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Since launching this project, data collection has been the central issue as the model structure and type of scenarios which can be analysed largely depends on the availability of data. IGES requested each modelers to make a list of required data and IGES distributed it to local collaborators to collect the required data for each sub-sector module. The following list is the summary of data requirements for comparative studies.
Cities can be defined in a number of ways such as central business district (CBD), densely inhabited district (DID), ward area, etc. Although the data for ward area or DID may be more appropriate indicator for socio-economic analysis of the city, due to the data constraints on technical variables, the data used this time refers to the city as defined by administrative boundary. Collecting the above listed data however, has been faced with several difficulties. Those are: (1) Development of comparable dataset for the four cities Each country has different statistical system and different definition even though the same terminology is used, which created the difficulty in interpreting the data. This problem has mostly been solved with the help of local collaborators through consultation at workshops, field survey, as well as e-mail exchange. (2) Effective collaboration in interdisciplinary and international joint research Another difficulty lies in the fact that this project is interdisciplinary in nature. Experts of specific sector are not necessarily familiarized with the data of other sectors even for their own country, about which we were too much optimistic at project formulation stage. Since local collaborators are experts in a specific field and we asked them to collect local data for not only their specialized field, but also the other sectors, data collection cannot be done smoothly. Interpretation of the technical term especially in waste management sector, with foreign language was also difficult. These difficulties, nonetheless, have been gradually cleared through a series of workshops and discussion among collaborators, which contributed to capacity building of the researchers involved. The detailed account of the collected data is given below. Energy Balance Data In order to link macro socio-economic framework of the cities and their energy consumption and GHG emission profile, data on energy balance, especially energy balance table, is essential. Availability of such data differs from city to city, and situation of each city is summarized in the Table 4-1-1.  While energy balance table of Beijing and Shanghai are published, the ones of Seoul and Tokyo are not. In the case of Seoul, energy balance table is obtained with the help of Prof. Jo at Andong National University, Korea. In the case of Tokyo, the data is obtained from internal report of Tokyo Metropolitan Government (TMG). The data for Tokyo however, is not a balance table, but final energy consumption data estimated by using basic unit data of consumption of various fuels by sector. Estimation method is clarified in the report of TMG.. Looking at the data, while data of Tokyo is rich in the type of sectors, Seoul data is most detailed in terms of energy types though sector is aggregated compared to Tokyo. The detail of Chinese data is in between Tokyo and Seoul. In order to enable the comparative study of energy consumption by sector, those energy balance data from each city are modified to the common format as shown below.  Sectoral Data In addition to the basic macro socio-economic data which is relatively easy to collect, sectoral data for transportation, residential & commercial (Res/Com) and municipal solid waste (MSW) management have also collected with continuous effort. Those sectoral data are in most cases, technical and even though the terminology is same among the cities, the estimation method, concept, definition, etc. are different. Necessary modification is made where applicable, and the data which is not available but vital, are estimated using existing data. Collected and estimated data are summarized in the Table 4-1-3. This is the best we could get by now. With more time and resource, more detailed data may be obtained in the future. Emission Factor Having estimated the energy consumption by sector in each city, the next step was to estimate the GHG emission by fuel type by sector. IGES collected the basic emission factor by sector for each city and provided those data to the experts. Experts in transportation, Res/com and MSW management utilized those data and developed their own methodology to calculate the emission from respective sectors. Again, those data are normally not published and collected from reports of commissioned survey by local government of each city. Such survey was targeted to specific issues at each locality and thus the definition, sector classification of the data used to calculate emission factor is not common among each report. Such differences of the data among each city is summarized in the Table 4-1-4.  
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