The rapid growth of urbanization and industrial development has led to an increase in greenhouse gas emissions, negatively impacting the quality of the urban environment. This has resulted in urban environmental pollution, a decline in citizens' quality of life, and reduced public health. Therefore, the primary objective of this study is to identify and analyze the spatial factors and urban land uses influencing carbon emissions in this metropolis.

The research adopts a descriptive-analytical approach based on spatial and statistical data. Spatial analysis methods such as Moran’s spatial autocorrelation and the geographically weighted regression (GWR) model have been utilized. The results indicate that carbon emissions in Tabriz exhibit a clustered pattern, with the highest concentrations found in industrial areas, densely populated regions, and zones with high building density. Key influencing variables include population density, building density, road network density, industrial land use, commercial land use, traffic volume, and building occupancy rate, all of which significantly contribute to increased carbon emissions. Conversely, an increase in green space land use has played a positive role in reducing carbon dioxide emissions.

The findings suggest that unbalanced urban development, the concentration of polluting industries, high building density, and an extensive road network directly contribute to rising carbon emissions. Based on these results, it is recommended that urban policies prioritize sustainable development, focusing on optimizing land use, expanding green spaces, and reducing traffic-related pollutants.

1. Introduction

Urbanization and rapid population growth have significantly altered the spatial structure of cities, leading to substantial environmental challenges, particularly in terms of carbon emissions. The increasing concentration of human activities, industrial development, and transportation networks has exacerbated the emission of greenhouse gases, particularly carbon dioxide (CO₂), which is a major contributor to climate change. In this context, large cities, especially metropolises in developing countries, are experiencing severe environmental degradation due to unbalanced urban expansion, inefficient land use planning, and increasing reliance on fossil fuels.

Tabriz, as one of Iran's major metropolitan areas, has undergone rapid and often unplanned urban development. This has led to a significant increase in the city's carbon footprint, with dense urban

cores, industrial zones, and high-traffic corridors contributing to the highest levels of emissions. Previous studies suggest that urban form, spatial structure, and land use configurations are critical factors influencing carbon emissions. However, a comprehensive spatial analysis of these relationships, particularly within the context of Tabriz, is lacking.

This study aims to analyze the spatial distribution of carbon emissions in Tabriz at the neighborhood level. By employing geospatial analytical techniques, it identifies the key determinants of carbon emissions and examines how urban spatial structure influences emission patterns. The research provides insights into how land use types, urban density, road networks, and green spaces interact to shape the environmental footprint of the city. Understanding these relationships is essential for designing effective urban policies that promote low-carbon development and mitigate the adverse effects of climate change.

2. Methodology

The research adopts an applied approach and employs a descriptive-analytical method. Data collection involves satellite imagery, census data, and urban planning documents. Geospatial analysis techniques, including spatial autocorrelation (Moran’s I) and geographically weighted regression (GWR), were applied to identify spatial clusters of carbon emissions and determine the influence of variables such as building density, population density, road network density, land use types, and traffic patterns.

3. Results

Findings indicate that carbon emissions in Tabriz exhibit a clustered spatial pattern, with significant correlations to factors such as industrial land use, building density, and road network density. High-emission zones are concentrated in industrial and densely populated areas, while the presence of green spaces effectively mitigates carbon emissions. The GWR model confirms that the spatial impact of these factors varies across the city, with industrial areas and high-traffic zones being the most significant contributors.

4. Discussion

The results highlight the uneven distribution of carbon emissions and the role of urban form in shaping environmental sustainability. Compact urban development and efficient land use planning can contribute to carbon reduction. Additionally, integrating green infrastructure and promoting sustainable transportation are key strategies for mitigating emissions.

5. Conclusion

This study underscores the necessity of spatially informed urban policies to curb carbon emissions in Tabriz. By prioritizing sustainable urban planning and adopting data-driven approaches, policymakers can foster low-carbon city development. The findings offer valuable insights for decision-makers aiming to balance urban growth with environmental sustainability.

Acknowledgments

Urban Spatial Structure, Carbon Emissions, Sustainable Development, Spatial Analysis, Tabriz Metropolis

Based on these results, it is recommended that urban policies prioritize sustainable development, focusing on optimizing land use, expanding green spaces, and reducing traffic-related pollutants

The findings of this research show that the carbon emission in the neighborhoods of Tabriz metropolis has a cluster pattern and is directly influenced by the urban spatial structure. In particular, factors such as building density, population density, road network density, industrial use, commercial use, traffic and the amount of green space play a key role in the amount of carbon emissions.

The analysis of the results of geographic weighted regression shows that industrial use has the greatest effect on carbon emissions.