Open Access
| Issue |
E3S Web Conf.
Volume 650, 2025
The 10th International Conference on Energy, Environment, and Information Systems (ICENIS 2025)
|
|
|---|---|---|
| Article Number | 01019 | |
| Number of page(s) | 14 | |
| Section | Energy | |
| DOI | https://doi.org/10.1051/e3sconf/202565001019 | |
| Published online | 10 October 2025 | |
- Nurlestari and S. Oktavilia, “Industrial Agglomeration and Economic Growth in Indonesia,” Efficient: Indonesian Journal of Development Economics, vol. 6, no. 1, pp. 1–12, 2023. [Google Scholar]
- Y. Wang, L. Huang, C. Huang, J. Hu, and M. Wang, “High-resolution modelling for criteria air pollutants and the associated air quality index in a metropolitan city,” Environ. Int., vol. 172, p. 107752, 2023. [Google Scholar]
- J. B. Johnson, “An Introduction to Atmospheric Pollutant Dispersion Modelling,” in Proc. 5th Int. Electron. Conf. Atmospheric Sciences, Rockhampton, Australia: CQUniversity, 2022. [Google Scholar]
- A. M. A. Istiyanto, “Modelling the Distribution of Air Pollutants from Tello PLTD Activities Using the Gauss Dispersion Model,” J. Sci. Phys. Educ., vol. 15, no. 1, pp. 36–44, 2019. [Google Scholar]
- F. Ogbozige, “Gaussian Plume Model Design of Effective Stack Height for Control of Industrial Emissions,” Int. J. Sci. Res. Publ., vol. 15, no. 1, pp. 95–104, 2023. [Google Scholar]
- H. Jumaah, M. Ameen, B. Kalantar, H. Rizeei, and S. Jumaah, “Air quality index prediction using IDW geostatistical technique and OLS-based GIS technique in Kuala Lumpur, Malaysia,” Geomatics, Natural Hazards and Risk, vol. 10, no. 1, pp. 2185–2199, 2019. [Google Scholar]
- M. R. Arif, A. E. Afiuddin, and T. A. Ramadani, “Emission Dispersion Modelling of SO₂ Using Gaussian Dispersion Model (Case Study: Coal-Fired Power Plant Chimney in Probolinggo District)” ECOLAB: Journal of Environmental Science and Technology, vol. 14, no. 2, pp. 137–145, Nov. 2020, p-ISSN: 0216-0897, e-ISSN: 2502-6267. [Google Scholar]
- Aprilleria et al., “The Effect of Land Wind and Sea Breeze on Pollutant Dispersion in Jakarta Using WRF-Chem Model,” Research Report, Bogor Agricultural Institute, 2017. [Google Scholar]
- I. Bugdayci, O. Ugurlu, and F. Kunt, “Spatial Analysis of SO₂, PM₁₀, CO, NO₂, and O₃ Pollutants: The Case of Konya Province, Turkey,” Atmosphere, vol. 14, no. 3, p. 462, 2023. [Google Scholar]
- N. Emekwuru and O. Ejohwomu, “Temperature, Humidity and Air Pollution Relationships During Rainy and Dry Seasons in Lagos, Nigeria,” Climate, vol. 11, no. 5, p. 113, 2023. [Google Scholar]
- M. T. Ali, I. M. Rafizul, and Q. H. Bari, “Dynamics of Atmospheric Emissions and Meteorological Variables in Bangladesh from Pre-to Post-COVID-19 Lockdown,” Heliyon, vol. 10, no. 20, e39578, 2024. [Google Scholar]
- M. Fardella et al., “Analysis of Dispersion Patterns of Total Suspended Particulate with Variations in Time and Location in Limestone Mines,” Serambi Eng. J., vol. 8, no. 2, pp. 5304–5312, 2023. [Google Scholar]
- K. Masroor et al., “Spatial Modelling of PM₂.₅ Concentrations in Tehran Using Kriging and IDW Methods,” J. Air Pollut. Health, vol. 5, pp. 89–96, 2020. [Google Scholar]
- Q. Ding, Y. Wang, and D. Zhuang, “Comparison of Common Spatial Interpolation Methods to Analyze Toxic Elements in Mining Regions,” J. Environ. Manage., vol. 212, pp. 23–31, 2018. [Google Scholar]
- P. L. Ohlert, M. Bach, and L. Breuer, “Accuracy assessment of inverse distance weighting interpolation of groundwater nitrate concentrations in Bavaria (Germany),” Environmental Science and Pollution Research, vol. 30, pp. 9445–9455, 2023. doi: 10.1007/s11356-022-22670-0. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.