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Soil Pollution

Soil Pollution refers to the contamination of soil with harmful substances, such as chemicals, heavy metals, or organic compounds, that can adversely affect the environment and human health.
This type of pollution can arise from industrial activities, agricultural practices, waste disposal, or accidental spills.
Exposure to soil pollutants can lead to a range of health issues, including respiratory problems, neurological disorders, and cancer.
Effective soil pollution analysis and remediation techniques are crucial for protecting ecosystems and human populations.
Researchers can leverage AI-driven tools like PubCompare.ai to optimize their soil pollution research protocols, enhancing reproducibility and improving the accuracy and efficiancy of their studies.

Most cited protocols related to «Soil Pollution»

Contaminated soil was collected from a former MGP site in Salisbury, NC, USA. The soil was sieved through a 10-mm wire screen, mixed with sterile 40/50 grade silica sand (Unimin Corporation, Le Sueur, MN) at a 50:50 ratio (dry weight), and stored at 4°C prior to column packing. Addition of the silica sand was necessary to maintain low-pressure flow during long-term column operation; preliminary column studies with the source material yielded very high inlet pressures (>100 psi). Sand addition had minimal impact on the indigenous soil microbial community as evaluated by denaturing-gradient gel electrophoresis (DGGE; data not shown). In subsequent discussion, the final packing material is referred to as “column soil”.
The column soil contained 83% sand, 14% silt, and 3% clay, with total organic matter of 8.3% as determined by a thermogravimetric method (27 (link)) and extractable organic matter of 0.64%. The total concentration of the PAHs analyzed was 295 ± 65 mg/kg dry soil (n = 33), with phenanthrene comprising 44% of the total PAH mass (129 ± 31 mg/kg). A complete list of physical properties and PAH concentrations for the column soil is presented in the Supporting Information (Tables S1 - S3).
Publication 2010
Clay Denaturing Gradient Gel Electrophoresis Microbial Community phenanthrene Physical Processes Polycyclic Hydrocarbons, Aromatic Silicon Dioxide Soil Pollution Sterility, Reproductive
The development of ENVO is now conducted using Protégé (http://protege.stanford.edu), rather than OBO Edit [22 (link)], allowing more expressivity through the Web Ontology Language (OWL). For global interoperability, we preferentially use relations from the Relations Ontology (RO; [23 ]) and the Basic Formal Ontology (BFO; [24 ]) to connect these classes. Additional relations are present, but will be incorporated into RO pending an open discussion and vetting process. The ontology is still released in both OBO and OWL formats and a number of custom exports have been made upon request (e.g. flat, character delimited formats suitable for import into relational databases, table-oriented analysis software, or network visualisation and analysis solutions). We continue to maintain obsoleted terms and link them to their replacements (where available) in a machine readable way to support automated updating of user implementations.
As with most other OBO Library ontologies, ENVO’s repository has been moved to its own GitHub “organization” (https://github.com/EnvironmentOntology). This change does not affect downstream users who consume the ontology using standard permanent URLs; however, it does provide a better mechanism for stakeholders to become involved with the development of the ontology through, for example, an improved issue tracker [25 ]. Further, it allows easier reference to previous versions of the ontology for backwards compatibility.
OWLTools (https://github.com/owlcollab/owltools) and ROBOT [26 ] (https://github.com/ontodev/robot/) are currently being used for release management, and for the import of classes from other OBO Foundry and Library ontologies in alignment with the Minimum Information to Reference an External Ontology Term (MIREOT; [27 ]) guidelines. These import procedures are primarily used to express environments that are dependent on entities defined outside of ENVO. For example, environments defined by anatomical entities and chemical entities are expressed using classes from ontologies such as the Uber Anatomy Ontology (UBERON; [28 (link)]) and the Chemical Entities of Biological Interest Ontology (CHEBI; [29 (link)]) to prevent duplicating existing, well-developed semantics relevant to terms such as ‘xylene contaminated soil’ [ENVO_00002146] and ‘axilla skin environment’ [ENVO_08000001].
We have created a TermGenie instance (http://envo.termgenie.org/) [30 (link)] that allows for web-based addition of new terms that conform to a pre-defined template, or following a free-form pattern. We are also documenting our design patterns (ODPs) using the emerging ‘dead simple owl design patterns’ standard (https://github.com/dosumis/dead_simple_owl_design_patterns) and are using these patterns to generate small portions of the ontology. Further, we have begun to use the results of text-mining approaches, noted in [1 (link)], discussed below, and documented by Pafilis et al. [31 (link)], to automatically generate experimental classes which, upon curation, can be integrated into the core ontology.
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Publication 2016
Axilla cDNA Library Character Skin Soil Pollution Surgical Replantation Xylene
Total metagenomic DNA was isolated from the triplicate samples of the initial contaminated soil and from the SPME-enriched microbial cultures (three biological replicates per each treatment) obtained at the end of the enrichment procedure. DNA extraction was performed using the FastDNA Spin Kit for Soil (MP Bio, USA) according to the manufacturer’s instructions. Primers 515 forward 5′-GTGYCAGCMGCNGCGG-3′ and 926 reverse 5′-CCGYCAATTYMTTTRAGTTT-3′ (adapted from Walters, et al.67 (link) with modification of the forward primer) were used to target hypervariable regions V4–V5 of the 16S rRNA genes amplified by PCR in a final volume of 15 µL with: KAPA HiFi HotStart ReadyMix (Kapa Biosystems, Boston, MA, USA) containing 0.02 U/µL of KAPA HiFi HotStart DNA Polymerase, 2.5 mM MgCl2 and 0.3 mM of each dNTP; 0.3 µM of each primer (Generi Biotech, Czech Republic); and template DNA (~20 ng). The cycling program was set as follows: 5 min at 95 °C, 20 cycles of 20 s at 98 °C, 15 s at 56 °C, 15 s at 72 °C and a final extension of 5 min at 72 °C. A volume of 0.5 µL of the PCR product was used as the template for another round of PCR, which was performed under the same conditions except that the final reaction volume was 25 µL, with 1 µM of each primer, and the cycle number was decreased to 5-10. The forward and reverse primers used for the second PCR were modified with sequencing adapters and internal barcodes of variable length (5–8 bp) using the TaggiMatrix spreadsheet courtesy of Travis C. Glenn at the University of Georgia (http://www.baddna.org). The resultant PCR products were purified using AMPure XP Beads (Agencourt, Beckman Coulter, USA). Further amplicon-sample library preparation and sequencing analysis on an Illumina MiSeq instrument were performed at the Core Facility for Nucleic Acid Analysis at the University of Alaska Fairbanks.
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Publication 2017
Biopharmaceuticals DNA-Directed DNA Polymerase DNA Library Magnesium Chloride Metagenome Nucleic Acids Oligonucleotide Primers Ribosomal RNA Genes Sequence Analysis Soil Pollution Solid Phase Microextraction
We used six healthy honeybee colonies (Apis mellifera ligustica Spinola, 1806, located at the UCSD Biology Field Station apiary, La Jolla, USA), studied forager and in-hive honeybees, and followed standard collection and rearing methodologies [49 (link)]. To test the effect of season, we collected bees at two different colony developmental stages: early spring (February–March 2016) and summer (July 2016). We tested the synergistic and individual effects of FPF exposing bees to five acute oral doses of FPF or FPF + PRO. Based on current guidelines [50 ,51 (link)], we tested FPF doses (375 and 750 ng bee−1) considered field-realistic, since bees can ingest higher FPF doses while foraging (see electronic supplementary material for the worst-case scenario estimations).
Following previous studies [22,28,52], we used a relatively high PRO dose that nonetheless, on its own, has no impact on bee survival (7000 ng bee−1 [22 (link),52 (link)]). PRO is one of the most commonly used fungicides that contaminates bees and the environment [31 (link),32 (link)]. Bees can be simultaneously exposed to FPF and PRO (or another SBI fungicide with similar mode of action) because they are used on the same crops and ornamentals, including fruits (e.g. citrus), oilseeds (e.g. soya bean, peanuts), cereals (e.g. corn, sorghum) [10 ,12 (link),15 ,53 –55 ], although guidelines state that flupyradifurone should not be directly tank-mixed with azole fungicides when applied to flowering crops [10 ]. These pesticides can be used multiple times over a year in the same crop (and over different seasons) and applied in multiple ways (i.e. aerial, chemigation or ground application). In addition, bees can also be exposed to pesticides that drift from different crops (i.e. buffer zones) or are stored in the same hive [56 (link),57 (link)]. FPF and PRO are easily taken up by plants and thus contaminated soil and water may lead to unintended absorption. This can result in prolonged, multi-year contamination [56 (link),58 (link),59 (link)]. Bees can therefore be exposed to pesticide combinations that are contraindicated in tank mixes [6 (link)].
We tested a control dose (0 ng bee−1), a total of six doses of FPF (375, 750, 1500, 3000, 6000, 12 000 ng bee−1, respectively corresponding to 37.5, 75, 150, 300, 600, 1200 ppm), and five doses of the positive control dimethoate (DIM; 50, 100, 200, 400, 800 ng bee−1, respectively corresponding to 5, 10, 20, 40, 80 ppm). In the combined FPF + PRO treatment, each FPF dose was tested in combination with a single sublethal dose of PRO (7000 ng bee−1, corresponding to 700 ppm). We used technical grades of all active ingredients. The test solutions (sucrose 50% w/w, 100 µl cage−1, 10 µl bee−1,) were provided inside each cage using an Eppendorf cap [60 ], contained acetone as a solvent (0.7%) and were completely consumed 60 min after oral administration [60 ].
We measured the effects of treatment on bee survival (1–48 h) and the frequency of bees exhibiting abnormal behaviours (1–4 h, see below).
Detailed methods are reported in the electronic supplementary material.
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Publication 2019
Acetone Administration, Oral Agricultural Crops Apis Arachis hypogaea Azoles Bees Buffers CAGE1 protein, human calmodulin acceptor protein 60 Cereals Citrus Combined Modality Therapy Crop, Avian Dimethoate flupyradifurone Fruit Industrial Fungicides Pesticides Plants Problem Behavior Soil Pollution Solvents Sorghum Soybeans Sucrose Urticaria Zea mays
The degree of soil HM pollution was assessed as follows: first soil pH values were categorized into three classes: <6.5, 6.5 ≤ pH ≤ 7.5, and >7.5; second, the pollution threshold for each soil HM was determined by land use (e.g., paddy fields) and pH class; third, the single pollution index (SPI) for each HM was determined (Equation (1)); finally, the Nemerow composite pollution index (NCPI) was calculated (Equation (2)).
Pi=CiSi
where Ci is the concentration of soil HM i, and Si is the pollution threshold of i [32 ].
NCPI=(Pimax)2+(P¯i)22
where Pimax is the maximum SPI value of each HM and P¯ is the mean SPI of each HM [32 ].
As NCPI is a comprehensive index, it was used to classify the soils in terms of HM pollution. Table 1 shows the classifications of the single pollution index (SPI) and Table 2 shows the classifications of Nemerow composite pollution index (NCPI).
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Publication 2017
Soil Pollution

Most recents protocols related to «Soil Pollution»

The metal pollution index is a measure of
soil quality by evaluating single substances. It was introduced by
Müller to evaluate the measured metal concentrations by comparing
preindustrial levels in sediments.52 It
is widely used in defining river sediment quality in studies, but
this index is also preferred to express metal pollution in soils.53 (link),54 (link) In eq 2, Cn is the current metal (n) concentration in the soil and Bn is the geochemical background value (BGV) of the metal in
the sample. The factor 1.5 is the coefficient for the background matrix
coming from geogenic variations. Igeo was
categorized into six classes:52 <0:
unpolluted; 0–1: unpolluted to moderately polluted; 1–2:
moderately polluted; 2–3: moderately to strongly polluted;
3–4: strongly polluted; 4–5: strongly to extremely polluted;
and >5: extremely polluted.
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Publication 2023
Factor V Metals Rivers Soil Pollution
Based on the obtained results, indicators have been calculated, the use of which is an important tool when describing the relationships between the soil and the plant. They also allow us to compare the transfer and bioaccumulation of the tested heavy metals. The following indicators were used in the work:
MR (Mobility ratio)—corresponding to BAC (Biological accumulation coefficient), which explains the transport from the soil to the individual organs of the plants, calculated on the basis of the metal content of the above ground plant part (Cplant) to the soil content (Csoil) [5 (link)].
MR=Cplant/Csoil
sTF (Sap translocation factor) – describing transport only in the plant; it has been modified for research purposes and has been calculated on the basis of the metal content in the aerial parts of plants (Cplant) to the content in birch sap (Csap) [5 with modifications].
sTF=Cplant/Csap
PIi (Single soil pollution index)—comparison of the current concentration of a given mineral (i) in the soil (Csoil) with the geochemical background (Bm); [14 (link)]; the following values were adopted as Bm: Zn – 67 mg/kg; Cu – 39 mg/kg; Cr – 69 mg/kg; Ni – 55 mg/kg; Pb – 17 mg/kg; Cd – 0.1 mg/kg [38 (link), 39 (link)].
PIi=Csoil/Bm
Any result greater than 1 means that the metal content in the test sample was higher than that considered typical [14 (link)].
PI total (Sum of soil pollution indexes)—is the sum of the indices of individual heavy metals [14 (link)]
PI=ΣiPI
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Publication 2023
Betula Bioaccumulation Biopharmaceuticals Metals Metals, Heavy Minerals Plant Components, Aerial Plants Range of Motion, Articular Soil Pollution Translocation, Chromosomal
This study estimates the human health risks (non-carcinogenic and carcinogenic) due to exposure to contaminated soil via ingestion, dermal contact, and inhalation exposure pathways for children and adults. USEPA [48] , [39] proposed health risk assessment method was applied (Table 2), and model parameters and references dose are presented in Table 3 and Table S3, respectively.

Exposure parameters and their values were adopted from USEPA [49] , [50] .

Table 3
ParameterUnitChildAdults
Body weight (BW)kg1570
Exposure frequency (EF)days/year350350
Exposure duration (ED)years630
Ingestion rate (IR)mg/day200100
Inhalation rate (IRair)m3/day1020
Skin surface area (SA)cm221005800
Soil adherence factor (AF)mg/cm20.20.07
Dermal Absorption factor (ABS)none0.10.1
Dermal exposure ratio (FE)none0.610.61
Particulate emission factor (PEF)m3/kg1.3 × 1091.3 × 109
Conversion factor (CF)kg/mg10−610−6
Average time (AT)
For carcinogensdays365 × 70365 × 70
For non-carcinogens365 × ED365 × ED
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Publication 2023
Adult Carcinogens Child Health Risk Assessment Homo sapiens Inhalation Exposure Skin Soil Pollution
Black soldier fly larvae (BSFL; Hermetia illucens) were obtained from the commercial BSF producing company Bestico, (Berkel en Rodenrijs, The Netherlands). The following substrates were tested: chicken feed (CF; control diet), pig manure slurry mixed with roadside silage grass (PMLSG), the organic wet fraction of municipal household waste (OWF), secondary sludge from slaughter waste (SW), fast food waste (FFW), mushroom stems (MS) and pig manure solid (PMS). Chicken feed is a commercial broiler feed which was used as the control diet [33 (link),36 (link),37 (link)]. Pig manure slurry was a mixture of pig feces and urine, and it was mixed with roadside silage grass (1:1 w/w) to produce PMLSG. The organic wet fraction used in this experiment makes around 30–35% of the municipal household waste. It was contaminated by physical contaminants such as glass and plastic that were not removed. The solid phase of the secondary sludge from slaughter waste was also used as an experimental substrate. The fast food waste consisted of fries, vegetables, bread and meat products but not any non-food waste and was collected within maximum 4 days after disposal. The mushroom stems are a soft substrate and may have been contaminated by soil. The different substrates were selected based on the results of a prior study published by Veldkamp [33 (link)].
Substrates were obtained one week before the start of the rearing cycle and stored at 4 °C until use. Some of the substrates were pre-treated in a cutter to decrease particle size which included PMLSG (~2 cm), FFW (~1 cm) and MS substrates (~0.5 cm). All substrates are brought to 35% dry matter by adding water and/or cellulose/wood shavings to decrease or increase the DM in the substrate, respectively. Since the used substrates all have a different weight-to-volume ratio, different quantities of substrates and larvae were added to the containers to maintain a substrate layer of approximately 5 cm such that every BSFL gets 0.54 g of the wet substrate (Table 1). The containers were filled one day before starting the experiment, thus allowing them to adapt to the ambient temperature in the climate chamber without any external heating. On top of each substrate, 1850 starter BSFL (8 day old) per kilogram of wet substrate were incubated in 21 plastic containers (75 cm × 47 cm × 15 cm). Each substrate was tested in triplicate in a climate chamber (7 treatments × 3 replicates). The chamber temperature was set to 28 °C and the relative humidity (RH) was 70% from day 0 until day 5 and was 40–60% from day 6 until the end of the experiment. The rearing chamber was dark. The plastic containers were stacked in three columns each with seven containers (one container per repetition) arranged based on escaping probability, i.e., the containers with the highest moisture content were placed at the bottom to avoid escaping larvae falling into containers below them. Each column was placed in a non-escape box (cubic box; 120 cm × 100 cm × 60 cm). The experimental period was 7 to 8 days which was determined by visual checking of the substrate consumption or the presence of ~10% prepupae.
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Publication 2023
Agaricales Bread Cellulose Chickens Climate Cuboid Bone Diet Fast Foods Feces Food G-substrate Households Humidity Larva Maggots Meat Products Physical Examination Poaceae Silage Simuliidae Sludge Soil Pollution Soldiers Stem, Plant Urine Vegetables
The oil-contaminated soil sample was collected from the Southwest University of Science and Technology, Mianyang, Sichuan Province (N 31.53791, E 104.69388). For the isolation and screening of lipase-producing strains, 5 g of the soil sample was weighed in 45 mL of physiological saline, incubated for 1 h at 30 °C while being shaken at 200 r/min, and then rested. A quantity of 1 mL of supernatant was added to 20 mL of enrichment medium (yeast paste 0.2 g/L, NaCl 0.5 g/L, Na2HPO4 3.5 g/L, KH2PO4 1.5 g/L, MgSO4-7H2O 0.5 g/L), and this was incubated for 24 h at 30 °C while being shaken at 200 r/min. After gradient dilution of the enrichment medium, 100 μL of 10−6~10−8 dilution was coated onto the oil assimilation plate containing rhodamine B (25 mL olive oil emulsion was mixed well with 175 mL LB medium, 200 μL 10% rhodamine B solution was added, and the mixture was shaken). After incubation at 30 °C for 2 d, a pure culture capable of producing degradation circles was obtained, named WCO-9. The single colony of strain WCO-9 was selected and inoculated in an LB liquid medium. Cells in the logarithmic growth phase were obtained by shaking at 200 r/min and incubating at 30 °C for 12 h and were then stored in glycerol tubes. Finally, the WCO-9 strain was identified and registered by the Guangdong Microbial Culture Collection Center with the serial number GDMCC No: 61851. The scanning electron microscopy observation, 16S rDNA analysis and whole genome sequencing were performed using cells from the logarithmic growth stage.
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Publication 2023
Cells DNA, Ribosomal Emulsions Glycerin isolation Lipase Oil, Olive Paste physiology rhodamine B Saline Solution Scanning Electron Microscopy Sodium Chloride Soil Pollution Strains Sulfate, Magnesium Technique, Dilution Yeasts

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More about "Soil Pollution"

Soil contamination, ground pollution, land degradation, and environmental toxicology are all terms related to soil pollution.
This type of pollution can arise from a variety of sources, including industrial activities, agricultural practices, waste disposal, and accidental spills.
Exposure to soil pollutants can lead to a range of health issues, such as respiratory problems, neurological disorders, and cancer.
Effective soil pollution analysis and remediation techniques are crucial for protecting ecosystems and human populations.
Researchers can leverage AI-driven tools like PubCompare.ai to optimize their soil pollution research protocols, enhancing reproducibility and improving the accuracy and efficiancy of their studies.
Soil pollution analysis often involves the use of techniques like nutrient agar, HPLC, and Optima 4300 DV.
Researchers may also use statistical software like Statistica 10 or SPSS 20.0 to analyze their data.
The PowerSoil DNA Isolation Kit and BigDye Terminator v3.1 Cycle Sequencing Kit can be used for DNA extraction and sequencing, respectively.
In addition, researchers may use Quarter strength Ringer's solution and Whatman filter paper for sample preparation and filtration.
Antimicrobial agents like ampicillin may also be used in some soil pollution studies.
By incorporating these insights and techniques, researchers can enhance the accuracy and efficiency of their soil pollution studies, ultimately contributing to the protection of the environment and human health.