A comparison of worker risk of injury while working on fully automated side loaders and other residential collection trucks at a large solid waste collection company

The study aim was to determine whether using automated side loader (ASL) trucks in higher proportions compared to other types of trucks for residential waste collection results in lower injury rates (from all causes). The primary hypothesis was that the risk of injury to workers was lower for those who work with ASL trucks than for workers who work with other types of trucks used in residential waste collection. To test this hypothesis, data were collected from one of the nation’s largest companies in the solid waste management industry. Different local operating units (i.e. facilities) in the company used different types of trucks to varying degrees, which created a special opportunity to examine refuse collection injuries and illnesses and the risk reduction potential of ASL trucks.^ The study design was ecological and analyzed end-of-year data provided by the company for calendar year 2007. During 2007, there were a total of 345 facilities which provided residential services. Each facility represented one observation.^ The dependent variable – injury and illness rate, was defined as a facility’s total case incidence rate (TCIR) recorded in accordance with federal OSHA requirements for the year 2007. The TCIR is the rate of total recordable injury and illness cases per 100 full-time workers. The independent variable, percent of ASL trucks, was calculated by dividing the number of ASL trucks by the total number of residential trucks at each facility.^ Multiple linear regression models were estimated for the impact of the percent of ASL trucks on TCIR per facility. Adjusted analyses included three covariates: median number of hours worked per week for residential workers; median number of months of work experience for residential workers; and median age of residential workers. All analyses were performed with the statistical software, Stata IC (version 11.0).^ The analyses included three approaches to classifying exposure, percent of ASL trucks. The first approach included two levels of exposure: (1) 0% and (2) >0 - <100%. The second approach included three levels of exposure: (1) 0%, (2) ≥ 1 - < 100%, and (3) 100%. The third approach included six levels of exposure to improve detection of a dose-response relationship: (1) 0%, (2) 1 to <25%, (3) 25 to <50%, (4) 50 to <75%, (5) 75 to <100%, and (6) 100%. None of the relationships between injury and illness rate and percent ASL trucks exposure levels was statistically significant (i.e., p<0.05), even after adjustment for all three covariates.^ In summary, the present study shows that there is some risk reduction impact of ASL trucks but not statistically significant. The covariates demonstrated a varied yet more modest impact on the injury and illness rate but again, none of the relationships between injury and illness rate and the covariates were statistically significant (i.e., p<0.05). However, as an ecological study, the present study also has the limitations inherent in such designs and warrants replication in an individual level cohort design. Any stronger conclusions are not suggested.^

Do charges to freight trucks and trains in the European Union reflect their social marginal costs? Application to the case of Spain

In the last few years, the European Union (EU) has become greatly concerned about the environmental costs of road transport in Europe as a result of the constant growth in the market share of trucks and the steady decline in the market share of railroads. In order to reverse this trend, the EU is promoting the implementation of additional charges for heavy goods vehicles (HGV) on the trunk roads of the EU countries. However, the EU policy is being criticised because it does not address the implementation of charges to internalise the external costs produced by automobiles and other transport modes such as railroad. In this paper, we first describe the evolution of the HGV charging policy in the EU, and then assess its practical implementation across different European countries. Second, and of greater significance, by using the case study of Spain, we evaluate to what extent the current fees on trucks and trains reflect their social marginal costs, and consequently lead to an allocative-efficient outcome. We found that for the average case in Spain the truck industry meets more of the marginal social cost produced by it than does the freight railroad industry. The reason for this lies in the large sums of money paid by truck companies in fuel taxes, and the subsidies that continue to be granted by the government to the railroads.

New trucks save fuel. 1979.

Mode of access: Internet.

Some measures of accessibility of large trucks to the Texas highway system. Final report.

Texas State Department of Highways and Public Transportation, Transportation Planning Division, Austin

A feasibility study of a sealed safety monitor for trucks carrying LNG and other hazardous materials. Final report.

Energy Department, Office of Operational Safety Programs, Washington, D.C.

A computer program (VEHSIM) for vehicle fuel economy and performance simulation (automobiles and light trucks). Volume I: description and analysis. Final report.

National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

A computer program (VEHSIM) for vehicle fuel economy and performance simulation (automobiles and light trucks). Volume II: users guide. Final report.

National Highway Traffic Safety Administration, Office of Research and Development, Washington, D.C.

The effect of truck size and weight on accident experience and traffic operations. Volume III: accident experience of large trucks. Final report.

Federal Highway Administration, Washington D.C.

A computer program (VEHSIM) for vehicle fuel economy and performance simulation (automobiles and light trucks). Volume IV: enhancements. Final report.

National Highway Traffic Safety Administration, Office of Research and Development, Washington D.C.