Spatial Analysis of Environmental Hazards

Spatial Analysis of Environmental Hazards

Spatial analysis of the factors influencing households direct energy consumption and CO2 emission in Ardabil

Authors
Taher Parizadi
Habibollah Fasihi
Fahad Agah
Kharazmi University
10.52547/jsaeh.8.4.89
Abstract
Spatial analysis of the factors influencing households’ direct energy

consumption and CO2 emission in Ardabil

Problem Statement

Carbon management and its production resources are important not only for the preservation of non-renewable resources but also for the prevention of global warming and its adverse consequences. Direct consumption of fuel and energy by households plays a major role in CO2 production and it’s spatial distribution. Therefore, in order to plan and manage carbon emissions, it is very important to identify the factors influencing household energy consumption. This paper aimed to investigate the relationship between household characteristics such as age, income, family size, household head age, house area, etc. and energy consumption which ordinally results in more emissions. The study area is Ardabil city. It has an area of 6289 ha and a population of about 530000 people.



Research Method

Consumption of natural gas, electricity and car fuel has been the criteria for determining the amount of household energy consumption. The data of the first two cases obtained from the bills of household’s consumption and the data of car fuel consumption and the other other required data, were collected through a survey as well. Based on the Cochran's formula, statistical samples including 383 households were selected as a sample of the households residing in Ardabil. A questionnaire was also used to collect the data. Data on energy consumption variables were first converted to Mj and then converted to CO2 emissions. The data was then entered into Arc GIS to draw spatial distribution maps using Kriging interpolation Tool. Finally, using TerrSet Geospatial Monitoring and Modeling System software, the spatial relationship maps were produced and the adjusted R values were calculated.



Findings and Conclusions

Findings demonstrate that in Ardabil, household fuel consumption cause to an emission of more than 226,515 grams of CO2 per household every month which is three times more than the mean value for all the Iranian households. In the study area, the average amount of energy consumption and carbon emission of households residing in municipality districts 2 and 3 are higher than same figure for all the households residing in the city. In contrast, in the municipality districts of 1 and 5, energy consumption and CO2 emission are lower than the mean value for the whole Ardabil households. In district 4, the figure is very close to the mean value for all the households. More than 80 percent of household CO2 emission emitted from fuel consumption in homes and this ratio is almost the same throughout the city and in all municipality districts. After that, the ratio of transportation CO2 emission is about 15%, and electricity consumption has a ratio of less than 5% as well. In four lots located in the southwest, north, northeast and the center of the city, every year, households emit less than 172640 g/m of CO2. In contrast, in 4.8% of the city surface area, the lots located in southwestern and southeastern, households’ emission of CO2 is the most (more than 308923 g/m). The adjusted R, which represents the spatial relationship between the variables with CO2 emission, for all the 11 variables, were 0.67, 0.66, 0.72, 0.80, 0.87 and 0.88 for the city, district 1, district 2, district 3, district 4 and district 5 respectively and these values indicate that there is a high correlation between these variables. The highest adjusted R values (0.8 and more) belong to the strip-shaped lots locate in the central and eastern fringes of the city and they cover almost half of the surface area of district 2 and a small part of district 1. Areas where R value is less than 0.2 cover almost the whole surface of district 5 in the northeast of the city. Also, variables of “number of people who have a driving license in any household”, “household head age”, “household size and “house surface area”, represent a high correlation between these variables and CO2 emissions. Also, the correlation between the variables level of “education of household head”, “household head income” and “having electrical appliances” indicate that there is the lowest correlation between the variables and with CO2 emissions.

Key Words: Energy, CO2, Household consumption, Spatial relation, Ardebil


Keywords
Energy
CO2
Household consumption
Spatial relation
Ardebil
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Spatial Analysis of Environmental Hazards
Volume 8, Issue 4
Winter 2021
Pages 89-102