Rating locomotive crew diesel emission exposure profiles using statistics and Bayesian Decision Analysis

Air quality on UK diesel and hybrid trains

Concentrations of particulate matter (PM10, PM2.5), ultrafine (UFP), particle number (PNC), black carbon (BC), nitrogen dioxide (NO2) and nitrogen oxides (NOX) were measured in train carriages on diesel and bi-mode trains on inter-city and long-distance journeys in the United Kingdom (UK) using a high-quality mobile measurement system. Air quality on 15 different routes was measured using highly-time resolved data on a total of 119 journeys during three campaigns in winter 2020 and summer 2021; this included 13 different train classes. Each journey was sampled 4-10 times with approximatively 11,000 min of in-train concentrations in total. Mean-journey concentrations were 7.552 µg m-3 (PM10); 3.936 µg m-3 (PM2.5); 333-11,300 # cm-3 (PNC); 225-9,131 # cm-3 (UFP); 0.6-11 µg m-3 (BC); 28-201 µg m-3 (NO2); and 130-3,456 µg m-3 (NOX). The impact of different factors on in-train concentrations was evaluated. The presence of tunnels was the factor with the largest impact on the in-train particle concentrations with enhancements by a factor of 40 greater than baseline for BC, and a factor 6 to 7 for PM and PNC. The engine fuel mode was the factor with the largest impact on NO2 with enhancements of up to 14-times larger when the train run on diesel compared to the times running on electric on hybrid trains. Train classes with an age < 10 years observed the lowest in-train PM, BC and NOX concentrations reflecting improvements in aspects of rail technology in recent years. Air quality on UK diesel trains is higher than ambient concentrations but has lower PM2.5 and PNC than most other transport modes, including subway systems, diesel and petrol cars. This paper adds significantly to the evidence on exposure to poor air quality in transport micro-environments and provides the industry and regulatory bodies with reference-grade measurements on which to establish in-train air quality guidelines.

Air quality in cabin environment of different passenger cars: effect of car usage, fuel type and ventilation/infiltration conditions

Despite that commuters spend only 5.5% of their time in cabin vehicles, their exposure to harmful air pollutants, originated from the vehicle itself, and traffic emission is considered significant. In this study, two passenger cars with different type of fuels were investigated in terms of air quality and thermal comfort of their cabin. Investigation was performed in the city of Kozani, Northern Greece. Moreover, air samples near the exhausts were taken, in order to compare concentration of compounds found indoors. Twelve volatile organic compounds and CO₂ were measured inside the cabin when the cars were stopped, when idle and when they were cruising in medium and heavy traffic roads, under various ventilated conditions. Thermal comfort was investigated while driving the cars through the city traffic. Results showed that the air around the diesel exhaust is less affected by emissions from the engine compared to LPG fuel. This is reflected to the TVOC measured into the cabin. Results also revealed that the air quality of a diesel fuel moving car with open windows is only affected by the traffic emissions from neighbouring vehicles, while for the car with LPG fuel, the self-pollution from its own exhaust might contribute together with the outdoor air.

Beyond descriptive statistics: using additional analyses to determine the technological feasibility of meeting a new exposure limit

In determining whether a new permissible exposure limit is technologically feasible, the Occupational Safety and Health Administration (OSHA) and various courts have used poorly defined criteria such as whether "most employers most of the time" are able to comply with a standard. This vague definition creates problems when employers try to determine the best way to protect their workers and estimate the costs to remain in compliance with the permissible exposure limit. This article proposes a more rigorous approach to determine feasibility. By utilizing the best available statistical methods, employers and rule makers can better understand the variability within existing exposure data to determine the feasibility of new exposure limits. There are several readily available statistical tools that can be used for this purpose. To illustrate these techniques, a subset of data from the foundry industry and analysis from the OSHA respirable crystalline silica rulemaking proceeding are compared to methods published by the National Institute for Occupational Safety and Health in 1977 and a more sophisticated Bayesian approach. The results of this analysis suggest that complying with a new permissible exposure limit is more challenging than what is implied by OSHA's analysis, and calls into question its method of determining compliance. In the same vein, OSHA should move away from assessing compliance based on individual measurements and instead use a statistical approach to determine if a workplace is in compliance. These changes will encourage employers to better characterize occupational exposures, and will ultimately lead to better protection for employees while also providing employers protection from violations due to one-off overexposures.

Occupational Exposure to Diesel Particulate Matter in Municipal Household Waste Workers

OBJECTIVE

The purposes of this study were to determine the following: 1) the exposure levels of municipal household waste (MHW) workers to diesel particulate matter (DPM) using elemental carbon (EC), organic carbon (OC), total carbon (TC), black carbon (BC), and fine particulate matter (PM 2.5) as indicators; 2) the correlations among the indicators; 3) the optimal indicator for DPM; and 4) factors that influence personal exposure to DPM.

METHODS

A total of 72 workers in five MHW collection companies were assessed over a period of 7 days from June to September 2014. Respirable EC/OC samples were quantified using the thermal optical transmittance method. BC and PM 2.5 were measured using real-time monitors, an aethalometer and a laser photometer. All results were statistically analyzed for occupational and environmental variables to identify the exposure determinants of DPM.

RESULTS

The geometric mean of EC, OC, TC, BC and PM 2.5 concentrations were 4.8, 39.6, 44.8, 9.1 and 62.0 μg/m3, respectively. EC concentrations were significantly correlated with the concentrations of OC, TC and BC, but not with those of PM 2.5. The exposures of the MHW collectors to EC, OC, and TC were higher than those of the drivers (p<0.05). Workers of trucks meeting Euro 3 emission standard had higher exposures to EC, OC, TC and PM 2.5 than those working on Euro 4 trucks (p<0.05). Multiple regression analysis revealed that the job task, European engine emission standard, and average driving speed were the most influential factors in determining worker exposure.

CONCLUSIONS

We assessed MHW workers' exposure to DPM using parallel sampling of five possible indicators. Of these five indicators, EC was shown to be the most useful indicator of DPM exposure for MHW workers, and the job task, European emission standard, and average driving speed were the main determinants of EC exposure.