Accurate estimation of vehicle exhaust emissions at urban intersections is essential to assess environmental impacts and support sustainable traffic management. Traditional emission models often rely on aggregated traffic volumes or measures of average speed that fail to capture the dynamic behaviors of vehicles such as acceleration, deceleration, and idling. This study presents a methodology that leverages video data from smart intersections to estimate vehicle emissions at microscale and in real time. Using a CenterNet-based object detection and tracking framework, vehicle trajectories, speeds, and classifications were extracted with high precision. A structured preprocessing pipeline was applied to correct noise, missing frames, and classification inconsistencies to ensure reliable time-series inputs. Subsequently, a lightweight emission model integrating vehicle-specific coefficients was employed to estimate major pollutants including CO and NOx at a framelevel resolution. The proposed algorithm was validated using real-world video data from a smart intersection in Hwaseong, Korea, and the results indicated significant improvements in accuracy compared to conventional approaches based on average speed. In particular, the model reflected variations in emissions effectively under congested conditions and thus captured the elevated impact of frequent stopand- go patterns. Beyond technical performance, these results demonstrate that traffic video data, which have traditionally been limited to flow monitoring and safety analysis, can be extended to practical environmental evaluation. The proposed algorithm offers a scalable and cost-effective tool for urban air quality management, which enables policymakers and practitioners to link traffic operations with emission outcomes in a quantifiable manner.

본 연구에서는 열유도상분리법으로 제조한 polyvinylidene fluoride (PVDF) 중공사막의 오염성과 화학적 세척에 대한 실험을 진행하였다. 오염수는 소 혈청 단백질(bovine serum albumin, BSA)과 카올린(kaolin)을 이용해 제조하였으며, 차아 염소산나트륨(NaOCl), 구연산(citric acid), 황산(H2SO4)으로 화학적 세척을 진행한 후 뒤 표면 전하 분석기, 주사전자현미경 (scanning electron microscope, SEM) 그리고 에너지 분산 X선 분광법(energy dispersive X-ray spectroscopy, EDX)을 통해 세 척 효율을 평가하였다. PVDF 분리막은 높은 내화학성과 열적 안정성을 가지는 분리막으로 화학적 세척을 진행한 결과 가장 좋은 효율은 차아염소산나트륨으로 세척한 것으로 그 결과 투과도는 793.2 L/(m2.h.bar)로 초기 투과량인 945.3 L/(m2.h.bar) 값과 비교하였을 때 약 84% 회복률을 보여주었다. 이는 수처리 공정에서의 막 오염 방지 및 세척의 중요성을 제시한다.