遗传投影寻踪回归在城市环境质量评价中的应用

引入投影降维的思想,将遗传投影寻踪与回归分析技术运用到城市环境质量评价中。将此技术与神经网络方法进行实例比较,投影寻踪回归方法不但可以合理地作出环境质量的综合评价,而且消除了神经网络方法中类别判断不够精确的影响。     

秦皇岛市“创模”对策研究及效益分析

介绍了秦皇岛市创建国家环境保护模范城市的意义,重点阐述了完成创模任务的主要对策,包括:构建以旅游业为中心、特色产业互融互促的现代产业体系;加快城乡一体化建设;提升城镇发展质量和水平;加强重大基础设施建设;积极推广清洁能源,深入开展工程节能;积极推进循环经济发展等。秦皇岛市创建国家环境保护模范城市,将会在环境、经济和社会三方面产生明显的综合效益。     

Watershed Regressions for Pesticides (warp) Models for Predicting Atrazine Concentrations in Corn Belt Streams1

Stone, Wesley W. and Robert J. Gilliom, 2012. Watershed Regressions for Pesticides (WARP) Models for Predicting Atrazine Concentrations in Corn Belt Streams. Journal of the American Water Resources Association (JAWRA) 48(5): 970‐986. DOI: 10.1111/j.1752‐1688.2012.00661.x Abstract: Watershed Regressions for Pesticides (WARP) models, previously developed for atrazine at the national scale, are improved for application to the United States (U.S.) Corn Belt region by developing region‐specific models that include watershed characteristics that are influential in predicting atrazine concentration statistics within the Corn Belt. WARP models for the Corn Belt (WARP‐CB) were developed for annual maximum moving‐average (14‐, 21‐, 30‐, 60‐, and 90‐day durations) and annual 95th‐percentile atrazine concentrations in streams of the Corn Belt region. The WARP‐CB models accounted for 53 to 62% of the variability in the various concentration statistics among the model‐development sites. Model predictions were within a factor of 5 of the observed concentration statistic for over 90% of the model‐development sites. The WARP‐CB residuals and uncertainty are lower than those of the National WARP model for the same sites. Although atrazine‐use intensity is the most important explanatory variable in the National WARP models, it is not a significant variable in the WARP‐CB models. The WARP‐CB models provide improved predictions for Corn Belt streams draining watersheds with atrazine‐use intensities of 17 kg/km² of watershed area or greater.     

Comparison of the Performance of Statistical Models in Forecasting Monthly Total Dissolved Solids in the Rio Grande1

Abudu, S., J.P. King, Z. Sheng, 2011. Comparison of the Performance of Statistical Models in Forecasting Monthly Total Dissolved Solids in the Rio Grande. Journal of the American Water Resources Association (JAWRA) 48(1): 10‐23. DOI: 10.1111/j.1752‐1688.2011.00587.x Abstract: This paper presents the application of autoregressive integrated moving average (ARIMA), transfer function‐noise (TFN), and artificial neural networks (ANNs) modeling approaches in forecasting monthly total dissolved solids (TDS) of water in the Rio Grande at El Paso, Texas. Predictability analysis was performed between the precipitation, temperature, streamflow rates at the site, releases from upstream reservoirs, and monthly TDS using cross‐correlation statistical tests. The chi‐square test results indicated that the average monthly temperature and precipitation did not show significant predictability on monthly TDS series. The performances of one‐ to three‐month‐ahead model forecasts for the testing period of 1984‐1994 showed that the TFN model that incorporated the streamflow rates at the site and Caballo Reservoir release improved monthly TDS forecasts slightly better than the ARIMA models. Except for one‐month‐ahead forecasts, the ANN models using the streamflow rates at the site as inputs resulted in no significant improvements over the TFN models at two‐month‐ahead and three‐month‐ahead forecasts. For three‐month‐ahead forecasts, the simple ARIMA showed similar performance compared to all other models. The results of this study suggested that simple deseasonalized ARIMA models could be used in one‐ to three‐month‐ahead TDS forecasting at the study site with a simple, explicit model structure and similar model performance as the TFN and ANN models for better water management in the Basin.     

苏南某市河流水质参数时空变异性研究

以苏南某市区320km2内的河流为研究对象,基于对高锰酸盐指数、NH3-N、TP3个主要水质参数的监测,应用地质统计学的变差函数球状模型和Kriging插值法,对河流有机污染指标、富营养化指标进行了空间插值,用以揭示其时空分布特征及变化趋势,并绘制了时空分布等值线图。结果表明,受不同区域污染物来源的差异、不同河道自身条件的差异和不同水期水生植物、入流水量、河水流动性的差异等因素的影响,研究区河流水质参数呈现出不同的时空变异特征;各水质参数污染均相当严重,尤以富营养化指标氮磷最为显著。     

活性艳橙K-7R分子印迹聚合物微球的制备及结合特性研究

以微米级聚苯乙烯微球为种球,活性艳橙K-7R为模板分子,甲基丙烯酸为功能单体,乙二醇二甲基丙烯酸酯为交联剂,采用单步溶胀聚合法在水相中制得了分子印迹聚合物微球(MIPs),并用平衡吸附实验研究了其吸附性能。通过Scatchard分析,结果表明,MIPs在识别K-7R过程中存在两类结合位点,高亲和力结合位点的平衡离解常数Kd1=14.855μmol/L,最大结合量Qmax1=1.282μmol/g;低亲和力结合位点的平衡离解常数Kd2=70.939μmol/L,最大结合量Qmax2=3.930μmol/g。该MIPs对K-7R有较高的亲和性和选择性。     

脂肽类生物表面活性剂液体发酵条件的响应面优化

通过Plackett-Burman和Box-Behnken实验对解淀粉芽孢杆菌XZ-173液体发酵生产表面活性素进行了响应面优化研究。首先使用Plackett-Burman实验对影响表面活性素产量的17个因素进行显著性筛选,结果表明,MnSO4、CuSO4、温度和转速为显著性因素。再运用Box-Behnken实验对这4个显著因素的取值进一步优化,得到各因素优化后的数值分别为4.4 mg/L(MnSO4)、0.18 mg/L(CuSO4)、29℃(温度)和163 r/min(转速)。响应面分析结果表明:该菌株产生表面活性素的最佳培养基为:葡萄糖15 g/L,蛋白胨5 g/L,L-谷氨酸钠6 g/L,KH2PO40.8 g/L,MgSO40.4 g/L,KCl 0.4 g/L,酵母提取物3 g/L,L-苯丙氨酸2.5 mg/L,MnSO44.4 mg/L,CuSO40.18 mg/L,FeSO40.12 mg/L;最适培养条件:pH 7.5,温度29℃,转速163 r/min,接种量5%,装液量50 mL/250 mL,摇床培养36 h。在优化后的条件下,表面活性素实际产量为336 mg/L,实际实验结果与模型预测结果相一致。表面活性素采用HPLC技术分离,发现其在浓度仅为50 mg/L时EI24就可达到70%以上,反映了表面活性素优异的乳化活性以及广阔的应用前景。     

抗压实验法厌氧颗粒污泥机械强度的测定及影响因素分析

通过首先对厌氧颗粒污泥样品进行筛分,然后测定其机械强度,解决了实际操作过程中现有抗压实验法出现的精确度与重现性较差的问题。通过对不同来源厌氧颗粒污泥样品机械强度的测定、对比分析发现,厌氧颗粒污泥的机械强度大小与反应器的规模、反应器所采用水力负荷存在一定的正相关性,且与其主要金属元素（Ca、Fe和Mg）含量的大小存在着密切的关系。     

沼气农业复合生态系统能值分析

以沼气为纽带的农业综合利用系统对农村和偏远地区可持续发展具有重要意义。本文基于能值流图和指标体系,构建了沼气农业复合生态系统的综合评价框架,并以国家沼气农业示范区广西恭城县为案例,分析养殖-沼气-种植"三位一体"典型沼气农业复合系统的能值投入产出量及其结构,利用能值系统结构功能指标对该系统进行经济生态多元分析,评估其投资率、产出率、环境压力以及可持续性等系统综合表现,并与国内外其他农业系统进行比较分析。系统投入结果表明,恭城县沼气农业复合系统总投入中人类经济反馈在系统中所占比例最大,可更新环境资源次之,其中又以肥料、农药和劳工与管理的投入最大;系统产出表明,目前仍以种植业和养殖业为主导,水产业相对薄弱,而新兴的沼气产业因其低耗高产的特点,发展势头良好;而能值系统结构功能指标表明该农业系统整体具有环境负荷低、产出效率高、可持续性强等优势。依照能值分析各项结果,本文对沼气农业系统优化配置和进一步推广应用提出了参考建议。     

中国西北寒旱区农牧民生活碳排放评估

围绕碳排放权开展的气候谈判愈来愈关注贫困人口与弱势群体的生存权与发展权,一方面由于受制于其薄弱的社会经济水平,贫困人口与弱势群体在气候变化实践中表现出更高的脆弱性,另一方面则因气候变化减缓与适应行动而造成的贫困人口生活成本的增加以及生活水平的下降。然而,对这些地区和人口的排放权判断主要基于国家层面和地区层面宏观数据的分析,其结果掩盖了国家和地区内部不同社会经济水平下的人口排放差异,不能准确揭示贫困人口和脆弱群体的低碳排放事实。本文基于国际碳排放评估对人口生活排放的需求,结合IPCC参考方法,利用投入产出分析模型构建了人口生活碳排放评价指标体系,并用于对甘肃、青海和宁夏干旱-高寒地区农牧民生活碳排放的样本调查和分析。评估表明,中国西北干旱—高寒区人口生活碳排放仅为1.85tCO2/人,其中用于满足基本生活需要的碳排放量达到87.25%。研究发现,生活在更冷(海拔更高)区域内的人口生活排放量更高;随着家庭收入的增长,人口生活排放量也随之上升;家庭成员数量越多,家庭的人均碳排放量就会越低。