The rapid growth of smart cities resulted in an increasing need for precise, real time observation of environmental conditions to address challenges such as air pollution, unsafe emissions, and other climate related problems. These challenges put a risk on the environment and have a direct effect on public health as well as standard of life Traditional surveilling and data processing approaches often struggle to manage with the scale, speed, and intricacy necessary for effectively analyzing high frequency sensor data. This work proposes a framework that combines quantum computing and quantum sensors within an Internet of Things (IoT) architecture to remarkably improve environmental monitoring. Quantum sensors provide highly sensitive detection capabilities for pollutants, chemical threats, and subtle environmental shifts that traditional sensors may overlook. Concurrently, quantum computing offers the processing power needed to handle large, multidimensional datasets with unexpected speed and precision, exceeding the capabilities of classical computing systems. The combination of these technologies enables real-time data analysis, predictive modeling, and prompt decision-making, empowering cities to issue early warning notifications, identify emerging trends, and implement preventative strategies before problems intensify. This chapter also explores ongoing research and potential hurdles to implementation, such as costs, hardware readiness, and data security, while suggesting strategic approaches for integration. By combining cutting-edge quantum technologies with urban IoT infrastructures, the proposed system establishes a basis for smarter, more resilient, and environmentally adaptive cities in the future.