Implementation of the Water Footprint as a water performance indicator in industrial manufacturing units located in Greece: Challenges &amp; Prospects

doi:10.21203/rs.3.rs-2568685/v1

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Implementation of the Water Footprint as a water performance indicator in industrial manufacturing units located in Greece: Challenges & Prospects

https://doi.org/10.21203/rs.3.rs-2568685/v1

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published 29 Nov, 2023

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Global water resources are under great pressure, so sustainable water and wastewater management is essential for every industrial unit. The Water Footprint (WF) is a multidimensional indicator of volumetric water use and pollution and is applied throughout the production cycle from the supply chain to the end user. The state-of-the art method of calculating the direct (operational) WF requires detailed records of water consumption and wastewater production per process, that are usually not available. In order to effectively implement the indicator, modifications to the standard calculation method are usually necessary, to meet the requirements and characteristics of each production unit. The present study analyzes the modifications required for WF assessment in three production units in Greece (i.e., cement, brewery and natural cosmetics) for which the WF is calculated for each production process and for the whole unit The WF assessment performed for the three case studies showed that both water consumption rates and WFs are within the lowest values (4.7 hL water/hL beer for brewery case study and 0.155 L/kg cement for cement case study) of the ranges reported in the international literature (4-8.8 hL water/hL beer and 0.14–0.413 L/kg cement). The total WF of the brewery after applying mass balances was calculated at 23.8 hL water / hL beer with virtual Grey WF contributing at 79.7% and Blue WF at 20.3%. For the cement manufacturing unit, using estimations from the plant operators and data from international literature the total WF of the plant was assessed at 0.159 L / kg cement with Blue WF contributing at 95.8%, Green WF at 1% and virtual Grey WF at 3.2%. For the natural cosmetics unit, after modifying the system boundaries properly, the total WF was assessed at 81.6 L / kg bulk with virtual Grey WF contributing at 88.8%. Through WF assessment, strategic actions could be identified to reduce water consumption and a benchmark could be provided to assess water performance between companies of the same branch.

Water Footprint

sustainable water management

cement production

brewery

cosmetics

Water resources are under pressure worldwide due to groundwater aquifers’ over-pumping and wastewater discharges in water bodies. Sustainability of water resources is a sine-qua-non condition for any form of sustainable development, leading to the necessity to invent relevant indicators (indexes) and propose relevant management schemes (scenarios). At a regional scale, an assessment tool has been proposed to advance long-term water supply resilience and water resource stewardship (Water Foundation, 2019). In a corresponding reasoning, water resources sustainability index for water-stressed basins is proposed, evaluating and comparing water demand and supply for three water availability future scenarios. (Vieira and Sandoval-Solis 2018).

Industries are rapidly required to comply with the principles of sustainable development in order to rationally manage the natural resources they use. Large-scale industrial water use has made accessibility to safe and clean water difficult (Yusuf et al 2020). Water needs in industry, may account for as much as 80% of the total water withdrawal, in some highly developed countries. Major applications of industrial water use include thermoelectric power plants, manufacturing plants, ore and oil refineries and hydroelectric dams. Water is used in these industrial branches for cooling, dilution and chemical reaction purposes (Hossain 2019).

A set of clear strategies adopted by industrial organizations is crucial to set the objectives and guide change and transition towards circular economy of water (Morseletto 2020). Strategies focusing on water savings are therefore the main pathways leading to more sustainable use of water and constitute the categories to which the various solutions and applications can be traced back (Morseletto et al. 2022).

Some of these circular economy applications focusing of water could be water recycling, water reuse and industrial symbiosis through exchange water networks between industrial plants. The practice of partial or total water recycling and reusing can be applied to any type of industry. However, microbiological and physical–chemical analysis is essential before water reuse, due to chemical and biological contaminants carried by water/reclaimed wastewater (Bailone et al. 2022). On the other hand, water reuse applications can be restrained in some industrial branches e.g., food industry because of high water quality needs in processing.

Eco-Industrial Parks, designed on the concept of industrial symbiosis, are rapidly growing in numbers, found particularly in Asia and Europe (Aggeri, 2021). In these parks, water exchange networks are established between plants in order to minimize freshwater consumption and wastewater discharge by maximizing wastewater reuse (Aussel et al. 2023). The evaluation of circular economy practices towards water circularity in an industrial plant could be achieved through extensive monitoring and recording of water consumption and wastewater production in their production units, enabling strategic actions deployment to reduce water consumption and reuse treated wastewater within the unit. A number of tools (indicators) can be applied, to enable industries address their water-related sustainability targets, such as the Water footprint (WF) (Hoekstra et al. 2009), Blue Water Scarcity (BWS) and Water Pollution Level (WPL) indexes (Bai et al. 2018). Through WF assessment, water use and pollution in a plant can be evaluated in a single indicator, while BWS index highlights the pressure of plant’s operation to local water resources and WPL index indicates the level of pollution of local water resources from the plant’s operation. Both BWS and WPL are interconnected to WF, since blue WF and grey WF are used for the calculation of each index, respectively. In the context of WF assessments in industrial units, it is crucial to evaluate the impacts of water reuse within the production unit, on the water availability and water pollution in the region and catchment, where the plant is operating (Ene et al. 2013). Finally, the idea of a relative index comparing current water consumption with an estimated minimum achievable value has been proposed (Aldhudaithi et al 2022).

Despite the wide acceptance of WF as an indicator for sustainability, its current implementation in industry is very limited and there is still a need to clarify the procedures necessary to obtain pertinent data, where not available, and to assess the influence of consumptions during calculations on the values obtained.

The aim of the present article is to analyze the state-of-the-art methodology for calculating the Operational WF of industrial units and the adjustments / modifications required in the methodology so as to calculate it based on available data. Industries with high values of specific water consumption, i.e. L water / kg product, in Greece are the Food and Beverage (e.g., brewery) ranging from 1.7 to 5 L water / L product, Non-metallic Minerals sector (e.g., cement production) ranging from 0.14 to 0.326 L water / kg cement and Cosmetics. A brewery located in the River Basin EL0228, a cement manufacturing plant and a natural cosmetics production plant, both located in the River Basin (EL06) are used as Case Studies. The application of the WF in these units, with a very different profile of water consumption in their processes, is demonstrated, and the BWS is calculated for each one.

To achieve their sustainability targets, industries need to deploy assessment methods to evaluate their water use in terms of water availability and pollution of local water resources (Willet et al 2019). The interconnections between sustainability, industrial water use, and assessment methods is captured by the concept of ‘Sustainable Systems Indicators’ (SSIs) proposed by Veleva et al. (2001). The OECD classification of assessment methods (OECD, 2009) which is the most suitable since it is the closest to practice within industry, is comprised of six categories: 1) Key Performance Indicators, 2) Socially Responsible Investment Indices, 3) Composite Indices, 4) Material and Energy Flow Analysis, 5) Environmental Accounting, 6) Life Cycle Analysis. WF assessment falls into the category of Material and Energy Flow Analysis method, which has the largest percentage of use of SSI at 42% compared to the other methods. The underlying concepts of mass/energy balancing are suitable for SSIs because they can be used over any scale and can therefore be applied outside the immediate boundaries of the industrial system (Willet et al 2019).

Initially, WF was focused on crops and national consumption (Hoekstra and Hung 2002). Hoekstra and Chapagain (2007, 2008) improved the national WF accounts by considering all forms of consumption and trade, including animal and industrial products and municipal water uses. After 2008, the scope broadened, whereby also increasing attention on manufacturing within certain geographic areas expanded the WFs in the context of the limited water availability per area (Hoekstra 2017).

Water footprint in the context of sustainability assessment has been introduced through six widely recognised methods i.e., i) water footprint by Hoekstra (Chapagain & Hoekstra 2004); ii) ISO 14046 water footprint following an impact assessment approach with water input output analysis; iii) stress weighted approach by Brent (Brent 2004) comparing the use of different types of resources through a distance-to-target normalization, iv) swiss ecological scarcity method (Frischknecht et al. 2009) proposing a set of ‘eco-factors’ to assess freshwater resource use; v) life cycle inventory by Owens (Owens 2001) suggesting a set of indicators among different types of freshwater uses in terms of water quantity and quality ; vi) impact assessment of freshwater consumption according to Pfister et al. (2009) assessing freshwater consumption on midpoint and endpoint level, focusing only on freshwater consumption. All methods are based on the same water type concept proposed by Hoekstra et al (2009), which follows a volumetric approach (i.e., assessment of the volume of water associated with a particular production activity). This methodology could provide a baseline for inventorying water use data, however further differentiation is needed for impact assessment, customized to the characteristics and needs of the study area and the system boundaries (Sala et al. 2013).

Water footprint (WF), according to Hoektra et al (2009), is a multidimensional indicator of volumetric water use and pollution, measuring the amount of water used to produce goods and services. It can refer to a process, a product, an entire company, a sector, a community, even a nation. The WF of an industry is defined as the total volume of fresh water used, directly and indirectly, to produce its products and services. It consists of Operational WF, focusing on the industrial processes i.e. manufacturing & packaging, and of Supply Chain WF, focusing on the raw materials used in the production line (Gerbens-Leenes and Hoekstra 2008). Both direct and indirect water use are included in the indicator, representing water consumption and pollution throughout the full production cycle from the supply chain to the end-user (Hoekstra et al. 2009).

Despite the wide importance of WF as a water sustainability indicator in industry, very limited studies have been conducted to assess the indicator for industrial plants. The majority of scientific studies, corporate and international reports account and report water consumption and wastewater generation data and volumes. Therefore, they are mainly focused on water consumption and wastewater production data and rates in different industrial branches as well as some WF assessment studies available in international literature.

Water consumption for the manufacturing and power generation industries constitutes over 70% of total industrial water consumption in most European countries, mainly consumed for cooling purposes. Power generation industry has the largest water consumption ranging from 52.2% (Latvia) to 99.4% (Cyprus) of total industrial water needs. In most countries, petrochemical and chemical industries consume the largest amounts of water compared to other manufacturing industries and the average consumption ranges from 0.2 m³/inhabitant in Cyprus and Malta to 205.8 m³/inhabitant in Finland (Eurostat 2020).

Currently, water demand in manufacturing industries accounts for 22% of global freshwater withdrawal, and in some countries industrial water consumption exceeds water needs in agriculture (Sachidananda et al. 2020). Typical water consumption per inhabitant in EU countries for food & beverage industry ranges from 1.7 m³/inhabitant in to 15.8 m³/inhabitant, for textiles industry from 1.7 m³/inhabitant to 15.8 m³/inhabitant, for pulp and paper industry from 1.7 m3/inhabitant to 15.8 m3/inhabitant and for refined petroleum products, chemicals and chemical products ranges from 0.2 m³/inhabitant to 205.8 m³/inhabitant (Eurostat 2020).

Focusing on breweries, cement production and cosmetics units, which are characterized as water intense branches within the manufacturing industries, very limited studies on WF are available in literature, probably due to the restrained availability of data from industrial units (Hosseinian and Nezamoleslami 2018; Gerbens-Leenes et al. 2018). Nevertheless, many studies report water consumption and wastewater generation data for the selected branches, based on which a preliminary evaluation of water use can be performed.

Data on water consumption in the brewing processes retrieved from literature are reported in Table 1. Data for craft beer (Morgan et al. 2021) are not included, due to the brewery capacity, the non-inclusion of packaging process and the non-existence of filtration process. Beer is expressed to hL, a common measurement unit in the branch. Breweries consume large amount of water in their production processes, so proper monitoring and identification of water intense processes are crucial for the implementation of strategic actions for water savings. World Bank (2007) and the Government of Canada (Environment Canada 1997) propose that a water consumption rate of 4 to 6 hL water / hL beer is optimal for sustainable water consumption in breweries.

Table 1

Water consumption rates in beer production (normalized to hL water / hL beer, so as to be comparable)
Water Consumption Rates (hL water / hL beer)	Literature Source
4–10	Fillaudeau, Blanpain-Avet and Daufin 2005
4–10	Hannover 2002
4–11	Perry and De Villiers 2003
4.90–12.64	Kunze 2004
6	Taylor 2018
4.73	van der Merwe and Friend 2002
5–6	Perry and De Villiers 2003
5.5–8.8	Ramukhwatho et al. 2016

Concerning wastewater generation from breweries, limited data are available and are presented in Table 2.

Table 2

Wastewater consumption rates in beer production
Wastewater Production Rates (hL wastewater / hL beer)	Literature Source
1.3–1.8	Olajire 2012
1.9–11.50	Reed 2006
5.5–9.7	Briggs et al. 2004

For cement production industry, two WF assessment studies are available, estimating both direct (production processes) and virtual (energy consumption and transportation) WF. According to Hosseinian and Nezamoleslami (2018) the direct operational WF was estimated at 0.17 L / kg cement and the virtual WF at 1.95 L / kg cement for a plant in Iran. Gerbens-Leenes et al. (2018) estimated the WF of cement using data from the Ecoinvent database, resulting to 0.68 L / kg cement for the total operational blue WF of Portland cement, higher than both the above value and the average of Table 3, and to 210 L / kg cement for grey WF, counting for mercury as a primary pollutant. Finally, in many corporate sustainability reports and research articles, water consumption rates reported for cement manufacturing plants range from 0.14 to 1.28 L / kg cement (Table 3).

Table 3

Water consumption rates in cement production (normalized to L / kg cement)
Water Consumption Rates (L water / kg cement)	Literature Source
0.229, 0.232	Cemex (2019, 2018)
0.17, 0.14, 0.24, 0.260	Lafarge (2019, 2018, 2012)
0.267	Heidelberg Cement (2019).
0.36	China Resources Cement (2019)
0.264, 0.274, 0.413, 0.408	Cement Argos (2019, 2018, 2017, 2016)
0.185, 0.281, 0.260, 0.3, 0.360	Holcim (2014, 2013, 2012, 2010)
0.521, 1.028, 0.537	Marceau et al. (2006)
0.195	Hydraulic Binder Industries Union (2002).

Cosmetics can be divided into two main categories; synthetic cosmetics, in which ingredients have been developed in a lab, and natural cosmetics, which contain at least 95% of natural ingredients. Water is the main ingredient of most cosmetics products and usually water is the main ingredient, accounting for more than 2/3 of the volume of a formula (Cosmetics Business 2019).

Cosmetics industries are already investing on water sustainability in the manufacturing and end-use phases of their products. L'Oréal achieved 60% reduction of water consumption in 2020, compared to 2005, and enabled consumers to reduce water consumption by 25% when using the product, compared to 2016, through changing the formulas to optimize water consumption and recycling and reuse application within the manufacturing sites (L'Oréal 2019, 2020). Also, Unilever reduced the WF of its products by 47% the last 10 years, investing also in new hair products that could save 460 l of water per bottle of conditioner (Unilever 2020).

Concerning natural cosmetics, only one WF assessment study is available, estimating both direct WF from the production processes and virtual WF from energy consumption and transportation (Francke and Castro 2013). Blue, Green and Grey WF were assessed for the whole product cycle, from the supply chain to the end user, for a 450g Macadamia soap, with data from Ecoinvent being combined with real water consumption measurements. Many studies have been conducted showcasing sustainability practices, nevertheless neither water consumption and wastewater generation data nor metrics for natural cosmetics plants are available, only tendencies in water use between the years (Bom et al. 2019; Kolling et al. 2022; Secchi et al. 2016; Aguiar et al. 2022).

3.1. Water Footprint state-of-the-art methodology

Both Operational and Supply Chain WF are comprised of three components, blue, green and grey. Blue and green are related to the origin and use of water, while grey is related to water pollution (Hoekstra et al. 2009).

Βlue WF represents the amount of fresh water consumed, evaporated or incorporated into the product, given by the following equation (Hoekstra et al. 2009):

$${WF}_{blue}=BlueWaterEvaporation+BlueWaterIncorporation \left[volume\right] \left(1\right)$$

Water recycled within the unit is not accounted in Βlue WF calculation.

Green WF refers to rainwater collected and used in the production process or in other applications within the unit, such as cleaning and irrigation, given by the following equation (Hoekstra et al. 2009):

$${WF}_{green}=GreenWaterEvaporation+GreenWaterIncorporation \left[volume\right] \left(2\right)$$

Grey WF is an indicator of the degree of freshwater pollution from wastewater discharges and is given by the following equation (Hoekstra et al. 2009):

$${WF}_{grey}=\frac{Effl\times ({C}_{effl}-{C}_{nat})}{{C}_{max}-{C}_{nat}} \left[volume\right] \left(3\right)$$

Effl: volumetric flow of the wastewater outlet (L)

C_effl: concentration of the pollutant in wastewater outflow (mg/L)

C_nat: concentration of the pollutant in the recipient water body (mg/L)

C_max: maximum concentration of pollutant for discharge according to national legislation (mg/L)

The present study focuses on the estimation and analysis of the operational WF of three industrial units in Greece. A stepwise methodology is followed for the WF assessment as proposed by Gerbens-Leenes and Hoekstra (2008) and is presented below. Additionally, water intense processes and internal water recycling practices, leading to water savings, are identified.

An additional step is added in order to assess the BWS of each unit, since these are located in different areas. The BWS index is the ratio of total blue WF to available blue water resources, indicating the pressure of plants’ operation to local water resources (Hoekstra et al. 2009).

$$BWS=\frac{Total Blue WF \left[volume\right]}{Available water resources \left[volume\right]} \left(4\right)$$

The index value could classify the contribution of the plant to water scarcity as low (BWS < 1.0), moderate (BWS = 1.0-1.5), significant (BWS = 1.5-2.0) and severe (BWS > 2.0) (Bai et al. 2018). The BWS Index calculation gives an added value to WF assessment since the pressure on the local water resources by the unit is quantified and evaluated.

Metrics of water scarcity and stress have evolved over the last three decades from simple threshold indicators to holistic measures characterizing human environments and freshwater sustainability. Water scarcity could be also expressed as the ratio or percentage of total annual withdrawals of a region to the annual (renewable) resources estimated by mean annual river runoff (Withdrawal-to-availability ratio indicator) or as the number of people that compete to be sustained by a single flow unit of water—defined as 10⁶ m³ year^− 1 (Water Scarcity index indicator) (Damkjaer and Taylor 2017).

3.2. Standard procedure for WF estimation of an industrial unit

For the implementation and assessment of the WF indicator in industry, three industrial production units of different branches in Greece with various profiles of water consumption and wastewater management were selected: beer production, cement production and natural cosmetics manufacturing. The brewery operates continuously (24 hours a day, 7 days a week) producing eight types of beer by changing the dilution levels in filtering process, temperature and hops concentration. The cement manufacturing plant operates also continuously, producing two types of cement i.e., portland and synthetic cement, while the natural cosmetics plant operates for 16 hours a day, 5 days a week and in batch mode production, since the available vessels are used for the production of all types of products depending on the production schedule of the plant. Their water uses differ significantly: the cement plant consumes significant amounts of water to cool the mechanical equipment, in the beer production unit water is incorporated into the final product and the main water-intense process is the cleaning of the production and packaging processes (Clean in Place - CIP), and in the natural cosmetics industry a great proportion of the final product is comprised of water and large water amounts are used for equipment cleaning, due to the use of the same equipment for the different batches.

The procedure proposed by Gerbens- Leenes and Hoekstra (2008) includes the following steps:

Step 1: System boundaries – Units & Processes included in the assessment

The units and processes from which the industry is comprised are described and the annual water inputs and wastewater outputs are determined. Units are selected in such way that they are small enough, placed in one place and each to produce a homogeneous product.

Step 2: Calculation of the Operational WF of each process / unit

The WF of each process or group of processes is estimated, using the following equation:

$$WF\left[i\right]={WF}_{blue}\left[i\right]+{WF}_{green}\left[i\right]+ {WF}_{grey}\left[i\right] \left[annual volume\right] \left(5\right)$$

For the estimation of the blue WF, primary data on freshwater consumption per process are needed from the industry. Also, for the green WF calculation, data on the rainwater consumed in the process are necessary. For the calculation of the grey WF, the values of pollutants’ concentration in wastewater are needed, as well as their discharge permits to the recipient body, in accordance with the national legislation. For all the three case studies, a Grey WF is calculated, as wastewater (treated within the plants) undergoes further treatment in offsite Wastewater Treatment Plants (WWTPs), prior its discharge in a water body. Also, Grey WF is calculated for the whole units and not per process, due to data availability. For the three case studies, Grey WF is estimated based on the most common wastewater pollutant. Following Eq. (3), we choose to analyse the worst case scenario in terms of pollutant’s concentration and wastewater receiving body, which is assumed to be surface water. The most common pollutant in all three case studies is COD. However, COD concentrations are not recorded for surface waters in Greece, so Grey WFs will be assessed for BOD, as they both measure the amount of organic compounds in water. BOD concentration in surface water (C_nat) of EL06 is 3.95 mg/L and of EL02 is 2.80 mg/L (Greek Ministry of the Environment and Energy 2022). Also, C_max of BOD is 25 mg/L based on the Greek legislation for wastewater discharges in surface water bodies.

Step 3: Calculation of the total Operational WF of the industry

The sum of the operational WFs of each process constitutes the total operational WF of the industry.

$$WFtotal=\sum _{i=1}^{x}\left(BWF\left[i\right]\right) \left(6\right)$$

Step 4: Calculation of the BWS index

For the estimation of the BWS, water resources availability data were retrieved from the River Basins Management Plans of the areas where the plants are located (Greek Ministry of the Environment and Energy 2017) and Stathatou (2017).

3.2. Analysis of the Case Studies

The state-of-the-art method of calculating the operational WF requires detailed records of water consumption and wastewater generation per process that are usually not available from the industries, so adjustments and modifications to the standard calculation method are required on a case-by-case basis (Bai et al. 2018). Such adjustments can be achieved through the use of data from the literature, logical assumptions based on process characteristics and unit operators’ estimates as well as mass balances to calculate water consumption and wastewater production in processes.

3.2.1. Case Study 1: Brewery

The production processes as well as the water consumption inputs and wastewater generation spots in the unit are shown in Fig. 1. Also, water is consumed in the offices.

In the unit, the main freshwater source is the public water supply network and, in case of additional water demand, groundwater is consumed. Freshwater and groundwater undergo intensive treatment (Activated Carbon Filtration, Reverse Osmosis, Deaeration) before entering the production processes, due to the very high water quality standards for breweries (Directive 98/83/EC). Eight distinct water streams are produced with different qualities. In Table 4, all streams and their uses are presented alongside with the treatment they undergo; Water Treatment is not included in Fig. 1, as it is extensive with many processes involved. Water losses in the Water Treatment unit are estimated at about 0–1% of the total water inflow.

Table 4

Water streams in the unit
No	Water Stream	Treatment	Use
1	Raw water	-	Firefighting, Malting
2	Filtered water	Sand filtration	CIP, Pushwater, Offices
3	Filtered water Dechlorinated (FWDE)	Sandfiltration, Activated carbon filtration	Production of Mashing water and Lautering water
4	Service water Dechlorinated (SWDE)	Sandfiltration, Activated carbon filtration, Precoat filters, Cuno filters, Reverse osmosis, Deaeration	CIP, Pushwater, Hot brewing water, Cold brewing water
5	Soft water	Sandfiltration, Activated carbon filtration, Precoat filters, Cuno filters, Reverse osmosis, Deaeration	Filtering, Boiler room
6	Service water Chlorinated (SWCH)	Sandfiltration, Activated carbon filtration, Chlorination	Packaging, Engine room, CIP
7	Mashing water (45^οC)	Produced from mixing of FWDE with hot brewing water (85^οC)
8	Lautering / Sparging water (70^οC)	Produced from mixing of FWDE with hot brewing water (85^οC)

In the Cellars / Beer unit and specifically in the Wort Production subunit, FWDE is consumed in Mashing and Lautering, SWED for cleaning Mashing, Lautering, Boiling and Whirlpooling processes and SWDE for Wort Cooling in the heat exchanger. From the cleaning, wastewater is produced and directed to the WWTP of the unit. In addition, within the unit, soft water is used in Filtering process for beer dilution. SWDE is also used for cleaning in all processes of the unit i.e., Fermentation/Maturation/Filtration, producing wastewater. In the Packaging unit, SWCH is utilized for the cleaning of bottles, cans and kegs and in the water baths of Pasteurization. Also, SWCH for cleaning purposes is consumed in cleaning of the fillers. Wastewater in Packaging is generated from the cleaning of the bottles, cans and kegs, cleaning of the fillers and from the baths of Pasteurization.

In the brewery, surface and groundwater is consumed in the production unit and wastewater is generated, so only Blue and Grey WF are calculated. Wastewater undergoes primary, secondary and tertiary treatment to reduce its load, and then is directed for further treatment in the WWTP of the local Industrial Αrea, so a theoretical Grey WF can be calculated based on the outflow of the unit.

The WF of each process is calculated, using water consumption data (hL water / hL beer) provided by the Brewery. However, water consumption and wastewater production are not recorded in each single process, so proper adjustments are needed.

The WF estimation was performed for 2017, 2018 and 2019 and the data used for the estimation, provided by the industry, are the following:

Monthly water volume consumptions, in m³ or hL, retrieved from the water metering network (water meters are placed in most production process);
Capacity of the unit in terms of packaged beer and finished product in volume units (hL);
Records of average monthly COD concentrations in the WWTP outlet;
Treated wastewater outflows during winter and summer period;
Since Mashing water is not measured directly, it is derived from mixing 96.5% of total FWDE (measured), with a measured quantity of hot brewing water. The mixing ratio is considered constant;
Lautering / Sparging water is not measured directly and is derived from mixing 96.5% of total FWDE (measured) with a measured quantity of hot brewing water. The mixing ratio is considered constant;
Steam recovery and recondensation in the Boiler Room is achieved at 80%.

The adjustments applied in the Brewery Case Study are the following:

Use of mass balance equations to calculate the volume of water and wastewater in the water pretreatment unit as well as for water losses;

The assumptions needed for WF estimation follow:

Brewery wastewater usually has high BOD due to the presence of organic components (Amenorfenyo et al. 2019). COD concentrations are related to BOD using the BOD: COD ratio of 0.6 for brewery wastewater (Brewers Association 2015)
Based on Gerbens-Leenes and Hoekstra (2008), the WF of a process is zero, when water is recycled after its use in the process. Therefore, WF of Wort cooling is zero, as cold brewing water, after receiving the heat of the wort in the heat exchanger, returns to the hot brewing water tank and is reused as hot brewing water.

The operational WFs are summed and the outcomes are presented in the Results Section. For the calculation of BWS Index, the total Blue WF of the plant from Step 3 is needed as well as the available blue water resources in the area where the plant is located. The available renewable water resources (surface and ground water) of the basin EL0228 are at 924 million m³ per year (Greek Ministry of the Environment & Energy, 2017).

3.2.2. Case Study 2: Cement manufacturing plant

The production processes as well as the water consumption inputs and wastewater generation spots in the cement production plant are shown in Fig. 2. Also, water is consumed for wetting and cleaning of the roads within the unit and the transportation trucks for dust reduction, which is accounted in the wetting of raw materials process, and water is also consumed in the offices.

The plant uses mainly groundwater and limited quantities of rainwater, to cover production needs, and freshwater for personnel needs. Rainwater is collected in a tank within the plant and used for wetting of the raw materials and the roads as well as for additional cooling of the processes. In the Preparation of the raw materials, a combination of rainwater and freshwater is used for wetting of the raw materials to eliminate dust, and groundwater water is also used for external cooling of the coal mill. In the Clinker production phase, groundwater is mainly consumed for spraying of the bag filters of the rotary kiln, and the same applies for clinker cooling bag filters in the Cement production. In the Cement production stage, groundwater water is also used for external cooling of the mill in the clinker grinding process. The cooling of the mechanical equipment of all manufacturing processes (i.e., crushing, pre-homogenization, grinding, homogenization, flour preheating, rotary kiln, clinker cooling and clinker grinding) is achieved through a closed-loop cooling system with recycled water, so the WF of the cooling of the mechanical equipment is zero. In the cement manufacturing plant, wastewater is mainly produced by the runoff of wetting of raw materials and cleaning of the roads and trucks. Also, municipal wastewater is produced from the offices. Both streams of wastewater are directed to an offsite WWTP.

The WF estimation was performed for 2016, 2017, 2018 and 2019 and the data used for the estimation, provided by the Industry, are the following:

Yearly volumes of groundwater, rainwater and municipal water consumed, in m³, retrieved from the water metering network;
Records of volumes of water consumed in the processes, for dust control, for cooling, in the offices and the water losses of the unit;
Capacity of the unit in terms of tonnes of cement produced;
Wastewater production per year in m³.

The assumptions needed for WF estimation follow:

Based on industry’s estimations, the distribution of the total process water is 60% in the bag filters’ spraying of the rotary kiln, 10% in the bag filters’ spraying of the clinker cooling, 20% in the cooling of the cement mill and 10% in the coal mill cooling;
Water losses are due only to evaporation phenomena, in processes in which the temperature is above 150 ^oC and their distribution corresponds to the distribution of process water;
Grey WF of wetting of raw materials process is not estimated due to data limitations.
For the estimation of the wastewater volume from the offices, an assumption of 50 L of wastewater per employee and day (Asano et al. 2007) is used and the number of workers in the plant (i.e., 156 workers). The effluent volumes are assumed to be constant as they are calculated based on the number of workers in the plant, assumed to be constant.
COD concentrations in wastewater from the offices are not available, so typical values from the literature are used (176–238 mg/L) (Va et al. 2018). COD concentrations are related to BOD using the BOD: COD ratio of 0.4 for municipal wastewater (Henze and Comeau 2022).

The operational WFs of the processes are summed and the outcomes are presented in the Results Section. For the calculation of BWS Index, the total Blue WF of the plant from Step 3 is needed as well as the available blue water resources in the area where the plant is located. The available renewable water resources (surface and ground water) of the basin EL06 are at 490 million m³ per year (Stathatou 2017).

3.2.3. Case Study 3: Natural cosmetics production plant

The production processes as well as the water consumption inputs and wastewater generation spots are presented in Fig. 3. Water is also consumed in irrigation of the plants and in the offices.

In the plant, freshwater is used for cleaning of the equipment (production vessels and packaging pumps) and to cover personnel needs. Also, the plant includes a water pretreatment unit using a double-pass Reverse Osmosis (RO) system. After the first pass, part of the permeate is directed to the Boiler room, to produce hot water for cleaning of the Packaging Fillers and steam for the jackets of the Production Vessels. After the second pass, ultrapure water is produced for bulk production and cleaning of the vessels. Production vessels are cleaned firstly with freshwater and then with ultrapure water after the production of each bulk. Also, rainwater is collected and mixed with the condensate from RO system and used for irrigation within the plant.

The natural cosmetics manufacturing unit is comprised of 6 separate mixing tanks with agitators and jackets and 5 packaging units, one for each product category (i.e., lipstick, bottles, cream jars, sackets and samples, tubes). Water is an essential ingredient for the final products, so ultrapure water is embedded in the product. Also, substantial freshwater and ultrapure water quantities are used for cleaning of the production tanks and packaging equipment (i.e., fillers, pumps). Wastewater is produced from cleaning operations and from the offices and undergoes primary and biological treatment to reduce its organic load and then it is directed for further treatment in an offsite WWTP.

The WF estimation was performed for 2020 and 2021 and the data used for the estimation, provided by the industry, are the following:

Monthly water volume consumptions, in m³ or L, retrieved from the water metering network;
Capacity of the unit in terms of final bulk produced (kg);
Records of average monthly COD concentrations in the onsite Wwtp outflow for 2020 and 2021;
Monthly outflow records of treated wastewater (m³).

Rainwater is not measured and it cannot be quantified through assumptions or mass balances, so Green WF could not be estimated.

The modifications in the initial methodology needed for the Natural Cosmetics Case study are the following:

Based on the available data, the unit boundaries for WF estimation needed to be adjusted as follows:
- WF of production; i.e., ultrapure water used in the production mixing vessels including ultrapure water stream for cleaning
- WF of cleaning of production processes & packaging units; i.e., freshwater used for cleaning the vessels and the packaging equipment
- WF of irrigation; i.e., water used for irrigation of the plants within the unit
- WF of offices.

The assumptions needed for WF estimation follow:

Grey WF is calculated for BOD based on COD values that the plant monitors in wastewater. COD concentrations are related to BOD using the BOD: COD ratio of 0.496 for cosmetics wastewater (Lima et al. 2022).

For the calculation of BWS Index, the total Blue WF of the plant is needed as well as the available blue water resources in the area where the plant is located, the River basin EL06.

4.1. Brewery Case Study Results

The unit consumes only freshwater for the production processes, so the blue WF of each process was estimated as well as the total grey WF of the plant. The blue WF of the distinct processes and utilities are calculated and the results are presented in the following Table 5.

Table 5

Blue WF (hL water / hL beer) of each process
Unit / Process	Blue WF 2017	Blue WF 2018	Blue WF 2019	3 years’ average Contribution to the total BLUE WF
Water Treatment unit	0.00127	0.0569	0.0168	0.531%
Malting	0.457	0.441	0.346	8.82%
Beer Production
Wort Production
Mashing	0.431	0.398	0.466	9.18%
Lautering	0.542	0.553	0.515	11.4%
Cellars
Filtering	0.433	0.386	0.426	8.83%
Beer Production CIPs	1.15	1.14	1.19	24.6%
Packaging
Fillers	0.506	0.285	0.274	7.55%
Pasteurization baths	0.230	0.288	0.217	5.22%
Packaging CIP & Washes	0.608	0.878	0.721	15.6%
Engine Room	0.131	0.110	0.0651	2.17%
Boiler Room	0.124	0.104	0.0759	2.16%
Utilities
Fire fighting	0.0976	0.130	0.0723	2.12%
Logistics	0.0215	0.011	0.0101	0.304%
Canteen	0.00473	0.006	0.00455	0.105%
Irrigation of plants	0.0536	0.115	0.0172	1.31%
TOTAL BLUE WF (hL water/hL beer)	4.79	4.90	4.41

The largest contribution to the total Blue WF has the Beer Production Unit (54.0%) followed by the Packaging Unit (28.4%) and Malting (8.82%) (Fig. 4). By analyzing the WF of each process of the Beer Production Unit, almost 50% of the WF of the unit derives from Beer Production CIPs and Lautering process follows with 21.1% contribution to the units’ WF (Fig. 5). Therefore, water savings actions (e.g., water recycling) could be targeted on these two processes.

As mentioned in Section 3.3., the WF of Wort cooling is zero since cold brewing water, leaving the heat exchanger, returns to the hot brewing water tank and is reused as hot brewing water. By applying this water saving practice, the plant saves up to 122,000 m³ of water per year. Also, by recovering 80% of the steam in the boiler room the plant reduces its WF by 26–28%.

The total Grey WF of the plant ranges from 18.6 to 18.8 hL water / hL beer for the 3 years of the study, with CIPs contributing to the Grey WF by 66%. It is noted that the calculated Grey WF is not the actual Grey WF of the plant, as wastewater undergoes further treatment in the WWTP of the Industrial area.

The Total WF of the plant is 23.9 hL water / hL beer for 2017, 24.1 for 2018 and 23.3 for 2019 with an average contribution of Grey WF at 79.7% and Blue WF at 20.3%. The Total WF is lower in 2019 compared to 2018 and 2017, due to the reduction of water consumption in the Packaging unit, the Boiler room, the Engine room and the Utilities.

The BWS Index of the plant is estimated at 0.72 × 10^− 3 for 2017, 0.75 × 10^− 3 for 2018 and 0.67 × 10^− 3 for 2019, which is expected because of the size of the manufacturing unit. In all three years, the BWS Index is below 1.0, so the plants’ contribution to water scarcity is low. Also, comparing water consumption within the plant with literature, it can be concluded that water consumption is similar to rates in other units worldwide and within the range proposed for sustainable water consumption in breweries (World Bank 2007; Environment Canada 1997).

4.2. Cement Manufacturing Case Study Results

For the cement manufacturing case study, ground water and rainwater are consumed, so blue and green WFs were assessed as well as the total grey WF of the plant. The blue WF of each manufacturing process is presented in the following Table 6.

Table 6

Blue WF (L water / kg cement) of each cement manufacturing process
Process	Blue WF 2016	Blue WF 2017	Blue WF 2018	Blue WF 2019	4 years’ average contribution to the total BLUE WF
Rotary Kiln	0.0740	0.0800	0.0820	0.0760	51.1%
Clinker cooling	0.0120	0.0130	0.0140	0.0130	8.5%
Cement grinding	0.0250	0.0270	0.0270	0.0250	17.0%
Coal mill cooling	0.0120	0.0130	0.0140	0.0130	8.5%
Wetting of raw materials / Dust control	0.0220	0.0270	0.0190	0.0190	14.3%
Offices	0.72 × 10^− 3	0.71 × 10^− 3	0.71 × 10^− 3	1.21 × 10^− 3	0.5%
TOTAL BLUE WF	0.146	0.161	0.157	0.147

In Fig. 6, the contribution of each process to the total blue WF is presented for each year of the study. The largest contribution to the total Blue WF has the spraying of the rotary kiln bag filters (51.1%), followed by the cooling of the cement grinding process (17.0%) and wetting for dust control (14.3%) Therefore, water savings actions (e.g., water recycling, wastewater reuse) should target these three processes, which do not require high water quality.

Wetting of raw materials / Dust control has also green WF, which is assessed at 1.92 × 10^− 3 L / kg cement for all four years as rainwater consumption is assumed constant. The Grey WF of the Offices is estimated for all four years at 4.74 × 10^− 3 L / kg cement. The contribution of Blue and Grey WF to the total WF of the Offices is presented in Fig. 7.

The total WF of the plant is assessed at 0.152 L / kg cement for 2016, 0.167 for 2017, 0.163 for 2018 and 0.154 for 2019. Blue WF is contributing by 95.8% to the total WF, Grey WF follows with 3.2% (4years’ average) contribution and Green WF with 1%. The BWS Index of the plant is estimated at 0.82 × 10^− 3 for 2016, 0.93 × 10^− 3 for 2017, 0.88 × 10^− 3 for 2018 and 0.82 × 10^− 3 for 2019. In all three years, the BWS Index is below 1.0, so the plants’ contribution to regional water scarcity is low.

Comparing the results to the findings of the international literature, the total WF of the plant in the current study is very close to the total WF of production estimated by Hosseinian and Nezamoleslami (2018) (0.17 L / kg cement), derived through the total water consumption and wastewater generation of the plant and not by adding the WF of each process. Concerning water consumption rates (i.e., L / kg cement) in cement manufacturing plants, the plant seems to have similar water consumption rates to other plants found in the literature with relative low rates (i.e., 0.14–0.16 L / kg cement) of water consumption. On the other hand, Gerbens-Leenes et al. (2018), where data from the Ecoinvent database are used, estimate much higher Blue and Grey WFs.

4.3. Natural Cosmetics Case Study Results

For the natural cosmetics case study, the blue WF of each process is presented in the following Table 7.

Table 7

Blue WF (L water / kg bulk) of each production process
Process	Blue WF 2020	Blue WF 2021	2 years’ average contribution to the total BLUE WF
Production vessels	6.06	6.91	71.7%
Cleaning of production processes & packaging units	0.38	0.56	5.2%
Offices	2.45	1.72	23.1%
TOTAL BLUE WF	8.89	9.19

In Fig. 8, the contribution of each process to the total blue WF is presented for each year of the study. The largest contribution to the total Blue WF is resulting from the Production vessels, as ultrapure water is used for bulk production and cleaning of the vessels (71.7%), followed by the WF of the Offices (23.1%) and the Cleaning of production processes and packaging units with freshwater and hot water (60^οC) (5.2%) (Fig. 8). The total WF of the plant is assessed at 90.9 L / kg bulk for 2020 and 72.2 L / kg bulk for 2021. Grey WF is contributing with 88.8% to the total WF, followed by Blue WF at 11.3% (Fig. 9). The values of the total WF are very large due to i) increased Grey WF mainly because of high concentrations of COD in wastewater and ii) limited water recycling practices within the plant. For both years, the BWS Index is below 1.0, so the plants’ contribution to regional water scarcity is low.

Industries are rapidly required to comply with the principles of sustainable development in order to rationally manage the natural resources they use. Water needs in industry may account for as much as 80% of the total water withdrawal, in some highly developed countries, therefore circular economy applications uptake is prominent. The evaluation of circular economy practices towards water circularity in an industrial plant could be achieved through extensive monitoring and recording of water consumption and wastewater production. The WF assessment is an effective tool enabling industries depict their water consumption and wastewater generation trigger points and address their water-related sustainability targets. Despite the wide importance of WF as water sustainability indicator in industry, very limited studies have been conducted to assess the indicator for industrial plants. Also, the limited WF assessment studies published, evaluate the WF of the total plant and do not follow a per process approach.

The literature review also showcases that most industries do not assess water consumption and wastewater generation in every single manufacturing process, condition that is also confirmed in the present study, where water and wastewater volumes are not monitored systematically, while data are recorded on annual or monthly basis, with relatively low level of analysis. Consequently, adjustments and assumptions were necessary to overcome the lack of data, through the application of mass balances for missing water meters, use of real measured data reported in international literature for manufacturing plants using similar production processes, without knowing possible differences in the production lines, and estimations given by the operators of each process in the plants. As evidenced by literature, in WF assessment studies, a similar approach is followed, using data from either international literature to overcome missing data (Francke and Castro 2013) or from life cycle inventory databases e.g., Ecoinvent (Gerbens-Leenes et al. 2018). However, eventually, using data and models from databases leads to inaccurate assessments of both Blue and Grey WF, since these are not necessarily customized to the case-to-case processes and do not use real water consumption and wastewater production measurements. To this end, WF assessment would be best performed per process using raw data from the industrial plants. On the other hand, studies performed with real data could serve to enrich existing databases and therefore lead to more accurate assessments.

The WF assessment performed for the three case studies showed that both water consumption rates and WFs are within the lowest values (4.7 hL water/hL beer for brewery case study and 0.155 L/kg cement for cement case study) of the ranges reported in the international literature (4-8.8 hL water/hL beer and 0.14–0.413 L/kg cement) and the trend of water consumption of each process is relatively constant between the years of the assessment. Also, the existing water saving practices (e.g., water recycling in the heat exchanger, recycled closed loop for mechanical cooling, steam recondensation) reduce WF by about 40%, as processes where water is recycled do not contribute to WF. Additional suggestions for WF reduction could be the use of rainwater for fillers washing, cleaning of the floor and common areas and in the utilities for the brewery, reuse of treated wastewater in cooling for the cement plant and recondensation of steam in the cosmetics plant.

In addition to the importance of the WF as a water stress indicator of a production unit, it could also support sustainability reporting and provide a benchmark for companies of the same branch to compare their practices in terms of water sustainability. Also, WF could be the key to water efficiency labelling in consumer products (Simeonidou and Vagiona 2018; Nydrioti and Grigoropoulou 2022) as it could give consumers a quantified measurement of water consumption during manufacturing, leading them to choose products with lower water usage.

Acknowledgements

The authors would like to thank the brewery, the natural cosmetics and the cement manufacturing companies for providing the data for the research.

Ethical approval

Not applicable, because this article does not contain any studies with human or animal subjects

Competing Interests

The authors have no relevant financial or non-financial interests to disclose.

Funding

No funds, grants, or other support was received.

Compliance with ethical standards

The Authors declare that there is no conflict of interest.

Consent to publish

All authors read and approved the final manuscript.

Consent to participate

Not applicable, because this article does not contain any studies with human or animal subjects

Author contributions

Helen Grigoropoulou: Conceptualization, Review, Supervision. Ioanna Nydrioti: Validation, Visualization, Writing - Original Draft, Data curation for cosmetics plant. Melina – Margaret Moutsaki: Formal analysis, Data curation for cement plant. Nikolaos Leounakis: Formal analysis, Data curation for brewery.

Availability of data and materials

The datasets generated and/or analysed during the current study are available from the corresponding author on reasonable request.

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published 29 Nov, 2023

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Editorial decision: Major Revision
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Implementation of the Water Footprint as a water performance indicator in industrial manufacturing units located in Greece: Challenges & Prospects

Status:

Journal Publication

Version 1

Abstract

Figures

1. Introduction

2. WF Assessment In Selected Industrial Branches: A Review

3. Materials & Methods

3.1. Water Footprint state-of-the-art methodology

3.2. Standard procedure for WF estimation of an industrial unit

3.2. Analysis of the Case Studies

3.2.1. Case Study 1: Brewery

3.2.2. Case Study 2: Cement manufacturing plant

3.2.3. Case Study 3: Natural cosmetics production plant

4. Results & Discussion

4.1. Brewery Case Study Results

4.2. Cement Manufacturing Case Study Results

4.3. Natural Cosmetics Case Study Results

5. Conclusions

Declarations

References

Status:

Journal Publication

Version 1