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Evaluating environmental impacts of alternative construction waste management approaches using supply-chain-linked life-cycle analysis Murat Kucukvar, Gokhan Egilmez and Omer Tatari Waste Manag Res 2014 32: 500 originally published online 22 May 2014 DOI: 10.1177/0734242X14536457 The online version of this article can be found at: http://wmr.sagepub.com/content/32/6/500
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research-article2014
WMR0010.1177/0734242X14536457Waste Management and ResearchKucukvar et al.
Original Article
Evaluating environmental impacts of alternative construction waste management approaches using supplychain-linked life-cycle analysis
Waste Management & Research 2014, Vol. 32(6) 500–508 © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/0734242X14536457 wmr.sagepub.com
Murat Kucukvar1, Gokhan Egilmez2 and Omer Tatari1
Abstract Waste management in construction is critical for the sustainable treatment of building-related construction and demolition (C&D) waste materials, and recycling of these wastes has been considered as one of the best strategies in minimization of C&D debris. However, recycling of C&D materials may not always be a feasible strategy for every waste type and therefore recycling and other waste treatment strategies should be supported by robust decision-making models. With the aim of assessing the net carbon, energy, and water footprints of C&D recycling and other waste management alternatives, a comprehensive economic input–output-based hybrid life-cycle assessment model is developed by tracing all of the economy-wide supply-chain impacts of three waste management strategies: recycling, landfilling, and incineration. Analysis results showed that only the recycling of construction materials provided positive environmental footprint savings in terms of carbon, energy, and water footprints. Incineration is a better option as a secondary strategy after recycling for water and energy footprint categories, whereas landfilling is found to be as slightly better strategy when carbon footprint is considered as the main focus of comparison. In terms of construction materials’ environmental footprint, nonferrous metals are found to have a significant environmental footprint reduction potential if recycled. Keywords Construction waste management, environmental footprint, hybrid life-cycle assessment, supply chain, sustainability, US buildings
Introduction Today, recycling of construction waste materials has been considered as one of the best strategies in minimization of construction and demolition (C&D) debris (Tam and Tam, 2006). However, recycling of construction waste materials will not always be a feasible for every waste type, and therefore these recycling strategies should be supported by robust decisionmaking models. Life-cycle assessment (LCA) is a popular tool to analyse the sustainability of waste management systems, and has gained a tremendous interest over the last few years to develop environmentally sound waste management strategies. There are mainly three types of LCA models utilized for environmental impact assessment of waste management systems, namely: process LCA (P-LCA), economic input–output LCA (EIO-LCA), and hybrid LCA. Among the LCA methodologies, P-LCA has been widely used to analyse the environmental performance of solid waste management systems. By using P-LCA as the methodology, several LCA frameworks have been developed to be used as robust LCA models: for instance, Organic Waste Research (ORWARE; Eriksson, 2005), Integrated Solid Waste Management (ISWM; Christensen et al., 2007), Municipal Solid Waste (MSW) Decision Support Tool (MSW-DST; Solano et al., 2002), Waste Analysis Software Tool for Environmental
Decisions (WASTED; Diaz and Warith, 2006), and Waste Reduction Model (WARM), developed by US Environmental Protection Agency (EPA) (Weitz et al., 2002). In addition to the aforementioned P-LCA-based waste management systems’ environmental impact assessment frameworks, several studies have also been conducted by using P-LCA methodology, where the main focus was solely on the process-specific environmental impacts of waste management systems. Examples include McDougall and Hruska (2000), Christensen et al. (2007), Finnveden et al. (2007), Thorneloe et al. (2007), Villanueva and Wenzel (2007), Merrild et al. (2008), Eisted et al. (2009), Damgaard et al. (2009), Astrup et al. (2009), Larsen et al. (2009), Johnson et al. (2008), Manfredi and Christensen (2009), Ortiz et al. (2010), Coelho and de Brito (2013), and (Song et al., 2013).
1Department
of Civil, Environmental, and Construction Engineering, University of Central Florida, Orlando, FL, USA 2Department of Industrial and Manufacturing Engineering, North Dakota State University, Fargo, ND, USA. Corresponding author: Gokhan Egilmez, North Dakota State University, Fargo, ND 58102, USA. Email: [email protected]
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Kucukvar et al. See Tam and Tam (2006) for a review of recent developments in LCA associated with construction industry, including the recycling materials. Compared to studies that utilized P-LCA, only a handful of studies have analysed different solid waste management systems using EIO-LCA. EIO-LCA models basically quantify the environmental impacts by integrating macro-level economic input and output tables with environmental impact multipliers (Egilmez et al., 2013). Augmenting the input–output tables with flows of waste, Japan has led the development of solid waste extended EIOLCA for analysing different waste management alternatives from a life-cycle perspective (Nakamura and Kondo, 2002). This model can analyse environmental impacts and economic impacts such as sector output and employment of different waste treatment alternatives. Nakamura and Kondo (2006) developed the waste input– output LCA model and used it to compare traditional waste treatment strategies with recycling for electrical home appliances. Huang et al. (1994) used EIO-LCA model to analyse the direct and indirect impacts of regional solid waste generation and treatment systems. This model quantifies the effects of different waste management systems on economic and environmental factors. DiStefano and Belenky (2009) developed a hybrid LCA model to compare energy consumptions and greenhouse gas (GHG) emissions for landfilling of MSW to biodegradation of MWS in anaerobic digesters. This study used a combined application of EIO-LCA and P-LCA to take advantage of both models for an in-depth environmental analysis of different waste treatment strategies. In another study, EIO-LCA methodology was used to analyse the environmental burdens associated with the collection, recycling, and disposal of MSW (Morris, 2004). The researchers assessed and compared environmental impacts from kerbside collection for recycling, waste processing, and transportation of recyclable materials collected from households and/or businesses against environmental impacts associated with kerbside collection and disposal of mixed solid waste. In addition, Pimenteira et al. (2005) analysed the social and economic implications of solid waste management using an input–output methodology. This study quantified the energy savings obtained from recycling as well as the avoided emissions of GHGs. On the other hand, Choi et al. (2010) utilized the EIOLCA to analyse the economic impacts of electronic waste in Atlanta, Georgia. In their study, researchers developed a regional economic model that explicitly incorporated the flow of recyclable commodities and related industries within the input–output framework. This modelling approach identified structural differences and relevant economic impacts in the process of integrating the reuse of recycled materials within the economic input–output model. In another study, Huang et al. (2009) used EIO analysis to thoroughly estimate the entire upstream and downstream carbon emissions. The results of the literature review indicate that none of the LCA-based decision support tools within waste management used an input–output methodology to analyse the indirect
resource and energy savings through recycling and the indirect GHG reductions associated with using recycled materials to produce new industrial products from building-related C&D materials. However, recycling of these waste materials will minimize primary and secondary industrial activities to produce virgin materials and might result in considerable environmental savings for various C&D waste management strategies in the USA. Therefore, the current study targets this gap and offers a comprehensive C&D waste management strategy for conventional and green buildings.
Scope of the study As a comprehensive solution for the assessment of construction waste industries’ contribution to GHG emissions from recycling, incineration, waste collection and transportation, and landfill, the extended life-cycle system boundary is proposed to analyse the direct and indirect environmental impacts of different waste management systems using a comprehensive EIO-LCA modelling. We developed a hybrid LCA model, where P-LCA model is combined with the EIO analysis. In this approach, onsite (process) environmental impacts of each waste management system is collected, while higher-order (supply chain) impacts, including the production of energy or material inputs, are covered by the EIO analysis. Such a hybrid LCA approach enables us to quantify the direct and indirect environmental impacts of C&D management systems. In addition, this proposed model will enable the policy makers to understand indirect environmental savings related to recycling of different waste materials. For example, recycling aluminium will result in GHG emissions during recycling process. However, recycled products will be used as secondary materials in the factory and will minimize several resource inputs as well as indirect industrial processes to produce virgin materials. We believe that that expanded system boundaries and inclusion of all upstream supplier effects will be critical to holistically evaluate the environmental impacts and savings related to waste recycling. In this paper, three main waste management processes such as recycling, incineration with heat recovery, and conventional landfilling were analysed for nine different building-related C&D waste materials: concrete, wood, nonferrous and ferrous metals, cardboard, plastic, glass, paper, and cardboard. The environmental impacts associated with management of these waste materials are considered as global warming potential (eqv-CO2), primary energy consumption (TJ), and water withdrawals (m3). For the recycling, collection and transportation of C&D, materials recovery process, and producing new products from recycled materials are holistically investigated under the scope of this research. For incineration, transportation of waste to incineration facility, processing of waste, and energy recovery from waste is analysed. Lastly, the environmental impacts related to conventional landfilling is quantified for the life-cycle phases of transportation of C&D to landfill and landfilling of each C&D waste materials.
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Hybrid LCA model development EIO-LCA model consists of the 428 sectors’ input–output tables for the US economy augmented with sector-level water use, energy consumptions, and GHG emissions vectors have been used. Hence, the carbon, energy, and water footprints of C&D waste treatment alternatives has been investigated from a holistic perspective. EIO analysis considers the sector-level interdependencies and represents sectoral direct requirements which are represented by matrix A (Kucukvar and Tatari, 2013). This matrix basically includes the US dollar value of inputs required from other sectors to produce US$1 worth of output. The total output of a sector in this economic model with a final demand of f can be expressed as (Joshi, 1999):
x = (I – A)–1 f (1)
where x represents the overall outputs of sectors, I is the identity matrix, and f is the final demand vector representing the change in a final demand of desired sector. After the EIO model has been established, overall environmental impacts can be calculated by multiplying the economic output of each industrial sector by the environmental impacts associated with per dollar of output. A vector of environmental outputs can be formulated as follows (Hendrickson et al., 2006):
Oi = EiX = Ei (I – A)–1 f (2)
where Oi denotes the total environmental outputs (direct plus indirect) vector for the environmental impact category of i, and Ei represents a diagonal matrix which consist of the environmental impact per dollar of output for each industrial sector. In this analysis, we developed a hybrid LCA model considering the environmental impacts related to waste management alternatives. The proposed hybrid LCA model quantifies total environmental burden associated with the waste management systems which is presented as follows:
ri = Ei (I – A)–1 f +Qiei (3)
where ri is the total environmental impact, which is the sum of environmental burdens associated with the production of resource inputs (including all supply chains) and the direct environmental burdens associated with waste treatment processes, Qi is the total input requirements for a process, and ei is unit environmental impact factor associated with the consumption of Qi. For instance, GHGs are highly emitted during the transportation of C&D wastes. For C&D transportation, diesel is consumed as a fuel during the transfer of C&D waste from construction site to material recovery facility or landfill area. In our hybrid LCA model, equation 2 quantifies the direct plus indirect GHG emissions considering the whole supply chain of diesel production. In addition, tailpipe GHG emissions (process emissions) are also taken into account using equation 3 which represents the mathematical framework of developed hybrid model. All other environmental
burdens for C&D waste management alternatives are quantified by the same hybrid LCA model.
Data collection In this paper, several important life-cycle phases, including material production from virgin and recycled products, transportation, material recovery, incineration with heat recovery, and landfilling, were analysed for the nine building-related C&D waste materials. In addition, six major building sectors consisting of residential renovation, residential new construction, residential demolition, commercial renovation, commercial new construction, and commercial demolition have been analysed, and the net carbon, energy, and water footprints associated with management of C&D materials coming from these building sectors were quantified using the proposed comprehensive LCA methodology. The amount of C&D waste and waste composition data for each building sector was gathered from the earlier joint studies of Franklin Associates (1998) and the US EPA (2003). Several studies and waste LCA tools have been used to collect the life-cycle inventory data for different C&D waste management alternatives. First of all, the process data for producing each building material from virgin resources and recycled C&D waste are compiled by Christensen (2011). This detailed data set included all electricity, fuel, and other resource inputs, the amount of residues for landfilling, and atmospheric GHG emissions associated with producing building materials from recycled or virgin materials. In addition, electricity and fuel consumption and GHG emissions data for material recovery processes were gathered from the LCA study of Denison (1996)). The US EPA’s WARM model has been used for quantifying the emissions related to incineration and landfilling of each C&D material (US EPA, 2010), and energy production efficiency and electricity generation related to incineration of cardboard, paper, plastic, and wood waste are obtained from the WASTED model developed by Diaz and Warith (2006). For transportation of C&D waste from construction site to material recovery facility and from construction site to landfill area or incineration plant, a transportation distance of 50 km is assumed for each transfer process. Fuel consumption and emission factors data are provided by National Renewable Energy Laboratory (NREL) life-cycle inventory database for a diesel-powered single-unit truck (NREL, 2010). For the EIO-based environmental impact analysis, the producer prices of each energy and material input are calculated by using several publicly available data from the US Department of Energy, US Energy Information Administration, US EPA, and US Geological Survey. After calculating the cost of each input requirement, direct plus indirect environmental burdens associated with recycling and other treatment options were quantified by using the EIO-LCA tool, which was developed by the Green Design Institute at Carnegie Mellon University (2002). For example, residential renovations sector produced 71×103 Mt of concrete waste, and approximately 16×103 kWh of electricity
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Kucukvar et al. Table 1. Water savings (m3).
Table 2. Energy savings (TJ).
Material
Recycling
Landfilling
Incineration
Material
Recycling
Landfilling
Incineration
Concrete Drywall Cardboard Paper Glass Plastic Ferrous metal Nonferrous metal Wood
–2.35E–03 5.87E–04 1.49E–02 7.34E–02 1.39E–02 1.43E–01 1.93E–02 8.33E–01 –1.95E–03
–8.14E–02 –8.14E–02 –8.14E–02 –8.14E–02 –8.14E–02 –8.14E–02 –8.14E–02 –8.14E–02 –8.14E–02
NA NA –3.55E–03 –3.55E–03 NA –3.49E–03 NA NA –3.55E–03
Concrete Drywall Cardboard Paper Glass Plastic Ferrous metal Nonferrous metal Wood
7.100E–04 1.490E–03 5.260E–03 2.069E–02 5.000E–03 3.919E–02 6.440E–03 2.209E–01 8.200E–04
–7.231E–05 –7.231E–05 –7.231E–05 –7.231E–05 –7.231E–05 –7.231E–05 –7.231E–05 –7.231E–05 –7.231E–05
NA NA –3.201E–06 –3.201E–06 NA –3.195E–06 NA NA –3.202E–06
was saved when producing per tonne natural aggregate from this recycled concrete instead of virgin resources extracted from mining area. This saved electricity, in turn, resulted in 292 m3 water, 0.13 TJ energy, and 10.8 tonne of GHG emission savings considering all direct and indirect economic savings associated with producing electricity. By using this approach, carbon, water, and energy footprints related to several waste management processes have been calculated considering the direct and indirect connections among all sectors. In the next section, the results of developed hybrid LCA model have been presented with details.
reducing water consumption. Even though both recycling and landfilling strategies resulted in negative water saving for concrete and wood, it is more reasonable to recycle concrete and wood rather than landfill due to having over 90% less water consumption in recycling compared to landfilling. Moreover, if cardboard, paper, plastic, and wood’s secondary waste management strategy needs to be justified other than recycling; incineration is found to be a significantly better option compared to landfilling since it is resulted in over 95% less water consumption potential when compared to landfilling.
Environmental footprint analysis results
Energy footprint
In this section, water, energy and carbon footprint results associated with the three waste management strategies are illustrated. The detailed EIO-LCA model’s input and outputs are provided in Appendix.
Water footprint In this section, water footprint analysis results are discussed for recycling, landfilling, and incineration of per tonne C&D waste. First of all, recycling of ferrous and nonferrous metals, plastic, glass, paper, and cardboard is found to be beneficial for water footprint reductions (Table 1). This is because recycling of these materials reduced water consumptions for the direct and indirect processes required for material production processes. Among these C&D materials, nonferrous metals showed the highest potential for reducing overall water footprint. On the contrary, recycling of C&D wastes such as wood, drywall, concrete, and cardboard did not show a significant contribution to water footprint savings. When compared to recycling, landfilling and incineration did not help the environmental sustainability in terms of water footprint reduction whereas resulted in loss. Therefore, it is important to conclude that a high recycling of nonferrous metal, plastic, and paper should be encouraged by policy makers to diminish the net water footprint of the building-related construction wastes due to being the top three materials with significant water saving potentials. On the other hand, since recycling of concrete and wood provided negative water saving (loss), their corresponding recycling processes need to be improved towards
For energy footprint analysis, the amount of fossil fuel consumptions has been quantified in terms of terajoules (TJ) for recycling, landfilling, and incineration of per tonne C&D waste. Analysis results revealed that recycling of ferrous and nonferrous metals, plastic, glass, paper, and cardboard is found to have significant energy footprint reduction potential among the waste treatment alternatives (Table 2). This is due to recycling of these materials reduced the production-related fuel consumptions by reducing the dependency on virgin resources. Among C&D materials, recycling of nonferrous metals and plastics revealed the highest potential to reduce the total energy footprint. On the other hand, recycling of wood, drywall, concrete, and cardboard is not found to have a considerable impact on energy footprint reductions compared to other C&D materials. In addition, landfilling and incineration did not reveal significant energy footprint savings. Therefore, it is likely to conclude that high recycling of metals, glass, plastic and paper will be critical for reducing the net energy footprint of the C&D management systems. As a secondary waste treatment strategy for cardboard, paper, plastic and food; incineration is found to be a better option compared to landfilling, since incineration has an approximately 95% less energy footprint (Table 2).
Carbon footprint In this research, carbon footprint is defined as the total emissions of GHGs expressed as CO2-equivalent related to recycling, landfilling, and incineration of per tonne C&D waste. Analysis results showed that recycling of ferrous and nonferrous metals is found
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to have significant benefits for reducing total GHG emissions (Table 3). This is because recycling of these metals reduced the amount of electricity and fuel inputs which are utilized for production of these materials. In addition to that, process-related onsite emissions are decreased when using recycled metals. Recycling of other C&D materials such as paper, glass, and cardboard are also contributed to reductions in the net GHG emissions. On the contrary, recycling of C&D wastes such as wood, drywall, and concrete did not provide a significant benefit in terms of carbon footprint, compared to other C&D materials. Especially, recycling of wood and concrete has negative impacts on the net carbon emissions. In addition, incineration of wood, plastic, paper, and cardboard resulted in higher GHG emissions, and therefore combustion of these materials is not found to be an environmentally friendly waste treatment option. Therefore, it is likely to conclude that a high recycling of metals, glass, plastic, and paper will have a key importance for decreasing the net energy footprint of the C&D management systems. As a secondary waste management strategy, both landfilling and incineration
Table 3. GHG emissions savings (tCO2-eqv.). Material
Recycling
Landfilling
Incineration
Concrete Drywall Cardboard Paper Glass Plastic Ferrous metal Nonferrous metal Wood
–7.026E–02 1.042E–02 1.832E–01 7.681E–01 2.136E–01 6.293E–01 2.374E+00 1.467E+01 –7.120E–02
–5.277E–02 –5.277E–02 –5.277E–02 –5.277E–02 –5.277E–02 –5.277E–02 –5.277E–02 –5.277E–02 –5.277E–02
NA NA –5.188E–01 –5.188E–01 NA –1.299E+00 NA NA –8.088E–01
resulted in negative saving. However, landfilling is a less environmentally damaging option for cardboard, paper, plastic, and wood since their carbon footprint potentials are 89–96% less than incineration depending on the material type.
Total C&D waste and net carbon footprint Figure 1 shows the total waste composition of the major C&D waste materials obtained from different US building sectors. Based on the waste composition data, wood has the highest percentage share among other C&D wastes for all residential and nonresidential sectors. In addition, concrete, ferrous metals, and drywall are found to have high quantities between the construction waste materials. Especially, for residential sectors, drywall and wood contributed highly on the overall waste composition. Among the metals, ferrous metals have a considerable contribution to the net waste amount of commercial demolition sector whereas nonferrous metals did not show a significant construction to the total waste composition for all building types. After analysing the waste compositions from previously mentioned building sectors, it is important to understand the net carbon footprint savings associated with the recycling of C&D wastes. Table 4 presents the net GHG savings and emissions for recycling of construction materials for each industrial sector. The results show that commercial demolition, commercial renovation, and residential renovation sectors have the highest GHG reduction potentials associated with recycling of C&D wastes. Especially, recycling of ferrous metals played a critical role in this result. Although recycling of nonferrous metals has the highest potential for GHG reduction, it did not have a considerable impact on the overall GHG savings for
Figure 1. Total composition of C&D waste.
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Kucukvar et al. Table 4. Net GHG emissions and savings related to recycling. Material
Residential
Commercial
Renovation
New construction
Demolition
Renovation
New construction
Demolition
Concrete Drywall Cardboard Paper Glass Plastic Ferrous metal Nonferrous metal Wood
–1.24E+03 2.80E+05 7.41E+04 1.81E+05 2.09E+04 1.28E+04 1.98E+06 1.05E+06 –2.11E+05
–1.40E+04 9.14E+04 7.73E+04 1.17E+04 5.70E+03 4.87E+04 1.91E+05 4.96E+05 –2.99E+04
–4.99E+04 1.60E+04 7.94E+03 7.67E+03 3.49E+03 5.10E+03 8.53E+05 1.10E+05 –8.24E+04
–1.24E+05 7.74E+04 1.75E+04 3.45E+04 4.30E+03 4.63E+04 3.83E+06 5.71E+05 –7.56E+04
–2.38E+04 2.51E+03 4.85E+04 2.29E+05 8.83E+03 9.41E+05 1.04E+07 9.76E+04 –2.04E+05
–2.94E+04 2.13E+04 9.02E+04 0.00E+00 6.79E+02 1.11E+05 1.09E+06 0.00E+00 –1.77E+04
commercial new construction, commercial demolition, and residential demolition. This is because the total amounts of nonferrous metal in C&D waste of those sectors were minimal. Among the building sectors, residential new construction, residential demolition, and commercial new construction have the lowest carbon footprint reduction potential when their C&D wastes are recycled. Another important finding to be made with regard to carbon footprint results is that recycling of concrete waste, which is commonly found in residential demolition and commercial renovation has a negative impact on GHG savings by increasing the net carbon footprint (Table 4). Therefore, it was likely to conclude that among the C&D wastes, special focus should be given on recycling of ferrous metals for the sectors of residential renovation, residential demolition, and commercial renovation.
Direct and indirect GHG emissions Previous LCA studies on carbon footprint analysis of waste management systems generally estimated the direct emissions and emissions from purchased energy; however they give less focus on supply-chain emissions. Comprehensive LCA methods such as EIO-LCA or hybrid LCA are vital for tracking total emissions across the entire supply-chain, and narrowly defined carbon footprint estimation boundaries will generally result in significant underestimates of carbon emissions for providing products and services (Huang et al., 2009; Matthews et al., 2008). To accomplish a more detailed carbon footprint analysis, GHG emissions are quantified using a hybrid LCA model and divided into different categories. Firstly, the direct onsite emissions from material production from virgin resources or recycled materials, incineration, and landfilling are analysed. Secondly, the transportation-related GHG emissions, including tailpipe emissions and emissions from the production of diesel fuel, are quantified. Lastly, the upstream GHG emissions, indirect emissions from production of energy and material inputs used for material production, material recovery, incineration, and landfilling, are investigated.
In this study, the production phase compared to two different processes from carbon footprint accounting perspective: production of materials from virgin resources or recycled materials Analysis results show that production-related indirect GHG emission savings are found to be over 50% of the total GHGs for the majority of C&D materials, with exception of some materials such as glass, plastic, and ferrous metals. For these materials, the production-related direct emission savings are found to be higher compared to other emission categories. For nonferrous metals, indirect GHG savings account for almost 80% of total carbon footprint due to reductions in high electricity consumption for nonferrous metal production. In addition, recycling of glass, plastic, and ferrous metals significantly reduced the process-specific GHG emissions for these building products. On the contrary, cardboard and papers showed negative values for onsite GHG emissions due to increasing onsite emissions related to using recycled materials instead of virgin sources (Figure 2). For the material recovery phase, supply-chain GHG emissions are found to be the most dominant when compared to other categories due to high GHG emissions for the production of purchased electricity and fuels. As can be seen in Figure 3, for all C&D wastes, the contribution of supply-chain emissions to overall carbon footprint is found to be over 70% compared to other emissions categories. For ferrous and nonferrous metals, supplychain emissions again have the highest relative contribution to total carbon footprint. In addition, the relative contribution of transportation-related GHG emissions to overall carbon footprint was lower when compared with onsite and supply-chain GHG emissions. Therefore, it is likely that the energy efficiency of material recovery processes should be increased to lower the overall carbon footprint of recycling. As shown in Figure 3, the relative contribution of onsite emissions to total GHG emissions are found to be higher compared to transportation and supply-chain emissions due to high emissions during the landfilling process. Transportation and supply-chain GHG emissions are found to be negligible due to their low contribution to overall carbon footprint. Based on analysis results, onsite GHG emissions account for approximately 70% of the total carbon footprint. This is because the landfilling process
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Figure 2. Contribution of onsite, transportation, and supply-chain impacts on recycling-related GHG emissions.
Figure 3. Contribution of onsite, transportation and supply-chain impacts on GHG emissions related to material recovery, landfilling, and incineration.
emits large amounts of GHGs from landfill area and equipment used in disposal of C&D waste (Figure 3). When looked more closely at the incineration phase, onsite GHG emissions that represent carbon emissions related to combustion of cardboard, paper, plastic, and wood account for more than 90% of the overall GHG emissions. For
this life-cycle phase, transportation and supply-chain GHG emissions seem to be negligible compared to onsite emissions. Another important finding to be made with regard to GHG emission results is that supply-chain emissions include the GHG savings associated with electricity generation through combustion. However, these savings do not have a significant
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Kucukvar et al. impact on the total carbon footprint of incineration due to high process emissions (Figure 3).
Conclusion The overarching goal of this study was to evaluate the net environmental footprint of different C&D waste treatment alternatives. A hybrid LCA model has been developed to investigate the sustainability of recycling, incineration, and landfilling of C&D materials from a holistic perspective. Among the C&D materials, recycling of concrete, drywall, and wood did not have a significant contribution to the net environmental footprint savings. The results indicate that recycling of ferrous and nonferrous metals help in the environmental sustainability by reducing total GHG emissions. Therefore, we recommend that special focus should be given on the recycling of ferrous and nonferrous metals if significant reductions in total GHG emissions are the goal. The importance of metal recycling in carbon footprint reduction was also supported by the earlier EIO studies (e.g. Lave et al., 1999). After metallic wastes, recycling of paper products provided the second highest GHG savings. A hybrid LCA results showed that recycling of paper is more beneficial than incineration, thus increased recycling is desirable. Merrild et al. (2008) also concluded that expanding the system boundary of LCA to consider the minimization of raw material and energy consumption by using the paper associated with recycling is critical and made recycling better waste management alternative for reducing overall GHG emissions. In addition, per tonne, recycling of other C&D wastes such as plastic, cardboard, and glass will have a positive impact on reductions in energy and carbon footprints. This is due to using recycled products instead of virgin material in the manufacturing process. Hence, recycling of these materials significantly reduces the demand for energy as well as GHG emissions in the manufacturing processes (Chen and Lin, 2008). In addition, landfilling and incineration can be considered as a secondary strategy after recycling for some environmental impact categories. Especially, incineration is a better option as a secondary strategy after recycling for water and energy footprint categories whereas landfilling is a slightly better strategy when carbon footprint is considered as the main focus of comparison. It is important to note that the net environmental impacts of construction waste recycling are not limited to GHG emissions, water withdrawal, and fossil energy consumption. Toxic releases into air, water, and soil, liquid and hazardous waste generation, and groundwater pollution are still critical for assessing the environmental sustainability of C&D recycling, incineration, and landfilling. Also, the environmental impacts of waste treatment alternatives for other C&D waste types such as asphalt, brick, ceramic tiles, and insulation materials should be considered. In addition to environmental footprints, socioeconomic impacts such as employment, reductions in social cost related to minimized environmental emissions, and reduced dependency on imports should also be taken into account for analysing the recycling of C&D materials from a more holistic perspective. Last
but not least, transportation distance of waste materials and the uncertainties in manufacturing processes-related data acquired from literature might affect the LCA results to some extent. Therefore, such impacts can also be integrated into a stochastic LCA model where the uncertainty in environmental footprint is included. Consequently, it is expected that the findings of this research will facilitate better decision making in treating C&D waste considering the direct and indirect impacts of various waste management alternatives.
Declaration of conflicting interest The authors declare that there is no conflict of interest.
Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.
References Astrup T, Fruergaard T and Christensen TH (2009) Recycling of plastic: accounting of greenhouse gases and global warming contributions. Waste Management Research 27, 763–772. Carnegie Mellon University Green Design Institute (2002) Economic input– output life cycle assessment (EIO-LCA), US 2002 Industry Benchmark model. Pittsburgh, PA: CMU Green Design Institute. Available at: http:// www.eiolca.net/copyright/index.html (consulted January 2013). Chen TC and Lin CF (2008) Greenhouse gases emissions from waste management practices using Life Cycle Inventory model. Journal of Hazardous Materials 155, 23–31. Choi T, Jackson RW, Green Leigh N, et al. (2010) A baseline input–output model with environmental accounts (IOEA) applied to e-waste recycling. International Regional Science Review 34, 3–33. Christensen TH (ed) (2011) Solid waste technology & management (Vol. 2). Chichester, UK: Wiley. Christensen TH, Bhander G, Lindvall H, et al. (2007) Experience with the use of LCA-modelling (EASEWASTE) in waste management. Waste Management Research 25, 257–262. Coelho A and de Brito J (2013) Environmental analysis of a construction and demolition waste recycling plant in Portugal – Part I: energy consumption and CO2 emissions. Waste Management 33, 1258–1267. Damgaard A, Larsen AW and Christensen TH (2009) Recycling of metals: accounting of greenhouse gases and global warming contributions. Waste Management Research 27, 773–780. Denison RA (1996) Environmental life-cycle comparisons of recycling, landfilling, and incineration: a review of recent studies. Annual Review of Energy and the Environment 21, 191–237. Diaz R and Warith M (2006) Life-cycle assessment of municipal solid wastes: development of the WASTED model. Waste Management 26, 886–901. DiStefano TD and Belenky LG (2009) Life-cycle analysis of energy and greenhouse gas emissions from anaerobic biodegradation of municipal solid waste. Journal of Environmental Engineering 135, 1097–2005. Egilmez G, Kucukvar M and Tatari O (2013) Sustainability assessment of U.S. manufacturing sectors: an economic input output-based frontier approach. Journal of Cleaner Production 53, 91–102. Eisted R, Larsen AW and Christensen TH (2009) Collection, transfer and transport of waste: accounting of greenhouse gases and global warming contribution. Waste Management Research 27, 738–745. Eriksson O (2005) Municipal solid waste management from a systems perspective. Journal of Cleaner Production 13, 241–252. Finnveden G, Bjorklund A, Moberg A, et al. (2007) Environmental and economic assessment methods for waste management decision-support: possibilities and limitations. Waste Management Research 25, 263–269. Franklin Associates (1998) Characterization of building-related construction and demolition debris in the United States, prepared for the US Environmental Protection Agency, report no. EPA530-R-98-010. Prairie Village, KS:Franklin Associates.
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Hendrickson CT, Lave LB and Matthews HS (2006) Environmental life cycle assessment of goods and services: an input–output approach. Washington, DC: RFF Press. Huang GH, Anderson WP and Baetz BW (1994) Environmental input–output analysis and its application to regional solid-waste management planning. Journal of Environmental Management 42, 63–79. Huang YA, Lenzen M, Weber C, et al. (2009) The role of input–output analysis for the screening of corporate carbon footprints. Economic Systems Research 21, 217–242. Johnson J, Reck BK, Wang T, et al. (2008) The energy benefit of stainless steel recycling. Energy Policy 36, 181–192. Joshi S (1999) Product environmental life-cycle assessment using input– output techniques. Journal of Industrial Ecology 3, 95–120. Kucukvar M and Tatari O (2013) Towards a triple bottom-line sustainability assessment of the US construction industry. International Journal of Life Cycle Assessment 18, 958–972. Larsen AW, Merrild H and Christensen TH (2009) Recycling of glass: accounting of greenhouse gases and global warming contributions. Waste Management Research 27, 754–762. Lave LB, Hendrickson CT, Conway-Schempf NM, et al. (1999) Municipal solid waste recycling issues. Journal of Environmental Engineering 125, 944–949. Manfredi S and Christensen TH (2009) Environmental assessment of solid waste landfilling technologies by means of LCA-modeling. Waste Management New York NY 29, 32–43. Matthews HS, Hendrickson CT and Weber CL (2008) The importance of carbon footprint estimation boundaries. Environmental Science And Technology 42, 5839–5842. McDougall FR and Hruska JP (2000) The use of Life Cycle Inventory tools to support an integrated approach to solid waste management. Waste Management Research 18, 590–594. Merrild H, Damgaard A and Christensen TH (2008) Life cycle assessment of waste paper management: the importance of technology data and system boundaries in assessing recycling and incineration. Resources, Conservation and Recycling 52, 1391–1398. Morris J (2004) Comparative LCAs for curbside recycling versus either landfilling or incineration with energy recovery. International Journal of Life Cycle Assessment 10, 273–284.
Nakamura S and Kondo Y (2002) Input–output analysis of waste management. Journal of Industrial Ecology 6, 39–63. Nakamura S and Kondo Y (2006) A waste input–output life-cycle cost analysis of the recycling of end-of-life electrical home appliances. Ecological Economics 57, 494–506. NREL. US life cycle inventory database: transport, train, diesel powered. 2010. Available at: https://www.lcacommons.gov/nrel/search (consulted 12 May 2014). Ortiz O, Pasqualino JC and Castells F (2010) Environmental performance of construction waste: comparing three scenarios from a case study in Catalonia, Spain. Waste Management 30, 646–654. Pimenteira CAP, Carpio LGT, Rosa LP, et al. (2005) Solid wastes integrated management in Rio de Janeiro: input–output analysis. Waste Management New York NY 25, 539–553. Solano E, Ranjithan R, Barlaz MA, et al. (2002) Life-cycle-based solid waste management. I: model development. Journal of Environmental Engineering 128, 981. Song Q, Wang Z and Li J (2013) Environmental performance of municipal solid waste strategies based on LCA method: a case study of Macau. Journal of Cleaner Production, 57, 92–100. Tam V and Tam C (2006) A review on the viable technology for construction waste recycling. Resources, Conservation and Recycling 47, 209–221. Thorneloe SA, Weitz KA and Jambeck J (2007) Application of the US decision support tool for materials and waste management. Waste Management New York NY 27, 1006–1020. US Environmental Protection Agency (2003) Estimating 2003 Buildingrelated construction and demolition materials amounts. Washington, DC: EPA. Available at: http://www.epa.gov/epawaste/conserve/imr/cdm/pubs/ cd-meas.pdf (consulted January 2013). US Environmental Protection Agency (2010) Waste Reduction Model (WARM). Washington, DC: EPA. Available at: www.epa.gov/climatechange/wycd/ waste/calculators/Warm_Form.html (consulted January 2013). Villanueva A and Wenzel H (2007) Paper waste – recycling, incineration or landfilling? A review of existing life cycle assessments. Waste Management New York NY 27, S29–S46. Weitz KA, Thorneloe SA, Nishtala SR, et al. (2002) The impact of municipal solid waste management on greenhouse gas emissions in the United States. Journal of the Air and Waste Management Association 52, 1000–1011.
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Evaluating environmental impacts of alternative construction waste management approaches using supply-chain-linked life-cycle analysis Murat Kucukvar, Gokhan Egilmez and Omer Tatari Waste Manag Res 2014 32: 500 originally published online 22 May 2014 DOI: 10.1177/0734242X14536457 The online version of this article can be found at: http://wmr.sagepub.com/content/32/6/500
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research-article2014
WMR0010.1177/0734242X14536457Waste Management and ResearchKucukvar et al.
Original Article
Evaluating environmental impacts of alternative construction waste management approaches using supplychain-linked life-cycle analysis
Waste Management & Research 2014, Vol. 32(6) 500–508 © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav DOI: 10.1177/0734242X14536457 wmr.sagepub.com
Murat Kucukvar1, Gokhan Egilmez2 and Omer Tatari1
Abstract Waste management in construction is critical for the sustainable treatment of building-related construction and demolition (C&D) waste materials, and recycling of these wastes has been considered as one of the best strategies in minimization of C&D debris. However, recycling of C&D materials may not always be a feasible strategy for every waste type and therefore recycling and other waste treatment strategies should be supported by robust decision-making models. With the aim of assessing the net carbon, energy, and water footprints of C&D recycling and other waste management alternatives, a comprehensive economic input–output-based hybrid life-cycle assessment model is developed by tracing all of the economy-wide supply-chain impacts of three waste management strategies: recycling, landfilling, and incineration. Analysis results showed that only the recycling of construction materials provided positive environmental footprint savings in terms of carbon, energy, and water footprints. Incineration is a better option as a secondary strategy after recycling for water and energy footprint categories, whereas landfilling is found to be as slightly better strategy when carbon footprint is considered as the main focus of comparison. In terms of construction materials’ environmental footprint, nonferrous metals are found to have a significant environmental footprint reduction potential if recycled. Keywords Construction waste management, environmental footprint, hybrid life-cycle assessment, supply chain, sustainability, US buildings
Introduction Today, recycling of construction waste materials has been considered as one of the best strategies in minimization of construction and demolition (C&D) debris (Tam and Tam, 2006). However, recycling of construction waste materials will not always be a feasible for every waste type, and therefore these recycling strategies should be supported by robust decisionmaking models. Life-cycle assessment (LCA) is a popular tool to analyse the sustainability of waste management systems, and has gained a tremendous interest over the last few years to develop environmentally sound waste management strategies. There are mainly three types of LCA models utilized for environmental impact assessment of waste management systems, namely: process LCA (P-LCA), economic input–output LCA (EIO-LCA), and hybrid LCA. Among the LCA methodologies, P-LCA has been widely used to analyse the environmental performance of solid waste management systems. By using P-LCA as the methodology, several LCA frameworks have been developed to be used as robust LCA models: for instance, Organic Waste Research (ORWARE; Eriksson, 2005), Integrated Solid Waste Management (ISWM; Christensen et al., 2007), Municipal Solid Waste (MSW) Decision Support Tool (MSW-DST; Solano et al., 2002), Waste Analysis Software Tool for Environmental
Decisions (WASTED; Diaz and Warith, 2006), and Waste Reduction Model (WARM), developed by US Environmental Protection Agency (EPA) (Weitz et al., 2002). In addition to the aforementioned P-LCA-based waste management systems’ environmental impact assessment frameworks, several studies have also been conducted by using P-LCA methodology, where the main focus was solely on the process-specific environmental impacts of waste management systems. Examples include McDougall and Hruska (2000), Christensen et al. (2007), Finnveden et al. (2007), Thorneloe et al. (2007), Villanueva and Wenzel (2007), Merrild et al. (2008), Eisted et al. (2009), Damgaard et al. (2009), Astrup et al. (2009), Larsen et al. (2009), Johnson et al. (2008), Manfredi and Christensen (2009), Ortiz et al. (2010), Coelho and de Brito (2013), and (Song et al., 2013).
1Department
of Civil, Environmental, and Construction Engineering, University of Central Florida, Orlando, FL, USA 2Department of Industrial and Manufacturing Engineering, North Dakota State University, Fargo, ND, USA. Corresponding author: Gokhan Egilmez, North Dakota State University, Fargo, ND 58102, USA. Email: [email protected]
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Kucukvar et al. See Tam and Tam (2006) for a review of recent developments in LCA associated with construction industry, including the recycling materials. Compared to studies that utilized P-LCA, only a handful of studies have analysed different solid waste management systems using EIO-LCA. EIO-LCA models basically quantify the environmental impacts by integrating macro-level economic input and output tables with environmental impact multipliers (Egilmez et al., 2013). Augmenting the input–output tables with flows of waste, Japan has led the development of solid waste extended EIOLCA for analysing different waste management alternatives from a life-cycle perspective (Nakamura and Kondo, 2002). This model can analyse environmental impacts and economic impacts such as sector output and employment of different waste treatment alternatives. Nakamura and Kondo (2006) developed the waste input– output LCA model and used it to compare traditional waste treatment strategies with recycling for electrical home appliances. Huang et al. (1994) used EIO-LCA model to analyse the direct and indirect impacts of regional solid waste generation and treatment systems. This model quantifies the effects of different waste management systems on economic and environmental factors. DiStefano and Belenky (2009) developed a hybrid LCA model to compare energy consumptions and greenhouse gas (GHG) emissions for landfilling of MSW to biodegradation of MWS in anaerobic digesters. This study used a combined application of EIO-LCA and P-LCA to take advantage of both models for an in-depth environmental analysis of different waste treatment strategies. In another study, EIO-LCA methodology was used to analyse the environmental burdens associated with the collection, recycling, and disposal of MSW (Morris, 2004). The researchers assessed and compared environmental impacts from kerbside collection for recycling, waste processing, and transportation of recyclable materials collected from households and/or businesses against environmental impacts associated with kerbside collection and disposal of mixed solid waste. In addition, Pimenteira et al. (2005) analysed the social and economic implications of solid waste management using an input–output methodology. This study quantified the energy savings obtained from recycling as well as the avoided emissions of GHGs. On the other hand, Choi et al. (2010) utilized the EIOLCA to analyse the economic impacts of electronic waste in Atlanta, Georgia. In their study, researchers developed a regional economic model that explicitly incorporated the flow of recyclable commodities and related industries within the input–output framework. This modelling approach identified structural differences and relevant economic impacts in the process of integrating the reuse of recycled materials within the economic input–output model. In another study, Huang et al. (2009) used EIO analysis to thoroughly estimate the entire upstream and downstream carbon emissions. The results of the literature review indicate that none of the LCA-based decision support tools within waste management used an input–output methodology to analyse the indirect
resource and energy savings through recycling and the indirect GHG reductions associated with using recycled materials to produce new industrial products from building-related C&D materials. However, recycling of these waste materials will minimize primary and secondary industrial activities to produce virgin materials and might result in considerable environmental savings for various C&D waste management strategies in the USA. Therefore, the current study targets this gap and offers a comprehensive C&D waste management strategy for conventional and green buildings.
Scope of the study As a comprehensive solution for the assessment of construction waste industries’ contribution to GHG emissions from recycling, incineration, waste collection and transportation, and landfill, the extended life-cycle system boundary is proposed to analyse the direct and indirect environmental impacts of different waste management systems using a comprehensive EIO-LCA modelling. We developed a hybrid LCA model, where P-LCA model is combined with the EIO analysis. In this approach, onsite (process) environmental impacts of each waste management system is collected, while higher-order (supply chain) impacts, including the production of energy or material inputs, are covered by the EIO analysis. Such a hybrid LCA approach enables us to quantify the direct and indirect environmental impacts of C&D management systems. In addition, this proposed model will enable the policy makers to understand indirect environmental savings related to recycling of different waste materials. For example, recycling aluminium will result in GHG emissions during recycling process. However, recycled products will be used as secondary materials in the factory and will minimize several resource inputs as well as indirect industrial processes to produce virgin materials. We believe that that expanded system boundaries and inclusion of all upstream supplier effects will be critical to holistically evaluate the environmental impacts and savings related to waste recycling. In this paper, three main waste management processes such as recycling, incineration with heat recovery, and conventional landfilling were analysed for nine different building-related C&D waste materials: concrete, wood, nonferrous and ferrous metals, cardboard, plastic, glass, paper, and cardboard. The environmental impacts associated with management of these waste materials are considered as global warming potential (eqv-CO2), primary energy consumption (TJ), and water withdrawals (m3). For the recycling, collection and transportation of C&D, materials recovery process, and producing new products from recycled materials are holistically investigated under the scope of this research. For incineration, transportation of waste to incineration facility, processing of waste, and energy recovery from waste is analysed. Lastly, the environmental impacts related to conventional landfilling is quantified for the life-cycle phases of transportation of C&D to landfill and landfilling of each C&D waste materials.
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Hybrid LCA model development EIO-LCA model consists of the 428 sectors’ input–output tables for the US economy augmented with sector-level water use, energy consumptions, and GHG emissions vectors have been used. Hence, the carbon, energy, and water footprints of C&D waste treatment alternatives has been investigated from a holistic perspective. EIO analysis considers the sector-level interdependencies and represents sectoral direct requirements which are represented by matrix A (Kucukvar and Tatari, 2013). This matrix basically includes the US dollar value of inputs required from other sectors to produce US$1 worth of output. The total output of a sector in this economic model with a final demand of f can be expressed as (Joshi, 1999):
x = (I – A)–1 f (1)
where x represents the overall outputs of sectors, I is the identity matrix, and f is the final demand vector representing the change in a final demand of desired sector. After the EIO model has been established, overall environmental impacts can be calculated by multiplying the economic output of each industrial sector by the environmental impacts associated with per dollar of output. A vector of environmental outputs can be formulated as follows (Hendrickson et al., 2006):
Oi = EiX = Ei (I – A)–1 f (2)
where Oi denotes the total environmental outputs (direct plus indirect) vector for the environmental impact category of i, and Ei represents a diagonal matrix which consist of the environmental impact per dollar of output for each industrial sector. In this analysis, we developed a hybrid LCA model considering the environmental impacts related to waste management alternatives. The proposed hybrid LCA model quantifies total environmental burden associated with the waste management systems which is presented as follows:
ri = Ei (I – A)–1 f +Qiei (3)
where ri is the total environmental impact, which is the sum of environmental burdens associated with the production of resource inputs (including all supply chains) and the direct environmental burdens associated with waste treatment processes, Qi is the total input requirements for a process, and ei is unit environmental impact factor associated with the consumption of Qi. For instance, GHGs are highly emitted during the transportation of C&D wastes. For C&D transportation, diesel is consumed as a fuel during the transfer of C&D waste from construction site to material recovery facility or landfill area. In our hybrid LCA model, equation 2 quantifies the direct plus indirect GHG emissions considering the whole supply chain of diesel production. In addition, tailpipe GHG emissions (process emissions) are also taken into account using equation 3 which represents the mathematical framework of developed hybrid model. All other environmental
burdens for C&D waste management alternatives are quantified by the same hybrid LCA model.
Data collection In this paper, several important life-cycle phases, including material production from virgin and recycled products, transportation, material recovery, incineration with heat recovery, and landfilling, were analysed for the nine building-related C&D waste materials. In addition, six major building sectors consisting of residential renovation, residential new construction, residential demolition, commercial renovation, commercial new construction, and commercial demolition have been analysed, and the net carbon, energy, and water footprints associated with management of C&D materials coming from these building sectors were quantified using the proposed comprehensive LCA methodology. The amount of C&D waste and waste composition data for each building sector was gathered from the earlier joint studies of Franklin Associates (1998) and the US EPA (2003). Several studies and waste LCA tools have been used to collect the life-cycle inventory data for different C&D waste management alternatives. First of all, the process data for producing each building material from virgin resources and recycled C&D waste are compiled by Christensen (2011). This detailed data set included all electricity, fuel, and other resource inputs, the amount of residues for landfilling, and atmospheric GHG emissions associated with producing building materials from recycled or virgin materials. In addition, electricity and fuel consumption and GHG emissions data for material recovery processes were gathered from the LCA study of Denison (1996)). The US EPA’s WARM model has been used for quantifying the emissions related to incineration and landfilling of each C&D material (US EPA, 2010), and energy production efficiency and electricity generation related to incineration of cardboard, paper, plastic, and wood waste are obtained from the WASTED model developed by Diaz and Warith (2006). For transportation of C&D waste from construction site to material recovery facility and from construction site to landfill area or incineration plant, a transportation distance of 50 km is assumed for each transfer process. Fuel consumption and emission factors data are provided by National Renewable Energy Laboratory (NREL) life-cycle inventory database for a diesel-powered single-unit truck (NREL, 2010). For the EIO-based environmental impact analysis, the producer prices of each energy and material input are calculated by using several publicly available data from the US Department of Energy, US Energy Information Administration, US EPA, and US Geological Survey. After calculating the cost of each input requirement, direct plus indirect environmental burdens associated with recycling and other treatment options were quantified by using the EIO-LCA tool, which was developed by the Green Design Institute at Carnegie Mellon University (2002). For example, residential renovations sector produced 71×103 Mt of concrete waste, and approximately 16×103 kWh of electricity
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Kucukvar et al. Table 1. Water savings (m3).
Table 2. Energy savings (TJ).
Material
Recycling
Landfilling
Incineration
Material
Recycling
Landfilling
Incineration
Concrete Drywall Cardboard Paper Glass Plastic Ferrous metal Nonferrous metal Wood
–2.35E–03 5.87E–04 1.49E–02 7.34E–02 1.39E–02 1.43E–01 1.93E–02 8.33E–01 –1.95E–03
–8.14E–02 –8.14E–02 –8.14E–02 –8.14E–02 –8.14E–02 –8.14E–02 –8.14E–02 –8.14E–02 –8.14E–02
NA NA –3.55E–03 –3.55E–03 NA –3.49E–03 NA NA –3.55E–03
Concrete Drywall Cardboard Paper Glass Plastic Ferrous metal Nonferrous metal Wood
7.100E–04 1.490E–03 5.260E–03 2.069E–02 5.000E–03 3.919E–02 6.440E–03 2.209E–01 8.200E–04
–7.231E–05 –7.231E–05 –7.231E–05 –7.231E–05 –7.231E–05 –7.231E–05 –7.231E–05 –7.231E–05 –7.231E–05
NA NA –3.201E–06 –3.201E–06 NA –3.195E–06 NA NA –3.202E–06
was saved when producing per tonne natural aggregate from this recycled concrete instead of virgin resources extracted from mining area. This saved electricity, in turn, resulted in 292 m3 water, 0.13 TJ energy, and 10.8 tonne of GHG emission savings considering all direct and indirect economic savings associated with producing electricity. By using this approach, carbon, water, and energy footprints related to several waste management processes have been calculated considering the direct and indirect connections among all sectors. In the next section, the results of developed hybrid LCA model have been presented with details.
reducing water consumption. Even though both recycling and landfilling strategies resulted in negative water saving for concrete and wood, it is more reasonable to recycle concrete and wood rather than landfill due to having over 90% less water consumption in recycling compared to landfilling. Moreover, if cardboard, paper, plastic, and wood’s secondary waste management strategy needs to be justified other than recycling; incineration is found to be a significantly better option compared to landfilling since it is resulted in over 95% less water consumption potential when compared to landfilling.
Environmental footprint analysis results
Energy footprint
In this section, water, energy and carbon footprint results associated with the three waste management strategies are illustrated. The detailed EIO-LCA model’s input and outputs are provided in Appendix.
Water footprint In this section, water footprint analysis results are discussed for recycling, landfilling, and incineration of per tonne C&D waste. First of all, recycling of ferrous and nonferrous metals, plastic, glass, paper, and cardboard is found to be beneficial for water footprint reductions (Table 1). This is because recycling of these materials reduced water consumptions for the direct and indirect processes required for material production processes. Among these C&D materials, nonferrous metals showed the highest potential for reducing overall water footprint. On the contrary, recycling of C&D wastes such as wood, drywall, concrete, and cardboard did not show a significant contribution to water footprint savings. When compared to recycling, landfilling and incineration did not help the environmental sustainability in terms of water footprint reduction whereas resulted in loss. Therefore, it is important to conclude that a high recycling of nonferrous metal, plastic, and paper should be encouraged by policy makers to diminish the net water footprint of the building-related construction wastes due to being the top three materials with significant water saving potentials. On the other hand, since recycling of concrete and wood provided negative water saving (loss), their corresponding recycling processes need to be improved towards
For energy footprint analysis, the amount of fossil fuel consumptions has been quantified in terms of terajoules (TJ) for recycling, landfilling, and incineration of per tonne C&D waste. Analysis results revealed that recycling of ferrous and nonferrous metals, plastic, glass, paper, and cardboard is found to have significant energy footprint reduction potential among the waste treatment alternatives (Table 2). This is due to recycling of these materials reduced the production-related fuel consumptions by reducing the dependency on virgin resources. Among C&D materials, recycling of nonferrous metals and plastics revealed the highest potential to reduce the total energy footprint. On the other hand, recycling of wood, drywall, concrete, and cardboard is not found to have a considerable impact on energy footprint reductions compared to other C&D materials. In addition, landfilling and incineration did not reveal significant energy footprint savings. Therefore, it is likely to conclude that high recycling of metals, glass, plastic and paper will be critical for reducing the net energy footprint of the C&D management systems. As a secondary waste treatment strategy for cardboard, paper, plastic and food; incineration is found to be a better option compared to landfilling, since incineration has an approximately 95% less energy footprint (Table 2).
Carbon footprint In this research, carbon footprint is defined as the total emissions of GHGs expressed as CO2-equivalent related to recycling, landfilling, and incineration of per tonne C&D waste. Analysis results showed that recycling of ferrous and nonferrous metals is found
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to have significant benefits for reducing total GHG emissions (Table 3). This is because recycling of these metals reduced the amount of electricity and fuel inputs which are utilized for production of these materials. In addition to that, process-related onsite emissions are decreased when using recycled metals. Recycling of other C&D materials such as paper, glass, and cardboard are also contributed to reductions in the net GHG emissions. On the contrary, recycling of C&D wastes such as wood, drywall, and concrete did not provide a significant benefit in terms of carbon footprint, compared to other C&D materials. Especially, recycling of wood and concrete has negative impacts on the net carbon emissions. In addition, incineration of wood, plastic, paper, and cardboard resulted in higher GHG emissions, and therefore combustion of these materials is not found to be an environmentally friendly waste treatment option. Therefore, it is likely to conclude that a high recycling of metals, glass, plastic, and paper will have a key importance for decreasing the net energy footprint of the C&D management systems. As a secondary waste management strategy, both landfilling and incineration
Table 3. GHG emissions savings (tCO2-eqv.). Material
Recycling
Landfilling
Incineration
Concrete Drywall Cardboard Paper Glass Plastic Ferrous metal Nonferrous metal Wood
–7.026E–02 1.042E–02 1.832E–01 7.681E–01 2.136E–01 6.293E–01 2.374E+00 1.467E+01 –7.120E–02
–5.277E–02 –5.277E–02 –5.277E–02 –5.277E–02 –5.277E–02 –5.277E–02 –5.277E–02 –5.277E–02 –5.277E–02
NA NA –5.188E–01 –5.188E–01 NA –1.299E+00 NA NA –8.088E–01
resulted in negative saving. However, landfilling is a less environmentally damaging option for cardboard, paper, plastic, and wood since their carbon footprint potentials are 89–96% less than incineration depending on the material type.
Total C&D waste and net carbon footprint Figure 1 shows the total waste composition of the major C&D waste materials obtained from different US building sectors. Based on the waste composition data, wood has the highest percentage share among other C&D wastes for all residential and nonresidential sectors. In addition, concrete, ferrous metals, and drywall are found to have high quantities between the construction waste materials. Especially, for residential sectors, drywall and wood contributed highly on the overall waste composition. Among the metals, ferrous metals have a considerable contribution to the net waste amount of commercial demolition sector whereas nonferrous metals did not show a significant construction to the total waste composition for all building types. After analysing the waste compositions from previously mentioned building sectors, it is important to understand the net carbon footprint savings associated with the recycling of C&D wastes. Table 4 presents the net GHG savings and emissions for recycling of construction materials for each industrial sector. The results show that commercial demolition, commercial renovation, and residential renovation sectors have the highest GHG reduction potentials associated with recycling of C&D wastes. Especially, recycling of ferrous metals played a critical role in this result. Although recycling of nonferrous metals has the highest potential for GHG reduction, it did not have a considerable impact on the overall GHG savings for
Figure 1. Total composition of C&D waste.
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Kucukvar et al. Table 4. Net GHG emissions and savings related to recycling. Material
Residential
Commercial
Renovation
New construction
Demolition
Renovation
New construction
Demolition
Concrete Drywall Cardboard Paper Glass Plastic Ferrous metal Nonferrous metal Wood
–1.24E+03 2.80E+05 7.41E+04 1.81E+05 2.09E+04 1.28E+04 1.98E+06 1.05E+06 –2.11E+05
–1.40E+04 9.14E+04 7.73E+04 1.17E+04 5.70E+03 4.87E+04 1.91E+05 4.96E+05 –2.99E+04
–4.99E+04 1.60E+04 7.94E+03 7.67E+03 3.49E+03 5.10E+03 8.53E+05 1.10E+05 –8.24E+04
–1.24E+05 7.74E+04 1.75E+04 3.45E+04 4.30E+03 4.63E+04 3.83E+06 5.71E+05 –7.56E+04
–2.38E+04 2.51E+03 4.85E+04 2.29E+05 8.83E+03 9.41E+05 1.04E+07 9.76E+04 –2.04E+05
–2.94E+04 2.13E+04 9.02E+04 0.00E+00 6.79E+02 1.11E+05 1.09E+06 0.00E+00 –1.77E+04
commercial new construction, commercial demolition, and residential demolition. This is because the total amounts of nonferrous metal in C&D waste of those sectors were minimal. Among the building sectors, residential new construction, residential demolition, and commercial new construction have the lowest carbon footprint reduction potential when their C&D wastes are recycled. Another important finding to be made with regard to carbon footprint results is that recycling of concrete waste, which is commonly found in residential demolition and commercial renovation has a negative impact on GHG savings by increasing the net carbon footprint (Table 4). Therefore, it was likely to conclude that among the C&D wastes, special focus should be given on recycling of ferrous metals for the sectors of residential renovation, residential demolition, and commercial renovation.
Direct and indirect GHG emissions Previous LCA studies on carbon footprint analysis of waste management systems generally estimated the direct emissions and emissions from purchased energy; however they give less focus on supply-chain emissions. Comprehensive LCA methods such as EIO-LCA or hybrid LCA are vital for tracking total emissions across the entire supply-chain, and narrowly defined carbon footprint estimation boundaries will generally result in significant underestimates of carbon emissions for providing products and services (Huang et al., 2009; Matthews et al., 2008). To accomplish a more detailed carbon footprint analysis, GHG emissions are quantified using a hybrid LCA model and divided into different categories. Firstly, the direct onsite emissions from material production from virgin resources or recycled materials, incineration, and landfilling are analysed. Secondly, the transportation-related GHG emissions, including tailpipe emissions and emissions from the production of diesel fuel, are quantified. Lastly, the upstream GHG emissions, indirect emissions from production of energy and material inputs used for material production, material recovery, incineration, and landfilling, are investigated.
In this study, the production phase compared to two different processes from carbon footprint accounting perspective: production of materials from virgin resources or recycled materials Analysis results show that production-related indirect GHG emission savings are found to be over 50% of the total GHGs for the majority of C&D materials, with exception of some materials such as glass, plastic, and ferrous metals. For these materials, the production-related direct emission savings are found to be higher compared to other emission categories. For nonferrous metals, indirect GHG savings account for almost 80% of total carbon footprint due to reductions in high electricity consumption for nonferrous metal production. In addition, recycling of glass, plastic, and ferrous metals significantly reduced the process-specific GHG emissions for these building products. On the contrary, cardboard and papers showed negative values for onsite GHG emissions due to increasing onsite emissions related to using recycled materials instead of virgin sources (Figure 2). For the material recovery phase, supply-chain GHG emissions are found to be the most dominant when compared to other categories due to high GHG emissions for the production of purchased electricity and fuels. As can be seen in Figure 3, for all C&D wastes, the contribution of supply-chain emissions to overall carbon footprint is found to be over 70% compared to other emissions categories. For ferrous and nonferrous metals, supplychain emissions again have the highest relative contribution to total carbon footprint. In addition, the relative contribution of transportation-related GHG emissions to overall carbon footprint was lower when compared with onsite and supply-chain GHG emissions. Therefore, it is likely that the energy efficiency of material recovery processes should be increased to lower the overall carbon footprint of recycling. As shown in Figure 3, the relative contribution of onsite emissions to total GHG emissions are found to be higher compared to transportation and supply-chain emissions due to high emissions during the landfilling process. Transportation and supply-chain GHG emissions are found to be negligible due to their low contribution to overall carbon footprint. Based on analysis results, onsite GHG emissions account for approximately 70% of the total carbon footprint. This is because the landfilling process
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Figure 2. Contribution of onsite, transportation, and supply-chain impacts on recycling-related GHG emissions.
Figure 3. Contribution of onsite, transportation and supply-chain impacts on GHG emissions related to material recovery, landfilling, and incineration.
emits large amounts of GHGs from landfill area and equipment used in disposal of C&D waste (Figure 3). When looked more closely at the incineration phase, onsite GHG emissions that represent carbon emissions related to combustion of cardboard, paper, plastic, and wood account for more than 90% of the overall GHG emissions. For
this life-cycle phase, transportation and supply-chain GHG emissions seem to be negligible compared to onsite emissions. Another important finding to be made with regard to GHG emission results is that supply-chain emissions include the GHG savings associated with electricity generation through combustion. However, these savings do not have a significant
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Kucukvar et al. impact on the total carbon footprint of incineration due to high process emissions (Figure 3).
Conclusion The overarching goal of this study was to evaluate the net environmental footprint of different C&D waste treatment alternatives. A hybrid LCA model has been developed to investigate the sustainability of recycling, incineration, and landfilling of C&D materials from a holistic perspective. Among the C&D materials, recycling of concrete, drywall, and wood did not have a significant contribution to the net environmental footprint savings. The results indicate that recycling of ferrous and nonferrous metals help in the environmental sustainability by reducing total GHG emissions. Therefore, we recommend that special focus should be given on the recycling of ferrous and nonferrous metals if significant reductions in total GHG emissions are the goal. The importance of metal recycling in carbon footprint reduction was also supported by the earlier EIO studies (e.g. Lave et al., 1999). After metallic wastes, recycling of paper products provided the second highest GHG savings. A hybrid LCA results showed that recycling of paper is more beneficial than incineration, thus increased recycling is desirable. Merrild et al. (2008) also concluded that expanding the system boundary of LCA to consider the minimization of raw material and energy consumption by using the paper associated with recycling is critical and made recycling better waste management alternative for reducing overall GHG emissions. In addition, per tonne, recycling of other C&D wastes such as plastic, cardboard, and glass will have a positive impact on reductions in energy and carbon footprints. This is due to using recycled products instead of virgin material in the manufacturing process. Hence, recycling of these materials significantly reduces the demand for energy as well as GHG emissions in the manufacturing processes (Chen and Lin, 2008). In addition, landfilling and incineration can be considered as a secondary strategy after recycling for some environmental impact categories. Especially, incineration is a better option as a secondary strategy after recycling for water and energy footprint categories whereas landfilling is a slightly better strategy when carbon footprint is considered as the main focus of comparison. It is important to note that the net environmental impacts of construction waste recycling are not limited to GHG emissions, water withdrawal, and fossil energy consumption. Toxic releases into air, water, and soil, liquid and hazardous waste generation, and groundwater pollution are still critical for assessing the environmental sustainability of C&D recycling, incineration, and landfilling. Also, the environmental impacts of waste treatment alternatives for other C&D waste types such as asphalt, brick, ceramic tiles, and insulation materials should be considered. In addition to environmental footprints, socioeconomic impacts such as employment, reductions in social cost related to minimized environmental emissions, and reduced dependency on imports should also be taken into account for analysing the recycling of C&D materials from a more holistic perspective. Last
but not least, transportation distance of waste materials and the uncertainties in manufacturing processes-related data acquired from literature might affect the LCA results to some extent. Therefore, such impacts can also be integrated into a stochastic LCA model where the uncertainty in environmental footprint is included. Consequently, it is expected that the findings of this research will facilitate better decision making in treating C&D waste considering the direct and indirect impacts of various waste management alternatives.
Declaration of conflicting interest The authors declare that there is no conflict of interest.
Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.
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