Nitrate leaching from soil presents a significant threat to soil health, as it can result in nutrient loss, soil acidification, and structural damage. It is crucial to quantify the spatial heterogeneity of nitrate leaching and its drivers. A total of 509 observational data points regarding nitrate leaching in northern China were collected, capturing the spatial and temporal variations across crops such as winter wheat, maize, and greenhouse vegetables. A machine learning (ML) model for predicting nitrate leaching was then developed, with the random forest (RF) model outperforming the support vector machine (SVM), extreme gradient boosting (XGBoost), and convolutional neural network (CNN) models, achieving an R-2 of 0.75. However, the performance improved significantly after integrating the four models with Bayesian optimization (all models had R-2 > 0.56), which realized quantitative prediction capabilities for nitrate leaching loss concentrations. Moreover, the XGBoost model exhibited the highest fitting accuracy and the smallest error in estimating nitrate leaching losses, with an R-2 value of 0.79 and an average absolute error (MAE) of 3.87 kg/ha. Analyses of the feature importance and SHAP values in the optimal XGBoost model identified soil organic matter, chemical nitrogen fertilizer input, and water input (including rainfall and irrigation) as the main indicators of nitrate leaching loss. The ML-based modeling method developed overcomes the difficulty of the determination of the functional relationship between nitrate loss intensity and its influencing factors, providing a data-driven solution for estimating nitrate-nitrogen loss in farmlands in North China and strengthening sustainable agricultural practices.

Land-use change may significantly influence streamflow. The semi-empirical model PhosFate was used to analyze the impact of land use and climate change on streamflow by choosing the Guishui watershed as a pilot site and then expanding, applying it to all of North China. The Guishui watershed (North Beijing, China) has experienced a dramatic decline in its streamflow in recent decades. Parallel to this, significant land-use change has happened in this area; afforestation programs have increased forest cover from 41% (1980) to 59% (2013) and a similar increase in forest cover can also be observed in North China. Managing flow decline requires separating climatic and direct human-influenced effects. The results showed the following: (1) Afforestation is a major factor that decreased total flow in the Guishui watershed from 1996 to 2014; total flow increased by around 24% more than the actual dataset in the constant scenario (no afforestation) and decreased by 5% more than the actual dataset in the forest scenario (all agriculture land use transferred to forests). (2) When forest coverage increases, the Qinghai-Tibet Plateau and the Loess Plateau are the most sensitive areas regarding total flow in North China; the total flow change rate increased by up to 25% in these two areas when land use shifted from sparse vegetation to mixed forests. After analyzing the contributions of these two factors, we formulated recommendations on future afforestation practices for North China. In the central-north and northwest districts, the annual precipitation is under 520 mm and 790 mm, respectively, and the practice of afforestation should be more carefully planned to prevent severe damage to streams. This research also proved that the PhosFate model can be used in North China, which would be a practical tool for watershed management.

The light absorption black carbon (BC) and brown carbon (BrC) are two important sources of uncertainties in radiative forcing estimate. Here we investigated the light absorption enhancement (E-abs) of BC due to coated materials at an urban (Beijing) and a rural site (Gucheng) in North China Plain (NCP) in winter 2019 by using a photoacoustic extinctiometer coupled with a thermodenuder. Our results showed that the average (+/- 1s) E-abs was 1.32 (+/- 0.15) at the rural site, which was slightly higher than that at the urban site (1.24 +/- 0.15). The dependence of E-abs on coating materials was found to be relatively limited at both sites. However, E-abs presented considerable increases as a function of relative humidity below 70%. Further analysis showed that E-abs during non-heating period in Beijing was mainly caused by secondary components, while it was dominantly contributed by enhanced primary emissions in heating season at both sites. In particular, aerosol particles mixed with coal combustion emissions had a large impact on E-abs (>1.40), while the fresh traffic emissions and freshly oxidized secondary OA (SOA) had limited E-abs (1.00-1.23). Although highly aged or aqueous-phase processed SOA coated on BC showed the largest E-abs, their contributions to the bulk absorption enhancement were generally small. We also quantified the absorption of BrC and source contributions. The results showed the BrC absorption at the rural site was nearly twice that of urban site, yet absorption Angstrom exponents were similar. Multiple linear regression analysis highlighted the major sources of BrC being coal combustion emissions and photochemical SOA at both sites with additional biomass burning at the rural site. Overall, our results demonstrated the relatively limited winter light absorption enhancement of BC in different chemical environments in NCP, which needs be considered in regional climate models to improve BC radiative forcing estimates. (C) 2021 Elsevier B.V. All rights reserved.

The properties of summer radiation and aerosols were studied at Xinzhou, a suburban site on the North China Plain (NCP) by using ground-based measurements in 2014. The radiation detections under clear and cloudy skies showed that longwave radiation presented a sigmate pattern, with a maximum of 392.6 W m(-2) at 1700 local standard time (LST) associated with the cloud radiative forcing, and a minimum of 360.0 W m(-2) at 0600 LST when the lowest surface temperature (17.1 degrees C) occurred. Solar radiation, including global, direct, diffuse, photosynthetically active, ultraviolet-A, and ultraviolet-B, exhibited a single peak at similar to 1300 LST. A bimodal size distribution, with fine mode aerosols showing a peak between 0.1 and 0.2 mu m and coarse mode aerosols showing a peak at similar to 5 mu m, was observed at Xinzhou. The dominant aerosol type was black carbon coating on coarse particles (85.7%) for the cases with aerosol optical depth at 400 nm (AOD) greater than 0.4, leading to a lower single scattering albedo (0.81) than the typical value (similar to 0.90) at the other stations on the NCP. The mean values of EAE and AAE (extinction and absorption angstrom ngstrom exponent, respectively) were 1.14 +/- 0.15 and 0.58 +/- 0.28 for the aerosol measurements. The average of instantaneous aerosol direct radiative forcing at the bottom of the atmosphere was -138.9 +/- 33.0 W m(-2)for the cases with AOD > 0.4. The results in this study are expected to improve understanding at suburban sites on the NCP of aerosol properties and their impacts on regional radiation budgets.

Light-absorbing components of atmospheric aerosols have gained particular attention in recent years due to their climatic and environmental effects. Based on two-year measurements of aerosol absorption at seven wavelengths, aerosol absorption properties and black carbon (BC) were investigated in the North China Plain (NCP), one of the most densely populated and polluted regions in the world. Aerosol absorption was stronger in fall and the heating season (from November to March) than in spring and summer at all seven wavelengths. Similar spectral dependence of aerosol absorption was observed in non-heating seasons despite substantially strong absorption in fall. With an average absorption Angstrom exponent (alpha) of 1.36 in non-heating seasons, freshly emitted BC from local fossil fuel burning was thought to be the major component of light-absorbing aerosols. In the heating season, strong ultraviolet absorption led to an average alpha of 1.81, clearly indicating the importance of non-BC light-absorbing components, which were possibly from coal burning for domestic heating and aging processes on a regional scale. Diurnally, the variation of BC mass concentrations experienced a double-peak pattern with a higher level at night throughout the year. However, the diurnal cycle of alpha in the heating season was distinctly different from that in non-heating seasons. a peaked in the late afternoon in non-heating seasons with concomitantly observed low valley in BC mass concentrations. In contrast, alpha peaked around the midnight in the heating season and lowered down during the daytime. The relationship of aerosol absorption and winds in non-heating seasons also differed from that in the heating season. BC mass concentrations declined while alpha increased with increasing wind speed in non-heating seasons, which suggested elevated non-BC light absorbers in transported aged aerosols. No apparent dependence of alpha on wind speed was found in the heating season, probably due to well mixed regional pollution. Pollution episodes were mostly encountered under low winds and had a low level of alpha, implying aerosol absorption should be largely attributed to freshly emitted BC from local sources under such conditions. Extensive field campaigns and long-term chemical and optical measurements of light-absorbing aerosols are needed in the future to further advance our understanding on optical properties of light-absorbing aerosols and their radiative forcing in this region. (C) 2016 The Authors. Published by Elsevier Ltd.