Contemporary Biological Methods of Mine Reclamation in the Kemerovo Region – Kuzbass

Introduction. Coal mining is the main source of anthropogenic impact on the landscapes of the Kemerovo Region – Kuzbass. The current mine reclamation rate lags far behind the annual increase in disturbed lands. A reclamation fund can be a perfect solution to this relevant issue. The present research objective was to analyze and structure the available data on the anthropogenic impact of coal mining in Kuzbass. The article reviews new effic ient methods of reclamation and resoiling. Study objects and methods. The study featured ten years of research publications that were registered in the PubMed database of the National Center for Biotechnology Information (USA), Elsevier (Scopus, ScienceDirect), the Web of Science, and the Russian Electronic Library (eLibrary.ru). Results and discussion. The research revealed the following Kuzbass districts that experience the greatest mining impact: Novokuznetsk, Prokopyevsk, Kemerovo, Belovo, and Leninsk-Kuznetskiy. The authors also identified the most common pollutants associated with coal mining. Polycyclic aromatic hydrocarbons (PAHs) appeared to be the most dangerous pollutants: as waste coal burns, these substances cover considerable distances with the wind. Biodegradation seems to be the optimal solution because PAHs are known to be carcinogenic, and most mine tips are located near settlements. The article also features mine reclamation laws and introduces a list of plants with a high absorption capacity recommended for biological reclamation, as well as microorganisms and their consortia used for bioremediation. Conclusion. The authors identified the most promising methods of mine reclamation in the Kemerovo region, i.e. bioremediation with pollutant-binding microbial consortia and plants.

The influence of fast-growing species composition on natural regeneration of coal mine reclamation

Natural regeneration on mine reclamation can be an indicator of reclamation success. Enterolobium cyclocarpum, Samanea saman, Senna siamea, and Paraserianthes falcataria are mostly planted fast-growing species at the beginning of reclamation. Those species bind and enrich nitrogen to improve the natural regeneration of ex-mined land. This research aims to determine fast-growing species and the growth rate of natural regeneration development in the ex-mined site. The research was conducted in mine reclamation areas with different ages: 1 (125.14 ha), 4 (323.76 ha), 6 (199.44 ha), 9 (285.18 ha), and 11-year-old plantation (75.39 ha). The statistical analysis of Multivariate Analysis showed that biological species were mostly grouped with P. falcataria than E. cyclocarpum and S. siamea in the 11-year-old plantation area as well as in the 9-year-old plantation area. Most natural species were grouped with C. cyclocarpum rather than S. saman and S. siamea in a 6-year-old plantation area. In contrast, the biological species had no groups with E. cyclocarpum and S. siamea as fast-growing species in the 1-year-old plantation area. Generally, the most dominant planted fast-growing species were E. cyclocarpum (with the mean total number ± standard deviation, (35 ± 17.1)) and P. falcataria (28 ± 8.3). The number of natural regeneration species and individuals in areas dominated by P. falcataria (5 ± 1.7 and 25 ± 10.5) was greater than in areas with predominance of E. cyclocarpum (4 ± 2.6 and 11 ± 4.8). Thus, species selection is necessary to increase natural regeneration. However, further research is required to measure the tolerability of fast-growing species on other natural regeneration species.

The possibility of reclamation criteria success in Indonesia: soil condition, vegetation structure and species composition

There are two regulations for mine reclamation success in the forestry area in Indonesia, namely Minister of Forestry Regulation No. P.60/Menhut-II/2009 and Minister of Energy and Mineral Resources Decree No. 1827.K/30/MEM/2018. Both regulations rule vegetation and soil success. This study aims to analyse criteria parameters from both regulations in the mine reclamation and compare them to the surrounding secondary natural forest (SNF). This study was conducted in 6 six types of mine reclamation stand structures: 1, 4, 6, 9, 11-year-old plantation and SNF using 1 hectare of the circular plot each (total 6 ha). Soil samples were collected from 40 cm depth to analyse physical, biological and chemical conditions. Mine reclamation areas had almost similar physical, biological and chemical soil conditions with SNF. Nevertheless, due to the potential acid-forming (PAF) material from overburden, the 1-year-old plantation had pH = 3.23-3.27. The highest diversity index and the number of species and families in all reclamation areas were H’ = 1.82 (11-year-old); 14 species (9-year-old); and 11 families (9-year-old), comparing with SNF were H’ = 3.48; 67 species, and 31 families. Conversely, vegetation structure parameters in mine reclamation areas were higher than SNF (diameter at height breast (DBH; 1.3 m) = 28.42 cm; tree density = 469/ha; basal area = 35.04 m2/ha; and total height = 16.85 m). Compared to the SNF, vegetation structure and soil conditions are mostly possible for mine reclamation success. Still, species composition needs to be considered further as a standard interval to meet the criteria.

Land Cover Classification Based on UAV Photogrammetry and Deep Learning for Supporting Mine Reclamation: A Case Study of Mae Moh Mine in Lampang Province, Thailand

Detailed, accurate, and frequent mapping of land cover are the prerequisite regarding areas of reclaimed mines and the development of sustainable project-level for goals. Mine reclamation is essential as the extractive organizations are bounded by-laws that have been established by stakeholders to ensure that the mined areas are properly restored. As databases at the mines area become outdated, an automated process of upgrading is needed. Currently, there are only few studies regarding mine reclamation which has less potential of land cover classification using Unmanned Aerial Vehicle (UAV) photogrammetry with Deep learning (DL). This paper aims to employ the classification of land cover for monitoring mine reclamation using DL from the UAV photogrammetric results. The land cover was classified into five classes, comprising: 1) trees, 2) shadow, 3) grassland, 4) barren land, and 5) others (as undefined). To perform the classification using DL, the UAV photogrammetric results, orthophoto and Digital Surface Model (DSM) were used. The effectiveness of both results was examined to verify the potential of land cover classification. The experimental findings showed that effective results for land cover classification over test area were obtained by DL through the combination of orthophoto and DSM with an Overall Accuracy of 0.904, Average Accuracy of 0.681, and Kappa index of 0.937. Our experiments showed that land cover classification from combination orthophoto with DSM was more precise than using orthophoto only. This research provides framework for conducting an analytical process, a UAV approach with DL based evaluation of mine reclamation with safety, also providing a time series information for future efforts to evaluate reclamation. The procedure resulting from this research constitutes approach that is intended to be adopted by government organizations and private corporations so that it will provide accurate evaluation of reclamation in timely manner with reasonable budget.

SOIL CHARACTERISTICS AND MICROBIAL RESPONSES IN POST-MINE RECLAMATION AREAS IN A TYPICAL RESOURCE-BASED CITY, CHINA

Mining activities worldwide have resulted in soil nutrient loss, which pose risks to crop and environmental health. We investigated the effects of post-mine reclamation activities on soil physicochemical properties and microbial communities based on 16S rRNA sequencing and the further statistical analysis in the coal base in Peixian city, China. The results revealed significant differences in soil microbial relative abundance between reclamation and reference soils. Proteobacteria was the most abundant phyla in all seven mine sites regardless of reclamation age while considerable differences were found in microbial community structure at other levels among different sites. Notebly, Gammaproteobacteria, member of the phylum Proteobacteria, had relatively high abundance in most sites. Furthermore, Kendall’s tau-b correlation heatmap revealed that potentially toxic elements and other physicochemical properties play vital roles in microbial community composition.

Growth of Shorea Leprosula Seedlings Prepared in Combo Nursery Technique to Support Mine Reclamation

Combo nursery technique is a technique where seedlings/cuttings of Shorea leprosula, Gliricidia sepium, and Brachiaria decumbens grass were planted in one polybag to support mining reclamation. To reduce competition effects among the three species, optimum media and size of polybag need to be investigated. The objective of this experiment is to analyse the effect of size of polybag and media composition on the growth of S. leprosula, G. sepium, and B. decumbens grass in the combo nursery technique. The experiment used Randomised Complete Design in Factorial with two factors, i.e. media compositions (soil : compost (2 : 1, v/v), (1 : 1, v/v), (1 : 2, v/v), and soil : compost : rice husk (7:3:1, v/v/v); and size of polybag (15 x 20 cm, 20 x 20 cm, dan 25 x 25 cm). Each treatment had four replications, and each replication consisted of four polybags. The results showed no significant interaction effects between the composition of media and the size of polybag; however, media compositions of soil: compost (1:1) and (1:2), and the sizes of polybag 20 x 20 cm and 25 x 25 cm significantly eliminated competition and significantly increased the growth of S. leprosula and the number of tiller of B. decumbens grass.