Monitoring of Phenol in Wastewater Bioremediation by HPLC

Bioremediation emphasizes the detoxification and destruction of toxic substances by microorganisms. Wastewater obtained from an industrial concern was solvent extracted with methyl alcohol and dichloromethane and analysed by GC/MS. Besides phenol, a large variety of organic compounds were detected. Under controlled laboratory conditions, the wastewater was innoculated with a mixed culture of microorganisms specially selected for their abilities to degrade phenol. Samples were collected at regular intervals from the stirred tank bioreactor and analysed for phenol by reverse phase HPLC with a C18 column. Results shows that from an initial phenol concentration of 987 ppm, slightly more than 50% was destroyed within 163 hours. The dry weight of the microorganisms and the plate count (CFU/ml) shows a steady increase from 0.5238 gms to 0.5355 gms and from 1.1E+9 to 1.94E+13 respectively over the same period. This suggested that the phenol was consumed by the microorganisms as the sole carbon source.     

Gender differences and demographic influences in perceived concern for driver safety and support for impaired driving countermeasures

IntroductionDriving safety, impaired driving, and legislation to address these concerns remain important issues. It is imperative countermeasures be targeted toward the most appropriate groups. This paper explores the potential relationship between gender and driving attitudes toward safety issues and impaired-driving countermeasures.MethodThe data are from the 2007 Impaired Driving Survey commissioned by Transport Canada and Mothers Against Drunk Driving (MADD) Canada. The survey is a, stratified by region, telephone survey of 1,514 Canadian drivers 18 years of age and older with a valid driver's license who had driven within the past 30 days.ResultsThe findings illustrate a consistent impact of gender on these issues. Other variables were also identified as relevant factors although less consistently. Current findings suggest that strategies for building support for interventions, or for changing risk perception/concern for risky driving behaviors should be tailored by gender to maximize the potential for behavior change.ImpactThis information may assist program and policy developers through the identification of more or less receptive target groups. Future research directions are also presented.     

Age group differences in collision risk

Introduction

The purpose of the current study was to examine differences in factors associated with self-reported collision involvement of three age groups of drivers based on a large representative sample of Ontario adults. Method: This study was based on data from the CAMH Monitor, an ongoing cross-sectional telephone survey of Ontario adults 18 years and older from 2002 to 2005. Three age groups were examined: 18-34 (n = 1,294), 35-54 (n = 2,428), and 55+ (n = 1,576). For each age group sample, a logistic regression analysis was conducted of self-reported collision involvement in the last 12 months by risk factor measures of driving exposure (kilometers driven in a typical week, driving is stressful, and driving on busy roads), consuming five or more drinks of alcohol on one occasion (past 12 months), cannabis use (lifetime, and past 12 months), and driving after drinking among drinkers (past 12 months), controlling for demographics (gender, region, income, and marital status). Results: The study identified differences in factors associated with self-reported collision involvement of the three age groups of adult drivers. The logistic regression model for the youngest group revealed that drivers who reported that driving was stressful at least some of the time, drank five or more drinks on an occasion, and drove after drinking had an increased risk of collision involvement. For the middle age group, those who reported using cannabis in the last 12 months had significantly increased odds of reporting collision involvement. None of the risk factor measures showed significant associations with collision risk for older drivers (aged 55+). Impact: The results suggest potential areas for intervention and new directions for future research.     

Is there a link between motor vehicle collisions and being a cigarette smoker in Canada? Analysis of survey data from Ontario from 2002 to 2014

Objective: Although most research on drugs and driving has focused on the use of alcohol and cannabis, research that has been conducted on cigarette smoking and collisions has found that smokers have an increased collision involvement. Studies dating from 1967 through 2013 have shown a crude relative risk of about 1.5 among smokers compared to nonsmokers. In Canada, the association between smoking and collisions has not been recently investigated. Studies that have examined the association between smoking and collisions often did not control for all confounding factors, such as alcohol use and driving exposure, which have been associated with increased collision rates. Additionally, a number of these studies were examined in countries and at times when prevalence of smoking was much higher than is currently the case in Canada. The purpose of this research is to examine the association between self-reported current smoking and past-year collision involvement, controlling for confounding factors, in a large representative sample of adult drivers in Ontario, Canada, from 2002 and 2014.

Method: Data are based on the Centre for Addiction and Mental Health (CAMH) Monitor, an ongoing, rolling telephone survey of Ontario adults that provides epidemiological surveillance of indicators related to alcohol, tobacco, and other drug use, as well as physical and mental health. The survey uses random-digit-dialing methods via Computer-Assisted Telephone Interview, with response rates over 50%.

Results: Prevalence of self-reported collision involvement within the past year for 2002–2014 was 8.6% among those who currently smoke compared to 6.5% of nonsmokers. Logistic regression analysis, controlling for the potential confounding effects of sociodemographics, driving exposure measures, drinking frequency, and hazardous alcohol use, found that the overall odds for collision involvement in the preceding year among current smokers for 2002–2014 was 1.27 (95% confidence interval [CI], 1.06–1.53) times that of nonsmokers.

Conclusions: These findings indicate that despite a substantial reduction in overall prevalence of smoking in Canada, smokers still have a significantly increased odds of collision involvement, even when controlling for alcohol and exposure. Additionally, the results are consistent with the increased odds/risks of motor vehicle collisions found in other countries.     

Literature review on risky driving videos on YouTube: Unknown effects and areas for concern?

Objective: Entry of terms reflective of extreme risky driving behaviors into the YouTube website yields millions of videos. The majority of the top 20 highly subscribed automotive YouTube websites are focused on high-performance vehicles, high speed, and often risky driving. Moreover, young men are the heaviest users of online video sharing sites, overall streaming more videos, and watching them longer than any other group. The purpose of this article is to review the literature on YouTube videos and risky driving.

Methods: A systematic search was performed using the following specialized database sources—Scopus, PubMed, Web of Science, ERIC, and Google Scholar—for the years 2005–2015 for articles in the English language. Search words included “YouTube AND driving,” “YouTube AND speeding,” “YouTube AND racing.”

Results: No published research was found on the content of risky driving videos or on the effects of these videos on viewers. This literature review presents the current state of our published knowledge on the topic, which includes a review of the effects of mass media on risky driving cognitions; attitudes and behavior; similarities and differences between mass and social media; information on the YouTube platform; psychological theories that could support YouTube's potential effects on driving behavior; and 2 examples of risky driving behaviors (“sidewalk skiing” and “ghost riding the whip”) suggestive of varying levels of modeling behavior in subsequent YouTube videos.

Conclusions: Every month about 1 billion individuals are reported to view YouTube videos (ebizMBA Guide 2015 ebizMBA Guide. Top 15 most popular websites. 2015. Available at: http://www.ebizmba.com/articles/most-popular-websites [Google Scholar]) and young men are the heaviest users, overall streaming more YouTube videos and watching them longer than women and other age groups (Nielsen 2011 Nielsen. State of the media: the social media report. Q3. 2011. Available at: http://www.nielsen.com/us/en/insights/reports/2011/social-media-report-q3.html [Google Scholar]). This group is also the most dangerous group in traffic, engaging in more per capita violations and experiencing more per capita injuries and fatalities (e.g., Parker et al. 1995 Parker D, Reason J, Manstead ASR, Stradling SG. Driving errors, driving violations and accident involvement. Ergonomics. 1995;38:1036–1048.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]; Reason et al. 1990 Reason J, Manstead A, Stradling S, Baxter J, Campbell K. Errors and violations on the roads: a real distinction? Ergonomics. 1990;33:1315–1332.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]; Transport Canada 2015 Vingilis E, Yilderim-Yenier Z, Fischer P, et al. Self-concept as a risky driver: Mediating the relationship between racing video games and on-road driving violations in a community-based sample. Transp Res Part F Traffic Psychol Behav. 2016;43:15–23. [Google Scholar]; World Health Organization 2015 World Health Organization. Road traffic injuries. Fact sheet no. 358. 2015. Available at: http://www.who.int/mediacentre/factsheets/fs358/en/# Accessed March 14, 2016. [Google Scholar]). YouTube also contains many channels depicting risky driving videos. The time has come for the traffic safety community to begin exploring these relationships.     

Characteristics and predictors of recidivist drink-drivers

Objective: The current study compared characteristics of nonrecidivist versus recidivist drink-drivers and of recidivists in their first versus second appearance at Back on Track (BOT), the remedial measures program for impaired drivers in Ontario, Canada.

Methods: Information from 59,134 convicted drivers who participated in BOT between 2000 and 2010 was examined to identify drivers who completed the program a second time following reconviction.

Results: A total of 586 recidivists were identified. Compared to nonrecidivist drivers, recidivists at first attendance were more likely to be male and had higher scores on measures of alcohol dependence and adverse legal consequences of substance use. Compared to nonrecidivist drivers, recidivists at second attendance were significantly older, had a higher income, were more likely to be retired, and were less likely to be employed part-time. They had fewer legal problems. Recidivists reported fewer drinking days and fewer drinks per occasion but greater use of benzodiazepines than nonrecidivists and had higher scores on a measure of future risk of alcohol- and drug-related problems. Comparison of recidivists' characteristics at first versus second attendance confirmed many of these findings, with second-time recidivists reporting fewer drinks per drinking day and greater use of benzodiazepines and having higher scores on a measure of future substance use problems than first-time recidivists.

Conclusions: Results suggest that identification of drivers at increased risk of recidivism may be possible at first program attendance by examining indicators of increased alcohol-related problems. In addition, recidivists appear to show a greater readiness to change at second attendance. Implications for remedial program development and recommendations for future research are discussed.