Impact of Long-Term Irrigation with Treated Sewage on Soil Magnetic Susceptibility and Organic Matter Content in North China

Dielectric barrier discharge plasma for the remediation of microplastic-contaminated soil from landfill

The huge amount of plastic waste accumulated in landfills has caused serious microplastic (MP) pollution to the soil environment, which has become an urgent issue in recent years. It is challenging to deal with the non-biodegradable MP pollutants in actual soil from landfills. In this study, a coaxial dielectric barrier discharge (DBD) system was proposed to remediate actual MP-contaminated landfill soil due to its strong oxidation capacity. The influence of carrier gas type, applied voltage, and air flow rate was investigated, and the possible degradation pathways of MP pollutants were suggested. Results showed the landfill soil samples contained four common MP pollutants, including polyethylene (PE), polypropylene (PP), polystyrene (PS), and polyvinyl chloride (PVC) with sizes ranging from 50 to 1500 μm. The MP pollutants in the soil were rapidly removed under the action of reactive oxygen species (ROS) generated by DBD plasma. Under the air flow rate of 1500 mL min^-1, the maximum remediation efficiency represented by mass loss reached 96.5% after 30 min treatment. Compared with nitrogen, when air was used as the carrier gas, the remediation efficiency increased from 41.4% to 81.6%. The increased applied voltage from 17.5 to 24.1 kV could also promote the removal of MP contaminants. Sufficient air supply was conducive to thorough removal. However, when the air flow rate reached 1500 mL min^-1 and continued to rise, the final remediation efficiency would be reduced due to the shortened residence time of ROS. The DBD plasma treatment proposed in this study showed high energy efficiency (19.03 mg kJ^-1) and remediation performance (96.5%). The results are instructive for solving MP pollution in the soil environment.

Vertical distribution and affecting factors of Escherichia coli over a 0-400 cm soil profile irrigated with sewage effluents in northern China

Quantification and evaluation of the spatial distribution and the primary factors that affect Escherichia coli (E. coli) distribution in soils is important to assess soil pollution and potential contamination of groundwater. However, little information is available on distribution of E. coli in deep soil layers. To analyze the spatial distribution and factors affecting E. coli over a 0-400 cm soil profile, soil samples were collected from two land use type in the sewage irrigation fields. The primary factors dominating the spatial distribution of E. coli were quantified by the model of principal component analysis with multiple linear regression (PCA-MLR). The results indicated that the number of E. coli under cropland decreased greatly with soil depth. The average number of E. coli over the 0-400 cm profile under forestland was 49 × 10⁴ colony-forming unit/g (cfu/g), which was significantly higher than that under cropland (20 × 10⁴ cfu/g). For forestland and cropland, the average number of E. coli at depths of 300-400 cm decreased by 85% and 88%, respectively, compared to that at depths of 0-100 cm. The presence of E. coli at the depths of 300-400 cm was at high level (forestland: 3 × 10⁴ cfu/g; cropland: 2 × 10⁴ cfu/g) for the potential risks of shallow groundwater. The PCA-MLR model estimated that the factors of soil organism, soil salt and land type use contributed 28%, 29% and 43%, respectively, to the distribution of E. coli. According to the Monte Carlo simulation, the average number of E. coli over the 0-400 cm profile was 46 ± 17 × 10⁴ cfu/g in the sewage irrigated area, and the interval distribution with a probability of 95% varied between 14 × 10⁴ cfu/g and 78 × 10⁴ cfu/g. The findings of this study are useful for understanding negative effects of sewage irrigation on pathogens in deep soil and are critical to assess the potential risks of groundwater pollution.

Effect of Sewage Irrigation on the CT-Measured Soil Pore Characteristics of a Clay Farmland in Northern China

Sewage irrigation has a strong influence on the physical, chemical, and biological properties of soil. However, the effects of sewage irrigation on the pore characteristics of soil are not well understood. This study compares the effects of sewage irrigation and groundwater irrigation on computed tomography (CT)-measured pore parameters and examines the relationships between CT-measured pore parameters and soil physicochemical and microbial properties. Intact soil cores were collected from S1 irrigated with sewage for 25 years, S2 irrigated with sewage for 52 years, and CK irrigated with groundwater. Various soil pore characteristics were determined, including the total pore number, macropore number (>1 mm diam.), coarse mesopore number (0.264⁻1 mm diam.), total porosity, macroporosity, coarse mesoporosity, and circularity. The results indicated that sewage irrigation significantly affected soil pore number and porosity. Compared with S1 and S2, CK exhibited a higher average total pore number (91), macropore number (40), coarse mesopore number (51), total porosity (2.08%), macroporosity (1.90%), and coarse mesoporosity (0.18%) throughout the 50⁻350 mm layer. At depths of 200⁻350 mm, S2 exhibited the lowest average total pore number (33), macropore number (13), coarse mesopore number (21), total porosity (0.42%), macroporosity (0.35%), and coarse mesoporosity (0.07%) among the three sites. In addition, the average pore numbers and porosity at depths of 200⁻350 mm decreased with increasing sewage irrigation time. There were significant positive correlations between pore features (including pore numbers and porosity) and soil properties (phosphorus content and fungi numbers). Our results suggest that decreased macropore numbers and macroporosity in the sewage-irrigated farmland may strongly intensify the accumulation of metals and nutrients in the upper layer. The findings of this study are useful for understanding the negative effects of sewage irrigation on soil pore structure and are critical for developing sustainable strategies in agriculture.

Characteristics of soil C:N ratio and δ13C in wheat-maize cropping system of the North China Plain and influences of the Yellow River

To better understand the characteristics of soil organic matter (SOM) in the North China Plain, we evaluate the large scale variations of soil organic carbon (SOC), total nitrogen (TN), carbon to nitrogen (C:N) ratio and stable carbon isotopic compositions (δ¹³C) in SOC over 0-100 cm. To assess the influence of the Yellow River, 31 sites are selected from the wheat-maize double cropping system, and grouped into two: 10 sites near and 21 sites far from the river. Our data show that mean soil C:N ratio is low (7.6-9.9) across the region, and not affected by the Yellow River. However, SOC and TN are significantly (P < 0.05) lower in subsoil near the Yellow River (2.0 and 0.2-0.3 g kg^-1 for SOC and TN) than far away (3.1 and 0.4 g kg^-1); δ¹³C is significantly more negative below 60 cm near the river (-23.3 to -22.6‰) than far away (-21.8 to -21.4‰). We estimate that the contributions of wheat and maize to SOC are 61.3-68.1% and 31.9-38.8%, respectively. Our analyses indicate that the overall low levels of SOC in the North China Plain may be associated with the low soil C:N ratio and less clay content. The hydrological processes may also partly be responsible, particularly for those near the Yellow River.

Identification of Heavy Metal Pollution Derived From Traffic in Roadside Soil Using Magnetic Susceptibility

The study integrates surface and vertical distribution of magnetic susceptibility and heavy metal contents (Pb, Cu, Zn and Fe) to characterize the signature of vehicle pollutants in roadside soils at Linfen city, China. Sites with reforestation and without vegetation cover were investigated. The results showed that magnetic susceptibility and heavy metal contents were higher at the roadside without trees than in the reforest belt. The variations of magnetic susceptibility and heavy metal contents decreased both with distance and with depth. The maximum value was observed at 5-10 m away from the roadside edge. The vertical distribution in soil revealed accumulation of pollutants in 0-5 cm topsoils. The average contents were higher than the background values and in the order Fe (107.21 g kg^-1), Zn (99.72 mg kg^-1), Pb (90.99 mg kg^-1), Cu (36.14 mg kg^-1). Coarse multi domain grains were identified as the dominating magnetic particles. Multivariate statistical and SEM/EDX analyses suggested that the heavy metals derived from traffic sources. Trees act as efficient receptors and green barrier, which can reduce vehicle derived pollution.