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Contribution of Atmospheric Nitrogen Compounds to N Deposition in a Broadleaf Forest of Southern China

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Pedosphere 2007年第3期17卷 360-365页

作者： HU Zheng-Yi XU Cheng-Kai ZHOU Li-Na SUN Ben-Hua HE Yuan-Qiu ZHOU Jing CAO Zhi-Hong State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil Science Chinese Academy of SciencesNanjing 210008 （China） College of Forest Resources and Environment Nanjing Forestry University Nanjing 210007 （China） College of Resources and Environment Northwest Sci-Tech University of Agriculture and Forestry Yangling 712100（China）

A one-year study in a typical red soil region of southern China was conducted to determine atmospheric nitrogen (N) fluxes of typical N compounds (NH3, NH4-N, NO3-N, and NO2) and contribution of three sources (gas, rainwater, and particles) to N deposition. From July 2003 to June 2004, the total atmospheric N deposition was 70.7 kg N ha-1, with dry deposition accounting for 75% of the total deposition. Dry NH3 deposition accounted for 73% of the dry deposition and 55% of the total deposition. Moreover, NO2 contributed 11% of the dry deposition and 8% of the total deposition. Reduced N compounds (NH4+ and NH3) were the predominate contributors, accounting for 66% of the total deposition. Therefore, atmospheric N deposition should be considered when soil acidification and critical loads of atmospheric deposition on soils are estimated.

关键词：华南地区阔叶林大气氮化合物 N沉积红壤

Assessment of Nitrogen Pollutant Sources in Surface Waters of Taihu Lake Region

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Pedosphere 2007年第2期17卷 200-208页

作者： XIE Ying-Xin XIONG Zheng-Qin XING Guang-Xi SUN Guo-Qing ZHU Zhao-Liang State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil Science Chinese Academy of Sciences Nanjing 210008 （China） National Engineering Research Center for Wheat Henan Agricultural University Zhengzhou 450002 （China） Department of Physics Portland State University Portland Oregon 97207 （USA）

The nitrogen (N) pollution status of the 12 most important rivers in Changshu, Taihu Lake region was investigated. Water samples were collected from depths of 0.5-1.0 m with the aid of the global positioning system (GPS). The seasonal variations in the concentrations of different N components in the rivers were measured. Using tension-free monolith lysimeters and 15N-labeled fertilizer, field experiments were carried out in this region to determine variations of 15N abundance of NO3- in the leachate during the rice and wheat growing seasons, respectively. Results showed that the main source of N pollution of surface waters in the Taihu Lake region was not the N fertilizer applied in the farmland but the urban domestic sewage and rural human and animal excreta directly discharged into the water bodies without treatment. Atmospheric dry and wet N deposition was another evident source of N pollutant of the surface waters. In conclusion, it would not be correct to attribute the N applied to farmlands as the source of N pollution of the surface waters in this region.

关键词：太湖表层水污染氮污染污染源

Application of Equilibrium Partitioning Approach to the Derivation of Sediment Quality Guidelines for Metals in Dianchi Lake

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Pedosphere 2007年第3期17卷 284-294页

作者： CHEN Yun-Zeng YANG Hao ZHANG Zhen-Ke QIN Ming-Zhou JIN Feng LU Jun-Jie Institute of Resources and Environment Henan University Kaifeng 475001 （China） State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil Science Chinese Academy of SciencesNanjing 210008 （China） College of Geography Nanjing Normal University Nanjing 210097 （China） key laboratory of Coast and Island Development of MOE Nanjing University Nanjing 210093 （China）

For the past 20 years, numerous studies have been carried out on the application of equilibrium partitioning approach (EqPA) for the derivation of sediment quality guidelines (SQGs). However, for metals, few Equilibrium-partitioning-based numerical SQGs have been developed or are currently available because of the confounding factors mediating the bioavailability of metals. A study was conducted at Dianchi Lake, which is a heavily eutrophicated lake on the Yunnan-Guizhou Plateau, China with the focus on the measurement of partitioning coefficient (Kp) and SQGs derivation and normalization to acid volatile sulfide (AVS), fine material, and organic carbon. Using new normalization methods, SQGs were formulated for seven metals including copper, zinc, lead, cadmium, chromium, mercury, and arsenic in Dianchi Lake. In Dianchi Lake sediments, the fine material contributed 25.4%-36.0% to the SQG values, with the largest contribution to the SQG value of mercury; AVS contributed 2.9%-75.0% to the SQG values, with the largest contribution to the SQG value of cadmium. This indicated that the fine material and the AVS were the most important controlling factors to the bioavailability of mercury and cadmium, respectively. The contribution of total organic carbon (TOC) to the SQG values of copper and lead was 3.8% and 7.1%, respectively, indicating that at relatively lower concentrations, the contribution of TOC was not significant. In addition to normalization methods, appropriate procedures for the application of EqPA including sample collection, storage, and analysis are also essential to improve the reliability of SQGs. The normalized Dianchi Lake SQGs were higher than most of the empirically based SQGs developed in North America, but lower than Hong Kong interim SQGs except for cadmium and arsenic. The differences could be attributed to the approaches used for derivation of SQGs and the water quality criteria adopted and the differences in the physical and chemical characteristics of the sediments.

关键词：滇池湖泊水体沉积物环境质量基准平衡分配法金属污染

Mapping soil erodibility in southeast China at 250 m resolution:Using environmental variables and random forest regression with limited samples

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International soil and Water Conservation Research 2022年第1期10卷 62-74页

作者： Zhiyuan Tian Feng Liu Yin Liang Xuchao Zhu State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing210008China

soil erodibility(K factor)mapping has been accomplished mainly by soil map-linked or geo-statistical interpolation.However,the resulting maps usually have coarse spatial resolution at a regional scale.The objectives of this study were a)to map the K factors using a set of environmental variables and random forest(RF)model,and b)to identify the important environmental variables in the predictive mapping on a regional scale.We collected 101 surface soil samples across southeast China in the summer of 2019.For each sample,we measured the particle size distribution and organic matter content,and calculated the K factors using the nomograph equation.The hyperparameters of RF were optimized through 5-fold cross validation(m_(ay)=2,n_(tree)=500,p=63),and a digital map with 250 m resolution was generated for the K factor.The lower and upper limits of a 90% prediction interval were also pro-duced for uncertainty analysis.It was found that the important environmental variables for the K factor prediction were relief,climate,land surface temperature and vegetation indexes.Since the existing K factor map has an average polygonal area of 6.8 km^(2),our approach dramatically improves the spatial resolution of the K factor to 0.0625 km^(2).The new method captures more distinct differences in spatial details,and the spatial distribution of the K factor derived from RF prediction followed a similar pattern with kriging interpolation.This suggests the presented approach in this study is effective for mapping the K factor with limited sampling data.

关键词： soil K factor Predictive soil mapping Machine learning Uncertainty

Improving inherent soil productivity underpins agricultural sustainability

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Pedosphere 2023年第1期33卷 3-5页

作者： Jia Bao ZHANG State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of SciencesNanjing 210008(China)

There is now increasing attention to how to raise global food production and security due to the expanding population worldwide.Stable and high yield of crops depends on soil quality improvement,which relies on inherent soil productivity increase.Improvement in inherent soil productivity can provide a range of benefits for soil structure,microorganisms,nutrient cycling,and carbon sequestration.The underlying mechanisms related to inherent soil productivity improvement under different agricultural management practices on large scales need to be further clarified.Therefore,to achieve agricultural sustainability,efforts need to focus on developing technologies related to straw return,tillage management,and cover cropping and understanding their relationships with inherent soil productivity improvement.

关键词： soil crops return

基于反应成膜技术的水基丙烯酸酯乳液包衣控释肥料的研制(英文)

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Chinese Journal of Chemical Engineering 2015年第1期23卷 309-314页

作者：申亚珍赵聪周健民杜昌文 State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil Science Chinese Academy of Sciences

Waterborne acrylic emulsions modified with organic siloxanes and aziridine crosslinker were synthesized and applied as coating of controlled release fertilizer. The free films were characterized and the nutrient release profiles of the coated fertilizers were determined. The results show that methyl silicone oil and methylsilanolate sodium could not improve water resistance performance and glass transition temperature Tgof coatings, while the firmness is enhanced. Aziridine crosslinker improves the water resistance performance, firmness and Tg. Incorporation of methyl silicone oil and aziridine crosslinker gives an excellent aqueous acrylic emulsion for coated controlled release fertilizer, with the 30-day cumulative nutrient release reduced to 16% and an estimated nutrient release duration over 190 days. Therefore, this waterborne coating is promising to meet the requirements for controlled release of nutrient and environmental protection.

关键词：包膜控释肥料应用反应层玻璃化转变温度水性丙烯酸有机聚硅氧烷养分释放曲线抗水性能

Modeling spatio-temporal distribution of soil moisture by deep learning-based cellular automata model

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Journal of Arid Land 2016年第5期8卷 734-748页

作者： SONG Xiaodong ZHANG Ganlin LIU Feng LI Decheng ZHAO Yuguo YANG Jinling State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of Sciences

soil moisture content （SMC） is a key hydrological parameter in agriculture,meteorology and climate change,and understanding of spatio-temporal distributions of SMC in farmlands is important to address the precise irrigation scheduling.However,the hybrid interaction of static and dynamic environmental parameters makes it particularly difficult to accurately and reliably model the distribution of SMC.At present,deep learning wins numerous contests in machine learning and hence deep belief network （DBN） ,a breakthrough in deep learning is trained to extract the transition functions for the simulation of the cell state changes.In this study,we used a novel macroscopic cellular automata （MCA） model by combining DBN to predict the SMC over an irrigated corn field （an area of 22 km^2） in the Zhangye oasis,Northwest China.Static and dynamic environmental variables were prepared with regard to the complex hydrological processes.The widely used neural network,multi-layer perceptron （MLP） ,was utilized for comparison to DBN.The hybrid models （MLP-MCA and DBN-MCA） were calibrated and validated on SMC data within four months,i.e.June to September 2012,which were automatically observed by a wireless sensor network （WSN） .Compared with MLP-MCA,the DBN-MCA model led to a decrease in root mean squared error （RMSE） by 18%.Thus,the differences of prediction errors increased due to the propagating errors of variables,difficulties of knowing soil properties and recording irrigation amount in practice.The sequential Gaussian simulation （s Gs） was performed to assess the uncertainty of soil moisture estimations.Calculated with a threshold of SMC for each grid cell,the local uncertainty of simulated results in the post processing suggested that the probability of SMC less than 25% will be difference in different areas at different time periods.The current results showed that the DBN-MCA model performs better than the MLP-MCA model,and the DBN-MCA model provides a powerful tool for predicting SMC in highly non-linear forms.Moreover,becau

关键词： soil moisture soil moisture sensor network macroscopic cellular automata （MCA） deep belief network （DBN） multi-layer perceptron （MLP） uncertainty assessment hydropedology

Effects of Rice-Wheat Rotation and Afforestation on Microbial Biomass Carbon in Coastal Salt-Affected soils of Eastern China

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Pedosphere 2017年第5期27卷 938-948页

作者： JIN Wenhui YANG Jingsong YAO Rongjiang YU Shipeng LIU Meixian XIE Wenping State Key Laboratory of Soil and Sustainable Agriculture Nanjing Institute of Soil Science Chinese Academy of Sciences

Rice-wheat rotation and poplar afforestation are two typical land use types in the coastal reclaimed flatlands of eastern China.This study investigated two rice-wheat rotation lands(one reclaimed from 1995 to 2004 and cultivated since 2005, RW1, and the other reclaimed from 1975 to 1995 and cultivated since 1996, RW2) and a poplar woodland(reclaimed from 1995 to 2004 and planted in2004, PW1) to determine the effects of land use types and years of cultivation on soil microbial biomass and mineralizable carbon(C) in this coastal salt-affected region. The results showed that the soil in PW1 remained highly salinized, whereas desalinization was observed in RW1. The total organic C(TOC) in the top soil of PW1 and RW1 did not show significant differences, whereas at a soil depth of 20–30 cm, the TOC of RW1 was approximately 40%–67% higher than that of PW1. The TOC of 0–30-cm soil in RW2 was approximately 37% higher than that in RW1. Microbial biomass C(MBC) and mineralizable C(MNC) exhibited the trend of RW2 > RW1 > PW1. Sufficient nutrition with more abundant C substrates resulted in higher MBC and MNC, and soil respiration rates were negatively correlated with C/N in RW1 and RW2. Nutrient deficiency and high salinity played key roles in limiting MBC in PW1. These suggested that rice-wheat rotation was more beneficial than poplar afforestation for C accumulation and microbial biomass growth in the coastal salt-affected soils.

关键词：土壤微生物生物量碳滨海盐渍土稻麦轮作中国东部盐渍化造林土地利用类型再生栽培

Using a Two-Liquid-Phase System to Investigate the Biodegradation of Trichlorobenzenes

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Pedosphere 2015年第2期25卷 169-176页

作者： SONG Yang WANG Fang BIAN Yong-Rong YE Mao JIANG Xin State Key Laboratory of Soil and Sustainable Agriculture Institute of Soil ScienceChinese Academy of Sciences

Due to easy volatilization of volatile organic compounds from water,it is difficult to monitor their aerobic biodegradation in the traditional single water system.Whether a two-liquid-phase system(TLPS) could overcome this obstacle and enhance the degradation of volatile contaminants? In this study,a TLPS composed of silicone oil and water was employed to investigate the biodegradation of volatile compounds,trichlorobenzenes(TCBs),by the adapted microorganisms in an activated soil.The degradation and volatilization of TCBs in TLPS and in a single water system were compared.The results showed that due to volatilization losses of TCBs,the mass balance of TCBs in a single water system was very low.In contrast,using TLPS could effectively inhibit the volatilization losses of TCBs and achieved a very good mass balance during the biodegradation process.Meanwhile,the TLPS could increase microbial activity and microbial growth during the degradation process.With TLPS,the TCB degradation was in descending order of 1,2,4-TCB> 1,2,3-TCB>> 1,3,5-TCB,which was related to the exposed concentration of the contaminants in soil.This study showed that TLPS could be employed as an effective tool to evaluate the biodegradation of volatile hydrophobic organic compounds,which could not be achieved with the traditional single water system.

关键词：生物降解性系统调查三氯苯两液相挥发性有机化合物挥发性污染物生物降解过程微生物活性