. 1, is projected to increase by 55 per cent by 2050, mainly because of the growing demands from manufacturing (400 per cent), thermal electricity generation (140 per cent) and domestic use (130 per cent).

As a result, freshwater availability will be increasingly strained over this time period, and more than 40 per cent of the global population is projected to be living in areas of severe water stress by 2050. There is also clear evidence that groundwater supplies are diminishing, with an estimated 20 per cent of the world’s aquifers being over-exploited, some critically so.

It is predicted that population growth will necessitate 60 per cent more food by 2050 and thus a 19 per cent increase in agricultural water use. Allied to this, the foods eaten by the people have a significant impact on water consumption. The increasing population in the middle class worldwide leads to more people choosing western-style diets, which are high in protein, sugar and fat, all of which are expensive in terms of water for food production.

The water consumed in the production of an agricultural or industrial product is termed ‘virtual water’. Every day a person drinks two to four litres of water, but they will also consume 2,000-5,000 litres of virtual water embedded in their daily food. There is a hidden cost of water in the food we eat.

Agriculture and food production use 24 per cent of abstracted supplies, with 17 per cent used for public water supply and 15 per cent for industry. Half of the water used for manufacturing goes to the chemicals sector and petrol refineries.

In parallel with addressing the sources of water supply, wastage through leakage needs to be minimised. The EU has stated that up to 50 per cent of water resources are being lost through leakage in water infrastructures and that the industry itself must play a major role in setting Sustainable Economic Leakage Levels (SELL).

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Figure 1: Water demand. (Note: OECD: Organisation for Economic Co-Operation and Development. BRIICS: Brazil, Russia, India, Indonesia, China, South Africa. ROW: Rest of the world).

Water conservation programmes within commercial/retail and domestic sectors have historically been successfully completed. Water utilisation in New York City declined from 806 litres per capita per day (lpcd) in 1980 to 481 lpcd in 2010, a drop of more than 40 per cent.

Furthermore, analysis of the supply cost of water in several countries, as outlined in Table 1, illustrates that it varies, however in industrial expenditure terms, it is consistently low.

In industry, water conservation investments provide a relatively low payback, which leads to difficulty with their justification.

In order to assist and encourage attention in all these areas, a system of assigning real or added value to water is required.

Water-energy nexus


Table 1: OECD estimates of prices for water by broad sector usage

Table 1: OECD estimates of prices for water by broad sector usage

On a worldwide basis, water, energy and food are considered as one nexus, with the water-energy link being a subset of that. Aspects of the nexus include the strong interdependencies between water and energy generation. The increased utilisation of both water and energy has had effects on climate change and subsequently on the environment.

Both are undergoing a rapidly growing demand worldwide, while also serving as resource constraints. Both are subject to regional quality variability, with fluctuations in supply and demand. Internationally, energy has been included in regulated markets for a long time, while water has been added more recently.

However, dissimilarities also exist, the most prominent being the relative cost of each, with the cost of exploration and treatment or generation, along with distribution and environmental taxes being allocated to energy, whereas water typically only incurs the significantly smaller abstraction, treatment and distribution costs. The business of energy is much greater than that of water and involves a correspondingly larger financial industry and consequentially, those involved in policy making are influenced by this fact.

Energy data is available for most countries worldwide, usually in a variety of formats, however there is considerably less water data available due to its non-existence and this is a significant factor in it not being prioritised at all levels – locally, nationally and globally.

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Figure 2: Energy requirement to deliver 1m3 water safe for human ingestion from various water sources. (excludes critical elements such as the distance the water is transported or the level of efficiency)

Any wastage of water has direct implications for energy wastage and improvements made in water systems have a direct impact on energy utilisation.

The energy required to deliver 1m3 of water safe for human ingestion from various water sources is illustrated in Fig. 2 and demonstrates several important facts. Firstly, the dependency on energy for purification is demonstrated. Secondly, the significant quantity of energy required for drinking water is apparent.

Thirdly, the difference in the relative quantities of energy required is dependent on the source of water and highlights the importance of the efficient utilisation of freshwater resources.

Also, local and regional impacts of biofuels could be substantial, as their production is among the most water intensive types of fuel production. The current focus on the shift towards electrically powered transport systems also has a significant impact due to the intensive water demands of the generation stations.

Water management


The carbon footprint of an organisation is defined as being the total of all the greenhouse gases caused by the organisation. Presently, companies calculate their carbon footprint and strive to improve it by reducing their emissions. In the not-so-distant future, companies are also expected to declare a water-footprint in a similar manner to the declaration of a carbon footprint presently.

This footprint will be applicable to products, processes and organisations and will be based on life cycle assessments (LCAs). It will be necessary to accurately quantify the water used in a verifiable and consistent manner. In order to facilitate this, a new international standard entitled ISO14046 Environmental Management: Water Footprint, was launched in July 2014.

Many multinationals now require measures of the quality and quantity of supply of energy and water. Some of the companies have already even commenced highlighting their water effectiveness measure by publishing real-time dashboards on the internet that display how their data centres are performing against these metrics.

Water footprint labelling is being introduced in certain countries and is expected to operate in a manner similar to carbon footprint labelling, thus increasing consumer awareness.

The European Union (EU) Energy Related Products Directive (ErP) replaces the original Eco-Design directive. The original directive covered equipment that directly used energy, whereas the new directive addresses products that are energy related as well as those that do not directly use energy, such as water consuming devices.

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Figure 3: Three phase model for Energy – Water demand reduction

The objective is an improvement in environmental considerations, resulting in the reduction of the consumption of resources such as energy and water at all stages of the life cycle, from the design stage, through manufacture, use and disposal. The CE mark thus indicates compliance with the ErP directive, along with the existing predominantly safety-related directives.

A three-phase model for the relationship between water demand and energy use is illustrated in Fig. 3, identifying the benefits to energy use obtained at different stages of water demand reduction.

Water management case history using ISO50001 Energy Management Systems


University College Cork is a case study of managing water by means of the Energy Management Standard ISO50001. The data over two calendar years since the introduction of the standard in 2011 was analysed. UCC was the first third level institution worldwide to achieve certification, along with being the first public sector body in Ireland to be certified.

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Figure 4: Water utilisation in UCC

The benefits of following the program were realised through the 18 per cent reduction in total annual usage, from 67,434 m3/year to 54,966 m3/year. This was achieved despite an increased level of activity within the facility. The average utilisation at similar times of the second year is lower than the first and the annualised trend is also decreasing within the second year, as illustrated in Fig. 4.

The solution: value-system modelling


At present, there is no standardised methodology or framework for the assignment of values to water utilities. Such a system, as proposed and developed by the author, would facilitate analysis through simulation of the situation regarding utilisation.

This would lead in due course to more efficient systems involving employment of water of an appropriate grade with reduced overall utilisation, reduced cost and improved environmental performance.

The necessary treatments which the water undergoes and the associated costs add value to each utility. The value-system facilitates simulation modelling, with the requirements of the facility formulating the outputs of the model.

Water value-system procedure


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Figure 5: Value-system methodology

The steps involved in setting up a value-system are illustrated in Fig. 5. The procedure commences with the initiation of the process.

The first activity to be undertaken is the development of a Plant Flow Diagram (PFD) for the facility. Many facilities do not have a complete PFD for their water systems. If exact paths or sources of water are not known, then the routes of pipes need to be determined and confirmed.

Once completed, the PFD should allow the identification of all the major water systems. The water systems nominated at this stage should be determined and designated by the use/application rather than the ultimate destination/disposal method.

The listing of water systems then forms the basis of the value-added (VA) table, as per Table 2, with one water system per row. The steps involved in the treatment and preparation of each of the water systems are then identified and listed as columns within the table. Variables representing the cost of that treatment, typically per unit volume, are assigned within the table where the treatment is relevant to this water system and left blank where not relevant.

In certain cases, the cost of the treatment is constant across all the water systems, in other cases the variable depends on the particular system. Typically all treatments are not apparent until illustrated on the PFD and subsequently outlined in the VA table.

The value of each of the variables is then determined. Considerable effort is required to establish all values as the data needs to be mined from several different sources, sometimes with partial data from several origins being combined to provide an overall perspective.

In most cases, a cost is initially established and then a flowrate of the water service determined during the time period within which the cost was incurred, with division of one by the other providing a cost/flow unit rate which is then used as the variable in the population of the table.

A simulation model is then developed using appropriate software. While all the mathematical operations are basic, the interconnectivity of all the data sources and sinks of a large facility may prove challenging. Typically, the primary desired output of the model is the Value-Added Factor (VAF) for the selected water system, which represents the calculated true added value as a multiple of the initial water supply cost.

An additional benefit of the model is that it facilitates the performance of simulations of different scenarios, ranging from fluctuations in energy or chemical prices, to the benefits of altering operational procedures.

Value-system application to a manufacturing facility


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Figure 6: PFD showing water flow through the manufacturing factory

A manufacturing factory, owned by a multinational, has been selected as a typical industrial water-consuming facility in order to discuss the application of the water value-system methodology. The PFD, illustrated in Fig. 6, was developed from a compilation of drawings, site inspections and interviews with operational personnel.

The complete value-system for the factory is presented in Table 2. Water utilisation within the factory has been deemed to be classifiable into nine different water utilities, each represented by a row in the table.

The activities within the factory which add value to the water are represented by the columns. This includes all life-cycle activities from when the water enters the factory to when it exits, including those before and after the utilisation of the water.

Selection of water system for case study


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Table 2: Overall Factory Water Systems Value Added Table

The de-ionised water (DIW) utilised by the facility is generated by a dedicated electrically powered, self-contained generation skid, using mains water as a raw material. The skid removes the presence of ions within the water and produces DIW along with a waste stream. The DIW is then used during the manufacturing process.

The DIW system was selected as a case study due to its potentially high value, distinctly identifiable applications and potentially modifiable utilisation pattern.

Mathematical Description of True Value of DIW System

Using the logic and notation described, the true value (€) of a volume V of Deionised Water di is given by equation (i):

DIW True Value (€)   =   Vdi*{M + (Pdi+Edi+Sdi+SMdi+Ddi) + (FWastedi/Vdi*L) +

(1-FWasteoffsitedi/Vdi)*(N+O)+(FWasteoffsitedi/Vdi*OC)}…..equation (i)

where:

Vdi is the volume of DIW for which the true value is being determined (m3), FWastedi is the Flow of DIW Waste which is treated in the Led Italia Srl (LED) waste separation unit (m3), FWasteoffsitedi is the Flow of DIW Waste which is treated offsite after the LED unit (m3), with all other variables as per Table 2.

Simulation software model


In order to simulate and analyse the water utilisation within the factory, it is necessary to select a suitable software system and model type. Simulink from Mathworks is proposed to be the most suitable, as it easily allows the visualisation and modification of the conceptual model being developed.

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Figure 7: Simulation model data flow for a manufacturing factory

Simulink utilises Matlab and is a model based package designed for simulation with customisable sets of building block suites. The interactive graphics allow visualisation of the data or signal flows and allows the user to import data from Excel.

The data flow of a typical simulation model is illustrated in Fig. 7. The model has two distinct but related functions: the first of which is to take all available raw data and convert it into a usable format. These are called manipulated value-added variables as listed in the VA table, typically a cost per unit flow for example €/m3. This is performed by accumulating all relevant raw data costs in the correct proportions and dividing by the relevant flowrates.

The second function of the model is to calculate the total added value of any individual water stream within the factory as requested by the user. This is performed by combining all the relevant value-added variables determined in the first function, to enable the value of any particular water system to be determined through the correct assignment and apportioning of costs incurred by that water system. The result from this calculation is also cost per unit volume.

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Figure 8: Section of simulation model showing DIW-associated water flows and associated costs

The DIW relevant section of the overall facility simulation model is illustrated in Fig. 8, showing the main inputs to the left and outputs to the right, relating to the DIW calculations. The primary output of concern for this application is the deionised water cost per unit volume, as described in equation (i).

Data collation


There are two forms of data used in the simulation model which may be categorised by origin, namely actual data mined directly from the facility’s operation, maintenance and monitoring systems and calculated data, generated based on a combination of available and estimated information.

In all cases, it is essential to identify and obtain the most critical data, as typically it becomes increasingly difficult to completely identify all data values and the diminishing returns received from the increased effort naturally terminates the process.

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Table 3: Data required for DIW section of model

The data requirements for the DIW section of the model along with a summary of the status of original availability of the data (calculated by value for costs), and the corresponding model descriptors is presented in Table 3.

Initial data from research and origin of costs for DIW


The required data has been collated and the model has been run, with results extracted, yielding a true value for the DIW system, however unfortunately they have been withheld from this publication as they are pending publication in a research journal.

However, the raw data may also be analysed so as to provide an insight into the cost origin of the system being researched. In order to review the data, it is first necessary to normalise it, as per groups of variables within equation (i), an operation performed by the software model as part of the functionality. Two separate operations are required.

Firstly the DIW system data is required per unit volume of utilised DIW, rather than total generated DIW, and in order to achieve this the raw variables Edi, SMdi and Ddi are divided by the utilised volume (F22-F23) instead of the generated volume (F22). Secondly the waste systems data is required to be apportioned as per the quantity of DIW being processed by that system as part of its overall processing volume.

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Figure 9: Detail of cost origins for DIW generation

The variables L and OC are factored by Fwastedi and the variables N and O are factored by (1-Fwasteoffsitedi). The resulting normalised variables provide a representative allocation of the source or origin of the costs which comprise the overall true cost or added value of a unit of DIW. Illustration of the normalised variables in Fig. 9 demonstrates the heretofore unrealised significance of certain contributory components, thus highlighting the benefit of the initial data collation phase.

Discussion of findings


Examination of the values for the cost origin variables in Fig. 9 readily allows the identification of the dominant inputs which are all direct consequences of installing and operating a DIW system and account for a combined total of 67 per cent. All three dominant variables have a simple linear relationship with the volume and hence will influence the overall total value in a linear manner if varied.

The remaining variables do not significantly influence the overall, however consideration needs to be given to the variables which are consumption dependent, as reduced consumption overall will increase the specific cost per volume.

The methodology implemented has been successful, nevertheless as per all analyses, it is restricted insofar as it generated the true value for the system considered, for the facility analysed, for the circumstances prevailing at the time and for the data available.

The determination and presentation of the origins of the cost of the DIW, in Fig. 9, assists in providing significant information relating to the operation of the facility. It also identifies the areas to be targeted in order to achieve cost savings.

Reduction of the expenditure on DIW is possible through influence on the inputs to the main variables identified or through a reduction in consumption. Interestingly the significance of the system depreciation and the inability to alter it is evident; it is a direct consequence of investment, thus highlighting the criticality of prudent selection and effective cost management of capital investment.

Fundamentally, the concept of assigning value to the water stream utilised, including disposal costs, could be disputed. The pre-treatment of the water is required by the product being manufactured and the disposal is as a result of the contamination caused by the product, however the water stream is being assigned the costs, rather than the product. Assigning costs to the product is also facilitated by the methodology and could be achieved if required.

Future research in this area shall include determination of Value Added Factors for other services and in other industries. The water services are typically very similar in each industry group. The critical high value, influentiable services should be prioritised and the information disseminated. The information may be used for remedial modifications of existing facilities or may also be used in the design and review of new installations.

Conclusions


Concerns regarding the future availability and cost of water have stimulated interest in the management of this valuable resource. The ‘EU Framework Programme for Research and Innovation research Horizon 2020’, which commenced in 2014, predicts €500 million per year EU public investment in water research in Europe.

As well as efficiency, other factors such as wastage through ageing distribution networks, conservation measures and wastewater treatment developments to facilitate recycling, also need to be considered.

Increasing energy demands are restricting future water planning measures, again emphasising the requirement for a comprehensive integrated approach from policy makers. In order to achieve a system closer to a functioning circular economy, there needs to be an increased focus on water. Water and energy efficiency need to be addressed simultaneously in a cohesive manner.

Data is required to perform all calculations, the extent of which is determined by the objectives of the study and the availability of which significantly influences the accuracy. Improved data availability in this area of industry is an evident requirement, which is being addressed. The methodology proposed, and hence the data requirements, may be applied to the critical water systems only if required.

Along with providing a particularly useful insight into the operation of the facility, which may be used for benchmarking and internal cost control, it also provides the data necessary to enable the financial justification of any changes required. The data may also be used as a component for the determination of a water footprint or a life-cycle cost for the factory or even a particular product. If the proposed methodology is implemented, changes will be possible and will result in water, energy and cost savings along with environmental benefits.

Using the model, the variables may also be modified and sensitivity/scenario analyses performed, thus enabling benefits to water and energy consumption, waste reduction and also operational efficiencies.

Ranges for value added factors can be compiled for all critical services in typical factories, thus effectively providing indicative true value costs without the requirement to perform the extensive data gathering and modelling.

The true value of water is an intelligent efficiency indicator to be used in water management. It may be used to contribute to water foot-printing, system/regulation compliance, product pricing strategy, facility benchmarking for smart manufacturing or even as a green taxation declaration.

The author would also like to acknowledge the support of the Irish Research Council under the Enterprise Partnership Scheme, in association with ENMS Ltd, along with the John Sisk Postgraduate Research Scholarship in Civil Engineering

http://www.engineersjournal.ie/wp-content/uploads/2016/03/aaacol1b.jpghttp://www.engineersjournal.ie/wp-content/uploads/2016/03/aaacol1b-300x300.jpgDavid O'RiordanChembiofuel,climate change,Cork,energy,UCC,water
Author: Brendan Walsh, chartered engineer and PhD candidate, under the tutorship of Dr Dominic O’Sullivan, UCC School of Engineering, http://www.ucc.ie/en/ierg/ Abstract In order to further the progress towards industrial sustainability, a focus on improving critical areas has identified that water demand-side management and, by association, energy, requires attention. The world’s current utilisation...