Multi-peril risk assessment for business downtime of industrial facilities     

Prabhu  Saurabh  Javanbarg  Mohammad  Lehmann  Marc  Atamturktur  Sez 《Natural Hazards》2019,99(3):1327-1343

The chemical industry is one of the most important industry sectors in terms of energy consumption and CO₂ emissions in China. However, few studies have undertaken accounting of the CO₂ emissions in the chemical industry. In addition, there are some shortcomings in the traditional accounting method as a result of poor data availability, such as the incomplete consideration of emission sources and overestimation of actual emissions. Based on the traditional accounting method and the actual situation of the chemical industry, this study proposes a method called the Emission Accounting Model in the Chemical Industry, which covers fossil energy-related emission, indirect emission generated by electricity and heat, carbonate-related process emission and the reuse of CO₂. In particular, fossil energy used as feedstock is included. By applying the Emission Accounting Model in the Chemical Industry in China, the calculated CO₂ emissions would be 19–30% less than the result from the traditional method. In addition, it is found that the indirect CO₂ emissions generated by electricity and heat account for 67% of the total amount, the fossil energy-related emissions account for approximately 37%, the process-related emissions accounted for 2%, and reuse of CO₂ accounts for ??6% in 2016. The production of ammonia, ethylene and calcium carbide generated approximately half of the total CO₂ emissions in 2016. In addition, in view of emission sources and carbon source flow, two other bottom-up accounting methods are proposed that can take effect when the chemical plant-level data are available.

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Impact of local site conditions on portfolio earthquake loss estimation for different building types     

Elnaz Peyghaleh  Vahidreza Mahmoudabadi  James R. Martin  Alireza Shahjouei  Qiushi Chen  Mohammad Javanbarg  Sara Khoshnevisan 《Natural Hazards》2018,94(1):121-150

This article presents a sensitivity analysis investigating the impact of using high-resolution site conditions databases in portfolio earthquake loss estimation. This article also estimates the effects of variability in the site condition databases on probabilistic earthquake loss ratios and their geographical pattern with respect to structural characteristics of different building types. To perform the earthquake loss estimation here, the OpenQuake software developed by Global Earthquake Model is implemented in Clemson University’s supercomputer. The probabilistic event-based risk analysis is employed considering several notional portfolios of different building types in the San Francisco area as the inventory exposure. This analysis produces the stochastic event sets worth for 10,000 years including almost 8000 synthetically simulated earthquakes. Then, the ground motion prediction equations are used to calculate the ground motion per event and incorporate the effect of five site conditions, on amplifying or de-amplifying the ground motions on notional building exposure locations. Notional buildings are used to account for various building characteristics in conformance with the building taxonomy represented in HAZUS software. The HAZUS damage functions are applied to model the vulnerability of various structural types of buildings. Finally, the 50-year average mean loss and probabilistic loss for multiple values for probability of exceedance (2, 10, 20, and 40%) in 50 years are calculated, and the impact of different site condition databases on portfolio loss ratios is investigated for different structural types and heights of buildings. The results show the aggregated and geographical variation of loss and loss ratio throughout the region for various site conditions. Comparing the aggregated loss and loss ratio, while considering different databases, represents normalized differences that are limited to 6% for all building taxonomy with various heights and for all PoEs. However, site-specific loss ratio errors are significantly greater and in some cases are more than 20%.  相似文献