响应面法用于优化污水厂脱氮工艺的研究

在单因素试验基础上,采用Box-Behnken响应面法对新疆某联合式污水厂的脱氮单元进行优化,结果表明,对脱氮性能的影响由强到弱依次为碳氮比(C/N)、有机负荷(F/M)和内回流比(R).模型优化后的最佳工况条件C/N为7.45、R为52.61％、F/M为0.10 d-1,污水厂在该工况下进行验证试验,其NH3-N、TN平均去除率分别为87.23％、91.20％,在出水中的测定均值分别为0.37 mg/L、6.09 mg/L,均满足一级A标准.NH3-N和TN去除率与预测值相对误差分别为0.38％和0.55％,与模型预测值较接近.     

Odour from municipal solid waste (MSW) landfills: a study on the analysis of perception

The objective of this work was to develop a relationship between odour intensity and odour concentration by using data collected from various sensitive areas of the municipal solid waste (MSW) landfill site. A number of well-known psychophysical models (e.g., Weber-Fechner law, Steven's power law, Beidler's and Laffort's models) have been discussed that can successfully relate the perceived intensity with the odour concentration. Respective parameters for each of the models were estimated by the nonlinear Levenburg-Marquardt parameter estimation method. The overall performance of the model was tested statistically against sets of data from the olfactometry analysis. The model based on the Weber-Fechner law was ranked 1 in case of five out of nine samples and it has been found more representative of the less intense odour samples. The model based on Laffort's equation has represented the intensity-concentration relationship better with extremely low uncertainties on both parameters k1 and k2 for comparatively more intense odour samples.     

复杂矿井通风系统分支阻力可调性数值研究

笔者应用数字实验方法 ,通过调节分支阻力 ,研究它对通风系统的影响。研究结果表明 :当一些分支的阻力调到接近完全隔断风流的极大值时 ,网络分析结果仍然正常 ,不影响迭代技术 ;同样也说明了分支阻力预先输入的可行性 ;各分支阻力的变化对通风系统的影响程度是不一样的 ,这由分支在通风网络中的位置决定 ;通过分析 ,给出了通风系统中两风机的相互影响的情况。     

夜光藻赤潮与环境因子关系的模糊分析

针对在2006年夏天渤海湾赤潮重点监控区中发生的一次夜光藻赤潮,考虑到夜光藻赤潮过程与环境因子的复杂关系和赤潮监测数据的不确定性,利用模糊逻辑方法对监测数据样本进行了分析。本文的研究对象为1号、2号和4号站位包含有夜光藻赤潮过程的7月26日~8月20日的连续监测数据,给出了隶属度函数和模糊规则的提取方法,利用生成的模糊逻辑规则阐述了此次夜光藻赤潮的生消过程并分析了夜光藻赤潮与若干环境因素之间的变动关系,为进一步研究该海域的夜光藻赤潮机理并预测夜光藻赤潮奠定了基础。     

基于SAVEE方法的海岛空间价值评价——以南沙群岛为例

对SAVEE评价方法的理论基础、分析步骤、应用条件和优缺点进行了系统归纳和总结,构建了SAVEE评价分析模型。以南沙群岛的空间价值评价为例开展实证研究,尝试将SAVEE方法应用于海岛空间价值评价。结果表明:SAVEE评价法计算简便,可操作性强,能够量化体现每个因子价值,评价结果清晰易懂。SAVEE为空间价值评价方法提供了新的选择,具有极大的应用前景。     

基于自适应网络模糊推理方法在河道洪水预报中的应用

对于易受洪灾的地区而言,快速而准确的洪水预报非常重要,能够为洪水预警消息的发布提供更长的先导时间,从而为可能受灾地区的人们提供更充足的时间以采取相应的防洪措施或安全转移。 常用的预报模型包括基于物理性模型和基于系统技术模型。尽管物理性模型能对洪水形成的物理过程提供很好的解释, 水文学家并不愿意使用它们,因为模型中参数的率定是比较复杂的。因此,一种基于纯数据集的黑箱技术已被广泛采纳。常用的黑箱模型包括线性模型(LR)、自回归移动平均模型(ARMA)和人工神经网络模型（ANN）等。 在当前的研究中,一个相对新颖的黑箱模型--基于自适应网络的模糊推理系统（ANFIS）被用来对长江某河段的洪水进行预报。与此同时,一个线性回归模型（LR）用来作为ANFIS模型的对照。在构建ANFIS中,混合学习算法 (即误差反衍（BP）耦合最小二乘法（LSE）) 用来训练模型的参数。此外,为避免出现过度训练现象,原始数据集基于统计特征值划分成3个子集：训练集、测试集和校正集。当对ANFIS模型训练时,测试集用来帮助控制训练代数。结果表明,ANFIS的预报效果优于LR模型。分析认为ANFIS能够提供预报精度是因为其采用了局部拟合技术,通常它会优于LR模型所采用的全局拟合技术。最后,对本研究而言,最适合的ANFIS模型是输入量为梯形的成员度函数。     

滇池流域TN、TP入湖负荷预报预警系统

以流域模型HSPF和贝叶斯递归回归树算法(BRRT)为计算模块,建立了滇池流域27条主要入湖河流和33个散流区的TN、TP入湖负荷预报预警系统.同时,构建了考虑历史排放规律和预测负荷计算预警指数(EWI)评价预警等级的两套预警体系.结果表明:BRRT替代模型在流域内以农业面源为主的柴河子流域校准和验证的可决系数R2均大于0.8,模拟结果相对可靠;根据预警时间选取预警体系;适用于6月份之前的预警体系一(EWS-1),利用现状排放量和历史排放量的关系计算预警指数.适用于6月份之后的预警体系二(EWS-2),主要考虑现状排放量、历史平均排放量、排放限值和预测排放量之间的关系计算3个预警指数,最终以最严格的作为综合预警指数EWI评价预警等级;根据柴河子流域"十二五"规划的TN和TP排放限值为130.2 t·a-1、6.8 t·a-1,应用此系统对2011年2、4、9和11月做出预警检验,各月份预警结果基本处于红色和黑色预警,该系统可为流域提供预警支持.     

Maximum likelihood fitting of the Poisson lognormal distribution

In this paper some properties and analytic expressions regarding the Poisson lognormal distribution such as moments, maximum likelihood function and related derivatives are discussed. The author provides a sharp approximation of the integrals related to the Poisson lognormal probabilities and analyzes the choice of the initial values in the fitting procedure. Based on these he describes a new procedure for carrying out the maximum likelihood fitting of the truncated Poisson lognormal distribution. The method and results are illustrated on real data. The computer program for calculations is freely available.

Testing of the Storm Water Management Model Low Impact Development Modules

Stormwater infrastructure designers and operators rely heavily on the United States Environmental Protection Agency’s Storm Water Management Model (SWMM) to simulate stormwater and wastewater infrastructure performance. Since its inception in the late 1970s, improvements and extensions have been tested and evaluated rigorously to verify the accuracy of the model. As a continuation of this progress, the main objective of this study was to quantify how accurately SWMM simulates the hydrologic activity of low impact development (LID) storm control measures. Model performance was evaluated by quantitatively comparing empirical data to model results using a multievent, multiobjective calibration method. The calibration methodology utilized the PEST software, a Parameter ESTimation tool, to determine unmeasured hydrologic parameters for SWMM’s LID modules. The calibrated LID modules’ Nash–Sutcliffe efficiencies averaged 0.81; average percent bias (PBIAS) ?9%; average ratio of root mean square error to standard deviation of measured values 0.485; average index of agreement 0.94; and the average volume error, simulated vs. observed, was +9%. SWMM accurately predicted the timing of peak flows, but usually underestimated their magnitudes by 10%. The average volume reduction, measured outflow volume divided by inflow volume, was 48%. We had more difficulty in calibrating one study, an infiltration trench, which identified a significant limitation of the current version of the SWMM LID module; it cannot simulate lateral exfiltration of water out of the storage layers of a LID storm control measure. This limitation is especially severe for a deep LIDs, such as infiltration trenches. Nevertheless, SWMM satisfactorily simulated the hydrologic performance of eight of the nine LID practices.     

Mechanisms and impacts of an incentive-based conservation program with evidence from a randomized control trial

Conservation science needs more high-quality impact evaluations, especially ones that explore mechanisms of success or failure. Randomized control trials (RCTs) provide particularly robust evidence of the effectiveness of interventions (although they have been criticized as reductionist and unable to provide insights into mechanisms), but there have been few such experiments investigating conservation at the landscape scale. We explored the impact of Watershared, an incentive-based conservation program in the Bolivian Andes, with one of the few RCTs of landscape-scale conservation in existence. There is strong interest in such incentive-based conservation approaches as some argue they can avoid negative social impacts sometimes associated with protected areas. We focused on social and environmental outcomes based on responses from a household survey in 129 communities randomly allocated to control or treatment (conducted both at the baseline in 2010 and repeated in 2015–2016). We controlled for incomplete program uptake by combining standard RCT analysis with matching methods and investigated mechanisms by exploring intermediate and ultimate outcomes according to the underlying theory of change. Previous analyses, focused on single biophysical outcomes, showed that over its first 5 years Watershared did not slow deforestation or improve water quality at the landscape scale. We found that Watershared influenced some outcomes measured using the survey, but the effects were complex, and some were unexpected. We thus demonstrated how RCTs can provide insights into the pathways of impact, as well as whether an intervention has impact. This paper, one of the first registered reports in conservation science, demonstrates how preregistration can help make complex research designs more transparent, avoid cherry picking, and reduce publication bias.