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What is Polluting Delhi’s Air?Understanding Uncertainties in Emissions Inventories

Ishita Jalan, Hem Himanshu Dholakia
March 2019 | Risks & Adaptation

Citation: Ishita Jalan and Hem H. Dholakia (2019) ‘What is Polluting Delhi’s Air? Understanding Uncertainties in Emissions Inventory’, March.

Overview

Fixing Delhi's air quality requires a deep understanding of the sources that contribute to air pollution. Despite multiple source apportionment studies specific to Delhi NCR, policymakers can’t design an effective action plan due to varying estimates. This study brings clarity on the existent discrepancies and attempts to understand the gaps and opportunities to develop emissions inventory for source apportionment studies.

Our study focuses on five emission inventory studies (CPCB 2010; IIT Kanpur 2015; TERI 2018; SAFAR 2018; Guttikunda 2018) on Delhi NCR. It draws comparisons between emissions inventories for ten sources of air pollution for PM 10 and PM 2.5.

Key Observations

  • Transport, in terms of overall trend, is the largest contributor of PM 2.5 and its contribution ranges from 17.9 per cent (Guttikanda 2018) to 39.2 per cent (SAFAR 2018). However, according to IIT Kanpur (2016), transport is the second largest contributor after road dust while Guttikanda (2018) found industry as the major contributor of PM 2.5, followed by road dust and transport.
  • Road dust is the largest contributor of PM10 and its contribution ranges from 35.6 per cent (TERI 2018) to 65.9 per cent (Guttikanda 2018). This observation is common across all the five studies, owing to the common methodology they used. Yet, with the wide range of estimation for the sector, it is clear that different studies have included other factors in the methodology of developing an emissions inventory.

Sector-wise contribution to PM2.5 (%)

Source: CEEW analysis, 2019

Sector-wise contribution to PM10 (%)

Source: CEEW analysis, 2019

Why Do Emissions Inventories Currently Vary?

  • Study regions chosen
    These five emission inventory studies have considered different geographical boundaries and regions for their analysis. This has led to varying estimates and discrepancies depending on the inclusion/exclusion of peripheral or across the border emissions.
  • Source of air pollution
    The components of the sources of air pollution are determined after mapping the sources of air pollution in the study region. Variation occurs based on the selection by researchers as well as resource constraint causing unreliable estimates.
  • Differences in data collection/sampling
    In the process of data collection, differences could occur due to varying data sources, sampling methods, sampling points, quality of surveys, and seasonal changes during sampling.
  • Understanding of sectoral activity
    Experts often differ in their understanding of the magnitude of activity in a particular sector. This leads to variations in calculating direct emissions, emissions from fuel consumption, and reduction in pollution as a result of pollution abatement technologies.
  • Calculating emissions factor
    Different emission factors have been employed by different studies leading to variation in final estimates for the emissions inventory. Emissions factors are used to estimate the quantity of pollutants released based on data collected.

Key Recommendations

  • Improve data transparency
    Lack of transparency on sampling frame and sample details as well as the lack of a common database is common to all sectors and studies. There is need for data transparency and public datasets to make emission inventories more reliable.
  • Quantify uncertainties
    With no clear understanding on uncertainties, it is difficult to gauge the spread and confidence levels for each emissions inventory estimate. It becomes critical to quantify uncertainties in the studies.
  • Develop multi-year inventories
    The dynamic nature of the issue of air pollution demands a frequent update of source apportionment studies. Developing multi-year inventories will support pollution control agencies to identify pollution sources and design control responses accurately and on time.
  • Evolve common guidelines
    To avoid several existent uncertainties in inventory development, CPCB should design a common set of guidelines for developing inventories. This will help organisations eliminate differences and also effectively scale the effort to other cities in India.
  • Complement source apportionment studies with top-down and bottom-up methods
    Better reconciliation of estimates for source apportionment from dispersion modelling and receptor modelling will help in understanding the details of sources of air pollution.
    Source apportionment using receptor modelling acts as a feedback to the emissions inventory- based source apportionment. Therefore, we need to complement the two methods for the analysis to develop a better understanding on the sources of air pollution.
Transport sector is the largest emitter of PM2.5 particles (17.9 per cent to 39.2 per cent) and road dust is the largest contributor of PM10 particles (35.6 per cent to 65.9 per cent).

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