It is now widely observed that lifestyle pattern of the metropolitan cities of developing countries are changing rapidly. With changing income distribution pattern and changing socio-economic profile of people, lifestyle pattern of the metropol- itan cities of developing countries are gradually converging the developed country counterparts. While countries are under- going fast economic growth and profound societal transformation, energy consumption and GHG emissions in the transport sector is increasing exponentially given the scale of urban expansion and continued quest of higher living standards. In this context, an attempt has been made to estimate the carbon footprint arising from household’s use of road transport in the city of Kolkata, one of the dynamic metropolitan cities of India. The objective of the paper is twofold. Firstly, to estimate the car- bon footprint of the city households across various income categories from road transport use and secondly, to find out how the footprint changes or rather what factors drive changes in the footprint values.
The study has been based on primary surveys done across the city of Kolkata by choosing about 500 households across various income classes defined. Estimation of carbon footprint shows a clear picture of the relation between people’s afflu- ence and the average per capita footprint. It clearly shows that per capita footprint from transport use increases with income. The lower middle income category, comprising 38 per cent of the population generates the highest total footprint at 47.8 tonnes annually On the other hand, the low income category comprising about 33 per cent of the population generates the lowest carbon footprint at 16.1 tonnes annually, with a per capita footprint of 0.026 tonnes. The middle income category also generates a substantial amount of total footprint amounting to about 36 tonnes annually. The high income category comprising merely 7.5 per cent of the population generates about 22.5 tonnes of footprint annually, with the highest per capita footprint of 0.385 tonnes. Thus it can be said that though the low, lower middle and middle income sections generate high total footprints, owing to a larger representation in the total population, it is actually the high income group in the city, whose per capita footprint is increasing and gradually approaching very high levels.
To determine what factors determine changes in the footprint values, a multiple linear regression model has been estab- lished with per capita carbon footprint as the dependent variable and per capita income, vehicle ownership, per capita trans- port expenditure and number of family members as the independent variables. Ideally speaking, education and awareness levels generally have a key impact on reducing carbon footprint. To examine this relationship, a variable called the average education level of the household was constructed. However, it is found in this case that public in general is not much aware of the threats of climate change or its drivers and impacts. Hence this variable has been dropped from our analysis as the coefficient for education variable turned out to be insignificant. It was also believed that other than income, there are some other factors that might determine households’ choice of transport. A dummy variable was used to explain this factor and it also turned out to be insignificant and was dropped from the model. Factors that have significant and positive impact on per capita footprint of households from road transport use are income, vehicle ownership and per capita transport expenditure.
India, by virtue of its size, has a large affluent population, but as a percentage of population they are merely 10 per cent to 15 per cent. With this background in place, it remains to be asked precisely what kind of policy measures may be helpful in reforming unsustainable use of transport and energy. This is a difficult question to answer, particularly because not much effort has been made in the past to consciously address this question, more so because it reflects political difficulties in implementing policies that change the way people live. People who maintain a high lifestyle (say through high vehicle own- ership) are reluctant to compromise on the same, while those who do not, aspire for it. It is therefore not easy to make life- style changes since it is very difficult to change the mindsets of people even if they do not have to compromise on their comfort level to a large extent. In this paper we have talked about carbon footprints resulting from road transport use by various income classes and we have found that high income, high per capita transport expenditure and high vehicle own- ership patterns results in higher footprints.
It is now widely observed that lifestyle pattern of the metropolitan cities of developing countries are changing rapidly. With changing income distribution pattern and changing socio-economic profile of people, lifestyle pattern of the metropol- itan cities of developing countries are gradually converging the developed country counterparts. While countries are under- going fast economic growth and profound societal transformation, energy consumption and GHG emissions in the transport sector is increasing exponentially given the scale of urban expansion and continued quest of higher living standards. In this context, an attempt has been made to estimate the carbon footprint arising from household’s use of road transport in the city of Kolkata, one of the dynamic metropolitan cities of India. The objective of the paper is twofold. Firstly, to estimate the car- bon footprint of the city households across various income categories from road transport use and secondly, to find out how the footprint changes or rather what factors drive changes in the footprint values.The study has been based on primary surveys done across the city of Kolkata by choosing about 500 households across various income classes defined. Estimation of carbon footprint shows a clear picture of the relation between people’s afflu- ence and the average per capita footprint. It clearly shows that per capita footprint from transport use increases with income. The lower middle income category, comprising 38 per cent of the population generates the highest total footprint at 47.8 tonnes annually On the other hand, the low income category comprising about 33 per cent of the population generates the lowest carbon footprint at 16.1 tonnes annually, with a per capita footprint of 0.026 tonnes. The middle income category also generates a substantial amount of total footprint amounting to about 36 tonnes annually. The high income category comprising merely 7.5 per cent of the population generates about 22.5 tonnes of footprint annually, with the highest per capita footprint of 0.385 tonnes. Thus it can be said that though the low, lower middle and middle income sections generate high total footprints, owing to a larger representation in the total population, it is actually the high income group in the city, whose per capita footprint is increasing and gradually approaching very high levels.To determine what factors determine changes in the footprint values, a multiple linear regression model has been estab- lished with per capita carbon footprint as the dependent variable and per capita income, vehicle ownership, per capita trans- port expenditure and number of family members as the independent variables. Ideally speaking, education and awareness levels generally have a key impact on reducing carbon footprint. To examine this relationship, a variable called the average education level of the household was constructed. However, it is found in this case that public in general is not much aware of the threats of climate change or its drivers and impacts. Hence this variable has been dropped from our analysis as the coefficient for education variable turned out to be insignificant. It was also believed that other than income, there are some other factors that might determine households’ choice of transport. A dummy variable was used to explain this factor and it also turned out to be insignificant and was dropped from the model. Factors that have significant and positive impact on per capita footprint of households from road transport use are income, vehicle ownership and per capita transport expenditure.India, by virtue of its size, has a large affluent population, but as a percentage of population they are merely 10 per cent to 15 per cent. With this background in place, it remains to be asked precisely what kind of policy measures may be helpful in reforming unsustainable use of transport and energy. This is a difficult question to answer, particularly because not much effort has been made in the past to consciously address this question, more so because it reflects political difficulties in implementing policies that change the way people live. People who maintain a high lifestyle (say through high vehicle own- ership) are reluctant to compromise on the same, while those who do not, aspire for it. It is therefore not easy to make life- style changes since it is very difficult to change the mindsets of people even if they do not have to compromise on their comfort level to a large extent. In this paper we have talked about carbon footprints resulting from road transport use by various income classes and we have found that high income, high per capita transport expenditure and high vehicle own- ership patterns results in higher footprints.
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