Chemical composition of waters and the phytoplankton of the lakes within the delta of the Selenga river

Field observations showed that the characteristics of chemical composition of waters and the development of plankton algae in the lakes within the delta of the Selenga river are determined by their flowage. The most open Lake Nekipelovskoe communicates with the Selenga outlets throughout a year, and Lake Zavernyaikha only at the period of an open channel. Lake Semenovskoe and Lake Khlystov Zaton are located in the islands and are isolated from the outlets. According to composition of main ions, the lakes under investigation refer to the hydrocarbonate class, the calcium group. The sum of ions in the water of Lake Nekipelovskoe approaches the one in the Selenga (86?221 mg/dm³), and the highest sums of ions were recorded in the wintertime in the lakes isolated from the outlets (446?743 mg/dm³). The lakes of the delta are characterized by a high trophicity. The maximum concentrations of total phosphorus in Lake Nekipelovskoe and Lake Zavernyaikha were 68 and 122 μg mg/dm³, and in Lake Semenovskoe and Lake Khlystov Zaton ?0.8 and ?0.63 μg mg/dm³, respectively. The most intense development of algae is observed in Lake Zavernyaikha, which is due to the high population of Baikal endemics. Lake Zavernyaikha showed a close negative correlation between the concentration of NO ₃ ^? , mineral phosphorus and phytoplankton biomass; the correlation coefficient was ?0.8 and ?0.63, respectively. The lakes exhibited increased contents readily hydrolysable organic matter, and a decrease in dissolved oxygen concentration in winter; hydrogen sulfide was repeatedly recorded in Lake Khlystov Zaton. The water quality in the lakes during the springtime varies from “quite clean” to “weakly polluted”; at low-water periods, especially in winters, it can drop to the category of “exceedingly dirty”. The water quality of the Selenga can be influenced by the lakes during spring floods when material accumulated during the wintertime is transported to the river outlets and further to Lake Baikal.     

Probability of serviceability failure in a braced excavation in a spatially random field: Fuzzy finite element approach

A simplified framework is proposed for evaluating the probability of “serviceability failure” in a braced excavation in a spatially random field. Here, the “serviceability failure” is said to occur when the excavation-induced wall or ground movement exceeds specified limiting values. Knowledge of this probability can aid in engineering decision-making to prevent damage to adjacent infrastructures. The proposed framework consists of five elements: (1) finite element method (FEM) for analyzing wall and ground responses in a braced excavation, (2) fuzzy set modeling of parameter uncertainty, (3) spatial averaging technique for handling spatial variability, (4) vertex method for processing fuzzy input through FEM model, and (5) interpretation of fuzzy output. The proposed framework is demonstrated through a well-documented case history. The results show the proposed framework is simple and effective for assessing the probability of serviceability failure in a braced excavation in a spatially random field. To focus on the proposed fuzzy FEM approach, the scope of this paper is limited to one-dimensional modeling of spatial variability with an assumed exponential autocorrelation function.     

Multi-peril risk assessment for business downtime of industrial facilities

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.