How Tree Risk Assessment Methods Work: Sensitivity Analyses of Sixteen Methods Reveal the Value of Quantification and the Impact of Inputs on Risk Ratings

2020 ◽  
Vol 46 (6) ◽  
pp. 402-431
Author(s):  
M.B. Norris ◽  
G.M. Moore
Keyword(s):  
Risk Assessment ◽  
Sensitivity Analysis ◽  
Latin Hypercube Sampling ◽  
Assessment Methods ◽  
Sensitivity Analyses ◽  
Risk Level ◽  
Input Variables ◽  
Group 2 ◽  
The Impact ◽  
Risk Scale

Sixteen tree risk assessment methods were subjected to sensitivity analysis to determine which factors most influenced the output of each method. The analyses indicate the relative influence that the input variables exert on the final risk value. Excel was used to create a simple ± 25% or ± 1 rank change (depending on the method) for each criterion, with the change to the output recorded as a percentage. Palisade’s @Risk software was used to undertake a Monte Carlo (with Latin Hypercube sampling) simulation of 5000 iterations based on the input variables and output formula. From the simulation, multivariate stepwise regression was undertaken to determine the influence of each method’s input variables in determining the output values. Results from the sensitivity analysis indicate some clear and strong differences amongst the 16 methods, reflecting that the underlying mathematics, input categories, ranges, and scaling influence the way that different methods process and express risk. It is not surprising that methods perform differently in different circumstances and express risk level differently. The analyses demonstrated that most methods placed too great an emphasis on limited aspects of risk assessment. Most methods strongly focused on the hazard or defect aspects of assessment and the likelihood of failure rather than the consequence aspect of an assessment. While methods were uniquely different, they could be placed into 3 broad groups: Group 1 methods produced a normal distribution with most values around the mean; Group 2 methods produced outputs at the lower end of the risk scale; and Group 3 methods produced outputs evenly if not continuously across the risk scale. Users of tree risk assessment should understand the strengths and weaknesses of any method used, as it could be relatively simple to challenge the results of a risk assessment based on limitations inherent in the underlying methodology.

Applying the risk principle to optimize accuracy and equity in correctional risk assessment: Results From a Simulation

2021 ◽  
pp. 0306624X2098652
Author(s):  
Grant Duwe
Keyword(s):  
Risk Assessment ◽  
Predictive Accuracy ◽  
Ethnic Disparities ◽  
Simulated Data ◽  
Risk Assessments ◽  
Risk Level ◽  
Risk Levels ◽  
Risk Principle ◽  
Changes In Risk ◽  
The Impact

As the use of risk assessments for correctional populations has grown, so has concern that these instruments exacerbate existing racial and ethnic disparities. While much of the attention arising from this concern has focused on how algorithms are designed, relatively little consideration has been given to how risk assessments are used. To this end, the present study tests whether application of the risk principle would help preserve predictive accuracy while, at the same time, mitigate disparities. Using a sample of 9,529 inmates released from Minnesota prisons who had been assessed multiple times during their confinement on a fully-automated risk assessment, this study relies on both actual and simulated data to examine the impact of program assignment decisions on changes in risk level from intake to release. The findings showed that while the risk principle was used in practice to some extent, the simulated results showed that greater adherence to the risk principle would increase reductions in risk levels and minimize the disparities observed at intake. The simulated data further revealed the most favorable outcomes would be achieved by not only applying the risk principle, but also by expanding program capacity for the higher-risk inmates in order to adequately reduce their risk.

scholarly journals Quantitative Microbial Risk Assessment for Workers Exposed to Bioaerosol in Wastewater Treatment Plants Aimed at the Choice and Setup of Safety Measures

2018 ◽  
Vol 15 (7) ◽  
pp. 1490 ◽  
Author(s):  
Annalaura Carducci ◽  
Gabriele Donzelli ◽  
Lorenzo Cioni ◽  
Ileana Federigi ◽  
Roberto Lombardi ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Sensitivity Analysis ◽  
Wastewater Treatment ◽  
Health Risk ◽  
Average Risk ◽  
Quantitative Microbial Risk Assessment ◽  
Exposure Limits ◽  
Microbial Risk Assessment ◽  
Microbial Risk ◽  
The Impact

Biological risk assessment in occupational settings currently is based on either qualitative or semiquantitative analysis. In this study, a quantitative microbial risk assessment (QMRA) has been applied to estimate the human adenovirus (HAdV) health risk due to bioaerosol exposure in a wastewater treatment plant (WWTP). A stochastic QMRA model was developed considering HAdV as the index pathogen, using its concentrations in different areas and published dose–response relationship for inhalation. A sensitivity analysis was employed to examine the impact of input parameters on health risk. The QMRA estimated a higher average risk in sewage influent and biological oxidation tanks (15.64% and 12.73% for an exposure of 3 min). Sensitivity analysis indicated HAdV concentration as a predominant factor in the estimated risk. QMRA results were used to calculate the exposure limits considering four different risk levels (one illness case per 100, 1.000, 10.000, and 100.000 workers): for 3 min exposures, we obtained 565, 170, 54, and 6 GC/m3 of HAdV. We also calculated the maximum time of exposure for each level for different areas. Our findings can be useful to better define the effectiveness of control measures, which would thus reduce the virus concentration or the exposure time.

scholarly journals Pollution Characteristics of Microplastics in Soils in Southeastern Suburbs of Baoding City, China

2020 ◽  
Vol 17 (3) ◽  
pp. 845 ◽  
Author(s):  
Chuan Du ◽  
Handong Liang ◽  
Zhanping Li ◽  
Jie Gong
Keyword(s):  
Risk Assessment ◽  
Secondary Ion Mass Spectrometry ◽  
Ferrous Metal ◽  
Reference Method ◽  
Negative Ion ◽  
Risk Level ◽  
Environmental Media ◽  
Wide Range ◽  
Water Ecosystems ◽  
The Impact

Microplastics (MPs) are emerging pollutants that exist in different environmental media. Because of their wide range and large potential environmental hazards, they have attracted widespread attention in recent years. At present, the research on MP is mostly concentrated on the water ecosystems, and the impact on soil ecosystems is less studied. In this study, 12 typical soil samples from southeastern suburbs of Baoding city were investigated and characterized by time-of-flight secondary ion mass spectrometry (TOF-SIMS) combined with mass high resolution mode and positive and negative ion imaging mode. Four types of MPs, poly (propylene) (PP), poly (vinyl chloride) (PVC), poly (ethylene terephthalate) (PET), and poly (amide 6) (PA6), were quickly identified, of which PET and PA6 accounted for the largest proportion of both up to 30.2%; the particle size of the obtained MPs ranged from 0 to 35 μm, of which the proportion of <10 μm MPs was more than 26.3%, while that of 20–25 μm and 25–35 μm MPs was relatively small (17.83% and 9.3%, respectively). Risk assessment results of the MP in the soil showed that the risk level of MPs in the non-ferrous metal industrial parks and in concentrated with small workshops areas is relatively high, and attention should be paid to such areas. In addition, the study provides a reference method for the investigation and risk assessment of MPs in terrestrial soils, coastal beaches, and sediments.

scholarly journals Practical Risk Assessment of Ground Vibrations Resulting from Blasting, Using Gene Expression Programming and Monte Carlo Simulation Techniques

2020 ◽  
Vol 10 (2) ◽  
pp. 472 ◽  
Author(s):  
Amir Mahdiyar ◽  
Danial Jahed Armaghani ◽  
Mohammadreza Koopialipoor ◽  
Ahmadreza Hedayat ◽  
Arham Abdullah ◽  
...  
Keyword(s):  
Gene Expression ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Gene Expression Programming ◽  
Sensitivity Analyses ◽  
Accurate Estimation ◽  
Blasting Operation ◽  
Simulation Techniques ◽  
Input Variables ◽  
The Impact

Peak particle velocity (PPV) is a critical parameter for the evaluation of the impact of blasting operations on nearby structures and buildings. Accurate estimation of the amount of PPV resulting from a blasting operation and its comparison with the allowable ranges is an integral part of blasting design. In this study, four quarry sites in Malaysia were considered, and the PPV was simulated using gene expression programming (GEP) and Monte Carlo simulation techniques. Data from 149 blasting operations were gathered, and as a result of this study, a PPV predictive model was developed using GEP to be used in the simulation. In order to ensure that all of the combinations of input variables were considered, 10,000 iterations were performed, considering the correlations among the input variables. The simulation results demonstrate that the minimum and maximum PPV amounts were 1.13 mm/s and 34.58 mm/s, respectively. Two types of sensitivity analyses were performed to determine the sensitivity of the PPV results based on the effective variables. In addition, this study proposes a method specific to the four case studies, and presents an approach which could be readily applied to similar applications with different conditions.

scholarly journals The Impact of Suboptimal Diet on Type 2 Diabetes at Global, Regional, National, and Sub-National Levels: A Comparative Risk Assessment Analysis

2020 ◽  
Vol 4 (Supplement_2) ◽  
pp. 877-877
Author(s):  
Meghan O'Hearn ◽  
Gitanjali Singh ◽  
Frederick Cudhea ◽  
Victoria Miller ◽  
Jianyi Zhang ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Risk Assessment ◽  
Whole Grains ◽  
Dietary Factors ◽  
Sub Saharan Africa ◽  
Sensitivity Analyses ◽  
Comparative Risk Assessment ◽  
Comparative Risk ◽  
The Impact

Abstract Objectives To prioritize dietary factors for reducing the growing burden of type 2 diabetes (T2D) worldwide, we estimated the impact of suboptimal diet on T2D incidence at global, regional, national, and subnational levels between 1990 and 2015. Methods A comparative risk assessment framework estimated T2D incidence attributable to suboptimal diet in strata jointly stratified by year, nation, age, and sex, across 185 countries. We estimated direct (dietary composition) etiologic effects of 8 factors including nuts/seeds, whole grains, yogurt, processed meats, unprocessed red meats, glycemic load (estimated from refined grains), sugar-sweetened beverages (SSBs) and potatoes. Population demographics were from the United Nations; stratum-specific mean dietary intakes and distributions from Global Dietary Database (GDD), diet-T2D etiologic effects from meta-analyses of prospective cohort studies; and T2D incidence from the Global Burden of Disease study. These inputs and their uncertainties were used to calculate the stratum-specific population attributable fraction (PAF) and then absolute attributable cases, with joint effects estimated using multiplicative PAFs. Results In 2015, suboptimal intakes of these 8 factors were jointly estimated to cause 10.9 million T2D cases (95% UI 7.2–15.3), representing 59.6% of all cases (39.3–83.3%) among adults age 25 + y globally. Low intake of whole grains (3.6 million cases (3.4–3.8)) followed by high intake of SSBs (2.7 million cases (2.5–2.9)) had the largest estimated attributable burdens. Across 7 world regions, highest diet-attributable burdens of T2D were in High Income Countries (2516 cases per million (2115, 2870)) and Former Soviet Union (2341 cases per million (1465, 2970)); and lowest in Sub-Saharan Africa (797 cases per million (333, 1435)). The proportion of T2D attributable to suboptimal diet was generally greater in males vs. females and in younger vs. older age groups. Results for specific countries, trends over time, and further sensitivity analyses will be presented. Conclusions These novel findings provide the most updated estimates of diet-attributable T2D globally, helping to inform priorities for targeted healthcare system, policy, industry and public health interventions to reduce T2D. Funding Sources Gates Foundation.

scholarly journals Use of the correlation between input variables in estimating the risk of feedlot finishing of steers and young steers

2014 ◽  
Vol 86 (2) ◽  
pp. 945-954 ◽  
Author(s):  
PAULO S. PACHECO ◽  
JOÃO RESTLE ◽  
LEONIR L. PASCOAL ◽  
FABIANO N. VAZ ◽  
RICARDO Z. VAZ ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Stochastic Dominance ◽  
Net Present Value ◽  
Latin Hypercube Sampling ◽  
Risk Estimate ◽  
Present Value ◽  
Random Input ◽  
Financial Indicator ◽  
Input Variables ◽  
Diet Intake

The objective of this study was to evaluate the risk of feedlot finishing of steers (22.8 months) and young steers (15.2 months), using or not a correlation between the random input variables (data collected from 2004 to 2010) in the simulation of the Net Present Value (NPV) financial indicator. The animals were fed a diet containing roughage:concentrate ratio of 60:40 for 34 and 143 days, respectively, until they had reached a predetermined slaughter weight of 430 kg. For the NPV simulation, Latin Hypercube sampling was used, with 2000 interactions. The stochastic dominance analysis, test of differences between pairs of curves of cumulative distributions and sensitivity analysis were carried out. The NPV simulation using the correlation resulted in the best option for risk estimate. The confinement of young steers was the alternative of investment most viable than confinement of steers (NPV ≥ 0 of 80.4 vs. 62.3% in the simulation with correlation, respectively). Sensitivity analysis determined the following items had the greatest impact on the estimate of NPV: prices of fat and thin cattle, initial and final weights, diet costs, minimum rate of attractiveness and diet intake.

Sensitivity analysis of an integrated numerical flow model output to key parameters used in common qualitative vulnerability assessment methods

2020 ◽  
Author(s):  
Joanna Doummar ◽  
Assaad H. Kassem
Keyword(s):  
Sensitivity Analysis ◽  
Vulnerability Assessment ◽  
Groundwater Vulnerability ◽  
Assessment Methods ◽  
Qualitative Assessment ◽  
Model Parameters ◽  
Karst Aquifers ◽  
Model Output ◽  
Local Sensitivity ◽  
The Impact

&lt;p&gt;Qualitative vulnerability assessment methods applied in karst aquifers rely on key factors in the hydrological compartments usually assigned different weights according to their estimated impact on groundwater vulnerability. Based on an integrated numerical groundwater model on a snow-governed karst catchment area (Assal Spring- Lebanon), the aim of this work is to quantify the importance of the most influential parameters on recharge and spring discharge and outline potential parameters that are not accounted for in standard methods, when in fact they do play a role in the intrinsic vulnerability of a system. The assessment of the model sensitivity and the ranking of parameters are conducted using an automatic calibration tool for local sensitivity analysis in addition to a variance-based local sensitivity assessment of model output time series (recharge and discharge) &amp;#160;for two consecutive years (2016-2017) to various model parameters. The impact of each parameter was normalized to estimate standardized weights for each of the process based key-controlling parameters. Parameters to which model was sensitive were factors related to soil, 2) fast infiltration (bypass function) typical of karst aquifers, 3) climatic parameters (melting temperature and degree day coefficient) and 4) aquifer hydraulic properties that play a major role in groundwater vulnerability inducing a temporal effect and varied recession. Other less important parameters play different roles according to different assigned weights proportional to their ranking. Additionally, the effect of slope/geomorphology (e.g., dolines) was further investigated. &amp;#160;In general, this study shows that the weighting coefficients assigned to key vulnerability factors in the qualitative assessment methods can be reevaluated based on this process-based approach.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;

scholarly journals Uncertainty and Sensitivity Analysis of the In-Vessel Hydrogen Generation for Gen-III PWR and Phebus FPT-1 with MELCOR 2.2

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4884
Author(s):  
Piotr Darnowski ◽  
Piotr Mazgaj ◽  
Mateusz Włostowski
Keyword(s):  
Sensitivity Analysis ◽  
Hydrogen Generation ◽  
Rank Correlation ◽  
Correlation Coefficients ◽  
Latin Hypercube Sampling ◽  
Severe Accident ◽  
Sensitivity Analyses ◽  
Pressurized Water ◽  
Water Reactor ◽  
Best Estimate

In this study, uncertainty and sensitivity analyses were performed with MELCOR 2.2.18 to study the hydrogen generation (figure-of-merit (FoM)) during the in-vessel phase of a severe accident in a light water reactor. The focus of this work was laid on a large generation-III pressurized water reactor (PWR) and a double-ended hot leg (HL) large break loss of coolant accident (LB-LOCA) without a safety injection (SI). The FPT-1 Phebus integral experiment emulating LOCA was studied, where the experiment outcomes were applied for the plant scale modelling. The best estimate calculations were supplemented with an uncertainty analysis (UA) based on 400 input-decks and Latin hypercube sampling (LHS). Additionally, the sensitivity analysis (SA) utilizing the linear regression and linear and rank correlation coefficients was performed. The study was prepared with a new open-source MELCOR sensitivity and uncertainty tool (MelSUA), which was supplemented with this work. The FPT-1 best-estimate model results were within the 10% experimental uncertainty band for the final FoM. It was shown that the hydrogen generation uncertainties in PWR were similar to the FPT-1, with the 95% percentile being covered inside a ~50% band and the 50% percentile inside a ~25% band around the FoM median. Two different power profiles for PWR were compared, indicating its impact on the uncertainty but also on the sensitivity results. Despite a similar setup, different uncertainty parameters impacted FoM, showing the difference between scales but also a significant impact of boundary conditions on the sensitivity analysis.

scholarly journals Recent findings from the Upper Limb Consortium Study: new approaches to risk assessment and additional health outcomes

2019 ◽  
Vol 63 (1) ◽  
pp. 948-954
Author(s):  
Carisa Harris ◽  
David Rempel ◽  
Alysha R Meyers ◽  
Stephen Bao ◽  
Jay Kapellusch ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Rotator Cuff ◽  
Health Outcomes ◽  
Upper Extremity ◽  
Musculoskeletal Disorders ◽  
Upper Limb ◽  
Assessment Methods ◽  
Work Related ◽  
Upper Extremity Musculoskeletal Disorders ◽  
The Impact

Historically, work-related upper-extremity musculoskeletal disorders (MSD) have comprised a significant portion of the number and cost of injuries in the workplace. The problem of work-related upper-extremity MSD has been, and continues to be, widespread and costly. This panel will present recent research from the Upper Extremity Musculoskeletal Consortium studies. Presentations will be made on new health outcomes such as wrist tendinosis, epicondylitis and rotator cuff syndrome, as well as provide updates on applying new risk assessment methods to prior analyses. The application of the Revised Strain Index will be presented as will a comparison of results from the 2001 ACGIH TLV for Hand Activity to the 2018 ACGIH TLV for Hand Activity. Additionally, the impact of healthy worker survivor effect on the pooled analyses of incident CTS and CTS related disability will be discussed.

scholarly journals Reconciling laboratory and field assessments of neonicotinoid toxicity to honeybees

2015 ◽  
Vol 282 (1819) ◽  
pp. 20152110 ◽  
Author(s):  
Mickaël Henry ◽  
Nicolas Cerrutti ◽  
Pierrick Aupinel ◽  
Axel Decourtye ◽  
Mélanie Gayrard ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Policy Decision ◽  
Assessment Methods ◽  
Field Surveys ◽  
Missing Link ◽  
Annual Crops ◽  
Exposure Pathway ◽  
Study Country ◽  
Neonicotinoid Pesticides ◽  
The Impact

European governments have banned the use of three common neonicotinoid pesticides due to insufficiently identified risks to bees. This policy decision is controversial given the absence of clear consistency between toxicity assessments of those substances in the laboratory and in the field. Although laboratory trials report deleterious effects in honeybees at trace levels, field surveys reveal no decrease in the performance of honeybee colonies in the vicinity of treated fields. Here we provide the missing link, showing that individual honeybees near thiamethoxam-treated fields do indeed disappear at a faster rate, but the impact of this is buffered by the colonies' demographic regulation response. Although we could ascertain the exposure pathway of thiamethoxam residues from treated flowers to honeybee dietary nectar, we uncovered an unexpected pervasive co-occurrence of similar concentrations of imidacloprid, another neonicotinoid normally restricted to non-entomophilous crops in the study country. Thus, its origin and transfer pathways through the succession of annual crops need be elucidated to conveniently appraise the risks of combined neonicotinoid exposures. This study reconciles the conflicting laboratory and field toxicity assessments of neonicotinoids on honeybees and further highlights the difficulty in actually detecting non-intentional effects on the field through conventional risk assessment methods.

Sign in / Sign up

Export Citation Format

Share Document