Antibiotics are emerging contaminants of increasing concern in recent years. A total of 71 representative farmland soils along the Fenhe River in Shanxi Province were collected to investigate the occurrence of tetracyclines (TCs), sulfonamides (SAs), and quinolones (QLs). Additionally, the effects of population, livestock and poultry density, and soil properties on antibiotic distribution were also evaluated.
Materials and methodsFarmland topsoil samples along the Fenhe River were collected and freeze-dried at ??20 °C. The antibiotics in soils were extracted with a mixture of acetonitrile, EDTA-SPB, and Mg(NO3)2-NH3·H2O at the ratio of 2:1:1 (v/v/v). The extracted antibiotics were analyzed by liquid chromatography tandem mass spectrometry (LC-MS/MS).
Results and discussionThe antibiotics were universally detected. The detection frequencies of sulfaclozine, enrofloxacin, norfloxacin, and ciprofloxacin reached 100%. Norfloxacin was the most abundant antibiotic in soils (27.21 μg kg?1). The distribution of antibiotics in soils along Fenhe River varied as midstream (8.62 μg kg?1) > downstream (4.58 μg kg?1) > upstream (3.49 μg kg?1). Oxytetracycline along the upstream and midstream was mainly caused by the emission of livestock and poultry and the overuse of human. The main sources of antibiotics along the downstream were livestock and poultry farms. Antibiotics were generally negatively correlated with sand content, pH, and organic matter, while cation exchange capacity had positive correlation with most of antibiotics such as tetracycline, sulfamonomethoxine, enrofloxacin, sulfameter, and sulfachinoxalin. SAs and TCs had little ecological risk, while QLs posed low or medium ecological risks.
ConclusionsThis study provided a scientific basis for antibiotic pollution control and agricultural safety supervision along the Fenhe River. Although no high risk of antibiotics was observed in soil samples based on the calculation, the widespread distribution of antibiotics in farmland soil along Fenhe River should be addressed.
相似文献Purpose
Identifying the spatial distribution and degree of heavy metal contamination in the soils is required for urban environmental management. Magnetic measurement provides a rapid means of determining spatial distribution and degree of soil pollution and identifying various anthropogenic sources of heavy metals. The purpose of this study was to characterize the magnetic signature of heavy metal contamination and identify the sources of heavy metals in urban soils from steel industrial city.Materials and methods
A total of 115 urban topsoils from Anshan city, Northeast China, were collected and determined for magnetic properties and heavy metal concentration. Magnetic susceptibility (χlf) and saturation isothermal remanent magnetization (SIRM) were determined as proxy for ferrimagnetic mineral concentration. Magnetic minerals were identified by using Curie temperature, X-ray diffraction (XRD), and scanning electron microscope (SEM) equipped with an energy-dispersive X-ray spectrometer (EDS). The Pearson’ correlation and matrix cluster analyses were used to establish the relationship between magnetic parameters and heavy metal concentrations.Results and discussion
Urban topsoils exhibit characteristic magnetic enhancement. The magnetic measurement in particle size fractions indicates that 50–2 μm fraction has the highest low-field magnetic susceptibility (χlf), while <2 μm has the highest frequency-dependent magnetic susceptibility (χfd) value. The soil χlf and SIRM values are significantly correlated with the contents of metals (Fe, Pb, Zn, Cu, and Cr) and Tomlinson pollution load index (PLI), which indicates that χlf and SIRM could be served as better indicators for the pollution of heavy metals in the urban topsoil. Spatial distribution maps of χlf, SIRM, and PLI indicate that the pollution hotspots tend to associate with the regions within and close to steel industrial zones. XRD and Curie temperature analyses indicate that the main magnetic minerals of urban topsoils are magnetite (Fe3O4), hematite (α-Fe2O3), and metallic iron. Magnetic minerals mostly occur in the pseudo-single-domain/multidomain (PSD/MD) grain size range, which is the dominant contributor to the magnetic enhancement of topsoils. SEM observation reveals that magnetic particles in soils exist in irregular-shaped particles and spherule. Results reveal that heavy metals from industrially derived and traffic emissions coexist with coarse-grained magnetic phases.Conclusions
It is concluded that the magnetic measurement could be regarded as a proxy tool to detect the level of heavy metal pollution and identify the source of heavy metals in urban soils. Magnetic properties provide a fast and inexpensive method to map the spatial distribution of long-term pollution from steel industrial origin on region scale.Purpose
The present work concerns the distribution of ten heavy metals (Sb, As, Cd, Cr, Cu, Hg, Mn, Ni, Pb, and Zn) in the surrounding agricultural soils of the world largest antimony (Sb) mine in China. The objective is to explore the degree and spatial distribution of heavy metal pollution of the Sb mine-affected agricultural soils. The presented data were compared with metal concentrations in soils from mining and smelting sites in China and other countries. 相似文献Purpose
The Yellow River Delta, an active land-ocean interaction area, will develop into a large eco-economic region in East China during the coming decade. It is necessary to assess the geochemical features of heavy metals in the soils. The objectives of this research were to evaluate the concentrations and distribution of heavy metals (Cr, Ni, Cu, Zn, Pb, and Cd) in soil profiles of the area and to identify their sources.Materials and methods
Horizon samples were collected based on pedogenic features from bottom to top in each profile to a depth of 120 cm and a total of 92 samples were collected. The sampling sites were grouped into four lines from inland to coastal area with three land use types (cotton field, cereal field, and wetland). The concentrations of Cr, Ni, Cu, Zn, Pb, and Cd were measured by inductively coupled plasma-mass spectrometry. Iron oxide fractions in the soil were extracted by oxalate-oxalic acid and dithionite-citrate-bicarbonate. X-ray diffraction (XRD) was used to determine the mineral composition of the soils. Multivariate statistical analysis and historical data were employed to identify the possible sources of these heavy metals.Results and discussion
The mean concentrations of heavy metals were elevated along the Yellow River region and in the southern part of the delta; however, they were generally lower than the Chinese guideline values. As for the depth distribution of heavy metals in soil profiles, the maximum values of Cr, Ni, Cu, Zn, and Cd in middle horizon of cotton field were almost twice than those in surface horizon. The iron oxides and XRD analysis indicated that the trace elements accumulation appeared to be related with the contents of crystalline iron oxide and layer silicates. Historical data from suspended sediments of the Yellow River and principal component analysis (PCA) implied that most of the metals (Cr, Ni, Cu, and Zn) were sourced from natural alluviation and sedimentation.Conclusions
The Yellow River Delta soils were slightly polluted by heavy metals the Yellow River Delta. The special pedogenic horizon characterized by higher iron oxides and layered silicates minerals in the middle and lower part of the soil profile was found with heavy metals enrichment, which required to be studied further. Suspended sediments transported by the Yellow River were suggested to be one of the major sources for the heavy metals accumulation in the basal soils of this region. 相似文献To identify the sources and levels of contamination with anthropogenically derived heavy metals (HMs) for appropriate pollution control. We quantified anthropogenic influences with respect to HM pollution in soil, based on multiple pollution indices and cluster analysis derived from the results of an annual nationwide survey conducted in Korea.
MethodsContamination levels of HMs in soils were quantitatively evaluated using multiple pollution indices: contamination factor (CF), geo-accumulation index (Igeo), Nemerow’s integrated pollution index (NIPI), and pollution load index (PLI). Hierarchical cluster analysis was conducted to elucidate the correlations between HMs and contamination sources. A total of 2214 HM concentration data including six contamination sources were used to evaluate the pollution state of anthropogenic effects of HMs.
ResultsThe CFs for Zn and Cu revealed a broad enrichment of these HMs in all pollution sources. Scrap recycling sites (SRS) had the highest likelihood of pollutant distribution in soil surfaces. NIPI and PLI varied with the extent of anthropogenic activities or land use, especially in SRS, waste disposal sites (WDS), transport maintenance sites (TMS), and industrial sites (INS), and anthropogenic sources were divided into three discrete clusters: INS-TMS-LDS (land development sites), SRS-WDS, and vicinities of industrial sites (VIS).
ConclusionOur results confirmed that soil pollution indices combined with cluster analysis were useful to identify sources of anthropogenic HMs in urban soil, as well as to assess the levels of HM contamination.
相似文献Purpose
The effect of soil heavy metals on crops and human health is an important research topic in some fields (Agriculture, Ecology et al.). In this paper, the objective is to understand the pollution status and spatial variability of soil heavy metals in this study area. These results can help decision-makers apportion possible soil heavy metal sources and formulate pollution control policies, effective soil remediation, and management strategies.Materials and methods
A total of 212 topsoil samples (0–20 cm) were collected and analyzed for eight heavy metals (Cd, Hg, As, Cu, Pb, Cr, Zn, and Ni) from agricultural areas of Yingbao County in Lixia River Region of Eastern China, by using four indices (pollution index (PI), Nemerow pollution index (PIN), index of geo-accumulation (I geo), E i /risk index (RI)) and cluster analysis to assess pollution level and ecological risk level of soil heavy metals and combining with geostatistics to analyze the concentration change of heavy metals in soils. GS+ software was used to analyze the spatial variation of soil heavy metals, and the semi-variogram model is the main tool to calculate the spatial variability and provide the input parameters for the spatial interpolation of kriging. Arcgis software was used to draw the spatial distribution of soil heavy metals.Results and discussion
The result indicated that the eight heavy metals in soils of this area had moderate variations, with CVs ranging from 23.51 to 64.37 %. Single pollution index and Nemerow pollution index showed that about 2.7 and 1.36 % of soil sampling sites were moderately polluted by Cd and Zn, respectively. The pollution level of soil heavy metals decreased in the order of Cd?>?Zn?>?Pb?>?As?>?Cu?>?Cr?>?Ni?>?Hg. The I geo values of heavy metals in this area decreased in the order of Zn?>?Cd?>?As?>?Pb?>?Cu?>?Cr?>?Hg?>?Ni. According to the E i index, except Cd that was in the moderate ecological risk status, other heavy metals in soils were in the light ecological risk status, and the level of potential ecological risk (RI) of soil sampling sites of the whole area was light.Conclusions
The results of four indices and the analysis of spatial variation indicated that the contents of Cd and Zn were contributed mainly by anthropogenic activities and located in the south-east of this study area. However, the contents of Hg, As, Cu, Pb, Cr, and Ni in soils were primarily influenced by soil parent materials.The purpose of this study is to study the major sources, concentrations, and distributions of polycyclic aromatic hydrocarbons (PAHs) in three different types of green space in Shanghai. In addition, we will quantitatively assess the burden of PAHs in the soil, as well as the potential carcinogenic risk of PAHs in humans. These results will provide valuable information for soil remediation and human health risk management.
Materials and methodsA total of 166 surface soil samples were collected in parks, greenbelts, and woodlands. Soils were extracted using accelerated solvent extraction (ASE). PAHs were analyzed by gas chromatography-mass spectrometry (GC-MS). The positive matrix factorization (PMF) model was used to identify major PAH emission sources and quantitatively assess their contributions to PAHs. The incremental lifetime cancer risk (ILCR) was used to quantify the potential health risk of PAHs.
Results and discussionThe average concentrations of ∑15 PAHs are 227?±?95 ng g?1, 1632?±?251 ng g?1, and 1888?±?552 ng g?1 in the woodland, park, and greenbelt soils, respectively. The PMF results show that biomass (33%), coal (21%), vehicles (17%), natural gas (14%), oil (9%), and coke (7%) are the dominant sources of PAHs in the park soils. Diesel (40%), tire debris (30%), biomass (15%), gasoline (9%), and oil (5%) are the main sources in the greenbelt soils. Biomass (48%), vehicles (37%), and coal (15%) are the main sources in the woodland soils. The ILCRs of adults and children who are exposed to PAHs in soils range from 9.53?×?10?8~1.42?×?10?5.
ConclusionIn three types of green space in Shanghai, the dominant PAHs are high–molecular weight (HMW) compounds (≥?4 rings). This may be due to the proximity of the sampling site to emission sources. In addition, low–molecular weight (LMW) PAHs (with 2–3 rings) are relatively unstable, and these compounds are prone to volatilization and degradation. Source identification indicates that biomass combustion is the most dominant PAH source in the park and woodland soils, while vehicles are the dominant PAH source in the greenbelt soils. The ILCRs of adults and children indicate potential health risks, and children have a greater health risk than adults.
相似文献