Abstract:- for a[G4] seasonal variation. The observation for quality

Abstract:- Air quality models (also referred to as atmospheric chemical transport models and, in the case of ozone and PM, photochemical models) simulate the atmospheric concentrations and deposition fluxes to the Earth’s surface of air pollutants by solving the mass conservation equations that represent the emissions, transport, dispersion, transformations and removal of those air pollutants and associated chemical species. In the last two decades, various deterministic air quality models have come into being and are being routinely applied for operational forecasting/scenario studies of air pollution concentration in many countries throughout the world. An air quality model or chemical transport model (CTM) is usually driven by a numerical weather forecast model. However, it has been observed that there might arise considerable differences between modeled and measured air pollutant concentrations. The application of data assimilation techniques has the potential to reduce this gap, thus making significant improvements in air quality modeling results. The study is focused on the domain G1 Delhi-NCR and North East England including part of its neighboring areas with a gridG2  resolution of 3 _ 3 km2. Data assimilation will be G3 carried out for the retrospective simulation in post-processing (offline) mode for aG4  seasonal variation. The observation for quality shall be retrieved from air quality data inventoriesG5 

 

Introduction: –   Rapid economic growth in India brought many benefits; environment deteriorated. A large section of Indian population is exposed to poor urban air quality in the cities. Air pollution is one of the most dangerous environmental problems, causing many ill health effects and many deaths in India, as per WHO reports on about 75% population of India is exposed to unsafe air quality. Particulate matter (PM2.5 & PM10) plays an important role in air pollution both indoor and outdoor. As PM are carcinogenic in nature poses a serious threat to human health. As the report says Delhi is one of the most polluted cities in the world and pollution has affected the lives of the people in the city and nearby, pollution has decreased the life expectancy of people living in Delhi NCR area which is an alarming situation. The air pollution and resultant air quality can categorize from the vehicular transportation, industrial and domestic activities. The measurement of air quality is a complicated process; the most of watched pollutants are particulate matter (PM2.5 & PM10), NOx, SOx, Ozone. Due to pollution, the level of PM10 is very high in Indian cities. There are many cities in India which have crossed the critical level of these pollutants. The level of pollution is many times higher than that of official critical value for those pollutant set by World health organization (WHO). There is a need to counter these issues by adopting strategies to improve total air quality. The control of air quality is far away from individual efforts, this has to encounter with policy-making and implementation by public authorities, the government official at regional, national and at international level.

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Research gap: – The air pollution monitoring largely depend on the in-situ monitoring station in the different part of the country. Which does not give us accurate measure of the pollution in the area where monitoring stations are not established. The aim of this research is to fill that gap by adopting scientific approach by using satellite data (e.g. MODIS AOD,) to monitor the pollution concentration at the regional & national level and adopting the same approach to the global level by comparing the result from modeling software and monitoring station data.

Objective:-

1.  Develop a scheme to forecast air quality in the study area (Delhi NCR & North East England) by using WRF-CHEM and OMI.

2. The modelG6  will be compared to two regions (North East England & Delhi NCR) which will allow us to calibrate the model output and applying in the different region. G7 G8 G9 G10 

3. Simulation of regional CTM (Chemical Transport Models)) over Delhi NCR for the pollutant (PM, NOG11 x).

4. Data assimilation for two different regions (Delhi NCR, North East England) on the contrast of different topographic and meteorological condition.

 

 

Methodology: – WRF/Chem is an “online” model in which the air quality component is completely consistent with the meteorological component (Grell et al., 2005). This study uses the Weather Research and Forecasting Model (Skamarock et al., 2008) coupled with Chemistry (Grell et al., 2005; Fast et al., 2006) to simulate the meteorology and chemistry over the model domain (Delhi NCR & North East England). The parent domain which covers the Indian subcontinent with a spatial resolution of 90 km, the next domain is the first nested domain which encompasses North India region with resolution of 30 km and the second nested domain is which encapsulates the area under analysis, i.e. urban air shed over Megacity Delhi-NCR with spatial resolution of 10 km centered at 28.52_N and 77.12_E.The same approach shall be applied to the second study area which is North East England located at  54.9456° N and G12 G13 1.9480° W.G14 G15 G16 

 

 

The expected outcome of the studyG17 G18 : –  G19 G20 G21 

·         A chemical transport model (CTM) to provide air quality analysis and forecast over the study area.G22 

·         This study will focus to overcome gap between in-situ air quality measures and CTM measures

·         It will establish a standard for analysis for air quality in the area where site-specific forecast system is not available.G23 

 

 

 

 

Benefit of the Study:-

·         This study will develop an approach for those areas where these kind studies have not been conducted to understand the present and future air quality.G24 G25 

·         The study will underline the ill effect of poor air quality in developing nations likes of India which is presently riding on high economic growth.