6 Heat Vulnerability Index Development and Application in Medan City, Indonesia
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6.10 Electricity and Gas Emission
Electricity and gas consumptions in 2015 were collected from statistical agency of
Medan City (https://medankota.bps.go.id). In this paper, electricity and gas consumptions were assumed as having the same rate of emission, hence its consumption was
converted to emission using method applied by the Japanese Environmental Agency
(https://www.env.go.jp/air/report/h16-05). The conversion factors are presented in
Appendix 1 and 2. 2.3.4 Gas Emission from land transportation oil consumption.
Due to lack of data of vehicles number per sub-district, the data on gas emission were derived for each sub-district by using congestion hotspot number and
total number of vehicle in the city (Medan Transportation Bureau 2016). Annual
oil consumption and subsequently its emission were estimated by the assumption of 10,000 km/year travel distance per each vehicle. Furthermore, we assumed
consumptions were same as emission.
6.11 Sensitivity to Heat
Sensitivity to heat was conducted based on number of demographic and socioeconomic variables. There were multiple factors considered as increasing risk of
health, namely population density related to tendency of increased population density
in the central city districts with higher heat exposing (Coutts et al. 2007), age related
to higher mortality among elderly people and children (Reid et al. 2009; Coutts
et al. 2007; Wolf and McGregor 2013), income level as poverty frequently increase
heat exposure in various aspects of life (Kim et al. 2011). This includes those with
pre-existing illness or impaired physical or mental health (Kaiser et al. 2001; Reid
et al. 2009). In the study area, the lower income people are often living in houses
with aluminum roof and without cooling system, and their work is located outdoors
(i.e., peddler, construction worker, public transportation driver). Residents of lower
income with respiratory, cardiovascular or nervous system problem are at increased
risk of mortality as they are unable to take care for themselves or they have limited
mobility (Tomlinson et al. 2011a, b; Wolf and McGregor 2013). In this study, the
number of patients with hypertension and respiratory patients were included into
analysis as one of the illness triggering the heart attack (Pan et al. 1995) but also due
to the data availability.
6.12 Heat Vulnerability Index
The Heat Vulnerability Index was created based on 13 indicators as shown in Table
6.1.
95
6.10 Electricity and Gas Emission
Electricity and gas consumptions in 2015 were collected from statistical agency of
Medan City (https://medankota.bps.go.id). In this paper, electricity and gas consumptions were assumed as having the same rate of emission, hence its consumption was
converted to emission using method applied by the Japanese Environmental Agency
(https://www.env.go.jp/air/report/h16-05). The conversion factors are presented in
Appendix 1 and 2. 2.3.4 Gas Emission from land transportation oil consumption.
Due to lack of data of vehicles number per sub-district, the data on gas emission were derived for each sub-district by using congestion hotspot number and
total number of vehicle in the city (Medan Transportation Bureau 2016). Annual
oil consumption and subsequently its emission were estimated by the assumption of 10,000 km/year travel distance per each vehicle. Furthermore, we assumed
consumptions were same as emission.
6.11 Sensitivity to Heat
Sensitivity to heat was conducted based on number of demographic and socioeconomic variables. There were multiple factors considered as increasing risk of
health, namely population density related to tendency of increased population density
in the central city districts with higher heat exposing (Coutts et al. 2007), age related
to higher mortality among elderly people and children (Reid et al. 2009; Coutts
et al. 2007; Wolf and McGregor 2013), income level as poverty frequently increase
heat exposure in various aspects of life (Kim et al. 2011). This includes those with
pre-existing illness or impaired physical or mental health (Kaiser et al. 2001; Reid
et al. 2009). In the study area, the lower income people are often living in houses
with aluminum roof and without cooling system, and their work is located outdoors
(i.e., peddler, construction worker, public transportation driver). Residents of lower
income with respiratory, cardiovascular or nervous system problem are at increased
risk of mortality as they are unable to take care for themselves or they have limited
mobility (Tomlinson et al. 2011a, b; Wolf and McGregor 2013). In this study, the
number of patients with hypertension and respiratory patients were included into
analysis as one of the illness triggering the heart attack (Pan et al. 1995) but also due
to the data availability.
6.12 Heat Vulnerability Index
The Heat Vulnerability Index was created based on 13 indicators as shown in Table
6.1.