Dynamic risk assessment using failure assessment and Bayesian theory

To ensure the safety of a process system, engineers use different methods to identify the potential hazards that may cause severe consequences. One of the most popular methods used is quantitative risk assessment (QRA) which quantifies the risk associated with a particular process activity. One of QRA's major disadvantages is its inability to update risk during the life of a process. As the process operates, abnormal events will result in incidents and near misses. These events are often called accident precursors. A conventional QRA process is unable to use the accident precursor information to revise the risk profile. To overcome this, a methodology has been proposed based on the work of Meel and Seider (2006). Similar to Meel and Seider (2006) work, this methodology uses Bayesian theory to update the likelihood of the event occurrence and also failure probability of the safety system. In this paper the proposed methodology is outlined and its application is demonstrated using a simple case study. First, potential accident scenarios are identified and represented in terms of an event tree, next, using the event tree and available failure data end-state probabilities are estimated. Subsequently, using the available accident precursor data, safety system failure likelihood and event tree end-state probabilities are revised. The methodology has been simulated using deterministic (point value) as well as probabilistic approach. This Methodology is applied to a case study demonstrating a storage tank containing highly hazardous chemicals. The comparison between conventional QRA and the results from dynamic failure assessment approach shows the significant deviation in system failure frequency throughout the life time of the process unit.     

Gaseous mercury fluxes from the forest floor of the Adirondacks

The flux of gaseous elemental mercury (Hg⁰) from the forest floor of the Adirondack Mountains in New York (USA) was measured numerous times throughout 2005 and 2006 using a polycarbonate dynamic flux chamber (DFC). The Hg flux ranged between −2.5 and 27.2 ng m⁻² h⁻¹ and was positively correlated with temperature and solar radiation. The measured Hg emission flux was highest in spring, and summer, and lowest in winter. During leaf-off periods, the Hg emission flux was highly dependent on solar radiation and less dependent on temperature. During leaf-on periods, the Hg emission flux was fairly constant because the forest canopy was shading the forest floor. Two empirical models were developed to estimate yearly Hg⁰ emissions, one for the leaf-off period and one for the leaf-on period. Using the U.S. EPA's CASTNET meteorological data, the cumulative estimated emission flux was approx. 7.0 μg Hg⁰ m⁻² year⁻¹.     

Release flux of mercury from different environmental surfaces in Chongqing, China

An investigation was conducted to estimate mercury emission to the atmosphere from different environmental surfaces and to assess its contribution to the local mercury budget in Chongqing, China. Mercury flux was measured using dynamic flux chamber (DFC) at six soil sites of three different areas (mercury polluted area, farmland and woodland) and four water surfaces from August 2003 to April 2004. The mercury emission fluxes were 3.5 ± 1.2–8.4 ± 2.5 ng m⁻² h⁻¹ for three shaded forest sites, 85.8 ± 32.4 ng m⁻² h⁻¹ for farming field, 12.3 ± 9.8–733.8 ± 255 ng m⁻² h⁻¹ for grassland sites, and 5.9 ± 12.6–618.6 ± 339 ng m⁻² h⁻¹ for water surfaces. Mercury exchange fluxes were generally higher from air/water surfaces than from air/soil surfaces. The mercury negative fluxes were found in tow soil sites at overcast days (mean = −6.4 ± 1.5 ng m⁻² h⁻¹). The diurnal and seasonal variations of mercury flux were observed in all sites. The mercury emission responded positively to the solar radiation, but negatively to the relative humidity. The mercury flux from air/soil surfaces was significantly correlated with soil temperature, which was well described by an Arrhenius-type expression with activation energy of 31.1 kcal mol⁻¹. The annual mercury emission to the atmosphere from land surface is about 1.787 t of mercury in Chongqing.     

On modelling the global copper mining rates,market supply,copper price and the end of copper reserves

The world supply and turnover of copper was modelled using simple empirical estimates and a COPPER systems dynamics model developed for this study. The model combines mining, trade markets, price mechanisms, population dynamics, use in society and waste as well as recycling, into a whole world system. The degree of sustainability and resource time horizon was estimated using four different methods including (1) burn-off rates, (2) peak discovery early warning, (3) Hubbert's production model, and (4) COPPER, a system dynamics model. The ultimately recoverable reserves (URR) have been estimated using different sources that converge around 2800 million tonne, where about 800 million tonne have already been mined, and 2000 million tonne remain. The different methods independently suggest peak copper mine production in the near future. The model was run for a longer period to cover all systems dynamics and delays. The peak production estimates are in a narrow window in time, from 2031 to 2042, with the best model estimate in 2034, or 21 years from the date of writing. In a longer perspective, taking into account price and recycling, the supply of copper to society is estimated to run out sometime after 2400. The outputs from all models put focus on the importance of copper recycling so that society can become more sustainable with respect to copper supply.