ssnnooiissssiimmee 22OOCC the BaU situation. In this case study, we assumed that the target product and region of concern were consumer cars in urban areas of Vietnam. This is because cars have not become widespread in Vietnam and controlling the production volume of cars could have a big influence on the country’s CO2 emissions. We have proposed a quantification method for narrative scenarios using participatory backcasting. Judging from the results of the case study, the proposed method worked well in obtaining quantitative scenarios 28 4.2 Case Study of Narrative Scenario Quantification The case study results are summarized as follows: Phase 1. Workshop preparation by the scenario designers 1. The scenario designers decided to use a simple simulation model called “product circulation model,” which was developed to evaluate the environmental impact of product lifecycles, considering consumer behaviors (Onozuka et al., 2021). This model was able to estimate environmental impact changes when various measures (e.g., sharing and remanufacturing) were considered. 2. The scenario designers set tentative input values and their rationales for the product circulation model. For example, the penetration rate of car-sharing services was set at 50% assuming that circumstances relating to car-sharing services would be similar to those in Bangkok, Thailand, referring to previous research done by other scholars. Table 3 gives some examples of input values and the rationales for them set by the scenario designers. 3. The scenario designers suggested a few discussion points, which focused mainly how parameter values would change from those in BaU scenarios. For example, they raised a discussion point about how to set the value of the parameter “Users of car-sharing services per shared car” because it was strongly related with the main measure (sharing services) of the narrative scenario. Phase 2. Discussion by the workshop participants Table 3 Examples of parameter values and their rationales established in the quantification workshop. The workshop participants discussed how to modify the input values based mainly on the discussion points proposed by the scenario designers. For example, “Users of car-sharing services per shared car” was modified from 50 to 10 through discussion by participants: “It is assumed in the narrative scenario that people will stop owning cars and use sharing services instead. However, this input parameter value refers to the current situation in a developed country, where people already own cars. Value (2020) Parameter Penetration rate of car sharing services 0% Users of car sharing services per shared car - Annual car mileage 10000 Value (BaU) Tentative value set by scenario designers 0% 50% - 50 10000 10000 S. ONOZUKA et al. After workshopUnit 50% - 10 - km / year 5000 Considering the time a sharing-service user would use the car in a day, 10 would be more appropriate than 50 to make the value more consistent with the storylines.” Two other qualitative statements were also discussed. One was on lifestyle changes due to COVID-19 - “we can assume that the demand for mobility will decrease because remote work is being promoted to address the COVID-19 situation.” This value was halved after considering a mobility report (Apple, 2020). The other was on renewable energy. One participant said “Renewable energy should also be taken into consideration because it has huge potential for reducing CO2 emissions.” In this narrative scenario, we assumed that renewable energy would be used at the Sustainable Development scenario in the World Energy Outlook 2020 (International Energy Agency, 2020). Table 3 presents some of the input parameter values and rationales discussed at the workshop. Phase 3. Review and modification Based on the discussion by the participants, the scenario designers set input parameter values to estimate the CO2 emissions and shared them with the workshop participants. Figure 2 shows the quantification results, which showed that CO2 emissions would be reduced by 60% compared with the BaU scenario in 2050. Note that the workshop participants agreed on all the final quantification results in the second workshop. level of the Rationales The same level as in Thailand. Reference: 45% in Bangkok, Thailand at 2050 (Sekine et al., 2020). The same level as in Japan (assumed by the scenario designers). Reference: Internet questionnaire. Considering is not (comment by participants). Reduced because of lifestyle change caused by COVID-19 (comment from workshop). In 2020, mileage was almost halved in Vietnam.required, 50 time Fig. 2 Quantification result of case study. realistic 5. Discussion
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