ASAP-Delhi will provide authoritative assessment of the sources, formation process, burden and characteristics of air pollutants in Delhi, and the influence of the surrounding NCR (National Capital Region), with a focus upon particulate matter as the pollutant with the greatest impact upon health, and a philosophy of deriving pollutant source, budget and behaviour insights from direct atmospheric observations. ASAP-Delhi is a self-contained component of the NERC-MRC-MoES-DBT programme Atmospheric Pollution and Human Health in an Indian Megacity, within which complementary observational / modelling / health / policy projects will be delivered.
Background and Rationale
The city of Delhi and the surrounding NCR are home to some 46 million people. Besides Delhi (ca. 18 million), the NCR includes 18 surrounding cities which have witnessed rapid development, industrialisation and urbanisation. Delhi was recently ranked the most polluted city in the world for ambient air pollution by the WHO.1 The most prominent air pollutant is particulate matter (PM), which dominates health impacts at the levels observed in Delhi,2 and exerts further amenity and economic reductions through reduced visibility. The annual mean PM2.5 level in Delhi in 2014 was 153 μg/m3, 15 times the WHO guideline, while daily mean PM2.5 levels exceeded 550 μg/m3 during recent pollution events.3 Approximately 1 in 3 adults in Delhi exhibits respiratory symptoms due to poor air quality, a fraction which surges to about 2 in 3 for children.4 Vehicle-emitted nanoparticles (<100 nm) alone result in over 500 excess deaths per million people in Delhi - with vehicle ownership to increase five-fold over the next 15 years.5 Recent initiatives have increased the coverage and quality of monitoring data in Delhi, but optimal strategies to improve air quality and health require detailed understanding of the characteristics, sources and formation mechanisms for PM - factors where substantial knowledge gaps exist.
Emissions from Delhi are superimposed upon the regional PM loading, which is modified by input from the NCR around Delhi. Background effects include dust input, exacerbated by low relative humidity (RH) in summer enhancing particle re-suspension,6 seasonal biomass burning, and long-range transport of precursor emissions.7 These may be significant: for example, 11 to 69 % of particulate (PM10) loading in Delhi is derived from the surrounding areas depending on the wind direction and season.8 Additional contributions can be expected from the agricultural residue burning in the surrounding states of Punjab and Haryana that are located in the prevailing upwind direction.9 These observations clearly suggest a need for background observations to track input to the Delhi area from long-range transport processes at different times of the year. The NCR hosts much heavy industry (e.g. power generation, brick kilns), light industry which relocated from Delhi following implementation of Indian Supreme Court orders in 1996, and major population centres,10 and has been overlooked in many previous air pollution studies which tend to focus exclusively upon “Delhi”.11 There are no significant recent observational data on the impact of NCR City Cluster emissions upon pollutant loadings in Delhi.10
Primary sources of PM within Delhi include vehicle emissions, road dust, coal combustion, domestic heating and cooking, industrial emissions, open refuse burning and construction.10,12-17 Secondary inorganic aerosol (SIA; primarily sulphates, nitrates and chlorides) was found to contribute 16 % to PM2.5 mass in winter in 2004, but over 40 % in 2014; equivalent summer figures are 20 and 35 % respectively.13,17 Secondary organic aerosol, recently found to comprise 17 – 25 % of PM2.518 may be particularly important given areas of substantial urban vegetation.19 Understanding the budgets of primary and secondary components of PM and their relationship to precursor emission sources is required to accurately predict impacts of air quality policies.
Source contributions to PM have been quantified using multivariate statistical methods, where ambient data and knowledge of contributing sources are used to assign contributions to the observed loading. Most studies have used principal component analysis, diagnostic ratios or enrichment factor methods, with more recent work using positive matrix factorization (PMF) and chemical mass balance (CMB) models.20 Most studies attribute a majority of PM mass to traffic, dust, coal combustion and biomass combustion, although there is a very large variability in the quantitative estimation of source contributions, e.g. vehicles, 7 – 40 %; dust, 17 – 56%; industrial, 4 – 21%.17 Seasonal variations show higher contributions from dust in summer and combustion in winter.13 There are few multi-site studies, which tend to comprise multiple locations within Delhi21 rather than exploiting city / rural background contrasts (or cross-NCR measurements) for source apportionment. Data on chemical characterization of individual sources (prerequisite to CMB analyses) is limited22-24 and most studies omit the organic molecular species of most utility as source markers. A recent critical review20 emphasised the very wide range of conclusions reached regarding PM sources in Delhi, attributed to differences in sampling locations / seasons, and to methodological weaknesses in studies to date. These included identification of chemically implausible sources, failure to apply multiple receptor models to identify systematic weaknesses, lack of application of molecular markers in CMB, failure to disaggregate exhaust vs. non-exhaust vehicle sources, and use of datasets of insufficient size for robust analyses.20
There is therefore a pressing need for a substantive, coherent and coordinated assessment of the sources and formation of Particulate Matter in Delhi. ASAP-Delhi addresses this need, with a philosophy of obtaining insights into pollutant sources and budgets (and hence health impacts) from high quality direct observation - i.e. based upon robust measurement of the species actually present in air at ground level within Delhi where exposure occurs, without dependence upon other data. This will complement, and validate, less direct assessments based upon (e.g.) emission inventories / modelling, or metrics from earth observation, aircraft platforms, or sensor networks.
Overall goal
Provide an authoritative assessment of the sources, formation, characteristics and burden of particulate matter in Delhi, and the surrounding NCR city cluster, with a particular focus on PM2.5 and nanoparticles as the components with the greatest impact upon human health.
Objectives
- Characterise the abundance, chemical and physical properties of particulate matter (PM) in Delhi, and the surrounding NCR city clusters, with a focus on PM2.5 and nanoparticle number.
- Produce source profiles including molecular markers for selected PM sources in Delhi / the NCR via targeted field observations and secondary data analyses.
- Directly quantify the sources of PM2.5 (mass and number) in Delhi and the surrounding NCR city clusters using a variety of independent, established and novel receptor modelling methods.
- Assess the impacts of the NCR City Cluster pollutant burden upon air pollution levels in Delhi (and vice-versa), via novel analyses of existing and new observations.
- Elucidate the formation mechanism(s) of PM during severe pollution episodes in Delhi, to assess the relative importance of primary emissions, secondary formation and regional contributions.
Project Principle Investigators (PIs)
Lead UK PI
Professor William Bloss (University of Birmingham)
Lead Indian PI
Prof Mukesh Khare (IITD - Indian Institute of Technology - Delhi)
UK Principal Investigating Partners
University of Birmingham
University of Surrey
Indian Principal Investigating Partners
Indian Institute of Technology - Delhi (IITD)
National Physical Laboratory (NPL)
Other Project Partners
Central Road Research Institute (CRRI)
University of Texas
INFN, Italy
CAS-China
DRI Reno
Delhi Pollution Control Committee (DPCC)
Visit Partners page for full list of partners and bios.