Arsenic speciation and sorption in acid mine drainage and the polluted water of the Kosva river basin, Russia

Acid mine drainage (AMD) of the abandoned coal mines of the Kizelovsky coal basin (the Urals, Russia) is one of the worst natural disasters in the region. Acidic sulphate waters with a high content of metals freely flow into the surface water bodies. Arsenic, found in elevated concentrations in AMD, is an element of concern due to its potential toxicity to humans and animals. The aim of this work is determination of chemical speciation of inorganic arsenic in AMD as well as the surface water and groundwater affected by mine drainage, and assessment the natural removal of As from mine drainage due to adsorption on precipitated hydrous ferric oxide (HFO). Geochemical speciation (PHREEQC) revealed that arsenic occurs in all water samples as As(V). Surface complexation model shows that, HFO induced by the natural attenuation process may remove 46–85% of total arsenic in AMD and only 28% in polluted groundwater (on average).

Evaluation of the Influencing Factors of Using Underground Space of Abandoned Coal Mines to Store Hydrogen Based on the Improved ANP Method

Storage is currently a major obstacle to the promotion of hydrogen energy. Hydrogen storage in abandoned coal mines can achieve the effective use of underground space while meeting the growing demand for energy storage facilities, which can bring economic and environmental benefits. However, research in this area has been limited to the conceptual discussion stage, without establishing a scientific evaluation method for the potential of modifying and utilizing abandoned coal mine space. In this study, based on the analytic network process (ANP), the Apriori algorithm is introduced to mine the association rules for various influencing factors. First, the Apriori algorithm is applied to mine association rules between indicators, eliminate unnecessary influence relationships, simplify the network structure model, and optimize the ANP weight calculation results; second, the solution method of judgment matrix is improved with triangular fuzzy numbers, and the index weight is solved by fuzzy nine marks instead of the method of nine scale, which is convenient for experts to give the fuzzy scale while better reflecting the opinions of experts. Finally, the ANP algorithm is applied to rank the weights of the obtained influencing factors, discuss the main factors with higher weights, and analyze the feasibility of converting candidate coal mines into hydrogen storage facilities using the derived evaluation method in the case study. The evaluation methods and conclusions presented in this study provide analytical tools and a decision basis for analyzing the feasibility of converting underground space of abandoned coal mines into hydrogen storage facilities and assessing the economic indicators.

Decreasing methane emissions from China's coal mining with rebounded coal production

China is the world’s largest anthropogenic methane (CH4) emitter, with coal mine methane (CMM) as one of the main contributors. However, previous studies have not reach consensus on the magnitude and trend of China’s CMM emissions since 2010. Through distribution fitting and Monte Carlo methods, dynamic emission factors (EFs) of CMM at the province-level were derived with high confidence; along with the updated data on surface mining, abandoned coal mines, and methane utilization, we revealed that China’s annual CMM emissions were estimated at 20.11 Tg between 2010 and 2019 with a decline of 0.93 Tg yr-1. Although coal production was revived in 2017, we found that the growing trend of China’s CMM emissions since 2012 were curbed by the previously-overlooked factors including the growth of CMM utilization and coal production from surface mining, and decrease of emission factors driven by the closure of high CH4-content coal mines and a regional production shift to lower-emission areas.

Numerical simulation of flooding induced uplift for abandoned coal mines: simulation schemes and parameter sensitivity

Numerical simulation approaches have been widely applied to study mining induced subsidence, and they are potential methods to study the flooding induced uplift for abandoned mines. This paper gives an overview about different numerical approaches to simulate uplift induced by flooding abandoned underground mines, including three different hydraulic conditions, considering both unconfined and confined water conditions. Four basic simulation schemes using 1-dimensional rock column models verified by analytical solutions demonstrate these procedures. The results reveal that flooding induced uplift is mainly related to the pore pressure in the mine goaf. The parameter study documents that height and stiffness of the mine goaf have the strongest influence on maximum surface uplift.

Lost but Not Forgotten: Identifying Unmapped and Unlisted Environmental Hazards including Abandoned Mines

Environmental databases play an essential role in the management of land and communities, including mapping and monitoring environmental hazards over time (i.e., abandoned mines). Over the last century, mines have closed for many reasons, but there has been no comprehensive database of the locations of closed and abandoned mine sites kept for many regions of the world. As such, the locations of many mines have been lost from public knowledge, with no way for managers to assess the risks of land and water contamination, as well as subsidence. To address this knowledge gap, we present an integrated framework for identifying abandoned mine sites using a combination of satellite imagery, historical records, geographic evidence, and local knowledge. We tested this framework within the Newcastle, Illawarra, and Lithgow regions of NSW, Australia. We identified 61 abandoned coal mines which are currently unaccounted for in mine registries, with 56% of all mines in the Newcastle region being unmarked (N = 32), 36% in the Illawarra region (N = 22), and 20% in the Lithgow region (N = 7). These findings demonstrate that our framework has promising utility in identifying historic and unmarked environmental hazards in both national and international contexts.

Passive treatment test of acid mine drainage from an abandoned coal mine in Kaili Guizhou, China

Discharge of acid mine drainage (AMD) from abandoned coal mines of the YuDong catchment in Kaili City, Guizhou Province, China, has severely damaged local ecological environments. In this study, a laboratory-scale dispersed alkaline substrate (DAS) was studied for the treatment of simulated AMD. The experimental conditions and reaction mechanisms were preliminarily explored. The treatment effect and variation law of vertical effluent water quality of the experimental conditions were thoroughly analysed. The results indicated that small-sized limestone (diameter 5–7 mm) having a 20:1 mixture ratio with shavings and minimum HRT of 20 hours result in increasing effluent pH from 3.5 to 6.6, achieving 66.2% and 99.1% removal of Fe and Al, respectively. There were obvious differences in each reaction layer for the removal of various pollutants from AMD along the depth by DAS, the main reaction zone was first 20–30 cm of reaction column. The removal process of metal ions and sulfate was accompanied by bio-mineralization reaction. This test provided a valuable support for the local practical engineering applications, enriched the AMD processing technology experimental cases, and provided reference for the treatment technology of similar polluted areas. HIGHLIGHT A dispersed alkaline substrate was designed to treat the acid mine drainage from abandoned coal mines of YuDong valley, which provides a reference for the further design of site device and other similar contaminated areas. Combining the physical and chemical parameters of the effluent, mineralogical characterization of the filler along with the microbial diversity of the system, the mechanism of DAS treatment of AMD was analyzed.