A new prediction method of industrial atmospheric pollutant emission intensity based on pollutant emission standard quantification

● Established a quantification method of pollutant emission standard. ● Predicted the SO₂ emission intensity of single coking enterprises in China. ● Evaluated the influence of pollutant discharge standard on prediction accuracy. ● Analyzed the SO₂ emissions of Chinese provincial and municipal coking enterprises. Industrial emissions are the main source of atmospheric pollutants in China. Accurate and reasonable prediction of the emission of atmospheric pollutants from single enterprise can determine the exact source of atmospheric pollutants and control atmospheric pollution precisely. Based on China’s coking enterprises in 2020, we proposed a quantitative method for pollutant emission standards and introduced the quantification results of pollutant emission standards (QRPES) into the construction of support vector regression (SVR) and random forest regression (RFR) prediction methods for SO₂ emission of coking enterprises in China. The results show that, affected by the types of coke ovens and regions, China’s current coking enterprises have implemented a total of 21 emission standards, with marked differences. After adding QRPES, it was found that the root mean squared error (RMSE) of SVR and RFR decreased from 0.055 kt/a and 0.059 kt/a to 0.045 kt/a and 0.039 kt/a, and theR² increased from 0.890 and 0.881 to 0.926 and 0.945, respectively. This shows that the QRPES can greatly improve the prediction accuracy, and the SO₂ emissions of each enterprise are highly correlated with the strictness of standards. The predicted result shows that 45% of SO₂ emissions from Chinese coking enterprises are concentrated in Shanxi, Shaanxi and Hebei provinces in central China. The method created in this paper fills in the blank of forecasting method of air pollutant emission intensity of single enterprise and is of great help to the accurate control of air pollutants.     

古夫河着生藻类优势种体积与水质因子的相关性研究

通过研究长江三峡库区古夫河着生藻类优势种体积的变化,探索影响其体积的主要水质因子,为河流水质评价提供依据.于2010年12月至2012年2月,对古夫河着生藻类和地表水采样11次,共鉴定着生藻类197种,检测水质指标10项.选取Mcnaughton优势度指数(Y)>0.02的着生藻类(共30种)作为优势种并计算体积;利用主成分分析(PCA)分析优势种藻类在不同月份的体积变化.结果显示,硅藻门对冷暖季的变化较为敏感.将水质因子与优势种藻类体积进行典范对应分析(CCA),结果显示水质因子与藻类体积相关性大小为:溶解氧>氨氮>叶绿素a>酸碱度>硝态氮>总磷>水温>总氮>总有机碳>化学需氧量.Monte Carlo显著性检验结果为溶解氧和氨氮对着生藻类体积的影响最大,其次为叶绿素a、酸碱度和硝态氮.硅藻门藻类体积的变化可以判断古夫河水体中溶解氧、氨氮、叶绿素a、酸碱度、硝态氮的含量与变化.     

Uncertainties in a risk management context in early phases of offshore petroleum field development

The current risk management approach for the Norwegian offshore petroleum industry came into effect in 2001 and has been stable with minor changes for 15 years. Relatively few new installations were slated for development until quite recently, and several new projects have been started in the last few years. The paper considers the risk management approach in the pre-FEED phase and builds on two case studies selected from the most recent cases. These case studies have been evaluated with respect to how uncertainties are considered in the early phase, based on the submission of the Plan for Development and Operation, their evaluations by authorities and the supporting documents. Both case studies involve new concepts for which there is no experience from similar environments and/or water depths. In spite of what could have been expected, the case studies conclude that uncertainties have not been in focus at all during concept development. This appears to be definitely the case for the licensees, but also to be the case for the authorities. Some suggestions are presented for what could have been considered by the licensees and authorities.     

Optimizing the design of storage facilities through the application of ISD and QRA

Four strategies can be used to achieve safety in chemical processes: inherent, passive, active and procedural. However, the strategy that offers the best results is the inherent safety approach, especially if it is applied during the initial stages of a project. Inherently Safer Design (ISD) permanently eliminates or reduces hazards, and thus avoids or diminishes the consequences of incidents. ISD can be applied using four strategies: substitution, minimization, moderation and simplification. In this paper, we propose a methodology that combines ISD strategies with Quantitative Risk Assessment (QRA) to optimize the design of storage installations. As 17% of major accidents in the chemical industry occur during the storage process and cause significant losses, it is essential to improve safety in such installations. The proposed method applies QRA to estimate the risk associated with a specific design. The design can then be compared to others to determine which is inherently safer. The risk analysis may incorporate complex phenomena such as the domino effect and possible impacts on vulnerable material and human elements. The methodology was applied to the San Juanico tragedy that occurred in Mexico in 1984.     

Quantitative Pollution Spill Risk Assessment: Using A Gis-Based System

Federal and State agencies have recently advocated risk-based analysis as a mechanism for advancing regulatory reform and safety determination in marine systems. the present investigation promotes this objective through the development of risk-based environmental planning strategies for oil spill contingency plans. This alternative approach to contingency planning departs from conventional methodology by employing quantitative risk assessment methods to identify hazardous oil spill zones and sensitive environmental areas, R_o and R_e respectively. the product of this conversion is referenced on a single “Risk” layer within a Geographic Information System (GIS) framework allowing coastal managers to evaluate natural resource data with associated elements of oil spill risk. As a new tool for coastal pollution management, risk-based environmental planning strategies have shown potential for evolving more efficient oil spill contingency plans.     

Physiochemical properties influencing biomass abundance and primary production in Lake Hoare, Antarctica

The perennially ice-covered, closed basin lakes in the McMurdo Dry Valleys respond rapidly to environmental changes, especially climate. For the past 15 years, the McMurdo Dry Valleys Long-Term Ecological Research (MCM-LTER) program has monitored the physical, chemical and biological properties of the lakes in Taylor Valley. In order to better assess the physiochemical controls on the biological process within one of these lakes (Lake Hoare), we have used vertical profile data to estimate depth-dependent correlations between various lake properties. Our analyses reveal the following results. Primary production rates (PPR) are strongly correlated to light (PAR) at 12-15 m and to soluble reactive phosphorus (SRP) at 8-22 m. Chlorophyll-a (CHL) is also positively correlated to PAR at 14 m and greater depths, and SRP from 15 m and greater. This preliminary statistical analysis supports previous observations that both PAR and SRP play significant roles in driving plant growth in Lake Hoare. The lack of a strong relationship between bacterial production (BP) and dissolved organic carbon (DOC) is an intriguing result of the analysis.     

An optimal level of dust explosion risk management: Framework and application

The current research provides guidance on the prevention and mitigation of dust explosion using a Quantitative Risk Management Framework (QRMF). Using concepts drawn from previous studies, the framework consists of three main steps: (i) a new combined safety management protocol, (ii) the use of DESC (Dust Explosion Simulation Code) and FTA (Fault Tree Analysis) to assess explosion consequences and likelihood, respectively, and (iii) application of the hierarchy of controls (inherent, engineered and procedural safety). QRMF assessment of an industrial case study showed that the original process was at high risk. DESC simulations and Probit equations determined the destructive percentages. FTAs revealed high probabilities of explosion occurrence; in addition, detailed individual and societal risks calculations were made, before and after the framework was applied. Based on the hierarchy of controls technique, the framework showed significant risk reduction to the point where the residual risk was acceptable for the process.     

Quantitative risk analysis of urban natural gas pipeline networks using geographical information systems

This paper presents a novel quantitative risk analysis process for urban natural gas pipeline networks using geographical information systems (GIS). The process incorporates an assessment of failure rates of integrated pipeline networks, a quantitative analysis model of accident consequences, and assessments of individual and societal risks. Firstly, the failure rates of the pipeline network are calculated using empirical formulas influenced by parameters such as external interference, corrosion, construction defects, and ground movements. Secondly, the impacts of accidents due to gas leakage, diffusion, fires, and explosions are analyzed by calculating the area influenced by poisoning, burns, and deaths. Lastly, based on the previous analyses, individual risks and social risks are calculated. The application of GIS technology helps strengthen the quantitative risk analysis (QRA) model and allows construction of a QRA system for urban gas pipeline networks that can aid pipeline management staff in demarcating high risk areas requiring more frequent inspections.