Devi L Pinky, Chandana R, Bandhu Din
Department of Civil Engineering, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, 576104, Karnataka, India.
Department of Civil Engineering, Nagarjuna College of Engineering and Technology, Bengaluru, 562110, Karnataka, India.
Sci Rep. 2025 May 22;15(1):17805. doi: 10.1038/s41598-025-00814-9.
Particulate Matter (PM) emissions have emerged as a critical global concern due to rapid urbanisation, increased vehicular traffic, and construction activities. These emissions not only harm human health and the environment but also degrade building materials, posing a threat to infrastructure. This study focuses on assessing PM emissions, forecasting Air Quality Index (AQI) levels, and evaluating the structural health of buildings in Bangalore. Data from 12 monitoring stations across the city, collected between 2013 and 2021, were analysed to identify key pollutants, seasonal variations, and their impact on buildings. The study reveals that PM and PM are the primary pollutants, with concentrations peaking during summer and winter, while monsoon seasons show lower levels. A forecasting model with 93% accuracy was developed to predict AQI levels, demonstrating a strong correlation between predicted and actual values. Structural health monitoring, conducted using Non-Destructive Testing methods, highlights significant deterioration in buildings located in high-pollution areas, such as the Peenya Industry and K.R. Market. The findings underscore the urgent need for measures to mitigate pollution's impact on both public health and infrastructure. This study provides valuable insights for policymakers and urban planners to develop targeted strategies for improving air quality and preserving building integrity in rapidly urbanising cities.
由于快速城市化、车辆交通增加和建筑活动，颗粒物（PM）排放已成为全球关注的关键问题。这些排放不仅危害人类健康和环境，还会使建筑材料退化，对基础设施构成威胁。本研究重点评估班加罗尔的PM排放、预测空气质量指数（AQI）水平以及评估建筑物的结构健康状况。分析了2013年至2021年期间从全市12个监测站收集的数据，以确定关键污染物、季节变化及其对建筑物的影响。研究表明，PM和PM是主要污染物，浓度在夏季和冬季达到峰值，而季风季节浓度较低。开发了一个准确率为93%的预测模型来预测AQI水平，预测值与实际值之间显示出很强的相关性。使用无损检测方法进行的结构健康监测突出显示，位于高污染地区的建筑物，如佩尼亚工业区和K.R.市场，出现了明显的恶化。研究结果强调迫切需要采取措施减轻污染对公众健康和基础设施的影响。本研究为政策制定者和城市规划者提供了宝贵的见解，以便他们制定有针对性的战略，在快速城市化的城市中改善空气质量并维护建筑完整性。
