A methodological framework of landslide quantitative risk assessment in areas with incomplete historical landslide information

Landslide risk assessment(LRA)is of great significance to hazard prevention and mitigation.However,the historical landslide information is incomplete in most areas,which makes the landslide quantitative risk assessment(LQRA)extremely difficult.This research proposed a set of frameworks for LQRA,so as to achieve LQRA in areas with incomplete historical landslide information.Firstly,we constructed the convolutional neural network(CNN)model suitable for landslide susceptibility assessment(LSA)by studying the structure and hyperparameters optimization of CNN.Secondly,we proposed a method to calculate the temporal probability by using the Poisson model based on the time range of historical landslides occurrence,and then conducted landslide hazard assessment(LHA).Then,we established a mathematical model for landslide intensity of shallow landslide based on landslide area and slope,aiming at solving the problem that it is difficult to calculate landslide intensity due to the lack of landslide volume and velocity.Based on the landslide intensity and the hazard-resistant capacity of the element at risk,we assessed the landslide vulnerability.Finally,population risk map and economic risk map are obtained based on the landslide hazard,vulnerability,and estimated value of the elements at risk.The proposed LQRA framework was applied to Tumen City,China for testing and field validation.From the results,the CNN model built can help improve the accuracy of LSA.The proposed temporal probability calculation method is conducive to the completion of LHA in areas with incomplete historical landslide information.The established landslide intensity mathematical model has certain credibility.Since the landslide risk map is obtained through appropriate simplification and substitution estimation,its final value cannot be used as an accurate prediction of future losses,but it can be used as a reference for the extent of potential losses,so as to determine the areas where hazard prevention and mitigation measures need to be taken.

Study on Quantitative Assessment for the Social Risk of Major Geological Disasters

Based on the analysis of social risk of geological disasters,the index system of social risk evaluation was established. To assess the social risk quantitatively,a quantitative evaluation model of the social risk was established based on AHP,and the social risk of geological disasters was graded. Finally,the evaluation model was applied in a case.

Quantitative risk assessment & leak detection criteria for a subsea oil export pipeline

A quantitative risk assessment （QRA） based on leak detection criteria （LDC） for the design of a proposed subsea oil export pipeline is presented in this paper. The objective of this QRA/LDC study was to determine if current leak detection methodologies were sufficient, based on QRA results, while excluding the use of statistical leak detection; if not, an appropriate LDC for the leak detection system would need to be established. The famous UK PARLOC database was used for the calculation of pipeline failure rates, and the software POSVCM from MMS was used for oil spill simulations. QRA results revealed that the installation of a statistically based leak detection system （LDS） can significantly reduce time to leak detection, thereby mitigating the consequences of leakage. A sound LDC has been defined based on QRA study results and comments from various LDS vendors to assist the emergency response team （ERT） to quickly identify and locate leakage and employ the most effective measures to contain damage.

Quantitative Risk Assessment with Data Mining for Formaldehyde Content of Imported Textile

The assessment of potential risks posed by formaldehyde in clothing to consumers is of increasing concern worldwide,for free formaldehyde is harmful to human. Some papers focus on hazard and exposure assessment,using quantitative and semi-quantitative method, rather than assessment for the factors related to formaldehyde content. In order to perform early-warning research and risk management,the quantitative risk assessment is used to analyze the imported textile testing data and find the factors related to formaldehyde content. K-means algorithm is the core of the method. It can be concluded that the disqualified textiles have relations with main fiber components,fabric color,season month,and brand. Then the data in the same attribute are clustered by Kmeans algorithm. The different classes are defined as related danger level,respectively severe,moderate,and light.

Risk of Waterborne Parasitic Infection among Vegetables Producers in the City of Ouagadougou, Burkina Faso: An Attempt to Quantify Them Using the Quantitative Microbiological Risk Assessment Method

The use of wastewater in urban agriculture has been promoted as an alternative to water scarcity and as a means to increase soil fertilizer. However, the use of wastewater in urban agriculture raises major public health concerns, mainly due to the often high concentration of pathogenic micro-organisms. Waterborne parasites are a major health concern in this regard, especially in endemic areas, mainly due to the high environmental resistance of eggs/cysts combined with a low infectious dose. In this study, the parasitological risk to vegetables producers in Ouagadougou using polluted water was evaluated through the quantitative microbiological risk analysis method. For this purpose, the search for and quantification of viable parasite eggs and cysts in irrigation water was coupled with epidemiological surveillance of vegetables producers in Ouagadougou. Protozoa and helminths belonging to 9 species were recorded and samples analyzed. These include Ancylostoma sp., Ascaris lumbricoides, tapeworm’s sp, Strongyloides stercoralis, Entamoeba histolytica, Giardia lamblia. Despite the variability of isolated parasitic species, Ancylostoma sp. eggs were common and severe to all types of water. Moreover, epidemiological approach showed that there were more parasitic species found in irrigation water and also other parasitic species circulating among vegetable farmers. In addition, there is no statistical significant association between the type of water used for irrigation and the carried parasites by vegetable gardeners. However, contamination of the groups using the raw wastewater is once higher than those using well water. When one is interested in the groups using treated wastewater as a source of irrigation, these risks of contaminations are halved. These contaminations are halved when one looks at groups using treated wastewater as a source of irrigation water. Still, whatever the type of water used by the gardeners, they have a probability of infection with Ancylostoma sp. of around 9.83 × 10−1 pppy.

Cosmetic Safety and Risk Assessment Under the “New” Regulations

Regulations for the Supervision and Administration of Cosmetics was promulgated by the State Council on June 29,2020 and will take effect on January 1,2021.Compared with the previous Regulations on Health Supervision of Cosmetics,there are more items proposed for the safety of cosmetics.In this paper,the main changes of the safety supervision of cosmetics by comparing the“new”and“old”regulations were summarized with the potential influences on different groups(government,cosmetic enterprises and consumers)discussed.The important laws and regulations on cosmetic safety and risk assessment in China with recently added in vitro testing methods were summarized and the principal theory of cosmetic quantitative risk assessment was introduced.

Evaluation of bacterial pathogen diversity,abundance and health risks in urban recreational water by amplicon next-generation sequencing and quantitative PCR

The microbial quality of urban recreational water is of great concern to public health.The monitoring of indicator organisms and several pathogens alone is not sufficient to accurately and comprehensively identify microbial risks.To assess the levels of bacterial pathogens and health risks in urban recreational water,we analyzed pathogen diversity and quantified four pathogens in 46 water samples collected from waterbodies in Beijing Olympic Forest Park in one year.The pathogen diversity revealed by 16 S r RNA gene targeted next-generation sequencing（NGS） showed that 16 of 40 genera and 13 of 76 reference species were present.The most abundant species were Acinetobacter johnsonii,Mycobacterium avium and Aeromonas spp.Quantitative polymerase chain reaction（q PCR） of Escherichia coli（uid A）,Aeromonas（aer A）,M.avium（16S r RNA）,Pseudomonas aeruginosa（oaa） and Salmonella（inv A） showed that the aer A genes were the most abundant,occurring in all samples with concentrations of 10^（4–6） genome copies/100 m L,followed by oaa,inv A and M.avium.In total,34.8% of the samples harbored all genes,indicating the prevalence of these pathogens in this recreational waterbody.Based on the q PCR results,a quantitative microbial risk assessment（QMRA） showed that the annual infection risks of Salmonella,M.avium and P.aeruginosa in five activities were mostly greater than the U.S.EPA risk limit for recreational contacts,and children playing with water may be exposed to the greatest infection risk.Our findings provide a comprehensive understanding of bacterial pathogen diversity and pathogen abundance in urban recreational water by applying both NGS and q PCR.

Atmospheric dispersion of chemical,biological,and radiological hazardous pollutants:Informing risk assessment for public safety

Modern society is confronted with emerging threats from chemical,biological,and radiological(CBR)hazardous substances,which are intensively utilized in the chemical,medical,and energy industries.The atmospheric dis-persion of released CBR hazardous pollutants can influence a large percentage of the population owing to their rapid process with extensive spatial coverage.It is important to comprehensively understand the behaviors of the released CBR pollutants in the atmosphere to fully evaluate the risks and protect public safety.In this study,we reviewed the advancements in the atmospheric transport of CBR pollutants,including the urban atmospheric boundary layer,unique concepts,and models for CBR pollutants.We underlined the development of innovative methodologies(e.g.,inverse estimation and data assimilation methods)for the atmospheric transport of acciden-tally released CBR pollutants to reduce uncertainties in emissions and accumulated errors during dispersion by combining numerical models with monitoring data.Finally,we introduced progress in quantitative risk assess-ment,including exposure assessment and dose-response relationships for CBR hazardous pollutants.A framework,source,assimilation,fundamentals,exposure,and risk(SAFER),has been proposed to integrate the key compo-nents in the risk assessment of airborne CBR hazardous pollutants.These methods and models can contribute to effective risk preparedness,prevention,evidence-based policymaking,and emergency response to airborne CBR pollutants.

Probabilistic modeling for an integrated temporary acquired immunity with norovirus epidemiological data

Integration of acquired immunity into microbial risk assessment for illness incidence is of no doubt essential for the study of susceptibility to illness.In this study,a probabilistic model was set up as dose response for infection and a mathematical derivation was carried out by integrating immunity to obtain probability of illness models.Temporary acquire immunity from epidemiology studies which includes six different Norovirus transmission scenarios such as symptomatic individuals infectious,pre-and post-symptomatic infectiousness(low and high),innate genetic resistance,genogroup 2 type 4 and those with no immune boosting by asymptomatic infection were evaluated.Simulated results on illness inflation factor as a function of dose and exposure indicated that high frequency exposures had immense immunity build up even at high dose levels;hence minimized the probability of illness.Using Norovirus transmission dynamics data,results showed,and immunity included models had a reduction of 2e6 logs of magnitude difference in disease burden for both population and individual probable illness incidence.Additionally,the magnitude order of illness for each dose response remained largely the same for all transmission scenarios;symptomatic infectiousness and no immune boosting after asymptomatic infectiousness also remained the same throughout.With integration of epidemiological data on acquired immunity into the risk assessment,more realistic results were achieved signifying an overestimation of probable risk of illness when epidemiological immunity data are not included.This finding supported the call for rigorous integration of temporary acquired immunity in dose-response in all microbial risk assessments.