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     

中国高铁建设投资对国民经济和环境的短期效应综合评估

近年来,传统铁路发展远不能满足各行业对综合交通运输体系的需求,中国政府正加大对高铁行业的规划与投资。现有高铁网络与其他铁路共同构成的快速客运网,推动了产业的空间布局,加速了产业结构调整,提高了就业率,提升了区域间劳动力、资本、自然资源等配置效率,促进了区域经济协调发展。在中国政府大力建设高铁网络的当下,综合评估中国高铁建设投资给国民经济和环境带来的影响具有必要性和十分重要的现实意义。本文基于中国2012年投入产出表,利用投入产出技术和计量经济学模型,通过重新刻画投入产出模型中农村居民、城镇居民部门"收入-消费"内生关系,区分高铁与传统铁路在生产结构和投资结构的差异,构建基于居民消费局部内生化的高铁投资投入产出局部闭模型,评估中国高铁建设投资对经济、就业和能源环境的短期效应。结果表明:12012年中国高铁投资每亿元拉动总产出增加3.72亿元,GDP增长1.21亿元,投资总量给国民经济共带来总产出增长19 373.44亿元、GDP增长6 296.04亿元;2在拉动经济增长同时,高铁建设投资对就业拉动显著,每亿元高铁投资创造1 084个就业岗位,2012年因高铁投资新增就业岗位高达565.23万人。这意味着,在短期内,中国高铁建设投资会在发展社会经济、促进居民就业等方面注入强大的动力;3在环境层面,2012年高铁前期基础建设共带来83.42 Mt CO2排放,略大于传统铁路投资,但考虑到建成运营后,高铁具有清洁、稳定、高速等特点,高铁建设投资在环境层面优势会慢慢显现。     

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.     

短期有机冲击下船用景观一体化反硝化除磷装置的处理效能

为高效、稳定处理船舶生活污水,研究了船用景观一体化反硝化除磷装置面对短期水质波动的效能变化,采用富集反硝化聚磷菌(DPAOs)的ABR-CSTR连续流组合工艺耦合生态单元处理船舶生活污水,对比了ABR进水容积负荷(VLR)为1.2 kg·(m³·d)⁻¹、COD为350 mg·L⁻¹的基准条件,通过短期内提高进水中有机底物的浓度,来模拟1.5倍和2.0倍进水有机负荷的有机冲击,此外通过控制硝化液回流比及溶解氧获得应对冲击的调控策略。结果表明：在2种短期冲击下,COD去除率分别为94.1%和92.6%,出水BOD和TN可达标,生物单元出水磷平均为0.76 mg·L⁻¹和1.14 mg·L⁻¹,缺氧吸磷量为7.13 mg·L⁻¹和5.82 mg·L⁻¹,生态单元可深度降解氮磷及缓冲波动;在1.5倍VLR下,调整硝化液回流比由200%至300%,反硝化吸磷量由7.10 mg·L⁻¹升至7.41 mg·L⁻¹,在2.0倍冲击下,提高硝化液回流比对系统除磷帮助甚微,将DO从1.5 mg·L⁻¹升至2.0 mg·L⁻¹,吸磷量由5.17 mg·L⁻¹升至6.01 mg·L⁻¹,系统反硝化除磷效果得以提升;污泥特性方面,ABR内MLVSS/MLSS比值和EPS量随有机底物浓度的提高而上升,厌氧段EPS增幅最大,可由154.5 mg·g⁻¹升至164.2 mg·g⁻¹和183.4 mg·g ⁻¹。ABR-CSTR-生态单元一体化装置面对短期有机冲击具有稳定处理效果,研究结果可为船舶生活污水的治理提供参考。     

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。     

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。     

Short-term prediction of the influent quantity time series of wastewater treatment plant based on a chaos neural network model

By predicting influent quantity, a wastewater treatment plant (WWTP) can be well controlled. The nonlinear dynamic characteristic of WWTP influent quantity time series was analyzed, with the assumption that the series was predictable. Based on this, a short-term forecasting chaos neural network model of WWTP influent quantity was built by phase space reconstruction. Reasonable forecasting results were achieved using this method. Translated from Acta Scientiae Circumstantiae, 2006, 26(3): 416–419 [译自: 环境科学学报]     

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.     

多壁碳纳米管短期作用对厌氧颗粒污泥的影响

研究了不同质量浓度（1、20和100 mg·L-1） 多壁碳纳米管（multiwalled carbon nanotubes,MWCNTs） 短期（7 d） 作用对厌氧污泥系统的影响。结果表明：1、20和100 mg·L-1的 MWCNTs反应器出水中的COD、pH、VFA与对照组变化规律一致;其中,100 mg·L-1的MWCNTs可以诱导更快的底物利用率。不同质量浓度MWCNTs反应器的产气量和甲烷体积分数与对照组之间相比无显著差异（P>0.05）。运用修正Gompertz 方程拟合甲烷产量曲线以及计算最大比产甲烷速率（Umax,CH4）和最大比COD去除速率（Umax,COD）表明厌氧产甲烷菌产气特性没有受到MWCNTs的影响。实验研究结果为以后研究碳纳米管在厌氧废水处理中的影响提供了提供新的思路和方法。     

成都市道路移动源减排对空气质量的短期影响

近年来随着经济社会的高速发展,我国的空气污染问题日渐突出.管控污染源以减少污染物排放是改善空气质量的主要手段,且其效率如何会极大地影响空气质量的改善效果.但通常情况下,单一减排手段的实施对空气质量的改善的实际贡献往往在短时间内较难做出客观评价.本研究借助新冠疫情期间以道路移动源为主的各类污染源排放短期内大量下降的机会,通过疫情管控措施实施前后交通条件和空气质量的对比,分析道路移动源减排对空气质量改善的短期影响.结果表明,实施管控措施后,城市范围内道路交通条件明显改善,拥堵路段基本消失.受此影响,各类主要污染物浓度出现不同程度的下降,其中,受道路移动源贡献较大的NO₂浓度下降比例达40%~60%,PM_2.5因受气象条件影响较大而下降幅度较小.结合实时的交通数据估算其相应的尾气排放结果表明,疫情期间道路移动源排放的NO_x、HC、CO分别下降59.7%、59.9%和58.8%.本研究对于分析短时间内急速减排等应急措施对环境改善的效果,以及削减污染物排放对空气质量改善的潜力有重要的实际参考价值.