The quest for rational energy use and related environmental impacts has been visible for at least three decades. However, the freshwater crisis is also among the top agendas in the current world order. Many building rating systems and sustainable development goals (SDGs) are associated with optimising energy or water consumption, given the fact that one-third of greenhouse gas (GHG) emissions [1] and 50% of energy [2] consumed globally are attributed to buildings, their environmental impacts need serious checks. Attention is also required because buildings consume 16% of worldwide water [3]. So, the sustainability concept owes a lot to the global construction industry. Proponents realise the link of water, energy and carbon emissions towards regional sustainable development of freshwater availability, energy security and global warming mitigation [4]. Indeed, the comprehension of the water-energy-carbon link nudges the policymakers for socio-economic sustainability [5]. Besides energy priority for decades, water use in various activities, including construction, has started to seek attention. Construction is the most water-consuming sector after agriculture [6], and the Indian construction sector is perhaps the largest globally [7]. India needs to catch up in water and land resources and, hence, the energy to cater for a staggering 17% of the global population proportion [8]. The Indian construction sector accounts for 30% of the total country’s CO2 (GHG) emissions and 40% of energy consumption [9]. Conventional Indian houses are unsustainable and represent irresponsible resource consumption [10]. A sustainable building relies on less water and energy, emits fewer greenhouse gases (GHG), and uses materials more efficiently, while waste production is efficient for conventional buildings’ LC [11]. The established research on embodied energy (EE) in buildings has helped to have more energy-efficient buildings in recent years [12]. The strong relationship of EE with carbon emissions [13] means that carbon emissions from building construction have also been mitigated to a specific effect. However, simultaneous checks on embodied water (EW) parameters still need to be present in previous attempts, and the holistic Sustainable Built Environment (SBE) that is envisioned needs to be improved [14]. The scientific community is looking back at vernacular architecture to conserve water consumption in building construction [15]. The time has come to consider drinking water consumption assessment and reduction due to on-site construction personnel [16]. So, introspection in Indian houses involving EW parameters alongside conventionally taken EE or carbon emissions towards SBE is worthy.
The water embodied in materials through production, extraction and manufacturing of materials is known as indirect virtual water (VW) or materials embodied water (EW) [17]. Water footprint (WF) assessment, in addition, includes green water (stored in plants and soil) and grey water (polluted water). Stand-out Indian [18] or the Australian studies of 2004 [19], 2007 [20] and 2011 [21], along with a few other global studies from Spain [22] and Iran [23], reveal that VW or blue WF or total EW terms are inter-changeable, with supportive system boundary definition. Australia kickstarted the EW research in 2004. The first Indian study by Bardhan [17] and her follow-up investigation in 2016 [24], alongside a hotel-based Indian case [25] and the much-improvised 2022 Indian study [10], computed EW, including direct water, in the range of 16.27−27.6 kL/m2. Primarily, concrete and steel are EW-intensive materials [26]. Indian constructions are high on EW [14]. EW studies require enhanced explorations to contribute to environmental sustainability and water scarcity [22].
Like water, energy use in the building is attributed for almost its entire life till demolition. It is similarly composed of direct and indirect energy, as in EW definitions [27]. On a similar pattern, embodied carbon (EC) relates to material consumption, construction, and operational phases besides the demolition stage of building LC. Materials production mainly contributes to EE and GHG (EC) [28]. The phase of 2000−2017 sees a rapid increase in dwellings’ floor area but a minimal reduction in materials energy intensity [29]. Starting from the 2003 situation [30], Indian studies by Ramesh et al. [31], Shukla et al. [32], and the 2021 investigation by Vengala et al. [33] find EE in the 1610−7350 MJ/m2 range for different buildings and raise the bar of local manufacturing, materials, and construction techniques in optimising EE. The 13.9 GJ/m2 value shows the EE-intensive nature of UAE constructions in a study [34] based on the Australian EPiC database and material quantities to report initial EE (including the construction phase). EE predominantly contributes to LC energy; however, construction technologies and building materials innovations report EE cutting up to 62% [35]. Massively increasing Indian building stock accounts for 40% of the country’s electrical energy consumption [36]. A 2022 study emphasises the role of innovative construction practices for net zero buildings besides achieving SDGs through operational energy (OE) and emissions reduction [37].
Environment impacts, or energy issues of construction, are vastly covered in the research compared to EW [38]. A cradle-to-grave LCA study in Spain finds that the construction/renovation stage (60%) and use phase (40%) of residential buildings are environmentally impacting [39]. Including water consumed in electricity production is advocated in assessing buildings EW [40]. Bringing more renewables through international collaborations of wind-solar energy is a consolidating hope [41]. Table 1 highlights most of the existing scientific contributions specific to the construction sector at the building scale or urban level, highlighting interrelationships among two or all three of EW, EE, or EC parameters.
Construction sector-specific studies covering EW-EE or EW-EE-EC nexus
Country of study (Year) | Source | Parameters | Methodology/Remarks |
---|---|---|---|
Spain (2022) | [48] | EW, EC | Research survey, environmental, and economic data. Sustainability decision-making (reducing EC, EW) is achieved by identifying and adjusting impacting building materials and machinery. |
Australia (2022) | [49] | EW, EE, EC | QGIS. Direct interrelationship between the three parameters. Diverse residential constructions and efficient materials are required. |
USA (2023) | [40] | EW, EE | I-O method. 2.5%−31.2% in the share of EREW in total EW of construction materials. EW vis-à-vis energy use is vital towards achieving a truly sustainable built environment. |
India (2024) | [50] | EW, EE | Site-based. Global databases are fine for initiating EW studies, irrespective of regional contexts. Quantifications may differ depending on the database use; however, the chronology of top impacts remains similar. EW and EE have an inverse relationship concerning material consumption scenarios in conventional Indian houses. An EW conserving approach can also be a fitting EE solution if a material is thoughtfully selected during the design phase. |
USA (2022) | [42] | EW, EE | I-O-based hybrid method. EW and EE are weakly correlated, but EREW and EE are strongly correlated. An energy-carbon-water nexus perspective is required, rather than an energy component in isolation, to see the environmental impacts of construction. |
UK (2021) | [14] | EW, EE, EC | I-O methodology. There is no correlation between the water footprint and the construction sector’s energy or carbon footprints. |
USA (2023) | [44], [51] | EW, EE, EC | A macro-economic model based on I-O methodology. The EE is near perfect and positively correlated with EW. A decrease in EE use may not help decrease the majority of EW. Saving just EE may only help conserve 13%−16% of EW. Buildings’ environmental embodied impacts should be assessed through the energy-carbon-water nexus perspective. |
India (2016) | [52] | EW | Experiment based. A significant EW saving but not so much EE or carbon emissions saving by using gypsum plaster concerning conventional sand-cement plaster. So, EW and EE are not strongly correlated. |
Iran (2019) | [23] | EW | Process-based LCA. Construction-specific VW supply and consumption involves the dominant share of energy and GHG emissions. The EW−EE relationship still needs more concrete evidence. |
Saudi Arabia (2019) | [53] | EW | Overview study. Popular concepts-green and zero-energy buildings strive to save water and energy. Architects, town planners, and engineers must consider combining EW and EE in new buildings. |
Spain (2018) | [54] | Energy, water, and carbon | LCA method. The operation and maintenance building phase is covered. Renewable heating and lighting are emphasised in recommendations towards decreasing the environmental impacts of case buildings. |
As Table 1 outlines, a fragile EE−EW relationship [42], while a positive EE− EC (GHG) emission relationship is preliminary predicted [13]. A USA research team performed several scientific investigations based on the I-O model in 2022−2024 [42]-[44], highlighting the positive correlation between EE and EW while meticulously highlighting that energy-specific measures do not considerably control EW. The matter of energy-water dependency deserves profound insight due to feeble evidence [23]. The inter-dependency of EW and EE is anticipated, and the energy-water nexus perspective is crucial to evaluating resource consumption and the environmental impacts of buildings [42]. A total void exists in Indian-specific studies. An Indian scholar [45] sees the worth of energy-water linkage in building regulations and fewer regulations dealing with the operational phase of buildings. Non-compliance with building regulations is common [46], especially for conventional Indian stand-alone houses [10]. A construction sector-specific study [14] involving many developed and developing economies finds no notable correlation between water, energy and (GHG) carbon dioxide (CO2) footprints but hints at an energy-CO2 correlation. An Indian study [47] covering cradle-to-site finds a 90% share in buildings’ carbon footprint due to cement, brick, and steel, with cement alone contributing 60%. It finds high relevance of materials embodied energy for the carbon footprint of buildings and calls for pertinent material selection in the design phase.
Prolonged ignorance towards significant water impacts in construction exists due to increased focus on energy or CO2 (GHG) only. A city-level nexus-based review study [4] finds increased significance in the ‘energy-water’ nexus approach rather than including carbon. While the proponents [65], [56] argue for a combined consideration of EE and EW for buildings, studies must indicate the EW, EC, and EE relationship at the building level [44]. A study [54] involving two school buildings seeks energy, water, and carbon footprints in Spain. However, the operation and maintenance phase is included rather than embodied. Studies by USA scholars [44], [51] seek EC, EE and EW assessment for four university buildings based on the I-O model of a developed economy of the USA. The same scholars advance to intervene in the Architecture plus design (A+D) of urban buildings through the impact of surface aspect ratio on the three embodied parameters, using software modelling and I-O data [56]. It emerges as a solitary effort at the building level to seek sustainable building solutions based on the nexus of the three embodied parameters. So, the current endeavour is a worthy attempt to build EC, EE, and EW relationships for four conventional house constructions.
Not only Indian [10], [17] or US studies [57], [58] but also the proponents from other global locations [21], [59], [60] recommend using hybrid LCA methods owing to complexity and overestimation in the I-O method or underestimation in the process-based LCA method. Given the unreliability of input-output (I-O) methods in the current world order, precisely for developing economies like India, the process-based computations are more appropriate, provided the system boundary is robust. The absence of Indian-specific databases for unit material consumption, specifically for EW, nudges the use of established global databases. Relying on materials inventory is logical [17] and aligned with the universal database [34]. So, the literature encourages unravelling EW, EC (GHG), and EE relationships employing a process-based hybrid methodology.
The current study assesses EW, EC (GHG) and EE for four conventional houses in Jammu city, India, due to building material consumption covering cradle to gate (of production plant) stage only. The study uses the alone comprehensive database, i.e., the environmental performance in construction (EPiC) database, providing material-wise coefficients simultaneously for EW, EE, and EC (GHG) [61]. The authors of [34], [50] support the universal applicability of databases like EPiC for missing contextual databases or, in case precise construction procedures (like green rating requirements) are absent. The precise material inventory availability coupled with re-verification through field measurements and on-site visits are compulsory attributes behind the selection of the houses. Further, the cross-sectional technique is chosen to ensure near similarity in construction year and location of the case houses (to eliminate external agencies, if any) and define the conventional construction set-up of the location. The standard methodology recommended by ISO 14044 [62] or 14046 [63] LCA frameworks (Figure 1) is adhered to predict the house-wise impacts (disaggregated cases) and combined one (aggregated case). The current study is the first building-specific attempt to outline EW-EE-EC comparatives simultaneously and positively impact 2030 SDGs.
Methodology adopted in the study

The study location chosen is Jammu City in the union territory of Jammu and Kashmir (J&K), India. Table 2 details the essential modalities of the four houses (herein referred to as CR-1, CR-2, CR-3, and CR-4) to encapsulate the relevant leads. Individual houses taken in isolation are called disaggregated cases, while all houses taken together are termed aggregated cases (CR-T).
Description of the conventional houses under study: CR-1, CR-2, CR-3, and CR-4 are four contemporary residences (CR) chosen in the study
Description | CR-1 | CR-2 | CR-3 | CR-4 |
---|---|---|---|---|
Plot area [m2] | 500 | 250 | 125 | 250 |
Total construction area [m2] | 350 | 391 | 107 | 380 |
Number of floors | 2 | 2 | 1 | 2 |
Project completion year | 2022 | 2022 | 2021 | 2022 |
Is the cellar present? | No | |||
Building type | Stand-alone family house (plotted accommodation) | |||
Location | Jammu | |||
Ownership | Self-owned (family) | |||
Concrete mixing | In-situ | |||
Type of structure | RCC frame | Composite (few RCC columns with load-bearing brick walls) |
Jammu, a northern Indian city, has excellent potential for development after Article 370 abrogation in 2019. The city’s location and connectivity add to its potential to invite record development. The peripheral conventional houses forming the sprawling growth of the city are already reckoning. Conventional houses are generally single or two stories high and use brick walls with RCC roofs. Specialised construction procedures like green building norms are far from practice. Also, construction is typically driven by owner-contractor consensus concerning materials in structure and finishing works. The conventional architecture of the city is already debatable [64], while a neighbouring but smaller city − Katra, is urging for redevelopment owing to urbanisation [65]. Though modern vertical cities have pros and cons [66], Jammu will likely continue embracing low-rise house typologies for some time, given its seismic, socio-economic, topography and urban morphology considerations.
The state of Jammu and Kashmir, especially the Kashmir zone, has interesting vernacular buildings in wood but is covered in literature to a lesser extent [67]. Traditional architecture is losing its identity through globalisation and monotonous construction preferences [64]. Interestingly, studies seeking traditional and contextualisation of future developments [68] and contemplating potential alternate energy use [69] for Katra exist, but Jammu needs to be addressed as such. Brick manufacturing is available but is relatively informal with quality concerns. Sand and other aggregates used to be available in plenty through the Tawi River, but enormous constructions involved its exploitation and further strictness by the local administration. The city receives satisfactory rainfall but is less aware of techniques like rainwater tanks [70]. Due to the considerable slopy terrain of the city, rainwater ends in mere wastage. Previous research predicts high EW [10] and EE [35] consumption of such conventional houses in Jammu. The study involves four conventional houses in the old Jammu City expansions per Table 2 details.
The study proceeds with a set aim by merging various processes and techniques described below.
The study aims to improve the buildings’ sustainability through a combined matrix assessment of embodied energy, water, and carbon for conventional house constructions in the Indian context.
The research novelty and implications are:
The EC, EE and EW assessments are a rare phenomenon to date.
The comparative EW, EE, and EC assessment nudges in construction and A+D phase decision-making towards better sustainable built environments.
Inevitable evidence shown − whether the prevalent energy or carbon-conscious approaches are also worthy of controlling embodied water. Recommendations and solutions for alternatives, if any, constitute the outlined impact of this research.
The fact is that conventional houses are the largest typology by proportion in Indian constructions. So, such a selection of the building typology is fitting to envision sustainable built environments.
The exploration is a much-needed contribution to outline not only the scarce EW domain but also a way to address it. The established EE domain is further incremented, and a new dimension towards achieving 2030 SDGs is therefore inevitable.
The fact that the outcomes empower policymakers and people, alongside building professionals, towards the shared and distributed responsibilities for sustainable conventional houses, the study is impacting society.
The advanced study considers an inventory of 18 materials (15 material groups) instead of only brick, steel, and cement.
The research carries on the methodology under a joint preview of ISO 14044 [62] and ISO 14046 [63] frameworks as per Figure 1. As evident in this figure, the entire research methodology encompasses goal and scope identification, inventory analysis, impact assessment, and results interpretation and stands covered in dedicated sections accordingly. The stand-out results are summarised in the conclusions section.
The study carries for the material production phase in acronym to the cradle-to-gate (of the plant) stage only. The study trusts the near-uniform production process of maximum materials globally. Thus, the study relies on the material inventory as the standard parameter to predict EC, EE, and EW and uses the singular database. Multiple databases, houses of different contexts, or buildings with different typologies are not considered to eliminate overriding parameters like context, climate, construction controls, and other user/owner-specific parameters. The availability of only one database for EW, EC, and EE and covering only the cradle-to-gate phase also encourages the disqualification of other LCA phases for the intended comparative assessments of the three parameters. The study is limited to the conventional houses of fast-developing Jammu city and carefully selected through the cross-sectional technique to gauge the study’s intended purpose effectively. Unit material-wise consumptions are referred to through consultation of hybrid embodied coefficients. Such coefficients cover the entire complexities of production processes (direct and indirect consumptions), including the upstream impacts. So, the various production processes required to meet the process-based hybrid methodology are covered by adopting hybrid embodied coefficients of the EPiC database.
The study undertakes the material production phase, as illustrated in Figure 2. As this figure expresses, all the processes and stages until the material production (gate of production plant) are the thorough system boundary ingredients. As already discussed, the comprehensive production phase, including the complexity of upstream impacts, is covered by referencing hybrid embodied coefficients of the EPiC database. Figure 2 also clarifies the omissions of the LC phases from the system boundary.
Study boundary details

The study uses the following tools and techniques:
ISO 14044 and ISO 14046 LCA framework to methodologically process the research.
Cross-sectional technique to select the houses. Selected houses are typical conventional houses. Besides, they correlate in materials, height, construction technique, and external agencies (like climate), which is crucial for this study as they bear almost similar contexts of location and year of construction.
The process-based hybrid LC analysis approach employing the hybrid embodied coefficients for material consumption.
The EPiC database used because it is the only global database providing EC, EE, and EW consumptions per unit of material production.
Site visits and field-based records supported by on-site investigations to deduce precise material inventory; inventory precision is the basis for selecting cases.
Descriptive statistics to compute disaggregated and aggregated impacts, utilising material inventory and EPiC database.
System boundary analysis at length to gauge disaggregated and aggregated cases and material-wise consumptions.
Statistical modelling based on regression technique to unravel the inter-relationship between EC, EE, and EW
The material consumption quantities and respective hybrid embodied coefficients are essential to compute for inventory analysis. The inventory for each disaggregated case is arrived at via field investigations coupled with on-site records available.
The material inventory is available in conventional site units for most of the materials. Such quantities are converted into the same units through standard conversion factors of Indian materials to suit functional units provided in the EPiC database. Table 3 shows details of material-wise consumptions for each house under study and the aggregated case (CR-T). The table indicates that the study bears a more significant boundary by covering 18 materials.
Material inventory for the study cases
S. No. | Materials | Functional unit (FU) | House-wise material inventory [FU] | |||||
---|---|---|---|---|---|---|---|---|
CR-1 | CR-2 | CR-3 | CR-4 | CR-T | ||||
1 | Steel bars | 9,900 | 10,500 | 2,500 | 8,000 | 30,900 | ||
2 | Cement | 48,250 | 60,000 | 22,000 | 55,000 | 185,250 | ||
3 | Sand | 1,098,352 | 923,400 | 203,490 | 70,1100 | 2,926,342 | ||
4 | Brick | 196,000 | 157,500 | 77,000 | 147,000 | 577,500 | ||
5 | Coarse aggregates (gravel) | 145,001 | 118,400 | 59,200 | 128,000 | 450,601 | ||
6 | Aggregate (fine) | kg | 503,713 | 357,835 | 108,560 | 375,978 | 1,346,086 | |
7 | Ceramic tiles | 5,316 | 10,680 | 4,440 | 9,944 | 30,380 | ||
8 | Marble stone | 12,858 | 10,975 | 5,488 | 11,250 | 40,571 | ||
9 | Granite | 653 | 16,330 | 380 | 10,881 | 28,244 | ||
10 | SS railing | 70 | 200 | 100 | 100 | 470 | ||
11 | Iron grill | 650 | 900 | 400 | 300 | 2,250 | ||
12 | Glass | Float | 75 | 14 | 23 | 11 | 123 | |
Security | 0 | 102 | 0 | 88.3 | 190 | |||
13 | Paint (interior) water-based | 1,620 | 2,565 | 1,080 | 2,430 | 7,695 | ||
14 | Paint (exterior) | m2 | 460 | 473 | 270 | 405 | 1,608 | |
15 | Paint oil-based | 340 | 608 | 243 | 513 | 1,704 | ||
16 | PVC | 74.3 | 0 | 32.5 | 0 | 107 | ||
17 | Wood | m3 | 9.2 | 6.9 | 2.7 | 5.7 | 25 | |
18 | Plywood | 0 | 8.82 | 0.428 | 6.21 | 15 |
The EPiC database holds the monopoly and uniquely provides hybrid embodied coefficients for EC (GHG), EE and EW for maximum building materials. The details of hybrid embodied coefficients for EC, EE, and EW, as per the chronology and FU of materials in Table 3, are expressed in Table 4. The EW, EE and EC coefficients are herein notated as α, β, and λ, respectively. The coefficient α is expressed in L/FU, β in MJ/FU, and λ in kgCO2e/FU, as in Table 4.
Detail of hybrid embodied coefficients (source: EPiC database)
S. No. | Material | Functional unit (FU) | Material-wise hybrid embodied coefficients | |||
---|---|---|---|---|---|---|
α [L/FU] |
β [MJ/FU] |
λ [kgCO2e/FU] |
||||
1 | Steel bars | 37.1 | 38.8 | 2.9 | ||
2 | Cement | 7.8 | 11.8 | 1.3 | ||
3 | Sand | 1.8 | 0.34 | 0.024 | ||
4 | Brick | 1.8 | 3.5 | 0.32 | ||
5 | Coarse aggregates (gravel) | kg | 1.9 | 0.48 | 0.036 | |
6 | Aggregate (fine) | 1.9 | 0.48 | 0.036 | ||
7 | Ceramic Tiles | 15.2 | 18.9 | 1.3 | ||
8 | Marble Stone | 16.5 | 16.3 | 1.3 | ||
9 | Granite | 16.5 | 16.3 | 1.3 | ||
10 | SS Railing | 168 | 123 | 9.2 | ||
11 | Iron grill | 44.3 | 29.5 | 2.1 | ||
12 | Glass | Float | 335 | 296 | 21 | |
Security | 785 | 775 | 56.9 | |||
13 | Paint (interior) water-based | m2 | 16.1 | 8.7 | 0.53 | |
14 | Paint (exterior) | 14.7 | 9.3 | 0.47 | ||
15 | Paint oil-based | 14.7 | 9.3 | 0.47 | ||
16 | PVC | 670 | 574 | 26.7 | ||
17 | Wood | m3 | 58,411 | 41,597 | 2,269 | |
18 | Plywood | 69,363 | 63,691 | 3,680 |
The equations presented on the next page outline the total impacts for EW, EE, and EC for the disaggregated or aggregated houses, house-wise and material-wise. The calculated impacts of EC, EE, and EW on the study cases are represented in Table 5. The materials initially listed as 18 groups are rearranged here into 15 groups (combining the sub-groups under aggregates, paint, and glass) to simplify the impact revelations. Table 5 also clarifies the total house-wise quantities of EC, EE, and EW in the specified units in the last row.
Material and house-wise EC [kgCO2e], EE [MJ], and EW [L] assessment details
Material | Impact assessment house-wise (disaggregated cases) | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
CR-1 | CR-2 | CR-3 | CR-4 | |||||||||
EC | EE | EW | EC | EE | EW | EC | EE | EW | EC | EE | EW | |
Steel | 28,710 | 384,120 | 367,290 | 30,450 | 407,400 | 389,550 | 7,250 | 97,000 | 92,750 | 23,200 | 310,400 | 296,800 |
Cement | 62,725 | 569,350 | 376,350 | 78,000 | 708,000 | 468,000 | 28,600 | 259,600 | 171,600 | 71,500 | 649,000 | 429,000 |
Sand | 26,360 | 373,440 | 1,977,034 | 22,162 | 313,956 | 1,662,120 | 4,884 | 69,187 | 366,282 | 16,826 | 238,374 | 1,261,980 |
Brick | 62,720 | 686,000 | 352,800 | 50,400 | 551,250 | 283,500 | 24,640 | 269,500 | 138,600 | 47,040 | 514,500 | 264,600 |
Aggregates | 23,354 | 311,383 | 1,232,557 | 17,144 | 228,593 | 904,847 | 6,039 | 80,525 | 318,744 | 18,143 | 241,909 | 957,558 |
Ceramic tiles | 6,911 | 100,472 | 80,803 | 13,884 | 201,852 | 162,336 | 5,772 | 83,916 | 67,488 | 12,927 | 187,942 | 151,149 |
Marble stone | 16,715 | 209,585 | 212,157 | 14,268 | 178,893 | 181,088 | 7,134 | 89,454 | 90,552 | 14,625 | 183,375 | 185,625 |
Granite | 849 | 10,644 | 10,775 | 21,229 | 266,179 | 269,445 | 494 | 6,194 | 6,270 | 14,145 | 177,360 | 179,537 |
SS railing | 644 | 8,610 | 11,760 | 1,840 | 24,600 | 33,600 | 920 | 12,300 | 16,800 | 920 | 12,300 | 16,800 |
Iron grill | 1,365 | 19,175 | 28,795 | 1,890 | 26,550 | 39,870 | 840 | 11,800 | 17,720 | 630 | 8,850 | 13,290 |
Glass | 1,575 | 22,200 | 25,125 | 6,098 | 83,194 | 84,760 | 483 | 6,808 | 7,705 | 5,255 | 71,689 | 73,001 |
Paint | 1,235 | 21,534 | 37,842 | 1,868 | 32,369 | 57,187 | 814 | 14,167 | 24,929 | 1,719 | 29,678 | 52,618 |
PVC | 1,984 | 42,648 | 49,781 | 0 | 0 | 0 | 868 | 18,655 | 21,775 | 0 | 0 | 0 |
Wood | 20,875 | 382,692 | 537,381 | 15,656 | 287,019 | 403,036 | 6,126 | 112,312 | 157,710 | 12,933 | 237,103 | 332,943 |
Plywood | 0 | 0 | 0 | 32,458 | 561,755 | 611,782 | 1,575 | 27,260 | 29,687 | 22,853 | 395,521 | 430,744 |
Total | 256,021 | 3,141,854 | 5,300,449 | 307,346 | 3,871,609 | 5,551,120 | 96,439 | 1,158,677 | 1,528,612 | 262,718 | 3,258,001 | 4,645,644 |
The equations for the total impacts of EW, EE, and EC are following:
(1)
(2)
(3)
where Qj denotes the quantity of the j-th material represented in functional units (FU).
As an example for better understanding, eq. (2) is represented in expanded form as eq. (4):
(4)
Various impacts assessed in previous sections are interpreted under different set-ups using comprehensive system boundary analysis as described below.
Table 3 outlines the EC, EE, and EW consumptions with the change in the covered construction area of all disaggregated cases. The covered construction areas of all the disaggregated cases are plotted on the X-axis, while the Y-axis shows the quantities per functional unit as specified. The callouts in Figure 3 showcase the Y-axis entry corresponding to the respective construction area from the X-axis. Figure 3 shows that CR-2 possesses uniformly the highest EC, EE, and EW. CR-3 evidence the lowest consumption for all three components. CR-2 has the largest covered area (391 m2), and CR-3 has the smallest covered area (107 m2) among all disaggregated cases. So, the trend of consumption above, as illustrated in Figure 3, highlights the following:
I) The positive relationship between the covered area of construction and the impact quantities in the specified units. Quite generic, an increase in area is bound to result in higher consumption. An author [29] has expressed concern over the increased EE by increasing dwellings’ floor area, owing to minimal improvisation in EEC of materials.
Further, Table 2 shows CR-2 is larger in covered construction areas by 11.55%, 73%, and 3% than CR-1, CR-3, and CR-4, respectively. Total EW for CR-2 is larger by 4.5%, 73%, and 16% than for CR-1, CR-3 and CR-4, respectively, as concluded from Figure 3. EE is higher by 19%, 70%, and 16% for CR-2 than EE values for CR-1, CR-3, and CR-4, respectively. In the case of EC (GHG), CR-2 exhibits higher values by 17%, 69%, and 15% than CR-1, CR-3, and CR-4, respectively.
Illustration showing changes in EC, EE and EW consumptions as functions of covered construction area of all disaggregated cases

II) A single-storey non-RCC (CR-3) and a double-storey RCC frame construction house (CR-2) of significantly dissimilar areas exhibit a more pronounced and uniform positive relationship of EC, EE, or EW to the covered construction area. Notably, Indian scholars [71] advocated no correlation between EE and the mass of the building. CR-2 of significantly dissimilar areas exhibit a more pronounced and uniform positive relationship of EC, EE, or EW to the covered construction area. Notably, Indian scholars [71] advocated no correlation between EE and the mass of the building.
III) The percentage drop in the covered area of the houses does not correspond to the equal percentage variation in any of the three (EC, EE, EW) components. The covered areas for CR-2 and CR-4 are similar, yet EC, EE and EW consumptions for CR-2 outline considerably more than the rest of the cases (Figure 3). While EE and EC consumptions are marginally higher for CR-4 than CR-1, the 2nd highest EW consumption exists for CR-1 and is considerably higher than that of CR-4. The underlying basis is that CR-1 and CR-2 are RCC frame constructions while the others are composite. It outlines that:
IV) RCC constructions account for higher EW among conventional construction types, while the same may not hold equally well for EE and EC. The EW finding correlates with the study [12], while Indian studies [30]-[33] advocated the role of materials selection and construction techniques to reduce EE.
The need to cover an alternate boundary component arises to further the above findings, as scientific literature urges. Thus, house-wise and material-wise consumption per unit construction area of the houses is envisaged to comprehend the impacts better.
The respective disaggregated case impacts (Table 5) are illustrated in terms of the per unit covered construction area (Table 2) of each house in Figure 4. EC (GHG) consumption ranges from 691−901 kgCO2e/m2 across disaggregated cases, as per Figure 4. EE consumption range is 8,574−10,829 MJ/m2. Different Indian conventional residential-based studies showcased the upper EE value of 10,510 MJ/m2 [71], 9,360 MJ/m2 [72] or 7,350 MJ/m2 [31]. Australian studies reported a high EE of 13,000−14,400 MJ/m2 [73]-[75]. The current study EE results are henceforth a strong indication that Indian constructions are doing all right in the EE domain owing to extensive research in previous decades. Further, Indian conventional constructions are better EE-conscious than their Australian counterparts. At the same time, current EE numbers might further recede if the EPiC (Australian) database is replaced with an Indian one.
EC, EE, and EW impacts per unit area in disaggregated cases

Proponents [28], [76] argue that extensive human labour utilisation in Indian industry stands out in lesser values vis-à-vis electricity dominant production of other countries. An indication of high energy use in a developed country like Australia vis-à-vis developing one (India) cannot be ruled out.
EW consumption values show a range of 12,225−15,144 L/m2 for the disaggregated cases in the pre-construction phase, as evident in Figure 4. A prominent office-based Chinese study [77] deduced EW = 10,430 L/m2, while a prominent Iranian study [23] covering residential buildings found EW = 16,910 L/m2. Previous stand-out Indian studies [10], [17] based on houses reveal a much higher EW range of 22,390−25,600 L/m2, while a hotel-based Indian study [25] revealed an EW figure of 18,980 L/m2 in the pre-construction phase. The EWC values used by Indian studies [17], [25] are debatable. However, EW quantifications could be overestimated more because the underlying focus is only on brick, steel, and cement. So, the lesser EW computation in the current study is attributed to EPiC database use and reflects continuous EW reforms in Australia, which is the initiator of EW research. It unravels that computation across contexts may vary. Nevertheless, high EW consumption in conventional Indian houses cannot be ruled out besides needing more consolidation studies. In crux, developed countries (Australia) are already water use conscious, but developing ones like India are still awaiting regulations to come out of UFW attitude.
Figure 4 shows the highest EW for CR-1 while CR-3 possesses the highest EE and EC computed per unit construction area basis. The descending pattern for EE and EC is similar, i.e. CR-3 > CR-2 > CR-1 > CR-4, while the EW consumption trend as per Figure 4 differs. House-wise EW consumptions reveal CR-1 > CR-3 > CR-2 > CR-4 trend in descending order. It leads to:
A positive and uniform behaviour of EE and EC consumption in conventional houses concerning materials consumption correlates with studies [78], [79]. The trend of EW impacts across houses varies from that of EE or EC and primarily consolidates EW’s weak link to EE (or EC), as pointed out in studies [40], [80].
Small single-storey constructions (CR-3) have the highest EE and EC consumption among the study cases. Relatively higher EW consumption for single-storey construction emerges irrespective of the construction technique or area of the houses. So, it is fitting to conclude that building components like the foundation are highly impacting. An Indian study targets only the foundation part to assess EW in hot-dry climates [81]. The Jammu house owners construct foundations to withstand two or three floors in future, irrespective of constructing a single floor initially. The high EE consumptive nature of foundations is also identified in studies [32], [82].
The results support at least double-storey construction in future conventional residences. Jammu is a potentially developing city, and like most Indian cities, high-rise solutions could have significance in checking EW, EE, and EC. As discussed, given the various pros and cons of vertical cities [66], the cost of a high-rise building apartment unit and the terrain of Jammu to support such constructions are also to be contemplated simultaneously. The interpretations for Figure 3 and Figure 4 need to be further analysed to arrive at consolidated conclusions. Learning from the previous Indian [10] or Australian [83] house-based studies, system boundary analysis predominantly considers material-wise consumptions per unit construction area. Only aggregated case-based interpretations are envisaged to avoid any undue complexity.
Figure 5 clarifies the comparatives of aggregated (CR-T) material-wise EC, EE and EC impacts per unit construction area. The values are obtained by the ratio of the cumulative sum of consumptions for a particular material for all houses (Table 6) to the total construction area of all houses (1,228 m2), as shown in Figure 5. All the impacts are shown in distinguished colours in text and illustration (bar and line) in Figure 5, as per specified units provided in the bottom half. Further, the negligible impacts stand ignored to be illustrated through text in Figure 5 for the illustration legibility.
Material-wise EC, EE, and EW assessment for the aggregated case
Material | Impact assessment for the aggregated case (CR-T) | ||
---|---|---|---|
EC [kgCO2e] |
EE [MJ] |
EW [L] |
|
Steel bars | 89,610 | 1,198,920 | 1,146,390 |
Cement | 240,825 | 2,185,950 | 1,444,950 |
Sand | 70,232 | 994,956 | 5,267,416 |
Brick | 184,800 | 2,021,250 | 1,039,500 |
Aggregates | 64,681 | 862,410 | 3,413,705 |
Ceramic tiles | 39,494 | 574,182 | 461,776 |
Marble stone | 52,742 | 661,307 | 669,422 |
Granite | 36,717 | 460,377 | 466,026 |
SS railing | 4,324 | 57,810 | 78,960 |
Iron grill | 4,725 | 66,375 | 99,675 |
Glass | 13,411 | 183,891 | 190,591 |
Paint | 5,635 | 97,748 | 172,576 |
PVC | 2,852 | 61,303 | 71,556 |
Wood | 55,591 | 1,019,127 | 1,431,070 |
Plywood | 56.885 | 984,535 | 1,072,213 |
Total | 922,524 | 11,430,141 | 17,025,825 |
Figure 5 shows that cement (196.1 kgCO2e/m2) and brick (150.5 kgCO2e/m2) stand out from the rest of the materials for EC consumption. Similarly, cement (1,780.1 MJ/m2) and brick (1,646.0 MJ/m2) impact the EE criterion the most. However, sand (4,289.4 L/m2) is the most impacting EW material, followed by aggregates (2,779.9 L/m2).
The top EC-impacting materials are cement > brick > steel bars > sand > aggregates. The high EE and EC impact of brick, cement and steel are noted in Indian studies [47], [84]. EE impacts are pronounced for cement > brick > steel bars > wood > sand. Studies [82], [85]-[87] outline the high EE impacts of concrete and its constituents, while others emphasise significant high EE impacts for massive brick use in Indian conventional houses [30]-[33], [84]. Henceforth, proponents urge the adoption of AAC and concrete blocks as alternatives to massive brick use for combating EE [88].
Material-wise EC, EE, and EW per unit area in aggregated case

Notably, prominent materials for EW impacts are sand > aggregates > cement > wood > steel bars. Figure 5 illustration interpolates to:
An EC-conscious approach in selecting materials for conventional houses seems effective for EE conservation. The close association of EC (GHG) and EE has been consistently reported in the past, too [13], [89]. However, EW conservation requires broadening the EC or EE-conscious measures as sand and aggregates recede in priority for EE or EC. Outlined EW-specific attention for sand and aggregates is reported in a stand-out 2022 study [10] and studies [60], [90], [91].
Brick impacts in EW fail to emerge in the top 5 materials, but it stands out for EE and EC impacts. Pertinently, before 2022, Indian studies [17], [25] target to cover EW aspects only for brick, steel, and cement (top EE consumptive ones). A broad system boundary coverage through a 2022 study [10] identified the role of sand, aggregates, and other materials for EW consumption in conventional Indian houses. The current study consolidates it further.
Steel is not the prominent EW consumption material, contrary to previous scientific literature [17], [25], but consolidates the stand-out Indian studies of 2022 [10] and 2024 [50]. The marked Indian cities and current ones consider many materials beyond steel, cement, and brick. Moreover, the emphasis on steel-based resource consumption has been outlined for decades, greatly improving steel production. The EW debate’s inception was owed to Australia in 2004, and the EPiC database of Australia reflects the much-improvised EW of steel production in Australia since 2004.
The bottom line of the analysis arrives at a clear connection of EE and EC, but the EW aspect differs [14], [79].
The relationship between the impacting components (EC, EE, and EW) is evident in the sections above, hinting at a strong and positive one between EE−EC. Figure 6 and Figure 7 clarify the extent of the mutual inter-relationship between the three components through statistical modelling using the regression technique (R2 value). The material-wise EC consumptions per unit construction area in the aggregated case (like Figure 5) are plotted in the Y-axis, while corresponding EW and EE consumption values for all 15 materials are plotted in the X-axis, as per the specified units in Figure 6.
EC to EE and EW relationship graph using regression technique

The EC vs. EW relationship graph returns with an R2 value of 0.0869, meaning 8.69% fitness of positive and linear relationship is evident, while EC vs. EE relationship fitness amounts to 93.4%. In other words, Figure 6 indicates a weak relationship between EC and EW and a strong and positive interrelation between EC and EE. Considering the material inventory and pre-construction LCA phase, the finding of a significantly weak EC (GHG) and EW relationship at the building level is nothing short of a breakthrough. In contrast, the solid and positive EE−EC relation strengthens the previous attempts [13], [78], [79]. It implies that EE measures over the preceding decades check the EC component. However, EW measures invite a different outlook, as the abovementioned sections prove. Figure 7 further crystallises the takeaways.
Figure 7 aims at the EE vs. EW relationship by plotting material-wise EE consumptions per unit construction area in the aggregated case (Y axis) and corresponding EW consumptions (X axis) for all 15 materials. The consumption values are plotted in consistent units and stand specified through the axis labels in Figure 7. It reveals the EE−EW relationship through an R2 value of 0.1565, which means 15.65% strength of the positive and linear relationship. It translates as a weak EE to relationship considering the material consumption scenario of Indian conventional houses.
EE−EW relationship graph using regression technique

A weak EE−EW relationship is observed in a 2022 study [42] based on five institutional buildings and utilising the R2 value approach. Another study [40] reflects the weak EE−EW relationship using the R2 approach. While some studies [14], [42], [80] also find almost zero EE−EW relationship, interestingly, few studies [81], [92]-[94] hint at the probability of an EE−EW relationship to some extent. Nevertheless, various nexus studies, for example, a review study [4], find that 94% of the urban energy-water-carbon studies focus on the ‘energy-water nexus’ relationship instead of three components in one go at product or sector-level studies. So, a solid and positive EE−EC relationship and a weak EE−EW (and EC−EW) relationship seem to fit the global research scenario.
EPiC database tables show uniformity in positive or negative change in all three components (EC, EE, or EW) with change in unit material [61]. For example, if moving from material 1 to material 2 shows an EEC increase in EPiC, it would also increase EWC and ECC. So, a positive relationship interpretation reflects unit material consumption. However, the harmonious mix of material consumption patterns in conventional Indian houses demonstrates the strong EE−EC and extremely weak EE−EW or EC−EW relationships. So, quantity-wise material use pattern needs an interrogation to balance the three components in parallel.
It is observed that Jammu residences are discouraging wood use already. Reforms in the global steel and cement industry are also emerging consistently. The cessation of Jammu’s informal brick industry is inevitable due to resource consumption, cost, and quality concerns. EE research over the last three decades is visible in the rise of various alternative materials to substitute the primarily consumptive ones like brick. Such alternative materials are expected to make a mark in conventional Indian houses. Various construction methods like rat-trap bonds exposed masonry in concrete or ceramic bricks check EC, EE, and EW simultaneously through decreased use of brick and abandoning the plasterwork (sand). Further, there are apparent advantages in on-site water use (reduced curing and material use), reduced construction period, and the cost involved.
A positive and robust interrelationship between EE and EC but differing EW behaviour calls for a broad materials template identifying the top simultaneous impacts. An EW-conscious approach in selecting materials for conventional houses may disregard the importance of steel, brick, or cement, which otherwise are prominent considering EE (or EC) impacts. The novel area of EW has outlined materials like sand and aggregates. Amid the high global water-related concerns, EW’s approach deserves an overriding preference. Considering the combined matrix of EC, EE, and EW, it is essential to consider a high-impacting material palette. If wood use continues to be discarded in the conventional houses and EE reforms (strongly correlated to EC) are consolidating continuously, the EW impacting materials approach to devising a broad materials template is fitting. A refined approach under the EW umbrella, but with specific attention to brick, cement and steel, would unleash a new approach towards building sustainability in the 21st century. So, taking a holistic preview and recalling the outcomes of Figure 6 and Figure 7 besides Figure 5, this study proposes to conserve EC, EE, and EW by attending the use of the following materials: sand > aggregates > cement > steel bars > brick > plywood.
The current study is indeed subjective to conventional Indian constructions of Jammu. Nevertheless, it opens valuable horizons to the knowledgeable audience. Thanks to the established EE research, localised EE databases are in place. The EC has its basis directly in EE, so its determination is near exactitude using localised databases. However, EW assessment is an infant and untouched domain, yet the databases are seldom noticed, barring the Australian one. Pertinently, the use of global databases is recommended by the proponents irrespective of the context; for example, the EPiC database is applied for American [95], Mediterranean [96], [97], and Indian [10], [50] context-based studies. The identification and trend of top impacting materials on EW and EE are the same despite different databases consultation [50]. So, it is worthwhile to avoid getting carried away with the quantitative assessment; the chronology of the impacting materials, building elements, or construction phases holds significance. Thus, the study’s outcome in establishing a materials-wise chronology for the comparative EC−EE−EW assessment is valuable. Sustainable built environments are thus better envisioned by holistically considering the combined matrix of EC, EE, and EW in conventional constructions.
By reflecting on the impact of material use based on a single parameter or all three parameters, architects and societal players must seek and contemplate improvisations to better introspect in the A+D phase of buildings. The Indian manufacturing industry is relatively informal and primarily dependent on human labour. So, if and when the Indian database emerges, it can reflect differential EE, EC, and EW quantifications. Therefore, as already discussed, different databases return different quantities; hence, databases used have a subjective role. Still, based on a global database, the study reflects reverse psychology. It could encourage the industry to transpire EW numbers honestly and consolidate the knowledge bank for different regions and countries. EE research also flourished in a similar pattern in previous decades. The consumption numbers and specifically accentuating the top impacting materials in this research are still clinical vis-à-vis scientific literature. EPiC database is Australian-based, and it was the first country to intervene in the EW matter in 2004. It reflects the unit material-wise consumption for all three parameters, so the controls and assumptions, if any, remain the same. Using global databases, especially the EPiC database, is logical for now. The latest and continuously improvising databases like EPiC are understood to provide clinical resource consumption values (both direct and indirect) by including comprehensive and complex production steps, such as extraction of ores, in the case of steel production. Nevertheless, manufacturing reforms are also becoming identical in the current globalised era, making our findings increasingly rigorous.
After the inception of EW studies in 2004, the Australian manufacturing industry improved in EW conservation measures. While unregulated, irresponsible, and higher water consumption in most other countries, including India, there are lags in reporting in scientific literature. Through its massiveness, the Indian construction industry is pivotal in resource consumption in other countries. When coupled with UFW’s association with Indians, the water consumption scenario is enormously scary. The Indian construction sector already reflects much higher EW based on the current results. The quantifications go haywire when adding the 30% non-revenue water component attributed to only the leakages component in the country’s water supply scenario. So, the study aptly urges global academia and research groups to adopt global databases to create awareness about current EW consumption and further contemplate conserving EW.
On the methodology front, it has sufficient scope to replicate across different global regions for both EW assessment and its nexus to EE (or EC). The I-O method is not logical, acknowledging the absence of economy-based data in the Indian context. I-O methods bring many sectors into calculations, further resulting in overestimation, while the unreliability of developing nations’ economies is another challenge. Process-based methods almost invariably lag the comprehension to take all complex micro-level steps of a process, which results in underestimation. Using hybrid processes utilising accurate material inventories is fruitful, particularly in the scarce EW domain. The study considers only one process, i.e. material production phase (cradle-to-gate approach); multiple processes can be included in advanced EW studies in cradle-to-site or cradle-to-grave assessments. Since there are trade-offs between water and energy, developing a similar methodology, future studies can include further construction processes like on-site construction phase water use, electricity, and fuel consumption (indirect water) in on-site construction, material supply chain and workforce-related water and fuel consumptions. Knowing the various inventory from the site data and field investigations, EW assessment for a broader boundary condition and varied building typologies is inevitable.
Given the non-realisation of responsible water use behaviour without stringent policy reforms, user and facility-level water auditing is hard to find. Further, conventional houses are the ideal representation of Indian construction and seldom involve any attention to conservative resource use. Therefore, attending conventional typologies is more valid than conducting studies based on easy data availability. For now, hybrid and triangulation approaches for data collection as per the best of site records and availability (in consumption units or currency) should not be a barrier to conducting EW studies. Therefore, the current study should urge the researchers to follow suit and intervene in the dominant construction typologies in the respective regions.
The outcomes of the study are realistic and pragmatic. By developing the study outcomes, it is possible to unleash the effectiveness of the localised construction and architecture practices among the masses and administration. Realising more empirical studies are valuable in conserving resource consumption and having a checklist for dos and don’ts in the prevailing practices. Building bylaws and development controls can be redevised, considering materials, construction area, and number of floors vis-à-vis the plot size and economic status of the user. Auditing is the first step towards creating awareness. However, the current study is a lasting effort to encourage design, user, and policy interventions. The peer group must highlight the governing issues of current building construction practices and should seek ways to conserve resource efficiency, including EW. Indeed, it is time to test EE-conscious practices concerning EW consumption and the harmonious mix of A+D and other user-level approaches to wisely cater to all three parameters.
The current study, therefore, is much more than an auditing-only exercise. The research is novel to seek the interrelationship between the three components simultaneously. The current world is realising fast that water is indispensable to the future liveability of the planet, including any efforts towards SBE practice. The fact that EE- or EC-conscious solutions are not conserving EW is a realistic breakthrough to perceive future SBE. It unleashes a new horizon vis-à-vis the feeble existing research to consider even two components. A current study is a valid approach to seeking more contributions from academia and the material industry. The scope of the relationship equation between EC, EE, and EW is left to future studies with a larger sample. Various material and construction reforms need a broad outlook for consistent adaptation through technical platforms like sensitivity analysis, BIM applications and simulations. Techniques like AHP and TOPSIS can be helpful to draw conclusions involving experts and construction actors. Conventional constructions predominantly disobey the building regulations, too. So, the cost factor of the solutions is also worth intriguing as conventional construction clients have more orientation towards cost-cutting and efficiency. While studies can think of alternate solutions in constructions, our study has taken a more pragmatic approach of not deviating from the current practices. Instead, tweaking the current ones is more likely to get adopted in the Indian context. With EE research consolidated enough already while EC is strongly connected to it, the EW research invites profound contributions to seek a sustainable built environment in the 21st century and beyond.
The study is a novel attempt to seek EC, EE and EW assessments and their interrelationships in a single study. While the study consolidates the close association of EE and EC, it outlines the stand-out and differential behaviour of EW impacts stronger than the other two components for the conventional houses of Jammu in the pre-construction phase. A weak relationship unravels between EW to EE or EW to EC. The unprecedented study opts for a consistent database (EPiC) providing the hybrid embodied coefficients of building materials for all three components: EC, EE, and EW. The following findings stand out:
There is a positive and strong correlation of EE−EC.
EE’s conscious approach over the decades is controlling EC, too, but not the EW in building construction. EW’s conscious approach needs a varied canvas for construction techniques and building materials.
Cement, brick, and steel are dominant EE and EC impacts. However, sand and aggregates are the top EW-impacting ones. Brick does not even make it to the top 5 EW-impacting ones.
Indian conventional constructions seem considerate around EE already, while high on EW component vis-à-vis other prominent global works.
To cut the three components simultaneously, building professionals need to consider material-wise attention in the order of sand > aggregates > cement > steel bars > brick > plywood.
Global databases and material inventory are recommended for such studies across regions, primarily the infant EW domain.
Steel is not the topmost EW-impacting material, contrary to the previous studies.
Single-storey conventional houses are top EE and EC impacting while showing significantly high EW, too, hinting at the high foundation impacts on the three components. Conventional houses in Jammu should be at least double-storey.
RCC constructions have a high EW impact, while the same does not hold for EE or EC.
Previous EW studies’ approach to only considering top EE-impacting materials for identifying EW impact deserves significant improvisation. In the current study, recognising EW impacts for sand, aggregates, and plywood stands out. The study contributes to EE or EC research regarding assessments and relationships. It is a precious contribution to the scarce EW domain through various findings, while the first such attempt to outline the EW−EC relationship. The comparative relationship of EE, EW, and EC helps architects, society, and policymakers to seek better sustainable solutions and defy the emphasis on a single aspect of EE. The results outline the suitability of previous approaches, whether the energy-conscious building is equally EW- or EC-efficient. The research is novel and unfolds interesting yet critical aspects of approaching conventional buildings’ architectural design and construction.
The results call for more contributions to the study’s outcomes to identify the material use and alternatives. Improvised LCA boundary conditions in future nexus studies are inevitable. Simulation studies and techniques like sensitivity analysis, TOPSIS, and AHP are envisaged for future attempts in this domain. The key to seeking sustainable built environments is to pay specific attention to EW research and associated impacts outlined in the study.
The authors acknowledge the support of IIT Roorkee and SMVD University, Katra (J&K) in the research. We are incredibly grateful for the in-depth insights of the editor and the three anonymous reviewers. The corresponding author is specifically grateful to the Council of Scientific and Industrial Research, Government of India, for the travel grant support to the 18th SDEWES conference and the additional support rendered by the supervisor. The SDEWES team’s consideration for discounted registration is special. We also acknowledge all the technical and administrative help rendered by one and all at IIT Roorkee, India.
EC | Embodied carbon | [kgCO2e] |
EE | Embodied energy | [MJ] |
EW | Embodied water | [L] |
Q | Quantity of the material | [FU] |
α | Embodied water coefficient | [L/FU] |
β | Embodied energy coefficient | [MJ/FU] |
λ | Embodied carbon coefficient | [kgCO2e/FU] |
j | Index of material or group of materials |
A+D | Architecture plus Design |
AAC | Autoclaved Aerated Concrete |
AHP | Analytic Hierarchy Process |
BIM | Building Information Modeling |
ECC | EC Coefficient |
EEC | EE Coefficient |
EREW | Energy Related EW |
EWC | EW Coefficient |
EPiC | Environmental Performance in Construction |
FU | Functional Unit (kg, m2, or m3) |
GHG | Greenhouse Gas |
LC | Life Cycle |
LCA | LC Assessment |
OE | Operational Energy |
OW | Operational Water |
RCC | Reinforced Cement Concrete |
SBE | Sustainable Built Environment |
SDG | Sustainable Development Goals |
TOPSIS | Technique for Order of Preference by Similarity to Ideal Solution |
UFW | Unaccounted for Water use |
VW | Virtual Water |
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