Irrigation Water Allocation Using an Inexact Two‐Stage Quadratic Programming with Fuzzy Input under Climate Change

Agricultural irrigation accounts for nearly 70% of the total water use around the world. Uncertainties and climate change together exacerbate the complexity of optimal allocation of water resources for irrigation. An interval‐fuzzy two‐stage stochastic quadratic programming model is developed for determining the plans for water allocation for irrigation with maximum benefits. The model is shown to be applicable when inputs are expressed as discrete, fuzzy or random. In order to reflect the effect of marginal utility on benefit and cost, the model can also deal with nonlinearities in the objective function. Results from applying the model to a case study in the middle reaches of the Heihe River basin, China, show schemes for water allocation for irrigation of different crops in every month of the crop growth period under various flow levels are effective for achieving high economic benefits. Different climate change scenarios are used to analyze the impact of changing water requirement and water availability on irrigation water allocation. The proposed model can aid the decision maker in formulating desired irrigation water management policies in the wake of uncertainties and changing environment.     

Optimizing mixture properties of biodiesel production using genetic algorithm-based evolutionary support vector machine

Nowadays, biodiesel is used as one of the alternative renewable energy due to the increasing energy demand. However, optimum production of biodiesel still requires a huge number of expensive and time-consuming laboratory tests. To address the problem, this research develops a novel Genetic Algorithm-based Evolutionary Support Vector Machine (GA-ESIM). The GA-ESIM is an Artificial Intelligence (AI)-based tool that combines K-means Chaotic Genetic Algorithm (KCGA) and Evolutionary Support Vector Machine Inference Model (ESIM). The ESIM is utilized as a supervised learning technique to establish a highly accurate prediction model between the input--output of biodiesel mixture properties; and the KCGA is used to perform the simulation to obtain the optimum mixture properties based on the prediction model. A real biodiesel experimental data is provided to validate the GA-ESIM performance. Our simulation results demonstrate that the GA-ESIM establishes a prediction model with better accuracy than other AI-based tool and thus obtains the mixture properties with the biodiesel yield of 99.9%, higher than the best experimental data record, 97.4%.     

基于地面监测数据的2013~2015年长三角地区PM2.5时空特征

近年来,长三角地区灰霾天气持续增多,空气细颗粒物污染问题日益突出。基于2013年1月至2015年5月长三角地区及周边缓冲区内共214个空气质量监测站点PM_2.5逐时监测数据,运用普通克里金插值方法,从年、季、月尺度上分析了PM_2.5的空间分布格局和时间动态变化。结果表明:(1)2 a来,长三角地区PM_2.5浓度空间分布明显呈现整体北部高南部低,局部地区略有突出的分布特征;长三角地区PM_2.5浓度年均值为57.08μg/m³;其中,江苏省PM_2.5的年均值为三省市最高,为65.84μg/m³;其次为上海市,年均值为53.87μg/m³;浙江省PM_2.5的年均值较小,为51.53μg/m³。(2)从季节尺度分析,长三角地区PM_2.5浓度变化表现出冬春季高,夏秋季低的变化趋势;这与区域内冬季风向来源、降水稀少、气象扩散条件差有着密切的关系; (3)长三角地区月浓度变化大致呈U形分布; 12月份PM_2.5浓度最高; 3月份以后, PM_2.5浓度开始呈逐步下降趋势;在5~9月份,区域PM_2.5处于"U"字的谷底,其中6月份夏收时期秸秆焚烧、气象等因素导致PM_2.5浓度有略微升高;进入10月份后迅速攀升,且11、12月份呈现持续升高态势。     

氟苯胺同系物降解性能对比实验研究

利用驯化污泥研究了邻氟苯胺、对氟苯胺、2,4-二氟苯胺的好氧生物降解性能.结果表明,3种氟苯胺的好氧生物降解性能从高到低依次为,对氟苯胺、邻氟苯胺和2,4-二氟苯胺.降解动力学分析表明,在初始浓度在8～50 mg·L^-1范围内,除2,4-二氟苯胺在实验浓度8.56 mg/L时为一级反应,其他为零级反应.且它们的降解规律都符合Monod方程.污染物化学结构特性与其生物降解性能相关性研究表明,热力学参数与氟苯胺好氧生物降解性能相关性最好,空间参数次之,而电性参数最差.并研究了共代谢条件下葡萄糖和苯胺对2,4-二氟苯胺的好氧降解的影响,葡萄糖的引入有促进作用,而苯胺只在一定浓度范围内有促进作用.因而,氟苯胺的生产废水与生活污水合并处理以及多种组分混合废水处理是可行的.     

Great Basin Land Management Planning Using Ecological Modeling

This report describes a land management modeling effort that analyzed potential impacts of proposed actions under an updated Bureau of Land Management Resource Management Plan that will guide management for 20 years on 4.6 million hectares in the Great Basin ecoregion of the United States. State-and-transition models that included vegetation data, fire histories, and many parameters (i.e., rates of succession, fire return intervals, outcomes of management actions, and invasion rates of native and nonnative invasive species) were developed through workshops with scientific experts and range management specialists. Alternative restoration scenarios included continuation of current management, full fire suppression, wildfire use in designated fire use zones, wildfire use in resilient vegetation types only, restoration with a tenfold budget increase, no restoration treatments, and no livestock grazing. Under all the scenarios, cover of vegetation states with native perennial understory declined and was replaced by tree-invaded and weed-dominated states. The greatest differences among alternative management scenarios resulted from the use of fire as a tool to maintain native understory. Among restoration scenarios, only the scenario assuming a tenfold budget increase had a more desirable outcome than the current management scenario. Removal of livestock alone had little effect on vegetation resilience. Rather, active restoration was required. The predictive power of the model was limited by current understanding of Great Basin vegetation dynamics and data needs including statistically valid monitoring of restoration treatments, invasiveness and invasibility, and fire histories. The authors suggest that such computer models can be useful tools for systematic analysis of potential impacts in land use planning. However, for a modeling effort to be productive, the management situation must be conducive to open communication among land management agencies and partner entities, including nonprofit organizations.     

Assessing the Effects of Alternative Setback Channel Constraint Scenarios Employing a River Meander Migration Model

River channel migration and cutoff events within large river riparian corridors create heterogeneous and biologically diverse landscapes. However, channel stabilization (riprap and levees) impede the formation and maintenance of riparian areas. These impacts can be mitigated by setting channel constraints away from the channel. Using a meander migration model to measure land affected, we examined the relationship between setback distance and riparian and off-channel aquatic habitat formation on a 28-km reach of the Sacramento River, California, USA. We simulated 100 years of channel migration and cutoff events using 11 setback scenarios: 1 with existing riprap and 10 assuming setback constraints from about 0.5 to 4 bankfull channel widths (bankfull width: 235 m) from the channel. The percentage of land reworked by the river in 100 years relative to current (riprap) conditions ranged from 172% for the 100-m constraint setback scenario to 790% for the 800-m scenario. Three basic patterns occur as the setback distance increases due to different migration and cutoff dynamics: complete restriction of cutoffs, partial restriction of cutoffs, and no restriction of cutoffs. Complete cutoff restriction occurred at distances less than about one bankfull channel width (235 m), and no cutoff restriction occurred at distances greater than about three bankfull widths (∼700 m). Managing for point bars alone allows the setbacks to be narrower than managing for cutoffs and aquatic habitat. Results suggest that site-specific “restriction of cutoff” thresholds can be identified to optimize habitat benefits versus cost of acquired land along rivers affected by migration processes.     

乳化液废水均相催化湿式氧化动力学

在2L高压间歇反应釜中,以高浓度难降解乳化废水为处理对象,研究了温度对铜盐均相湿式氧化的影响和动力学特征.结果表明:升高温度对加快后期反应速度更为有利,催化剂有利于中间产物氧化,在200℃催化活性最高,在进水COD48 400mg/L,反应2h去除率为86.6%;催化剂在不同温度作用下机制有所差别:200℃时3个途径反应速度均加快,中间产物加速氧化更明显;220～240℃时反应向生成中间产物方向偏移,活性降低;通用模型能较好地预测均相催化过程.     

上海市“十四五”规划绿色发展驱动因素研究

本文首次以上海市“十四五”规划的视角,使用系统动力学方法研究上海市的绿色发展因素。首先确定了由经济、社会、环境、资源四个子系统交叉融合而构成上海市绿色发展系统,再基于系统动力学原理和上海市2012—2019年的数据构建上海市绿色发展模型,响应“十四五”规划在绿色发展方面设立的目标,构建多个未来发展情景并进行指标参数调控,依据各个情景的仿真结果,分析并总结了“十四五”规划背景下上海市的绿色发展特点。研究结果表明,影响绿色发展的关键因素由主到次依次为生态环境建设支出、研发支出、产业结构调整。相比于产业的投资结构调整,上海市对从业人员结构的调整可以高效平衡经济与环境的发展;加快科技创新可以在很大程度上抑制碳排放,从而快速实现上海市的“双碳”目标;针对化学污染物的治理,污染源防治不但十分有效,而且有利于持续性发展,这些措施应是上海市政府的首选。     

热阻力概念的修正及计算方法

以隧道火灾为背景,对一维加热管流中的热阻力进行了研究。通过压力场数值模拟与理论分析,直接证实了热阻力的存在,并表明传统概念上的热阻力明显大于实际的能量损失。根据能量方程提出水平无粘管流的热阻力应等于气流经过加热区的全压力降,而非静压力降;等截面管流的热阻力大小应为传统热阻力值的1/2。这一修正使热阻力概念具有了严格的流体力学意义。在定义新的热阻力系数基础上,建立了2个热阻力系数表达式及低马赫数条件下热阻力的近似表达式。将该近似表达式与热损失方程进行对比,表明两者在低马赫数条件下具有一致性。研究成果进一步发展了热阻力理论体系,对隧道火灾及其它相关工程热物理问题的研究与应用都具有重要价值。     

Time perspective balance and team adaptation in dynamic task contexts

The concept of time perspective balance has attracted increased attention from scholars in the past decade, reflected in published evidence suggesting positive outcomes ranging from enhanced mood to life satisfaction for those individuals possessing balance among their past, present, and future time perspectives, and assumedly able to shift their time perspective to match situational demands. In this paper, we consider the notion of time perspective balance in an organizational setting within which much consequential adaptation often occurs—the team environment—and explore different configurations of time perspective balance in teams facing dynamic task contexts. Drawing from work on situational awareness, we first consider the mechanism by which time perspective balance likely influences individual adaptation in dynamic task-focused situations. Next, we postulate what types of team configurations—ones with more balanced time perspective uniformity or ones with more time perspective variety—might be more appropriate in dynamic contexts given key team conditions. We illustrate our analysis with examples from healthcare team settings and offer ideas for future research.