A spatial and fleet disaggregated approach to calculating the NOX emissions inventory for non-road mobile machinery in London

Abstract

The latest London atmospheric emissions inventory (2016), which is calculated using fuel consumption and construction employment, estimates that, the construction sector contributes 34% of the total PM 10 emissions (the largest source), and 7% of the total NO X emissions (5 th largest source). These contribute significantly to NO 2 and PM 2.5 pollution problems in London, which is a major concern for public health. Real-world emission factors from tail-pipe measurements were coupled to a register for construction machinery, to develop a novel ‘spatial and fleet disaggregated’ emissions inventory for the construction sector in London. This method estimated 1,294 tonnes of NO X in 2018 and 1,578 tonnes of NO X in 2019 from non-road mobile machinery in the construction sector, approximately 55% and 45% lower for 2018 and 2019 respectively, than the current (2016) London atmospheric emissions inventory (2850 tonnes). However, compared to the current London atmospheric emissions inventory, the new NO X emissions are higher in central London, under-estimating the importance of this source in central London. The fleet-disaggregated emissions inventory enables potential policy to be developed by focusing on high-emitters registered on the London database. As a demonstration, two emission abatement scenarios were modelled – first: by retrofitting older generators with a SCR-DPF system, a potential 53% reduction in overall NO X emissions was predicted from all NRMM; and second: by accelerating the excavator fleet-turnover – a more modest 2-tonne reduction in overall NO X emissions was predicted from all NRMM in London. •Real-world emission factors from tail-pipe measurements were coupled to a register for construction machinery, to develop a novel method to calculating the NRMM emissions inventory in London •1294 tonnes of NO X in 2018 from NRMM in the construction sector, approximately 55% lower than 2016 LAEI •This novel method enables potential policy to be developed by focusing on high-emitters registered on the London database.