Sustainable pattern analysis of a publicly owned Material Recovery Facility in a fast-growing urban setting under uncertainty

Sustainable development goals are achievable through the installation of Material Recovery Facilities (MRFs) in certain solid waste management systems, especially those in rapidly expanding multi-district urban areas. MRFs are a cost-effective alternative when curbside recycling does not demonstrate long-term success. Previous capacity planning uses mixed integer programming optimization for the urban center of the city of San Antonio, Texas to establish that a publicly owned material recovery facility is preferable to a privatized facility. As a companion study, this analysis demonstrates that a MRF alleviates economic, political, and social pressures facing solid waste management under uncertainty. It explores the impact of uncertainty in decision alternatives in an urban environmental system. From this unique angle, waste generation, incidence of recyclables in the waste stream, routing distances, recycling participation, and other planning components are taken as intervals to expand upon previous deterministic integer-programming models. The information incorporated into the optimization objectives includes economic impacts for recycling income and cost components in waste management. The constraint set consists of mass balance, capacity limitation, recycling limitation, scale economy, conditionality, and relevant screening restrictions. Due to the fragmented data set, a grey integer programming modeling approach quantifies the consequences of inexact information as it propagates through the final solutions in the optimization process. The grey algorithm screens optimal shipping patterns and an ideal MRF location and capacity. Two case settings compare MRF selection policies where optimal solutions exemplify the value of grey programming in the context of integrated solid waste management.     

Multi-objective Programming and Social Welfare Analysis of Rural–urban Land Conversion Decision-making

Abstract

Rural–urban land conversion is an inevitable phenomenon in urbanization and industrialization. And the decision-making issue about this conversion is multi-objective because the social decision maker (the whole of central government and local authority) has to integrate the requirements of different interest groups (rural collective economic organizations, peasants, urban land users and the ones affected indirectly) and harmonize the sub-objects (economic, social and ecological outcomes) of this land allocation process. This paper established a multi-objective programming model for rural–urban land conversion decision-making and made some social welfare analysis correspondingly. Result shows that the general object of rural–urban land conversion decision-making is to reach the optimal level of social welfare in a certain state of resources allocation, while the preference of social decision makers and the value judgment of interest groups are two crucial factors which determine the realization of the rural–urban land conversion decision-making objects.     

华北地区冬半年空气污染天气客观分型研究

利用2013—2016年冬半年ERA-interim再分析资料,以及同期空气污染资料、地面常规气象观测资料和探空资料,采用PCT (Principal Component Analysis in T-mode)客观分型方法对华北地区冬半年海平面气压场进行天气分型,并探究不同月份不同天气型对应的空气污染状况及污染气象参数分布特征,进而从污染气象学的角度揭示重污染潜势天气型的气候特征.结果表明:冬半年海平面气压场共对应9种天气类型,其中,5型(均压场型)、6型(高压内部型)和8型(高压后部型)为3种重污染潜势天气型,冬半年对应的PM_(2.5)均值浓度分别为144.11、136.99和148.26μg·m~(-3),而1型(T型高压前部型)和3型(低压底部型)为两种清洁天气型,冬半年对应的PM_(2.5)均值浓度分别为97.12和80.83μg·m~(-3);重污染潜势天气型对应的边界层结构呈现出稳定能量大、混合层厚度和通风系数小的大气层结稳定的静稳天气特征,其能够反映大气污染潜势;研究还发现,即使是同一天气型,其在不同月份对污染物的扩散影响也存在差异,因此,建议在今后的污染潜势天气型研究中分月份进行.本研究可为华北地区空气污染潜势预报及大气重污染预报预警的客观化、自动化提供科学依据和技术支持.     

郑州市固体废物现状及控制对策探讨

通过对基准年（１９９８年）郑州市固体废物污染现状调查及存在问题分析，预测了２０００～２０１５年固体废物的产生量，提出郑州市固体废物远景规划目标，并明确实现这一目标的污染控制对策及具体投资项目。     

基于不同电力需求的中国减污降碳协同增效路径

当前我国同时面临改善生态环境质量和实现碳达峰碳中和两大战略任务,协同推进减污降碳已成为我国经济社会发展全面绿色转型的必然选择,电力部门在转型过程中将发挥重要作用.面向不同的电力需求情景,构建低成本实现碳达峰、碳中和的多目标模型,求解得出减污降碳协同增效最优路径方案.结果表明,在如期实现碳达峰、碳中和目标的前提下,减污和降碳协同性较好,两者协同控制可高效助力低碳转型的实现;优化电力部门发电结构是实现减污降碳协同增效的关键措施,研究期火电占比不断下降,清洁电力占比超过92.5%;不同电力需求下二氧化碳和主要大气污染物排放量有明显差异,其中二氧化碳排放量受电力需求影响最大,低电力需求、中等电力需求和高电力需求情景下峰值二氧化碳排放量分别为94.16亿、 104.09亿和107.46亿t,主要污染物二氧化硫、氮氧化物和颗粒物的排放同样表现出在低电力需求、中等电力需求和高电力需求情景下依次递增的趋势.电力需求的提高仅增加了电力部门内部发电结构调整的压力,未影响到其他部门的产量和活动水平,即电力需求导致的电力部门减排压力未表现出部门间传递的趋势.     

2016—2019年夏半年成都市区臭氧污染天气特征分析

为揭示成都市区臭氧污染气象条件特征,通过欧盟COST733天气客观分型软件对成都市区2016-2019年夏半年(5-9月)海平面气压场和500 hPa位势高度场进行大气环流形势分型,并结合同期臭氧监测数据、地面气象观测数据以及总云量实况分析产品,分析成都市区夏半年臭氧超标天气及气象要素特征.结果表明:成都市区2016-2019年夏半年共出现臭氧超标日数为159 d,超标率为26.0%,超标日主要集中于5-8月,小时超标多出现于14:00-17:00.臭氧污染日数最多的海平面气压场为弱低压型,其后依次为低压前部型、低压型、高压后部型.臭氧超标率最高的海平面气压场为低压前部型,其后依次为弱低压型、低压型、高压后部型.500 hPa位势高度场平直西风气流型臭氧超标日数最多,青藏高压型臭氧超标日数最少.青藏高压型是臭氧超标率最高的500 hPa位势高度场型,平直西风气流型臭氧超标率最低.成都市区臭氧超标日多出现在偏西北风下,近地面气象要素特征一般表现为风速1.2~1.6 m/s,气温在25℃以上,相对湿度多集中在70%左右,总云量和降水概率多低于60%,降水量级以小雨为主,太阳辐射和日照时数分别位于20.5~23.2 MJ/m2和6.0~7.8 h区间.小时臭氧超标近地面气象要素特征为气温和总辐射曝辐量相对较高,二者分别在30~36℃和0~3.5 MJ/m2之间,相对湿度在60%以下,总云量低于40%,以偏南风影响为主.研究显示,成都市区海平面气压场为低压型,500 hPa位势高度场为青藏高压型时,易发生臭氧污染.      

滑坡预测的改进前馈网络方法研究

作者提出了滑坡位移预测的一种改进前馈网络方法——目的规划法,与通常的前馈网络方法相比,该方法改进了网络的准则函数,降低了网络的灵敏度,改善了网络的泛化性能,提高了滑坡位移的预测精度。同时它是一种面向数据的方法,适合于不同地区不同条件下滑坡的预测。清江隔河岩库区滑坡和卧龙寺滑坡的实例研究表明了该方法的可行性及有效性。     

结构分析中模拟与仿真技术研究

由于像洪水、水灾、地震这样一类自然灾害的原型重复试验几乎是不可能的,因此计算机仿真技术在这一领域的应用具有重要的意义。本文探索了土木工程中模拟与仿真的概念、特征及实现途径,阐述了关于仿真智能化、可视化的技术细节及仿真的基本思路;结合面向对象程序设计（OOP）概念,提出了结构分析程序设计的原则及标准。在此基础上,编写了基于Windows的结构有限元分析软件SmartSEA.     

基于灾害风险评估的山地城市固定避难场所布局优化研究——以东川区为例

研究以各区域灾害风险评估系数作为权重系数,对山地小城市各区域避难场所进行优化布局。首先,通过风险值=危险性*脆弱性/抗灾救灾能力机理表达式构建灾害风险评估指标体系,并以模糊综合评价法得出灾害风险评估数值,在此基础上通过多目标选址优化模型来构建山地城市避难场所的优化模型,其中灾害风险评估系数作为影响布局的权重因素纳入其中。最后,以东川区为研究对象,对其固定避难场所进行优化布局研究,结果表明:东川区城区固定避灾场所数量可在接近最优解的情况下达到效果最优。     

Suitability of short or long conservation contracts under ecological and socio-economic uncertainty

Acquisition of land rights has become a primary tool used to protect terrestrial biodiversity. Fixed length contracts are often used when trying to secure conservation benefits on private land in agri-environment schemes and payment for environmental services schemes, but the duration of the conservation contracts used in different programmes varies. To date, very little research has been undertaken to determine the situations in which contracts of differing lengths are optimal or when conservation agencies or groups should use a portfolio of different contract lengths rather than relying on a single type. Using stochastic dynamic programming and related heuristic methods, we investigate how the choice between short or long conservation contracts is affected by uncertainty regarding the future availability of sites and their ecological condition. We also examine the benefits offered by using a portfolio of different contract lengths. Conservation agencies must pay private landowners a premium to secure longer agreements and because of this, shorter contracts are advantageous if sites are likely to remain available for conservation in the future. Long contracts are preferred when future site availability becomes more unlikely. In contrast to uncertainty over site availability, uncertainty over future ecological conditions has little effect on contract selection and only markedly influences the choice between short and long contracts when there is heterogeneity across sites in expected conservation outcomes and future availability of sites is also uncertain. Finally, when future site availability is unlikely, the use of a portfolio of short and long contracts would offer greater conservation gains than using either type in isolation, even though this option is not yet one that is commonly found in conservation practice.