Extended Abstract
Introduction
   The concept of mass-space, defined as the interaction between built environments (mass) and open/public areas (space), plays a pivotal role in shaping sustainable and livable cities. In industrializing metropolises such as Ahvaz, unplanned urban expansion has intensified noise pollution as an environmental stressor, a issue that has thus far received limited scholarly attention. Adopting an interdisciplinary approach, this study investigates the relationship between urban morphology and sonic ecology, proposing 'sound level' as an effective diagnostic tool for identifying and analyzing mass-space patterns in Ahvaz. As a hub for Iran's oil and gas industries, Ahvaz faces significant noise pollution challenges stemming from heavy traffic, concentrated industrial activity, and deficiencies in urban planning. Through sound mapping and examining its correlation with urban form, this research demonstrates how acoustic data can contribute to more equitable planning, reduced health risks, and the preservation of urban identity. While prior studies have predominantly focused on noise modeling in Western cities, this work addresses a gap in the literature concerning Middle Eastern urban contexts.
Materials and Methods
   This study employed a mixed-methods framework integrating field analysis, Geographic Information Systems (GIS), and statistical modeling. Acoustic data were collected at 300 sampling points using a stratified random sampling method and a calibrated KIMO DB100 sound level meter during two peak periods: daytime (9:00 AM) and nighttime (9:00 PM). To generate a city-wide sound level zoning map, the Inverse Distance Weighting (IDW) interpolation method was applied within ArcGIS software, with the output classified into five qualitative categories. The validity and reliability of the methodology were confirmed via a two-stage verification process: first, evaluation against independent data from 30 control points, which yielded a Mean Absolute Error (MAE) of 2.8 dB; and second, calculation of Pearson's correlation coefficient (r = 0.91) between the sound level layer and the municipal land-use map, confirming a strong spatial congruence.
Results and Discussion
   The findings indicate that approximately 54% of Ahvaz's area (equivalent to over 11,600 hectares) exceeds the national permissible sound level limits. This figure underscores the considerable scale of the noise pollution problem in this metropolis. The revealed spatial pattern demonstrates a direct correlation with the city's mass-space structure. The primary noise pollution hotspots (with levels of 78-70 dB) are concentrated in the industrial zones of the southeast, heavy-traffic corridors leading to the Karun River bridges, and dense residential-commercial cores. These areas clearly correspond to the city's intensive, high-activity 'mass.' Conversely, zones with the lowest sound levels (43-35 dB) predominantly align with open 'spaces,' including vacant lands, barren areas, and green spaces in the city's west and southwest, highlighting their role as urban respiratory spaces and acoustic buffers. The robust correlation coefficient (0.91) quantitatively confirms that sound level can serve as a reliable proxy indicator for identifying the intensity of human activity and analyzing mass-space configurations. Although this finding aligns with global studies in densely populated cities, the severity of pollution in Ahvaz's industrial areas and the emergence of a pronounced polarized pattern (noisy east versus quiet west) reveal the ineffectiveness of current zoning policies and a distinct spatial inequality that disproportionately affects lower-income residents.
Conclusion
   This study demonstrates that sound level mapping is a powerful, cost-effective, and objective tool for diagnosing spatial inequalities and analyzing the structure of urban mass-space. The findings emphasize the urgent necessity of integrating acoustic considerations into the urban planning, design, and management processes in Ahvaz. Practical solutions are proposed at three levels: at the physical/design level, establishing green belts and buffers as acoustic insulation and revising building regulations; at the macro-policy level, reviewing zoning plans and incorporating noise standards into master documents; and at the managerial level, deploying intelligent monitoring systems and designating quiet urban areas. This research provides a framework for urban planners and designers to utilize acoustic indicators in moving towards the formation of more sustainable, equitable, and higher-quality cities.