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>

Development of high-resolution emission inventory to study the relative contribution of a local power plant to criteria air pollutants and Greenhouse gases

Urban Climate ◽  
2021 ◽  
Vol 38 ◽  
pp. 100897
Author(s):  
Hossein Shahbazi ◽  
Ali Mostafazade Abolmaali ◽  
Hossein Alizadeh ◽  
Hooman Salavati ◽  
Hamidreza Zokaei ◽  
...  
Keyword(s):  
High Resolution ◽  
Power Plant ◽  
Greenhouse Gases ◽  
Air Pollutants ◽  
Emission Inventory ◽  
Local Power ◽  
Criteria Air Pollutants ◽  
Relative Contribution

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

A regional high-resolution emission inventory of primary air pollutants in 2012 for Beijing and the surrounding five provinces of North China

2018 ◽  
Vol 181 ◽  
pp. 20-33 ◽  
Author(s):  
Huanjia Liu ◽  
Bobo Wu ◽  
Shuhan Liu ◽  
Panyang Shao ◽  
Xiangyang Liu ◽  
...  
Keyword(s):  
High Resolution ◽  
Air Pollutants ◽  
North China ◽  
Emission Inventory

scholarly journals Daily variability of air pollution in locations of different population density

2019 ◽  
Vol 100 ◽  
pp. 00011
Author(s):  
Robert Cichowicz ◽  
Artur Stelęgowski
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Population Density ◽  
Air Pollutants ◽  
Daily Maximum ◽  
Air Contaminants ◽  
Daily Variability ◽  
Air Quality Monitoring Stations ◽  
Agricultural Areas ◽  
Daily Changes

The air quality levels vary during a day, especially in inhabited areas. Therefore, it seems reasonable to observe and analyze the occurrence of daily maximum and minimum level of air pollution. In this article, data obtained from automatic air quality monitoring stations located in 5 large, 5 small and medium cities and 5 villages in Poland was analyzed in 2012−2016. Those locations vary, inter alia, depending on number of inhabitants and population density, and for this reason also due to the presence of air contaminants. As an indicator of daily variability air pollution it was determined the ratio of maximum to minimum concentrations of selected air pollutants (NO2 and NOx, and O3, SO2, CO, PM10 and PM2.5, and benzene) in urban and agricultural areas. In winter, the daily changes were bigger in cities than in villages. While in summer, the level of daily variability was similar, irrespective of size of the settlement unit. The biggest daily changes concerned nitrogen oxides, the lowest − sulfur dioxide and dusts.

scholarly journals Spatial and Temporal Variations of Six Criteria Air Pollutants in Fujian Province, China

2018 ◽  
Vol 15 (12) ◽  
pp. 2846 ◽  
Author(s):  
Weicong Fu ◽  
Ziru Chen ◽  
Zhipeng Zhu ◽  
Qunyue Liu ◽  
Cecil van den Bosch ◽  
...  
Keyword(s):  
Air Pollution ◽  
Urban Areas ◽  
Air Pollutants ◽  
Ambient Air ◽  
Temporal Variations ◽  
Air Pollutant ◽  
Spatial And Temporal Variations ◽  
Effective Control ◽  
Fujian Province ◽  
Criteria Air Pollutants

Air pollution has become a critical issue in the urban areas of southeastern China in recent years. A complete understanding of the tempo-spatial characteristics of air pollution can help the public and governmental bodies manage their lives and work better. In this study, data for six criteria air pollutants (including particulate matter (PM2.5, PM10), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2) and ozone (O3)) from 37 sites in nine major cities within Fujian Province, China were collected between January 2015 to December 2016, and analyzed. We analyzed the spatial and temporal variations of these six criteria pollutants, as well as the attainment rates, and identified what were the major pollutants. Our results show that: (1) the two-year mean values of PM2.5 and PM10 exceeded the Chinese National Ambient Air Quality Standard (CAAQS) standard I levels, whereas other air pollutants were below the CAAQS standard I; (2) the six criteria air pollutants show spatial variations (i.e. most air pollutants were higher in the city center areas, followed by suburban areas and exurban areas, except for O3; and the concentrations of PM10, PM2.5, NO2, O3 were higher in coastal cities than in inland cities); (3) seasonal variations and the no attainment rates of air pollutants were found to be higher in cold seasons and lower in warm seasons, except for O3; (4) the most frequently present air pollutant was PM10, with PM2.5 and O3 being the second and third most frequent, respectively; (5) all the air pollutants, except O3, showed positive correlations with each other. These results provide additional information for the effective control of air pollution in the province of Fujian.

scholarly journals Development of a high-resolution emission inventory and its evaluation and application through air quality modeling for Jiangsu Province, China

2017 ◽  
Vol 17 (1) ◽  
pp. 211-233 ◽  
Author(s):  
Yaduan Zhou ◽  
Yu Zhao ◽  
Pan Mao ◽  
Qiang Zhang ◽  
Jie Zhang ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Air Quality ◽  
High Resolution ◽  
Emission Inventory ◽  
Spatial Scales ◽  
Air Quality Modeling ◽  
Nox Emissions ◽  
Quality Modeling ◽  
Emission Estimation ◽  
Southern Jiangsu

Abstract. Improved emission inventories combining detailed source information are crucial for better understanding of the atmospheric chemistry and effectively making emission control policies using air quality simulation, particularly at regional or local scales. With the downscaled inventories directly applied, chemical transport models might not be able to reproduce the authentic evolution of atmospheric pollution processes at small spatial scales. Using the bottom-up approach, a high-resolution emission inventory was developed for Jiangsu China, including SO2, NOx, CO, NH3, volatile organic compounds (VOCs), total suspended particulates (TSP), PM10, PM2.5, black carbon (BC), organic carbon (OC), and CO2. The key parameters relevant to emission estimation for over 6000 industrial sources were investigated, compiled, and revised at plant level based on various data sources and on-site surveys. As a result, the emission fractions of point sources were significantly elevated for most species. The improvement of this provincial inventory was evaluated through comparisons with other inventories at larger spatial scales, using satellite observation and air quality modeling. Compared to the downscaled Multi-resolution Emission Inventory for China (MEIC), the spatial distribution of NOx emissions in our provincial inventory was more consistent with summer tropospheric NO2 VCDs observed from OMI, particularly for the grids with moderate emission levels, implying the improved emission estimation for small and medium industrial plants by this work. Three inventories (national, regional, and provincial by this work) were applied in the Models-3 Community Multi-scale Air Quality (CMAQ) system for southern Jiangsu October 2012, to evaluate the model performances with different emission inputs. The best agreement between available ground observation and simulation was found when the provincial inventory was applied, indicated by the smallest normalized mean bias (NMB) and normalized mean errors (NME) for all the concerned species SO2, NO2, O3, and PM2.5. The result thus implied the advantage of improved emission inventory at local scale for high-resolution air quality modeling. Under the unfavorable meteorology in which horizontal and vertical movement of atmosphere was limited, the simulated SO2 concentrations at downtown Nanjing (the capital city of Jiangsu) using the regional or national inventories were much higher than those observed, implying that the urban emissions were overestimated when economy or population densities were applied to downscale or allocate the emissions. With more accurate spatial distribution of emissions at city level, the simulated concentrations using the provincial inventory were much closer to observation. Sensitivity analysis of PM2.5 and O3 formation was conducted using the improved provincial inventory through the brute force method. Iron and steel plants and cement plants were identified as important contributors to the PM2.5 concentrations in Nanjing. The O3 formation was VOC-limited in southern Jiangsu, and the concentrations were negatively correlated with NOx emissions in urban areas owing to the accumulated NOx from transportation. More evaluations are further suggested for the impacts of speciation and temporal and vertical distribution of emissions on air quality modeling at regional or local scales in China.

A high-resolution emission inventory of air pollutants from primary crop residue burning over Northern India based on VIIRS thermal anomalies

2020 ◽  
Vol 266 ◽  
pp. 115132 ◽  
Author(s):  
Tanbir Singh ◽  
Akash Biswal ◽  
Sahil Mor ◽  
Khaiwal Ravindra ◽  
Vikas Singh ◽  
...  
Keyword(s):  
High Resolution ◽  
Air Pollutants ◽  
Crop Residue ◽  
Emission Inventory ◽  
Thermal Anomalies ◽  
Northern India ◽  
Crop Residue Burning
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