Motor vehicle emissions especially occur at signalized intersections during idling, acceleration, and deceleration phases. The reduction of exhaust emissions from motor vehicles is on the focus of environmental studies. The main targets of this paper are the modeling of motor vehicle particulate matter (PM₁₀) emissions by American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) and California Line Source for Queuing and Hot Spot Calculations (CAL3QHCR) models and investigating the effectiveness of a hypothetical green wave scenario as a pollution reduction strategy. The portion of D010 State Road in Zonguldak (Turkey) is selected. Vehicle counting is applied for determining the traffic volume. Then, the PM₁₀ emission inventory is prepared. After that, PM₁₀ pollution distribution maps at signalized intersections are created by running air quality models. Next, the CAL3QHCR model is run again for the green wave scenario which assumes free flow at signalized intersections. The maximum PM₁₀ concentrations predicted by AERMOD and CAL3QHCR models are 16.8 µg/m³ and 14.9 µg/m³, respectively. Although these values are below the threshold value, it can be said that air quality may pose a threat to public health in the existence of other sources. With the implementation of signal optimization, the PM₁₀ pollution is reduced by 10–50% at intersections. Cumulative model validation is employed including other PM₁₀ sources in the study area. PM₁₀ contribution of other sources at Zonguldak air quality monitoring station is determined by the AERMOD model. Finally, the sum of model outputs is validated against measured concentrations. According to the validation, both models are found as satisfactory and AERMOD performed better than CAL3QHCR.

在怠速、加速和减速阶段，机动车排放尤其发生在信号交叉口。减少机动车尾气排放是环境研究的重点。本文的主要目标是通过美国气象学会/环境保护局监管模型 (AERMOD) 和加利福尼亚线源排队和热点计算 (CAL3QHCR) 模型对机动车颗粒物 (PM ₁₀ ) 排放进行建模并调查其有效性假设的绿浪情景作为减少污染的策略。选择了宗古尔达克（土耳其）的 D010 国道部分。车辆计数用于确定交通量。然后，PM ₁₀编制排放清单。之后，通过运行空气质量模型创建信号交叉口的PM ₁₀污染分布图。接下来，CAL3QHCR 模型再次针对绿波场景运行，该场景假设信号灯交叉口自由流动。AERMOD 和 CAL3QHCR 模型预测的最大 PM ₁₀浓度分别为 16.8 µg/m ³和 14.9 µg/m ³。虽然这些数值都低于阈值，但可以说空气质量在存在其他来源的情况下可能对公众健康构成威胁。随着信号优化的实施，交叉路口的 PM ₁₀污染减少了 10-50%。采用累积模型验证，包括其他 PM研究区有_10个来源。Zonguldak 空气质量监测站其他来源的PM ₁₀贡献由 AERMOD 模型确定。最后，模型输出的总和针对测量的浓度进行验证。根据验证，两个模型都令人满意，并且 AERMOD 的性能优于 CAL3QHCR。