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

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>

Low-power, open-path mobile sensing platform for high-resolution measurements of greenhouse gases and air pollutants

2015 ◽  
Vol 119 (1) ◽  
pp. 153-164 ◽  
Author(s):  
Lei Tao ◽  
Kang Sun ◽  
David J. Miller ◽  
Dan Pan ◽  
Levi M. Golston ◽  
...  
Keyword(s):  
High Resolution ◽  
Greenhouse Gases ◽  
Low Power ◽  
Air Pollutants ◽  
Mobile Sensing ◽  
Open Path ◽  
Sensing Platform

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 Emissions of air pollutants and greenhouse gases over Asian regions during 2000–2008: Regional Emission inventory in ASia (REAS) version 2

2013 ◽  
Vol 13 (4) ◽  
pp. 10049-10123 ◽  
Author(s):  
J. Kurokawa ◽  
T. Ohara ◽  
T. Morikawa ◽  
S. Hanayama ◽  
J.-M. Greet ◽  
...  
Keyword(s):  
Greenhouse Gases ◽  
Growth Rates ◽  
Air Pollutants ◽  
Power Plants ◽  
Emission Inventory ◽  
Mitigation Measures ◽  
Infrastructure Development ◽  
Emission Data ◽  
Large Power ◽  
China And India

Abstract. We have updated the Regional Emission inventory in ASia (REAS) as version 2.1. REAS 2.1 includes most major air pollutants and greenhouse gases from each year during 2000 and 2008 and following areas of Asia: East, Southeast, South, and Central Asia and the Asian part of Russia. Emissions are estimated for each country and region using updated activity data and parameters. Monthly gridded data with a 0.25 × 0.25° resolution are also provided. Asian emissions for each species in 2008 are as follows (with their growth rate from 2000 to 2008): 56.9 Tg (+34%) for SO2, 53.9 Tg (+54%) for NOx, 359.5 Tg (+34%) for CO, 68.5 Tg (+46%) for non-methane volatile organic compounds, 32.8 Tg (+17%) for NH3, 36.4 Tg (+45%) for PM10, 24.7 Tg (+42%) for PM2.5, 3.03 Tg (+35%) for black carbon, 7.72 Tg (+21%) for organic carbon, 182.2 Tg (+32%) for CH4, 5.80 Tg (+18%) for N2O, and 16.7 Pg (+59%) for CO2. By country, China and India were respectively the largest and second largest contributors to Asian emissions. Both countries also had higher growth rates in emissions than others because of their continuous increases in energy consumption, industrial activities, and infrastructure development. In China, emission mitigation measures have been implemented gradually. Emissions of SO2 in China increased from 2000 to 2006 and then began to decrease as flue-gas desulfurization was installed to large power plants. On the other hand, emissions of air pollutants in total East Asia except for China decreased from 2000 to 2008 owing to lower economic growth rates and more effective emission regulations in Japan, South Korea, and Taiwan. Emissions from other regions generally increased from 2000 to 2008, although their relative shares of total Asian emissions are smaller than those of China and India. Tables of annual emissions by country and region broken down by sub-sector and fuel type, and monthly gridded emission data with a resolution of 0.25 × 0.25° for the major sectors are available from the following url: http://www.nies.go.jp/REAS/ .

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

A high-resolution air pollutants emission inventory in 2013 for the Beijing-Tianjin-Hebei region, China

2017 ◽  
Vol 170 ◽  
pp. 156-168 ◽  
Author(s):  
Ji Qi ◽  
Bo Zheng ◽  
Meng Li ◽  
Fang Yu ◽  
Chuchu Chen ◽  
...  
Keyword(s):  
High Resolution ◽  
Air Pollutants ◽  
Emission Inventory ◽  
Pollutants Emission

scholarly journals High-resolution simulation of link-level vehicle emissions and concentrations for air pollutants in a traffic-populated East Asian city

2016 ◽  
Author(s):  
Shaojun Zhang ◽  
Ye Wu ◽  
Ruikun Huang ◽  
Han Yan ◽  
Yali Zheng ◽  
...  
Keyword(s):  
High Resolution ◽  
East Asia ◽  
Air Pollutants ◽  
Vehicle Emissions ◽  
Emission Inventory ◽  
Air Pollutant ◽  
Assessment Tools ◽  
Vehicle Emission ◽  
Temporal And Spatial ◽  
Resolution Simulation

Abstract. Vehicle emissions of air pollutants created substantial environmental impacts on air quality for many traffic-populated cities in East Asia. A high-resolution emission inventory is an irreplaceable tool compared with traditional tools (e.g., registration data based approach) to accurately evaluate real-world traffic dynamics and their environmental burden. In this study, Macao, one of the most populated cities in the world, is selected to demonstrate a high-resolution simulation of vehicular emissions and their contribution to air pollutant concentrations by coupling multi-models. First, traffic volumes by vehicle category on 47 typical roads were investigated during weekdays of 2010 and further applied in a networking demand simulation with the TransCAD model to establish hourly profiles of link-level vehicle counts. Local vehicle driving speed and vehicle age distribution data were also collected in Macao. Second, based on a localized vehicle emission model (e.g., the EMBEV-Macao), this study established a link-based vehicle emission inventory in Macao with high resolution meshed in a temporal and spatial framework. Furthermore, we employed the AERMOD model to map concentrations of CO, NO2 and primary PM2.5 contributed by local vehicle emissions during the weekdays of November 2010. This study has discerned the strong impact of traffic flow dynamics on the temporal and spatial patterns of vehicle emissions, such as a geographic discrepancy of spatial allocation up to 25 % between THC and PM2.5 emissions owing to spatially heterogeneous vehicle-use intensity between motorcycles and diesel fleets. We also identified that local vehicles are a dominant source of ambient NO2 in traffic-populated areas as evidenced by good agreement between AERMOD-simulated data and observed results. Therefore, this paper provides a case study and a solid framework for developing high-resolution environment assessment tools for other vehicle-populated cities in East Asia.

scholarly journals High-resolution inventory of technologies, activities, and emissions of coal-fired power plants in China from 1990 to 2010

2015 ◽  
Vol 15 (23) ◽  
pp. 13299-13317 ◽  
Author(s):  
F. Liu ◽  
Q. Zhang ◽  
D. Tong ◽  
B. Zheng ◽  
M. Li ◽  
...  
Keyword(s):  
High Resolution ◽  
Power Plant ◽  
Power Plants ◽  
Emission Inventory ◽  
Control Measures ◽  
Growth Trend ◽  
Large Power ◽  
Unit Level ◽  
Power Plant Emissions ◽  
Plant Emissions

Abstract. This paper, which focuses on emissions from China's coal-fired power plants during 1990–2010, is the second in a series of papers that aims to develop a high-resolution emission inventory for China. This is the first time that emissions from China's coal-fired power plants were estimated at unit level for a 20-year period. This inventory is constructed from a unit-based database compiled in this study, named the China coal-fired Power plant Emissions Database (CPED), which includes detailed information on the technologies, activity data, operation situation, emission factors, and locations of individual units and supplements with aggregated data where unit-based information is not available. Between 1990 and 2010, compared to a 479 % growth in coal consumption, emissions from China's coal-fired power plants increased by 56, 335, and 442 % for SO2, NOx, and CO2, respectively, and decreased by 23 and 27 % for PM2.5 and PM10 respectively. Driven by the accelerated economic growth, large power plants were constructed throughout the country after 2000, resulting in a dramatic growth in emissions. The growth trend of emissions has been effectively curbed since 2005 due to strengthened emission control measures including the installation of flue gas desulfurization (FGD) systems and the optimization of the generation fleet mix by promoting large units and decommissioning small ones. Compared to previous emission inventories, CPED significantly improved the spatial resolution and temporal profile of the power plant emission inventory in China by extensive use of underlying data at unit level. The new inventory developed in this study will enable a close examination of temporal and spatial variations of power plant emissions in China and will help to improve the performances of chemical transport models by providing more accurate emission data.

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