Scenario deduction of Natech accident based on dynamic Bayesian network: A case study of landslide accident in a liquor storage tank area in Guizhou Province,China

Industrial technical accidents caused by natural disasters are defined as Natech accidents, such as earthquakes and landslides, which can cause tremendous damage to industrial storage tanks, and lead to accidental leakage and even serious fire and explosion accidents. In this study, a landslide-induced storage tank accident model under earthquake disasters was proposed, and the relationship between landslide mass impact and target impact resistance was taken into account. Also, tank failure and the formation of the pool fire were considered to be the consequences of the Natech accident. Through scenario deduction, the dynamic process of landslide Natech was transformed qualitatively into a disaster chain network diagram composed of a scenario state, a disaster-causing factor and emergency management. The Bayesian network was used to learn and deduce the parameters of the network diagram, and in this process, the prior probability and conditional probability of nodes were obtained primarily by Monte Carlo simulation, and by an improved expert scoring method based on the fuzzy set theory. Through visualization software, the sensitivity analysis of landslide Natech was achieved. Finally, a case study of a liquor storage tank area in Guizhou Province, China was carried out, and the results show that a large amount of hazardous material leakage caused by buckling is key to the formation of pool fire accidents, and several prevention measures for earthquake-induced landslide Natech was proposed according to the sensitivity analysis.     

Optimal water quality monitoring network design for river systems

Typical tasks of a river monitoring network design include the selection of the water quality parameters, selection of sampling and measurement methods for these parameters, identification of the locations of sampling stations and determination of the sampling frequencies. These primary design considerations may require a variety of objectives, constraints and solutions. In this study we focus on the optimal river water quality monitoring network design aspect of the overall monitoring program and propose a novel methodology for the analysis of this problem. In the proposed analysis, the locations of sampling sites are determined such that the contaminant detection time is minimized for the river network while achieving maximum reliability for the monitoring system performance. Altamaha river system in the State of Georgia, USA is chosen as an example to demonstrate the proposed methodology. The results show that the proposed model can be effectively used for the optimal design of monitoring networks in river systems.     

The social context of childcare practices and child malnutrition in Niger's recent food crisis

In 2004–05, Niger suffered a food crisis during which global attention focused on high levels of acute malnutrition among children. In response, decentralised emergency nutrition programmes were introduced into much of southern Niger. Child malnutrition, however, is a chronic problem and its links with food production and household food security are complex. This qualitative, anthropological study investigates pathways by which children are rendered vulnerable in the context of a nutritional 'emergency'. It focuses on household-level decisions that determine resource allocation and childcare practices in order to explain why practices apparently detrimental to children's health persist. Risk aversion, the need to maintain self-identity and status, and constrained decision making result in a failure to invest extra necessary resources ingrowth-faltering children. Understanding and responding to the social context of child malnutrition will help humanitarian workers to integrate their efforts more effectively with longer-term development programmes aimed at improving livelihood security.     

基于灰色BP网络的火灾事故预测

将BP网络模型与灰色系统预测方法相结合,利用人工神经网络对GM(1,1)模型进行残差修正,建立了火灾事故预测模型.该模型兼具灰色系统与BP网络的优点,不但能体现火灾复杂的灰色系统行为,又能根据每次学习误差的不同调整学习速率,加快收敛速度.与单一的GM(1,1)模型相比,该模型预测结果具有更高的精度.     

Strategies for sustainable development of industrial park in Ulsan,South Korea—From spontaneous evolution to systematic expansion of industrial symbiosis

The Korea National Cleaner Production Center (KNCPC) affiliated to the Korea Institute of Industrial Technology (KITECH) has started a 15 year, 3-phase EIP master plan with the support of Ministry of Commerce, Industry, and Energy (MOCIE). A total of 6 industrial parks, including industrial parks in Ulsan city, known as the industrial capital of South Korea, are planning projects to find the feasibility of shifting existing industrial parks to eco-industrial parks. The basic survey shows that Ulsan industrial complex has been continuously evolving from conventional industrial complexes to eco-industrial parks by spontaneous industrial symbiosis. This paper describes the Korean national policies and the developmental activities of this vision to drive the global trend of innovation for converting the existing industrial parks to eco-industrial parks through inter-industry waste, energy, and material exchange in Ulsan Industrial complexes. In addition, the primary and supportive components of the Ulsan EIP pilot project, which will be implemented for 5 years is elaborated with its schedules and economic benefits.     

Transaction Costs Economics of Irreplaceability: <Emphasis Type="Italic">ex ante</Emphasis> and <Emphasis Type="Italic">ex post</Emphasis> Evaluation of Conservation Networks’ Vulnerability to Environmental Shocks

The theoretical concept, “asset specificity,” is applied to real data in the context of Danish nature conservation network planning in order to produce illustrative examples of an economic measure of the network’s vulnerability to exogenous shocks to the species composition. Three different measures of asset specificity are quantified from the shadow value of eliminating a key species from the individual grid cells. This represents a novel approach and a different interpretation of the term, as it is conventionally used as a qualitative indicator in the transaction cost economics literature. Apart from supplementing existing cost measures with an indicator of risk associated with investments in protected areas, this study demonstrates how the estimation and interpretation of various asset specificity measures for geographical areas may qualify policy makers’ choice of policy instrument in conservation planning. This differs from the more intuitive approach of basing policy instrument choice solely on the rarity of the species in a given area.     

When Has an Abandoned Field Become a Semi-Natural Grassland or Heathland?

This study presents a meta-analysis of a collective dataset describing the succession from abandoned fields to semi-natural grassland and heathland vegetation over the past century. The study objectives were to develop a method for statistical discrimination between abandoned fields and semi-natural habitats and to analyze the probability that an abandoned field had developed into a semi-natural habitat. A statistical classification model was developed, based on lists of vascular plants from 2059 plots from Danish semi-natural grasslands and heathlands, and abandoned fields of varying age. This model was shown to discriminate effectively between abandoned fields and semi-natural habitats, and it was found to be potentially useful for the detection of abandoned fields approaching semi-natural vegetation. We suggest that the model may help clarify restoration targets and assess biological condition in formerly cultivated areas. Statistical modeling revealed that succession age, period of abandonment and succession trajectory had significant effects on the probability that abandoned fields reached the semi-natural phase. Our study indicates that restoration projects targeting grassland and heathland should take local species pools and soil fertility into account. Nomenclature: Species names follow Flora Europaea (Tutin and others 1964–1993).     

Characterization of humic substances of different origin by means of mass spectrometry and neural networks

Mass spectrometry fingerprinting of humic acids extracted from different soils has been carried out using laser desorption/ionization mass spectrometry (LDI-TOF MS). LDI-TOF MS provides characteristic mass spectra fingerprints for the humic acids of different origin. The information given in the fingerprints was evaluated for natural grouping trends in the samples by neural networks computing tools, such as self-organizing feature map (SOFM). This approach is efficient for recognizing patterns in the humic acids samples independently of their characteristic variability; variability characterizing natural products such as humic substances. The use of multi-layer perceptron artificial neural networks gave a successful classification of the samples.     

Resource frontiers and agglomeration economies: The varied logics of transnational land-based investing in Southern and Eastern Africa

Actor-level data on large-scale commercial agriculture in Sub-Saharan Africa are scarce. The peculiar choice of transnational investing in African land has, therefore, been subject to conjecture. Addressing this gap, we reconstructed the underlying logics of investment location choices in a Bayesian network, using firm- and actor-level interview and spatial data from 37 transnational agriculture and forestry investments across 121 sites in Mozambique, Zambia, Tanzania, and Ethiopia. We distinguish four investment locations across gradients of resource frontiers and agglomeration economies to derive the preferred locations of different investors with varied skillsets and market reach (i.e., track record). In contrast to newcomers, investors with extensive track records are more likely to expand the land use frontier, but they are also likely to survive the high transaction costs of the pre-commercial frontier. We highlight key comparative advantages of Southern and Eastern African frontiers and map the most probable categories of investment locations.Supplementary informationThe online version contains supplementary material available at 10.1007/s13280-021-01682-z.