New policies to deal with climate change and other drivers impacting on resilience to flooding in urban areas: the CORFU approach

In the context of urban flood management, resilience is equal to resisting, recovering, reflecting and responding. The variety of causes of flooding and their consequences underpin the need for increased and internationally coordinated efforts to enhance technologies and policies for dealing with floods. This paper addresses this issue and presents some novel research ideas related to resilience to flooding in urban areas, which are under development within the EU FP7 project ‘Collaborative research on flood resilience in urban areas’ (CORFU). The approach adopted in this project aims to quantify the cost-effectiveness of resilience measures and integrative and adaptable flood management plans for different scenarios of relevant drivers: urban development, socio-economic trends and climate changes. It is believed that the way in which the different models are being put together, combined with the variability of conditions in case study areas in Asia and in Europe, will ultimately enable more scientifically sound policies for the management of the consequences of urban flooding.     

Characterization of dissolved organic carbon and Humic substances in the well water of the Blackfoot disease area in Taiwan

Since the early 1960s, many investigators have reported that blackfoot disease, a peripheral vascular disease, observed in southwestern Taiwan is due to drinking the higher arsenic concentration in well water. However, recent studies indicated that the relationship with blackfoot disease is not only with arsenic but also humic substances. This paper presents some results concerning the characterization (such as fluorescence, elemental composition, molecular weight and carbon distribution) of humic substances isolated from the Fuhsing well water of the blackfoot disease area. For comparison, the dissolved organic carbon (DOC) and humic substances in the normal well water from Chiuying and the Nanwan coastal water were also analyzed. In general, in the well water of the blackfoot disease area, extremely high concentrations of DOC (18.5mg/L) and fulvic acid (7.54mg/L) with high fluorescence intensity (59.1, equivalent to 0.0282uM quinine sulfate solution) and high percentages (over 50%) of low molecular weights of less than 1,000 were obtained compared with those of normal waters. C‐13 Nuclear magnetic resonance spectroscopy showed a high content (37.2%) of aromatic carbon. These higher concentrations of DOC and fulvic acid with the higher content of aromatic carbon in well water might be one of the key factors causing the blackfoot disease in Taiwan.     

Choosing classes for size projection matrix models

Projection matrix models are intensely used in ecology to model the dynamics of structured populations. When dealing with size-structured populations, there is no satisfactory algorithm to partition size into discrete classes. We show that the Vandermeer-Moloney algorithm for choosing classes is inconsistent with the Usher model, and systematically selects the finest classes. Considering that the matrix model is a discrete approximation of a continuous model, we define an approximation error as the sum of a distribution error (the difference between the discrete distribution and its continuous counterpart), and a sample error. The optimal partition of size into classes is the one that minimizes the approximation error. This method for choosing classes also shows that the choice of the class width cannot be disconnected from the choice of the time step. When applied to 520 trees of Dicorynia guianensis in French Guiana, this algorithm identified 8 classes of 11.4 cm in width, which is in agreement with the empirical choice of foresters.     

Injuries associated with the use of riding mowers in the United States, 2002-2007

Context: To examine injuries among patients treated in an emergency department (ED) related to the use of a riding lawn mower.Design and Setting: Data were obtained from the National Electronic Injury Surveillance System for the years 2002-2007. National estimates of ED visits for injuries associated with the use of a riding lawn mower were analyzed. Narrative text entries were categorized to provide a detailed record of the circumstances precipitating the injury. Average annual rates were calculated and logistic regression analyses were employed to determine risk estimates for patient disposition and demographic characteristics related to ED visits for injuries associated with riding mowers.Results: From 2002 through 2007, there were an estimated 66,341 ED visits for injuries related to the use of riding lawnmowers in the U.S., with an average annual rate of 6.0 ED visits per 100,000 males, and 1.6 ED visits per 100,000 females. Older adults had higher rates of ED visits for injuries (7.2/100,000) than younger age groups. The most common injuries involved contusions (24%); sprains/strains (22%) and fractures (17%). The majority of patients (90%) were treated and released the same day. Results of logistic regression analyses revealed that older adults were more likely to be hospitalized when compared to younger age groups; and incidents involving rollovers [OR = 5.45 (95% CI = 3.22-9.23)] and being run over [6.01 (95% CI 3.23-11.17)] were more likely to result in hospitalization when compared to all other circumstances of injury.Conclusions: Riding mowers present injury patterns and circumstances that are different than those reported for push mowers. Circumstances related to injuries and age groups affected were varied, making prevention of riding mower injuries challenging. Application/Impact: Findings support the need to increase awareness and/or change the design of riding mowers with respect to risk of rollover injuries.     

Explorative spatial analysis of traffic accident statistics and road mortality among the provinces of Turkey

Introduction

The aim of the study is to describe the inter-province differences in traffic accidents and mortality on roads of Turkey.

Method

Two different risk indicators were used to evaluate the road safety performance of the provinces in Turkey. These indicators are the ratios between the number of persons killed in road traffic accidents (1) and the number of accidents (2) (nominators) and their exposure to traffic risk (denominator). Population and the number of registered motor vehicles in the provinces were used as denominators individually. Spatial analyses were performed to the mean annual rate of deaths and to the number of fatal accidents that were calculated for the period of 2001-2006. Empirical Bayes smoothing was used to remove background noise from the raw death and accident rates because of the sparsely populated provinces and small number of accident and death rates of provinces. Global and local spatial autocorrelation analyses were performed to show whether the provinces with high rates of deaths-accidents show clustering or are located closer by chance. The spatial distribution of provinces with high rates of deaths and accidents was nonrandom and detected as clustered with significance of P < 0.05 with spatial autocorrelation analyses.

Results

Regions with high concentration of fatal accidents and deaths were located in the provinces that contain the roads connecting the Istanbul, Ankara, and Antalya provinces. Accident and death rates were also modeled with some independent variables such as number of motor vehicles, length of roads, and so forth using geographically weighted regression analysis with forward step-wise elimination. The level of statistical significance was taken as P < 0.05. Large differences were found between the rates of deaths and accidents according to denominators in the provinces. The geographically weighted regression analyses did significantly better predictions for both accident rates and death rates than did ordinary least regressions, as indicated by adjusted R² values. Geographically weighted regression provided values of 0.89-0.99 adjusted R² for death and accident rates, compared with 0.88-0.95, respectively, by ordinary least regressions.

Impact on industry

Geographically weighted regression has the potential to reveal local patterns in the spatial distribution of rates, which would be ignored by the ordinary least regression approach. The application of spatial analysis and modeling of accident statistics and death rates at provincial level in Turkey will help to identification of provinces with outstandingly high accident and death rates. This could help more efficient road safety management in Turkey.     

The relationship between recruitment processes, familiarity, trust, perceived risk and safety

Introduction and Method

Participants′ perceptions of the safety-related aspects of their organization′s recruitment processes were examined, as were their perceptions of safety aspects associated with new recruits.

Results

One hundred and fifty-four professional fire fighters indicated the trust they held in the safety-related aspects of their organizations′ selection and pre-start training. Perceived trust in pre-start training was negatively correlated (r = -.24, p < .01) with the risk associated with new recruits, and positively correlated (r = .50, p < .01) with ratings of trust in recruits to immediately work safely. Furthermore, trust in recruits to immediately work safely was negatively correlated (r = -.21, p < .01) with crews′ safety behavior toward recruits.

Conclusions

These results are interpreted as particularly dangerous for workers, as new recruits lack familiarity with aspects of their new workplace that cannot be addressed by either selection or pre-start training, making them a risk.

Impact on Industry

Organizations should actively identify new recruits, and encourage existing team members not to immediately trust new recruits to work safely.     

Validity of police-reported alcohol involvement in fatal motor carrier crashes in the United States between 1982 and 2005

Objective

To examine the validity of police-reported alcohol data for drivers involved in fatal motor carrier crashes.

Material and Methods

We determined the availability of blood alcohol concentration (BAC) and police-reported alcohol data on 157,702 drivers involved in fatal motor carrier crashes between 1982 - 2005 using Fatality Analysis and Reporting System (FARS) data. Drivers were categorized as motor carrier drivers if they operated a vehicle with a gross vehicle weight rating of greater than 26,000 pounds. Otherwise, they were classified as non motor carrier drivers. The sensitivity and specificity of police-reported alcohol involvement were estimated for both driver types.

Results

Of the 157,702 drivers, 18% had no alcohol information, 15% had BAC results, 42% had police-reported alcohol data, and 25% had both. Alcohol information varied significantly by driver, crash, and vehicle characteristics. For example, motor carrier drivers were significantly more likely (51%) to have BAC testing results compared to non motor carrier drivers (31%) (p < 0.001). The sensitivity of police-reported alcohol involvement for a BAC level ≥ 0.08 was 83% (95% CI 79%, 86%) for motor carrier drivers and 90% (95% CI 89%, 90%) for non motor carrier drivers. The specificity rates were 96% (95% CI 95%, 96%) and 91% (95% CI 90%, 91%), respectively.

Conclusions

The sensitivity and specificity of police-reported alcohol involvement are reasonably high for drivers involved in fatal motor carrier crashes. Further research is needed to determine the extent to which the accuracy of police-reported alcohol involvement may be overestimated because of verification bias.

Impact on the Industry

Based on the results of this study, the federal government should continue to work with states to strengthen their strategies to increase chemical testing of all drivers involved in fatal crashes.     

Chemical plant innovative safety investments decision-support methodology

Introduction

This article examines the extent to which investing in safety during the creation of a new chemical installation proves profitable.

Method

The authors propose a management supporting cost-benefit model that identifies and evaluates investments in safety within a chemical company. This innovative model differentiates between serious accidents and less serious accidents, thus providing an authentic image of prevention-related costs and benefits. In classic cost-benefit analyses, which do not make such differentiations, only a rudimentary image of potential profitability resulting from investments in safety is obtained.

Results

The resulting management conclusions that can be drawn from such classical analyses are of a very limited nature. The proposed model, however, is applied to a real case study and the proposed investments in safety at an appointed chemical installation are weighed against the estimated hypothetical benefits resulting from the preventive measures to be installed at the installation.

Conclusion

In the case-study carried out in question, it would appear that the proposed prevention investments are justified.

Impact on industry

Such an economic exercise may be very important to chemical corporations trying to (further) improve their safety investments.