Uncertainty Quantification of Contaminated Soil Volume with Deep Neural Networks and Predictive Models
Author:
Funder
Ford Motor Company
Publisher
Springer Science and Business Media LLC
Subject
General Environmental Science
Link
https://link.springer.com/content/pdf/10.1007/s10666-023-09924-y.pdf
Reference59 articles.
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2. Demougeot-Renard, H., & De Fouquet, C. (2004). Geostatistical Approach for Assessing Soil Volumes Requiring Remediation: Validation Using Lead-Polluted Soils underlying a Former Smelting Works. Environmental Science & Technology, 38(19), 5120–5126. https://doi.org/10.1021/es0351084
3. Schädler, S., Morio, M., Bartke, S., Rohr-Zänker, R., & Finkel, M. (2011). Designing sustainable and economically attractive brownfield revitalization options using an integrated assessment model. Journal of Environmental Management, 92(3), 827–837. https://doi.org/10.1016/j.jenvman.2010.10.026
4. Chen, Z., Huang, G., Chan, C., Geng, L., & Xia, J. (2003). Development of an Expert System for the Remediation of Petroleum-Contaminated Sites. Environmental Modeling & Assessment, 8(4), 323–334. https://doi.org/10.1023/B:ENMO.0000004584.53505.15
5. Carlon, C., Pizzol, L., Critto, A., & Marcomini, A. (2008). A spatial risk assessment methodology to support the remediation of contaminated land. Environment International, 34(3), 397–411. https://doi.org/10.1016/j.envint.2007.09.009
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