Title (Use Title style here)

Beyond Just Light Bulbs: The Mitigation of Greenhouse Gas Emissions in the Housing Sector in Mexico CityReyes

Beyond Just Light Bulbs: The Mitigation of Greenhouse Gas Emissions in the Housing Sector in Mexico CityAriadna I. Reyes-Sanchez, University of Texas at Austin, ariadna.reyes@utexas.eduAbstract. Climate change is a serious global challenge that urgently demands comprehensive mitigation policies, including in the housing sector. However, GHG emissions assessment in the housing sector is particularly challenging because urban planning factors such as location of jobs and transit services influence GHG emissions. Therefore, for mitigation strategies in the housing sector to be effective, they must be based on a comprehensive understanding of the complex nature of GHG emissions associated with housing development and use.

In Mexico, the Federal Government has implemented strategies for mitigating GHG emissions through the promotion of energy efficient technologies such as electricity-efficient bulbs. However, these strategies do not address GHG emissions stemming from the rapid growth of housing developments on the urban periphery. Recently, federal government-financed dwelling units have been developed on a massive scale in the urban fringe, without sufficient attention to public transportation and job creation.

In order to assess the impact of location and transportation on GHG emissions in the housing sector in Mexico City, a Life Cycle Assessment (LCA) was conducted to assess GHG emissions related to both construction and use of dwelling units. It was found that the use of gasoline for private transport is the principal contributor to GHG emissions, followed by the use of electricity. These findings suggest that the most effective mitigation strategy in the housing sector may be the promotion of resource-efficient dwelling units in urban locations. This calls into question the federal governments focus on technologies to mitigate GHG emissions instead of encouraging housing policies that support government financing of urban dwelling units.Proceedings of the International Symposium on Sustainable Systems and Technologies (ISSN 2329-9169) is published annually by the Sustainable Conoscente Network. Jun-Ki Choi and Annick Anctil, co-editors 2015. ISSSTNetwork@gmail.com.Copyright 2015 by Reyes Licensed under CC-BY 3.0.

Cite as:Beyond Just Light Bulbs: The Mitigation of Greenhouse Gas Emissions in the Housing Sector in Mexico CityProc. ISSST, Reyes. Doi information v3 (2015)

Introduction. Climate change is a serious global challenge that urgently demands comprehensive mitigation policies to address the contribution of the housing sector to climate change (Fuller & Crawford, 2011a; Stephan, Crawford, & de Myttenaere, 2012). Nevertheless, greenhouse gas (GHG) emissions assessment in the housing sector is particularly challenging because in addition to construction and daily use of housing units, urban planning factors such as density, location of jobs, and transit services also influence their occupants energy use and GHG emissions (Breheny, 1997; Ewing & Rong, 2008; Fuller & Crawford, 2011b; Guerra, 2014; Lee & Lee, 2014; Norman, Maclean, Asce, & Kennedy, 2006). Therefore, for mitigation strategies in the housing sector to be effective, they must be based on a comprehensive understanding of the complex nature and extent of GHG emissions associated with housing development and use (Ramesh, Prakash, & Shukla, 2010; Stephan et al., 2012).

Mexico City is one of the largest cities in the world, with a relatively higher level of economic development than other developing-world cities. Therefore, Mexico City could enable a better understanding of appropriate climate change policies in the housing sector that could serve as reference to other developing-world cities as their economies grow (Guerra, 2014) . As a matter fact, Mexico has been recognized as one of the international leaders in developing GHG emissions mitigation policies (Lankao, 2007; The World Bank, 2013). The Mexican federal government has implemented housing-related strategies for mitigating GHG emissions by promoting, subsidizing, and financing the purchase of energy efficient technologies such as electricity-saving bulbs and solar water heaters (SEMARNAT, 2012). However, these mitigation strategies do not address GHG emissions stemming from the rapid growth of housing developments on the urban periphery. In the last two decades, federal government-financed dwelling units have been developed on a massive scale in the urban fringe of Mexico City, unaccompanied by public transportation services or nearby jobs (Pradilla Cobos, 2005; UN, 2011). This has led to increasing automobile use and an attendant increase in GHG emissions, as residents in these distant housing developments are required to commute to central locations that offer services and employment opportunities.

In order to assess the impact of location and transportation on GHG emissions in the housing sector in Mexico City, a pioneering Life Cycle Assessment (LCA) was conducted to compare energy use related to both construction and use of dwelling units. The LCA reveals that the use of gasoline for private transport is the principal contributor to GHG emissions generated by housing, followed by the use of electricity and gas, respectively. These results call into question the Mexican federal governments focus on energy efficient technologies to mitigate GHG emissions instead of promoting housing policies that support government financing of dwelling units in the central city. The problem is not the promotion of energy-efficient technologies so much as making them the federal governments sole climate policy focus. The failure was relying on energy-efficient technologies to mitigate GHG emissions in housing developments placed on the urban periphery while effectively ignoring the resulting increases in car usage and accompanying GHG emissions.

One possible avenue for GHG emissions mitigation in the housing sector that integrates planning tools and technological innovations is implementing energy-efficient technologies in housing developments placed in central locations. Beyond the case of Mexico City, this investigation suggests that LCA represents a powerful methodological approach to develop comprehensive GHG emission baselines for the housing sector, which in turn can serve to encourage effective urban planning policies for mitigating GHG emissions in the housing sector. Climate Change Policymaking in the Housing SectorIn cities, more than three quarters of the worlds energy is consumed as a result of the use of housing units and commercial buildings, due to transportation and purchasing activities developed by large populations, according to Hoornweg et al (Hoornweg, Sugar, & Trejos Gomez, 2011; Prez-Lombard, Ortiz, & Pout, 2008). In households, residents use nearly 40% of the worlds energy but also influence energy use in the transport sector (Prez-Lombard et al., 2008). Hence, a holistic assessment of the contribution of the housing sector in developed and developing-world cities is necessary to more effectively mitigate global GHG emissions. However, the vast majority of GHG assessments in the housing sector have been carried out in developed-world cities (Guerra, 2014; Prez-Lombard et al., 2008; Ramesh et al., 2010). Thus, there is a poor understanding of the contribution to GHG emissions in developing-world cities, which are projected to embrace most global population growth in the following decades to come (Guerra, 2014; Stephan et al., 2012). By examining Mexico City, this investigation could enable a better understanding of appropriate climate change policies in the housing sector in developing world-cities. Greenhouse gas (GHG) emissions assessment in the housing sector is particularly challenging because in addition to construction and daily use, urban planning factors such as density and location of jobs influence energy use and GHG emissions (Norman et al., 2006). According to Hoornweg, denser cities have lower per capita energy consumption. Moreover, within urban territories, per capita energy use is lower in denser areas (Hoornweg et al., 2011). For example, Norman argues that low-density suburban development in Toronto is more energy and GHG emissions intensive by a factor of 2.02.5 than high-density urban core development (Fuller & Crawford, 2011b; Lee & Lee, 2014; Stephan et al., 2012). By comprehensively assessing energy use dwelling units in Belgium, Stephan et al. found that transportation energy accounts for 34-51% of the total life cycle energy consumption, followed by household operating energy of appliances, space heating and embodied energy, which account for 24%, 23% and 20%, respectively (Stephan et al., 2012). Therefore, it can be inferred from previous GHG assessments in the housing sector that urban density, which is largely influenced by the spatial location of housing developments, drives the extent to which residents use energy to commute from residential locations to job-rich areas (Fuller & Crawford, 2011b; Lee & Lee, 2014; Stephan et al., 2012).

Despite the fact that urban density significantly influences energy use, the vast majority of GHG emissions assessments in the housing sector completely disregard it (Ramesh et al., 2010). As a matter of fact, most GHG assessments in the housing sector examine dwelling embodied energy stage or household energy use stage, but neglect residents transportation-related energy consumption. Embodied energy in dwellings includes the manufacture of building materials, transportation of building materials to the construction site, and construction processes. Household energy use includes cooling and heating of interior dwelling spaces, and the operation of domestic water heating and appliances. Residents transport includes automotive transportation activities, such as cars and buses (Stephan et al., 2012). To illustrate the common exclusion of transportation costs from GHG assessments, Mexicos National Inventory of GHG attributed a 7% share of nationwide GHG emissions to the housing sector in 2010 (SEMARNAT, 2012). However, this GHG emissions assessment in the housing sector in Mexico included only electric and gas usage in the post-occupancy stage, but neglected dwelling embodied energy and energy use of residents transportation. Stephan et al. argue that a more holistic approach to assess energy use of dwellings is indispensable to more effectively mitigate GHG emissions in the housing sector. Stephan et al. propose widening the current typical scope of analysis, currently restricted to household energy use, to also account for dwelling embodied energy, but more importantly to account for residents transportation energy (Stephan et al., 2012).

Figure 1 A comprehensive approach to assess energy use and associated GHG emissions in housing unitsAdapted by (Stephan, Crawford, & de Myttenaere, 2011).

The Mexican federal government developed the National Strategy for Climate that delineated general guidelines to mitigate GHG emissions in various economy sectors, including the housing sector. The Special Program for Climate Change sought, as fulfillment of its GHG mitigation goal in the housing sector, to reduce GHG emissions by promoting energy-efficient technologies financed by green mortgages in 800,000 newly constructed housing units (SEMARNAT, 2012). The Institute of the National Fund for Workers Housing (INFONAVIT, in Spanish), on behalf of the federal Mexican government, has implemented the Green Mortgage Program since 2008 in order to encourage energy efficiency in the housing sector. The Green Mortgage Program addresses energy efficiency of new housing developments by promoting and financing energy-efficient technologies dealing with three resources: natural gas, electricity, and water. Reducing their consumption allows savings on energy usage, utility expenses, and attendant GHG emissions (Corona Suarez & May-Yam, 2013). According to Borras, the Mexican federal government fulfilled its proposed GHG mitigation goal since more than one million green mortgages were implemented in new housing units between 2007 and 2012 (Borras, 2012).

In order to address the housing demand of low and middle-income formal workers, the federal government has implemented ambitious national programs for housing. To illustrate this, in the previous presidential term almost six million families received government credits to buy newly constructed dwelling units situated on the urban periphery between 2006 and 2012 (Bredenoord, Lindert, & Smets, 2014; UN, 2011). Major housing developers acquired huge amounts of inexpensive rural land and developed housing developments on a massive scale in the last two decades (Bredenoord et al., 2014). As a matter fact, housing policies were the vehicles to promote peripheral housing developments that lack any sort of transit service, infrastructure, employment and educational opportunities. Ironically, these peripheral housing developments were the sites selected to implement INFONAVITs green mortgages. The failure was not to promote energy efficient-technologies on massive scale in the housing sector, the failure was to assume that these technologies are themselves sufficient to mitigate GHG emissions and to disregard urban planning factors that account for the lions share of energy use.

The remarkable misalignment between housing and climate change policies has exacerbated GHG emissions associated with increasing automotive transportation in the urban periphery of Mexico City. Life-cycle assessment (LCA) provides a thorough approach to assess the complex nature and extent of energy use associated with dwelling embodied energy, household energy use and residents transport energy. A holistic GHG emissions baseline in the housing sector is essential to understand the nature and extent of effective mitigation (Stephan et al., 2012). Moreover, a comprehensive GHG emissions baseline could serve to assess mitigation outcomes over time.A Life Cycle Assessment in Peripheral Housing Units in Mexico City.Despite the fact that aggregate population growth rates in the Metropolitan Area of Mexico City decreased in recent years, population in suburban areas have grown at an annualized rate of more than 10 percent from 1990 to 2010 (Guerra, 2014). Despite rapid suburbanization of the Metropolitan Area of Mexico City, jobs remained fairly centralized within the limits of Mexico City (Guerra, 2014). This has led to increasing automobile use and an associated increase in GHG emissions, as residents in suburban housing developments commute to a select few districts in Mexico City that concentrate employment, educational institutions, and services. In order to assess the impact of location and transportation on GHG emissions in the housing sector in Mexico City, a Life Cycle Assessment (LCA) was conducted to compare the contribution to GHG emissions of pre-use and use phases. The pre-use phase or dwelling embodied stage aggregates the use of energy, resources, and materials that result from the manufacture of building materials, materials transportation to the construction site, and housing units construction. The use phase aggregates not only the use of energy, resources, and materials that result from the stage of households use of the housing unit itself but also, crucially, the stage of residents transportation over a fifty-year service life period.

This LCA examines the contribution to GHG emissions of the typical government-financed housing unit located in the urban periphery of Mexico City between 2000 and 2012. The characterization of the typical housing unit included three key methods: a review of literature; four workshops with Mexican housing developers carried out between June and August 2011; and 17 separate field visits in peripheral housing developments in Mexico City conducted between July 2011 and December 2011. It was found that government-financed housing units share various patterns in their mode of construction and in their urban fringe location. Although these dwelling units are relatively small in their interior living area (from 30 to 60 square meter), they are often equipped with a yard and a parking space (CONAVI, 2010). However, this small housing unit is expected to grow over time as a result of a gradual self-help construction process carried out by residents in order to address their housing requirements over time. Some of the patterns of self-help observed in these housing developments include enlargement of a house by adding residential extensions (either upward or toward the rear of the lot), subdividing existing space to provide separate living spaces to some members of the family, as well as paving front setbacks in order to provide automobile parking (Eibenschutz Hartman & Benlliure B., 2009).

Housing developments usually have only one entry point, to which access is typically restricted by a gate. In addition, housing developments are zoned as single residential land use areas, which means that commercial land uses are officially prohibited from being added over time. The exclusively residential land use in peripheral housing developments has two main consequences. First, the lack of non-residential uses means that residents are required to travel a considerable distance to meet basic needs such as buying food and other basic products, to access to any sort of public service, activity or amenity. However, the lack of commercial uses in these housing developments induce conversions of residential spaces into informal businesses that sell basic products and services, such as groceries and clothes. In addition, streets are appropriated by informal markets known as tianguis, a sort of temporary farmers market (Eibenschutz Hartman & Benlliure B., 2009).

Considering the peripheral location and the lack of transit services in the urban fringe, it can be argued that this suburban housing model is directly inducing the intensive use of motorized means of transportation, particularly private passenger cars. The lack of efficient means of transportation in these housing developments triggers informal means of transportation, such as illegal bus fleets that tend to use second-hand vans and low-capacity buses (Eibenschutz Hartman & Benlliure B., 2009). These allow residents to move within the urban periphery and beyond. Second, the horizontal construction pattern (ground floor-oriented houses) in the urban fringe is inefficient in terms of land use, because it does not make efficient use of available urban land in central locations. In addition, these suburban housing developments do not offer green spaces such as parks or playgrounds. Instead, a relatively large proportion of land is devoted to roads and parking lots that encourage the use of private cars.

This paper presents the Life Cycle Inventory of the typical housing unit located in the urban fringe of the Metropolitan Area of Mexico City, promoted by the Mexican federal government between 2000 and 2012. A typical housing unit was characterized by examining 17 housing developments in the urban fringe of Mexico City. These housing developments lie within Mexico Citys border municipalities of the State of Mexico: two are in Chalco, four in Ecatepec, three in Ixtapaluca, five in Tecamac, one in Tlalnepantla, and two in Tultepec. Table 1 presents their main urban and architectural characteristics. First, their urban fringe location means they arose from the conversion of rural to urban land. Second, the average distance to the closest subway station is 26 km, which helps explain why buses and private cars are the main modes of transportation, and why these housing developments are spatially disconnected from transit services. Third, average living area accounts for 40 m2; however, the total area of the land parcel accounts for 160 m2, which includes the front setback, sidewalk, and an on-street parking space. The Floor Area Ratio (FAR) of this typical housing is only 0.25, suggesting an inefficient use of urban land and available infrastructure. However, it is worth mentioning that floor area is expected to increase as self-help construction activities emerge and living area is increased by residents over time. Fourth, it was observed that 80% of housing developments do not have sewage treatment plants on site, and thus waste water is sent to the municipal sewage treatment plants. However, in the State of Mexico only 28% of wastewater runoff was treated in 2011, suggesting an explanation for the observable water pollution of the rivers near these peripheral housing developments (Ducci, Plascencia, & De la Pea, 2013).Table 1 Urban and architectural characteristicsComponentFinding

Previous land useRural in transition to suburban

Distance to the closest subway station26.6 km

Accessibility to transportCar and bus

Average daily commute140 minutes

Land useResidential

Area of dwelling unit40m2

Area of land parcel160 m2

Floor area ratio0.25

The LCA was carried out for of the pre-use phase that includes building materials manufacture, materials transportation, and construction, as well as the use phase that includes household use and residents transportation. A fifty-year service life was considered. This period is based on the most common approaches in LCA in buildings (Ramesh et al., 2010; Stephan et al., 2012), which enables comparison with previous LCAs. The housing unit (subject of the LCA) was considered to include the following systems: a) the dwelling as residential structure, b) the adjoining public realm, including the components of the street such as sidewalks and pipelines, c) infrastructural elements, including sewage treatment plants, and d) the households resource consumption, including electricity, natural gas, water, gasoline, and diesel. The environmental impacts of the elements related to the housing units life cycle were estimated for the functional unit: one square meter of habitable housing over a 50-year lifespan.

Figure 2 Housing Units Systems: dwelling unit, urban section, infrastructure systems, and household useThe open LCA 1.2.6 program was used to process the inventories of LCA. The environmental impact assessment method developed by the Center of Environmental Science of Leiden University (CML 2001) was selected to estimate global warming impacts as a function of estimated GHG emissions. The CML 2001 was regularly used in previous LCA assessments in the housing sector. This study included environmental impacts found in previous LCA studies of products elaborated and used in Mexico. For example, it included environmental impacts found in an LCA of the manufacture of asphalt in the Metropolitan Area of Mexico. However, the main LCA reference database was the US-based National Renewable Energy Laboratory (NREL).

Two workshops with major Mexican developers were conducted in July 2011, in order to characterize urban and architectural patterns of the typical housing unit promoted by INFONAVIT, on behalf of the federal government, between 2000 and 2012. This architectural and urban characterization served to estimate flows of energy, building materials, and water for constructing the housing unit and its systems. Housing developers provided plans and databases that itemized earth-moving machinery to subdivide land and to build structures foundations; the consumption of building materials, water, and energy to construct housing units subsystems; and the generation of construction waste. Flows of energy, water, and resources consumed during the household operating phase were determined from the results of a survey with 1,414 responses from households. The survey was conducted on 17 housing developments that collectively contain nearly 110,000 households. The sample is large enough to ensure a 99% level of confidence with a standard error of 3%. The mode of the survey was done by knocking on doors and asking residents a questionnaire in person. From field visits reports, it was estimated that nearly 50% of total dwelling units in these housing developments seemed to be vacant as housing units conditions were dilapidated. Therefore, surveys were randomly conducted in dwelling units that were occupied by their residents. The total response rate was 70%.

The LCA inventory integrates flows of energy, resources, and materials required for the stages of pre-use, household use, and residents transport. Figure 3 shows the LCA scope accompanied by inputs and outputs associated with processes examined in this analysis. First, the manufacture of building components requires raw materials, energy, and water, which result in waste and GHG emissions. Second, transporting the components to the construction side requires the use of diesel, resulting in further GHG emissions. Third, the construction stage requires energy, water, and building materials, but generates GHG emissions and construction waste. Last, household use of the dwelling unit post-occupancy demands diesel, electricity, gas, gasoline, and water; these result in further GHG emissions and waste. It is worth mentioning that a REF _Ref418494534 \h \* MERGEFORMAT sensitivity analysis was carried out to ensure the validity of LCA assumptions, and thus empirical data from surveys was compared with peer-reviewed articles and statistics developed by federal and local institutions.

Figure 3 Housing Units Life Cycle Assessment ScopeIn order to estimate electricity flows, residents were asked how much they pay for their electricity bill and the frequency of this payment. After that, applicable electricity rates, measured in Mexican Pesos/kWh, were used to estimate flows of electricity (measured in units of kWh). It was estimated that the median value of annual electricity use accounts for 1,300 kWh, which was divided by dwelling construction area and then multiplied by 50 years of service life. Thus, electricity flows account for 1,625 kWh per square meter of habitable housing in a 50-year lifespan. In order to estimate flows of gas, residents were asked the type of gas they use (natural or Liquid Propane gas), how much they pay for their gas bill, and the frequency of this payment. Water flows in the household operating stage were estimated by asking the number of people living in the household; the type of water technologies used, such as high-flow or low-flow toilet; and daily patters of water use, such as the number of baths residents take per day. After that, the Water Use Calculator provided by INFONAVIT was used to estimate daily water use.

In order to estimate flows of gasoline and diesel, an origin-destiny survey was carried out. It included questions regarding the type and the number of means of transportation used to commute to job locations. These means of transportation include: walking, biking, bus, Bus Rapid Transit (BRT), subway, and private cars. Moreover, questions on the time spent in every means of transportation were included. After that, typical rates of gasoline and diesel usage per unit time were used to estimate flows of gasoline and diesel, in units of volume (NREL, 2012). Those rates were 2.25 liters of gasoline per hourly use of private car and 0.36 liters of diesel per hourly use of buses. Therefore, typical annual gasoline and diesel use accounts for 1,125 and 203 liters, respectively. In order to estimate flows of gasoline and diesel per square meter of habitable household in a fifty-year lifespan, gasoline and diesel consumption were divided by dwelling constructed area and then multiplied by household lifespan.Table 2 LCA inventory: materials, resources, and energy flows per square meter of habitable household in a fifty-year lifespanInputStageLCA PhaseSuburban household

ConcreteDwelling embodiedPre-use980 kg

SteelDwelling embodiedPre-use18 kg

AsphaltDwelling embodiedPre-use6 kg

PVCDwelling embodiedPre-use5kg

WaterDwelling embodiedPre-use79 liters

WaterHousehold operatingUse413 m3

GasHousehold operatingUse430 liters

ElectricityHousehold operatingUse1625 kWh

GasolineResidents Transport Use962 liters

DieselResidents Transport Use173 liters

The origin-destiny survey helped identify four patterns of residents transportation activities to commute to job locations. First, residents tend to use at least two means of transportation to commute to job locations. Residents spend an average of 140 minutes for daily commuting round trip. Second, buses seem to be the main transportation mode, in terms of time, since 53% of total commuting trips are done by bus. Therefore, residents use buses for 1.27 hours per day. However, most residents walk for several minutes before taking a bus. It was found that residents in peripheral housing developments are unable to access any high-capacity transit service, such as BRTs and subway. Third, residents use informal means of transportation to commute, such as second-hand vans and low-capacity buses. Fourth, 47% of total commuting trips are done using cars. This finding suggest that households living on the periphery remain less likely to drive. However, residents use private cars for, on average, 1.09 hours per day. Peripheral housing developments are explicitly designed to encourage car ownership, since they provide room for parking in the front setback and because they have only one entry point. In order to reach some places, residents have to walk much further than the length of the most direct route that would exist if there were an interconnected street network.

Results.LCA revealed that the total contribution of the housing unit to GHG emissions accounts for 3,750 kg CO2 equivalent per square meter of habitable household in a 50-year lifespan. It was found that 92% of total GHG emissions occurs during the use phase that aggregates household use and residents transport. Dwelling embodied energy, contributes 8% household-operating stage 42%, and residents transport 50% of total GHG emissions. See Figure 4.

Figure 4 Housing Unit's Contribution to GHG emissionsThe LCA revealed that the use of gasoline and diesel that result from residents transport is the principal contributor to GHG emissions with 50%, followed by the use of electricity with 22% and gas with 20%. Conclusion.LCA exposed that residents transportation is the main contributor to GHG emissions in suburban housing developments promoted by the Mexican federal government between 2000 and 2012. LCA findings elucidated the remarkable disconnection between housing policies, which largely promoted new housing developments in the urban fringe and climate change policies in the housing sector, which have a disproportionate focus on promoting energy-efficient technologies in peripheral housing developments. It is apparent that these GHG emissions mitigation policies in the housing sector effectively disregarded urban density, which is by far the leading factor determining the extent to which residents use energy to commute to their jobs (Fuller & Crawford, 2011b; Lee & Lee, 2014; Stephan et al., 2012).

One possible avenue for GHG emissions mitigation in the housing sector that comprehensively integrates housing policies and technological innovations is affordable housing densification in central areas. Despite assumptions that Mexico City is already densely developed, scholars argue that numerous vacant lots and underutilized buildings in central locations offer opportunities for urban densification (Sullivan & Ward, 2012; UN, 2011). While federal housing policies continue to facilitate government-financed housing developments on the urban periphery, privately financed high-rise residential building development is increasingly occurring in central locations (Eibenschutz Hartman & Benlliure B., 2009). Unfortunately, while such redevelopment of central locations may contribute significantly to GHG mitigation, these high-rise developments are priced out of reach for low-income people. Since wealthier people have smaller households but utilize more space, the result of this gentrification process may be a decline in the number of lower-income residents in some areas of the central city.

In addition, rehab housing strategies with energy-efficient technologies in central locations may be another effective GHG emission mitigation strategy in the housing sector. First, consolidated informal settlements placed in central locations that offer a large housing stock with high levels of urban density could serve to implement rehab strategies with energy efficient technologies. Energy-efficient technologies, such as solar water heaters and solar panels, could significantly reduce energy use and attendant GHG emissions without inducing car usage (Ward, Jimnez Huerta, & Virgilio, 2014). Second, existing housing developments promoted by the federal government placed in central locations in Mexico City similarly offer exceptional opportunities for rehab with energy-efficient technologies to more effectively mitigate GHG emission in the housing sector in Mexico City.

Beyond the case of Mexico City, this investigation suggests that LCA represents a powerful methodological approach to develop comprehensive GHG emission baselines for the housing sector, which in turn can serve to encourage effective housing policies for mitigating GHG emissions in the housing sector. A comprehensive GHG emissions baseline in the housing sector is essential to design, evaluate and verify GHG mitigation strategies in the housing sector over time. Mexico City could enable a better understanding of appropriate climate change policymaking in the housing sector that could serve as reference to other developing-world cities that aim at reaching Mexico Citys levels of urban and economic development.

Acknowledgements. The research and text have benefited greatly from Ricardo Ochoa, Bjorn Sletto, Jake Wegmann, and Barbara Brown. I would also like to thank Centro Mario Molina for financial support and assistance. References

Borras, V. (2012). Ms de 1 milln de hipotecas verdes otorgadas y 3.8 millones de familias beneficiadas | El Economista. El Economista. Retrieved from http://eleconomista.com.mx/columnas/columna-especial-valores/2012/11/01/mas-1-millon-hipotecas-verdes-otorgadas-38-millones-famBreheny, M. (1997). Urban compaction: feasible and acceptable? Cities, 14(4), 209217. http://doi.org/10.1016/S0264-2751(97)00005-X

CONAVI. (2010). Cdigo de Edificacin de Vivienda. Retrieved April 27, 2014, from http://www.cmic.org/comisiones/sectoriales/vivienda/biblioteca/archivos/CEV PDF.pdf

Corona Suarez, G. A., & May-Yam, K. E. (2013). Sustainable Practices in Mexican Housing Projects to Reduce Emissions Effecting Climate Change. Retrieved from http://papers.ssrn.com/abstract=2346575

Ducci, J., Plascencia, V. Z., & De la Pea, M. E. (2013). Tratamiento de aguas residuales en Mxico. Banco Internado de Desarrollo. Retrieved from idbdocs.iadb.org/wsdocs/getdocument.aspx?docnum=37783778?

Eibenschutz Hartman, R., & Benlliure B., P. (2009). Mercado formal e informal de suelo.

Ewing, R., & Rong, F. (2008). The impact of urban form on U.S. residential energy use. Housing Policy Debate, 19(1), 130. http://doi.org/10.1080/10511482.2008.9521624

Fuller, R. J., & Crawford, R. H. (2011a). Impact of past and future residential housing development patterns on energy demand and related emissions. Journal of Housing and the Built Environment, 26, 165183. http://doi.org/10.1007/s10901-011-9212-2

Fuller, R. J., & Crawford, R. H. (2011b). Impact of past and future residential housing development patterns on energy demand and related emissions. Journal of Housing and the Built Environment, 26(2), 165183. http://doi.org/10.1007/s10901-011-9212-2

Guerra, E. (2014). The Built Environment and Car Use in Mexico City: Is the Relationship Changing over Time? Journal of Planning Education and Research, 34(4), 394408. http://doi.org/10.1177/0739456X14545170

Hoornweg, D., Sugar, L., & Trejos Gomez, C. L. (2011). Cities and greenhouse gas emissions: moving forward. Environment and Urbanization, 23(1), 207227. http://doi.org/10.1177/0956247810392270

Lankao, P. R. (2007). How do Local Governments in Mexico City Manage Global Warming? Local Environment, 12(5), 519535. Retrieved from http://ezproxy.lib.utexas.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=a9h&AN=27777179&site=ehost-live

Lee, S., & Lee, B. (2014). The influence of urban form on GHG emissions in the U.S. household sector. Energy Policy, 68(0), 534549. http://doi.org/10.1016/j.enpol.2014.01.024

Norman, J., Maclean, H. L., Asce, M., & Kennedy, C. A. (2006). Comparing High and Low Residential Density: Life-Cycle Analysis of Energy Use and Greenhouse Gas Emissions, (March), 1021.

NREL. (2012). U.S. Life Cycle Inventory Database. Retrieved from https://www.lcacommons.gov/nrel/search

Prez-Lombard, L., Ortiz, J., & Pout, C. (2008). A review on buildings energy consumption information. Energy and Buildings, 40(3), 394398. http://doi.org/10.1016/j.enbuild.2007.03.007

Pradilla Cobos, E. (2005). Zona metropolitana del Valle de Mxico: megaciudad sin proyecto. Ciudades: Revista del Instituto Universitario de Urbanstica de la Universidad de Valladolid. Servicio de Publicaciones. Retrieved from http://dialnet.unirioja.es/servlet/articulo?codigo=2230701&info=resumen&idioma=ENG

Ramesh, T., Prakash, R., & Shukla, K. K. (2010). Life cycle energy analysis of buildings: An overview. Energy and Buildings, 42(10), 15921600. http://doi.org/10.1016/j.enbuild.2010.05.007

SEMARNAT. (2012). Quinta Comunicacin Nacional ante la Convencin Marco de las Naciones Unidas sobre el Cambio Climtico. Retrieved from http://unfccc.int/resource/docs/natc/mexnc5s.pdf

Stephan, A., Crawford, R. H., & de Myttenaere, K. (2011). Towards a more holistic approach to reducing the energy demand of dwellings. Procedia Engineering, 21, 10331041. http://doi.org/10.1016/j.proeng.2011.11.2109

Stephan, A., Crawford, R. H., & de Myttenaere, K. (2012). Towards a comprehensive life cycle energy analysis framework for residential buildings. Energy and Buildings, 55, 592600. http://doi.org/10.1016/j.enbuild.2012.09.008

Sullivan, E., & Ward, P. M. (2012). Sustainable housing applications and policies for low-income self-build and housing rehab. HABITAT INTERNATIONAL, 36(2), 312323. http://doi.org/10.1016/j.habitatint.2011.10.009

The World Bank. (2013). Mexico Seeks to Adapt to Climate Change and Mitigate its Effects. Retrieved May 6, 2015, from http://www.worldbank.org/en/results/2013/04/17/mexico-seeks-to-adapt-to-climate-change-and-mitigate-its-effects

UN. (2011). Estado de las Ciudades de Mxico 2011. Mxico, D.F.

Ward, P. M., Jimnez Huerta, E. R., & Virgilio, M. M. Di. (2014). Intensive Case Study Methodology for the Analysis of Self-Help Housing Consolidation, Household Organization and Family Mobility. Current Urban Studies, 02(02), 88104. http://doi.org/10.4236/cus.2014.220100

Ward, Peter; Jimnez, Edith; Di Virgilio, Mercedes. Housing Policy in Latin American Cities: A New Generation of Strategies and Approaches for 2016 UN-Habitat III | Lyndon B. Johnson School of Public Affairs. New York: Routledge, 2015. http://www.utexas.edu/lbj/publications/6199.

The Floor Area Ratio (FAR) quantifies the extent to which housing units take advantage of their available infrastructure; it is calculated by dividing the living area by total area of parcel.

Researchers who are interested in the results of this analysis can directly contact the author

The manufacture of concrete is the main contributor to GHG emissions of dwelling embodied energy, and it contributes to 7% of total GHG emissions.