粮食产量预测理论、方法与应用Ⅱ.粮食生产潜力短期预测理论、模型及其应用

粮食生产潜力短期预测结果可以检验粮食中长期生产潜力预测的准确性和为国家提供制定粮食生产战略的科学依据。粮食生产潜力短期预测理论即“趋势-波动理论”,它建立在粮食或作物“现状生产潜力”概念和“天-人-地概念模型”基础上,预测模型为最佳移动步长条件下的多年单产移动平均趋势模型,实际预测时采用系统预测方法。11个研究案例预测的平均误差为0.77％,最大误差为2.99％,预测精度高。本研究初步结论是：粮食生产潜力短期预测理论和模型是科学和实用的。     

ARIMA模型和GM(1,1)与ARMA(p,q)组合模型在滑坡短期预报中的对比分析

滑坡的短期预报研究是当前国内外滑坡领域的重要研究方向之一。在滑坡的中短期时间预报中,基于统计学的预测模型是主要的分析预测工具。采用两种理论上比较成熟的ARIMA模型和GM(1,1)与ARMA(p,q)组合模型来模拟滑坡的累积位移量,并对这两种模型的优缺点以及各自适用条件进行了对比分析。结果表明:两种模型都能较好地拟合滑坡累积位移量时间序列并做出一定精度的预测,但是两种模型的适用条件不同。本研究可为滑坡短期预报提供借鉴和参考。     

多壁碳纳米管短期作用对活性污泥系统脱氮除磷效果的影响

研究了不同质量浓度(1 mg/L和20 mg/h)多壁碳纳米管(Muhiwalled Carbon Nanotubes,MWCNTs)短期(21 d)作用对序批式活性污泥反应器(SBR)废水脱氮除磷效果的影响.结果表明,1mg/L和20mg/L MWCNTs废水的持续作用对反应器出水NH4+-N、NO3--N、NO2--N和TP质量浓度(分别为0.35 mg/L、4.5 mg/L、0.1 mg/L和0.15 mg/L)及1个反应周期内的氮磷转化过程并未产生明显的影响.活性污泥3h呼吸抑制试验表明,低质量浓度(ρ＜100 mg/L)MWCNTs短暂作用(3h)对活性污泥活性并没有明显的抑制作用.但当MWC-NTs质量浓度达到g/L级别后,MWCNTs对活性污泥活性存在明显的抑制作用,而且MWCNTs对活性污泥的呼吸抑制作用与质量浓度呈正相关性.研究表明,1 mg/k和20 mg/L MWCNTs对活性污泥系统短期作用并不影响活性污泥系统脱氮除磷的效果.     

A novel hybrid model for water quality prediction based on VMD and IGOA optimized for LSTM

● A novel VMD-IGOA-LSTM model has proposed for the prediction of water quality. ● Improved model quickly converges to the global optimal fitness and remains stable. ● The prediction accuracy of water quality parameters is significantly improved. Water quality prediction is vital for solving water pollution and protecting the water environment. In terms of the characteristics of nonlinearity, instability, and randomness of water quality parameters, a short-term water quality prediction model was proposed based on variational mode decomposition (VMD) and improved grasshopper optimization algorithm (IGOA), so as to optimize long short-term memory neural network (LSTM). First, VMD was adopted to decompose the water quality data into a series of relatively stable components, with the aim to reduce the instability of the original data and increase the predictability, then each component was input into the IGOA-LSTM model for prediction. Finally, each component was added to obtain the predicted values. In this study, the monitoring data from Dayangzhou Station and Shengmi Station of the Ganjiang River was used for training and prediction. The experimental results showed that the prediction accuracy of the VMD-IGOA-LSTM model proposed was higher than that of the integrated model of Ensemble Empirical Mode Decomposition (EEMD), the integrated model of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Nonlinear Autoregressive Network with Exogenous Inputs (NARX), Recurrent Neural Network (RNN), as well as other models, showing better performance in short-term prediction. The current study will provide a reliable solution for water quality prediction studies in other areas.     

杀虫剂及抗生素对发光菌的短期毒性与长期毒性

以毒物对青海弧菌Q67 (Vibrio-qinghaiensis sp.-Q67)发光抑制为毒性指标,基于短期微板毒性分析法(S-MTA法),建立了长期微板毒性分析法(L-MTA法),测定了吡虫啉(IMI)、抗蚜威(PIR)、啶虫脒(ACE)及敌百虫(DIP)等4种杀虫剂与氯霉素(CHL)、盐酸四环素(TET)、硫酸链霉素(STR)及硫酸巴龙霉素(PAR)等4种抗生素的短期(15 min)毒性和长期(12 h)毒性.采用短期毒性与长期毒性EC₅₀之比(RSL)为指标,表征同一物质的毒性差异. 结果表明:3种杀虫剂(IMI,ACE及PIR)的短期毒性与长期毒性差异不大(其RSL分别为0.84,0.81和1.11);杀虫剂DIP和2个抗生素(CHL及TET)的短期毒性与长期毒性差异明显(其RSL分别为11.76,9.67及154.38);另2个抗生素(STR和PAR)只有较强的长期毒性.      

The potential of statistical state space models in urban ozone forecasting

State space models for tropospheric urban ozone prediction are introduced and compared with linear regression models. The linear and non-linear state space models make accurate short-term predictions of the ozone dynamics. The average prediction error one hour in advance is 7 μg/m³ and increases logarithmically with time until it reaches 26 μg/m³ after 30 days. For a given sequence of solar radiation inputs, predictions converge exponentially with a time scale of 8 hours, so that the model is insensitive to perturbations of more than 150 μg/m³ O₃. The slow increase of the prediction error in addition to the uniqueness of the prediction are encouraging for applications of state space models in forecasting ozone levels when coupled with a model that predicts total radiation. Since a radiation prediction model will be more accurate during cloud-free conditions, in addition to the fact that the state space models perform better during the summer months, state space models are suitable for applications in sunny environments.     

Factors affecting the quantitative uncertainty of the estimated short-term intake. Part II—Practical examples

ABSTRACT

The effects of the spread of residue concentrations in the samples derived from the selected supervised trials and the number of trials were studied on the magnitude and uncertainty of the short-term dietary intakes calculated with the proposed new procedure (IESTI_p) and that one used currently by the FAO (Food and Agriculture Organization) and WHO (World Health Organization) Joint meeting on Pesticide Residues (JMPR) (IESTI_c). The residue data of 10 pesticides were obtained from supervised trials conducted on apples and pears. The methods described in Part I were used for the calculations of the uncertainty. The results indicate that the ratio of IESTI_P to IESTI_c (φ_IESTI) is directly proportional to the ratio of the estimated maximum residue level (MRL), recommended by the JMPR; to the highest residue (HR) observed in supervised trials, and it may have a wide range depending on the particular conditions. The φ_IESTI becomes greater with the increase of the difference between the mrl or maximum residue limit (MRL, established by the Codex Alimentarius Commission, CAC) and HR, and becomes smaller if the difference between the large portion (LP) and unit mass (U) decreases. The φ_IESTI ranged between 2 and 5.1 in the 16 cases examined indicating that the IESTI_p calculation method leads to higher intake estimates. The ratio of CV_IESTIp and CV_IESTIc ranged typically between 0.62 and 1.71. It rapidly increased up to 12 trials. For a larger number of trials, the ratio remained practically constant (1.69–1.71). The processing factor (PF) equally affects the MRL and HR values, therefore, it will not practically influence the φ_IESTI. The uncertainty of the estimated median residues depends on the spread and number of values in the residue datasets, which affects the uncertainty of the conversion factor (CF) and subsequently the uncertainty of the estimated IESTI_p. Residue values obtained from minimum nine independent trials are required for the correct calculation of the 95% confidence intervals of the calculated median residues. The uncertainty of the analytical results directly affects the median, HR values and indirectly the calculated mrl and the MRL derived from it. Therefore, it should also be considered for the calculation of the combined uncertainty of the conversion factors. For the correct interpretation of the results of dietary exposure calculations, the upper 95% confidence limit of the short-term intake should also be considered. However, it is not the current practice of regulatory agencies or JMPR.     

Impact of a proposed revision of the IESTI equation on the acute risk assessment conducted when setting maximum residue levels (MRLs) in the European Union (EU): A case study

ABSTRACT

Proposals to update the methodology for the international estimated short-term intake (IESTI) equations were made during an international workshop held in Geneva in 2015. Changes to several parameters of the current four IESTI equations (cases 1, 2a, 2b, and 3) were proposed. In this study, the overall impact of these proposed changes on estimates of short-term exposure was studied using the large portion data available in the European Food Safety Authority PRIMo model and the residue data submitted in the framework of the European Maximum Residue Levels (MRL) review under Article 12 of Regulation (EC) No 396/2005. Evaluation of consumer exposure using the current and proposed equations resulted in substantial differences in the exposure estimates; however, there were no significant changes regarding the number of accepted MRLs. For the different IESTI cases, the median ratio of the new versus the current equation is 1.1 for case 1, 1.4 for case 2a, 0.75 for case 2b, and 1 for case 3. The impact, expressed as a shift in the IESTI distribution profile, indicated that the 95th percentile IESTI shifted from 50% of the acute reference dose (ARfD) with the current equations to 65% of the ARfD with the proposed equations. This IESTI increase resulted in the loss of 1.2% of the MRLs (37 out of 3110) tested within this study. At the same time, the proposed equations would have allowed 0.4% of the MRLs (14 out of 3110) that were rejected with the current equations to be accepted. The commodity groups that were most impacted by these modifications are solanacea (e.g., potato, eggplant), lettuces, pulses (dry), leafy brassica (e.g., kale, Chinese cabbage), and pome fruits. The active substances that were most affected were fluazifop-p-butyl, deltamethrin, and lambda-cyhalothrin.     

废水可生物降解COD组分2种表征方法的比较

利用自行开发的混合呼吸速率测量仪在接种污泥的条件下对重庆某城市污水处理厂污水进行了呼吸速率测试（短期BOD测试,以呼吸速率测量重新进入内源呼吸阶段为结束）;同时应用美国产BI-2000电解质呼吸仪在不接种污泥的条件下对该污水进行了BOD测试（长期BOD测试,理论上以污水中所有有机物矿化为结束）。对2种测试方法及其结果进行了比较,结果表明,2种方法得到的BCOD存在很大差异,短期BOD测试方法得到的结果仅为长期BOD测试方法得到的结果的40％～60％。通过批式呼吸测量方法测定了原废水中的活性异养微生物浓度XH(0),结果表明,XH(0)与BCOD_st之和与BCOD_lt比较接近,两者之比在0.88～1.02之间,平均值为0.94。     

安徽省近49年短历时强降水事件趋势变化特征

为了加强对小时时间尺度的雨强特征及变化分析研究,基于安徽省1961～2009年16个台站1小时降水量资料,针对超过98%分位点的短历时强降水事件,分析其短历时强降水量、降水次数、降水强度、占总降水的比重及日分布的趋势变化特征。结果表明：近49 a来安徽省短历时强降水量总体呈增多趋势,且自东向西增加趋势逐渐显著。由M K突变检验法分析可知,2001年后有明显的向上突变整体增多,2005年后突变显著。主要是短历时强降水次数的增多导致短历时强降水量增多。近49 a来安徽省总降水量增加的78%来源于短历时强降水,且在总降水时间日趋减少的情况下,短历时强降水时间增加,对总降水的贡献越来越大。而在日分布方面,短历时强降水的日分布呈明显的双峰结构,频发时间段分别位于午后到傍晚、后半夜到早晨。但出现在上午的短历时强降水量及次数的增长趋势要明显超过午后到傍晚,因此可推测未来峰值和谷值的差异将减小,双峰的特征将逐渐减弱