A novel algorithm for optimizing hydrocyclone operations in the decontamination of potentially toxic elements in soils.

We present the Three-Parameter Penalized Attributive Analysis for Upgrading (3PPAA-U) method as a tool for selecting the Best Upgrading Condition (BUC) in process engineering. Conventional approaches tend to consider only maximizing recovery (ε) and minimizing yield (γc); in contrast, the proposed 3PPAA-U introduces and seeks to maximize a third parameter, the grade (λ). This multi-parameter approach has not yet been explored in existing literature. In addition to controlling multiple parameters, the method is also superior to others as it includes inverse standard deviation weighting to avoid the distortion of results due to data dispersion. This reduces the possibility of drawing conclusions based on extreme values. Furthermore, the method can be used with a target-to-distance correction to optimize separation for multi-component feeds. To illustrate our method, we present a practical application of 3PPAA-U. Soil contaminated with potentially toxic elements (PTEs) was subject to hydrocycloning under 12 different experimental conditions. Results of these 12 experiments were compared using 3PPAA-U and conventional methods to identify the best upgrading conditions (BUC). Analysis reveals that the 3PPAA-U approach offers a simple and effective criterion for selecting BUC. Furthermore, 3PPAA-U has uses beyond soil remediation. It offers a versatile tool for optimizing operations across various processing and manufacturing environments offering a way to manage factors such as concentration, temperature, pressure, pH, Eh, grain size, and even broader environmental and economic considerations.

Compositional baseline assessments to address soil pollution: An application in Langreo, Spain.

Potentially Toxic Elements (PTEs) are contaminants with high toxicity and complex geochemical behaviour and, therefore, high PTEs contents in soil may affect ecosystems and/or human health. However, before addressing the measurement of soil pollution, it is necessary to understand what is meant by pollution-free soil. Often, this background, or pollution baseline, is undefined or only partially known. Since the concentration of chemical elements is compositional, as the attributes vary together, here we present a novel approach to build compositional indicators based on Compositional Data (CoDa) principles. The steps of this new methodology are: 1) Exploratory data analysis through variation matrix, biplots or CoDa dendrograms; 2) Selection of geological background in terms of a trimmed subsample that can be assumed as non-pollutant; 3) Computing the spread Aitchison distance from each sample point to the trimmed sample; 4) Performing a compositional balance able to predict the Aitchison distance computed in step 3.Identifying a compositional balance, including pollutant and non-pollutant elements, with sparsity and simplicity as properties, is crucial for the construction of a Compositional Pollution Indicator (CI). Here we explored a database of 150 soil samples and 37 chemical elements from the contaminated region of Langreo, Northwestern Spain. There were obtained three Cis: the first two using elements obtained through CoDa analysis, and the third one selecting a list of pollutants and non-pollutants based on expert knowledge and previous studies. The three indicators went through a Stochastic Sequential Gaussian simulation. The results of the 100 computed simulations are summarized through mean image maps and probability maps of exceeding a given threshold, thus allowing characterization of the spatial distribution and variability of the CIs. A better understanding of the trends of relative enrichment and PTEs fate is discussed.

Benzo[a]pyrene sourcing and abundance in a coal region in transition reveals historical pollution, rendering soil screening levels impractical.

Benzo[a]pyrene (BaP) is a hazardous compound for human health and for environmental compartments. Its transfer and deposition through the atmosphere affects soil quality. In this context, we quantified the content of BaP and other Polycyclic Aromatic Hydrocarbons (PAHs) in the soils of a prominent Coal Region in Transition to test whether the soil screening levels in force are realistic and whether they reflect the complexity of regions closely linked to heavy industries and mining. In this regard, soil screening levels are thresholds often established without considering historical anthropogenic activities that affect soil (diffuse pollution). The 150 soil samples studied showed a notable content of high molecular weight PAHs, and BaP surpassed the threshold levels in practically the entire area. PAH-parent diagrams revealed a relatively homogenous fingerprint of four clusters obtained in a multivariate statistical study. In addition, molecular diagnostic ratios pointed to coal combustion as the main pollution source, whereas only some outliers appeared to be related to specific spills. A BaP threshold was calculated to be 0.24 mg kg-1, over 10 times the limit established in Spain. Finally, a factor analysis revealed a positive correlation of BaP with elements usually emitted in coal combustion processes, such as Tl and V. This observation fosters the hypothesis of a historical and indelible pollution fingerprint in soils whose sources, characteristics and potential environmental and health concerns deserve further attention. All things considered, caution should be taken when using soil screening levels in regions associated with coal exploitation and heavy industry.

Assessment of metal and metalloid contamination in soils trough compositional data: the old Mortórios uranium mine area, central Portugal.

Soils from the old Mortórios uranium mine area were studied to look for contamination, as they are close to two villages, up to 3 km away, and used for agriculture. They are mainly contaminated in U and As and constitute an ecological threat. This study attempts to outline the degree to which soils have been affected by the old mining activities through the computation of significant hot clusters, Traditional geostatistical approaches commonly use raw data (concentrations) accepting that the analyzed elements represent the soil's entirety. However, in geochemical studies these elements are just a fraction of the total soil composition. Thus, considering compositional data is pivotal. The spatial characterization, considering raw and compositional data together, allowed a broad discussion about not only the concentrations' spatial distribution, but also a better understanding on the possibility of trends of "relative enrichment" and, furthermore an insight in U and As fate. The highest proportions (compositional data) on U (up to 33%), As (up to 35%) and Th (up to 13%) are reached in the south-southeast segment. However, the highest concentrations (raw data) occur in north and northwest of the studied area, pointing out to a "relative enrichment" toward the south-southeast zone. The Mondego Sul area is mainly contaminated in U and As, but also in Co, Cu, Pb and Sb. The Mortórios area is less contaminated than the Mondego Sul area.

A coupled multivariate statistics, geostatistical and machine-learning approach to address soil pollution in a prototypical Hg-mining site in a natural reserve.

The impact of mining activities on the environment is vast. In this regard, many mines were operating well before the introduction of environmental law. This is particularly true of cinnabar mines, whose activity has declined for decades due to growing public concern regarding Hg high toxicity. Here we present the exemplary case study of an abandoned Hg mine located in the Somiedo Natural Reserve (Spain). Until its closure in the 1970s, this mine operated under no environmental regulations, its tailings dumped in two spoil heaps, one of them located uphill and the other in the surroundings of the village of Caunedo. This study attempts to outline the degree to which soil and other environmental compartments have been affected by the two heaps. To this end, we used a novel combination of multivariate statistical, geostatistical and machine-learning methodologies. The techniques used included principal component and clustering analysis, Bayesian networks, indicator kriging, and sequential Gaussian simulations. Our results revealed high concentrations of Hg and, secondarily, As in soil but not in water or sediments. The innovative methodology abovementioned allowed us to identify natural and anthropogenic associations between 25 elements and to conclude that soil pollution was attributable mainly to natural weathering of the uphill heap. Moreover, the probability of surpassing the threshold limits and the local backgrounds was found to be high in a large extension of the area. The methodology used herein demonstrated to be effective for addressing complex pollution scenarios and therefore they are applicable to similar cases.

Combining raw and compositional data to determine the spatial patterns of Potentially Toxic Elements in soils.

When considering complex scenarios involving several attributes, such as in environmental characterization, a clearer picture of reality can be achieved through the dimensional reduction of data. In this context, maps facilitate the visualization of spatial patterns of contaminant distribution and the identification of enriched areas. A set, of 15 Potentially Toxic Elements (PTEs) - (As, Ba, Cd, Co, Cr, Cu, Hg, Mo, Ni, Pb, Sb, Se, Tl, V, and Zn), was measured in soil, collected in Langreo's municipality (80km2), Spain. Relative enrichment (RE) is introduced here to refer to the proportion of elements present in a given context. Indeed, a novel approach is provided for research into PTE fate. This method involves studying the variability of PTE proportions throughout the study area, thereby allowing the identification of dissemination trends. Traditional geostatistical approaches commonly use raw data (concentrations) accepting that the elements analyzed make up the entirety of the soil. However, in geochemical studies the analyzed elements are just a fraction of the total soil composition. Therefore, considering compositional data is pivotal. The spatial characterization of PTEs considering raw and compositional data together allowed a broad discussion about, not only the PTEs concentration's distribution but also to reckon possible trends of relative enrichment (RE). Transformations to open closed data are widely used for this purpose. Spatial patterns have an indubitable interest. In this study, the Centered Log-ratio transformation (clr) was used, followed by its back-transformation, to build a set of compositional data that, combined with raw data, allowed to establish the sources of the PTEs and trends of spatial dissemination. Based on the obtained findings it was possible to conclude that the Langreo area is deeply affected by its industrial and mining legacy. City center is highly enriched in Pb and Hg and As shows enrichment in a northwesterly direction.

Nanoscale zero-valent iron-assisted soil washing for the removal of potentially toxic elements.

The present study focuses on soil washing enhancement via soil pretreatment with nanoscale zero-valent iron (nZVI) for the remediation of potentially toxic elements. To this end, soil polluted with As, Cu, Hg, Pb and Sb was partitioned into various grain sizes (500-2000, 125-500 and <125 µm). The fractions were pretreated with nZVI and subsequently subjected, according to grain size, to Wet-High Intensity Magnetic Separation (WHIMS) or hydrocycloning. The results were compared with those obtained in the absence of nanoparticles. An exhaustive characterization of the magnetic signal of the nanoparticles was done. This provided valuable information regarding potentially toxic elements (PTEs) fate, and allowed a metallurgical accounting correction considering the dilution effects caused by nanoparticle addition. As a result, remarkable recovery yields were obtained for Cu, Pb and Sb, which concentrated with the nZVI in the magnetically separated fraction (WHIMS tests) and underflow (hydrocyclone tests). In contrast, Hg, concentrated in the non-magnetic fraction and overflow respectively, while the behavior of As was unaltered by the nZVI pretreatment. All things considered, the addition of nZVI enhanced the efficiency of soil washing, particularly for larger fractions (125-2000 µm). The proposed methodology lays the foundations for nanoparticle utilization in soil washing operations.

Long-term ongoing impact of arsenic contamination on the environmental compartments of a former mining-metallurgy area.

Arsenic and mercury are potentially toxic elements of concern for soil, surficial and ground waters, and sediments. In this work various geochemical and hydrogeological tools were used to study a paradigmatic case of the combined effects of the abandonment of Hg- and As-rich waste on these environmental compartments. Continuous weathering of over 40years has promoted As and Hg soil pollution (thousands of ppm) in the surroundings of a former Hg mining-metallurgy site and affected the water quality of a nearby river and shallow groundwater. In particular, the high availability of As both in soils and waste was identified as one of the main determinants of contaminant distribution, whereas the impact of Hg was found to be minor, which is explained by lower mobility. Furthermore, potential additional sources of pollution (coal mining, high natural backgrounds, etc.) discharging into the study river were revealed less significant than the contaminants generated in the Hg-mining area. The transport and deposition of pollutants within the water cycle has also affected several kilometres downstream of the release areas and the chemistry of stream sediments. Overall, the environmental compartments studies held considerable concentrations of Hg and As, as remarkably revealed by the average contaminant load released in the river (several tons of As per year) and the accumulation of toxic elements in sediments (enrichment factors of As and Hg above 35).

Trace elements of concern affecting urban agriculture in industrialized areas: A multivariate approach.

The urban and peri-urban soils used for agriculture could be contaminated by atmospheric deposition or industrial releases, thus raising concerns about the potential risk to public health. Here we propose a method to evaluate potential soil pollution based on multivariate statistics, geostatistics (kriging), a novel soil pollution index, and bioavailability assessments. This approach was tested in two districts of a highly populated and industrialized city (Gijón, Spain). The soils showed anomalous content of several trace elements, such as As and Pb (up to 80 and 585 mg kg-1 respectively). In addition, factor analyses associated these elements with anthropogenic activity, whereas other elements were attributed to natural sources. Subsequent clustering also facilitated the differentiation between the northern area studied (only limited Pb pollution found) and the southern area (pattern of coal combustion, including simultaneous anomalies of trace elements and benzo(a)pyrene). A normalized soil pollution index (SPI) was calculated by kriging, using only the elements falling above threshold levels; therefore point-source polluted zones in the northern area and diffuse contamination in the south were identified. In addition, in the six mapping units with the highest SPIs of the fifty studied, we observed low bioavailability for most of the elements that surpassed the threshold levels. However, some anomalies of Pb contents and the pollution fingerprint in the central area of the southern grid call for further site-specific studies. On the whole, the combination of a multivariate (geo) statistic approach and a bioavailability assessment allowed us to efficiently identify sources of contamination and potential risks.

[Prenatal hydronephrosis: incidence, management and final diagnoses in 2003]. / Ectasia piélica de diagnóstico prenatal. Incidencia y protocolo de estudio durante el año 2003.

BACKGROUND: Prenatal diagnosis of renal pyelectasis usually involves postnatal studies to determine whether treatment is necessary or not. OBJECTIVES: To determine the incidence of fetal pyelectasis in our environment, to review our postnatal management protocol, and to review definitive diagnoses. PATIENTS AND METHOD: We performed a retrospective review of newborns with a prenatal diagnosis of pyelectasis. The variables recorded included prenatal ultrasound examinations, gestational age, sex, anthropometric data, postnatal study (ultrasound, cystography, isotopic renogram) and indication for antibiotic prophylaxis. RESULTS: There were 21 newborns (nine boys and 12 girls). Pyelectasia were located in the right kidney in 10 patients, on the left in seven and were bilateral in four. Antibiotic prophylaxis was administered at birth in seven neonates. Postnatal ultrasound was performed at 17.19 +/- 12.7 days of life and revealed no abnormalities in seven patients, hydronephrosis grade I-II in nine, hydronephrosis grade III in three and suspected double excretion system in two. Cystourethrography and isotopic renogram were performed in six neonates. The definitive diagnoses in the 21 patients were: no abnormalities in 10, non-complicated renal dilatation in seven, double excretion system in two, vesicoureteral reflux grade IV in one and pyeloureteral stenosis in one. None of these newborns had urinary tract infection. CONCLUSIONS: The incidence of prenatal pyelectasis in our hospital is 2 %. Most pyelectasia resolve spontaneously in the first year of life and invasive investigations are not required. Adequate monitoring of these children can avoid urinary tract infections and their sequelae.