Sensitivity analysis of Phast’s atmospheric dispersion model for three toxic materials (nitric oxide, ammonia, chlorine)

We present the results of a parametric sensitivity analysis of a widely used model for atmospheric dispersion of toxic gases, in order better to understand the influence of user-adjustable parameters on model outputs. We have studied 60 min continuous release scenarios for three different products (nitric oxide, ammonia and chlorine), chosen to cover a range of physical characteristics and storage conditions. For each product, we have broken down base-case scenarios into a number of sub-scenarios corresponding to different release conditions which determine physical phenomena (flow rate, release angle, release elevation and atmospheric stability class). The use of statistical tools to analyze the results of a large number of model executions allows us to rank model parameters according to their influence on the variability of a number of model outputs (distances and concentrations), on a per-scenario and per-product basis. Analysis of the results allows us to verify our understanding of the modeling of cloud dispersion.     

Relationships between diversity of grassland vegetation, field characteristics and land use management practices assessed at the farm level

In order to assess the impact of policies to encourage extensification in less favoured areas and improve our knowledge of extensive livestock systems, we analyzed relationships between the diversity of grassland vegetation and land use management practices and field characteristics. This study, conducted on a mountainous area in the centre of France, was based on 149 fields, mainly of natural grasslands belonging to 7 farmers. Regression analyses were performed to analyze the relations between the grassland vegetation types (five types established from the list of dominant species), management practices (cutting versus grazing and fertilization) and the topographic (altitude and aspect) and topologic (slope, distance and surface area) characteristics of the fields. The land use management rules used by the farmers were studied by specifying the grazing management rules of the herd (dairy cows), as well as those for conserved forage (mainly hay or silage) and were identified from observations mentioned on the “grazing schedules”, as well as from interviews at the beginning, in the middle and at the end of the study period. The statistical analysis showed that neither the topographic characteristics of the fields nor the distance from the cowshed or surface area were correlated with the grassland vegetation types. It was the management practices used, largely determined by the field slope, which determined the grassland vegetation type. On the other hand, farmers’ statements showed that the grazing and cutting management rules were mostly determined by the slope of the fields and the distance from the cowshed and, to a lesser extent, by the altitude and aspect. These results showed that the farmers take into consideration environmental differences when choosing fields to allocate for grazing and cutting at different seasons, particularly when they are constrained by these features. Nevertheless, when the constraints were minimal, a wide diversity of grassland vegetation types was also observed. This diversity was a result of attributing different functions to the fields which led to different management practices (defoliation methods and fertilization) and, thus, to different grassland vegetation types. Consequently, for farms where animal feed requirements vary according to the time of the year and the type of animal, we suggest that diversity in the grassland vegetation types is a sound component of these livestock systems.     

A goal oriented indicator framework to support integrated assessment of new policies for agri-environmental systems

The goal oriented framework (GOF) for indicators has been developed as part of a comprehensive research project developing computerised tools for integrated assessment of the effects of new policies or technologies on agricultural systems (SEAMLESS-IF). The ambition has therefore been to create an indicator framework where the environmental, economic and social dimensions of sustainable development can be related to each other in a consistent way. Integrated assessment tools rely on such frameworks to capture and visualise trade-offs (antagonisms or synergies) among indicators between and within the three dimensions of sustainable development. The specific aims of this paper are to (i) present the GOF (ii) present how the GOF can be used to select indicators within the integrated assessment framework SEAMLESS-IF and (iii) discuss the advantages and limitations with the proposed approach. We show that the GOF has several advantages. Its major rewards are its relative simplicity and the possibility to link indicators to policy goals of each dimension of sustainability and thereby facilitate the comparison of the impacts of the new policy on the different dimensions. Another important feature of the GOF is its multi-scale perspective, which will enable the comparison of effects of a new policy between scales. Yet, as typical for all indicator frameworks, the GOF has also biases either instigated by the issues the included models cover or by the stakeholders’ selection of indicators. However, due to the way the GOF and its indicators are technically implemented in SEAMLESS-IF, it can easily be extended and include new indicators to increase and update its policy relevance.     

A Review of Known and Hypothetical Transmission Routes for Noroviruses

Human noroviruses (NoVs) are considered a worldwide leading cause of acute non-bacterial gastroenteritis. Due to a combination of prolonged shedding of high virus levels in feces, virus particle shedding during asymptomatic infections, and a high environmental persistence, NoVs are easily transmitted pathogens. Norovirus (NoV) outbreaks have often been reported and tend to affect a lot of people. NoV is spread via feces and vomit, but this NoV spread can occur through several transmission routes. While person-to-person transmission is without a doubt the dominant transmission route, human infective NoV outbreaks are often initiated by contaminated food or water. Zoonotic transmission of NoV has been investigated, but has thus far not been demonstrated. The presented review aims to give an overview of these NoV transmission routes. Regarding NoV person-to-person transmission, the NoV GII.4 genotype is discussed in the current review as it has been very successful for several decades but reasons for its success have only recently been suggested. Both pre-harvest and post-harvest contamination of food products can lead to NoV food borne illness. Pre-harvest contamination of food products mainly occurs via contact with polluted irrigation water in case of fresh produce or with contaminated harvesting water in case of bivalve molluscan shellfish. On the other hand, an infected food handler is considered as a major cause of post-harvest contamination of food products. Both transmission routes are reviewed by a summary of described NoV food borne outbreaks between 2000 and 2010. A third NoV transmission route occurs via water and the spread of NoV via river water, ground water, and surface water is reviewed. Finally, although zoonotic transmission remains hypothetical, a summary on the bovine and porcine NoV presence observed in animals is given and the presence of human infective NoV in animals is discussed.     

Comparison of Extraction Methods for the Detection of Tick-Borne Encephalitis Virus RNA in Goat Raw Milk and Cream Cheese

Food and Environmental Virology - Infection with the tick-borne encephalitis virus (TBEV) can cause meningitis, meningoencephalitis and myelitis in humans. TBEV is an enveloped RNA virus of the...     

Identification and chemical characterization of industrial particulate matter sources in southwest Spain

A detailed physical and chemical characterization of coarse particulate matter (PM10) and fine particulate matter (PM2.5) in the city of Huelva (in Southwestern Spain) was carried out during 2001 and 2002. To identify the major emission sources with a significant influence on PM10 and PM2.5, a methodology was developed based on the combination of: (1) real-time measurements of levels of PM10, PM2.5, and very fine particulate matter (PM1); (2) chemical characterization and source apportionment analysis of PM10 and PM2.5; and (3) intensive measurements in field campaigns to characterize the emission plumes of several point sources. Annual means of 37, 19, and 16 microg/m3 were obtained for the study period for PM10, PM2.5, and PM1, respectively. High PM episodes, characterized by a very fine grain size distribution, are frequently detected in Huelva mainly in the winter as the result of the impact of the industrial emission plumes on the city. Chemical analysis showed that PM at Huelva is characterized by high PO4(3-) and As levels, as expected from the industrial activities. Source apportionment analyses identified a crustal source (36% of PM10 and 31% of PM2.5); a traffic-related source (33% of PM10 and 29% of PM2.5), and a marine aerosol contribution (only in PM10, 4%). In addition, two industrial emission sources were identified in PM10 and PM2.5: (1) a petrochemical source, 13% in PM10 and 8% in PM2.5; and (2) a mixed metallurgical-phosphate source, which accounts for 11-12% of PM10 and PM2.5. In PM2.5 a secondary source has been also identified, which contributed to 17% of the mass. A complete characterization of industrial emission plumes during their impact on the ground allowed for the identification of tracer species for specific point sources, such as petrochemical, metallurgic, and fertilizer and phosphate production industries.