快速工业化区域建设用地问题与制度优化研究——以佛山市南海区为例

快速工业化区域是工业化快速发展、工业化水平迅速提升、经济社会结构急剧变化的新兴地域类型。普遍存在着建设用地总量急剧扩张、空间无序分散、城乡缺乏统筹等问题。本文从佛山市南海区典型案例入手，运用新制度经济学原理。归纳和解析了快速工业化区域城乡建设用地的主要问题，认为双二元管理体制、农村土地产权不完善、城乡土地市场发育不平衡和部门规划不协调等是建设用地发展的主要体制性障碍因素，并从管理、产权、市场、规划等方面系统提出相应的制度优化对策。     

基于SE-FA的现役装备改进风险评价指标体系研究

现役装备改进是在原有产品基础上,通过采用各种改进措施,对产品的战术技术性能和结构进行局部改善,以达到提高或改进装备性能,延长装备使用寿命的目的.现役装备改进是一个复杂的系统工程过程,制约因素多、技术难度大,风险在所难免.为确保改进任务顺利进行,必须及时开展风险分析和评价研究,从而预先采取针对性措施加以防范.研究分析了现役装备改进的风险因子,构建了风险评价指标体系,并运用结构熵理论对指标体系的结构有序度进行了评价,提出了相对优化方案.最后,运用因子分析方法(FA)对构建的指标体系进行了因子分析,验证了指标体系的合理性.     

Alarm management optimization in chemical installations based on adapted HAZOP reports

Most current alarm systems used in chemical installations show poor performance due to alarm flooding. This study focuses on alarm management systems optimization using the deviation propagation relationship hidden in the hazard and operability study (HAZOP) report, which can be transformed into a critical information source for alarm optimization management. More concretely, this means matching the alarm tag number with the process deviations in the deviation column, possible cause column, and consequence column. Furthermore, a backtracking method and a reasoning method were established to identify the initial alarm and associated alarms. Besides, a root fault diagnosis was carried out. A method of detecting hardware faults and unreasonable alarm thresholds is established using alarm causality corresponding to the deviation causality and associated alarm generation-skipping tracing method. According to the severity of the consequence corresponding to the deviation, a determined alarm priority method is constructed. The results show that the deviation propagation relationship in the HAZOP report is clear, and the topological relationship is easy to build based on the deviation propagation relationship. With comprehensive and in-depth HAZOP analysis reports in China, the alarm management optimization technology based on adapted HAZOP reports shows good prospects for application and promotion.     

Improving collaboration in the implementation of global biodiversity conventions

Eight conventions make up the biodiversity cluster of multilateral environmental agreements (MEAs) that provide the critical international legal framework for the conservation and sustainable use of nature. However, concerns about the rate of implementation of the conventions at the national level have triggered discussions about the effectiveness of these MEAs in halting the loss of biodiversity. Two main concerns have emerged: lack of capacity and resources and lack of coherence in implementing multiple conventions. We focused on the latter and considered the mechanisms by which international conventions are translated into national policy. Specifically, we examined how the Strategic Plan for Biodiversity 2011–2020 and the associated Aichi Biodiversity Targets have functioned as a unifying grand plan for biodiversity conservation. This strategic plan has been used to coordinate and align targets to promote and enable more effective implementation across all biodiversity-related conventions. Results of a survey of 139 key stakeholders from 88 countries suggests streamlining across ministries and agencies, improved coordination mechanisms with all relevant stakeholders, and better knowledge sharing between conventions could improve cooperation among biodiversity-related conventions. The roadmap for improving synergies among conventions agreed to at the 13th Convention on Biological Diversity's Conference of Parties in 2016 includes actions such as mechanisms to avoid duplication in national reporting and monitoring on conventions and capacity building related to information and knowledge sharing. We suggest the scientific community can actively engage and contribute to the policy process by establishing a science-policy platform to address knowledge gaps; improving data gathering, reporting, and monitoring; developing indicators that adequately support implementation of national plans and strategies; and providing evidence-based recommendations to policy makers. The latter will be particularly important as 2020 approaches and work to develop a new biodiversity agenda for the next decade is beginning.     

An economic analysis of China’s domestic crude oil supply policies

ABSTRACT

China’s domestic oil production has lagged the growth in domestic oil consumption since the beginning of the 21st century, leading to a growing reliance on imports. In response, the Chinese government has introduced a number of policies, including import license constraints, to support domestic suppliers. In an effort to measure the economic impact of these policies we develop a short-run equilibrium model of China’s wholesale oil and gas market at the provincial scale. We construct counterfactual scenarios that suggest that relaxing policies that prioritize domestic production in 2016, when the average price of Chinese oil imports was US$42 per barrel (bbl), could have increased China’s import demand by 0.29 million barrels per day (MMbbl/d). This results in a substitution of 9% of China’s domestic production in 2016, and a reduction of US $2.8 billion in crude supply costs including transportation as the imported oil has more direct access to the country’s pipeline network, compared to the displaced domestic production. In addition, rising import prices since mid-2017 may provide a window of opportunity for Chinese policymakers to proceed with further deregulation of the domestic oil sector, as the short-term impact on domestic producers is reduced.     

危险品事故泄漏模糊路网应急资源优化研究

当危险品大规模泄漏事故发生后,应急物资快速配送对于减轻危险品对人员伤害和挽救损失有重要意义。首先从损毁路网修复和救援物资2个方面建立双层模型,从有限物资分配修复损毁路网和救援上进行优化分配,并通过路径优化时间最短分配物资,使应急救援系统的损失最小化。利用宽容分层的方法对模型进行求解,求解最优的物资分配和运输路径方案。最后利用算例,对模型和算法进行检验,找出需要修复受损路网中关键路段。     

天津盘山风景名胜区总体规划环境影响识别探讨

本文以天津盘山风景名胜区总体规划环境影响识别为例,分析规划本身对区域产业、社会、环保产生的直接影响,进而识别规划对资源环境要素产生的间接影响,并确定评价重点。     

Incorporating Uncertainty of Management Costs in Sensitivity Analyses of Matrix Population Models

The importance of accounting for economic costs when making environmental‐management decisions subject to resource constraints has been increasingly recognized in recent years. In contrast, uncertainty associated with such costs has often been ignored. We developed a method, on the basis of economic theory, that accounts for the uncertainty in population‐management decisions. We considered the case where, rather than taking fixed values, model parameters are random variables that represent the situation when parameters are not precisely known. Hence, the outcome is not precisely known either. Instead of maximizing the expected outcome, we maximized the probability of obtaining an outcome above a threshold of acceptability. We derived explicit analytical expressions for the optimal allocation and its associated probability, as a function of the threshold of acceptability, where the model parameters were distributed according to normal and uniform distributions. To illustrate our approach we revisited a previous study that incorporated cost‐efficiency analyses in management decisions that were based on perturbation analyses of matrix population models. Incorporating derivations from this study into our framework, we extended the model to address potential uncertainties. We then applied these results to 2 case studies: management of a Koala (Phascolarctos cinereus) population and conservation of an olive ridley sea turtle (Lepidochelys olivacea) population. For low aspirations, that is, when the threshold of acceptability is relatively low, the optimal strategy was obtained by diversifying the allocation of funds. Conversely, for high aspirations, the budget was directed toward management actions with the highest potential effect on the population. The exact optimal allocation was sensitive to the choice of uncertainty model. Our results highlight the importance of accounting for uncertainty when making decisions and suggest that more effort should be placed on understanding the distributional characteristics of such uncertainty. Our approach provides a tool to improve decision making.     

The costs of avoiding environmental impacts from shale‐gas surface infrastructure

Growing energy demand has increased the need to manage conflicts between energy production and the environment. As an example, shale‐gas extraction requires substantial surface infrastructure, which fragments habitats, erodes soils, degrades freshwater systems, and displaces rare species. Strategic planning of shale‐gas infrastructure can reduce trade‐offs between economic and environmental objectives, but the specific nature of these trade‐offs is not known. We estimated the cost of avoiding impacts from land‐use change on forests, wetlands, rare species, and streams from shale‐energy development within leaseholds. We created software for optimally siting shale‐gas surface infrastructure to minimize its environmental impacts at reasonable construction cost. We visually assessed sites before infrastructure optimization to test whether such inspection could be used to predict whether impacts could be avoided at the site. On average, up to 38% of aggregate environmental impacts of infrastructure could be avoided for 20% greater development costs by spatially optimizing infrastructure. However, we found trade‐offs between environmental impacts and costs among sites. In visual inspections, we often distinguished between sites that could be developed to avoid impacts at relatively low cost (29%) and those that could not (20%). Reductions in a metric of aggregate environmental impact could be largely attributed to potential displacement of rare species, sedimentation, and forest fragmentation. Planners and regulators can estimate and use heterogeneous trade‐offs among development sites to create industry‐wide improvements in environmental performance and do so at reasonable costs by, for example, leveraging low‐cost avoidance of impacts at some sites to offset others. This could require substantial effort, but the results and software we provide can facilitate the process.     

蛙跳算法优化的地下水质评价的参数化组合算子模型

传统的参数化多元组合算子模型在进行对数变换后,采用最小二乘法求解模型参数。在满足构建的优化目标函数条件下,直接用基于群集智能的混合蛙跳算法对参数化组合算子模型中的参数进行优化,避免了传统解法过程中需要进行的对数变换,因而使参数求解变得简化。改进后的参数化组合算子模型被应用于地下水水质评价,其评价结果与用其他多种方法的评价结果基本一致。从而表明:混合蛙跳算法优化得出的地下水水质评价参数化组合算子模型为地下水水质评价提供了一种简便和实用的新方法。