Investigative consequence analysis: A case study research of beirut explosion accident

Around 15:00 GMT on August 4th, an explosion occurred in the warehouse facility storing Ammonium Nitrate (AN) at Beirut port, Lebanon. The explosion resulted in more than 178 fatalities and injured more than 6500 people, and also left an estimated 300,000 people homeless and registered as an equivalent to a 3.3 magnitude earth quake. The accident was considered to be the largest of its kind and the most severe anthropological disaster of the decade, the financial loss the nation was subjected to post the explosion was estimated to be around $ 15 billion as informed by the governor. The storage conditions of ammonium nitrate at Beirut port is not definitively known to anyone, and there is no documentation provided so far from the authorities regarding the same. This work focuses on the investigation & consequence analysis of the explosion using TNT equivalent approach. The overpressure and the impulse obtained from TNT calculations are used in probit models to assess the damages caused on human beings and structures. The results obtained in this investigative approach are then utilized to provide an analytical inference relative to the damage proxy map reported by the advance rapid imaging analysis team from NASA. Also, this work examines the existing standards, fire safety measures and legal regulations for ammonium nitrate facilities in the region. AN explosion during storage like other fire and explosion accidents are definitely preventable owing to the technological advancements and developments to prevent or extinguish controllable fires. The significance of this work relates to the methods for calculation of consequences of explosion that are happening due to the storage of highly hazardous explosive materials in excessive quantities and insists the necessity of incorporating adequate safety measures while storing such reactive and hazardous materials.     

Evaluating the role of environmental quality in the sustainable rural economic development of England

The issue of the sustainable development of rural economies in England has recently received considerable attention. This is because many of the poorest areas in the country are rural, often of high environmental quality, but suffering from high unemployment and a lack of services and facilities. The rapid decline in agricultural incomes and in-migration of affluent urban workers since 1990 has exacerbated economic inequality in such areas. A number of factors have the potential to drive rural development and this paper applies, and considers, the feasibility of a method from the USA for combining economic and environmental variables in a regional growth model to examine the hypothesis that environmental quality is an important determinant of sustainable rural development in England. The model output suggests that, although environmental quality does play a role in sustainable rural development in England there are other, more important, factors driving development. These include business and communications infra-structure, the degree and opportunities for commuting and underlying employment prospects. The robustness and limitations of the method for combining economic and environmental variables is discussed in relation to the spatial interrelatedness of Local Authority Districts in England, and conclusions are drawn about areas for refinement and improvement of the method.

环境-经济系统整合模型的构建研究

环境经济系统整合模型的研究将环境的、经济的、社会的因素整合在可持续发展框架中．模拟、分析经济系统与环境系统之闻的相互作用和反馈关系。本文在分析环境经济系统整合模型构建的背景、理论与方法的基础上．设计了环境经济系统整合模型开发的技术路线．提出了环境经济系统整合模型的主要内容。     

Proposal of Indicators to Assess Urban Sustainability in Brazil

The research related here focuses on municipal situations where problems of sustainability may be defined and tackled on the basis of bottom-up management procedures with the participation of organized society. The aim is to build management models that may be implemented with reasonable administrative effort and cost. Implementation pursues the target of approaching a sustainable situation in the municipality. Environmental parameters for an ideal municipality with undefined geographical location are presented. For each parameter, a set of indicators is developed that can measure the prospect of sustainability. The indicators are defined in terms of numbers or literal concepts according to the possibility of measurement. Examples of management models are presented, which are able to approach the situation defined as sustainable by the indicators. The basic management tool is the learning curve of targeted communities, which is experimentally developed and applied. The indicators are grouped according to their range of applicability.     

New Development in Study of the Faustmann Optimal Forest Harvesting

Chinese forest resources have become very scarce in the face of rapid economic growth demand, while the reform of collective forest right system is in full swing across the country. It will directly affect the regeneration level of forest resources and the diverse ecological value functions. In this article, the mainstream model paradigm of forest economics, that is, the basic framework of the Faustmann model and its evolution process are made in a more detailed explanation, especially the extended model in...     

Using the land transformation model to forecast vacant land

Growing or shrinking cities can experience increases in vacant land. As urban populations and boundaries fluctuate, holes can open in once tight urban areas. Many cities chase growth-oriented approaches to dealing with vacancies. It is critical to understand land-use alteration to accurately predict transformations of physical change in order to make better informed decisions about this phenomenon. This research utilizes the land transformation model (LTM), an artificial neural networking mechanism in Geographic Information Systems, to forecast vacant land. Variable influence on vacant land prediction and accuracy of the LTM is assessed by comparing input factors and patterns, using time-series data from 1990 to 2010 in Fort Worth, Texas, USA. Results indicate that the LTM can be useful in simulating vacant land-use changes but more precise mechanisms are necessary to increase accuracy. This will allow for more proactive decisions to better regulate the process of urban decline and regeneration.     

Vertical migration of radionuclides in undisturbed grassland soils

Literature data on numerical values obtained for the parameters of the two most popular models for simulating the migration of radionuclides in undisturbed soils have been compiled and evaluated statistically. Due to restrictions on the applicability of compartmental models, the convection–dispersion equation and its parameter values should be preferred. For radiocaesium, recommended values are derived for its effective convection velocity and dispersion coefficient. Data deficiencies still exist for radionuclides other than caesium and for soils of non-temperate environments.     

Modelling plant species richness using functional groups

Conservation biologists increasingly rely on spatial predictive models of biodiversity to support decision-making. Therefore, highly accurate and ecologically meaningful models are required at relatively broad spatial scales. While statistical techniques have been optimized to improve model accuracy, less focus has been given to the question: How does the autecology of a single species affect model quality? We compare a direct modelling approach versus a cumulative modelling approach for predicting plant species richness, where the latter gives more weight to the ecology of functional species groups. In the direct modelling approach, species richness is predicted by a single model calibrated for all species. In the cumulative modelling approach, the species were partitioned into functional groups, with each group calibrated separately and species richness of each group was cumulated to predict total species richness. We hypothesized that model accuracy depends on the ecology of individual species and that the cumulative modelling approach would predict species richness more accurately. The predictors explained plant species richness by ca. 25%. However, depending on the functional group the deviance explained varied from 3 to 67%. While both modelling approaches performed equally well, the models of the different functional groups highly varied in their quality and their spatial richness pattern. This variability helps to improve our understanding on how plant functional groups respond to ecological gradients.     

Bayesian Small Area Models for Assessing Wildlife Conservation Risk in Patchy Populations

Abstract:  Species conservation risk assessments require accurate, probabilistic, and biologically meaningful maps of population distribution. In patchy populations, the reasons for discontinuities are not often well understood. We tested a novel approach to habitat modeling in which methods of small area estimation were used within a hierarchical Bayesian framework. Amphibian occurrence was modeled with logistic regression that included third-order drainages as hierarchical effects to account for patchy populations. Models including the random drainage effects adequately represented species occurrences in patchy populations of 4 amphibian species in the Oregon Coast Range (U.S.A.). Amphibian surveys from other locations within the same drainage were used to calibrate local drainage-scale effects. Cross-validation showed that prediction errors for calibrated models were 77% to 86% lower than comparable regionally constructed models, depending on species. When calibration data were unavailable, small area and regional models performed similarly, although poorly. Small area estimation models complement wildlife ecology and habitat studies, and can help managers develop a regional picture of the conservation status for relatively rare species.