Literature DB >> 17106780

Preparation and validation of gridded emission inventory of criteria air pollutants and identification of emission hotspots for megacity Delhi.

Manju Mohan1, Lalit Dagar, B R Gurjar.   

Abstract

Delhi is one of the many megacities struggling with punishing levels of pollution from industrial, residential, and transportation sources. Over the years, pollution abatement in Delhi has become an important constituent of state policies. In the past one decade a lot of policies and regulations have been implemented which have had a noticeable effect on pollution levels. In this context, air quality models provide a powerful tool to study the impact of development plans on the expected air pollution levels and thus aid the regulating and planning authorities in decision-making process. In air quality modeling, emissions in the modeling domain at regular interval are one of the most important inputs. From the annual emission data of over a decade (1990-2000), emission inventory is prepared for the megacity Delhi. Four criteria pollutants namely, CO, SO(2), PM, and NO(x) are considered and a gridded emission inventory over Delhi has been prepared taking into account land use pattern, population density, traffic density, industrial areas, etc. A top down approach is used for this purpose. Emission isopleths are drawn and annual emission patterns are discussed mainly for the years 1990, 1996 and 2000. Primary and secondary areas of emission hotspots are identified and emission variations discussed during the study period. Validation of estimated values is desired from the available data. There is a direct relationship of pollution levels and emission strength in a given area. Hence, an attempt has been made to validate the emission inventory for all criteria pollutants by analyzing emissions in various sampling zones with the ambient pollution levels. For validation purpose, the geographical region encompassing the study area (Delhi) has been divided into seven emission zones as per the air quality monitoring stations using Voronoi polygon concept. Dispersion modeling is also used for continuous elevated sources to have the contributing emissions at the ground level to facilitate validation. A good correlation between emission estimates and concentration has been found. Correlation coefficient of 0.82, 0.77, 0.58 and 0.68 for CO, SO(2), PM and NO(x) respectively shows a reasonably satisfactory performance of the present estimates.

Mesh:

Substances:

Year:  2006        PMID: 17106780     DOI: 10.1007/s10661-006-9400-9

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  5 in total

1.  A new method for estimating carbon dioxide emissions from transportation at fine spatial scales.

Authors:  Yuqin Shu; Nina S N Lam; Margaret Reams
Journal:  Environ Res Lett       Date:  2010-11-29       Impact factor: 6.793

2.  Impact of CNG implementation on PAHs concentration in the ambient air of Delhi: a comparative assessment of pre- and post-CNG scenario.

Authors:  P S Khillare; Tripti Agarwal; Vijay Shridhar
Journal:  Environ Monit Assess       Date:  2008-01-23       Impact factor: 2.513

Review 3.  Highlighting Uncertainty and Recommendations for Improvement of Black Carbon Biomass Fuel-Based Emission Inventories in the Indo-Gangetic Plain Region.

Authors:  Sutyajeet I Soneja; James M Tielsch; Subarna K Khatry; Frank C Curriero; Patrick N Breysse
Journal:  Curr Environ Health Rep       Date:  2016-03

4.  Evaluation of NPP-VIIRS Nighttime Light Data for Mapping Global Fossil Fuel Combustion CO2 Emissions: A Comparison with DMSP-OLS Nighttime Light Data.

Authors:  Jinpei Ou; Xiaoping Liu; Xia Li; Meifang Li; Wenkai Li
Journal:  PLoS One       Date:  2015-09-21       Impact factor: 3.240

5.  Measuring Spatial and Temporal PM2.5 Variations in Sacramento, California, Communities Using a Network of Low-Cost Sensors.

Authors:  Anondo Mukherjee; Steven G Brown; Michael C McCarthy; Nathan R Pavlovic; Levi G Stanton; Janice Lam Snyder; Stephen D'Andrea; Hilary R Hafner
Journal:  Sensors (Basel)       Date:  2019-10-29       Impact factor: 3.576

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.