H∞ loop-shaping controller design for a grid-connected single-phase photovoltaic system

This paper presents a H_∞ loop-shaping controller for controlling dc-link voltage by regulating the switching signal of the inverter associated with a grid-connected single-phase photovoltaic system. To facilitate a robust control design, state-space realisation of the system model is made with uncertainties represented by linear fractional transformation. The controller is achieved through H_∞ synthesis followed by obtaining desired loop shapes through the choice of the proper weighting functions. The controller order is reduced by Henkel-norm method for facilitating its practical implementation. Controller performance is evaluated through carrying out simulations on MATLAB/Simulink platform under standard and changing atmospheric conditions, and fault condition.     

Trace metals distribution and their dependence on some physico-chemical parameters in creek sediment

The concentrations of the trace metals Mn, Zn, Cr, V, Co, Ni, Ba, Pb, Cu, Cd, As and Hg, their spatial distribution, and their correlation as a function of physico-chemical parameters were investigated for grab sediment samples collected from different locations across the Thane Creek, Mumbai, India. Hydride generation atomic absorption spectrometry, inductively coupled plasma atomic emission spectrometry, and differential pulse anodic stripping voltammetry were adopted for chemical analyses. Various geochemical indices were evaluated. The studied metal/metalloids were compared with sediment quality guideline values. Besides, the role of different physico-chemical parameters of the sediments such as pH, CaCO₃, cation exchange capacity, total carbon, and of the relative composition in respect to very coarse, coarse and medium sand, fine sand and very fine sand, silt and clay fraction were also critically investigated. Positive one-to-one correlations between fine sand and very fine sand, silt and clay, and total carbon with sediment metal concentrations have been noticed. Multiple regression analysis reveals strong positive correlations between sediment metal concentrations and total carbon content only.     

基于卫星夜间灯光数据的中国分省碳排放时空模拟

中国能源统计数据"横向不可比,纵向不可加"现象依然突出,尤其是分省能源消费统计千差万别,给分省碳排放评估带来了较大困难,如何利用卫星遥感数据科学合理地估算中国分省碳排放是当前亟须研究的问题。本文运用DMSP/OLS全球稳定夜间灯光数据,在通过相互校正、年内融合和年际间校正等系列处理得到中国分省稳定夜间灯光数据的基础上,首先分别构建中国分省稳定夜间灯光亮度DN值与人均碳排放和单位面积碳排放之间的时空地理加权回归模型,两个模型整体效果均较好,拟合优度分别高达96.74%和99.24%;其次运用稳定夜间灯光亮度DN值对分省人均碳排放和单位面积碳排放进行时空模拟;最后运用人口规模和土地面积对分省碳排放进行估算。估算结果显示:(1)整体来看,2000—2013年年均碳排放模拟值与实际值6.3349×109t较为接近,两个模型的相对误差均在0.5%以内。(2)分年度来看,所有年份的相对误差均在5%以内,2006年分省加总碳排放模拟值与实际碳排放6.2036×109t最为接近,绝对误差和相对误差均较小,两个模型模拟值的相对误差均为0.04%。(3)分省域来看,2000—2013年年均碳排放模拟值与实际碳排放均非常接近,除海南和宁夏外,其余28个省区市的相对误差均在1%以内。(4)分年度分省域来看,以2013年为例,40%省份的相对误差在2%以内,70%省份的相对误差在5%以内。从整体、分年度、分省域、分年度分省域的估算结果来看,基于稳定夜间灯光数据的中国分省碳排放时空模拟效果良好。因此,运用卫星夜间灯光数据可以较为准确地对中国分省碳排放进行估算和预测,为卫星遥感影像数据服务分省碳排放监测和评估提供一种补充性参考。     

中国FDI环境效应的再检验

改革开放以来,外商直接投资(FDI)的涌入为中国经济发展注入了新活力,并成为中国经济高速增长的重要引擎之一。然而,随着康菲石油渤海漏油事故、江苏启东王子造纸排污和阿玛尼污染投诉等涉外污染事件报道频出,学术界对于FDI涌入可能带来的负面环境效应表现出一定担忧。现有文献多聚焦于整体层面的FDI环境效应检验,而对其区域差异及原因产生机制的系统探究并不多见。为此,本文从理论判断和命题推演出发,利用2003—2014年中国省际面板数据,以改进熵值法拟合环境污染综合指数,并构建普通面板模型,实证检验了FDI流入对中国环境污染的影响及其区域差异。结果表明,总体而言,"污染光环"假说在中国基本成立,即FDI流入在一定程度上改善了中国环境质量,但不同地区FDI的环境效应有所不同,其主要表现为沿海和内陆地区FDI具有显著的"污染光环"效应,且前者强于后者,而沿边地区FDI具有不明显的"污染天堂"效应。在此基础上,构造面板门槛模型,进一步系统考察了FDI对中国环境污染影响的4种主要吸收能力因素的门槛效应。门槛回归结果表明,FDI对中国环境污染的影响显著存在基于经济发展、环境规制、人力资本和金融发展水平的双门槛效应。经济发展、人力资本和金融发展水平越高,FDI的"污染光环"效应越明显,而适度的环境规制才更有利于FDI环境技术溢出的发挥。基于此,本文建议应进一步全方位地提高对外开放水平,一如既往地积极引进并监督FDI;同时地方政府也需认清地区发展的不平衡性,进而采取差异化的引资政策。     

中国新克强指数的构建与实证分析

随着中国经济进入新常态,英国《经济学人》杂志构建的克强指数已无法反映中国经济的全貌,如何客观地反映中国经济的真实状况成为一个迫切需要解决的现实问题。为更好地测度中国经济运行的真实状况,本文根据李克强总理提出的"未来会更加关注就业、居民收入和生态环境的持续改善"的愿景,在原有克强指数的基础上,增加年末就业人员数、农村居民家庭人均纯收入、城镇居民家庭人均可支配收入等就业和收入方面的指标,使用中国1995—2015年的相关数据和层次分析法构建了克强指数的修订版本即新克强指数,并将新克强指数与GDP增长率、克强指数进行了比较,发现新克强指数在反映中国经济波动和经济整体运行状态上有更为优良的性质。与GDP增长率相比,新克强指数克服了服务业比重提高带来的熨平效应,进而灵敏地反映中国经济波动情况,并对异常事件更加具有敏感性。相对于克强指数而言,新克强指数破除了因中国在第二产业上存在失衡性发展所带来的经济波动的杠杆效应,降低了经济增长中的虚假成分,从而与中国经济运行的整体关联度更为密切。此外,相对于克强指数而言,新克强指数在反映经济景气方面有着较好的时效性与关联性。采用时差相关分析法对新克强指数与宏观经济指标之间的关系进行分析,发现新克强指数在反映第一产业增加值、第三产业增加值、最终消费支出、资本形成总额、对外贸易、通货膨胀等方面具有优势。研究表明:新克强指数是更适宜测度中国经济的多元评价指标,为测度中国经济运行的真实状况提供了科学的参考依据。     

巢湖和太湖微囊藻毒素差异性研究

采用固相萃取高效液相色谱法检测巢湖和太湖水体中5种微囊藻毒素(MCs)——MC-RR、MC-YR、MC-LR、MC-LA、MC-LY的含量。结果表明,巢湖水体中的MCs以MC-RR、MC-LA、MC-LY为主,太湖水体主要以MC-RR、MC-LR、MC-LA为主,其中太湖MC-LR的最高质量浓度为2.558μg/L,超过《地表水环境质量标准》(GB 3838—2002)中对集中式生活饮用水地表水源地的限定值(1μg/L)。分析巢湖和太湖水体中MCs与水质指标之间的相关性,发现同种MCs与两湖环境因子的相关性存在明显差异。逐步回归拟合结果表明,氨氮和DO分别能与巢湖MC-LR、MC-LY进行拟合;Chl-a、TOC能与太湖MC-LR回归拟合,TOC能与太湖MC-YR进行拟合。由于多数MCs不能通过水质指标的拟合结果来预测,因此在未来研究中需结合环境因子和MCs的遗传机制来共同分析MCs在水中的分布规律。     

Using multivariate regression modeling for sampling and predicting chemical characteristics of mixed waste in old landfills

Municipal solid waste landfills pose a threat on environment and human health, especially old landfills which lack facilities for collection and treatment of landfill gas and leachate. Consequently, missing information about emission flows prevent site-specific environmental risk assessments. To overcome this gap, the combination of waste sampling and analysis with statistical modeling is one option for estimating present and future emission potentials. Optimizing the tradeoff between investigation costs and reliable results requires knowledge about both: the number of samples to be taken and variables to be analyzed.This article aims to identify the optimized number of waste samples and variables in order to predict a larger set of variables. Therefore, we introduce a multivariate linear regression model and tested the applicability by usage of two case studies. Landfill A was used to set up and calibrate the model based on 50 waste samples and twelve variables. The calibrated model was applied to Landfill B including 36 waste samples and twelve variables with four predictor variables.The case study results are twofold: first, the reliable and accurate prediction of the twelve variables can be achieved with the knowledge of four predictor variables (Loi, EC, pH and Cl). For the second Landfill B, only ten full measurements would be needed for a reliable prediction of most response variables. The four predictor variables would exhibit comparably low analytical costs in comparison to the full set of measurements. This cost reduction could be used to increase the number of samples yielding an improved understanding of the spatial waste heterogeneity in landfills.Concluding, the future application of the developed model potentially improves the reliability of predicted emission potentials. The model could become a standard screening tool for old landfills if its applicability and reliability would be tested in additional case studies.     

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。     

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.     

人力资本、社会资本与市民化抑制

新生代农民工问题的终结是市民化,但是目前许多新生代农民工存在市民化阻碍,这不利于我国城市化进程的推进和经济的持续健康发展。对沈阳和余姚两地区进行了案例调查,得到了两地区新生代农民工的调查数据。运用调查数据,首先采用需求可识别的biprobit模型对新生代的农民工市民化抑制程度进行了测度,并预测出新生代农民工个体的市民化抑制程度。在对新生代农民工个体的市民化抑制程度指标进行分位数回归分解的基础上,分析了人力资本和社会资本对新生代农民工市民化抑制程度的影响,以期促进新生代农民工的城市融入。研究发现:新生代农民工的社会资本水平是影响其市民化的关键因素,人力资本水平的提高只有在市民化抑制程度高于80%时才会使市民化抑制程度下降。因此,相应的政策建议为,政府应加强新生代农民工城市公共服务的享用水平;发展和健全农民工工会组织;在市民化抑制程度较高的地区应特别加强新生代农民工职业技能的培训。