BibTex Citation Data :
@article{AQCCM25851, author = {Indri Marlena and Haryono Setiyo Huboyo and Pertiwi Andarani and Annisa Nurul Sasikirana}, title = {Emission Inventory Estimation and Dispersion Model Study using AERMOD And CALINE4 From Transportation On Road}, journal = {Air Quality and Climate Change Management}, volume = {1}, number = {1}, year = {2025}, keywords = {}, abstract = { Urban air pollution has escalated due to increased vehicular traffic, necessitating accurate emission inventories and dispersion models. This study estimates emission loads and models pollutant dispersion using AERMOD and CALINE4, focusing on Semarang City’s transportation sector. Emission inventories were derived using the Tier 2 method, considering various vehicle categories and kilometers traveled. AERMOD and CALINE4 were employed to simulate the dispersion of NOx, SO2, PM10, HC, and CO. Emission data from January to December 2017 were collected, focusing on different vehicle types and road categories. AERMOD and CALINE4 models were utilized to predict pollutant concentrations, incorporating meteorological data and vehicle emission factors. The analysis revealed that motorcycles were the largest contributors to emissions, producing significant amounts of CO and HC. AERMOD results indicated high pollutant concentrations in Central Semarang, while CALINE4 estimated notable CO levels on Perintis Kemerdekaan Road. Both models showed variability due to atmospheric conditions, with wind speed and direction significantly affecting pollutant dispersion.The study underscores the critical role of emission inventories in air quality management, highlighting the need for targeted interventions to mitigate pollution from road transportation. Accurate modeling aids policymakers in developing effective strategies to improve urban air quality and public health. }, url = {https://ejournal2.undip.ac.id/index.php/aqccm/article/view/25851} }
Refworks Citation Data :
Urban air pollution has escalated due to increased vehicular traffic, necessitating accurate emission inventories and dispersion models. This study estimates emission loads and models pollutant dispersion using AERMOD and CALINE4, focusing on Semarang City’s transportation sector. Emission inventories were derived using the Tier 2 method, considering various vehicle categories and kilometers traveled. AERMOD and CALINE4 were employed to simulate the dispersion of NOx, SO2, PM10, HC, and CO. Emission data from January to December 2017 were collected, focusing on different vehicle types and road categories. AERMOD and CALINE4 models were utilized to predict pollutant concentrations, incorporating meteorological data and vehicle emission factors. The analysis revealed that motorcycles were the largest contributors to emissions, producing significant amounts of CO and HC. AERMOD results indicated high pollutant concentrations in Central Semarang, while CALINE4 estimated notable CO levels on Perintis Kemerdekaan Road. Both models showed variability due to atmospheric conditions, with wind speed and direction significantly affecting pollutant dispersion.The study underscores the critical role of emission inventories in air quality management, highlighting the need for targeted interventions to mitigate pollution from road transportation. Accurate modeling aids policymakers in developing effective strategies to improve urban air quality and public health.
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