Seismic hazard estimation based on the distributed seismicity in northern China

In this paper, we have proposed an alternative seismic hazard modeling by using distributed seismicites. The distributed seismicity model does not need delineation of seismic source zones, and simplify the methodology of probabilistic seismic hazard analysis. Based on the devastating earthquake catalogue, we established three seismi- city model, derived the distribution of a-value in northern China by using Gaussian smoothing function, and cal-culated peak ground acceleration distributions for this area with 2%, 5% and 10% probability of exceedance in a 50-year period by using three attenuation models, respectively. In general, the peak ground motion distribution patterns are consistent with current seismic hazard map of China, but in some specific seismic zones which in-clude Shanxi Province and Shijiazhuang areas, our results indicated a little bit higher peak ground motions and zonation characters which are in agreement with seismicity distribution patterns in these areas. The hazard curves have been developed for Beijing, Tianjin, Taiyuan, Tangshan, and Ji’nan, the metropolitan cities in the northern China. The results showed that Tangshan, Taiyuan, Beijing has a higher seismic hazard than that of other cities mentioned above.     

Ground motion attenuation relation for small to moderate earthquakes in Fujian region, China

We collect 1974 broad-band velocity records of 94 earthquakes (ML=2.8~4.9, △=13~462 km) from seven stations of the Fujian Seismic Network from March 1999 to March 2007. Using real-time simulation, we obtain the corresponding acceleration and then adopt different models to analyze the seismic data. As a result, a new attenuation relationship between PGA and PGV of the small and moderate earthquakes on bedrock site in Fujian region is established. The Yongchun earthquake occurred recently verifies the attenuation relationship well. This paper provides a new approach for studying the ground motion attenuation relationship using velocity records.     

Earthquake shaking scenarios for the metropolitan area of Lisbon

In this study, we simulate and compare ground motion shaking in the city of Lisbon and surrounding counties (metropolitan area of Lisbon (MAL)), using two possible earthquake models: the onshore source area of Lower Tagus Valley, M5.7 and M4.7 and the offshore source area, Marques de Pombal Fault, M7.6, one of the possible source of the 1755 Lisbon earthquake. The stochastic and a new hybrid stochastic-deterministic approach (DSM) are used in order to evaluate the ground shaking and to characterize its spatial variability. Results are presented in terms of response acceleration spectra (PSA) and peak ground acceleration (PGA) with respect to bedrock and surface. Site effects are evaluated by means of equivalent stochastic non-linear one-dimensional ground responses analysis, performed for a set of stratified soil profile units properly designed to cope with the soil site conditions of MAL region. A sensitive study is carried out using different input parameters and different approaches in order to give the basic information to evaluate the range of uncertainty in seismic scenarios.     

地面运动强度参数对RC桥梁地震需求的影响

在基于性能的地震工程学(PBEE)中,建立概率地震需求模型(PSDM)时需要对桥梁结构的工程需求参数(EDP)进行概率估计。其中,强地面运动参数(IM)的选择对EDP的概率估计影响很大,因此需要正确选择IM。分别采用目前最广泛使用的结构第一模态周期弹性谱加速度(5%阻尼比)Sa(T1,5%)和峰值地面加速度PGA作为IM,选择实际地震波并进行合理的调值,对一座钢筋混凝土桥墩进行IDA分析,其计算结果表明:对于不同性质EDP的概率估计值,以PGA作为IM计算所得的结果明显偏于非保守,且离散度一般也更大。说明可以针对不同性质的EDP,根据地面运动强度的大小,选择不同的IM,通过合理的调值对EDP进行概率估计,可以更加精确、高效地建立PSDM。     

Assessing traffic noise impact based on probabilistic and fuzzy approaches under uncertainty

Traffic noise can cause severe sound pollution for human communities. This paper proposes a hybrid approach to assess traffic noise impact under uncertainty. There are many factors influencing traffic noise level, but only three traffic parameters, namely, traffic flow, traffic speed and traffic component, are highly uncertain. These uncertain parameters are represented by probability distributions, and Monte Carlo simulations are performed to generate a noise distribution after considering about other certain influencing factors. Fuzzy set and binary fuzzy relations as well as probability analysis method are applied to identify the predicted traffic noise impacts in qualitatively and quantitatively. The applicability of this proposed technique is demonstrated using a case study.     

An integrated fuzzy-stochastic modeling approach for assessing health-impact risk from air pollution

High concentrations of air pollutants in the ambient environment can result in breathing problems with human communities. Effective assessment of health-impact risk from air pollution is important for supporting decisions of the related detection, prevention, and correction efforts. However, the quality of information available for environmental/health risk assessment is often not satisfactory enough to be presented as deterministic numbers. Stochastic method is one of the methods for tackling those uncertainties, by which uncertain information can be presented as probability distributions. However, if the uncertainties can not be presented as probabilities, they can then be handled through fuzzy membership functions. In this study, an integrated fuzzy-stochastic modeling (IFSM) approach is developed for assessing air pollution impacts towards asthma susceptibility. This development is based on Monte Carlo simulation for the fate of SO₂ in the ambient environment, examination of SO₂ concentrations based on the simulation results, quantification of evaluation criteria using fuzzy membership functions, and risk assessment based on the combined fuzzy-stochastic information. The IFSM entails (a) simulation for the fate of pollutants in ambient environment, with the consideration of source/medium uncertainties, (b) formulation of fuzzy air quality management criteria under uncertain human-exposure pathways, exposure dynamics, and SPG-response variations, and (c) integrated risk assessment under complexities of the combined fuzzy/stochastic inputs of contamination level and health effect (i.e., asthma susceptibility). The developed IFSM is applied to a study of regional air quality management. Reasonable results have been generated, which are useful for evaluating health risks from air pollution. They also provide support for regional environmental management and urban planning.     

A PRELIMINARY STUDY ON THE CORRELATIVITY OF SEISMIC HAZARD BETWEEN BEIJING AREA AND XIONG'AN NEW AREA

Xiong'an New Area is established on April 1, 2017 and some non-capital functions from Beijing would be transferred to this new area. As a political, economic, and cultural center of China, Beijing has a highly dense population, buildings, and transportation. With the rapid development of the urban economy, the population and assets exposed to dangerous areas with M ≥ 7 earthquakes have accumulated in an exponential manner, leading to a continuous surge in seismic risk in Beijing. Studying on the correlativity of seismic hazard between Beijing area and Xiong'an New Area is of great significance to judge whether Xiong'an can play a role in the dispersal of seismic risk of Beijing. Using Monte Carlo method to simulate synthetic earthquake sequences, and for each simulated earthquake, the peak ground acceleration data sets on each site of Beijing and Xiong'an can be calculated through the attenuation relationship. Based on the statistical analysis of the ground motion peak acceleration data sets, this paper holds that the correlativity of the ground motion between Beijing area and Xiong'an New Area is not high; the probability of Beijing and Xiong'an suffering at the same time from an exceeded fortification level of ground motion effect is very low; the probability of Beijing and Xiong'an suffering at the same time from a rare ground motion effect is extremely low. Through defibering population, assets, and setting up a remote backup of earthquake emergency equipment and supplies, Xiong'an New Area can disperse the high seismic risk of Beijing to some extent.