The generation of reliable updated information is critical to support the harmonization of socio-economic and environmental
issues in a context of sustainable development. The agro-environmental assessment and management of agricultural systems often
relies on indicators that are necessary to make sound decisions. This work aims to provide an approach to (a) assess the environmental
performance of commercial farms in the Pampas of Argentina, and (b) propose a methodological framework to calculate environmental
indicators that can rapidly be applied to practical farming. 120 commercial farms scattered across the Pampas were analyzed
in this study during 2002 and 2003. Eleven basic indicators were identified and calculation methods described. Such indicators
were fossil energy (FE) use, FE use efficiency, nitrogen (N) balance, phosphorus (P) balance, N contamination risk, P contamination
risk, pesticide contamination risk, soil erosion risk, habitat intervention, changes in soil carbon stock, and balance of
greenhouse gases. A model named Agro-Eco-Index was developed on a Microsoft-Excel support to incorporate on-farm collected data and facilitate the calculation of indicators
by users. Different procedures were applied to validate the model and present the results to the users. Regression models
(based on linear and non-linear models) were used to validate the comparative performance of the study farms across the Pampas.
An environmental dashboard was provided to represent in a graphical way the behavior of farms. The method provides a tool
to discriminate environmentally friendly farms from those that do not pay enough attention to environmental issues. Our procedure
might be useful for implementing an ecological certification system to reward a good environmental behavior in society (e.g.,
through tax benefits) and generate a commercial advantage (e.g., through the allocation of green labels) for committed farmers. 相似文献
The moisture from skin sweat and atmospheric water affects the thermal protective performance provided by multilayer protective clothing. Four levels of moisture content were selected to evaluate the impact of moisture on thermal protection under dry (thermal radiation) and wet (thermal radiation and low-pressure steam) heat exposure. Also, the role of moisture and its relationship with exposure time were analyzed based on skin heat flux and Henriques integral value. The addition of moisture to a fabric system was found to result in differences in second-degree and third-degree skin burn times. When moisture is added to a fabric system, it both acts as a thermal conductor to present a negative effect and provides a positive effect owing to thermal storage of water and evaporative heat loss. The positive or negative effects of moisture are mainly dependent on the thermal exposure time, the moisture content and the presence of hot steam. 相似文献
Objective: The present research relies on 2 main objectives. The first is to investigate whether latent model analysis through a structural equation model can be implemented on driving simulator data in order to define an unobserved driving performance variable. Subsequently, the second objective is to investigate and quantify the effect of several risk factors including distraction sources, driver characteristics, and road and traffic environment on the overall driving performance and not in independent driving performance measures.
Methods: For the scope of the present research, 95 participants from all age groups were asked to drive under different types of distraction (conversation with passenger, cell phone use) in urban and rural road environments with low and high traffic volume in a driving simulator experiment. Then, in the framework of the statistical analysis, a correlation table is presented investigating any of a broad class of statistical relationships between driving simulator measures and a structural equation model is developed in which overall driving performance is estimated as a latent variable based on several individual driving simulator measures.
Results: Results confirm the suitability of the structural equation model and indicate that the selection of the specific performance measures that define overall performance should be guided by a rule of representativeness between the selected variables. Moreover, results indicate that conversation with the passenger was not found to have a statistically significant effect, indicating that drivers do not change their performance while conversing with a passenger compared to undistracted driving. On the other hand, results support the hypothesis that cell phone use has a negative effect on driving performance. Furthermore, regarding driver characteristics, age, gender, and experience all have a significant effect on driving performance, indicating that driver-related characteristics play the most crucial role in overall driving performance.
Conclusions: The findings of this study allow a new approach to the investigation of driving behavior in driving simulator experiments and in general. By the successful implementation of the structural equation model, driving behavior can be assessed in terms of overall performance and not through individual performance measures, which allows an important scientific step forward from piecemeal analyses to a sound combined analysis of the interrelationship between several risk factors and overall driving performance. 相似文献