Life-cycle assessment framework [18
When LCA is applied to the building, the product studied is the building itself, and the assessment will be defined according to a certain level and contain all the materials processes. This level could be called “whole process of building” and there are many tools available to work at this level, e.g., BREEAM, (UK). If the LCA is concerned with a part of the building, building component or material, the level could be called “building material and component combination” (BMCC), and in this case it is very important to recognize the component impact equivalent according to the functional unit of the building.
6.1. Goal and Scope Definition
The first step of life-cycle assessment, this is a critical step to identify the purpose of the study, and determine the questions to be answered. It can affect the results of the LCA [20
]. Within this step the study holder forms the objectives, limitations and constraints of the study, and sets many important assumptions: mainly identifications of system boundaries, such as the full life time of a product or one phase of production; functional unit e.g., m2
floor area; data quality; and other limits. These should all be specified at this stage. The goal definition and scoping exercise ultimately defines the direction of the study and the benchmarks, with which the study will later be appraised in the interpretation stage. Within the life-cycle of any product there might be some areas of limited interest, these could be omitted within this phase, however, even describing the elements of whole life-cycle in general fashion will prevent missed opportunities for improvement [20
]. The goal and scope of a study may change according to many considerations within the study e.g., data unavailability, impact insignificance, etc. According to ISO 14040, the goal of any LCA states the intended application, the reasons for carrying out the study and the intended audience. This includes the product system to be studied, its functions, the functional unit, the system boundaries, allocation procedures, impact categories selected, methodologies of impact assessment, data requirements, assumptions, limitations, initial data quality requirements, and the type of critical review and report required for the study [18
]. The functional unit determination in this phase is critical as it is a reference to which all the inputs and outputs are related, and in the case of buildings there are many functional units which could be considered (m2
, each, number of occupants, etc.).
The general goal of holding an LCA on the level of buildings is to minimize the environmental burdens over the whole life-cycle [19
]. Whether designer or researcher, the life-cycle practitioner will have direct effect on the type of audience. In the case of designers the audience may be clients, but in the case of researchers the audience may be policy-makers, developers and investors. Buildings are always described as complex products, complexity which lays in the process of production. Due to the complexity of construction industry and the long life span of buildings, and because the scenarios within a building life span are not very clear, all subsequent phases of LCA will affect and modify the goal and scope definition phase in some way or another, so it will need review and modification within and after each phase.
LCA studies in the literature differ in terms of their goal and scope definition, and it is sometimes clear that their goals have changed according to unexpected problems raised during the LCA studies. Scheuer et al
. employed an LCA to find the environmental burdens of a university building in Michigan [31
]. They set the study boundaries to include only the building itself (structure, envelope, interior and backfill), and set the life span to 75 years, which is very long compared to most other studies, which typically assume 50 years. The study neglected the insignificant contributions, e.g., impacts from facilities used for production, and omitted the factors which are not related to building design, e.g., furniture, movable partitions, street and side walk modifications, etc. Lack of data had its influence on the scope of the study due to data unavailability; the study holder was forced to omit materials used during the construction process, and small replacement materials. For this case the materials omitted did not affect the results significantly, but in other cases, unavailability of national and realistic data might drive the study in the wrong direction, or change its goal and scope [31
]. Junnila et al
] assumed the study boundaries to be from raw materials acquisition through production and use to disposal. The main purpose of the study was to find the environmental impacts of a specific well described high-end office building in Finland, and used a national up-to-date manufacturer’s data, verified by independent third party. Lack of data affected the study, forcing omission of heavy metal emissions from transportation and use of construction equipment. The life span was assumed to be 50 years as in many other LCA studies applied to buildings. The study was limited to calculating the impact categories identified as most important in Finland, but again lack of data had its influence on the study forcing omission of ozone depletion and biodiversity, although they were mentioned as most important within the Finnish impact categories list [32
]. Within the goal and scope definition phase, Asif et al
. addressed eight different materials (timber, glass, concrete, aluminum, ceramic tiles, plaster board, slate and damp course), which he considered as significant in the studied Scottish house [33
]. The study identified five main materials, which are most important in terms of their embodied energy. The studied house had a specified description and layout, and the study allocated the embodied energy distribution according to the studied materials, and calculated one impact category - global warming potential [33
In many other examples of LCA studies presented later, it is clear that one of the main reasons hindering comparison is the difference in goal and scope definition. Within the goal and scope definition, a well established description of the case study building is necessary. The description should include as much detail as possible starting with: the function and the geographical location of the building, and passing through other technical features. The system boundaries should be clearly set, whether the study will consider the whole building life-cycle, or one phase of it; the whole building, or one system; and the environmental impact categories to be studied should be determined. Within this step, the LCA practitioner should also consider the functional unit, methodologies of impact assessment, data requirements, assumptions, limitations, initial data quality requirements, type of critical review and type of the report required for the study [18
In the case of whole building LCAs, the functional unit could be one of many (m2
internal space, m3
, each, number of occupants, etc.). The ease of comparing the outcome of the study to other studies is a very important factor in determining the functional unit [34
]. There have been many attempts to standardize the functional unit for buildings e.g., [16
], but there are no results available yet. Within the literature the most commonly used functional unit in life-cycle assessment of buildings is square meter floor area, however in specific cases this unit had been changed, for instance some studies considered the square meter of living floor area in the case of dwellings, some others used the ton of material as the unit when the study is related to a material environmental burden. It is important to note that all the environmental impacts calculated within one LCA study must refer to the chosen functional unit.
6.2. Inventory Analysis
The second step of the LCA is inventory analysis. It contains the “data collection and calculation procedures” [18
], and is of key importance since this data will be the basis for the study. Inventory is also tied to the scoping exercise since data collection and other issues may lead to refinement or redefinition of the system boundaries. Lack of data may result in changing the scope and/or objectives of the study, so data completeness is very important. ISO defines several levels in the inventory phase starting by data collection from available high quality resources; passing through data calculation, which involves validation of data collected, relating data to unit processes and relating calculated data to functional unit, down to allocation procedures when dealing with systems involving multiple products and recycling systems. The wider the system boundaries, the less the need for allocation, and in some cases there is no need for allocation, especially when there are no multiple products, and when the system boundaries are very wide (e.g., from cradle to grave) [20
]. Choosing the most appropriate data is critical as the quality of data sources is very important to assure the correctness of the results, and in some cases the data will drive the study and determine its quality level. Data quality is very important to determine the success of the study or its failure. Data nationality is an important factor to be considered when choosing the data sources (Table 1
This step is the more time intensive in the case of buildings as complex products (production process is complicated), the data collection includes all data related to input-output of energy, and mass flow in terms of quantities and emissions to air, water and land [35
]. The life-cycle of a building consists of many phases. The number of phases differs according to the goal of the study, and it could be three or more, but the sum of the proposed phases must result in the whole life-cycle of the building in all cases. For example, some studies use three phases starting by the pre-construction phase, which includes all the processes from materials extraction up to the start of building occupation, followed by usage phase, and ending with demolition phase, but each of these phases could be divided into many sub-phases according to the goal and scope of the study.
The life-cycle inventory phase (LCI) generally uses databases of building materials and component combinations. The availability and accuracy of data should always be clearly described within the goal and scope definition phase. This concerns the materials, components, and scenarios already finished, but building construction includes past, current and future activities and scenarios. All of them, and any assumptions related to them should be clearly mentioned [19
]. What is generally included within an LCA of buildings is the embodied energy of materials and building component combinations, the transport of materials and building components to site, the use of the building (as energy use), the waste of materials (sometimes), water consumption (sometimes), maintenance and replacement, demolition of the building, and transport of waste to the treatment site. What is generally not included is the transport of equipment to site, the construction phase at the site of the building, and construction waste [36
]. The goal of the study is the main driver to determine what is and what is not included, and data availability has direct effect on this as well, and it consequently can change the goal of the study. Whether included or not any process or item within the life-cycle assessment must be set clearly in the scope of the study, because any process included in the life-cycle of a building requires data to be included in the data inventory, whether collected, measured or estimated. The data should quantify the input and output of the building, and should be described well and thoroughly referenced.
Life-cycle inventories, until recently, lacked completeness and many problems hindered the production of an internationally accepted protocol to be used in LCA analyses. Currently available databases fit four categories: Public database developments, academic, commercial, and industrial [37
]. The most important is the fact that these data differ from one source to another in many ways: mainly boundary definitions, energy supply assumptions, energy source assumptions, product specifications, manufacturing differences, and complications in economic activities [37
]. For example, Sinclair [38
], found a variation in the embodied energy of a brick of between 5 and 50 MJ. Geographical factor has the greatest effect, as it underlies most of the variations mentioned early in this paragraph; accordingly it is important for each country to have its own data according to its construction industry resources and traditions. LCI involves collecting data for each unit process regarding all relevant inputs and outputs of energy and mass flow, as well as data on emissions to air, water and land. It includes calculating both the material and the energy input and output of a building system. The limitations associated with LCI have a subsequent impact on the reliability of the overall LCA findings. A higher level of completeness and reliability in LCI is needed to permit a more accurate and precise assessment of life-cycle environmental loadings from the manufacture of a particular product. There are many methods to calculate the LCI across a range of disciplines, but many obstacles are still unresolved. A lack of transparency between data centers (data or data origins and references are not accessible) makes it difficult to compare the results. There are some national and international databases that might be accepted in some cases, but in detailed local studies these databases should not be used as the international ones differ, and the national ones generally discuss the simple basic construction materials [37
]. However, these could be identified as a background source of data.
Researchers suggest that three approaches could be used to overcome data problems, namely process analysis, input/output analysis and hybrid analysis. The traditional method is process analysis, involving analysis of direct and indirect energy inputs to each product process. It usually begins with the final product and works backwards to the point of raw material extraction. In many cases the process of production might be difficult to understand, and problems will arise in the calculation phase, because of this lack of understanding. So this method is impracticable on its own [39
]. Process analysis results are found to be considerably lower than the findings of other methodologies [40
]. Input/output analysis can overcome the problems of process analysis. It is based on input/output tables, where the inputs may include energy and natural resources, and the outputs may include CO2
and other gases emissions. Both methods are widely used, but each of them has its own benefits and disadvantages. Process analysis can be significantly incomplete, due to complexity of the requirements for goods and services [41
]. While the accuracy of process analysis method can be higher, it is only relevant to the particular system considered, and can be subject to considerable variability [42
]. Input/output analysis uses national average data of each sector of the economy, and is considered to be more comprehensive than process analysis [41
]. It has a complete system boundary, but is generally used as a black box, with little understanding of the values being assumed in the model for each process. This method could give valuable estimates of the embodied energy but it is not as accurate as process analysis. Hybrid analysis is a combination of both methods and results in better quality data inventories. It minimizes the limitations of the other methods, and there are several types of hybrid analysis: input/output based hybrid analysis, process based hybrid analysis, tiered hybrid method and integrated hybrid analysis. Each works in a different way to deal with the deficiencies of traditional methods (the incompleteness of process analysis, and the low level of accuracy in the case of input/output analysis).
The quality of life-cycle assessment is directly related to the quality of inventory data, its correctness and its concordance with the goal of the study. The source of data might be one or more of direct measurements, laboratory measurements, governmental and industrial documents, trade reports and databases, national databases, environmental inventories, consultancies, academic sources, and engineering judgments [43
]. The source of data plays a role in its reliability, accompanied by acquisition methods and verification procedures used. Another important factor to be considered is the completeness of data, which relates to its statistical properties, and shows how representative the sample is, and whether the sample includes a sufficient amount of data. Three other indicators relate to the correlation between the data and the data quality goals, namely temporal correlation, geographical correlation, and technological correlation [44
]. Data quality indicators should be used to improve the data collection strategy, allowing the study holder to highlight the main data problems in the study, and help overcome data problems. Table 1
gives criteria for assessing the quality of data for LCA.
Data quality assessment matrix [44
Data quality assessment matrix .
|Reliability||Verified data based on measurement||Verified data partly based on assumptions or non-verified data based on measurements||Non-verified data partly based on assumptions||Qualified estimate (e.g., by industrial expert)||Non-qualified estimate|
|Completeness||Representative data from a sufficient sample of sites over an adequate period to even out normal fluctuations||Representative data from a smaller number of sites but for adequate periods||Representative data from an adequate number of sites but from shorter periods||Representative data but from a smaller number of sites and shorter periods or incomplete data from an adequate number of sites and periods||Representativeness unknown or incomplete data from a smaller number of sites and/or from shorter periods|
|Temporal correlation||Less than three years different from year of study||Less than six years different||Less than 10 years different||Less than 15 years different||Age of data unknown or more than 15 years different from year of study|
|Geographical correlation||Data from area under study||Average data from larger area in which the area under study is included||Data from area with similar production conditions||Data from area with slightly similar production conditions||Data from unknown area or area with very different production conditions|
|Technological correlation||Data from enterprises, processes and materials under study||Data from processes and materials under study but from different enterprises||Data from processes and materials under study but from different technology||Data on related processes or materials but same technology||Data on related processes or materials but different technology|
Some databases and tools of life-cycle assessment of WCP and BMCC.
Some databases and tools of life-cycle assessment of WCP and BMCC.
|Athena||Canada||Database + Tool||Academic||whole building design decision||Eco Calculator||www.athenaSMI.ca|
|Bath data||UK||Database||Academic||product comparison||No||people.bath.ac.uk/cj219/|
|BEE||Finland||Tool||Academic||whole building design decision||BEE 1.0||--------------------------|
|BEES||USA||Tool||Commercial||whole building design decision||BEES||www.bfrl.nist.gov/oae/software/bees.html|
|BRE 3||UK||Database + Tool||Public||whole building assessment||No||www.bre.co.uk|
|Boustead||UK||Database + Tool||Academic||product comparison||Yes||www.boustead-consulting.co.uk|
|DBRI 4 Database||Denmark||Database||Public|| ||No||www.en.sbi.dk|
|ECO-it||NL||Tool||Commercial||whole building design decision||ECO-it||www.pre.nl|
|ECO methods||France||Tool||Commercial||whole building design decision||Under development||www.ecomethods.com|
|Eco-Quantum||NL||Tool||Academic||whole building design decision||Eco-Quantum||www.ecoquantum.nl|
|Envest||UK||Tool||Commercial||whole building design decision||Envest||envestv2.bre.co.uk|
|Gabi||Germany||Database + Tool||Commercial||product comparison||Gabi 4||www.gabi-software.com|
|KCL-ECO||Finland||Tool||Commercial||product comparison||KCL-ECO 4.1||www.kcl.fi/eco|
|LCAiT||Sweden||Tool||Commercial ||product comparison||LCAiT||www.ekologik.cit.chalmers.se|
|LISA||Australia||Tool||Public||whole building design decision||LISA||www.lisa.au.com|
|Optimize||Canada||Database + tool||---------||whole building design decision||Yes||-----------------------|
|SEDA||Australia||Tool||Public||whole building assessment||SEDA||-----------------------|
|Simapro||NL||Database + Tool||Commercial||product comparison||Simapro 7||www.pre.nl|
|TEAM||France||Database + Tool||Commercial||product comparison||TEAM 3.0||www.ecobilan.com|
|Umberto||Germany||Database + Tool||Commercial||product comparison||Umberto||www.umberto.de|
|US LCI data||USA||Database||Public||product comparison||No||www.nrel.gov/lci|
Some of the datasets listed in Table 2
are complete, or there are extensive efforts of people working on completing them, but due to the wide range of materials in the construction industry, and the variety of construction techniques, none of these tools and data sets are able to model or compute the environmental impacts of a whole building or construction, including all the life-cycle phases and production processes in detail [31
]. The databases and tools listed vary according to study goal, users, application, data, and geographical location [35
]. Databases differ from one country or region to another according to many factors, including energy sources, supply assumptions, product specifications, manufacturing differences and complications in the economic activities [37
]. Each of these factors can produce significant variations in the environmental impact assessment, for instance, (whether delivered or end use) energy supply assumptions can cause significant differences in the embodied energy calculations, as different countries have different energy sources. For example, France depends strongly on nuclear power, while the UK depends more on gas and electricity, and this fundamental difference in the energy sources affects the environmental impacts of production.
The key steps to produce a life-cycle inventory are to: develop a flow diagram of the process being evaluated, develop a data collection plan, collect the data, and evaluate and report the results. The diagram of the process should be as detailed as possible to get a high level of accuracy, which means spending more time to get this level of detail in this step, which is already time and effort intensive. Of course the more detailed the diagram is, the more accurate the results are. Figure 2
is an example of a process flow diagram.
Medium detailed flow diagram of a building/construction.
Medium detailed flow diagram of a building/construction.
After drawing the detailed production diagram, the next step will be setting a data collection policy, and it will be useful to start by dividing the flow into sub flows, to be able to understand the inputs and outputs of each sub phase of the process. Defining data quality goals and setting benchmarks will take place before data collection, to test whether the data meets the goal requirements. Data sources and types should be explained well within this step, and then at the end of this step data spread sheets should be produced [43
]. After that, the data collection step will start followed by evaluation and validation of data, according to the benchmarks already set [45
]. The next step will be relating data to the functional unit of the building, which is different from the functional unit of BMCCs. For example, the functional unit of the concrete might be a ton of material, while the functional unit of the building might be m2
of floor area, so to relate the quantity of concrete used within the building to the functional unit used the sum of concrete used is divided by the area of the building (Figure 3
Simplified procedures for inventory analysis [45
Simplified procedures for inventory analysis [45
In the case of studying the whole life-cycle of a building using process analysis, there is no need for allocation procedures, which means distributing the impacts and relating them to the unit process. The allocation procedures are dependent on and directly related to the goal of the study. For example, if the goal of the study is to compare building systems in terms of their environmental impacts, the allocation procedures will be different from comparing the impacts of construction phases. The last step in the data inventory analysis is refining the system boundaries. This step includes verification of data collected using benchmarks, so the initial system boundaries may be revised, and then the results of the refining process and the sensitivity analysis shall be documented. Sensitivity analysis may result in exclusion of life-cycle stages or unit processes shown to have no significance, exclusion of inputs and outputs which are not significant to the results of the study, or inclusion of new unit processes inputs and outputs that are shown to be significant in the sensitivity analysis [45
6.3. Impact Assessment
ISO 14042 is the international standard for life-cycle impact assessment (LCIA); it defines the impact assessment as aiming to: “Examine the product system from an environmental point of view using impact categories and category indicators connected with the LCI results. The LCIA also provides information for the life-cycle interpretation phase [46
The impact assessment framework is a multi-step process, starting by selecting and defining impact categories, which are relevant to the buildings (such as, global warming, acidification, toxicity, etc., as listed in Table 3
which is an extended version of the table of published LCAs applied within the building sector in Europe and the USA within the last 15 years, produced by [35
] in 2007). This is followed by a classification step, which assigns LCI results to the impact categories, e.g., classifying carbon dioxide emissions as causing global warming, and modeling the impacts within impact categories using conversion factors, e.g., modeling the potential impact of carbon dioxide and methane on global warming using their respective GHG potentials [45
]. These steps could be followed by optional steps to express potential impacts in ways that can be compared. For instance, comparing the global warming impact of carbon dioxide and methane for two options, weight them and identify the most significant ones. At the end of the study all the results should be evaluated and reported [43
]. Impact categories could be grouped according to their region of effect, e.g., global warming has a global effect, whereas eutrophication has a local effect [45
The impact categories included within the LCA studies carried out by researchers of building environmental impacts differ according to the goal of the study, data availability, and significance of the impacts. For instance, among the researchers who produced whole construction process LCAs, Adalberth studied four dwellings located in Sweden and calculated five different impacts (GW, A, E, OD, HT, EL—Table 3
], however Peuportier studied three types of houses with different specifications located in France, and calculated twelve different impact categories [48
]. Again among other researchers who produced LCAs of BMCCs, Asif et al
. studied eight different building materials in a Scottish dwelling, and calculated one impact (GW) [33
], but Saiz et al.
studied green roofs in Spain and calculated eight different impacts [35
]. Within the literature of LCAs applied to whole buildings, the most commonly studied impacts were global warming, acidification, eutrophication, and ozone depletion, which were present in most studies (Table 4
Published LCAs applied within the building sector in Europe and the USA within the last 15 years, after [35
], with additional information.
Published LCAs applied within the building sector in Europe and the USA within the last 15 years, after , with additional information.
|Reference||BMCC||WPC||Content, country and year||Environmental impacts studied (see footnote)|
|Adalberth et al.|| ||x||Life-cycle of four dwellings located in Sweden (2001)||x||x||x||x||x||x||x|| || || || || || || |
|Ardente et al.||x|| ||LCA of a solar thermal collector, Italy (2005)||x|| || || || || || ||x|| ||x|| ||x||x|| |
|Asif et al.||x|| ||LCA for eight different materials for a dwelling in Scotland (2005)||x||x|| || || || || || || || || || || || |
|Citherlet et al.||x|| ||LCA of a window and advanced glazing systems in Europe (2000)||x||x||x|| ||x|| || || || || || || || ||x|
|Cole and Kernan|| ||x||LCA of a three-storey, office building for alternative structure materials in Canada.||x|| || || || || || || || || || || || || |
|Gustavsson and Sathre||x|| ||LCA Sweden case study: wood and concrete in building materials (2006)||x|| || || || || || || || || || || || ||x|
|Junnila|| ||x||LCA for a construction of an office: a Finland case study (2004)||x||x||x||x|| || || || || ||x|| || || || |
|Junnila and Horvath|| ||x||LCA of a high end office building in Finland (2003).||x||x||x||x|| || || || || ||x|| || || || |
|Junnila et al.|| ||x||Comparative LCA of office buildings in Europe and the United States (2006)||x||x||x||x|| || || || || || || || || || |
|Koroneos and Dompros||x|| ||LCA of brick production in Greece (2006)||x||x||x||x|| || ||x|| || || || || || ||x|
|Koroneos and Kottas|| ||x||LCA for energy consumption in the use phase for a house in Greece (2007)||x||x||x||x|| || || || || ||x|| || || ||x|
|Morel et al.||X|| ||Comparison of energy embodied in local construction materials with imported ones, France (2000)||x|| || || || || || || || || || || || || |
|Nebel et al.||x|| ||LCA for floor covering, Germany (2006)||x||x||x||x||x|| || || || || || || || ||x|
|Nicoletti et al.||x|| ||LCA of flooring materials (ceramic versus marble tiles), Italy (2002)||x||x||x|| ||x||x|| || ||x|| || || || ||x|
|Nyman andSimonson||x|| ||LCA of residential ventilation units over a 50 year life-cycle in Finland (2005)||x||x||x|| ||x|| || || ||x|| || || ||x|| |
|Peuportier|| ||x||Comparison of three types of houses with different specifications in France (2001)||x||x||x||x||x||x||x||x||x||x||x||x||x|| |
|Petersen and Solberg||x|| ||LCA by comparing wood and alternative materials in Norway and Sweden (2005)||x|| ||x||x||x||x|| || || || || || || || |
|Prek||x|| ||LCA of heating and air conditioning systems. Dwelling in Slovenia (2004)||x||x|| || ||x|| || || || || || || || || |
|Saiz et al.||x|| ||LCA for green roofs located in downtown Madrid, Spain (2006)||x||x||x||x||x||x|| ||x|| ||x|| || || ||x|
|Scheuer et al.|| ||x||LCA to a new University building in the USA (2003)||x||x||x|| ||x|| ||x|| || ||x|| || || ||x|
|Seppala et al.||x|| ||LCA for Finnish metal products (2002)||x|| || ||x|| ||x||x||x|| ||x|| || || ||x|
|Thormark|| ||x||LCA of residential houses in Sweden (2001)||x|| || || || || || || || || || || || || |
|Van der Lugt et al.||x|| ||LCA for using bamboo as building material in Western Europe (2006)||x|| || || || || || || || || || || || ||x|
|Wilson and Young||x|| ||Embodied energy payback period of photovoltaic installations in the UK (1995)||x|| || || || || || || || || || || || || |
|Yohanis and Norton|| ||x||LCA of open-plan office building in the UK (1999)||x|| || || || || || || || || || || || || |
Commonly used WPC impact categories.
Commonly used WPC impact categories.
|Impact category||Abbreviation||Scale||LCI data i.e., classification||Characterization factor|
|Global warming||GW||Global||Carbon Dioxide (CO2)||Global warming potential|
|Nitrogen Dioxide (NO2)|
|‘Hydro chlorofluorocarbons’ (HCFCS)|
|Methyl Bromide (CH3Br)|
|Acidification||A||Regional Local||Sulphur Oxides (SOX)||Acidification potential|
|Nitrogen Oxides (NOX)|
|Hydrochloric Acid (HCL)|
|Hydrofluoric Acid (HF)|
|Eutrophication||E||Local||Phosphate (PO4)||Eutrophication potential|
|Nitrogen Oxide (NO)|
|Nitrogen Dioxide (NO2)|
|Nitrates, and Ammonia (NH4)|
|Ozone depletion||OD||Global||Chlorofluorocarbons (CFCS)||Ozone depletion potential|
|Hydro chlorofluorocarbons (HCFCS)|
|Halons, and Methyl Bromide (CH3Br)|