Bayesian calibration of the nitrous oxide emission module of an agro-ecosystem model

Nitrous oxide (N₂O) is the main biogenic greenhouse gas contributing to the global warming potential (GWP) of agro-ecosystems. Evaluating the impact of agriculture on climate therefore requires a capacity to predict N₂O emissions in relation to environmental conditions and crop management. Biophysical models simulating the dynamics of carbon and nitrogen in agro-ecosystems have a unique potential to explore these relationships, but are fraught with high uncertainties in their parameters due to their variations over time and space. Here, we used a Bayesian approach to calibrate the parameters of the N₂O submodel of the agro-ecosystem model CERES-EGC. The submodel simulates N₂O emissions from the nitrification and denitrification processes, which are modelled as the product of a potential rate with three dimensionless factors related to soil water content, nitrogen content and temperature. These equations involve a total set of 15 parameters, four of which are site-specific and should be measured on site, while the other 11 are considered global, i.e. invariant over time and space. We first gathered prior information on the model parameters based on the literature review, and assigned them uniform probability distributions. A Bayesian method based on the Metropolis–Hastings algorithm was subsequently developed to update the parameter distributions against a database of seven different field-sites in France. Three parallel Markov chains were run to ensure a convergence of the algorithm. This site-specific calibration significantly reduced the spread in parameter distribution, and the uncertainty in the N₂O simulations. The model’s root mean square error (RMSE) was also abated by 73% across the field sites compared to the prior parameterization. The Bayesian calibration was subsequently applied simultaneously to all data sets, to obtain better global estimates for the parameters initially deemed universal. This made it possible to reduce the RMSE by 33% on average, compared to the uncalibrated model. These global parameter values may be used to obtain more realistic estimates of N₂O emissions from arable soils at regional or continental scales.     

盐城湿地沉积物环境特征及其影响因素研究

盐城沿海湿地是国家级自然保护区,正面临环境的污染和生态破坏的威胁。为了有效地保护和恢复其受损的生态功能,文章通过实地采样分析的方法研究了盐城湿地底泥氮、磷及有机物含量与分布规律及其影响因素。研究表明盐城湿地受潮流与河流水动力条件的长期综合作用,该区从陆地向海洋方向,沉积物粒度呈现由细变粗的总体变化规律。潮间带沉积物中氮、磷及有机碳在空间上也呈现出从光滩向高潮位区逐渐增加的趋势。沉积物中营养物释放与微小颗粒物的再悬浮成为潮间带水体富营养化的一个重要因素。     

稀土元素对包头引黄水库水中藻类的影响研究

为探明包头引黄水库藻类高发的原因,按标准方法进行藻类培养试验,研究稀土元素Ce对水库水体中藻类的影响。结果表明稀土元素Ce对藻的种类和生物多样性有抑制作用;低浓度(1mg/L)Ce对藻类个体总数具有明显的刺激作用,优势藻种为绿藻;高浓度(20mg/L)Ce对藻类的数量有抑制作用;低浓度稀土元素对藻类的刺激作用可能是包头引黄水库水体富营养化的影响因素之一。     

贝叶斯规整化BPNN定量流域非点源污染负荷研究

将贝叶斯规整化BP神经网络(BRBPNN)应用于渭河流域非点源污染、社会和经济之间相互作用的研究。采用相关系数法确定输入变量为"降雨"、"种植地"、"草地"、"人口密度"和"羊密度",输出变量为总氮负荷。结果表明用BRBPNN定量非点源污染负荷是可行的,综合选择最优网络模型结构为BRBPNN(3c-7-1),其训练集和预测集相关系数分别为1.0000和0.9780,对应的均方误差分别为88.32和3.21×102。采用权值理论分析各输入因子对网络的贡献,依次为"降雨">"羊密度">"种植地"。该研究可为流域非点源污染的治理提供依据。     

Investigating the impacts of crash prediction models on quantifying safety effectiveness of Adaptive Signal Control Systems

Introduction: Adaptive Signal Control System (ASCS) can improve both operational and safety benefits at signalized corridors. Methods: This paper develops a series of models accounting for model forms and possible predictors and implements these models in Empirical Bayes (EB) and Fully Bayesian (FB) frameworks for ASCS safety evaluation studies. Different models are validated in terms of the ability to reduce the potential bias and variance of prediction and improve the safety effectiveness estimation accuracy using real-world crash data from non-ASCS sites. This paper then develops the safety effectiveness of ASCS at six different corridors with a total of 65 signalized intersections with the same type of ASCS, in South Carolina. Results: Validation results show that the FB model that accounts for traffic volume, roadway geometric features, year factor, and spatial effects shows the best performance among all models. The study findings reveal that ASCS reduces crash frequencies in the total crash, fatal and injury crash, and angle crash for most of the intersections. The safety effectiveness of ASCS varies with different intersection features (i.e., AADT at major streets, number of legs at an intersection, the number of through lanes on major streets, the number of access points on minor streets, and the speed limit at major streets). Conclusions: ASCS is associated with crash reductions, and its safety effects vary with different intersection features. Practical Applications: The findings of this research encourage more ASCS deployments and provide insights into selecting ASCS deployment sites for reducing crashes considering the variation of the safety effectiveness of ASCS.     

基于APRIORI-TAN的交通事故伤害分析与预测*

为探究道路交通事故因素和事故伤害的相关性,以2 467起涉及人员伤亡的交通事故为数据集,运用Apriori算法分别挖掘事故伤害关联规则,并结合社会网络分析的可视化和核心-边缘分析构建受伤事故和死亡事故的关联规则网络。结果表明:事故伤害程度与事故时间、道路条件和交通环境等因素关系紧密,尤其死亡事故与碰撞固定物、人行横道事故、高速公路、高速道路、非市区、酒驾和超速存在高相关性。基于树型贝叶斯网络（TAN）构建事故伤害程度的预测模型,预测结果准确率可达87.56%。     

基于UHBs的输气管道高后果区泄漏燃爆事故分析

为探究输气管道高后果区中人的不安全行为（Unsafe Human Behaviors,UHBs）对输气管道泄漏燃爆事故发生的影响,结合模糊Bow-tie模型和贝叶斯网络对输气管道泄漏燃爆事故进行分析。构建基于T-S模糊故障树的输气管道泄漏燃爆模糊Bow-tie模型,并转化为贝叶斯网络;从人的不安全行为发生的可能性出发,将不同等级高后果区划分为不同等级人口敏感区;利用专家经验评判法得到不同等级人口敏感区基本事件的先验概率和中间事件的条件概率表;运用贝叶斯网络双向推理算法求解模糊Bow-tie模型。结果表明:随着地区人口敏感等级的提高,输气管道泄漏燃爆事故发生的概率随之增大,发现导致输气管道失效泄漏事故发生的最主要原因为施工破坏,失效原因与EGIG分析的结果基本相符,验证该方法在高后果区输气管道泄漏燃爆事故分析上的可行性,可为输气管道高后果区的安全管理提供决策依据。     

The effects of exogenous salicylic acid on growth and H2O2-metabolizing enzymes in rice seedlings under lead stress

Salicylic acid （SA） was an essential component of the plant resistance to pathogens and also plays an important role in mediating plant response to some abiotic stress. The possible effects of SA on the growth and H2O2-metabolizing enzymes in rice seedlings under lead stress were studied. When rice seedlings grown in nutrient solution containing Pb^2＋ （0, 0.05, 0.15, 0.25 mmol/L） for 18 d, the plant biomass as well as the chlorophyll content of leaves decreased with increasing Pb concentration. The pre-treatment with SA （treated with 0.1 mmol/L SA for 48 h before Pb stress） partially protected seedlings from Pb toxicity. The chlorophyll contents were significant higher in leaves of Pb-exposed with SA pre-treatment seedlings than in Pb-exposed plants at the same Pb intensity. SA pre-treated alone could significantly increase the length of shoot and root of seedlings but the vigour difference was not marked under long-term exposure to Pb toxicity. SA pre-treated influence the H2O2 level in leaves of seedlings by up-regulating the activity of superoxide dismutase （SOD）, repressing the activity of catalase （CAT） and ascorbate peroxidase （APX） depending on the concentrations of Pb^2＋ in the growth medium. The results supported the conclusion that SA played a positive role in rice seedlings against Pb toxicity.     

我国耕地资源生态安全的时空差异分析

在分析耕地资源生态安全内涵、特征和影响因素的基础上,构建了耕地资源生态安全评价指标体系,通过对我国耕地资源生态安全的动态变化分析,发现改革开放以来耕地资源生态安全程度呈先增后减的变化趋势,安全综合值先从1981年的0.891 8上升到1990年的0.941 0,随后又下降到2004年的0639 0。从2004年各省份的安全程度来看,安全状况差异非常明显,且经济发达省份的安全水平通常低于经济相对落后省份;通过障碍因素分析发现,改革开放前期的障碍因素主要是农民人均纯收入、财政支农等社会经济因素,中后期则转变为农药施用量、氮肥所占的比重等直接和间接影响因素,在各省份障碍因素中,单位耕地面积农药施用量、氮肥所占的比重、农村人均纯收入、耕地资源生态安全保护意识是最主要因素,经济发达省份障碍因素主要集中在直接和间接影响因素中,而经济相对落后省份则集中在社会经济因素。出台耕地资源生态安全保护法规和分区保护政策有助于提高我国耕地资源生态安全状况。     

微生物来源对餐厨垃圾厌氧消化产氢的影响

微生物来源对餐厨垃圾厌氧消化产氢的影响很大。在添加剂抑制耗氢菌的前提下,单独一种接种的条件下,剩余污泥的产氢效果是最好的,氢气的浓度和产量都最大,分别为47.1%和100.0 mLH2/g VS,其次是矿化污泥和矿化垃圾,颗粒污泥体系氢气的产量最少,分别为88.6 mLH2/g VS,57.8 mLH2/g VS和36.8 mLH2/g VS,其中颗粒污泥体系产生了甲烷气体而另外3中反应体系中并未检测到甲烷。污泥和矿化污泥混合后,在实验时间内,能够提高氢气的产量到106.4 mLH2/g VS,其余的混合体系的氢气的浓度和产量都较单独的剩余污泥体系的差。