Modelling local and synoptic scale influences on ozone concentrations in a topographically complex region of Southern Italy

A modelling study with the on-line coupled Eulerian chemical-weather model WRF/Chem for the Southern Italian region around Cosenza (Calabria) was conducted to identify the influences of synoptic scale meteorology, local scale wind systems and local emissions on ozone concentrations in this orographically complex region. Four periods of 5–7 days were chosen, one from each season, which had wind pattern characteristics representative of typical local climatological conditions, in order to study the local versus non-local impacts on ozone transport and formation. To account for the complex terrain, the horizontal resolution of the smallest modelling domain was 3 km. Model results were compared with measurements to demonstrate the capability of the model to reproduce ozone concentrations in the region. The comparison was favourable with a mean bias of ?1.1 ppb. The importance of local emissions on ozone formation and destruction was identified with the use of three different emission scenarios. Generally the influence of regional emissions on the average ozone concentration was small. However during periods when mountain-sea wind systems were well developed and synoptic scale winds were weak, the influence of local emissions from the urban area was at its greatest. The maximum influence of local emissions on ozone concentrations was 18 ppb.     

A Bayesian network analysis of workplace accidents caused by falls from a height

This article analyses, using Bayesian networks, the circumstances surrounding workplace tasks performed using auxiliary equipment (ladders, scaffolding, etc.) that may result in falls. The information source was a survey of employees working at a height. We were able to determine the usefulness of this approach – innovative in the accident research field – in identifying the causes that have the greatest bearing on accidents involving auxiliary equipment: in these cases, the adoption of incorrect postures during work and a worker’s inadequate knowledge of safety regulations. Likewise, the duration of tasks was also associated with both these variables, and therefore, with the accident rate. Bayesian networks also enable dependency relationships to be established between the different causes of accidents. This information – which is not usually furnished by conventional statistical methods applied in the field of labour risk prevention – allow a causality model to be defined for workplace accidents in a more realistic way. With this statistic tool, the expert is also provided with useful information that can be input to a management model for labour risk prevention.     

植物修复及强化调控系统根际土壤微生物研究综述

根际土壤微生物是植物修复及其强化修复技术的重要组成部分,了解根际土壤微生物生态效应有助于深入探索修复机制,从而进一步提高修复效率.微生物生态效应反映土壤生态变化,对于有效评估强化调控生态风险具有重要意义.在总结污染土壤植物修复根际微生物生态效应研究的基础上,综述强化调控措施与根际土壤微生物可能存在的相互影响,并分析利用微生物分子生态学技术评估强化调控措施施用风险的可行性.     

Investigation of Environmental Effects Based on Exergetic Irreversibility for Display Cases’ Units in Commercial Cooling

This study examines energetic and exergetic performances of display cases’ units used in market applications depending on different refrigerants. Besides CO₂ emission potential of each refrigerant based on exergetic irreversibility obtained from analyses is calculated by the method of Total Equivalent Warming Impact (TEWI). In this study, 1 kW cooling capacity and vapor compression cooling cycle is taken as reference and refrigerants of R-22, R-134a, R-404A, and R-507 together with alternative refrigerant R-407C and R152a are examined separately. According to analyses, R-404A gas, used widely in market applications, has low performance with average COP 3.89 and average exergy efficiency 55.20%. R-152a gas has the best performance by the thermodynamics parameters including COP 4.49, exergy efficiency 63.79%, and 0.23 kW power consumption and emission parameter 14097.490 ton CO₂/year. Although COP is used as a criterion to evaluate the systems, this study finally emphasizes the importance of exergy analysis and TEWI method which are important methods to determine irreversibility and emission potential of the systems.     

Investigation of Nanoparticle Additives to Biodiesel for Improvement of the Performance and Exhaust Emissions in a Compression Ignition Engine

Worldwide energy demand has been growing steadily during the past five decades and most experts believe that this trend will continue to rise. The amount of emitted harmful emission gases increases in parallel with increasing energy consumption. This increase has forced many countries to take various precautions, and various restrictions on emitted emissions have been carried. In this study, effects of addition of oxygen containing nanoparticle additives to biodiesel on fuel properties and effects on diesel engine performance and exhaust emissions were investigated. Two different nanoparticle additives, namely MgO and SiO₂, were added to biodiesel at the addition dosage of 25 and 50 ppm. Fuel properties, engine performance, and exhaust emission characteristics of obtained modified fuels were examined. As a result of this study, engine emission values NO_x and CO were decreased and engine performance values slightly increased with the addition of nanoparticle additives.