Process analysis, observations and modelling - Integrated solutions for cleaner air for Delhi


Over 4 years, this integrated proposal aims to reduce uncertainties in air quality prediction and forecasting for Delhi by undertaking process orientated observational and modelling analyses and then to derive sensitivity relationships linking air pollutant concentrations and emission controls. This new knowledge will be critical to formulate effective mitigation solutions for reducing air pollution over Delhi and surrounding regions. PROMOTE brings together a cross-disciplinary team of leading researchers from India and the UK to deliver these aims by addressing three key questions:

  1. What contribution is made by primary and secondary aerosols to the overall air pollution burden in Delhi during summer and winter conditions?
  2. How do the interactions between boundary layer dynamics and long-range transport of air pollution contribute to the local air quality of Delhi?
  3. By taking account of local, urban and regional sources, what are the most effective emission controls for mitigation interventions that will lead to significant reductions in air pollution and exposure levels over Delhi and the wider National Capital Region?

PROMOTE will address Q1 and Q2 by improving the representation of aerosol and boundary layer processes in the existing SAFAR air quality forecasting system. It will extend the capabilities of SAFAR to provide higher resolution predictions of air quality and, through an integrated modelling framework it will examine the sensitivities of air pollutant concentrations to changes in local, urban and regional air pollution contributions to address Q3. PROMOTE will contribute to both Theme 2 (Processes: physical and chemical) and Theme 4 (Mitigations and interventions) of the Air Pollution and Human Health in an Indian Megacity (APHH) programme by cooperating with other APHH projects and provide new knowledge to identify effective mitigation solutions for reducing air pollution in Delhi.

Background and Rationale

Air pollution has been widely recognized as a major global health risk. Given that 1 in every 10 total deaths can be attributed to air pollution (World Bank 2016), there are major implications for the cities of the world. Delhi is one of the largest megacities of the world with a current population of over 18 million. The National Capital Region (NCR), which includes the surrounding conurbations, has a population of 46 million (NCRPB Annual Report, 2011-2012). As part of the Indo-Gangetic Plain (IGP), Delhi is subject to air pollution from a complex mixture of local and regional sources including domestic, traffic, windblown dust, industry, coal based thermal power plants and long-range transport (LRT) from agricultural, biomass and biofuel burning and desert dust from the Thar desert (Bisht et al., 2015) particularly in the pre-monsoon season. The complex orography, synoptic circulation patterns and blocking effects of the Himalayas, all lead to large variations in meteorological conditions including extreme changes in the boundary layer (BL). As a consequence of the complex emissions and meteorology of the region, particulate matter (PM as PM10 and PM2.5), nitrogen oxides (NOx, NO2), sulphur dioxide (SO2), carbon monoxide (CO) and black carbon (BC) all peak during post-monsoon periods and remain elevated during winter making the NCR one of the most polluted areas. Combined with regional contributions from Asian brown haze, PM2.5 and PM10 levels exceed National Ambient Air Quality Standards by a factor of four with exceedances being even higher during winter fog and haze conditions (Tiwari et al., 2014). The annual socio-economic impact attributed to air pollution over Delhi has been estimated at 120000 deaths and a health cost of £110 million (WHO 2012).

A major uncertainty in the prediction of PM is the poor representation of organic aerosols (OA) in air quality models. OA may be of primary (POA) and secondary (SOA) origin and they make an important contribution to PM, exhibiting strong seasonal and diurnal variability (Bisht et al., 2015). The partitioning of pollutants to particles in urban air is driven by complex chemistry and meteorology and may be enhanced greatly in high humidity environments, including fogs. Although techniques to model OA of both biogenic and anthropogenic origin have become available recently, they need to be highly tuned to the environment of interest (Shrivastava et al., 2011).

Existing capability for modelling air quality in Delhi is encapsulated by the System of Air Quality and Weather Forecasting And Research (SAFAR) project which delivers daily air quality forecasts (Beig et al., 2015). Despite these developments, open questions remain regarding the inability of models to replicate chemical processes mediated by fog and the prediction of how LRT affects air pollution over Delhi. Furthermore, high resolution modelling capability is essential to forecast heterogeneities in air pollution concentrations due to the complex mixture of source distributions, chemical transformations and meteorological influences occurring at street, urban and regional scales. Building on innovative multiscale approaches developed in TRANSPHORM and PASODOBLE (FP7) and HiRAE (NERC) (Singh et al., 2014; Stocker et al., 2012), the SAFAR system will be enhanced providing seamless local to regional scale air quality forecasting and assessment capabilities for developing effective mitigation options. To address these issues, PROMOTE will conduct innovative coordinated process based investigations to characterise both local and regional scale influences on air pollution over Delhi. PROMOTE will deliver fresh scientific understanding of aerosol and pollution processes in this subtropical environment for delivering effective mitigation solutions to reduce air pollution and health impacts for the region.


  1. To examine the contribution of secondary aerosols to the air pollution burden in Delhi during distinct meteorological seasons by developing a new representative model scheme for subtropical urban environments (Q1);
  2. To investigate how boundary layer interactions lead to high air pollution events during pre-monsoon and stable winter fog periods affecting Delhi (Q2);
  3. To quantify local, urban and regional contributions to Delhi’s air quality through an improved understanding of aerosols, long-range transport and boundary layer processes (Q2);
  4. To undertake an operational and diagnostic evaluation of the SAFAR air quality forecasting system for Delhi incorporating improved organic aerosol, aerosol-fog and boundary layer process representations (Q1, Q2);
  5. To develop the first coupled local-urban-regional modelling system for predicting high resolution concentrations of PM2.5, PM10, NO2 and other pollutants with source attribution and then to quantify sensitivity response relationships for developing effective mitigation strategies for Delhi (Q2, Q3);
  6. To synthesise and translate the outcomes of PROMOTE with other APHH projects for providing datasets for exposure and health studies and contributing to a roadmap for implementing effective local and regional mitigation strategies to meet current and future compliance and health requirements in Delhi and NCR (Q3).

Through our analysis, we will deliver new knowledge on how local, urban and regional (LRT) sources of air pollution affect Delhi’s air quality. With an improved OA scheme and improved understanding of BL dynamics, sensitivities between air pollutant concentrations and changes in local (e.g. traffic, industrial) and regional (LRT) contributions will be quantified with a new coupled multiscale modelling system for recommending interventions and mitigation options for Delhi.