An evaluation and comparison of the various statistical and deterministic techniques for forecasting the concentration of criteria air pollutants

2011 ◽  
Vol 44 (1/2/3/4) ◽  
pp. 96
Author(s):  
Manju Mohan ◽  
Anurag Kandya ◽  
Manish Yadav
Keyword(s):  
Air Pollutants ◽  
Criteria Air Pollutants

Variations of Selected Criteria Air Pollutants During High Particulate Event

2019 ◽  
pp. 1043-1054
Author(s):  
Syabiha Shith ◽  
Leong Weng Woh ◽  
Nor Azam Ramli ◽  
Maisarah Sulaiman ◽  
Nur Baitul Izati Rasli ◽  
...  
Keyword(s):  
Air Pollutants ◽  
Criteria Air Pollutants

scholarly journals Spatial distribution and toxicity potential of gaseous criteria air pollutants in the ambient air around a typical haulage truck stop

2019 ◽  
Vol 1 (4) ◽  
Author(s):  
Mayowa Adeoye Lala ◽  
Olusola Adedayo Adesina ◽  
Lekan Taofeek Popoola ◽  
John Olusoji Owolabi ◽  
Babatunde Oyeleke Oyewale
Keyword(s):  
Spatial Distribution ◽  
Air Pollutants ◽  
Ambient Air ◽  
Criteria Air Pollutants ◽  
Toxicity Potential

Exploratory analysis of the atmospheric levels of BTEX, criteria air pollutants and meteorological parameters in a tropical urban area in Northeastern Brazil

2020 ◽  
Vol 152 ◽  
pp. 104265 ◽  
Author(s):  
Lícia P.S. Cruz ◽  
Daniela F. Santos ◽  
Ivanice F. dos Santos ◽  
Ícaro V.S. Gomes ◽  
Akácia V.S. Santos ◽  
...  
Keyword(s):  
Urban Area ◽  
Air Pollutants ◽  
Meteorological Parameters ◽  
Exploratory Analysis ◽  
Northeastern Brazil ◽  
Criteria Air Pollutants

RELATIONSHIP BETWEEN CRITERIA AIR POLLUTANTS AND PREVALENCE OF ASTHMA IN TAIWAN

Epidemiology ◽  
1998 ◽  
Vol 9 (Supplement) ◽  
pp. S120
Author(s):  
Lin YC ◽  
Guo YL ◽  
Su HJ
Keyword(s):  
Air Pollutants ◽  
Criteria Air Pollutants

Gridded Emission Inventory of Criteria Air Pollutants for National Capital Territory, Delhi

2020 ◽  
Author(s):  
Rahul Chaurasia ◽  
Manju Mohan
Keyword(s):  
Air Pollution ◽  
Spatial Distribution ◽  
High Resolution ◽  
Power Plant ◽  
Population Density ◽  
Air Pollutants ◽  
Emission Inventory ◽  
Road Density ◽  
Criteria Air Pollutants ◽  
National Capital

<p>The megacities of the world are experiencing a punishing level of air pollution where primary sources of emissions are industrial, residential and transportation. Delhi is also no exception and had been worst performing in terms of air quality and air pollution. In this backdrop, a high-resolution emission inventory becomes an essential tool to predict and forecast pollutant concentration along with the assessment of the impact of various government policies. This study aims to prepare a high-resolution gridded emission inventory (1km*1km) of criteria air pollutants (PM10, PM2.5, NO<sub>2</sub>, SO<sub>2 </sub>and CO) for Delhi-NCT (National Capital Territory).  The bottom-up gridded emission inventory has been prepared taking account of population density, land use pattern and socio-economic status. The emission from all the primary sectors has been taken into accounts such as transport, residential burning, industries, power plants, and municipal solid waste burning.  The emissions are estimated using emission factors and activity data for each sector. The emission factor for various fuel type burning is taken from CPCB (Central Pollution Control Board) reports and previous literature. Data corresponding to various sectors such as the amount of fuel consumed, population density, road density, traffic congestion points, industrial location, unauthorized colonies, slums, and total solid waste generation has been acquired from various government bodies, reports, and literature. The result reveals that the total estimated emissions from transportation, industries and domestic sector contribute nearly 72%, 60%, 52% of NOx, SO2 and PM10 emission respectively.  The transport sector has been found as the bulk contributor towards CO and NOx emissions. Domestic sector and Power plant emission have been found to be a bulk contributor of CO and SO2. Later, the spatial distribution of the emission is done using GIS technique (Arc-GIS). For spatial distribution of emission, district-wise population data, road density data, power plant location and digitization of the road network was carried out.</p>

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