Full Life Cycle Analysis of the Environmental Impact of Low- Income Housing in South Africa

Transcription

1 THE SOUTHERN AFRICAN HOUSING FOUNDATION INTERNATIONAL CONFERENCE, EXHIBITION & HOUSING AWARDS SEPTEMBER 2013 CAPE TOWN, SOUTH AFRICA PUBLIC PRIVATE PARTNERSHIPS Full Life Cycle Analysis of the Environmental Impact of Low- Income Housing in South Africa W. I. de Villiers Department of Civil Engineering Stellenbosch University, Tel: ; Fax: Prof W.P. Boshoff, A van Noordwyk, C Brewis, J Brits Department of Civil Engineering Stellenbosch University, bboshoff@sun.ac.za Tel: ; Fax: Keywords: LCA, environmental impact, low-income housing, South Africa Abstract This paper reports on the full life cycle analysis done on the pre-use, use and end-of-life phases of a South African low-income housing unit, to determine its environmental impact. A conventional block-and-mortar unit is compared to a light steel frame building unit of the same layout and dimensions. The environmental impact indicators used are carbon footprint, acidification potential, eutrophication potential, resource depletion and waste to land fill. The housing units were segregated and analysed according to the following components: foundation, walls, roofing, and transport. It was found that the results of the analyses, and subsequent environmental impacts, are sensitive to the system boundaries defined, especially the transport distances and waste disposal options selected. A number of important issues are highlighted, including the need to develop emission, normalisation and weighting factors relevant to the South African geographical, social and political context.

2 Introduction Since 1994 it is estimated that 3.3 million government subsidised housing units have been constructed in South Africa (Sexwale, 2013). It is also estimated that the country has a housing backlog of a further 2.1 million units. These figures represent a significant volume of construction and use of building materials. The materials commonly used in the construction of housing, namely cement and steel, are known to have significant environmental impacts, including harmful emissions and extensive use of non-renewable resources. The production processes of cement and steel both result in the emission of nitrogen oxides (NO x ), carbon oxides (CO x ) and sulphur oxides (SO x ) (EEA, 2009). In 2009 at the UN Climate Change Conference held in Copenhagen, President Jacob Zuma pledged South Africa to reduce emissions by 34 % below business as usual levels by 2020 and by 42 % by 2025, given the necessary financial and technological support (Zuma, 2009). In addition to this, of the 59 billion metric tons of materials extracted globally on an annual basis, 70% is attributed to the growth in human population (Krausmann et al, 2009). South Africa is also experiencing immense pressure on landfill sites. Construction and demolition (C&D) waste accounts for 10-20% of landfill space and reduction and recycling of this waste is an under-utilised strategy in this country (DEAT, 2005). There are therefore diverse and significant political, social and environmental pressures to reduce emissions, the use of non-renewable materials and to reduce the generation of waste in the construction of low-income housing. In order to do this, it is necessary to determine the current levels of emission, resource depletion and waste generation associated with the construction of low-income housing. This paper reports on the full life cycle analysis done on the pre-use, use and end-of-life phases of a South African low-income housing unit, to determine its environmental impact. The environmental impact indicators used are carbon footprint, acidification potential, eutrophication potential, resource depletion and waste generation. Although the environmental impact of a conventional block-andmortar unit is compared to a light steel frame building (LSFB) unit, the focus is less on comparing different types of construction but to obtain a general sense of whether the environmental impacts are significant and on which aspects attention must be focused to reduce the overall environmental impact of low-income housing. Life Cycle Analysis A full life cycle analysis (LCA) is used to determine the environmental impact of the housing units under consideration. A LCA is based on building life cycle theory, shown in Figure 1. The life cycle of a building is compartmentalised into the pre-use phase which includes all production and construction processes, the use phase, which covers the operational life of the building, including any maintenance, and the end-of-life phase of the building, which includes the demolition of the building and treatment of waste that is generated. Figure 1: Building life cycle theory (Wang et al, 2005)

3 ISO 14040:2006 Environmental management - Life cycle assessment defines the four phases of a LCA. These are goal and scope definition, inventory analysis, impact assessment and interpretation of the results. In the first phase the objective and system boundaries are determined. In the second phase the different components that are to be considered are quantified and in the third phase the impact associated with these components are determined. In the final phase the outcomes of the previous phase have to be interpreted and sensible conclusions drawn (Schreuer et al, 2003). For the third phase of a LCA, the quantification of the environmental impact, two different approaches can be used. The first approach is application oriented. This is a straightforward checklist approach based on building life cycle theory, which considers the qualitative and quantitative aspects of a building s impact, using predefined relative scores. Familiar application orientated methods include the United Kingdom s Building Research Establishment Environmental Assessment Method (BREEAM), the United States Leadership in Energy and Environmental Design (LEED) (Liu et al, 2010) and South Africa s Green Star models. The second approach, which is analysis oriented, is also based on building life cycle theory, but it is considered a more scientific approach. The actual quantitative environmental impact of each component of the building is determined, generally obtained from a materials database. These impacts are then accumulated using normalisation or equivalency and weighting factors for an overall environmental impact index. Popular examples of analysis orientated methods are the Building for Environmental Sustainability (BEES) model developed in the United States, the Canadian Athena model (Liu et al, 2010), the CML 2001 model developed by Leiden University, the Environmental Design of Industrial Products (EDIP) 1997 and 2003 models developed in Denmark, and the Ecoindicator 99 method developed by Goedkoop and Spriensma (1999) (Hishier & Weidema, 2010). However, these methods generally require the use of expensive software, are complex in their application and limited to the geographical context in which they were developed. The method used in this paper incorporates five different indicators, thereby covering a broad scope of different environmental impacts, but is still simple to apply. The proposed indicators are discussed in the following section. Environmental Impact Indicators The production process of cement contributes between 3% and 6% to global carbon dioxide annual emissions (Marland et al, 2007, Jegatheesan et al, 2009), as well as nitrogen oxides (NO x ), sulphur dioxide (SO 2 ) and carbon monoxide (CO) (EEA, 2009). The principal gas emissions in the steel production process are CO, SO x and NO x (EEA, 2009). Every material used over the life time of a housing unit has its origin in a natural resource. The depletion of these resources, as well as the waste that is generated in the construction, maintenance and demolition of a house must also be taken into account. Five environmental impact indicators were selected for the quantification process, of which the first three are emissions: EI 1 : carbon footprint (CF) EI 2 : acidification potential (AP) EI 3 : eutrophication potential (EP) EI 4 : resource depletion (RD) EI 5 : waste generation (WG) A brief discussion of each of these indicators follows.

4 EI 1 : Carbon Footprint (CF) Carbon footprint represents the greenhouse gases (GHG s), which include carbon dioxide (CO 2 ), methane, (CH 4 ), nitrous oxide (N 2 O), hydrofluorocarbons (HFC s), perfluorocarbons (PFC s) and sulphur hexafluoride (SF 6 ). The first three of the GHG s are commonly related to the built environment. To quantify the carbon footprint, these different gasses all need to be expressed in terms of carbon dioxide equivalents (CO 2eq ) (Azapagic et al, 2004). The relative effects that these gasses have on global warming, known as global warming potential (GWP) factors, are used to convert them to CO 2eq. Each material or production process involved in the creation of a housing unit is quantified in terms of the mass flow involved in the process ( ). Each mass flow also has an associated emission factor, which depends on the constituent materials and processes it undergoes ( ). The quantification of a specific mass flow (in kg) is then as follows: (Eq. 1) The conversion of different gas emission types to carbon dioxide equivalents is done as follows: (Eq. 2) where is the global warming potential factor shown in Table 1 and is the amount of mass flow, or gas emitted, in kg as determined in Equation 1. Table 1: GWP factors (Pachauri & Reisinger, 2007; Johnke et al, 2000) GHG Name Chemical Formula GWP for a 100-year time horizon Carbon dioxide CO 2 1 Oxides of nitrogen NO x 8 Methane CH Nitrous Oxide N 2 O 310 Ammonia NH 3 Not defined EI 2 : Acidification Potential (AP) Acidification of water and soil occurs mainly due to the transformation of gas pollutants such as SO 2 and NO x into acids such as HNO 3 and H 2 SO 4. Acidification potential is quantified in sulphur dioxide equivalents (SO 2eq ) and the acidification potential value, or second environmental impact, is then determined as follows: (Eq. 3) Where is the acidification factor shown in Table 2 and is the amount of mass flow, or gas emitted, in kg as determined in Equation 1. Only the emissions most relevant to the built environment are included. Table 2: Acidification factors (Azapagic et al, 2004; Azapagic et al, 2003) Name Chemical Formula Acidification factor (f) Oxides of nitrogen NO x 0.7 Sulphur dioxide SO 2 1 Ammonia NH

5 EI 3 : Eutrophication Potential (EP) Eutrophication potential is also included in the environmental impact indicators as this plays a significant role, especially in the landfilling of waste materials. Nutrients are leached from landfilled waste (Azapagic et al, 2004) and cause over fertilization of the soil, as well as ground water. This in turn leads to the release of foul odours, poisoning of fish and other water animals, and the intake of toxins by humans and livestock (Norris, 2003). Nitrogen and phosphates are the largest contributors to eutrophication. Eutrophication is measured in nitrogen oxide equivalents (NO 3e ) and is determined as follows: (Eq. 4) Where is the eutrophication potential factor shown in Table 3 and is the amount of mass flow, or gas emitted, in kg as determined in Equation 1. Table 3: Eutrophication potential factors (Heijungs et al, 1992) Name Chemical Formula Eutrophication factor Oxides of nitrogen NO x 1.35 Ammonia NH Ammonium NH Nitrate NO 3 1 Phosphorous PO Phosphorous pentoxide P 2 O EI 4 : Resource Depletion The fourth environmental impact indicator to be used is the depletion of natural resources. There are methods that make use of indexes or reserve-to-use ratios, but these are very complex in their implementation. Wang et al (2005) recommend using exergy to quantify the depletion of natural resources. Exergy is the maximum obtainable work potential of a material flow or process relative to its environment (Cornelissen et al, 2000). It is therefore the available energy that can be extracted from a system to bring it to equilibrium with its environment (Wang et al, 2005). A resource is a material which is in disequilibrium with its environment and therefore possesses exergy (Cornelisson et al, 2000). Processes such as refinement of a resource add value and exergy to that material (Rosen et al, 2008) and a direct relationship exists between the exergy use of fossil fuels and minerals, and the impact on the depletion of natural resources (Cornelissen et al, 2000). The first law of thermodynamics states that energy is conserved in all processes, even if it is converted. The second law of thermodynamics takes cognisance of the loss or gain of the quality or usefulness of the energy during conversion, in the so called non-conservation of entropy (De Meester et al, 2009). Exergy includes this quality concept and takes this another step further as it is also a measure of the potential for effecting change. Exergy is measured in Joule (J ex ). If a system is in equilibrium with the reference environment, then it has an exergy of zero (Rosen et al, 2008). This reference environment is defined at a temperature of 289K and atmospheric pressure of Pa (De Meester et al, 2009). The quantification of cumulative annual exergy demand is as follows according to De Meester et al (2009): 1. An inventory of all the materials and energy for the full life cycle is drawn up per annum

6 2. The embodied energy of the materials is calculated, using the Ecoinvent database for the Swiss Centre for Life Cycle Inventories 3. The embodied energy calculated in Step 2 is converted to exergy using the exoinvent method developed by De Meester et al (2009), together with earlier research done by Dewulf et al (2007) The last step requires conversion factors, called X-factors, which quantify the cumulative exergy extraction from the natural environment (Dewulf et al, 2007). These factors are defined as the exergy content in MJ ex /unit of reference flow. The Cumulative Exergy Extraction from the Natural Environment (CEENE), for a product j is determined as the sum of all reference flows, using the relevant X-factor, in MJ ex. This is the fourth environmental impact (EI) and is determined as follows: (Eq. 5) Where is the X factor for the reference flow and is the amount of reference flow required to produce product (Dewulf et al, 2007). EI 5 : Waste Generation The final environmental impact indicator measures the effect of construction and demolition (C&D) waste going to landfill. Current volumes of C&D waste are using up valuable landfill space and leading to illegal dumping of waste (dos Santos & Branco, 2004). A number of recycling and other waste reduction or diversion strategies can be employed, but the reality in South Africa is that most C&D waste goes to landfill. The final environmental indicator is therefore determined as follows: (Eq. 6) where is the total mass of waste (in kg) resulting from the demolition of the structure and is the material specific waste fraction factor, (in kg/kg), obtained from the materials database used. A summary of all the impact indicators discussed is shown in Table 4. Table 4: Environmental Indicators Indicator Formula Unit EI 1 Emission Carbon Footprint EI 2 Emission Acidification Potential kg CO 2eq kg SO 2eq EI 3 Emission Eutrophication Potential kg NO 3eq EI 4 Resource Depletion EI 5 Waste Generation J ex kg

7 The Swiss developed database, Ecoinvent, is used to obtain the environmental impact values for all the materials used in the housing units, according to the five selected environmental indicators. The Ecoinvent database was initiated in the early 1990 s by the Swiss Centre for Life Cycle Inventories. They are the world leaders in transparent and consistent life cycle inventory data and are recognized worldwide (Frischknecht & Jungblut, 2007). Normalisation and Weighting Factors In order to make the different environmental impacts comparable, they each need to be normalised and weighted into a single Environmental Impact Index (EII). No consensus has been reached in current research on how this aggregation should be done. A number of techniques are available to achieve this, including expert decision and analytical studies. Some even argue that trying to combine all impacts into one comparative index obscures the results and that a disaggregated form is of more value (Azapagic et al, 2004). However, for the purpose of this study, to determine which elements of a low-income housing unit have the greatest environmental impact, it is more useful to determine a comparative, accumulated single index. The normalisation is done by dividing each environmental impact by a common reference. The common reference used in this study is the average yearly environmental load in a specific region, divided by the number of inhabitants (per capita, per year). This is a widely used common reference (Goedkoop et al, 2008). The normalised environmental impacts are then multiplied by dimensionless weighting factors, which are based on political reduction targets for each environmental impact category (Stranddorf et al, 2005). Normalisation and weighting factors based on a global reference region are preferable, but not available in most instances. In these cases, the factors that are available have been used. Note that normalisation and weighting factors should be developed for Africa, as political reduction targets could vary greatly from those for Europe. The normalisation and weighting factors used in this study are shown in Table 5. Table 5: EDIP normalization and weighting factors (Stranddorf et al, 2005; Goedkoop et al, 2008) Environmental Impact Normalisation Unit (/capita/year) Value Weighting Factor Reference Region EI 1 Carbon Footprint kg CO 2eq Global EI 2 Acidification Potential kg SO 2eq Europe EI 3 Eutrophication Potential kg NO 3eq Europe EI 4 Resource Depletion MJ ex EI 5 Waste Generation kg Denmark The environmental impact EI 4, Resource Depletion, cannot be aggregated into the single EII as the weighting factors used for resources are based on proven reserves per person and not on political reduction targets (Goedkoop et al, 2008).

8 Reference Housing Project The proposed environmental impact index analysis method was applied to both a conventional blockand-mortar unit and a LSFB unit. One of the housing unit types used in an existing project, Watergang Housing Project, were used to define the conventional block-and-mortar housing unit. Watergang Housing Project is located in Kayamandi, Stellenbosch, shown in Figure 2, and was completed in April The 40m 2 single unit was used as the reference housing unit for the analysis. The plans, details and bill of quantities of this unit type were obtained. An equivalent LSFB housing unit was then designed based on these specifications. The unit layout of both the (a) block-and-mortar unit and the (b) LSFB unit are shown in Figure 2. Examples of the conventional block-and-mortar (a) and LSFB building systems (b) used are shown in Figure 3. Figure 2: Layout of a) a conventional block-and-mortar housing unit and b) a LSFB housing unit

9 Figure 3: Example of the a) conventional block-and-mortar and b) LSFB building systems Defining the system boundaries is a crucial step in the process. Deciding which processes are to be included in the analysis, and which are to be excluded, can have a significant impact on the outcome of the results. Figure 4 defines the system boundary for the study. The system boundaries for the block-and-mortar and LSFB units are similar and both include the transport related to building envelope materials, but both exclude the finishes and services. These latter aspects would be the same for both unit types, and would therefore only increase the overall environmental impact index by the same amount, and can thus be considered common factors. Figure 4: System boundary for the reference unit The housing units were both segregated and analysed according to the following components: Foundation (foundation and floor slab), Walls (external and internal walls), Roofing (roof structures, roof covering, ceiling and insulation) and Transport. The impact of the transport of the materials is included in the material impact factors, but these are based on European conditions, with generally higher population densities and shorter transport distances. In order to take this into account, additional transport distances are included. Transport therefore includes the impact of an additional 100km of transport of all materials to site during the pre-use and use phases, as well as and additional 15km from site to landfill during the end-of-life phase. Assumptions The following assumptions were made in the analysis of the housing units: - Project and construction time is estimated at 1 year, which facilitates the normalisation and comparison process. - Design working life of the housing unit was set as 30 years (SANS B, 2012, ), with maintenance performed on the ceiling, insulation, roof covering and plastering of the external walls every 10 years (SANS B, 2012, ), resulting in two maintenance procedures. - A truck size of 3.5 to 7.5t was used for the transportation of materials. - To account for South Africa s lower population density and greater transport distances, an additional 100km from production plant to site and 15km from site to landfill were included - At the end-of-life phase all material is taken to landfill and no recycling takes place.

10 Full Life Cycle Analysis Results The purpose of this study was to determine which elements in a low-income housing unit have the greatest environmental impact, thereby informing further research into the development of building materials with lesser environmental impacts. The results are therefore presented as a single aggregated Environmental Impact Indicator (EII) per housing element type, Foundation, Walls, Roofing and Transport, in Figure 5. This impact includes the effects of all three phases of the life cycle, and is a combined normalized and weighted impact of Carbon Footprint (EI 1 ), Acidification Potential (EI 2 ), Eutrophication Potential (EI 3 ) and Waste Generation (EI 5 ). The impact category of Resource Depletion (EI 4 ) is presented separately in Figure 6 as the weighting factor for this impact category is not commensurable with the other categories. The results are shown for both the conventional blockand-mortar (B&M) and LSFB housing units. Figure 5: Environmental Impact Indicator (EII) for full life cycle per house element including EI 1, EI 2, EI 3 and EI 5

11 Figure 6: Resource Depletion (EI 4 ) for full life cycle per house element Figure 5, containing the most environmental impact indicators, shows that the elements with the greatest environmental impacts over the life cycle of both the block & mortar and LSFB housing units are Walls and Foundations. These results indicate that efforts to reduce the environmental impact of low-income housing should be concentrated on finding alternative solutions to walling and foundation systems, especially ones with a reduced end-of-life phase impact. Emphasis must be placed on systems and materials that can be reused and recycled effectively and efficiently. When considering only Resource Depletion, in Figure 6, all house elements make a significant contribution, but it is again Walls that use the greatest amount of resources in the case of LSFB, and Roofing for both LSFB and conventional block-and-mortar. To use materials as optimally and efficiently as possible remains important. Sensitivity Analysis Sensitivity analyses were done with regards to the transport distances, disposal option at the end-oflife phase and the weighting factors. For the transport sensitivity analysis, the additional transport distance from production plant to site in the pre-use phase, originally assumed to be 100km, was varied between 0 and 200km. The additional transport distance from site to landfill location in the end-of-life phase, originally assumed to be 15km, was varied between 0 and 20km. The sensitivity analysis found that transport distance has a significant impact, but that the volume of material transported is of greater significance. In the disposal option sensitivity analysis, different disposal strategies for the end-of-life phase were considered, namely landfilling, recycling and incineration. Recycling made a significant difference on the environmental impact of both the conventional block-and-mortar and LSFB housing units.

12 However, little difference was found between the landfilling and incineration disposal options, due to the emissions which are still released during the incineration process. Certain weighting factors were chosen from literature for this study, but a range of weighting factors for each environmental impact category exists. These factors range between 1.05 and 1.34 between the different categories. The sensitivity of the EII to the weighting factors was therefore also investigated. It was found that the most significant sensitivity lies in the end-of-life phase for EI 5, the Waste Generation impact category. Whilst South Africa s landfill sites are under pressure, the circumstances in Europe are even worse, which could be the reason for the sensitivity of the EII to Waste Generation. For more detailed results on the sensitivity analyses, and the study in general, the reader is referred to Brewis (2012) and Brits (2012). Conclusions & Recommendations The results of the analysis show that the largest contributors to the EII within the different house elements are Walls and Foundations. The overall volume of material used to construct these elements can be reduced to a degree, to minimise the effect on Resource Depletion. However, the most significant difference can be made by devising walling and foundation systems using materials that can be reused or recycled effectively, to minimise the impact of the end-of-life phase. Note that the normalization and weighting factors used were developed for European or Global conditions. Factors that take the unique conditions in Africa into consideration, such as greater availability of land space, lower population densities, lower GDP s and generally different political and social priorities, do not exist but could influence the results of the analyses. To accurately reflect the local environmental impacts, such African normalization and weighting factors need to be developed. References Azapagic, A., Ernsley, A., Hamerton, L Polymers, the Environment and Sustainable Development. John Wiley & Sons Ltd. Azapagic, A., Perdan, S. & Clift R Sustainable Development in Practice: Case Studies for Engineers and Scientists. Chichester: John Wiley & Sons Ltd. Brewis, C Quantifying the environmental dimension of sustainability for the built environment: with a focus on low-cost housing in South Africa. Stellenbosch University MScEng Thesis. Available at: Brits, J Quantifying the sustainability of the built environment: Model for the determination of the environmental impact of the end-of-life phase. Stellenbosch University MScEng Thesis. Available at: Cornelissen, R.L., Nimwegen, P.A. & Hirs, G.G Exergetic Life Cycle Analysis. Proceedings of ECOS 2000, Enschede. De Meester, B., Dewulf, J., Verbeke, S., Janssens, A. & Van Langehove, H Exergetic life cycle assessment (ELCA) for resource consumption evaluation in the built environment. Building and Environment 44: Department of Environmental Affairs and Tourism (DEAT) National Waste Management Strategy Implementation South Africa: Recycling. Dewulf, J., Bösch, M.E., De Meester, B., Van der Vorst, G., Van Langenhove, H., Hellweg, S. & Huijbregts, M.A.J Cumulative Exergy Extraction from the Natural Environment (CEENE): a

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