Remote sensing-based prediction of organic carbon in agricultural and natural soils influenced by salt and sand mining using machine learning.

It is important to keep soil organic carbon (SOC) in balance to ensure soil health and quality. In this manner, mining activities have crucial impacts on SOC stocks, especially in semi-arid and arid regions such as Iran. For this purpose, SOC was measured at 180 randomly selected points in both natural and agricultural soils in the central part of Iran. Machine learning methods, such as GEP (Genetic Expression Programming), SVR (Support Vector Regression), and ANNs (Artificial Neural Networks), were developed and employed to estimate SOC for all sampled points, including both natural and agricultural soils. Following that, topography and remotely sensed data were employed as input variables to improve SOC prediction influenced by mining. The remotely sensed data and topography factors were extracted from Landsat 9 images and Digital Elevation Models (DEMs), respectively. Input variables were considered in three scenarios, including the use of topography factors (scenario I), the use of remote sensing data (scenario II), and the use of both topography factors and remote sensing data (scenario III). The results of this study showed that the most effective model for predicting SOC across all sampled data was SVR (ME = -0.1539%, R2 = 0.642 and RMSE = 0.620%) when employing scenario III. Furthermore, the results indicated that the optimal method for both natural and agricultural soils was the SVR method when employing scenario III. Further analysis through mapping SOC contents showed that mining activities influenced the distribution of SOC in the studied region. Overall, the predicted maps of SOC contents indicated that lower SOC contents were predominantly distributed in the vicinity of salt and sand mines, particularly in salt-rich areas, for both natural and agricultural soils.

Microplastics pollution in agricultural farms soils: preliminary findings from tropical environment (Klang Valley, Malaysia).

The aim of this research is to investigate the occurrence, characteristics, and potential sources of microplastic pollution at four agricultural farms in Malaysia's tropical region of Klang Valley. The mean number of microplastic particles found in the agricultural soils were 2.1 ± 0.44 to 3.4 ± 1.2 particles/kg. Farms B and D had the lowest and highest total microplastic particle counts, 1.5 and 6.0 particles/kg, respectively, which was in line with the intensity of plastic consumption at these farms. Microplastics particle sizes ranged from 16.7 to 1.246 µm, attributed to their extensive breakdown processes. The microplastic particle shapes (film, fiber, and fragment) and colors (black, white, red, and blue) from the soil samples reflected the type of plastic products used and unmanaged plastic waste at these farms. Plastic nets, mulching films, and unmanaged plastics waste constituted the major microplastics sources at these farms. Our findings confirm microplastic pollution in tropical agricultural soils as well as the need to assess the negative effects of long-term plastic use on agricultural soils.

Seasonal variation of potentially toxic metal contamination in Yamuna riverine ecosystem, Delhi, India.

The River Yamuna in Delhi region, the National Capital Territory (NCT) of India, carries potentially toxic metals such as Cr, Pb, Mn, Mg, Hg, Fe and Zn. These contaminants are discharged mainly from industrial wastes, agricultural and household activities and domestic sewage. A total of 12 stations (2.5 to 3.5 km apart from each other) were selected for the study, covering the upstream and downstream areas of river Yamuna in Delhi. The investigated sites were evaluated for significant difference between upstream and downstream locations of river Yamuna in three different time periods (June, October, February). Metal contamination were measured in water, sediments (2 µm) and nearby agriculture soil of the river Yamuna, and found with high metal loads as compared with the international standards, chiefly in the downstream sites as the river flows through the Delhi stretch. The multivariate statistical analysis revealed spatial and temporal variations in the metal concentrations which suggest seasonal variation and common point source of some metals while different sources of other metals. The contamination of the river water and adjoining agriculture soils points towards possible entry of these metals into the food chain. The study indicates that considering the current status of metal pollution, the surface water is not in good conditions for use as drinking purpose because of the high concentrations of few potentially toxic metals. Our study recommends regular monitoring of toxic metals in Yamuna river water and sediments, strict ban on the domestic, agriculture and industrial waste disposal for the restoration of the river to its natural state.

Integrated evaluation of the biological response of the earthworm Eisenia fetida using two glyphosate exposure strategies: soil enriched and soils collected from crops in Southeastern Mexico.

Under laboratory conditions, the toxicological effects of pesticides tend to be less variable and realistic than under field conditions, limiting their usefulness in environmental risk assessment. In the current study, the earthworm Eisenia fetida was selected as a bioindicator for assessing glyphosate toxic effects in two different trials to solve this dilemma. In Trial 1, the worms were exposed for 7 and 14 days to concentrations of a commercial glyphosate formulation (1 to 500 mg a.i. kg-1) currently used in the field. In Trial 2, the worms were kept in nine soils collected from different plots with crops for 14 days of exposure. In both experiments, glutathione S-transferase (GST), superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx), and acetylcholinesterase (AChE) activities and contents of lipid peroxidation (LPO) were evaluated. In T1, the glyphosate formulation produced a 40% inhibition of AChE activity and a significant increase in GST, SOD, CAT, and GPx activities and LPO contents in E. fetida on day 7. In T2, higher concentrations of glyphosate were detected in the soils of soybean, papaya, and corn (0.92, 0.87, and 0.85 mg kg-1), which induced a positive correlation between the levels of glyphosate residues with GST, SOD, CAT, GPx, and LPO and a negative correlation with AChE. These findings indicate that crop soils polluted with glyphosate elicited higher oxidative stress than under laboratory conditions, confirmed by IBRv2, PCA, and AHC analyses.

Heavy Metal(oid)s Contamination and Potential Ecological Risk Assessment in Agricultural Soils.

Soil pollution caused by heavy metal(oid)s has generated great concern worldwide due to their toxicity, persistence, and bio-accumulation properties. To assess the baseline data, the heavy metal(oid)s, including manganese (Mn), iron (Fe), Cobalt (Co), nickel (Ni), copper (Cu), zinc (Zn), arsenic (As), lead (Pb), mercury (Hg), chromium (Cr), and cadmium (Cd), were evaluated in surface soil samples collected from the farmlands of Grand Forks County, North Dakota. Samples were digested via acid mixture and analyzed via inductively coupled plasma mass spectrometry (ICP MS) analysis to assess the levels, ecological risks, and possible sources. The heavy metal(oid) median levels exhibited the following decreasing trend: Fe > Mn > Zn > Ni > Cr > Cu > Pb > Co > As > Cd > Hg. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) suggested the main lithogenic source for the studied metal(oid)s. Metal(oid) levels in the current investigation, except Mn, are lower than most of the guideline values set by international agencies. The contamination factor (Cf), geo accumulation index (Igeo) and enrichment factor (EF) showed considerable contamination, moderate contamination, and significant enrichment, respectively, for As and Cd on median value basis. Ecological risk factor (Er) results exhibited low ecological risk for all studied metal(oid)s except Cd, which showed considerable ecological risk. The potential ecological risk index (PERI) levels indicated low ecological risk to considerable risk. Overall, the results indicate the accumulation of As and Cd in the study area. The high nutrients of the soils potentially affect their accumulation in crops and impact on consumers' health. This drives the impetus for continued environmental monitoring programs.

Heavy metal(loid)s in agriculture soils, rice, and wheat across China: Status assessment and spatiotemporal analysis.

Heavy metal(loid)s (HMs) accumulation in agricultural soils, rice, and wheat is of particular concern in China, while the status and spatio-temporal distribution of HMs in the soil-crops system have been rarely reported at the national scale. This study aimed to summarize the overall pollution status, spatiotemporal patterns, and drivers of HMs in agricultural soil, rice, and wheat nationwide. The metal-polluted data from 1030 agricultural soils, rice, and wheat in China were collected from the literature published from 2000 to 2022. The results showed that Cd was the most prevailing contaminant in soils based on its spatiotemporal distribution and accumulation. The pollution cases and severe pollution percentage of Cd (103 %) and Hg (128 %) show an increasing trend pattern. Mining activities are the main anthropogenic sources of agricultural soil HMs in China. Cd and Pb had the highest exceedance rate in rice (33.5 and 32.2 %) and wheat (25.8 and 30.3 %). The rice from Hunan, Fujian, and Guangxi showed the highest average concentration of Cd and Pb, respectively, while wheat samples from Hubei had the greatest exceedance rate of Pb. Besides, HMs in crops was not usually corresponding to soil HMs but increased gradually from north to south areas. Several mitigation strategies and accurate health risk assessments model of HMs based on bioavailability were also proposed and recommended. Collectively, this review provides valuable information to improve the management of farmland nationwide, optimize the accurate risk assessment, and reduce HMs pollution.

[Accumulation Characteristics and Probabilistic Risk Assessment of Cd in Agricultural Soils Across China].

To understand cadmium (Cd) pollution status and associated health risks in agricultural soils of China, a database including Cd concentrations of 160446 soil samples from 240 cities (counties) in 31 provinces was constructed based on domestic and foreign literature. The contamination factor and geochemical accumulation index were applied to explore the pollution level of Cd, and then health risks for different population groups were evaluated with the probabilistic risk assessment method based on Monte Carlo simulation. The results indicated that soil Cd concentrations in China ranged from 0.012 to 23.33 mg·kg-1, with the geometric mean of 0.473 mg·kg-1, which was 1.58 times the risk screening value of heavy metals in the soil of agricultural land (GB 15186-2018) (6.50.05). Cd pollution in agricultural soils was mainly distributed in Yunnan, Hunan, Guangxi, and Gansu provinces in China, which may have been related to the mining and smelting activities. The non-carcinogenic risks for all the population groups could be negligible, whereas there were potential carcinogenic risks for adults and seniors, with 5.81% and 4.49% of carcinogenic risk values exceeding the threshold of 1E-06 set by USEPA for adults and seniors, respectively. The results of this study provided valuable information for the pollution prevention and risk control of soil Cd pollution. To improve the accuracy of health risk assessment results, the exposure ingestion route of agricultural products and bioavailability of soil Cd should be considered in the probabilistic ecological risk assessment.

Health risk assessment of trace metal(loid)s in agricultural soil using an integrated model combining soil-related and plants-accumulation exposures: A case study on Hainan Island, South China.

Traditional health risk assessment of trace metal(loid)s (TMs) in agricultural soil exclusively considers direct soil-related exposure and may underestimate the health risks they pose. In this study, the health risks of TMs were evaluated using an integrated model that combined soil-related and plant-accumulating exposures. A detailed investigation of common TMs (Cr, Pb, Cd, As, and Hg) coupled with probability risk analysis based on a Monte Carlo simulation was conducted on Hainan Island. Our results showed that, except for As, the non-carcinogenic risk (HI) and carcinogenic risk (CR) of the TMs were all within the acceptable ranges (HI < 1.0, and CR < 1E-06) for direct soil-related exposure to bio-accessible fractions and indirect exposure via plant accumulation (CR substantially lower than the warning threshold 1E-04). We identified crop food ingestion as the essential pathway for TM exposure and As as the critical toxic element in terms of risk control. Moreover, we determined that RfDo and SFo are the most suitable parameters for assessing As health risk severity. Our study demonstrated that the proposed integrated model combining soil-related and plant-accumulating exposures can avoid major health risk assessment deviations. The results obtained and the integrated model proposed in this study can facilitate future multi-pathway exposure research and could be the basis for determining agricultural soil quality criteria in tropical areas.

Occurrence, distribution and affecting factors of microplastics in agricultural soils along the lower reaches of Yangtze River, China.

Microplastics become one of the serious persistent pollutants in terrestrial environments, and thus may represent a threat to the quality of soil and inhabiting organisms. It is imperative to understand occurrence and distribution of microplastics in soils. In this study, a large-scale field survey encompassing 85 locations along the lower reaches of Yangtze River and estuary was performed to investigate the microplastics abundance in agricultural soils. Microplastics were isolated from all the samples and all depths (0-80 cm). The microplastics abundance in soils ranged from 4.94 items/kg to 252.70 items/kg, with an average of 37.32 items/kg. The most common microplastic type detected was Polypropylene (PP) occurring as white fragments with sizes ranging from 0.1 mm to 0.5 mm. Abiotic parameters such as soil pH and texture were the general factors being associated with microplastic abundance. Meantime, traffic was indicated as one important factor to affect the microplastic abundance. Overall, the road input seems to be the main source of microplastic pollution in agricultural areas along the Yangtze River and estuary. Further studies should elucidate the original of the plastic fragments in order to establish a baseline for regulative initiatives securing environmental protection.