Atmospheric deposition of antimony in a typical mercury-antimony mining area, Shaanxi Province, Southwest China

Widespread mercurous [Hg(I)] species in mercury droplet impacted environments: Evidence from an abandoned Hg smelting plant in Xunyang, China

Mercury (Hg) emissions from Hg smelting (roasting HgS ores) and artisanal small-scale gold mining predominantly include elemental Hg, in either liquid [Hg(0)l] or gaseous [Hg(0)g] form. The oxidation of Hg(0) into Hg(I) is the first step during Hg(0) oxidation, which enables Hg to enter the food web. However, this oxidation process remains poorly understood, particularly in Hg(0)l/Hg(0)g-impacted environments. Herein, we show the widespread occurrence of Hg(I) in Hg(0)l/Hg(0)g-exposed environmental matrices near an abandoned Hg smelting plant in Xunyang, Shaanxi, China, including water, sediment, soil, plant, fish, and insect. This plant produced elemental Hg by roasting HgS ore, leaving Hg(0)l in the factory area after abandonment, which continuously released Hg(0)l/Hg(0)g into the surrounding environment. In Hg(0)-impacted water, Hg(I) was one of the primary Hg species, with an average concentration of 876 (not detected to 6109) ng L-1 and an average Hg(I) to total dissolved Hg ratio of 46% (0-92%), exhibiting a decrease with increasing distance from the plant. Elevated levels of Hg(I) were observed when the upstream sample was simultaneously exposed to Hg(0)l and Hg(0)g, arising from aqueous Hg(0)l oxidation and comproportionation between Hg(II) (mainly from Hg(0)l oxidation) and dissolved Hg(0) (i.e., Hg2+ + Hg0 → Hg22+). These findings highlight the impact of Hg(0) (as Hg(0)l and Hg(0)g) on the environment, emphasizing the comproportionation formation of Hg(I) in natural waters.

Distribution, risk evaluation, and source allocation of cesium and strontium in surface soil in a mining city

Radioactive nuclides cesium (Cs) and strontium (Sr) possess long half-lives, with 135Cs at approximately 2.3 million years and 87Sr at about 49 billion years. Their persistent accumulation can result in long-lasting radioactive contamination of soil ecosystems. This study employed geo-accumulation index (Igeo), pollution load index (PLI), potential ecological risk index (PEPI), health risk assessment model (HRA), and Monte Carlo simulation to evaluate the pollution and health risks of Cs and Sr in the surface soil of different functional areas in a typical mining city in China. Positive matrix factorization (PMF) model was used to elucidate the potential sources of Cs and Sr and the respective contribution rates of natural and anthropogenic sources. The findings indicate that soils in the mining area exhibited significantly higher levels of Cs and Sr pollution compared to smelting factory area, agricultural area, and urban residential area. Strontium did not pose a potential ecological risk in any studied functional area. The non-carcinogenic health risk of Sr to the human body in the study area was relatively low. Because of the lack of parameters for Cs, the potential ecological and human health risks of Cs was not calculated. The primary source of Cs in the soil was identified as the parent material from which the soil developed, while Sr mainly originated from associated contamination caused by mining activities. This research provides data for the control of Cs and Sr pollution in the surface soil of mining city.

Changes of heavy metal concentrations in farmland soils affected by non-ferrous metal smelting in China: A meta-analysis

Long-term human smelting activities have resulted in substantial heavy metals (HMs) pollution of farmland soils around smelting sites, and the safety of farmland products is critical for human health. The current study focuses on HMs in farmland soils surrounding a single smelter, therefore the impact of smelting on a national scale needs to be investigated further. This study was based on 116 papers and 1143 sets of relevant data for meta-analysis, and a hierarchical mixed-effects model was used to quantify the changes of HMs concentrations in farmland soils affected by non-ferrous metal smelting on a national scale, as well as their relationships with relevant explanatory variables in China. Results showed that: (i) non-ferrous metal smelting substantially increased farmland soils HMs concentrations (323%), with each HM concentration increasing in the following order: Cd (2753%) > Pb (562%) > Hg (455%) > Zn (228%) > Cu (158%) > As (107%) > Ni (52%); (ii) the highest increase of HMs in vegetable fields (361%), but not significant in comparison to other farmland categories, and the increase of Pb, Zn, Cu and As concentrations were significantly different in different types of smelting areas; (iii) the increase of Hg was significantly higher in the northern region than in the southern region, and the opposite increase of Cu; (iv) the soil depth from 0 to 40 cm was significantly affected by smelting, and the increase of multiple HMs were significantly positively correlated with soil pH and negatively correlated with distance; (v) the other explanatory variables (farmland category and soil organic matter) were not significantly related to the effect of smelting. The results can provide some reference for protecting and restoring farmland soils around smelting areas.

Atmospheric deposition and trajectories of antimony in Central Europe

Antimony (Sb) concentrations were measured in wet atmospheric deposition at 10 high-elevation sites in the Czech Republic (Central Europe) during three winter seasons (2009-2011). Soluble and insoluble Sb forms were quantified in snow (vertical deposition) and rime (horizontal deposition) on mountain summits located equidistantly near the Czech borders with Austria, Germany and Poland. The highest Sb concentrations were found in the soluble form in rime (0.47 μg L^-1), while the lowest Sb concentrations were those in the insoluble form in snow (0.017 μg L^-1). The estimated average Sb deposition rate in Central Europe amounted to 1.3. 10^-4 g m^-2 yr^-1. Most Sb was deposited in the soluble form in snow (7.9. 10^-5 g m^-2 yr^-1), followed by the soluble form in rime (3.5. 10^-5 g m^-2 yr^-1). The corresponding insoluble fraction contained less Sb, namely 1.2. 10^-5 g m^-2 yr^-1 in snow and 2.3. 10^-6 g m^-2 yr^-1 in rime. The average Sb deposition in Central Europe, measured at an altitude of 1000 m a.s.l., was by six orders of magnitude higher compared to Sb deposition in the Arctic (7. 10^-10 g m^-2 yr^-1), and by four orders of magnitude lower compared to Sb deposition in a Sb-Hg mining district in China (7 g m^-2 yr^-1). Using the HYSPLIT model, backward trajectories of air masses indicated that the Sb sources were predominantly situated in Upper and Lower Silesia.

Refining the diagnostics of non-point source metals pollution to urban lakes based on interaction normalized PMF coupled with Bayesian network

Spatiotemporal variability complicates source apportionment of metals in urban lakes, especially when rainfall drives urban non-point source pollution. As, Cd, Cr, Pb, Hg, Ag, Co, Cu, Fe, Mn, Ni, Sb, Sr and Zn concentrations in 648 water samples collected before and after rain in 6 urban lakes of Beijing, China were determined during 2013-2015. The response of metals concentrations after rain to the interaction between rainfall and antecedent dry days was significant. Metals concentrations were normalized pursuant to the interaction effect as the input of positive matrix factorization (PMF) to develop the interaction normalized-PMF (IN-PMF). Four primary pollution sources were diagnosed. Sediment release was considered to be the main source of Fe, Co and Ni independent of rainfall. Hg, As and some Cr associated with pesticides and fertilizers were likely to come from soil erosion and runoff from green space. It is probable that road runoff was the dominant source for heavy metals related to traffic emissions, including Pb, Cd, Cu, Sb, Mn and Zn. Cr, Sr and some Cu and Zn as key elements of rooftops can be regarded as from roof runoff. The IN-PMF lowered roof and road runoff contributions and raised the contribution of soil erosion from green space, with Pb, Sb, Cu, Zn, Cd and Mn increasing by 15.9%, 10.7%, 13.1%, 12.2%, 13.3% and 16.8%. The results shed more light on the stormwater runoff pollution mitigation on impervious surfaces and metals enrichment problems in infiltration soil on green space in the low impact development (LID) setting. The Bayesian network revealed the spatial variability of transport and fate of metal elements from land surfaces to urban lakes, supplementing the secondary pollution sources from different land use. This study will provide new insights for source apportionment of non-point source pollution under the background of sponge city construction.

Effects of mining on the potentially toxic elements in the surrounding soils in China: A meta-analysis

Previous studies about the effects of mining on the potentially toxic elements (PTEs) in the surrounding soils mainly focused on single or few mining areas. However, these studies couldn't comprehensively quantify the mining-induced variations of soil PTE concentrations at the national scale. Moreover, the quantitative relationships between the effects of mining on soil PTEs and some related factors remained unclear at the national scale. This study first conducted a literature survey for soil PTE data affected by mining in China. Then, the random-effects model in the meta-analysis was used to quantify mining-induced variations of soil PTE concentrations in the surrounding areas. Last, the single meta-regression was used to explore the relationships between the effects of mining on soil PTEs and the related factors at the national scale. Results showed that: (i) mining-induced increases of soil PTE concentrations followed the order: Cd (1017%) > Hg (319%) > Pb (291%) > Zn (176%) > Cu (129%) > As (92%) > Ni (23%); (ii) mining-induced increases of soil PTE concentrations in clay (531%), non-ferrous mine (188%), paddy field (212%), and Central South China (290%) were more than those in other soil textures, mine types, land-use types, and geographical divisions, respectively; (iii) the effects of mining on soil PTEs were negatively correlated with soil pH (Q_M = 29.76, p < 0.01) and positively correlated with soil organic carbon (Q_M = 28.54, p < 0.01) and mean annual precipitation (Q_M = 91.75, p < 0.01); (iv) the effects of mining overall decreased with the sampling year (Q_M = 35.01, p < 0.01) and showed latitudinal zonality (Q_M = 180.39, p < 0.01). The above results provided valuable information for soil PTE mitigation in the areas affected by mining in China.

Accumulation, regional distribution, and environmental effects of Sb in the largest Hg-Sb mine area in Qinling Orogen, China

In this study, knowledge gaps on Sb concentration in rocks, ores, tailings, soil, river water, sediments, and crops of mine areas were identified and discussed in terms of contamination levels, spatial distribution, and environmental effects. Accordingly, Xunyang Hg-Sb mine, the largest Hg-Sb deposit in China as research region in this study, field sampling and laboratory analysis were conducted. The results showed elevated concentrations of Sb in the soil, sediment, and river water. The X-ray diffraction analysis indicated that the main minerals of the rocks were quartz, dolomite, calcite, and margarite. Based on the TESCAN integrated mineral analyzer analysis, the main ore minerals in the Gongguan mine were dolomite (93.97%), cinnabar (2.50%), stibnite (2.48%), calcite (0.38%), and quartz (0.38%). The μ-XRF analysis indicated that Sb distribution was similar to those of S and O, instead of those of Hg and As. The clear spatial variation of Sb concentration in environmental media, mines, tailings, and settling ponds affected Sb accumulation. Actinobacteriota, Proteobacteria, Acidobacteriota, and Chloroflexi were the dominant phyla in the soil. Patescibacteria, Proteobacteria, and Bdellovibrionota were negatively correlated with Sb in the soil (p < 0.05). Exposure to Sb through maize grain and cabbage consumption poses serious non-carcinogenic health risk for residents. This work provides a scientific basis for the environmental quality assessment of Sb mine areas and development of applicable guidelines.

Evaluation of Fetal Exposures to Metals and Metalloids through Meconium Analyses: A Review

This paper surveys the existing scientific literature on metals concentrations in meconium. We examine some 32 papers that analyzed meconium for aluminum, arsenic, barium, calcium, chromium, copper, iron, lithium, magnesium, manganese, zinc, lead, mercury, manganese, molybdenum, nickel, phosphorus, lead, antimony, selenium, tin, vanadium, and zinc. Because of the lack of detail in the statistics it is not possible to do a rigorous meta-analysis. What stands out is that almost every study had subjects with seemingly large amounts of at least one of the metals. The significance of metals in meconium is not clear beyond an indication of exposure although some studies have correlated metals in meconium to a number of adverse outcomes. A number of outstanding questions have been identified that, if resolved, would greatly increase the utility of meconium analysis for assessment of long-term gestational metals exposures. Among these are questions of the developmental and long-term significance of metals detected in meconium, the kinetics and interactions among metals in maternal and fetal compartments and questions on best methods for meconium analyses.

Particulate matter concentration from open-cut coal mines: A hybrid machine learning estimation

Particulate matter (PM) emission is one of the leading environmental pollution issues associated with the coal mining industry. Before any control techniques can be employed, however, an accurate prediction of PM concentration is desired. Towards this end, this work aimed to provide an accurate estimation of PM concentration using a hybrid machine-learning technique. The proposed predictive model was based on the hybridazation of random forest (RF) model particle swarm optimization (PSO) for estimating PM concentration. The main objective of hybridazing the PSO was to tune the hyper-parameters of the RF model. The hybrid method was applied to PM data collected from an open-cut coal mine in northern China, the Haerwusu Coal Mine. The inputs selected were wind direction, wind speed, temperature, humidity, noise level and PM concentration at 5 min before. The outputs selected were the current concentration of PM_2.5 (particles with an aerodynamic diameter smaller than 2.5 μm), PM₁₀ (particles with an aerodynamic diameter smaller than 10 μm) and total suspended particulate (TSP). A detailed procedure for the implementation of the RF_PSO was presented and the predictive performance was analyzed. The results show that the RF_PSO could estimate PM concentration with a high degree of accuracy. The Pearson correlation coefficients among the average estimated and measured PM data were 0.91, 0.84 and 0.86 for the PM_2.5, PM₁₀ and TSP datasets, respectively. The relative importance analysis shows that the current PM concentration was mainly influenced by PM concentration at 5 min before, followed by humidity > temperature ≈ noise level > wind speed > wind direction. This study presents an efficient and accurate way to estimate PM concentration, which is fundamental to the assessment of the atmospheric quality risks emanating from open-cut mining and the design of dust removal techniques.

Soil migration of antimony and arsenic facilitated by colloids in lysimeter studies

The migration behaviors of antimony (Sb) and arsenic (As) and its influence factors have not been well understood among the different soils. In this study, we used lysimeter experiments to investigate the migration behavior of Sb compared with that of As in four representative soil materials from China. All the experiments processes and management measures were conducted to simulate the actual natural environmental conditions. Results indicated that after two years of leaching, the concentrations of Sb and As at the soil surface had decreased, whereas they increased in the deep soil profiles. In the polluted soil materials, 28.5%-39.2% of Sb and 0.4%-1.3% of As existed in the stable fraction, respectively. As and Sb levels were higher in the surface soil layer, and decreased with the soil depth in the different soil profiles. In soil leachate, Sb was mainly found in particle sizes smaller than 0.45 μm with the organic colloids, which had a peak in the spring and summer. On contrast, As was found in particle sizes larger than 0.45 μm with the inorganic colloids such as iron (Fe) and aluminum (Al) oxides. Pearson correlation results showed that the concentrations of Sb in the soil leaching solution and 0.45-μm-filltered solution were all positively correlated with Fe and Al. The results confirmed that Sb was combined with Fe and Al in the solution, and As posed a greater environmental risk than Sb during the leaching process. This study will help us to describe and predict As and Sb pollution in the soil environment, providing a basis for managing soil contaminated by these pollutants.

The alpine meadow around the mining areas on the Qinghai-Tibetan Plateau will degenerate as a result of the change of dominant species under the disturbance of open-pit mining

Mining is well-known as one of the most aggressive human disturbances leading to massive and irreversible damages to natural ecosystems. However, the influence mechanisms of open-pit mining on plant communities and soil properties of alpine meadow on the Qinghai-Tibetan plateau are not well understood. In this study, we used structural equation modeling (SEM) to study the influence mechanisms in the disturbed areas of the Qulong copper mine. Our results revealed that the soil parameters of alpine meadow have been significantly changed by mining activities. SEM results showed that Plantago depressa Willd. was more suitable for growing in current soil conditions due to its tolerance to heavy metals than other dominant species, which meant that it would substitute the current two dominant species (Kobresia myosuroides (Villars) Fiori and Blysmus sinocompressus Tang et Wang) in the future and become the most important dominant species in the study area. Unfortunately, the Shannon-Wiener index, Alatalo evenness index and M-Gordon stability index are relatively low in the plot with Plantago depressa Willd. as the dominant species. In a word, the fragile alpine meadow ecosystem may degenerate in the future due to plants and soil disturbed by mining activities. Further, eight targeted recommendations were proposed to protect alpine meadow on the Qinghai-Tibetan plateau.

Environmental pollution and geo-ecological risk assessment of the Qhorveh mining area in western Iran

In order to evaluate the effect of mining activity on the environment of the Qhorveh mining area in the west of Iran, the geological, ecological and environmental data, related to social development and regional economic status, were used. The geological data included seven sub-indices, such as vegetation coverage, land utilization type, and fault activity; ecological data, with two sub-indices, such as degree of ecological environment recovery; and finally, environmental data, with three sub-indices, such as soil and dust pollutions. These were selected based on the literature and expert opinion which were utilized for environmental pollution and geo-ecological (EPGE) risk assessment of the study site. Remote sensing (RS) image, field sampling, digital elevation map, and data retrieved from different government agencies were used to generate layers for the sub-indices in the geographic information system (GIS) environment. In addition, the analytical hierarchy process (AHP) method was used to determine the weight of sub-indices. Five levels consisting of best, good, middle, poor and worst were used to describe the EPGE risk assessment of the Qhorveh mining area. Results showed that worst and poor levels of EPGE risk are in the east and northeast of the study area where the gold and pumice mines are located while best and good levels of EPGE risk are in its center where the stone mines are located. According to the results of this research, the EPGE risk assessment of the Qhorveh mining area is affected by the environmental pollution index with its highest weight (0.3908). It can be concluded that the integration of the RS, GIS and AHP methods proposed in this study improved the evaluation quality of EPGE risk assessment.