Using consequence analysis on some chlorine operation hazards and their possible effects on neighborhoods in central Taiwan

The applications of chlorine have been broadly used in many industrial products, such as bleaching agents, synthetic rubbers, plastics, disinfectants, iron chlorides, fire refractory materials, insecticides, and anti-freezers, etc. According to the Taiwan Environmental Protection Administration (TEPA), more than 30 thousand tons were used in the year 2000. In addition, there were more than 12 reported incidents from 2000 to 2003—mostly on using chlorine as disinfectants (five) and as process agents (four).

This study investigated 15 chlorine operation plants in central Taiwan. These chlorine usages included bleaching agents, disinfectants, iron chloride, synthesizing rubber plastics, and others. Thirteen plants were located in the industrial parks and two were in or near residential zones. The consequence analysis were used three different methods to analyze the worst-case scenarios (WCSs) and alternative release case scenarios (ACSs) in order to compare impact zones for applying various active and passive mitigation systems, such as confined space, scrubber, water-spray, and so no. For two plants in or near residential zones, multi-layers mitigation systems and operation limits should be implemented in order to enforce more stringent protection measures. However, there was no specific regulation for chlorine plants operated at different locations, such as industrial parks or residential zones. In order to reduce chemical accidents and their impacts on public safety, our results suggest that source mitigation/management and warning systems should be adopted simultaneously.     

Information Network Topologies for Enhanced Local Adaptive Management

We examined the principal effects of different information network topologies for local adaptive management of natural resources. We used computerized agents with adaptive decision algorithms with the following three fundamental constraints: (1) Complete understanding of the processes maintaining the natural resource can never be achieved, (2) agents can only learn by experimentation and information sharing, and (3) memory is limited. The agents were given the task to manage a system that had two states: one that provided high utility returns (desired) and one that provided low returns (undesired). In addition, the threshold between the states was close to the optimal return of the desired state. We found that networks of low to moderate link densities significantly increased the resilience of the utility returns. Networks of high link densities contributed to highly synchronized behavior among the agents, which caused occasional large-scale ecological crises between periods of stable and high utility returns. A constructed network involving a small set of experimenting agents was capable of combining high utility returns with high resilience, conforming to theories underlying the concept of adaptive comanagement. We conclude that (1) the ability to manage for resilience (i.e., to stay clear of the threshold leading to the undesired state as well as the ability to re-enter the desired state following a collapse) resides in the network structure and (2) in a coupled social–ecological system, the systemwide state transition occurs not because the ecological system flips into the undesired state, but because managers lose their capacity to reorganize back to the desired state. An erratum to this article can be found at .     

Socio-economic Comparison Between Traditional and Improved Cultivation Methods in Agroforestry Systems, East Usambara Mountains, Tanzania

The East Usambara Mountains, recognized as one of the 25 most important biodiversity hot spots in the world, have a high degree of species diversity and endemism that is threatened by increasing human pressure on resources. Traditional slash and burn cultivation in the area is no longer sustainable. However, it is possible to maintain land productivity, decrease land degradation, and improve rural people’s livelihood by ameliorating cultivation methods. Improved agroforestry seems to be a very convincing and suitable method for buffer zones of conservation areas. Farmers could receive a reasonable net income from their farm with little investment in terms of time, capital, and labor. By increasing the diversity and production of already existing cultivations, the pressure on natural forests can be diminished. The present study shows a significant gap between traditional cultivation methods and improved agroforestry systems in socio-economic terms. Improved agroforestry systems provide approximately double income per capita in comparison to traditional methods. More intensified cash crop cultivation in the highlands of the East Usambara also results in double income compared to that in the lowlands. However, people are sensitive to risks of changing farming practices. Encouraging farmers to apply better land management and practice sustainable cultivation of cash crops in combination with multipurpose trees would be relevant in improving their economic situation in the relatively short term. The markets of most cash crops are already available. Improved agroforestry methods could ameliorate the living conditions of the local population and protect the natural reserves from human disturbance.     

MODELING THE DISTRIBUTION OF DIFFUSE NITROGEN SOURCES AND SINKS IN THE NEUSE RIVER BASIN OF NORTH CAROLINA,USA1

This study quantified nonpoint source nitrogen (NPS‐N) sources and sinks across the 14,582 km² Neuse River Basin (NRB) located in North Carolina, to provide tabular data summaries and graphic overlay products to support the development of management approaches to best achieve established N reduction goals. First, a remote sensor derived, land cover classification was performed to support modeling needs. Modeling efforts included the development of a mass balance model to quantify potential N sources and sinks, followed by a precipitation event driven hydrologic model to effectively transport excess N across the landscape to individual stream reaches to support subsequent labeling of transported N values corresponding to source origin. Results indicated that agricultural land contributed 55 percent of the total annual NPS‐N loadings, followed by forested land at 23 percent (background), and urban areas at 21 percent. Average annual N source contributions were quantified for agricultural (1.4 kg/ha), urban (1.2 kg/ha), and forested cover types (0.5 kg/ha). Nonpoint source‐N contributions were greatest during the winter (40 percent), followed by spring (32 percent), summer (28 percent), and fall (0.3 percent). Seasonal total N loadings shifted from urban dominated and forest dominated sources during the winter, to agricultural sources in the spring and summer. A quantitative assessment of the significant NRB land use activities indicated that high (greater than 70 percent impervious) and medium (greater than 35 percent impervious) density urban development were the greatest contributors of NPS‐N on a unit area basis (1.9 and 1.6 kg/ha/yr, respectively), followed by row crops and pasture/hay cover types (1.4 kg/ha/yr).     

Food justice youth development: using Photovoice to study urban school food systems*

How do youth learn through participation in efforts to study and change the school food system? Through our participatory youth action research (YPAR) project, we move beyond the “youth as consumer” frame to a food justice youth development (FJYD) approach. We track how a group of youth learned about food and the public policy process through their efforts to transform their own school food systems by conducting a participatory evaluation of farm-to-school efforts in collaboration with university and community partners. We used the Photovoice research method, placing cameras in the hands of young people so that they themselves could document and discuss their concerns and perspectives. The research was designed to gain insight about youths’ knowledge of food, health, and community food systems. Drawing upon the youth group’s insights, we build a framework for building critical consciousness through FJYD.     

Developing an interdisciplinary and cross‐sectoral community of practice in the domain of forests and livelihoods

Although significant resources are being spent researching and fostering the relationship between forests and livelihoods to promote mutually beneficial outcomes, critical gaps in understanding persist. A core reason for such gaps is that researchers, practitioners, and policy makers lack the structured space to interact and collaborate, which is essential for effective, interdisciplinary research, practice, and evaluation. Thus, scientific findings, policy recommendations, and measured outcomes have not always been synthesized into deep, systemic understanding; learning from practice and implementation does not easily find its way into scientific analyses, and science often fails to influence policy. Communities of practice (CofPs) are dynamic sociocultural systems that bring people together to share and create knowledge around a common topic of interest. They offer participants a space and structure within which to develop new, systemic approaches to multidimensional problems on a common theme. Uniquely informed by a systems‐thinking perspective and drawing from the scientific and gray literatures and in‐depth interviews with representatives of established CofPs in the natural resource management and development domain, we argue that a well‐designed and adequately funded CofP can facilitate interdisciplinary and cross‐sectoral relationships and knowledge exchange. Well‐designed CofPs integrate a set of core features and processes to enhance individual, collective, and domain outcomes; they set out an initial but evolving purpose, encourage diverse leadership, and promote collective‐identity development. Funding facilitates effective communication strategies (e.g., in person meetings). We urge our colleagues across sectors and disciplines to take advantage of CofPs to advance the domain of forests and livelihoods.     

State of research on the automation of HAZOP studies

For more than 30 years, multiple research groups have worked on the automation of hazard and operability (HAZOP) studies, or more specifically on the hazard identification process. So far, very few of these approaches have been used in the chemical process industry. Automatic hazard identification is a knowledge-intensive process that demands high standards with regard to the way in which knowledge is stored and made available. There are various suitable approaches to the qualitative modeling of processes and plants, which are the foundation for reasoning systems that are used for the identification of hazards. Additionally, there are quantitative methods that are based on process simulations and can be used to identify potential hazards. The investigation of the state of research demonstrates that there are sophisticated technologies for automated systems that include powerful reasoning techniques. The benefits and shortcomings of existing technologies are discussed with regard to their industrial applicability. Often, the quality of the necessary specific and generic knowledge is not sufficient to detect potential hazardous events and operational malfunctions. Computer-aided HAZOP systems should be integrated with computer-aided design- or process simulation software using common data models based on the digital representation of the process plant. In order to be used by HAZOP practitioners automated systems need to be comprehensive, serve as specialized decision support systems, and be tested and evaluated using round robin tests.     

How certain are we about the certainty-equivalent long term social discount rate?

Theoretical arguments for using a term structure of social discount rates (SDR) that declines with the time horizon have influenced government guidelines in the US and Europe. The certainty equivalent discount rate that often underpins this guidance embodies uncertainty in the primitives of the SDR, such as growth. For distant time horizons the probability distributions of these primitives are ambiguous and the certainty equivalent itself is uncertain. Yet, if a limited set of characteristics of the unknown probability distributions can be agreed upon, ‘sharp’ upper and lower bounds can be defined for the certainty-equivalent SDR. Unfortunately, even with considerable agreement on these features, these bounds are widely spread for horizons beyond 75 years. So while estimates of the present value of intergenerational impacts, including the social cost of carbon, can be bounded in the presence of this ambiguity, they typically remain so imprecise as to provide little practical guidance.     

Solar energy for electricity and fuels

Solar energy conversion into electricity by photovoltaic modules is now a mature technology. We discuss the need for materials and device developments using conventional silicon and other materials, pointing to the need to use scalable materials and to reduce the energy payback time. Storage of solar energy can be achieved using the energy of light to produce a fuel. We discuss how this can be achieved in a direct process mimicking the photosynthetic processes, using synthetic organic, inorganic, or hybrid materials for light collection and catalysis. We also briefly discuss challenges and needs for large-scale implementation of direct solar fuel technologies.     

Fuzzy experts on recreational vessels, a risk modelling approach for marine invasions

Understanding risks from the human-mediated spread of non-indigenous species (NIS) is a critical component of marine biosecurity management programmes. Recreational boating is well-recognised as a NIS pathway, especially at a regional scale. Assessment of risks from this pathway is therefore desirable for coastal environments where recreational boating occurs. However, formal or quantitative risk assessment for the recreational vessel pathway is often hampered by lack of data, hence often relies on expert opinion. The use of expert opinion itself is sometimes limited by its inherent vagueness, which can be an important source of uncertainty that reduces the validity and applicability of the assessment. Fuzzy logic, specifically interval type-2 fuzzy logic, is able to model and propagate this type of uncertainty, and is a useful technique in risk assessment where expert opinion is relied upon. The present paper describes the implementation of a NIS fuzzy expert system (FES) for assessing the risk of invasion in marine environments via recreational vessels. The FES was based on expert opinion gathered through systematic elicitation exercises, designed to acknowledge important uncertainty sources (e.g., underspecificity and ambiguity). The FES, using interval type-2 fuzzy logic, calculated an invasion risk value (integrating NIS infection and detection probabilities) for a range of invasion scenarios. These scenarios were defined by all possible combinations of two vessel types (moored and trailered), five vessel components (hull, deck, internal spaces, anchor, fishing gear), two infection modes (fouling, water/sediment retention) and six frequently visited marine habitats (marina, mooring, farm, ramp, wharf, anchorage). Although invasion risk values determined using the FES approach was scenario-specific, general patterns were identified. Moored vessels consistently showed higher invasion risk values than trailered vessels. Invasion risk values were higher for anchorages, moorings and wharves. Similarly, hull-fouling was revealed as the highest infection risk mode after pooling results across all habitats. The NIS fuzzy expert system presented here appears as a valuable prioritising and decision-making tool for NIS research, prevention and control activities. Its easy implementation and wide applicability should encourage the development and application of this type of system as an integral part of biosecurity, and other environmental management plans.