scholarly journals Introducing ecological uncertainty in risk sensitivity indices: the case of wind farm impact on birds

2020 ◽  
Vol 30 (30) ◽  
pp. 11-16
Author(s):  
Corrado Battisti ◽  
Vincenzo Ferri ◽  
Luca Luiselli ◽  
Giovanni Amori
Keyword(s):  
Risk Assessment ◽  
Wind Farm ◽  
Risk Index ◽  
Central Italy ◽  
Risk Sensitivity ◽  
Flight Altitude ◽  
Falco Tinnunculus ◽  
Assessment Index ◽  
Gyps Fulvus ◽  
Ecological Uncertainty

In wind-farm impact assessments, it is useful to know the level of uncertainty that characterizes some key variables used to assess the sensitivity to risk in species of conservation concern. Here, we have introduced the use of the Shannon entropy as a value of ecological uncertainty of the prediction of the risk assessment index, obtained from two ecological traits (flight altitude and flight type). We based our evaluation of risk sensitivity on sampling of three common raptor birds (Gyps fulvus, Falco tinnunculus, Buteo buteo) all co-occurring in a wind farm landscape (central Italy). As to flight altitude, Gyps fulvus prefers the flight altitude category > 300 m, Falco tinnunculus categories closer to the ground, Buteo does not show clear preference for a particular flight altitude category. As regards the flight type, Gyps fulvus showed significant preference for circular and thermal flight patterns, Falco tinnunculus for rapid horizontal/vertical flight patterns, while Buteo was found to prefer constant directions and circular and thermal flight patterns. Multiplication of the scores associated with these eco-behavioural traits by the number of recorded occurrences allowed estimation of risk sensitivity used to compute the risk assessment index. We normalized the partial scores of the risk associated with these traits with H' values, thus obtaining more reliable species-specific normalized risk indices. The greater the entropy, the greater the level of uncertainty associated with it, and the lower the reliability of the risk index. Therefore, the entropy associated with flight behaviour diversity (altitude or type) could be a proxy for assessing uncertainty in wind power impact assessment. We think that normalizing indices of risk by including a measure of uncertainty can support decision makers in bird conservation and wind farm management.

scholarly journals A study on risk assessment of complex disasters in Busan coast

2021 ◽  
Vol 8 (4) ◽  
pp. 255-265
Author(s):  
Soonmi Hwang ◽  
Hyung-Min Oh ◽  
Soo-Yong Nam ◽  
Tae-Soon Kang
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
Storm Surge ◽  
Disaster Preparedness ◽  
Risk Index ◽  
Maximum Flow ◽  
Assessment Index ◽  
Inundation Depth ◽  
Complex Disasters ◽  
Four Levels

In the vicinity of the coast, there is a risk of complex disasters in which inland flooding, wave overtopping, storm surge, and tsunami occur simultaneously. In order to prepare for such complex disasters, it is necessary to set priorities for disaster preparedness through risk assessment and establish countermeasures. In this study, risk assessment is carried out targeting on Marine city, Centum city, and Millak waterside parks in Busan, where complex disasters have occurred or are likely to occur. For risk assessment, inundation prediction map constructed by the Ministry of Public Administration and Security in consideration of sea level rise, rainfall and storm surge scenarios and authorized data on social and economic risk factors were collected. The socioeconomic risk factors selected are population, basements, buildings, sidewalks, and roads, and the risk criteria for damage targets are set for each risk factors. And it was assessed considering the maximum inundation depth and maximum flow velocity of the inundation prediction map. Weights for each factor were derived through expert questionnaires. The risk assessment index that was finally evaluated by calculating the risk index for each element and applying weights was expressed as a risk map by different colors into four levels of attention, caution, alert and danger.

Gray relational analysis based assessment of escalator accident risk in subway station

2021 ◽  
pp. 1-10
Author(s):  
Zhiru Wang ◽  
Min Wang ◽  
Ruyu He ◽  
Ran S. Bhamra ◽  
Lili Yang
Keyword(s):  
Risk Assessment ◽  
Risk Index ◽  
Good Condition ◽  
Gray Relational Analysis ◽  
Subway Station ◽  
Risk Level ◽  
Accident Risk ◽  
Analysis Model ◽  
Assessment Index ◽  
Relational Analysis

In order to better achieve active defense in the escalator risk management, this study based on the vulnerability theory, task driven theory, management error theory, proposed a Gray Relational Analysis (GRA) based fuzzy assessment of escalator accident risk approach. The risk assessment index system of subway station escalator accident was constructed based on the commonness and essence of management defects; the weight of risk index was calculated scientifically and reasonably by using Analytic Hierarchy Process (AHP); escalator accident risk was evaluated by the combination of GRA and Fuzzy approach. The results show that escalator equipment, environment, safety knowledge of riders are all in good condition in the station. However, ‘Maintenance’ of escalator in the Beijing subway station is in an extremely high risk level. The contributions of this studies are: (1) general risk elements analysis model for escalator accidents which enable to compose any risk factor possible to induce escalator accident in subway station; (2) GRA based risk assessment approach can avoid the problem when expend the range to left and right. It can also judge whether the continuous improvement effect of the object is significant by the difference degree of each risk level before and after.

Transient Operation Risk Assessment of Power System with Wind Farm Integration Based on Dynamic Security Region

2015 ◽  
Vol 1092-1093 ◽  
pp. 122-126 ◽  
Author(s):  
Wen Feng Zhu ◽  
Yuan Zeng ◽  
Chao Qin ◽  
Xiao Fei Li ◽  
De Wei Liu
Keyword(s):  
Risk Assessment ◽  
Power System ◽  
Wind Power ◽  
Wind Farm ◽  
Risk Index ◽  
System Structure ◽  
Integrated Analysis ◽  
Dynamic Security ◽  
Security Region ◽  
Dynamic Security Region

With continuous expansion of the grid, the power system structure is becoming more complicated, leading to more and more uncertainty of the system. Especially, the massive integration of wind power and other renewable energy to the grid brings more challenges. In this paper, by taking use of DSR (dynamic security region) and risk assessment theory, it proposed the transient risk index calculation and integrated analysis method for wind power integration system, which was able to give quantitative indicators of the system day-ahead scheduling plan. The efficiency and practicality of theories mentioned herein were verified by standard numerical examples.

scholarly journals A novel methodology for epidemic risk assessment of COVID-19 outbreak

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
A. Pluchino ◽  
A. E. Biondo ◽  
N. Giuffrida ◽  
G. Inturri ◽  
V. Latora ◽  
...  
Keyword(s):  
Human Mobility ◽  
Risk Index ◽  
A Priori ◽  
Geographical Area ◽  
Central Italy ◽  
Policy Model ◽  
Italian Regions ◽  
Northern Regions ◽  
Seasonal Flu ◽  
Epidemic Risk

AbstractWe propose a novel data-driven framework for assessing the a-priori epidemic risk of a geographical area and for identifying high-risk areas within a country. Our risk index is evaluated as a function of three different components: the hazard of the disease, the exposure of the area and the vulnerability of its inhabitants. As an application, we discuss the case of COVID-19 outbreak in Italy. We characterize each of the twenty Italian regions by using available historical data on air pollution, human mobility, winter temperature, housing concentration, health care density, population size and age. We find that the epidemic risk is higher in some of the Northern regions with respect to Central and Southern Italy. The corresponding risk index shows correlations with the available official data on the number of infected individuals, patients in intensive care and deceased patients, and can help explaining why regions such as Lombardia, Emilia-Romagna, Piemonte and Veneto have suffered much more than the rest of the country. Although the COVID-19 outbreak started in both North (Lombardia) and Central Italy (Lazio) almost at the same time, when the first cases were officially certified at the beginning of 2020, the disease has spread faster and with heavier consequences in regions with higher epidemic risk. Our framework can be extended and tested on other epidemic data, such as those on seasonal flu, and applied to other countries. We also present a policy model connected with our methodology, which might help policy-makers to take informed decisions.

scholarly journals A Multivariate High-Order Markov Model for the Income Estimation of a Wind Farm

Energies ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 388
Author(s):  
Riccardo De Blasis ◽  
Giovanni Batista Masala ◽  
Filippo Petroni
Keyword(s):  
Markov Model ◽  
Electricity Market ◽  
Wind Farm ◽  
Central Italy ◽  
High Order ◽  
Distribution Model ◽  
Spot Price ◽  
Model Parameters ◽  
Price Series ◽  
Cross Correlations

The energy produced by a wind farm in a given location and its associated income depends both on the wind characteristics in that location—i.e., speed and direction—and the dynamics of the electricity spot price. Because of the evidence of cross-correlations between wind speed, direction and price series and their lagged series, we aim to assess the income of a hypothetical wind farm located in central Italy when all interactions are considered. To model these cross and auto-correlations efficiently, we apply a high-order multivariate Markov model which includes dependencies from each time series and from a certain level of past values. Besides this, we used the Raftery Mixture Transition Distribution model (MTD) to reduce the number of parameters to get a more parsimonious model. Using data from the MERRA-2 project and from the electricity market in Italy, we estimate the model parameters and validate them through a Monte Carlo simulation. The results show that the simulated income faithfully reproduces the empirical income and that the multivariate model also closely reproduces the cross-correlations between the variables. Therefore, the model can be used to predict the income generated by a wind farm.

scholarly journals The Relationship Between Elder Risk Assessment Index Score and 30-Day Readmission From the Nursing Home

2011 ◽  
Vol 39 (1) ◽  
pp. 91-96 ◽  
Author(s):  
Paul Y. Takahashi ◽  
Anupam Chandra ◽  
Stephen Cha ◽  
Aleta Borrud
Keyword(s):  
Risk Assessment ◽  
Nursing Home ◽  
Index Score ◽  
Assessment Index ◽  
The Relationship

scholarly journals Environmental Risk Assessment of Petroleum Activities in Surface Sediments, Suez Gulf, Egypt

2021 ◽  
Vol 9 (5) ◽  
pp. 473
Author(s):  
Magda M. Abou El-Safa ◽  
Mohamed Gad ◽  
Ebrahem M. Eid ◽  
Ashwaq M. Alnemari ◽  
Mohammed H. Almarshadi ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Risk Assessment ◽  
Heavy Metal ◽  
Surface Sediment ◽  
Surface Sediments ◽  
Surf Zone ◽  
Risk Index ◽  
Negative Relationship ◽  
Anthropogenic Sources ◽  
Suez Gulf

The present study focuses on the risk assessment of heavy metal contamination in aquatic ecosystems by evaluating the current situation of heavy metals in seven locations (North Amer El Bahry, Amer, Bakr, Ras Gharib, July Water Floud, Ras Shokeir, and El Marageen) along the Suez Gulf coast that are well-known representative sites for petroleum activities in Egypt. One hundred and forty-six samples of surface sediments were carefully collected from twenty-seven profiles in the intertidal and surf zone. The hydrochemical parameters, such as pH and salinity (S‰), were measured during sample collection. The mineralogy study was carried out by an X-ray diffractometer (XRD), and the concentrations of Al, Mn, Fe, Cr, Cu, Co, Zn, Cd, and Pb were determined using inductively coupled plasma mass spectra (ICP-MS). The ecological risks of heavy metals were assessed by applying the contamination factor (CF), enrichment factor (EF), geoaccumulation index (Igeo), pollution load index (PLI), and potential ecological risk index (RI). The mineralogical composition mainly comprised quartz, dolomites, calcite, and feldspars. The average concentrations of the detected heavy metals, in descending order, were Al > Fe > Mn > Cr > Pb > Cu > Zn > Ni > Co > Cd. A non-significant or negative relationship between the heavy metal concentration in the samples and their textural grain size characteristics was observed. The coastal surface sediment samples of the Suez Gulf contained lower concentrations of heavy metals than those published for other regions in the world with petroleum activities, except for Al, Mn, and Cr. The results for the CF, EF, and Igeo showed that Cd and Pb have severe enrichment in surface sediment and are derived from anthropogenic sources, while Al, Mn, Fe, Cr, Co, Ni, Cu, and Zn originate from natural sources. By comparison, the PLI and RI results indicate that the North Amer El Bahry and July Water Floud are considered polluted areas due to their petroleum activities. The continuous monitoring and assessment of pollutants in the Suez Gulf will aid in the protection of the environment and the sustainability of resources.

scholarly journals Reforestation Impacted Soil Heavy Metal Fractionation and Related Risk Assessment in the Karst Area, Southwest China

Forests ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 891
Author(s):  
Qian Zhang ◽  
Guilin Han ◽  
Xingliang Xu
Keyword(s):  
Heavy Metals ◽  
Risk Assessment ◽  
Ecological Risk ◽  
Southwest China ◽  
Risk Index ◽  
Contamination Factor ◽  
Karst Area ◽  
Risk Assessment Code ◽  
Bcr Sequential Extraction ◽  
Soil Heavy Metals

Human agricultural activities have resulted in widespread land degradation and soil contamination in the karst areas. However, the effects of reforestation after agricultural abandonment on the mobility risks and contamination of heavy metals have been rarely reported. In the present study, six soil profiles were selected from cropland and abandoned cropland with reforestation in the Puding karst regions of Southwest China. The Community Bureau of Reference (BCR) sequential extraction method was used to evaluate the compositions of different chemical fractions of soil heavy metals, including Fe, Mn, Cr, Zn, Ni, and Cd. The total contents of Cr, Ni, Zn, Cd, and Mn in the croplands were significantly higher than those in the abandoned croplands. For all soils, Cr, Ni, Zn, and Fe were mainly concentrated in the residual fractions (>85%), whereas Mn and Cd were mostly observed in the non-residual fractions (>65%). The non-residual fractions of Cd, Cr, Ni, and Zn in the croplands were higher than those in the abandoned croplands. These results indicated that the content and mobility of soil heavy metals decreased after reforestation. The individual contamination factor (ICF) and risk assessment code (RAC) showed that Cd contributed to considerable contamination of karst soils. The global contamination factor (GCF) and potential ecological risk index (RI) suggested low contamination and ecological risk of the investigated heavy metals in the croplands, moreover they can be further reduced after reforestation.

scholarly journals Health Risk Assessment Indicators for the Left-Behind Elderly in Rural China: A Delphi Study

2020 ◽  
Vol 17 (1) ◽  
pp. 340 ◽  
Author(s):  
Ruzhen Luo ◽  
Chunmei Zhang ◽  
Yanhui Liu
Keyword(s):  
Risk Assessment ◽  
Health Risk ◽  
Health Risk Assessment ◽  
Delphi Study ◽  
Index System ◽  
Urban Areas ◽  
Health Management ◽  
Assessment Index ◽  
Left Behind ◽  
Assessment Index System

In China, many young and middle-aged rural residents move to urban areas each year. The rural elderly are left behind. The number of the rural left-behind elderly is increasing with urbanization, but it is unclear which indicators can be used to assess their health condition. The health risk assessment index system was developed to improve the health level of the rural left-behind elderly. A two-round web-based Delphi process was used to organize the recommendations from fifteen Chinese experts in geriatrics, health management, social psychology who participated in this study. Meaningfulness, importance, modifiability, and comprehensive value of the health risk assessment indicators in the index system were evaluated. The effective recovery rates of the two-round Delphi were 86.67% and 92.31%, respectively. The judgement coefficient and the authority coefficient were 0.87 and 0.82, respectively. The expert familiarity was 0.76. Ultimately, the health risk assessment index system for the rural left-behind elderly consisted of five first-level indicators, thirteen second-level indicators, and sixty-six third-level indicators. The final indicators can be used to evaluate the health of the rural left-behind elderly and provide the basis for additional health risk interventions.

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