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Volume 3, Issue 1 (4-2016)
In the present era, most cities have been faced with numerous problems. But the environmental dimension has been more challenging. Many urban professionals constantly seek to present effective solutions in order to prevent damage to the environment. Thus, theories, models and many views in this subject have taken, including livability approach derived by the school of sustainable development. So today, as one of the views livability approach is rooted in the theory of sustainable development has been focused on, and the above approach can cause problems in multiple cities. In this research, Region 17 of Tehran as the most problem area, was selected; and the overall goal of this study is assessing the livability of the Region 17’s neighborhoods, and the objective aims are including the assessing of livability dimensions, i.e. the environmental, the historical pattern, the urban management policies, the social, services, activities and facilities, the urban economy at the local level and identifying the livability homogeneous clusters and assessment the impact of livability’s variables, dimensions and indicators in that area. According to the study of the history and theoretical foundations of livability, the most important dimensions, indicators and items related to livability were extracted and the all selected dimensions and indicators, rooted in history and theoretical basis of their livability. In the present study include the following six dimensions of environmental, historical pattern, urban management policies, social, services, activities and facilities, urban economy with 20 indicators and 94 items were considered and the pattern of research in terms of goal, is cognitive; in terms of nature and method, is comparative – assessment; and about location of territory is Tehran’s Region 17, in respect of timing, is temporal and related to the 2015. Combined data collection method is combined0 (documents, survey) and it is the type of quantitative-qualitative data (questionnaire). The data used in the research is preliminary data that were obtained by questionnaire. The statistical society are the residents and citizens of Tehran’s Region 17 who are questioning. The necessary actions to operationalize the research was conducted in several stages: 1) Adjustment of questionnaire (using five Likert scale ranging from very low to very high range, verifying the validity by experts, verifying the performance reliability of the questionnaire by using the Cronbach's alpha in software of SPSS as a result 0.8), 2) Determining the sample size and sampling (400 samples determined by Cochran formula, using multi-stage sampling), 3) Entering data into SPSS software and doing the statistical tests (parametric statistical tests such as one sample T-test, ANOVA, Friedman) analyzing the data by SPSS and statistical tests of one sample T-test, ANOVA, Friedman, represents the undesirable od livability and its dimensions, the difference between neighborhood in terms of livability and more economic effectiveness on the livability of Region’s 17 and its neighborhoods, 4) The showing of spatial diagrams of research findings and preparing the livability’s maps by using ArcGis software and interpolation method. Ultimately, according to the findings and viewpoints of researchers and field observations, it can be concluded that the causes of problems in this area should be within the region and neighborhoods, it's time to overcome the situation that has been searched. In other words, the root of the problems in the above range is due to its geographical bed’s situation and other substrate characteristics. The meaning of geographical bed’s situation, climatic and tectonic characteristics of the area and the order of the micro-feature is the problems with the nature of the social, economic, administrative, infrastructure etc, so that were formed following the influx of population. Until two important problems raised in this region is not considered to be flows: 1) Geographic bed features, 2) the capacity of Region 17 for accommodation of population and services to them.
Volume 8, Issue 4 (3-2022)
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
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