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CHAPTER 03. Methodology
The calculation of the EF of the two wilayas Algiers and Tipaza was built on data collected
locally by the management entities of the various activities considered, namely fishing, food
(crops and livestock), forestry, water, urbanization, and waste management. The component
model combines urban metabolism analysis of the two wilayas UMA, with life cycle
assessment LCA. This study also considered software application outputs, such as ArcGIS
mapping for the aim of producing complementary data necessary for the calculation of the
EF, in particular the energy and the land use statistics.
The scale of the study is based on the activity the wilayas under consideration residents.
Therefore, the amount of data to be collected is larger and more detailed, considering all the
components of an activity, compared to the original model, which focuses on final
consumption by sector. Consequently, the first step in calculating the EF is the selection and
the collection of data (inputs). This data includes first, the amount of material produced or
consumed in each activity sector, second the energy use comprising both embodied (gray)
energy (raw material extraction, manufacturing) or operational (maintenance and
conditioning). And finally, the extent of land occupied by each activity (infrastructure).
The energy consumed for each activity is converted into the quantity of resulting emissions
by using the LCA of the products manufactured or transported, of the fuels, of the energy
consumed by households through the GEMIS (Global Emission Model for Integrated Systems)
software.
3.1. Data collection
Information was gathered for each type of activity through discussions and working sessions
with the organizations responsible for creating and disseminating this information using
documentation defending the necessity for access to the information. The following table
(table 5) lists for each activity the information required, the entity solicited for the acquisition
of information, the structure, and the data quality (availability).
CHAPTER 03. Methodology
The calculation of the EF of the two wilayas Algiers and Tipaza was built on data collected
locally by the management entities of the various activities considered, namely fishing, food
(crops and livestock), forestry, water, urbanization, and waste management. The component
model combines urban metabolism analysis of the two wilayas UMA, with life cycle
assessment LCA. This study also considered software application outputs, such as ArcGIS
mapping for the aim of producing complementary data necessary for the calculation of the
EF, in particular the energy and the land use statistics.
The scale of the study is based on the activity the wilayas under consideration residents.
Therefore, the amount of data to be collected is larger and more detailed, considering all the
components of an activity, compared to the original model, which focuses on final
consumption by sector. Consequently, the first step in calculating the EF is the selection and
the collection of data (inputs). This data includes first, the amount of material produced or
consumed in each activity sector, second the energy use comprising both embodied (gray)
energy (raw material extraction, manufacturing) or operational (maintenance and
conditioning). And finally, the extent of land occupied by each activity (infrastructure).
The energy consumed for each activity is converted into the quantity of resulting emissions
by using the LCA of the products manufactured or transported, of the fuels, of the energy
consumed by households through the GEMIS (Global Emission Model for Integrated Systems)
software.
3.1. Data collection
Information was gathered for each type of activity through discussions and working sessions
with the organizations responsible for creating and disseminating this information using
documentation defending the necessity for access to the information. The following table
(table 5) lists for each activity the information required, the entity solicited for the acquisition
of information, the structure, and the data quality (availability).