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Chromium (Cr) contamination is widely distributed in agricultural soil and poses a threat to agricultural sustainability. Developing integrated models based on soil survey data can be an effective measure to accurately predict the spatial distribution of Cr. Focused on an agriculturally dominated area, this study presents a novel hybrid mapping model that combines land use regression (LUR) and geostatistical methods to predict Cr distribution in topsoil and examines the influence of various influencing factors on Cr content. The LUR model was first adopted to screen the influencing factors for Cr predictions. Then LUR, was combined with ordinary Kriging (OK_LUR) and geographically weighted regression Kriging (GWRK_LUR) to describe the spatial distribution of Cr. Results showed that Cr distribution was profoundly influenced by soil Cu and Zn content, the distance between the soil sampling and livestock farm, orchard areas within 100 m, and population density within 1000 m. The developed GWRK_LUR model significantly improved the prediction accuracy of the OK_LUR and LUR models (by 9% and 16%, respectively). This model provides a novel route to account for the spatial distribution of Cr in agricultural topsoil at a regional scale, which has potential application in pollution remediation. [ABSTRACT FROM AUTHOR]

The potential negative impacts of organochlorine pesticides on the environment and human health continue to receive attention. In order to study the spatial distribution characteristics of organochlorine pesticides in the inland alpine region, researchers collected soil and water samples in the Huangshui River Basin of the Qinghai–Tibetan Plateau and tested them for organochlorine pesticide residues represented by dichlorodiphenyltrichloroethane (DDT) and hexachlorohexane (HCH). The study identified the sources of OCPs by component analysis. We also constructed the LEVEL III model, applicable to the Huangshui River Basin, and used it to study the migration patterns of OCPs in various environmental media. OCPs were detected at low levels in the study area environment. The results of the OCPs source analysis show that there are both historical residuals and new sources in the region. Residual DDTs may originate from the mixture of technical DDTs and dicofol, and HCHs may originate from lindane or technical HCH. DDTs are mainly stored in soil, the input and output pathways are mainly atmospheric advection input and output, and its transport behavior in the environment is mainly air–soil exchange. Carcinogens in the study area pose little threat to people exposed to contaminated soil and contaminated water, but the cancer risk to children is greater than to adults. This study is helpful to managers of regional pesticide management and control. [ABSTRACT FROM AUTHOR]

Development of tin (Sn)‐based perovskite solar cells (PSCs) largely lags behind that of lead counterparts due to fast crystallization process of Sn perovskite and numerous defects in both bulk and surface of Sn perovskite films. Herein, this work reports a facile strategy of introducing 4‐fluorobenzylammonium iodide (FBZAI) as additives into Sn perovskite precursor to synergistically modulate the roles of benzylamine and fluorine in Sn‐based PSCs. Incorporation of FBZAI can increase crystallinity, passivate defects, and inhibit the oxidation of Sn2+, leading to suppression of nonradiative recombination and enhancement of charge transport and collection in devices. As a result, the best‐performing Sn‐based PSC with the FBZAI additive achieves the maximum PCE of 13.85% with the enhanced fill factor of 77.8% and open‐circuit voltage of 0.778 V. Our unencapsulated device exhibits good stability by maintaining 95% of its initial PCE after 160 days of storage. [ABSTRACT FROM AUTHOR]

Unsustainable human management has negative effects on cropland soil organic carbon (SOC), causing a decrease in soil health and the emission of greenhouse gas. Due to contiguous fields, large-scale mechanized operations are widely used in the Northeast China Plain, which greatly improves production efficiency while decreasing the soil quality, especially for SOC. Therefore, an up-to-date SOC map is needed to estimate soil health after long-term cultivation to inform better land management. Using Quantile Regression Forest, a total of 396 soil samples from 132 sampling sites at three soil depth intervals and 40 environmental covariates (e.g., Landsat 8 spectral indices, and WorldClim 2 and MODIS products) selected by the Boruta feature selection algorithm were used to map the spatial distribution of SOC in the cropland of the Northeast Plain at a 90 m spatial resolution. The results showed that SOC increased overall from the southern area to the northern area, with an average of 17.34 g kg−1 in the plough layer (PL) and 13.92 g kg−1 in the compacted layer (CL). At the vertical scale, SOC decreased, with depths getting deeper. The average decrease in SOC from PL to CL was 3.41 g kg−1. Climate (i.e., average temperature, daytime and nighttime land surface temperature, and mean temperature of driest quarter) was the dominant controlling factor, followed by position (i.e., oblique geographic coordinate at 105°), and organism (i.e., the average and variance of net primary productivity in the non-crop period). The average uncertainty was 1.04 in the PL and 1.07 in the CL. The high uncertainty appeared in the area with relatively scattered fields, high altitudes, and complex landforms. This study updated the 90 m resolution cropland SOC maps at spatial and vertical scales, which clarifies the influence of mechanized operations and provides a reference for soil conservation policy-making. [ABSTRACT FROM AUTHOR]