Quantifying the impact of factors on soil available arsenic using machine learning.

Arsenic (As) can accumulate in edible plant parts and thus pose a serious threat to human health. Identifying the contributions of various factors to soil available As is crucial for evaluating environmental risks. However, research quantitatively assessing the importance of soil properties on available As is scarce. In this study, we utilized 442 datasets covering total As, available As, and properties of farmland soils. The five machine learning models were employed to predict soil available As content, and the model with the best predictive performance was selected to calculate the importance of soil properties on available As and interpret the model results. The Random Forest model exhibited the best predictive performance, with R2 for the test set of dryland and paddy fields being 0.83 and 0.82 respectively, while also outperforming other machine learning models in terms of accuracy. Concurrently, evaluating the contribution of soil properties to soil available As revealed that increases in soil total arsenic, pH, organic matter (OM), and cation exchange capacity (CEC) led to higher soil available As content. Among these factors, soil total As had the greatest impact, followed by CEC. The influence of pH on soil available As was greater in dryland compared to OM, while in paddy fields, it was smaller than OM (p < 0.01). Sensitivity analysis results indicated that reducing soil total As content had the greatest effect on available As. In both dryland and paddy field soils, reducing soil total As had the most pronounced effect on available As, leading to reductions of 10.09% and 8.48%, respectively. Therefore, prioritizing the regulation of soil total As and CEC is crucial in As contamination management practices to alter As availability in farmland soils.

Potential in treating arsenic-contaminated water of the biochars produced from hyperaccumulator Pteris vittata and its environmental safety.

In this study, biochar derived from pyrolyzed aboveground parts of Pteris vittata (P. vittata) was modified with iron(Fe) and applied to aqueous solutions containing arsenite (As[III]) or arsenate (As[V]) for remediation purposes. The adsorption efficiency, biochar characteristics pre- and post-adsorption, microscopic As distribution, and As morphology were analyzed. Additionally, the potential and leaching safety of P. vittata biochar for As-contaminated water remediation were evaluated. Results indicated that P. vittata biochar contained oxygen-containing functional groups and aromatic structures. Modification with Fe increased specific surface area and total pore volume. Unmodified P. vittata biochar displayed low adsorption of As(III) and As(V), while Fe modification significantly enhanced As adsorption capacity and reduced As leaching by 69%-89%. Maximum adsorption capacities of Fe-modified P. vittata biochar for As(III) and As(V) were 7.64 and 10.2 mg/g, respectively, as determined by Langmuir fitting. The superior adsorption efficiency of As(V) over As(III) by Fe-modified biochar was attributed to better electrostatic interaction with the adsorbent. Analysis revealed similar As species in P. vittata biochar before and after adsorption, with a significant presence of As(III). Remarkably, As in P. vittata remained highly stable during pyrolysis and adsorption, possibly due to strong Fe-As binding. Fe-modified P. vittata biochar shows promise for application, but further pretreatment may be necessary to achieve optimal results.

Coking exhaust contributes to airborne particulate matter in the Beijing-Tianjin-Hebei region.

Coking was regarded as a predominant source of air pollution. Despite the adoption of more environmentally friendly equipment, whether the coking enterprises in the Beijing-Tianjin-Hebei (BTH) region are still causing regional air pollution is worthy of study, which is essential for the control of coking enterprises in this area. To improve the prediction accuracy of large-scale air pollutant distribution, the air particle distribution in the BTH region was simulated via land use regression (LUR) combined with Bayesian maximum entropy (BME); then, the distribution was correlated with the exhaust gas emitted from coking enterprises. Results indicated that the R2 of the "LUR + BME" method reached 0.95, higher than 0.82 using LUR alone. The air quality distribution presented a pattern of "low in the northern mountains and high in the southern plains", similar to the distribution of coking enterprises in BTH region. A significant correlation was found between exhaust emissions from coking enterprises and air quality in the BTH region, confirming the contribution of coking emissions to air pollution in this region, and the necessity to continue the strict control on coking enterprises in BTH area.

An evidence-based guideline on treating lumbar disc herniation with traditional Chinese medicine.

BACKGROUND: Lumbar disc herniation (LDH), as one of the most common causes of lower back pain, imposes a heavy economic burden on patients and society. Conservative management is the first-line choice for the majority of LDH patients. Traditional Chinese medicine (TCM) is an important part of conservative treatment and has attracted more and more international attention. STUDY DESIGN: Evidence-based guideline. METHODS: We formed a guideline panel of multidisciplinary experts. The clinical questions were identified on the basis of a systematic literature search and a consensus meeting. We searched the literature for direct evidence on the management of LDH and assessed its certainty-generated recommendations using the grading of recommendations, assessment, development, and evaluation (GRADE) approach. RESULTS: The guideline panel made 20 recommendations, which covered the use of Shentong Zhuyu decoction, Shenzhuo decoction, Simiao San decoction, Duhuo Jisheng decoction, Yaobitong capsule, Yaotongning capsule, Osteoking, manual therapy, needle knife, manual acupuncture, electroacupuncture, Chinese exercise techniques (Tai Chi, Baduanjin, or Yijinjing), and integrative medicine, such as combined non-steroidal anti-inflammatory drugs, neural nutrition, and traction. Recommendations were either strong or weak, or in the form of ungraded consensus-based statement. CONCLUSION: This is the first LDH treatment guideline for TCM and integrative medicine with a systematic search, synthesis of evidence, and using the GRADE method to rate the quality of evidence. We hope these recommendations can help support healthcare workers caring for LDH patients.

Intercropping of Pteris vittata and maize on multimetal contaminated soil can achieve remediation and safe agricultural production.

Soil contamination by multimetals is widespread. Hyperaccumulator-crop intercropping has been confirmed to be an effective method for arsenic (As)- or cadmium (Cd)-contaminated soil that can achieve soil cleanup and agricultural production. However, the influencing factors and response of hyperaccumulator-crop intercropping to multimetal-contaminated soil are still unclear. In this study, intercropping of the As hyperaccumulator Pteris vittata and maize was conducted on two typical types of multimetal-contaminated soil, namely, Soil A contaminated by As, Cd, and lead (Pb) and Soil B contaminated by As, Cd, and chromium (Cr). Intercropping reduced As, Cd, and Pb in the maize grains by 60 %, 66.7 %, and 20.4 %, respectively. The concentrations of As, Cd, Pb, and Cr in P. vittata increased by 314 %, 300 %, 447.3 %, and 232.6 %, respectively, relative to their concentrations in the monoculture plants. Two soils with different levels of contamination showed that higher heavy metal content might diminish the ability of intercropping to reduce soil heavy metal risk. No notable difference in soil microbial diversity was found between the intercropped and monocultured plants. The composition of microbial communities of intercropping groups were more similar to those of monoculture P. vittata on two different soils (Soils A and B). An imbalance between the amount of As taken up by the plants and the reduction in As in the soil was observed, and this imbalance may be related to watering, As leaching, and heterogeneity of soil As distribution. Reducing the risk resulting from As leaching and enhancing the efficiency of phytoextraction should be emphasized in remediation practices.

Identifying driving factors of soil heavy metal at the mining area scale: Methods and practice.

Identifying driving factors is of great significance for understanding the mechanisms of soil pollution. In this study, a data processing method for driving factors was analyzed to explore the genesis of Arsenic (As) pollution in mining areas. The wind field that affects the atmospheric diffusion of pollutants was simulated using the standard k-ε model. Machine learning and GeoDetector methods were used to identify the primary driving factors. The results showed that the prediction performances of the three machine learning models were improved after data processing. The R2 values of random forest (RF), support vector machine, and artificial neural network increased from 0.45, 0.69, and 0.24 to 0.55, 0.76, and 0.52, respectively. The importance of wind increased from 20.85% to 26.22%. The importance of distance to the smelter plant decreased from 43.26% to 33.19% in the RF model. The wind's driving force (q value) increased from 0.057 to 0.235 in GeoDetector. The average value of historical atmospheric dust reached 534.98 mg/kg, indicating that atmospheric deposition was an important pathway for As pollution. The outcome of this study can provide a direction to clarify the mechanisms responsible for soil pollution at the mining area scale.

Research advances in mechanisms of arsenic hyperaccumulation of Pteris vittata: Perspectives from plant physiology, molecular biology, and phylogeny.

Pteris vittata, as the firstly discovered arsenic (As) hyperaccumulator, has great application value in As-contaminated soil remediation. Currently, the genes involved in As hyperaccumulation in P. vittata have been mined continuously, while they have not been used in practice to enhance phytoremediation efficiency. Aiming to better assist the practice of phytoremediation, this review collects 130 studies to clarify the progress in research into the As hyperaccumulation process in P. vittata from multiple perspectives. Antioxidant defense, rhizosphere activities, vacuolar sequestration, and As efflux are important physiological activities involved in As hyperaccumulation in P. vittata. Among related 19 genes, PHT, TIP, ACR3, ACR2 and HAC family genes play essential roles in arsenate (AsⅤ) transport, arsenite (AsⅢ) transport, vacuole sequestration of AsⅢ, and the reduction of AsⅤ to AsⅢ, respectively. Gene ontology enrichment analysis indicated it is necessary to further explore genes that can bind to related ions, with transport activity, or with function of transmembrane transport. Phylogeny analysis results implied ACR2, HAC and ACR3 family genes with rapid evolutionary rate may be the decisive factors for P. vittata as an As hyperaccumulator. A deeper understanding of the As hyperaccumulation network and key gene components could provide useful tools for further bio-engineered phytoremediation.

Hair-biomonitoring assessment of rare-earth-element exposure in residents of the largest rare-earth mining and smelting area of China.

The long-term and large-scale mining of rare earth minerals may lead to an accumulation of rare earth elements (REEs) in the environment, posing potential health risks to residents. We collected scalp hair (n = 254) from residents of a smelting area, a mining area, and a reference area to clarify human exposure to REEs. The contents of 15 REEs investigated in human hair samples were notably higher in the mining and smelting areas than in the reference area. Significant differences between some REEs were observed between the mining and smelting areas, for instance, cerium (Ce), dysprosium, and praseodymium. In the study areas, exposure to different sources of REEs may be one of the factors that contributed to the variations of REE correlations and clusters in human hair. Furthermore, in the smelting area, Ce contents in hair decreased with increasing age of children. However, Ce contents in the hair of adults increased with age. In contrast, Ce accumulation continuously increased in the reference area residents' hair with age. Regression results indicated that age and location were more important than sex when considering the influence on REE accumulation in residents' hair. The results of this study may help policymakers to implement guidelines to alleviate residents' exposure to REE in mining and smelting areas.

Phytoextraction of As by Pteris vittata L. assisted with municipal sewage sludge compost and associated mechanism.

Pteris vittata L. (PV), an arsenic (As) hyperaccumulator, has a potential to extract As from As-polluted soils. Since available As in soils can be taken up by PV, As fraction variation associated rhizosphere environmental characteristics caused by municipal sewage sludge compost (MSSC) could provide possible to strengthen As phytoextraction by PV. In this study, the mechanism of phytoextraction of PV aided by MSSC was revealed from aspect of environmental characteristics of rhizosphere soils and physiological properties of PV. The effect of MSSC on available As in soils was investigated by soil incubation experiment. Furthermore, the influences of MSSC on enzymes activities, communities of soil bacteria and fungi, As concentrations, and As fraction in rhizosphere soils of PV were explored, and then the biomass and As accumulation of PV were examined by greenhouse pot experiments. After 90 days, available As in soil incubation experiment significantly increased by 32.63 %, 43.05 %, and 36.84 % under 2 %, 5 %, and 10 % treatment, respectively, compared with control treatment. Moreover, As concentrations in rhizosphere soils of PV under 2 %, 5 %, and 10 % treatment decreased by 4.62 %, 8.68 %, and 7.47 %, respectively, compared with control treatment. The available nutrients and enzyme activities in rhizosphere soils of PVs were improved under the MSSC treatment. Affected by MSSC, the dominant phylum and genus for both bacterial and fungal communities didn't change, but their relative abundance increased. Additionally, MSSC significantly increased biomass of PV with corresponding mean ranging from 2.82 to 3.42 g in shoot and 1.82 to 1.89 g in root, respectively. And the concentrations of As in shoot and root of PV treated by MSSC increased by 29.04 %-144.7 % and 26.34 %-81.78 %, respectively, in relative to control. The results of this study provided a basis for MSSC-strengthened phytoremediation for As-polluted soils.

The influence of diverse fertilizer regimes on the phytoremediation potential of Pteris vittata in an abandoned nonferrous metallic mining site.

Organic waste comprises a large amount of hydrocarbon containing organic substances, which is regarded as a potential resource rather than simply a waste. A field experiment was conducted in a poly-metallic mining area to investigate the potential of organic waste to facilitate the soil remediation process. Different organic wastes and a commonly used commercial fertilizer were added to heavy metal contaminated soil, which was under phytoremediation using the As hyperaccumulator Pteris vittata. The influence of diverse fertilizer regimes on the biomass of P. vittata and heavy metal removal by P. vittata, was investigated. The soil properties were analyzed after the application of phytoremediation with or without the addition of organic wastes. Results indicated that sewage sludge compost is an appropriate amendment to improve the phytoremediation efficiency. Compared to the control, the application of sewage sludge compost significantly reduced the extractability of As in soil by 26.8 %, and increased the removal of As and Pb by 26.9 % and 186.5 %, respectively. The highest removal of As and Pb reached 33 and 34 kg/ha, respectively. The sewage sludge compost-strengthened phytoremediation improved soil quality. And the diversity and richness of the bacterial community were improved, as represented by the increase in Shannon and Chao index. With improved efficiency and acceptable cost, the organic waste-strengthened phytoremediation can be used to control the risks posed by high concentrations of heavy metals in mining areas.

Impacts of land uses on spatio-temporal variations of seasonal water quality in a regulated river basin, Huai River, China.

Land use impacts from agriculture, industrialization, and human population should be considered in surface water quality management. In this study, we utilized an integrated statistical analysis approach mainly including a seasonal Mann-Kendall test, clustering analysis, self-organizing map, Boruta algorithm, and positive matrix factorization to the assessment of the interactions between land use types and water quality in a typical catchment in the Huai River Basin, China, over seven years (2012-2019). Spatially, water quality was clustered into three groups: upstream, midstream, and downstream/mainstream areas. The water quality of upstream sites was better than of mid-, down-, and mainstream. Temporally, water quality did not change significantly during the study period. However, the temporal variation in water quality of up-, down-, and mainstream areas was more stable than in the midstream. The interactions between land use types and water quality parameters at the sub-basin scale varied with seasons. Increasing forest/grassland areas could substantially improve the water quality during the wet season, while nutrients such as phosphorus from cropland and developed land was a driver for water quality deterioration in the dry season. Water area was not a significant factor influencing the variations of ammonia nitrogen (NH3-N) and total phosphorus (TP) in the wet or dry season, due to the intensive dams and sluices in study area. The parameters TP, and total nitrogen (TN) were principally linked with agricultural sources in the wet and dry seasons. The parameters NH3-N in the dry season, and chemical oxygen demand (CODCr) in the wet season were mainly associated with point source discharges. Agricultural source, and urban point source discharges were the main causes of water quality deterioration in the study area. Collectively, these results highlighted the impacts of land use types on variations of water quality parameters in the regulated basin.

An interpolation method incorporating the pollution diffusion characteristics for soil heavy metals - taking a coke plant as an example.

The existing spatial interpolation methods in the prediction of soil heavy metal distribution are generally based on spatial auto correlation theory, rarely considering the pollution patterns. By contrast, in polluted sites, heavy metals have a strong heterogeneity even within a very small area, which is not exactly in line with auto correlation theory. This contradiction may lead to inaccuracy in spatial prediction. Atmospheric diffusion and deposition are one of the main sources of soil heavy metal pollution caused by coal-related production activities. To improve the prediction accuracy, the diffusion patterns of pollutants were considered in this paper by integrating Geodetector, Co-Kriging (COK), and partition interpolation. Geodetector was used to identify the main driving factors of soil pollution, based on which, the main driving factors were used as covariates introduced into the interpolation method (COK). Specifically, the amount of particulate matter deposition obtained by a pollutant diffusion model (AERMOD) was used as a covariate. For comparison, the distances to quenching, coke oven, and ammonium sulfate section were also used as covariates. Compared with the Ordinary Kriging method, the method COK-AERMOD established here decreased the root mean square error values of As (2.05 reduced to 1.89), Cd (0.18 reduced to 0.16), Cr (19.07 reduced to 12.97), Cu (6.92 reduced to 4.72), Hg (0.32 reduced to 0.28), Ni (16.92 reduced to 16.10), Pb (18.29 reduced to 16.62), and Zn (159.68 reduced to 153.66). This method in this paper is informative for the interpolation of soil elements in contaminated areas with known pollution source and diffusion patterns.

Composition of Three Common Chinese Herbal Medicines and the Influence of Preparation Types on the Bioaccessibility of Trace Elements.

The high concentration of trace elements in Chinese herbal medicine (CHM) is an important research topic for quality control. This study investigated the total concentration of trace elements in three herbs used as both medicine and supplementary food, including Astragalus membranaceus, Glycyrrhiza, and Isatidis. Further, the effects of different preparation ways, such as decoct, granule, and oral liquid, on the bioaccessibility of trace elements in CHM were disclosed. Results indicated that the total concentrations of trace elements in these three herbs were lower than the medical standards, but the concentrations of As and Pb in CHMs were higher than the standards for supplementary food. Different preparations ways affect bioaccessibility. Powder and oral liquid show a high bioaccessibility possibly because of the grinding process and the repeated extraction with ethanol. Among the three different CHMs, Isatidis showed higher bioaccessibility of As, which may be related to the sulfur fumigation process of this CHM. The three investigated CHMs were found to be safe as medicine but presented risks as supplementary food. The apparent influence of preparation procedures on the bioaccessibility of trace elements indicated that it is necessary to appropriately regulate preparation processes for CHMs.

Abundance, spatial variation, and sources of rare earth elements in soils around ion-adsorbed rare earth mining areas.

Rare earth elements (REEs) concentrated in soils have attracted increasing attention about their impact on soil health as emerging contaminants. However, the sources of REEs enriched in soils are diverse and need to be further investigated. Here, surface soil samples were collected from southern Jiangxi Province, China. REEs contents and soil physicochemical properties were determined, and cerium (Ce) and europium (Eu) anomalies were calculated. Moreover, we established a model to further identify the main sources of REEs accumulation in the studied soils. Results show that the abundance of soil REEs reveals larger spatial variation, suggesting spatially heterogeneous distribution of REEs. The median content of light REEs in soils (154.5 mg kg-1) of the study area was higher than that of heavy REEs and yttrium (35.8 mg kg-1). In addition, most of the soil samples present negative Ce anomalies and all the soil samples present negative Eu anomalies implying the combined effect of weathering and potential exogenous inputs on soil REEs. Positive matrix factorization modeling reveals that soil REEs content is primarily influenced by soil parent materials. Potential anthropogenic sources include mining-related leachate, traffic exhaust, and industrial dust. These results demonstrate that the identification of sources of soil REEs is an important starting point for targeted REEs sources management and regulation of excessive and potentially harmful REEs levels in the soil.

Potentially toxic elements exposure biomonitoring in the elderly around the largest polymetallic rare earth ore mining and smelting area in China.

Potentially toxic elements (PTEs) can be released during mining operations and ore processing. The pollution and health risk related to PTEs in total suspended particulates (TSPs) around the largest polymetallic rare earth mining area (Bayan Obo) and smelting area (Baotou) in Inner Mongolia, China, were evaluated. PTEs in the hair of the elderly living in these two areas and a reference area (Hohhot) were also examined. Relationships between PTEs in TSPs and hair with categorical factors (location, gender, etc.) were also modeled. Multivariate statistical analyses were carried out to analyze the possible sources of the PTEs in TSPs. The bubble maps of the concentrations of PTEs indicated that high concentrations of PTEs were near the industrial area where smelting plants and power plants were located. In addition, health risks were assessed for adults in the mining and smelting area. The carcinogenic risk of Cr was high for residents in the study areas. Also, the residents were exposed to a non-carcinogenic risk of Ni. Significant mean value differences were observed between PTEs in the hair of the elderly in Baotou and Hohhot. Results of the linear regression model indicated that around 31 % of the Pb in hair could be explained by the linear regression model, it could be affected by Ni and Zn in TSPs, but location, gender, and sampling time showed no significant contribution. Age was not significantly associated with the PTEs levels in hair in Baotou and Bayan Obo. The results provide important scientific evidence for a better understanding of the effects of PTEs in TSPs in polymetallic ore mining and smelting areas.

Responses of soil greenhouse gas emissions to land use conversion and reversion-A global meta-analysis.

Exploring the responses of greenhouse gas (GHG) emissions to land use conversion or reversion is significant for taking effective land use measures to alleviate global warming. A global meta-analysis was conducted to analyze the responses of carbon dioxide (CO2 ), methane (CH4 ), and nitrous oxide (N2 O) emissions to land use conversion or reversion, and determine their temporal evolution, driving factors, and potential mechanisms. Our results showed that CH4 and N2 O responded positively to land use conversion while CO2 responded negatively to the changes from natural herb and secondary forest to plantation. By comparison, CH4 responded negatively to land use reversion and N2 O also showed negative response to the reversion from agricultural land to forest. The conversion of land use weakened the function of natural forest and grassland as CH4 sink and the artificial nitrogen (N) addition for plantation increased N source for N2 O release from soil, while the reversion of land use could alleviate them to some degree. Besides, soil carbon would impact CO2 emission for a long time after land use conversion, and secondary forest reached the CH4 uptake level similar to that of primary forest after over 40 years. N2 O responses had negative relationships with time interval under the conversions from forest to plantation, secondary forest, and pasture. In addition, meta-regression indicated that CH4 had correlations with several environmental variables, and carbon-nitrogen ratio had contrary relationships with N2 O emission responses to land use conversion and reversion. And the importance of driving factors displayed that CO2 , CH4 , and N2 O response to land use conversion and reversion was easily affected by NH4 + and soil moisture, mean annual temperature and NO3 - , total nitrogen and mean annual temperature, respectively. This study would provide enlightenments for scientific land management and reduction of GHG emissions.

A holistic assessment of spatiotemporal variation, driving factors, and risks influencing river water quality in the northeastern Qinghai-Tibet Plateau.

The Qinghai-Tibet Plateau (QTP) is the source for many of the most important rivers in Asia. It is also an essential ecological barrier in China and has the characteristic of regional water conservation. Given this importance, we analyzed the spatiotemporal distribution patterns and trends of 10 water quality parameters. These measurements were taken monthly from 67 monitoring stations in the northeastern QTP from 2015 to 2019. To evaluate water quality trends, major factors influencing water quality, and water quality risks, we used a series of analytical approaches including Mann-Kendall test, Boruta algorithm, and interval fuzzy number-based set-pair analysis (IFN-SPA). The results revealed that almost all water monitoring stations in the northeastern QTP were alkaline. From 2015 to 2019, the water temperature and dissolved oxygen of most monitoring stations were significantly reduced. Chemical oxygen demand, permanganate index, five-day biochemical oxygen demand, total phosphorus, and fluoride all showed a downward trend across this same time frame. The annual average total nitrogen (TN) concentration fluctuation did not significantly decrease across the measured time frame. Water quality index (WQI-DET) indicated bad or poor water quality in the study area; however, water quality index without TN (WQI-DET') reversed the water quality value. The difference between the two indexes suggested that TN was a significant parameter affecting river water quality in the northeastern QTP. Both Spearman correlation and Boruta algorithm show that elevation, urban land, cropland, temperature, and precipitation influence the overall water quality status in the northeastern QTP. The results showed that between 2015 and 2019, most rivers monitored had a relatively low risk of degradation in water quality. This study provides a new perspective on river water quality management, pollutant control, and risk assessment in an area like the QTP that has sensitive and fragile ecology.

Responses of diversity and arsenic-transforming functional genes of soil microorganisms to arsenic hyperaccumulator (Pteris vittata L.)/pomegranate (Punica granatum L.) intercropping.

Intercropping of arsenic (As) hyperaccumulator (Pteris vittata L.) with crops can reduce the As concentration in soil and the resulting ecological and health risks, while maintaining certain economic benefits. However, it is still unclear how As-transforming functional bacteria and dominant bacteria in the rhizosphere of P. vittata affect the microbial properties of crop rhizosphere soil, as well as how As concentration and speciation change in crop rhizosphere soil under intercropping. This is of great significance for understanding the biogeochemical cycle of As in soil and crops. This study aimed to use high-throughput sequencing and quantitative polymerase chain reaction (qPCR) to analyze the effects of different rhizosphere isolation patterns on the bacterial diversity and the copy number of As-transforming functional genes in pomegranate (Punica granatum L.) rhizosphere soil. The results showed that the abundance of bacteria in the rhizosphere soil of pomegranate increased by 16.3 %, and the soil bacterial community structure significantly changed. C_Alphaproteobacteria and o_Rhizobiales bacteria significantly accumulated in the rhizosphere of pomegranate. The copy number of As methylation (arsM) gene in pomegranate rhizosphere soil significantly increased by 63.37 %. The concentrations of nonspecifically sorbed As (F1), As associated with amorphous Fe (hydr)oxides (F3), and the total As (FT) decreased; the proportion of As (III) in pomegranate rhizosphere soil decreased; and the proportion of As (V) increased in pomegranate rhizosphere soil. c_Alphaproteobacteria and o_Rhizobiales accumulated in crop rhizosphere soil under the intercropping of P. vittata with crops. Also, the copy number of As methylation functional genes in crop rhizosphere soil significantly increased, which could reduce As (III) proportion in crop rhizosphere soil. These changes favored simultaneous agricultural production and soil remediation. The results provided the theoretical basis and practical guidance for the safe utilization of As-contaminated soil in the intercropping of As-hyperaccumulator and cash crops.

Apportionment and location of heavy metal(loid)s pollution sources for soil and dust using the combination of principal component analysis, Geodetector, and multiple linear regression of distance.

The accurate identification of sources for soil heavy metal(loid) is difficult, especially for multi-functional parks, which include multiple pollution sources. Aiming to identify the apportionment and location of heavy metal(loid)s pollution sources, this study established a method combining principal component analysis (PCA), Geodetector, and multiple linear regression of distance (MLRD) in soil and dust, taking a multi-functional industrial park in Anhui Province, China, as an example. PCA and Geodetector were used to determine the type and possible location of the source. Source apportionment of individual elements is achieved by MLRD. The detection results quantified the spatial explanatory power (0.21 ≤ q ≤ 0.51) of the potential source targets (e.g., river and mining area) for the PCA factors. A comparative analysis of the regression equation (Model 1 and Model 3) indicated that the river (0.50 ≤ R2 ≤0.78), main road (0.47 ≤ R2 ≤ 0.81), and mine (0.14 ≤ R2 ≤ 0.92) (p < 0.01) were the main sources. Different from the traditional source apportionment methods, the current method could obtain the exact contributing sources, not just the type of source (e.g., industrial activities), which could be useful for pollution control in areas with multiple sources.