Aerosol Characterization and receptor modEling Group


Understanding Atmospheric Aerosols over India:
Key to Enhancing Air Quality, Improving Human Health, and Mitigating Climate Change

Air pollution is linked with many of the United Nations Sustainable Development Goals (UN SDGs). Reduction of air pollution has clear benefits in improving human and ecosystem health. Further, air pollution and climate change influence one another and global long-term climate targets are linked to the shorter-term SDGs. An essential component of air pollution control is reducing atmospheric aerosol burdens. The challenge with managing and mitigating the adverse impacts of these particles lies in the fact that understanding them at any given time is akin to hitting a moving target. This is so because ambient particles (and their gaseous pre-cursors) are emitted by natural and anthropogenic sources, have several chemical constituents, undergo atmospheric transformations, are influenced by meteorology, have a variety of transport and removal mechanisms, and typically span over six orders of magnitude in size (1 nm - 100 µm aerodynamic diameter) with different morphologies. All of these characteristics result in very large spatio-temporal heterogeneities necessitating location/region specific measurements and modeling.

Our research interests are in aerosol characterization, transformations, and source-specificity of its impacts. Our group works at the interface of aerosol science/technology and atmospheric dynamics, with a focus on coupling air quality management with health and climate end-points. Our interests lie in three broad categories: (i) field and laboratory measurements for air pollutants (ii) modelling to establish quantitative source-receptor relationships, and (iii) spatially resolved near-real time particle characterization to understand aerosol transformations and human health effects.

Considerable progress has been made in the first two categories and we seek to continue building capacity for measurements and modeling including the use and development of novel approaches for aerosol physico-chemical characterization and the integration of in-situ/satellite measurements for use in hybrid receptor/chemical transport models for source apportionment. With reference to the third category, we seek to set-up an air pollution lab on wheels, equipped with several near real-time instruments. Measurements made using this lab will provide chemical composition resolved aerosol size distributions together with optical properties evolving on time-scales of the order of seconds to minutes. This work, in addition to enhancing the understanding of several phenomenon including new particle formation, atmospheric aging and mixing states, will provide inputs that permit the identification of spatio-temporally varying pollutant sources. This information is crucial for designing air pollution control strategies and mitigating health effects, especially in highly polluted locations across India.

Overall, we seek to couple findings from these broad categories of work, collaboratively, with other leading groups across the globe, to deliver solutions for operational air quality management and to provide a framework for enhancing air quality, climate and heath co-benefits. The endeavor is also to provide a data-centric structure for environmental justice actions aimed at protecting the health of disadvantaged population groups. A brief description of the key themes of work we are currently engaged in follow:

1. Aerosol Sampling & Physico-Chemical Analyses

An air quality monitoring station capable of time-integrated aerosol measurements was set-up by my group at Van Vihar National Park in Bhopal to make measurements for over two years, and it continues to operate now on IISER Bhopal campus, to understand local and regional source impacts on air quality. In order to establish robust source-receptor relationship, this effort will now be augmented with co-located measurements of gaseous pollutants (SOx, NOx, volatile organic compounds (VOC), O3 , CO and NH3) for ambient and source samples. To better understand aerosol climate effects, co-located aerosol absorption and scattering measurements have commenced. We will soon measure cloud condensation nuclei (CCN) collaboratively with other research groups.
While we are well set-up to measure trace elements, inorganic ions, organic and elemental carbon and assess particle morphology in bulk aerosol, our results suggest that these measurements will have to be expanded to better separate primary and secondary organic aerosols. Thus, we are developing the capacity to measure thermal-optical carbon fractions and a suite of organic molecular markers/ source tracers for inputs to receptor models. We have commenced collaborative research with IISER Kolkata on obtaining aerosol C isotope (δ13 C) in ambient and source samples, to resolve fossil fuel and biomass combustion sources. Additionally, we seek to leverage the existing research expertise in EES at IISER Bhopal for characterization of aerosol trace element isotopic abundances. In addition to better source apportionment, these measurements will also improve an understanding of what controls isotope fractionation and variability at source and during transport.

2. Quantitative Source-Receptor Relationships

Quantitative source-receptor relationships can be estimated by Receptor Models (RMs) based on measured concentrations of pollutants at the receptor site or by source oriented Chemical Transport Models (CTMs) based on chemistry and transport. Both these approaches have their strengths and weaknesses. CTMs utilize emission inventories of sources, provide high spatio- temporal resolution estimates of air pollutants but are computing intensive and often do not reproduce aerosol observations well due to model processes and input data limitations. RMs on the other hand often require no a-priori source information, derive directly from data collected at the receptor and do not demand high computing power. They however require field work, chemical analyses, and are not applicable for all classes of pollutants.

Despite the limitations mentioned above RMs are an effective air quality management tool in several scenarios. Further, explicit least-squares factor analytic approaches such as Positive Matrix Factorization (PMF) allow conceptual models for various data creation situations to be built. Existing and newly developed expanded RM approaches allow the incorporation of meteorological parameters, source profile and strength constraints along with aerosol mass and chemical composition. We have applied such models to understand the air quality over Bhopal. For example, we not only were we able to perform aerosol mass apportionment but were also able to apportion aerosol scattering to different sources. We continue to develop other integrated and hybrid modeling frameworks that couple RM outputs with various other approaches for source apportionment

3. Aerosol Health Effects

As far as aerosol health effects are concerned, to account for better estimates for spatially continuous PM2.5 over Central India for epidemiological and exposure assessment studies, we have used satellite proxies along with output from global chemical transport models, land use information and road density network over Central India to estimate daily PM2.5 concentrations over Central India. Our study shows that 92.97% population in Central India is living above National Ambient Air Quality Standards (NAAQS) in 2018 -2019.

We are now developing models that will help assess source-specific aerosol health effects. Additionally, we are currently setting up experiments in aerosol lung deposition studies utilizing 3D printed models of the human lung. We will be using the experimental results generated to feed into computational fluid dynamics simulations of aerosol lung transport collaboratively with research groups in Chemical Engineering at IISER Bhopal. The results from these efforts will enhance our understanding of size-selective aerosol lung-surface interactions.