Journal Pre-proof Sustainability performance of hotel buildings in the Himalayan region Silu Bhochhibhoya, Massimo Pizzol, Francesco Marinello, Raffaele Cavalli PII:
S0959-6526(19)34408-7
DOI:
https://doi.org/10.1016/j.jclepro.2019.119538
Reference:
JCLP 119538
To appear in:
Journal of Cleaner Production
Received Date: 28 May 2019 Revised Date:
25 November 2019
Accepted Date: 1 December 2019
Please cite this article as: Bhochhibhoya S, Pizzol M, Marinello F, Cavalli R, Sustainability performance of hotel buildings in the Himalayan region, Journal of Cleaner Production (2020), doi: https:// doi.org/10.1016/j.jclepro.2019.119538. This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Ltd.
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Sustainability performance of hotel buildings in the Himalayan region Silu Bhochhibhoya1*, Massimo Pizzol2, Francesco Marinello3, Raffaele Cavalli3 1
Department of Construction Management and Engineering, University of Twente, The Netherlands
2
Department of Planning, Aalborg University, Denmark
3
Department of Land, Environment, Agriculture and Forestry, University of Padova, Italy
*Email:
[email protected],
[email protected] Telephone: +31-(0)-626 772 576
Abstract This study provides the first comprehensive overview of the sustainability performance of the hotel sector in the Himalayan region: Sagarmatha National Park and Buffer Zone, using both environmental, economic, and technical criteria. In particular, the performance of 45 buildings in this region were measured and quantified in terms of life cycle based carbon footprint, life cycle costs, heat loss rate, number of guests, energy consumption, and area. Buildings were classified into three types: traditional, semi-modern and modern. The statistical analysis included testing for significant differences between such categories by means of ANOVA, and determination of the correlation between the same parameters. Results show a significant difference between the buildings’ total carbon footprint and operation stage carbon footprint while, there is no significant difference between the buildings’ life cycle costs. Traditional buildings have on average the largest carbon footprint and life-cycle cost over the typical building lifespan of 50 years of building lifespan. The ANOVA tests highlight how heat loss rate, size of the building and number of tourists in the hotels are significantly different across the building types. A strong positive correlation is observed between environmental impact, economic impact and energy consumption for the household activities, and a negative correlation with the number of guests and building size. By considering several buildings, this study allows to draw new and more general conclusions about effective sustainability strategies in the whole hotel sector in the Himalayan region. In particular, it shows that reducing impacts in the operation stage should be highly prioritized, focusing on reducing energy consumption and heat loss and shifting to the use of renewable energy sources. Keywords: Heat loss rate; Sustainable building; Sagarmatha National Park; Life Cycle Assessment; Life Cycle Costing; energy consumption
1. Introduction The building sector consumes a substantial amount of resources and energy and generates a considerable environmental impact worldwide (Scheuer et al., 2003; Vijayan & Kumar, 2005). Buildings represent long-term investments and are associated with environmental impacts over their entire life span (Cole, 1999). Therefore, lowering energy intensity and the environmental impacts of buildings is increasingly becoming a priority all over the world (Boscaro et al., 2015; Ferreira et al., 2015). One way of understanding the performance of buildings is by means of life cycle thinking (Passer et al., 2012). This means considering the entire life cycle of buildings and evaluating the impacts associated with the extraction, manufacturing and transportation of their construction materials, as well as the impacts of building construction, operation, maintenance and end of life stages (Ghose et al., 2017; Ortiz et al., 2009; Passer et al., 2012; Pittet et al., 2012). In this regard, tools such as Life Cycle Assessment (LCA) and Life Cycle Costing (LCC) are particularly fit for purpose ( Bhochhibhoya et al., 2017; Braganca Luis, 2012; Moschetti et al., 2015). These tools can support decision-making on environmentally friendly building technologies and materials and can help to minimize the environmental impact and reduce the capital cost of buildings, ultimately making them more sustainable (Gustavsson L, 2006; Passer et al., 2012; Petersen & Solberg, 2005; Zabalza Bribián et al., 2011). The environmental impact of buildings and building materials vary from country to country and from region to region (Pittet et al., 2012). Developing countries have generally less efficient manufacturing facilities compared to highly industrialized ones, and they show larger environmental impacts per unit of product delivered to the consumer (Asif et al., 2007; Buchanan A, 1994; Emmanuel, 2004; Pittet et al., 2012). Furthermore, the energy used for raw material extraction and processing, the transportation means and the distances traveled are different between developing and industrialized countries, which reflects on the overall environmental impacts of buildings in a life cycle perspective (Cole, 1999; Huberman N, 2008; Pearlmutter, 2007; Pittet et al., 2012). Information about the environmental impact of buildings in developing countries is currently limited, although they represent the most vulnerable areas on the world associated with climate change (Gentle & Maraseni, 2012; Pandit, 2013; Pouliotte et al., 2009). In developing countries like Nepal, modern construction techniques are slowly replacing traditional ones, a process that is intensified by the growth of tourism. While traditional buildings are commonly built using raw but locally available materials, modern ones intended to host tourists are technologically more advanced but less rooted in the culture as use imported materials (Bodach et al., 2014; Stevens, 2003). Development of tourism industry has become a major policy of the government of Nepal to increase employment and economic growth. The global contribution of the travel and tourism sector to Nepal’s Gross Domestic Product (GDP) was 3.7% in 2014 (World travel and tourism council, 2014), and as this sector is expected to grow, more buildings will be constructed to accommodate tourists. Previous research has investigated the environmental impacts of hotels but the focus has been limited to its energy consumption and to other countries than Nepal. There are abounds number of LCA case studies in the building sector in the literatures but limited number of LCA studies in the hotel building considering all life cycle stages. König et al. (2007) performed LCA of tourism resort with renewable materials in Portugal. While, Sisman, (1994) conducted the LCA
of package holiday offered by the tour operator Bristish Airways Holidays (BAH) in the Seychelles. The entire tourism sector in Penghu island of Taiwan were studied by Kuo and Chen (2009). As far as the authors are aware, only few LCA studies have been conducted in the LCA of hotel buildings; however, neither considered the full life cycle. For example, König et al. (2007) considered the design phase of the resort. Kuo and Chen (2009) considered the whole trip of one tourism service such as transportation, accommodation and recreation activity in Penghu island to conduct the LCA. Sisman, (1994) focused on construction of tourism infrastructures, infrastructure management, transport of goods and tourists within Seychelles. The Sagarmatha National Park and Buffer Zone of Nepal (SNPBZ) is the most popular destinations for trekking tourism in Nepal. The tourist influx grew from approximately 20014 visitors in 1998 to 37124 visitors in 2014 (Sagarmatha National Park Office, 2019) and is still increasing. Tourism is the main source of income and employs 60 – 80% of the local population (Salerno et al 2013; Posch et al., 2015). Although tourism has improved the economic conditions of the local communities (Manfredi et al., 2010; Salerno et al., 2010) it has simultaneously led to a fast growth in construction of buildings with negative effects such as loss of vegetation cover, incision, soil loss, and intensified resource use (Manfredi et al., 2010; Salerno et al., 2010; Nicholson et al., 2019). The increase in population of both locals and tourists also lead to the increase in energy demand. Moreover, the hotels are one of the most demanding energy consumers due to their 24- hours based operation for variety of facilities and functions provided (Dascalaki & Balaras, 2004; Deng, 2003; Filimonau et al., 2011). In the park, energy is supplied from locally available sources (firewood and animal dung) as well as commercial ones (kerosene, LPG, and electricity). The commercial sources of energy need to be transported to the park over long distances with high environmental and economic costs. The number of modernized concrete buildings is increasing in the Park. These buildings carry a substantial burden in terms of materials requirement and transport but are thermally efficient as use insulation materials such as glass-wool and polystyrene. Traditional buildings, on the other hand, use local materials with lower transport requirements and cost, but are less thermally efficient compared to the modern ones. Given these trade-offs, it is important to identify what are sustainable building designs that reduce the overall use of materials, energy, and transport in the park, and LCA and LCC are valuable tools in this sense (Ristimäki et al., 2013; Singh et al., 2011). Typically, LCA studies of buildings are conducted starting from primary data on a limited number of buildings or building construction alternatives, and this is especially the case for studies in developing countries (Almutairi et al., 2015; Ozolins et al., 2010; Pittet et al., 2012; Sonnemann, 2006). These LCAs provide important information regarding the details on the impacts in each life cycle stage of the building under analysis but, due to the intrinsic variability of the buildings, their results are difficult to generalize to e.g. all buildings in a certain region. In this context, it is important to understand the environmental and economic performance of different types of hotel buildings in the Himalayan region of Nepal, in order to minimize the impact of future building construction projects related to the increasing tourism in this region. Therefore, the objective of this study is to assess the environmental and economic impact of the hotel sector in Himalaya in a life cycle perspective by analyzing a large number of buildings and comparing their performance. Furthermore, the physical and technical performance of the hotel buildings were studied. By using data on several buildings of different type and located in
different settlements of the park, this study aims to provide results with higher general validity, making a step forward compared to the state of the art. 2. Materials and methods 2.1. Study design, study area and typical building types Bhochhibhoya et al. (2017) compared the life cycle environmental impacts and costs of three buildings in Sagarmatha National Park and Buffer Zone (SNPBZ): a traditional building, a semimodern one, and a modern one. However, the comparison was limited to three buildings and did not allow drawing generalizable conclusions. To give a more comprehensive picture on the environmental and economic aspects of the life cycle of Himalayan buildings, this study considers a larger sample of lodges of a different type located in all three Village Development Committees (VDC) of the Park. The same LCA modeling as in Bhochhibhoya et al. (2017) was applied to assess the environmental footprint and costs of all the buildings. In addition, new parameters such as heat loss rate, number of guests, and area of the lodges were measured that are then analyzed and documented in this study. Finally, a statistical analysis was performed to determine how solid are the differences between building types and which helps in drawing generalizable conclusions. The Sagarmatha National Park and Buffer Zone (SNPBZ) is located in the Solukhumbu district in the Eastern Development Region ranges in elevation from 2300 m at Surke to 8848 m.a.s.l. at the highest peak in the world: Mount Everest. The park covers an area of 1148 km2 and is centred on 27° 30’ 19” N by 86° 30’ 53”E. It The mean temperature of the coldest month, January, is 0.4°C and precipitation ranges from 450 – 1800 mm. The park is divided into three village development committees (VDCs): Namche (population > 1600), Khumjung as core areas in the north (population > 1800) and Chaurikharka (population > 2400) as a buffer zone in the south of the park (Government of Nepal 2011; Ngaire et al., 2019). Buildings in the park can be classified into three types: traditional, semi-modern and modern, as depicted in Fig 1.
Fig 1: Different hotel types and relative wall cross section (Photos and design by Silu Bhochhibhoya; sources:(Bhochhibhoya et al., 2017) The traditional type of building follows the ancestral house design that mainly used locally available materials such as wood, stone, and mud, and it is used both by local families and tourists. The modern type of buildings is built mainly for purpose of tourist accommodation to enhance the tourism and is constructed by using imported materials i.e. cement, steel rod and insulation materials like glass wool and polystyrene. The semi-modern type of buildings is the partial transformation of traditional into the modern building that uses wooden planks, dry stones and fewer amount of cement and mud for pointing, with limited or no insulation material (Bhochhibhoya, 2016). 2.2 Choice of parameters and data acquisition In this study, the performance of Himalayan buildings in the park was assessed by considering environmental, economic, and technical criteria (Table 1). Each criterion was quantified using different parameters, measured for each of the buildings under analysis. For the environmental criterion, energy consumption was chosen as there is evidence that the operational energy use and consequent GHG emissions has the greatest share (up to 90-95%) of the total building lifecycle impact in the hotel sector (Blengini, 2009; Filimonau et al., 2011; Rønning & Brekke, 2009). The energy consumption of different activities such as cooking, space heating, lighting, heating water, and use of power appliances during the operation stage of the building life cycle were considered in this study, cf. Bhochhibhoya et al. (2017). The hotel sector has significant seasonal variation on the energy consumption (Bhochhibhoya et al., 2017). This study included the environmental impact associate with the raw material acquisition and manufacture, construction, operation, maintenance and replacement of the building. The end of life of the building was not considered in this study due to the limited information on building
demolition, waste transportation and different waste treatment process (Bhochhibhoya et al., 2017). For the economic criterion, Life Cycle Cost (LCC) was chosen as the main parameter as it accounts all the cost associate to investment, operation, maintenance, and disposal of a building or building system over a period of time (Sieglinde K. Fuller, 1996). For the technical criterion, thermal performance of the building was chosen as heat loss rate of the building. The heat loss rate was chosen as a parameter to assess the fraction of the thermal power needed to compensate for the heat loss via building elements (Vihola et al., 2015). Moreover, building area and a number of guests were chosen as parameters as these have great influence on the energy consumption in the building and provide a good indication of building physical size. Table 1 The three assessment criteria and related measurement parameters Environmental criterion
Economic criterion
Energy consumption (kWh/person.night)
Material (euro)
Construction GWP impact (kg CO2-eq)
Labour cost (euro)
Operation GWP impact (kg CO2-eq)
Operation (euro)
Physical criterion
and
Technical
cost Heat loss rate (Watt/m3) Area (m2)
cost Number of guest (person/m2)
Maintenance GWP impact (kg CO2-eq) Total GWP impact (kg CO2-eq)
This study focused on buildings that have a commercial purpose such as hotels and lodges, as the growth of tourism is expected to an increase the number of such kinds of constructions in the study area. Primary data were collected from 45 buildings located in nine different villages of the Park. All these buildings are defined as “commercial” buildings because of their touristic purpose: they are accommodations for tourists during the holiday season (also known as tourist season). The tourist season starts from April-May and October–November. The number of sampled buildings was selected based on the total number of existing buildings in each settlement. The number of sampled commercial traditional buildings is lower than for the other building types. This is due to the fact that only traditional buildings providing both restaurant and lodging services were included in the analysis, in order to benchmark buildings with a similar and comparable function. Moreover, the settlements of the main tourist routes were given priority. The total numbers of existing and sampled buildings in nine different villages in the Park are given in Table 2 and Fig 2. Table 2 Total existing and sampled hotel building Traditional
Semi-modern
Modern
Total
Existing building
34
79
37
150
Sampled building
4
16
25
45
Fig. 2:
Sampling site in Sagarmatha National Park and Buffer Zone
A survey was conducted among hotel owners of the sampled buildings in the park and consisted of two separate questionnaires. A first questionnaire targeted the collection of inventory data required to perform the LCA and allowed to determine the type of material used in each building, the source of local material used, the quantity used, transportation distance and means, energy used for processing and transportation, and energy consumption during household activities. The second questionnaire focused on construction costs, operation cost, maintenance and replacement cost of the building and was prepared in order to gather data to perform the LCC. Construction costs included both material cost and transportation cost. The energy costs associated with building operation included costs for cooking, lighting, heating water, space heating and use of other electrical appliances (Bhochhibhoya et al., 2017). Maintenance costs was mainly associated with the cost of painting that is applied in the interval of ten years and costs associated with the replacement of materials during the entire life span of the buildings. In order to test the efficacy and level of understanding of the developed questionnaires, a trial survey was carried out in the small town of Nepal called Banepa, prior to the actual survey. The results from the trial survey showed that the questionnaire should be closed-ended with options.
Some irrelevant questions were identified and removed, and the trial survey helped therefore to refine the final questionnaire. The improved survey was then administered to the hotel owners in the sampled buildings in different settlements. The field survey in the Park was carried out during peak tourist season in the month of May/April 2014. Additionally to the survey, direct in situ measurement of the number and dimensions of rooms, doors, and windows, wall thickness, type of material used, were undertaken.. The source of commercial materials, type of transportation means and transportation distance from manufacturer to construction were also determined by directly interviewing hotel owners. 2.3 Data processing and statistical analysis
Primary data collected in the field survey were further processed to calculate the buildingspecific environmental and economic impacts and the thermal transmittance. Furthermore, statistical analysis was conducted in order to identify significant differences between building types and between life cycle stages for the life-cycle indicators. For the environmental and economic assessment of the sampled buildings, LCA and LCC were applied using both primary and secondary data. For modeling the manufacturing process of the used materials, the Eco-invent database v.3.3 –consequential model was used (Bhochhibhoya et al., 2017; Wernet et al., 2016). The LCA modelling were carried out in SimaPro 8 and the IPCC 2013 GWP 100a and ReCiPe methodology were used for the environmental impact assessment of the hotel sector. In this study, Global Warming Potential (GWP) was chosen to measure the life-cycle environmental performance in terms of carbon footprint. GWP is a mainstream indicator in LCA (Knauf Marcus, 2015) and recommended by IPCC since 1990 to convey the impact of greenhouse gas (GHG) emissions on climate change (Almeida et al., 2015; Houghton et al., 1990; Tanaka et al., 2010). In particular, GWP with a time horizon of 100 years was calculated for the construction, operational, and maintenance stages as well as for the total life cycle, using the IPCC 2013 and Recipe impact assessment method, cf. Bhochhibhoya et al. (2017). The heat loss rate was determined by the thermal transmittance of the materials, net area of the building element and the difference in the temperature inside and outside of the building. The thermal transmittance (also known as U-value) was defined as the rate of heat transfer in watts per square meter of area per degree difference in temperature. The U-value is calculated from the thermal resistance of the different materials, cavities and layers of a building element, such as a wall, that oppose the transmission of heat by varying amount (McMullan, 2012). Thermal resistance (R) is a measure of the opposition to heat transfer in a building element for a layer of material of a particular thickness can be calculated by (1): =
(1)
where R is the thermal resistance (m2K/W); d is the thickness of the material (m); λ is the thermal conductivity of the material (W/m K). The thermal resistance (R) of the consecutive layers in a building element, the wall as an example, is calculated as in equation (2): = + + +
+ +
(2)
where, and represent the outside and inside surface resistance respectively due to the connection on the surface of the wall. The thermal transmittance (U-value) (W/m2K) is calculated as the reciprocal of the thermal resistance using equation (3), e.g. for the case of a wall: =
(3)
After calculating the thermal transmittance of different building elements, the rate of heat loss for instance for a wall is calculated by equation (4): = × × ∆"
(4)
where A is the net area of the wall (m2); U is the thermal transmittance coefficient (W/m2K) and ∆" represents the difference between outside and inside temperature of the wall (K). The overall heat loss of the building is expressed by equation (5):
= + + + # + #
(5)
Following the above methods, the heat loss rate was computed for each of the buildings included in the survey in the study area. To compare the heat loss of different buildings in different villages, the rate of heat loss was calculated per cubic meter. Having proper insulation, thermally efficient buildings reduce the heating needs as compared to other building types. Thus, the lower is the heat demand, the higher is the efficiency of the building. Buildings are expected to have variable performance due to the different design and material used, but it is not clear if different building types perform significantly different from a statistical point of view. For this reason, a statistical analysis was conducted to get a broad overview of the overall performance of the entire hotel sector in the Park (S. Bhochhibhoya, 2016). One-way, between-subjects ANOVA with unbalanced groups was, therefore, applied to investigate the differences in each parameter between the building types. A Tukey HSD test was performed to determine which groups in the sample differ significantly from each other. Furthermore, a oneway ANOVA was conducted in order to compare the effects of environmental, economic and technical criteria on the different life cycle stages (construction, operation, maintenance and replacement stages) of the buildings in the Park. Thus, such analysis highlights the presence of statistically significant differences between the means of environmental, economic and technical parameters on the different life cycle stages of the building in the Park. Furthermore, correlation analysis was conducted to measure the strength of association between three criteria (environmental, economic and technical) on the different life cycle stages of the buildings in the Park. Pearson correlation coefficient was used to measure the strength and direction of the linear relationship between pairs of variables. Statistical Package for the Social Sciences (SPSS), version 16 was used to conduct the statistical analysis. 3. Results and Discussion 3.1 Sustainability performance of the different building types:
Table 3 shows the results obtained for the parameters measured and calculated for the entire hotel sector of the Park for the year 2014, whereas Table 4 reports the ANOVA results regarding differences in these parameters between building types.
Table 3 Performance of buildings according to the parameters investigated in the study Modern
Semi-modern
Traditional
Environmental criterion
GWP construction
0.12±0.13(25) (0.03 - 0.54)
0.08±0.04(16) (0.03-0.54)
0.09±0.03(4) (0.06-0.12)
GWP (kg CO2eq/person.night)
GWP operation
4.41±2.28(25) (1.21 - 10.28)
5.73±3.23(16) (2.13-13.25)
7.76±2.35(4) (5.67-10.63)
GWP maintenance & replacement
0.09±0.05(25) (0.03 - 0.22)
0.11±0.05(16) (0.04-0.19)
0.15±0.05(4) (0.10-0.22)
GWP total
4.61±2.29(25) (1.31 - 10.48)
5.92±3.27(16) (2.22-13.45)
8.54±3.21(4) (6.01-12.95)
Economic criterion
Cost construction
0.09±0.05(25) (0.03 - 0.24)
0.07±0.04(16) (0.03-0.16)
0.08±0.03(4) (0.05-0.11)
Cost (Euro/person.ni ght)
Cost operation
4.99±3.84(25) (1.21 - 18.46)
5.34±3.84(16) (1.48-13.01)
8.04±6.46(4) (2.83-16.70)
Cost maintenance & replacement
0.66±0.41(25) (0.20 - 1.75)
0.55±0.27(16) (0.19-1.05)
0.68±0.19(4) (0.44-0.85)
Cost total
5.74±3.91(25) (1.54 - 19.43)
5.97±3.87(16) (3.87-13.75)
8.81±6.46(4) (3.80-17.40)
Energy consumption (kWh/person.night)
7.39±4.97(25) (1.68 - 22.49)
10.06±7.43(16) (1.47-25.94)
14.78±5.99(4) (7.60-19.83)
Heat loss rate (Watt/m3)
36.80±5.49(25) (25.23-45.11)
48.21±8.38(16) (39.13-61.40)
47.25±4.36(4) (41.24-53.37)
Number of tourist (person/year)
845 ±385 (25) (240-1680)
498 ±268 (16) (240-1200)
318 ±120 (4)
Area (m²)
597.9±240(25)
325.76±157(16) (159 -760)
304±199(4) (1650-650)
Physical and Technical criterion
(228-1052)
(192-432)
Mean±Standard deviation (n) (minimum – maximum) Environmental criterion:
The operation stage has the largest share of total GWP, (97% of total GWP on average) due to the energy use for different household activities, and this confirms previous results (Bhochhibhoya et al., 2017). This conclusion differs from the conclusion of the previous study where only three buildings were analyzed and the modern one had the highest impact (Bhochhibhoya et al., 2017). This shows how important it is to account for the intrinsic variability of the buildings in the Park, which is substantial, and how difficult it is to generalize LCA results taken from a small sample of only three buildings. It also shows that considering a larger sample of 45 lodges of different building types gives a more nuanced and comprehensive picture of the life cycle impact of buildings in the park, thus providing a better support for decision making on sustainable construction practices in the study area. In the traditional building, the GWP of operation stage is on average 76% higher than that of modern building that uses kerosene and LPG for cooking and electricity for the space heating. The GWP of operation stage in traditional building is 35% higher than that of the semi-modern
buildings. In traditional buildings, the average energy consumption for different household activities consists of 12.15 kWh/person.night. It is important to highlight that traditional buildings depend largely on firewood and cattle dung for cooking and space heating in stoves, which are an inefficient combustion process. The traditional building mostly used the open fireplace for cooking (Salerno et al., 2010), with more heat waste that is utilized for space heating, however, requiring more energy for cooking. Therefore, the reduction of impacts in the operation stages in the traditional buildings lies in a reduction of impacts in the operation stage (Bhochhibhoya et al., 2017). In all building types in the study area, the construction stage contributes only with 1% of the total GWP and 2% by maintenance and replacement stage. Even though in this study, construction, maintenance, and replacement stage have less environmental and economic impacts compared to operation stage, there is still a room for improvement in these stages. Since progress in energy efficiency is already mature, the next step is improving the efficiency in the construction stage. As emphasized in a previous study (Bhochhibhoya, 2016; Bhochhibhoya et al., 2017), it can be concluded that use of local materials along with the proper insulation and use of renewable energy is recommended for sustainable building design in the Himalayan region. This may be misleading since the result of other impact categories such as eutrophication, toxicity etc. are left out. A previous study (Bhochhibhoya et al., 2017) where LCA and LCC of three buildings are presented in detail shows that the impact categories of Ozone Depletion Potential, Eutrophication Potential, Acidification Potential, Photochemical Ozone Creation Potential, and Particulate Matter Formation Potential follow the same trend as GWP. It was, therefore, considered redundant to analyze all of the impact categories, and this lead to the selection of GWP as the only parameter to compare the life-cycle environmental impacts of the buildings. Despite interesting, water footprint was not included in this study, mainly due to two reasons. Firstly, it was difficult to retrieve water use information, connected with the specific type of building and not associated to direct consumption from the guests. Secondly, average footprint would be very much influenced by the specific diets offered by different restaurant services (Borsato et al., 2018) but such analysis goes beyond the scopes of the present work. Economic criterion:
Results of the life cycle costs of three building types for a lifespan of 50 years show that the traditional buildings acquire on average the highest cost, 53% higher than modern buildings and 47% higher than semi-modern building. The average operation cost is higher in traditional buildings as a larger amount of energy is consumed in different household activities. The operation stage is responsible for the largest share of total cost by 90%. The studies by Bhochhibhoya et al., (2017), Cuéllar-Franca and Azapagic (2012), Pittet et al. ,(2012) also confirmed that the impact of operation stage ranges between 80 and 90%. Average construction and replacement cost are relatively low in all building types, compared to the operation stage. Physical and Technical criterion:
The average energy consumption for household activities is dominant in the traditional buildings, which is twice as higher than that of modern buildings and 1.5 times higher than that of the semimodern buildings. It is important to note that firewood is still the dominant source of energy for cooking and space heating in a traditional building, where it covers 90% of total energy demand. In addition, stoves used in the Park have an efficiency of just 11.6 % (Sulpya, 1996), that results
in 88.4 % heat waste (Bhochhibhoya, 2016). As a result, the heat waste from cooking is mainly utilized for space heating as most of the traditional building has combined kitchen and living room. The study estimates that the semi-modern buildings are less thermal efficient, as they demand more heat on average (48.21 Watt/m3) to keep the room warm. The materials and thickness of the walls used are less efficient in retaining heat within these building as compared to modern and traditional buildings. The heat demand is, therefore, high in buildings of this type due to the limited insulation used. On the other hand, traditional and modern buildings have high resistance offered by the wall material and use of proper insulation resulting in a lower consumption of energy for the space heating. Technology has greatly influenced building construction methods in the Himalaya. The use of the imported insulating material in walls and the use of double glazed window system has lowered the energy demand for space heating in the modern buildings in the study area as compared to traditional and semi-modern building. Traditional buildings are rich in traditional knowledge as they are designed respective to outdoor climate also called climate responsive design or solar passive building design. With a passive design, a reduction in the need for heat energy and a more comfortable thermal indoor environment can in principle be obtained (Bodach et al., 2014; Rijal et al., 2010). The study by Rijal et al., (2010) claimed that the traditional buildings are well adapted to the local climate that is mainly designed with the high thermal mass of the wall, floor and roof (Stevens, 2003), thick wall (0.5-1 meter) and small opening that uses local materials for construction and insulation. However, the amount of local material such as mud, stone, and wood used per square meter in the traditional building is much higher compared to modern and semi-modern buildings (Houghton et al., 1990). The intensified use of these resources in the park results in the vulnerability in the high-mountain landscape. Therefore, it is important to construct the building using locally available materials, based on rational selection processes and avoiding the spawning of building and excessive construction in the area (Morel et al., 2001). Differences in the number of hosted tourists and area are also significant between building types. Modern buildings host more guests on average compared to semi-modern and traditional buildings. In terms of average building size, the modern building is bigger in size compared to the semi-modern and traditional buildings. Table 4 shows the testing for differences between building types on environmental, economical, physical and technical parameters. Analysis of variance (ANOVA) is a statistical technique to test if the parameters we considered in this study have significant different or not from each other. ANOVA checks the impact of all parameters by comparing the means of different samples to prove if all the parameters are equally effective or not. ANOVA uses F-statistic to measures if the means of different samples are significantly different or not. Lower the F-ratio, the more similar are the sample means. Table 4 ANOVA results when testing for differences between building types on all parameters. ANOVA GWP construction (kgCO2-
Between Groups
Sum of Squares
df
Mean Square
F
Sig.
.013
2
.007
.597
.555
eq/person.night)
GWP operation (kgCO2eq/person.night)
GWP maintenace & replacement (kgCO2eq/person.night) GWP total (kgCO2eq/person.night)
Cost construction (Euro/person.night)
Cost operation (Euro/person.night)
Cost maintenance & replacment (Euro/person.night) Cost total (Euro/person.night)
Energy consumption (kWh/person.night)
3
Heat loss rate (Watt/m )
Number of tourist
Within Groups
.460
42
.011
Total
.473
44
Between Groups
46.397
2
23.198
Within Groups
297.716
42
7.088
Total
344.113
44
Between Groups
.016
2
.008
Within Groups
.117
42
.003
Total
.134
44
Between Groups
59.269
2
29.634
Within Groups
317.112
42
7.550
Total
376.381
44
Between Groups
.001
2
.001
Within Groups
.092
42
.002
Total
.093
44
Between Groups
32.346
2
16.173
Within Groups
700.081
42
16.669
Total
732.427
44
Between Groups
.127
2
.063
Within Groups
5.196
42
.124
Total
5.322
44
Between Groups
33.012
2
16.506
Within Groups
716.892
42
17.069
Total
749.904
44
Between Groups
216.670
2
108.335
Within Groups
1528.255
42
36.387
Total
1744.925
44
Between Groups
1409.956
2
704.978
Within Groups
1852.665
42
44.111
Total
3262.621
44
Between Groups
1740032.640
2
870016.320
Within Groups
4681906.560
42
111473.966
Total
6421939.200
44
Between Groups
997162.370
2
498581.185
Within Groups
1761945.247
42
41951.077
Total
2759107.617
44
Area (m2)
3.273
.048
2.941
.064
3.925
.027
.280
.757
.970
.387
.513
.603
.967
.389
2.977
.062
15.982
.000
7.805
.001
11.885
.000
Environmental criterion: The one-way ANOVA was conducted to compare the effect of the building type on the environmental performance of modern, semi-modern, and traditional building types. There was a significant effect of the building type on the total GWP of the buildings at the p<0.05 level [F( 2,42) = 3.92, p = 0.027]. A significant difference between building types in terms of GWP related to operation stage was observed at the p<0.05 level [F(2,42) = 3.27, p = 0.048]. However, there was not a significant effect between building types in terms of GWP related to construction [F(2,42) = 0.59, p = 0.555], maintenance and replacement stages [F(2,42) =2.941, p = 0.064]. The Turkey test gave evidence of a significant difference between modern and traditional building on total GWP with p-value 0.029. However, no significant difference was found between the semi-modern buildings and the other building types.
Similarly, in case of operation stage, the Turkey test highlighted a significant difference between modern and traditional building (p-value=0.06), whereas there is no significant difference between semi-modern buildings and other building types. Economic criterion: The one-way ANOVA was conducted to compare the effect of building type on the life-cycle costs of the buildings in the Park. No significant effect of building type on the total life cycle costs was observed [F(2,42) = 0.967, p = 0.389). Neither was the effect of building type on the costs related to other life cycle stages proven to be significant by the ANOVA test, due to the high variability in costs and the lower number of traditional buildings in the sample which may not give an accurate overview of this building type and limits the significance of the test itself. Physical and Technical criterion: The one-way ANOVA was conducted to compare the effect of different building type on the physical and technical parameters of the buildings in the Park. There was a significant effect of building type on the heat loss rate, number of tourist and the area of the buildings at p<0.05 level: [F(2,42) = 15.982 ,p = 0.000] for the heat loss rate, [F(2,42) = 7.805, p = 0.001] for the number of tourists and [F(2,42) = 11.885, p = 0.000] for the area of the building. 3.2. Correlation between different building parameters:
Fig 3 shows the correlation matrix calculated for all building parameters. When the Pearson’s Rvalue is close to 1, a strong correlation is observed between two variables. A positive sign indicates a direct relationship while a negative sign indicates an inverse relationship. As expected, results show that total GWP is strongly correlated with operation stage. The reason is that the operation stage accounts for the largest share of the carbon footprint in a building’s life cycle. This is in accordance with results reported in previous studies (Asdrubali et al., 2013; Bhochhibhoya et al., 2017; Cuéllar-Franca and Azapagic, 2012; Ortiz et al., 2009). Similarly, the total GWP is strongly positively correlated with total life cycle costs as well as the operation costs and energy consumption. This indicates that the operation stage associated with energy consumption is highly responsible (Bhochhibhoya, 2016) for the largest share of environmental and economic impacts.
Fig. 3: Correlation matrix of different building parameter. The acronyms of con: construction; ope: operational; rep: replacement; tot: total; cons: consumption Heat loss rate of the building is negatively correlated with all the other parameters, although this correlation is very weak. The heat loss rate of the buildings mainly depends on the type and the size of the materials used in the building, and therefore the correlation is higher with construction stage-related parameters. Even though the environmental and economic impacts are higher in the construction stage than in the operation, maintenance and replacement stage, in the modern building, the efficient use of fuels and the insulation helps to reduce the GWP and the cost in operation stage. The efficient use of LPG (Liquid Petroleum Gas) and Kerosene and use of insulation such as glass-wool and polystyrene in the building envelope help the modern building reducing energy consumption in cooking and space heating thus consequently reducing the environmental and economic impact in operation stage. As expected, the number of guests is negatively correlated with GWP, life cycle cost, operation, maintenance and especially replacement stages. The higher is the number of the guests in the hotel, the lower is the environmental and economic impact as this is measured per guest and per night stay and obviously, this means that the share of impacts per person decreases with the
increasing number of guests. It is interesting to see the strong correlation between a number of guests and replacement costs, showing that hosting people “consume” the building and leads to higher maintenance requirements. The results confirm also that the number of guests is positively correlated with the size of the building. That indicates, the larger is the size of the building, the higher is the number of guests (S. Bhochhibhoya, 2016). 4. Conclusions The main aim of this study was to get a comprehensive overview of the environmental and economic performance of the entire hotel sector in the Sagarmatha National Park and Buffer Zone, including a life cycle perspective. In addition to that, the buildings were also analyzed based on physical and technical parameters such as energy consumption, heat loss rate and size of the lodge. This analysis should inform and promote future sustainable construction practices in the area. Results show that, on average, traditional buildings have the highest life cycle GWP and cost compared to modern and semi-modern building types. In the traditional building, the GWP of the operation stage is higher than other type of buildings as the traditional buildings depend largely on the conventional energy source such as firewood and cattle dung for cooking and space heating. Moreover, the fireplace used for cooking and space heating has low efficiency. Therefore, it is recommended that energy efficient cooking and heating stoves should be used in traditional buildings to achieve it. The operation stage is responsible for the largest share of carbon footprint and of operational cost. The high carbon footprint and high cost in the operation stage are associated with energy consumption in different household activities. This can be doable by using the more efficient stove, heating stove, light bulb and use of renewable energy from solar PV, wind and hydropower. The obtained results show that the semi-modern buildings are less thermal efficient compared to modern and traditional buildings, as they demand more heat on average to keep the room warm. This is due to the limited insulation used as well as the less efficient material and thickness of the wall. The main improvement would be to use local material with proper insulation. The different insulating materials have different thermal conductivity, thus different thermal performance. Accordingly, the selection of insulation materials by local people determines the energy demand for space heating. The local people can either chose to install expensive and imported glass wool and cheap polystyrene or locally available mud plaster to reduce the heat demand. The initial investment in insulation could save the additional future expenses in energy for space heating. It is recommended to insulate using locally available material that are cost effective and have short payback period rather than using expensive and imported insulation materials. There are indeed also socio-cultural factors that are not taken into account by this study and that might make the traditional buildings a valuable or even preferable option. An example is the need of preserving the ancestral building design that is typical of the region and thus an element of the local culture and landscape. The study of the cultural heritage, health and safety, socioeconomy repercussion from the sustainable building are important indicators to study in the
future. Apart from LCA and LCC, other tools like S-LCA and water footprint could be useful for assessing the sustainability of the building sector. Another limitation of the study is an unbalanced sample of buildings for each type as only four traditional buildings were sampled. Most of the traditional-commercial buildings in the Park are now used only as a restaurant and do not provide lodging options. Thus, in order to have a proper comparison among different building types, these buildings were not included in the sample. The results on traditional building could vary with the increased size of the sample. On the basis of this study, it is concluded that a sustainable building design with low energy demand, high thermal efficiency and use of local materials with proper insulation is recommended for buildings in the park. Well insulated, thermally efficient buildings would reduce the use of heating and ultimately the GWP. In addition, the use of renewable energy and use of energy efficient stoves, heating stoves, and light bulbs should be encouraged in the Park. It is necessary to combine the modern technologies with traditional knowledge for achieving a truly sustainable building design. The traditional building style should be maintained to coexist together with modern living and comfort. It is important to take in account the relevant solutions that require a balanced mix of tradition and modernity in order to provide for the highly delicate mountainous ecosystems. The outcome of this study can assist both local people and policy makers in the hotel building in steering decision processes for future development of tourism facilities construction. This research outcome can be extrapolated to other mountainous regions of low-income countries as we aspect the similar trade offs between using efficient but imported costly materials versus local cheap but less efficient ones.To optimize the sustainability in the buildings under the LCA perspective, it is important to accounts building’s facade solution (insulation materials and type and width of masonry), use of renewable energy. Therefore, it is important to conduct the detail studies on the alternatives energy source such as solar, wind, hydropower to optimize the building sustainability.
Acknowledgments The authors thank Fondazione Cassa di Risparmio di Padova e Rovigo for the funding to conduct Ph.D. project at the Department of Land, Environment, Agriculture, and Forestry of the University of Padova. The authors are thankful to Ramesh Kumar Maskey for his help throughout the project work. The authors are also thankful to Shital Kumar Gupta, Michela Zanetti, Peter Gill for their help in reviewing the paper.
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Highlights • Sustainability of modern, semi-modern and traditional hotel buildings in Himalayan region • Analysis of life cycle based GWP, life cycle costs, energy consumption, thermal efficiency of the hotel buildings • Traditional hotel buildings exhibit high carbon footprint and life-cycle cost over 50 years • Lower energy consumption and heat loss rate and higher renewable energy are needed • Reduction of impacts in the operational stage is recommended for all buildings types
Declaration of interests ☒ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. ☐The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: