TOWARDS THE REGULATION OF NON-ROAD DIESEL EMISSIONS IN AUSTRALIA

subtracting the attributable numbers of deaths in each age group from the expected numbers of deaths, as described by Miller and Hurley (2003) and Broome et al. (2020). For 2018, the NRDEattributable YLL were calculated by summing the difference between the age at death and life expectancy for all attributable deaths in five-year age groups (up to age 85-plus) using a life table method.

3.5.3. Impacts of future changes in NRDE emissions

In a future scenario with static emissions – as well as a static population size and age structure – the annual YLL attributable to air pollution would also remain constant. However, NRDE emissions were projected to change over the coming decades, and considerable reductions could potentially be achieved through management interventions. Yet the health impacts of year-to-year changes in NRDE emissions would not be realised immediately because air pollution-related diseases are acquired on a range of timescales. Therefore, a separate analysis was conducted to determine the future YLL due to the changes in NRDE emissions (and exposure, using the intermediate year factors) between 2018 and 2043. This accounted for the timing of acute and chronic air pollution exposure effects.

The cessation lag in health effects of future changes in exposure was modelled by apportioning 30% of the total health effect into year 1, a further 50% over the years 2–5 and the final 20% across years 6–20, as recommended by the USEPA (Walton 2010). The lag-weighted mortality impacts were then added to the health burden for the 2018 base year, and future health effects were modelled over time. As noted earlier, health impacts were modelled out to 2063 to include the effects of changes in emissions leading up to 2043.

To minimise uncertainties associated with demographic model projections, the annual YLL values were generated on the assumption of identical population sizes and age structures. The health modelling also assumed no further changes in concentrations after 2043.

4. Results

4.1. Engine stock

4.1.1. BAU scenario

The total number of NRDEs in Australia in 2018 was estimated to be around 640,000 units. The stock was projected to increase to around 750,000 units by 2028 (a 17% increase relative to 2018), and to around 945,000 units by 2043 (a 48% increase relative to 2018). The largest numbers of engines were in agricultural equipment, reflecting the large annual sales in the sector and the long lifetime of many engines. Stocks of generators and industrial equipment were also substantial.

In 2018, the largest single category of the stock by power rating was sub-8 kW engines (17%), and engines up to 37 kW comprised over 40% of the stock. The number of engines tended to decrease with increasing power, noting peaks in the 75130 kW (11%) and 225-450 kW (12%) bands. Engines <37 kW accounted for half of the increase in stock between 2018 and 2043.

4.1.2. Effects of management scenarios

Figure 5 shows the effects of the management scenarios on the NRDE tier distribution. For the BAU scenario, in 2018, almost one third of NRDEs in the Australian stock were not compliant with any emission standard (Tier 0). More than 50% of engines were certified as either Tier 2 or Tier 3. In 2028, almost 30% of engines were projected to meet Tier 4 standards, and over 20% were projected to meet Tier 3. Some 14% were projected to not comply with any standard. By 2043, around 45% of engines were expected to be compliant with Tier 4 standards, with 11% not complying with any standard.

In MS1 the transition to Tier 4 occurred gradually over the timeframe of the analysis, given that a substantial proportion of the sales of new engines in the years after the industry agreement would still follow the BAU projection. In 2028, the changes in the stock were small relative to the BAU scenario. In 2043 MS1 had a larger, but still modest, impact on the stock. The Tier 4f stock proportion was 47% in MS1, compared with 36% in the BAU scenario.

In MS2 the changes in the stock in 2028 were also relatively small. In 2043, however, the picture was rather different, with there being a large increase in the Tier 4f proportion of the stock compared with the BAU scenario, from 36% to 88%.

In MS3 the changes in the stock in 2028 were more substantial. In particular, there was an increase the Tier 4f proportion of the stock from 23% (BAU) to 42% (MS3). In 2043, there was again a large increase in the Tier 4f proportion of the stock compared with the BAU scenario, from 36% to 93%.

4.2. Emissions

The national emissions in the BAU and management scenarios are given in Table 3, and additional details are provided below.