The evaluation of sewage sludge as soil amendment for post-mining land rehabilitation

The lack of organic matter is one of the key difficulties in the reclamation of technogenically disturbed lands formed in the mineral deposits’ development areas. As a solution, it is proposed to reclaim post-mining lands with the use of organic soil additive — sewage sludge of the pulp and paper industry. The article presents the results of the primary assessment of soil substrates improved with pulp and paper mill sewage sludge and peat moss (in comparison) by analysing the effect on the vegetation cover (pot experiments under controlled microclimate conditions). Additionally, this article presents primary methods for assessing plant growth and development and digital image analysis as a non-destructive sampling method for assessing plant growth (biomass).

Keywords: Amendment, Biomass, Green cover, Image analysis, Leaf area index, Technosols.
For citation:

Rudzisha E., Petrova T. A. The evaluation of sewage sludge as soil amendment for post-mining land rehabilitation. MIAB. Mining Inf. Anal. Bull. 2022;(10-2):127—134. [In Russ]. DOI: 10.25018/0236_1493_2022_102_0_127.

Acknowledgements:
Issue number: 10
Year: 2022
Page number: 127-134
ISBN: 0236-1493
UDK: 622
DOI: 10.25018/0236_1493_2022_102_0_127
Article receipt date: 20.03.2022
Date of review receipt: 15.07.2022
Date of the editorial board′s decision on the article′s publishing: 10.09.2022
About authors:

Rudzisha E.1, Graduate Student, e-mail: rudzisha@gmail.com, ORCID ID: 0000-0002-6728-4576;
Petrova T. A.1, Cand. Sci. (Eng.), Assistant Professor, e-mail: Petrova_TA@pers.spmi.ru ORCID ID: 0000-0001-5914-6395;
1 Saint-Petersburg Mining University, 199106, Saint-Petersburg, Russia.

 

For contacts:

Rudzisha E., rudzisha@gmail.com.

Bibliography:

1. The state (national) report on the status and use of lands of the Russian Federation in 2019. Moscow, 2020.

2. Rybak J., Khayrutdinov, M. M., Kuziev, D. A., Kongar-Syuryun, Ch. B., Babyr, N. V. (2022). Prediction of the geomechanical state of the rock mass when mining salt deposits with stowing. Journal of Mining Institute, 253, 61−70. DOI: 10.31897/PMI.2022.2.

3. Alekseenko, V. A., Bech, J., Alekseenko, A. V., Shvydkaya, N. V., Roca, N. (2018). Environmental impact of disposal of coal mining wastes on soils and plants in Rostov Oblast, Russia. J. Geochemical Explorer, 184, 261−270. DOI:10.1016/j.gexplo.2017.06.003.

4. Rybak, J., Kongar-Syuryun, C., Tyulyaeva, Y., Khayrutdinov, A. M. (2021). Creation of backfill materials based on industrial waste. Minerals, 11(7), 739. DOI: 10.3390/ min11070739.

5. Nash, W. L., Daniels, W. L., Haering, K. C., Burger, J. A., Zipper, C. E. (2016). Longterm Effects of Rock Type on Appalachian Coal Mine Soil Properties. J. Environ. Qual, 45(5), 1597−1606. DOI: 10.2134/jeq2015.10.0540.

6. Alekseenko, A. V., Drebenstedt, C, Bech, J. (2022). Assessment and abatement of the eco-risk caused by mine spoils in the dry subtropical climate. Environmental Geochemistry and Health, 44(6), 1581−1603. DOI:10.1007/s10653−021−00885−3.

7. Halecki, W., Klatka, S. (2021). Application of Soil Productivity Index after Eight Years of Soil Reclamation with Sewage Sludge Amendments. Environmental Management, 67(15), 822−832. DOI:10.1007/s00267−020−01422−1.

8. Khordan, M. M., Bek, D., Garsiya-Sanches, E., Garsiya-Orenes, F. (2016). Bulk density and aggregate stability assays in percolation columns. Journal of Mining Institute, 222, 877. DOI: 10.18454/pmi.2016.6.877.

9. Kelessidis, A., Stasinakis, A. S. (2012). Comparative study of the methods used for treatment and final disposal of sewage sludge in European countries. Waste Management, 32 (6), 1186−1195. DOI:10.1016/j.wasman.2012.01.012.

10. Smirnov, Y. D., Suchkova, M. V. (2019). Beneficial use of sewage sludge incineration ash in the national economy. Water and ecology: problems and solutions, 3(79), 16–25. DOI: 10.23968/2305−3488.2019.24.3.16−25.

11. Matveeva, V. A., Smirnov, Y. D., Suchkov, D. V. (2021). Industrial processing of phosphogypsum into organo-mineral fertilizer. Environmental Geochemistry and Health, 2, 2−13. DOI:10.1007/S10653−021−00988-X.

12. Jin, X. (2021). High-Throughput Estimation of Crop Traits: A Review of Ground and Aerial Phenotyping Platforms. IEEE Geoscience and Remote Sensing Magazine, 9 (1), 200−231. DOI: 10.1109/MGRS.2020.2998816.

13. Pashkevich, M. A., Petrova, T. A., Rudzisha, E. (2019). Lignin sludge application for forest land reclamation: feasibility assessment. Journal of Mining Institute, 235, 106. DOI: 10.31897/pmi.2019.1.106.

14. Elsayed, S., Barmeier, G., Schmidhalter, U. (2018). Passive Reflectance Sensing and Digital Image Analysis Allows for Assessing the Biomass and Nitrogen Status of Wheat in Early and Late Tillering Stages, 9, 1−15. DOI: 10.3389/fpls.2018.01478.

15. Sunoj, S., McRoberts, K. C., Benson, M., Ketterings, Q. M. (2021). Digital image analysis estimates of biomass, carbon, and nitrogen uptake of winter cereal cover crops. Computers and Electronics in Agriculture, 184, 106093. DOI: 10.1016/j.compag.2021.106093.

16. Bumgarner, N. R., Miller, W. S., Kleinhenz, M. D. (2012). Digital image analysis to supplement direct measures of lettuce biomass. Horttechnology, 22 (4), 547−555. DOI: 10.21273/HORTTECH.22.4.547.

17. Laxman, R. H., Hemamalini, P., Bhatt, R. M., Sadashiva, A. T. (2018). Non-invasive quantification of tomato (Solanum Lycopersicum L.) plant biomass through digital imaging using phenomics platform. Indian Journal of Plant Physiology, 23(2), 369−375. DOI: 10.1007/s40502−018−0374−8.

18. Korotaeva A. E., Pashkevich M. A. Spectrum survey data application in ecological monitoring of aquatic vegetation. MIAB. Mining Inf. Anal. Bull. 2021;(5–2):231-244. [In Russ]. DOI: 10.25018/0236_1493_2021_52_0_231.

19. Tikhonova S. A., Struchkova G. P., Kapitonova T. A. Manmade pollution assessment in water bodies in Yakutia using color response curves and satellite images. MIAB. Mining Inf. Anal. Bull. 2021;(12–1):213-222. [In Russ]. DOI: 10.25018/0236_1493_2021_121_0_213.

20. Chianucci, F., Lucibelli, A., Dell’Abate, M. T. (2018). Estimation of ground canopy cover in agricultural crops using downward-looking photography. Biosystems Engineering, 169, 209−216. DOI:10.1016/j.biosystemseng.2018.02.012.

21. Xu, D., Pu, Y., Guo, X. (2020). A Semi-Automated Method to Extract Green and Non-Photosynthetic Vegetation Cover from RGB Images in Mixed Grasslands. Sensors, 20 (23), 6870. DOI:10.3390/s20236870.

22. Xiong, Y., West, C. P., Brown, C. P., Green, P. E. (2019). Digital Image Analysis of Old World Bluestem Cover to Estimate Canopy Development. Agron. J. 111, 1247−1253. DOI:/10.2134/agronj2018.08.0502.

23. Dinalankara, S. (2018). Vision-Based Automated Biomass Estimation of Fronds of Salvinia molesta. 2018 IEEE International Conference on Information and Automation for Sustainability (ICIAfS), 1−6. DOI:10.1109/ICIAFS.2018.8913395.

24. Hu, B., Bennett, M. A., Kleinhenz, M. D. (2016). A new method to estimate vegetable seedling Vigor, piloted with tomato, for use in grafting and other contexts. Horttechnology 26, 767−775. DOI: 10.1109/ICIAFS.2018.8913395.

25. Huang, W., Su, X., Ratkowsky, D. A., Niklas, K. J., Gielis, J., Shi, P. (2019). The scaling relationships of leaf biomass vs. leaf surface area of 12 bamboo species. Global Ecology and Conservation, 20. DOI:10.1016/j.gecco.2019.e00793.

Our partners

Подписка на рассылку

Раз в месяц Вы будете получать информацию о новом номере журнала, новых книгах издательства, а также о конференциях, форумах и других профессиональных мероприятиях.