In a first of its kind study, data regarding heavy-duty vehicle mobile air conditioning (MAC) system refrigerant (R134a) leak rates were collected by directly measuring leak rates from in-use medium- and heavy-duty on- and off-road equipment, and by analyzing large transit bus refrigerant use records provided by fleet managers. The estimated average annual leak rates for all types of MAC systems and vehicles (except large buses) may be higher for older vehicles (2005 and older model years) and averaged 306 g/yr (0.675 lb/yr) per vehicle. The average annual leak rates for 2006 and newer systems are estimated to be 103 g/yr (0.227 lb/yr) per vehicle. Average annual leak rates for all model years combined are estimated at 257 g/ yr (0.567 lb/yr). These values represent leaks resulting from typical in-use operation, and do not include leaks from equipment servicing, technician error, sudden discharge events (e.g., as a result of accidents), or other sources. The distribution of the measured leak rates cannot be firmly established, but it appears to resemble a log-normal distribution, with most results being grouped at the low-end and a few “gross emitters” with emission rates several times higher than average.

These gross emitters have a disproportionate effect on the overall emission inventory. The annual R134a leak rate from large buses was estimated to be nearly 1,340 g/year (2.9 lb/year) per bus. Unlike the estimates for other vehicle types, this estimate includes all types of leaks from the MAC system. Leak rates were combined with the offroad and medium/heavyduty on-road vehicle population data for California to estimate annual R134a emissions. Estimated annual leakage of R134a from heavy-duty vehicles in California is estimated to be 1.35 MT CO2E per year, assuming different leak rates by age group. Due to small sample sizes and simple assumptions for projecting leak rates to an “annualized” basis, substantial uncertainty remains regarding emission inventory estimates for this population. Results from this study should be combined with future interview and survey results from large fleet maintenance personnel to address the most significant sources of uncertainty and knowledge gaps.