Background
A recent study (WHO, 2014) identified Delhi as the most polluted city in the world (based on PM2.5 annual concentrations), with considerable health impacts for ~19 million inhabitants, causing an estimated 20,000 premature deaths annually, mainly due to particulate matter (PM) and ozone (O3). This figure is anticipated to rise to ~30,000 by 2025 (Lelieveld et al., 2015). This analysis does not include effects of nitrogen dioxide (NO2) and does not explicitly consider PM composition (e.g. metals and polycyclic hydrocarbons, particularly detrimental to human health). In the face of continuing rapid growth in population, city authorities in Delhi have initiated a range of measures to control air quality, including use of compressed natural gas in public transport, relocation of industries and introduction of Metro transport. Despite this, air quality continues to deteriorate. The accurate quantification of the emissions of primary air pollutants and precursors for PM and O3, and their variations in space and time is an important pre-requisite for modelling air quality, human exposure and other effects on regional climate and visibility. It is also necessary for identifying the most economically and socially acceptable solutions for air pollution abatement. Emissions in Delhi, as with other developing (mega)cities in India and beyond, are complex, as the contributions from diffuse sources such as traffic, biomass burning for cooking and heating and small industrial sources are large compared with emissions from large plants. Whilst emissions in developed cities, including those in the UK, have previously been thought to be comparably well understood, the recent revelations around NOx emissions from diesel engines has highlighted the fact that emission factors established in the laboratory or provided by vehicle manufacturers cannot reliably be translated to real-world conditions (Vaughan et al., 2015). This adds further uncertainty to the emission factors of the Indian vehicle fleet, which are already poorly described. Some compound classes, although precursors for harmful air pollutants, are not currently covered by conventional emission inventory activities. For example, our own work has identified intermediate-chain hydrocarbons to be an important component of diesel emissions (Dunmore et al., 2015), making a significant contribution to the formation of secondary organic aerosol in urban areas and beyond (Gentner et al., 2013; Ots et al., 2016). Similarly, urban emission estimates of NH3 in India are sparse, despite its importance as a precursor for secondary aerosol and the fact that satellite products appear to identify India as the global hotspot of NH3 concentrations (van Damme et al., 2015).
This project seeks to provide a step change in the characterisation, quantification and modelling of air pollutant emissions for Delhi, providing emission estimates at 1 km2 resolution, together with temporal profiles describing their diurnal and annual variability. This emission inventory will build on targeted emission factor measurements in the laboratory and, for vehicle sources, in the real world. The inventory will further be informed by and assessed through independent top-down micrometeorological flux measurements, together with a boundary layer budget technique to quantify emissions averaged over two independent sample areas covering ≈10 km2. A chemistry and transport model will be used to further evaluate the emissions against measurements from the wider research programme as well as existing air quality networks and to quantify the effect the refinement of the emissions has made for the predicted concentrations and, by inference, for human exposure.
DelhiFlux targets Theme 1 (Emissions) of the NERC-MRC-MoES-DBT AQ-in-an-Indian-Megacity programme, whilst WPs 3 and 5 also address aspects of Theme 2 (Processes), and WP1 provides biofuel emission factors particularly relevant for human (indoor) exposure (Theme 3). Only on the basis of a robust sector-resolved present-day emissions inventory will the wider programme be able to explore the efficacy of mitigation options (Theme 4).
Objectives
- To improve the emission factor database for key source types and compounds in Delhi through a combination of lab and field based emission factor measurements, using harmonised instrumentation.
- To compile a state-of-the-art emission inventory for the greater Delhi area at a spatial resolution of 1 km2, together with temporal profiles of the diurnal and seasonal variability.
- To inform and evaluate this emission inventory through direct and independent emission flux (~10 km2), boundary layer enhancement measurements (~100 km2) at the urban scale, as well as concentration measurements in collaboration with other APHH-India projects.
- To apply atmospheric transport modelling to assess the performance of the emission inventory against concentration measurements and quantify the implications of the emissions improvements for air quality indicators.