Sustainable city

Sustainable city

Carbon storage capacity in a city with a cold and mountainous climate: the case study of Urmia city and Suburb

Document Type : Research Paper

Authors
1 Faculty of Geography, University of Tehran, Tehran, Iran.
2 Associate Prof. Physical Geography department, Faculty of Geography, University of Tehran
3 Department of Physical Geography, Faculty of Geography, University of Tehran.
10.22034/jsc.2024.434150.1758
Abstract
A B S T R A C T
In the research, the carbon storage capacity of Urmia's urban and suburb green infrastructures were analyzed. Urmia is characterized by a cold climate with a dense building structure with scattered green spaces, especially in the surrounding areas and neighborhoods of the city. The research was carried out using the carbon storage model available in the InVest software package. The results revealed that more than 57% of the study area has a carbon storage capacity of less than 2 tons, and less than 6 percent of the area has more than 30 tons per hectare, which is limited to the gardens and groves along the Shahrchai River. Soil carbon storage has the highest share with 2344.41 tons, and above biomass carbon storage followed closely with 1403.47 tons. The total amount of carbon storage in the studied area is 3900.9 tons per year. The carbon storage was highest in gardens and groves, followed by barren lands with sparse vegetation and rocky outcrops mountain’s without vegetation and soil cover had no carbon storage. Dense plants and trees have the highest storage capacity per unit area, However, the amount of storage depends on the season, so it is necessary to consider the selection and expanding the urban green spaces according to the types of plants and their compatibility with the climatic conditions and urban spaces of Urmia. As a result, it is necessary to create and develop urban green spaces at the same time as physical development, it should be the priority of Urmia's urban development plans.
Extended Abstract
Introduction
Cities with high energy consumption, extensive changes of land cover/ land use, increasing impervious surfaces and construction fraction, change of surface geometry and topography, and as a result, a change in the surface energy balance and water cycle pattern and abundant production of greenhouse gases. The city’s growth and changes in the land cover pattern cause extensive social and environmental changes. Ecosystem services are benefits that human societies receive from ecosystems and natural resources and are divided into four categories as regulation, provision, support, and cultural services. Hence, carbon storage is a win-win approach (by creating recreational spaces, adjusting air temperature, and air pollution) to moderate the destructive effects of human activity in solving the problems of increasing greenhouse gas emissions in urban spaces. 
Since cities have become significant carbon emissions sources, accurate carbon storage and sequestration assessment is needed in the city area. Urmia is facing an increase in population, followed by the sprawl of urban areas. Therefore, calculating the effects of urbanization growth and land cover changes on the amount of ecosystem services and valuing these services is necessary to improve the understanding of urban ecology and achieve sustainable ecosystem services. The study aims to calculate the carbon storage capacity of Urmia City according to the changing conditions of urban green spaces in hot and cold periods.
 
Methodology
The most important data required for the research was the land cover map of Urmia city and suburbs, which was prepared by processing Landsat 8 satellite images for 2020. Also, the data related to carbon stock in four main reservoirs were extracted from the information available from the Intergovernmental Panel on Climate Change (IPCC). The InVEST (Integrated Valuation of Ecosystem Services and Exchanges) model was used to analyze the amount of carbon storage in each LULC class. The InVEST-CSS carbon sequestration model
 
 
estimates the amount of carbon stored in a land cover and values the amount of sequestered carbon over time. This model first collects the biophysical amount of carbon stored in four carbon pools (above-ground biomass including all living biomass above the soil; below-ground biomass including all living biomass of live roots; soil including the organic components of the land; and dead wood biomass containing all non-living biomass related to dead leaves, branches, and trunks) based on land use/land cover (LULC) maps provided by users. The second step consists of an evaluation model that approximately determines the value of carbon sequestered by ecosystems (the net value of sequestered carbon) in a given period.
 
Results and discussion
Most of the land cover in the suburbs is land with soil and rock outcrops. The main characteristic of a compact and medium-height building characterizes the area of the city. According to the model outputs, the above biomass carbon storage in the city center has average conditions. Lands with rocky outcrops in the study area have the lowest carbon storage values. On the other hand, Shahrchai River route has the highest amount of carbon storage (between 40 and 50 tons per hectare). Concerning dead organic matter, the city area is located on two levels with no carbon storage capacity and low storage capacity between 0.1 and 2 tons per hectare. Over 57% of the study area has carbon storage between 0.1 and 2 tons per hectare. Also, less than 6% of the range of carbon storage capacity is above 30 tons per hectare, which is limited to the gardens and groves along the Shahrchai. About 67% of above-ground biomass has a low carbon storage capacity range of 0.1 to 2 tons per hectare, which is a total of 25750 tons of carbon storage capacity. More than 30% of the area with the characteristics of barren lands and with rocky facies and intensive construction uses cannot store carbon from the source of dead organic matter. As an important carbon storage reservoir, soil in the city and suburbs of Urmia has 2344 tons of carbon storage capacity. According to the total carbon storage values of all resources, a large city area with a storage capacity between 15 and 30 tons per hectare has been calculated. The total amount of storage in the area is 3900 tons, which is more than 10 tons per hectare on average for all uses. The most important role or ecosystem service of carbon storage is soil, with 234441 tons, and the least is dead organic matter, with 37633 tons. The highest amounts of carbon storage per surface unit (tons per hectare) are in garden lands and groves at 75.19 tons per hectare, agricultural lands at 14.73 tons per hectare, and lands with less vegetation at 10.33 tons per hectare.
 
Conclusion
Based on the calculations in the current situation, about 3900 tons are stored in the total 358 hectares of the study area with an average of 10 tons of carbon per hectare by the existing land uses. Contrary to the results of Podyal et al. (2017) or Abu Hashem et al. (2016) that the development of the urban areas of the Mediterranean coast and the reduction of natural covers in that climatic region led to a decrease in the amount of carbon storage and the intensification of climate change at the local and urban scale. In Urmia, due to the mountains without soil cover and, as a result, lack of vegetation in the suburbs, the urban growth with the development of green spaces has increased the urban carbon storage capacity. It is necessary to pay more attention to developing green infrastructures under the principle of climate adaptation by adjusting atmospheric carbon and regulating the city's atmospheric conditions. Carbon storage capacity maps can be a good help for the better management of ecosystems at different spatial scales so that managers can better identify the places of protection, harvest, and development, and with proper and intelligent management, they can ensure the continuation of reserved ecosystem services carbon in the environment.
 
Funding
There is no funding support.
 
Authors’ Contribution
It is confirmed, the first author in writing the initial text, ran the model (40 percent), getting their output, the second author in editing the text, analysis and the process of sending and answering judgments (30 percent), and the third author in running the model, analyzes (30 percent) have participated
 
Conflict of Interest
Authors declared no conflict of interest.
 
Acknowledgments
 We are grateful to all the scientific consultants of this paper.
Keywords

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