Tallam Teja, Kurre Sai Sahitya, Viswanath Badri
Department of Civil Engineering, VNR VJIET, Hyderabad, India.
Environ Sci Pollut Res Int. 2025 Jul 14. doi: 10.1007/s11356-025-36749-x.
Air pollution remains a pressing global concern, significantly contributing to climate change and environmental degradation. Among the primary contributors, greenhouse gases-especially from carbon emissions-play a critical role in the warming of the Earth's atmosphere. In urban areas, vehicular emissions are the second-largest source of carbon emissions, following industrial outputs. This study quantifies the carbon footprint of urban intersections by analyzing carbon monoxide (CO) emissions at signalized intersections, where vehicular idling and acceleration are concentrated. Three four-way signalized intersections in Hyderabad, India, were selected for an in-depth analysis of CO levels in relation to traffic parameters, namely nearing traffic volume (NV), red signal duration (RT), queue length during red time (QLR), and intersection area (IA). CO emissions were measured using an electrochemical carbon monoxide meter (HTC), which provided real-time CO concentration data. Traffic parameters were collected via videography and analyzed using the DATAFROMSKY software to extract vehicle counts and movements. The study applied Multiple Linear Regression (MLR) and Support Vector Regression (SVR) models to predict CO levels at these intersections. Performance assessments using RMSE and MAPE indicated that the SVR model outperformed MLR, achieving an RMSE of 1.12 and a MAPE of 0.085. Furthermore, intersections were ranked based on the National Air Quality Index (AQI), with all three sites falling within the "Poor" category, registering AQI values of 207, 276, and 276, respectively. This study highlights the critical need for targeted interventions at urban intersections to mitigate CO emissions and improve air quality in alignment with sustainable environmental objectives.
空气污染仍然是一个紧迫的全球问题，对气候变化和环境退化有重大影响。在主要污染源中，温室气体——尤其是碳排放——在地球大气变暖中起着关键作用。在城市地区，车辆排放是仅次于工业产出的第二大碳排放源。本研究通过分析信号交叉口的一氧化碳（CO）排放来量化城市交叉口的碳足迹，车辆空转和加速集中在这些信号交叉口。印度海得拉巴的三个四路信号交叉口被选来深入分析与交通参数相关的一氧化碳水平，这些交通参数包括接近交通量（NV）、红灯时长（RT）、红灯期间排队长度（QLR）和交叉口面积（IA）。使用电化学一氧化碳测量仪（HTC）测量一氧化碳排放，该测量仪提供实时一氧化碳浓度数据。通过摄像收集交通参数，并使用DATAFROMSKY软件进行分析，以提取车辆数量和行驶情况。该研究应用多元线性回归（MLR）和支持向量回归（SVR）模型来预测这些交叉口的一氧化碳水平。使用均方根误差（RMSE）和平均绝对百分比误差（MAPE）进行的性能评估表明，SVR模型优于MLR模型，RMSE为1.12，MAPE为0.085。此外，根据国家空气质量指数（AQI）对交叉口进行排名，所有三个地点都属于“差”类别，AQI值分别为207、276和276。本研究强调了在城市交叉口采取针对性干预措施以减少一氧化碳排放并根据可持续环境目标改善空气质量的迫切需求。
