Application of SIM-air modeling tools to assess air quality in Indian cities

2012 ◽  
Vol 62 ◽  
pp. 551-561 ◽  
Author(s):  
Sarath K. Guttikunda ◽  
Puja Jawahar
Keyword(s):  
Air Quality ◽  
Modeling Tools ◽  
Air Modeling ◽  
Indian Cities

scholarly journals Impact of Urban Growth on Air Quality in Indian Cities Using Hierarchical Bayesian Approach

Atmosphere ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 517 ◽  
Author(s):  
Prakhar Misra ◽  
Ryoichi Imasu ◽  
Wataru Takeuchi
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Developing Countries ◽  
Air Quality ◽  
Bayesian Approach ◽  
Urban Growth ◽  
Chemical Transport ◽  
Pm 2.5 ◽  
Brick Kilns ◽  
Indian Cities

Several studies have found rising ambient particulate matter (PM 2.5 ) concentrations in urban areas across developing countries. For setting mitigation policies source-contribution is needed, which is calculated mostly through computationally intensive chemical transport models or manpower intensive source apportionment studies. Data based approach that use remote sensing datasets can help reduce this challenge, specially in developing countries which lack spatially and temporally dense air quality monitoring networks. Our objective was identifying relative contribution of urban emission sources to monthly PM 2.5 ambient concentrations and assessing whether urban expansion can explain rise of PM 2.5 ambient concentration from 2001 to 2015 in 15 Indian cities. We adapted the Intergovernmental Panel on Climate Change’s (IPCC) emission framework in a land use regression (LUR) model to estimate concentrations by statistically modeling the impact of urban growth on aerosol concentrations with the help of remote sensing datasets. Contribution to concentration from six key sources (residential, industrial, commercial, crop fires, brick kiln and vehicles) was estimated by inverse distance weighting of their emissions in the land-use regression model. A hierarchical Bayesian approach was used to account for the random effects due to the heterogeneous emitting sources in the 15 cities. Long-term ambient PM 2.5 concentration from 2001 to 2015, was represented by a indicator R (varying from 0 to 100), decomposed from MODIS (Moderate Resolution Imaging Spectroradiometer) derived AOD (aerosol optical depth) and angstrom exponent datasets. The model was trained on annual-level spatial land-use distribution and technological advancement data and the monthly-level emission activity of 2001 and 2011 over each location to predict monthly R. The results suggest that above the central portion of a city, concentration due to primary PM 2.5 emission is contributed mostly by residential areas (35.0 ± 11.9%), brick kilns (11.7 ± 5.2%) and industries (4.2 ± 2.8%). The model performed moderately for most cities (median correlation for out of time validation was 0.52), especially when assumed changes in seasonal emissions for each source reflected actual seasonal changes in emissions. The results suggest the need for policies focusing on emissions from residential regions and brick kilns. The relative order of the contributions estimated by this study is consistent with other recent studies and a contribution of up to 42.8 ± 14.1% is attributed to the formation of secondary aerosol, long-range transport and unaccounted sources in surrounding regions. The strength of this approach is to be able to estimate the contribution of urban growth to primary aerosols statistically with a relatively low computation cost compared to the more accurate but computationally expensive chemical transport based models. This remote sensing based approach is especially useful in locations without emission inventory.

scholarly journals High Resolution Chemistry Transport Modeling with the On-Line CHIMERE-WRF Model over the French Alps—Analysis of a Feedback of Surface Particulate Matter Concentrations on Mountain Meteorology

Atmosphere ◽  
2020 ◽  
Vol 11 (6) ◽  
pp. 565 ◽  
Author(s):  
Bertrand Bessagnet ◽  
Laurent Menut ◽  
Rémy Lapere ◽  
Florian Couvidat ◽  
Jean-Luc Jaffrezo ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Air Quality ◽  
High Altitude ◽  
Wrf Model ◽  
Synoptic Situation ◽  
Modeling Tools ◽  
Meteorological Model ◽  
French Alps ◽  
On Line

Air pollution is of major concern throughout the world and the use of modeling tools to analyze and forecast the pollutant concentrations in complex orographic areas remains challenging. This work proposes an exhaustive framework to analyze the ability of models to simulate the air quality over the French Alps up to 1.2 km resolution over Grenoble and the Arve Valley. The on-line coupled suite of models CHIMERE-WRF is used in its recent version to analyze a 1 month episode in November–December 2013. As expected, an improved resolution increases the concentrations close to the emission areas and reduced the negative bias for Particulate Matter that is the usual weakness of air quality models. However, the nitrate concentrations seem overestimated with at the same time an overestimation of surface temperature in the morning by WRF. Different WRF settings found in the literature are tested to improve the results, particularly the ability of the meteorological model to simulate the strong thermal inversions in the morning. Wood burning is one of the main contributor of air pollution during the period ranging from 80 to 90% of the Organic Matter. The activation of the on-line coupling has a moderate impact on the background concentrations but surprisingly a change of Particulate Matter (PM) concentrations in the valley will affect more the meteorology nearby high altitude areas than in the valley. This phenomenon is the result of a chain of processes involving the radiative effects and the water vapor column gradients in complex orographic areas. At last, the model confirms that the surrounding glaciers are largely impacted by long range transport of desert dust. However, in wintertime some outbreaks of anthropogenic pollution from the valley when the synoptic situation changes can be advected up to the nearby high altitude areas, then deposited.

scholarly journals General overview: European Integrated project on Aerosol Cloud Climate and Air Quality interactions (EUCAARI) – integrating aerosol research from nano to global scales

2011 ◽  
Vol 11 (6) ◽  
pp. 17941-18160 ◽  
Author(s):  
M. Kulmala ◽  
A. Asmi ◽  
H. K. Lappalainen ◽  
U. Baltensperger ◽  
J.-L. Brenguier ◽  
...  
Keyword(s):  
Air Quality ◽  
Radiative Forcing ◽  
Climate Models ◽  
Global Climate ◽  
Global Scale ◽  
Global Climate Models ◽  
Modeling Tools ◽  
Emissions Inventory ◽  
Airborne Measurements ◽  
Aerosol Cloud

Abstract. In this paper we describe and summarize the main achievements of the European Aerosol Cloud Climate and Air Quality Interactions project (EUCAARI). EUCAARI started on 1 January 2007 and ended on 31 December 2010 leaving a rich legacy including: (a) a comprehensive database with a year of observations of the physical, chemical and optical properties of aerosol particles over Europe, (b) the first comprehensive aerosol measurements in four developing countries, (c) a database of airborne measurements of aerosols and clouds over Europe during May 2008, (d) comprehensive modeling tools to study aerosol processes fron nano to global scale and their effects on climate and air quality. In addition a new Pan-European aerosol emissions inventory was developed and evaluated, a new cluster spectrometer was built and tested in the field and several new aerosol parameterizations and computations modules for chemical transport and global climate models were developed and evaluated. This work enabled EUCAARI to improve our understanding of aerosol radiative forcing and air quality-climate interactions. The EUCAARI results can be utilized in European and global environmental policy to assess the aerosol impacts and the corresponding abatement strategies.

scholarly journals VISUALISING URBAN AIR QUALITY USING AERMOD, CALPUFF AND CFD MODELS: A CRITICAL REVIEW

2020 ◽  
Vol XLIV-4/W3-2020 ◽  
pp. 355-363
Author(s):  
N. Ridzuan ◽  
U. Ujang ◽  
S. Azri ◽  
T. L. Choon
Keyword(s):  
Air Quality ◽  
Urban Area ◽  
Air Pollutants ◽  
Dispersion Model ◽  
Ambient Air ◽  
Urban Air Quality ◽  
Urban Air ◽  
Air Quality Modelling ◽  
Modeling Tools ◽  
Wide Range

Abstract. Degradation of air quality level can affect human’s health especially respiratory and circulatory system. This is because the harmful particles will penetrate into human’s body through exposure to surrounding. The existence of air pollution event is one of the causes for air quality to be low in affected urban area. To monitor this event, a proper management of urban air quality is required to solve and reduce the impact on human and environment. One of the ways to manage urban air quality is by modelling ambient air pollutants. So, this paper reviews three modelling tools which are AERMOD, CALPUFF and CFD in order to visualise the air pollutants in urban area. These three tools have its own capability in modelling the air quality. AERMOD is better to be used in short range dispersion model while CALPUFF is for wide range of dispersion model. Somehow, it is different for CFD model as this model can be used in wide range of application such as air ventilation in clothing and not specifically for air quality modelling only. Because of this, AERMOD and CALPUFF model can be classified in air quality modelling tools group whereas CFD modelling tool is classified into different group namely a non-specific modelling tool group which can be implemented in many fields of study. Earlier air quality researches produced results in two-dimensional (2D) visualization. But there are several of disadvantages for this technique. It cannot provide height information and exact location of pollutants in three-dimensional (3D) as perceived in real world. Moreover, it cannot show a good representation of wind movement throughout the study area. To overcome this problem, the 3D visualization needs to be implemented in the urban air quality study. Thus, this paper intended to give a better understanding on modeling tools with the visualization technique used for the result of performed research.

Classification and transformation of aerosols over selected Indian cities during reduced emissions under COVID-19 lockdown

2021 ◽  
Author(s):  
Pradeep Attri ◽  
Siddhartha Sarkar ◽  
Devleena Mani
Keyword(s):  
Air Quality ◽  
Atmospheric Chemistry ◽  
Indian Subcontinent ◽  
Human Mobility ◽  
Chemical Species ◽  
Anthropogenic Emissions ◽  
Eastern Region ◽  
Vehicular Emissions ◽  
Ambient Concentrations ◽  
Indian Cities

<p>An improved air quality around the globe and over India has been witnessed during the Covid-19 pandemic lockdown. Using surface observations of particulate matter and chemical species data and products from the MERRA-2 reanalysis Ångstrom exponent (α) and aerosol optical depth (AOD), this study documents the changes in atmospheric chemistry over the Indian subcontinent as a result of nationwide lockdown. Two major cities are selected in five Indian regions to cover a large spatial domain. A general shift from fine to coarse particle size, predominantly of dust type, in all regions is observed, which implies a lowered residence time of aerosol in the atmosphere during decreased anthropogenic emissions. For the studied period, Thiruvananthapuram is the cleanest city with marine origin aerosols and an average PM<sub>2.5 </sub>concentration of 7.69±2.40µg/m<sup>3</sup> in the last phase of nationwide lockdown. Over Delhi and Ahmedabad, industrial and vehicular emission play important role in influencing the air quality. The diurnal variation of O<sub>3</sub> and NO<sub>2</sub> and their interdependency on each other vary over space and time, with the sharp nighttime O<sub>3 </sub>peak observed in the southern region for each lockdown phase. Biomass burning type aerosols decrease over the eastern region. In lockdown, NO<sub>2</sub> also shows a significant correlation with population density (R<sup>2</sup> = 0.75; p < 0.05), suggesting human mobility (and accordingly vehicular emissions) as the major contributor to NO<sub>2</sub> concentration in the atmosphere. The results of present study did not find any relationship between the ambient concentrations of pollutants to the cumulative increase in COVID-19 cases. However, there is a significant relationship with O<sub>3</sub> concentrations, and in turn with NO<sub>2</sub>, which can be associated with respiratory ailments.</p>

scholarly journals Investigating the Influence of the Implementation of an Energy Development Plan on Air Quality Using WRF-CAMx Modeling Tools: A Case Study of Shandong Province in China

Atmosphere ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 660 ◽  
Author(s):  
Luo ◽  
He ◽  
Yu ◽  
He ◽  
Zhang ◽  
...  
Keyword(s):  
Air Quality ◽  
Source Apportionment ◽  
Rural Areas ◽  
Emission Reduction ◽  
Fine Particles ◽  
Thermal Power ◽  
Shandong Province ◽  
Atmospheric Environment ◽  
Modeling Tools ◽  
Coal Burning

In this paper, the Weather Research Forecast (WRF) Comprehensive Air Quality Model with Extensions (CAMx) modeling system with the particulate source apportionment technology (PSAT) module was used to study and analyze the spatial and temporal distribution of atmospheric pollutant concentrations and the source apportionment of fine particles (PM2.5) under the base year and an emission reduction scenario in the Shandong province, China. Our results show that industry is the largest contributor of PM2.5. In addition, the contribution of key energy-related industries was as high as 29.5%, with the thermal power industry being the largest individual contributor. In January, the largest contribution came from residents, reaching 41.3%. Moreover, loose coal burning in rural areas contributed up to 19.4% in winter. Our results also show that the emission reduction scenario had palpable effects on the reduction of air pollution. The more the emissions of SO2, NOx, PM2.5, and PM10 were reduced, the more the average concentration was decreased. The implementation of energy conservation and emission reduction policies by industry and resident is conducive to improving the quality of the atmospheric environment. In particular, a comprehensive control of loose coal burning in winter could significantly improve heavy pollution by particulate matter in winter.

scholarly journals REGIONAL-SCALE MODELING OZONE AIR QUALITY OVER THE CONTINENTAL SOUTH EAST ASIA

2009 ◽  
Vol 12 (2) ◽  
pp. 111-120
Author(s):  
Nghiem Hoang Le ◽  
Oanh Thi Kim Nguyen
Keyword(s):  
Air Quality ◽  
East Asia ◽  
Urban Areas ◽  
Regional Scale ◽  
Ground Level ◽  
South East Asia ◽  
Modeling Tools ◽  
Ozone Concentrations ◽  
Ozone Levels ◽  
Monitoring Stations

Long range transport of ozone and its precursors can significantly impact the air quality in downwind regions. The problem of regional transport of ozone has been studied for more than three decades in Europe and U.S but not yet in Southeast Asia. This study investigated the regional scale distribution of tropospheric ozone over the Continental South East Asia Region (CSEA) of Thailand, Burma, Cambodia, Lao and Vietnam. The Models-3 Community Multi-scale Air Quality (CMAQ modeling system, driven by the NCAR/Penn State Fifth-Generation Mesoscale Model (MM5), is used for the purpose. The model domain covers the longitude range from 91'E to 111°E and the latitude range from 5°N to 25°N. Two most recent ozone episodes of March 24-26, 2004 and January 2-4, 2005 were selected which represent the typical meteorological conditions for high ozone concentrations periods of a year. The episode analysis was made based on available data from 10 and 4 monitoring stations located in Bangkok of Thailand and Ho Chi Minh City (HCMC) of Vietnam, respectively. The episodes were characterized with hourly ozone levels above the National Ambient Air Quality Standards of Thailand and Vietnam of 100 ppb at a number of the monitoring stations. The maximum ground level concentrations of ozone for March 2004 and January 2005 episodes reached 173 ppb and 157 ppb, respectively, in the urban plume of the Bangkok Metropolitan Region (BMR). The simulations were performed with 0.5o 0.5° emission input data which was prepared from the regional anthropogenic emission inventory used in the Transport and Chemical Evolution over the Pacific (TRACE-P), and the biogenic emissions obtained from the Global Emissions Inventory Activity (GEIA). The simulated overall picture of ground level ozone concentrations over CSEA domain shows that the concentrations were high at the downwind areas at a considerable distance from large urban areas such as BMR and HCMC. During March 2004 episode the ozone plume moved northeastward following the Southwesterly monsoon and the maximum width of the modeled plume with the ozone above 100 ppb was about 70 km from BMR. For HCMC the ozone plume moved northward and the concentration in the city plume was lower with the width of isopleth of 50ppb of around 40 km. During the Jan 2005 episode the ozone plume moved southwestward following the Northeasterly monsoon and the width of the modeled plume with the ozone concentration above 100 ppb in BMR was 50 km while for HCMC the width of the 40ppb isopleth was about 30 km. The model performance was evaluated on the available observed hourly ozone concentrations. The model system was shown to be able to reproduce the peak ozone levels that occurred during the episodes at these two large urban areas, and capture the day by day variations during the selected episodes. The performance statistics MNBE, NGE, and UPA for the simulated ozone concentrations are within U.S. EPA guidance criteria and are comparable to those reported previous for other regional ozone simulations. It is shown that the MM5/CMAQ system is the suitable modeling tools for ozone prediction over the CSEA.

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