In:
Earth System Science Data, Copernicus GmbH, Vol. 15, No. 2 ( 2023-02-08), p. 661-680
Abstract:
Abstract. This paper presents a bottom-up methodology to estimate
multi-pollutant hourly gridded on-road traffic emission using advanced
traffic flow and speed data for Delhi. We have used the globally adopted
COPERT (Computer Programme to Calculate Emissions from Road Transport)
emission functions to calculate the emission as a function of speed for 127
vehicle categories. At first, the traffic volume and congestion (travel time delay) relation is applied to model the 24 h traffic speed and flow for all the major road links of Delhi. The modelled traffic flow and speed shows an anti-correlation behaviour having peak traffic and emissions in
morning–evening rush hours. We estimated an annual emission of 1.82 Gg for PM (particulate matter), 0.94 Gg for BC (black carbon), 0.75 Gg for OM (organic matter), 221 Gg for CO (carbon monoxide), 56 Gg for NOx (oxides of nitrogen), 64 Gg for VOC (volatile organic compound), 0.28 Gg for NH3 (ammonia), 0.26 Gg for N2O (nitrous oxide) and 11.38 Gg for CH4 (methane) for 2018 with an uncertainty of 60 %–68 %. The hourly emission variation shows bimodal peaks corresponding to morning and evening rush hours and congestion. The minimum emission rates are estimated in the early morning hours whereas the maximum emissions occurred during the evening hours. Inner Delhi is found to have higher emission flux because of higher road density and relatively lower average speed. Petrol vehicles dominate emission share (〉50 %) across all pollutants except PM, BC and NOx, and within them the 2W (two-wheeler motorcycles) are the major contributors. Diesel-fuelled vehicles contribute most of the PM emission. Diesel and CNG (compressed natural gas) vehicles have a substantial contribution in NOx emission. This study provides very detailed spatiotemporal emission maps for megacity Delhi, which can be used in air quality models for developing suitable strategies to reduce the traffic-related pollution. Moreover, the developed methodology is a step forward in developing real-time emission with the growing availability of real-time traffic data. The complete dataset is publicly available on Zenodo at
https://doi.org/10.5281/zenodo.6553770 (Singh et al., 2022).
Type of Medium:
Online Resource
ISSN:
1866-3516
DOI:
10.5194/essd-15-661-2023
DOI:
10.5194/essd-15-661-2023-supplement
Language:
English
Publisher:
Copernicus GmbH
Publication Date:
2023
detail.hit.zdb_id:
2475469-9
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