scholarly journals Ambient Air Quality Assessment Using Air Quality Index of Delhi

10.29007/mpmq ◽  
2018 ◽  
Author(s):  
Jaykumar Patel ◽  
Hirva Salvi ◽  
Neha Patel
Keyword(s):  
Air Quality ◽  
Air Pollutants ◽  
Quality Index ◽  
Monsoon Season ◽  
Urban Air Pollution ◽  
Winter Season ◽  
Ambient Air ◽  
Data Interpretation ◽  
Air Quality Index ◽  
Central Pollution Control Board

Urban air pollution is rapidly increasing in Indian cities. It affects the health and mental status of urban dwellers. In the present study, air pollutants data were collected for a year 2016 at 4 locations in Delhi from Central Pollution Control Board. The present study incorporates the analysis of the ambient air in Delhi city using Air Quality Index (AQI). An AQI is proposed for the city of Delhi, India for easy data interpretation and understanding of air quality. The air pollutants analyzed are Sulfur dioxide (SO2), Nitrogen dioxide (NO2) and Particulate matter (PM2.5). The locations selected are Dwarka, R.K Puram, Panjabi Baugh, and Anand Vihar. The AQI were calculated using IND-AQI procedure. It has been observed that AQI’s values of all four locations falls under very poor category. The overall AQI was found under very poor and sever categories. It was found that AQI values were very high during winter season and low during monsoon season. The AQI of PM2.5 was found exceeding the limits for all the months in each location. Thus, it is observed that PM2.5 is critical pollutant at these four locations in Delhi.

Application of nonlinear land use regression models for ambient air pollutants and air quality index

2021 ◽  
Vol 12 (10) ◽  
pp. 101186
Author(s):  
Licheng Zhang ◽  
Xue Tian ◽  
Yuhan Zhao ◽  
Lulu Liu ◽  
Zhiwei Li ◽  
...  
Keyword(s):  
Land Use ◽  
Air Quality ◽  
Air Pollutants ◽  
Regression Models ◽  
Quality Index ◽  
Ambient Air ◽  
Air Quality Index ◽  
Land Use Regression ◽  
Ambient Air Pollutants

scholarly journals A Literature Review on Prediction of Air Quality Index and Forecasting Ambient Air Pollutants using Machine Learning Algorithms

2020 ◽  
Vol 5 (8) ◽  
pp. 1148-1152
Author(s):  
Radhika M. Patil ◽  
Dr. H. T. Dinde ◽  
Sonali. K. Powar
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Air Quality ◽  
Literature Review ◽  
Air Pollutants ◽  
Quality Index ◽  
Ambient Air ◽  
Air Quality Index ◽  
Machine Learning Algorithms ◽  
Ambient Air Pollutants

Day by day the air pollution becomes serious concern in India as well as in overall world. Proper or accurate prediction or forecast of Air Quality or the concentration level of other Ambient air pollutants such as Sulfur Dioxide, Nitrogen Dioxide, Carbon Monoxide, Particulate Matter having diameter less than 10µ, Particulate Matter having diameter less than 2.5µ, Ozone, etc. is very important because impact of these factors on human health becomes severe. This literature review focuses on the various techniques used for prediction or modelling of Air Quality Index (AQI) and forecasting of future concentration levels of pollutants that may cause the air pollution so that governing bodies can take the actions to reduce the pollution.

scholarly journals Analysis of Air Quality Index Distribution of PM10 and PM2.5 Concentrations in Ambient Air of Al-Hillah City, Iraq

2021 ◽  
Vol 1058 (1) ◽  
pp. 012014
Author(s):  
Ruqayah Ali Grmasha ◽  
Shahla N. A. Al-Azzawi ◽  
Osamah J. Al-sareji ◽  
Talal Alardhi ◽  
Mawada Abdellatif ◽  
...  
Keyword(s):  
Air Quality ◽  
Quality Index ◽  
Ambient Air ◽  
Air Quality Index ◽  
Pm10 And Pm2.5 ◽  
Index Distribution

scholarly journals Geomatics Approach for Assessment of respiratory disease Mapping

2014 ◽  
Vol XL-8 ◽  
pp. 205-211 ◽  
Author(s):  
M. Pandey ◽  
V. Singh ◽  
R. C. Vaishya
Keyword(s):  
Fuzzy Logic ◽  
Air Quality ◽  
Human Health ◽  
Quality Index ◽  
Spatial Clustering ◽  
Statistical Significance ◽  
Ambient Air ◽  
Industrial Area ◽  
Air Quality Index ◽  
Statistical Techniques

Air quality is an important subject of relevance in the context of present times because air is the prime resource for sustenance of life especially human health position. Then with the aid of vast sums of data about ambient air quality is generated to know the character of air environment by utilizing technological advancements to know how well or bad the air is. This report supplies a reliable method in assessing the Air Quality Index (AQI) by using fuzzy logic. The fuzzy logic model is designed to predict Air Quality Index (AQI) that report monthly air qualities. With the aid of air quality index we can evaluate the condition of the environment of that area suitability regarding human health position. For appraisal of human health status in industrial area, utilizing information from health survey questionnaire for obtaining a respiratory risk map by applying IDW and Gettis Statistical Techniques. Gettis Statistical Techniques identifies different spatial clustering patterns like hot spots, high risk and cold spots over the entire work area with statistical significance.

scholarly journals Emission from Uyo Main Refuse Dumpsite and Potential Impact on Health

2020 ◽  
pp. 8-13
Author(s):  
S. A. Nta ◽  
M. J. Ayotamuno ◽  
A. H. Igoni ◽  
R. N. Okparanma
Keyword(s):  
Air Quality ◽  
Quality Index ◽  
Ambient Air ◽  
Air Quality Index ◽  
Volatile Organic Carbon ◽  
Highly Sensitive ◽  
Volatile Organic ◽  
Landfill Emissions ◽  
Potential Impact ◽  
Pm2.5 And Pm10

This paper presents potential impact on health of emission from landfill site on Uyo village road, Uyo local government area of Akwa Ibom State, Nigeria. Three sampling points were assessed for particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), sulphur dioxide (SO2), carbon monoxide (CO), hydrogen sulphide H2S, ammonia (NH3), total volatile organic carbon (TVOC) and hydrogen cyanide (HCN) using highly sensitive digital portable meters. The data obtained were expressed in terms of an air quality index. Air quality index indicates that the ambient air can be described as unhealthy for sensitive groups for NO2, unhealthy for SO2 and PM2.5 and moderate for CO, respectively. H2S, NH3, TVOC, HCN, PM10 were not indicated in USEPA air quality standards. It recommended that stringent and proper landfill emissions management together with appropriate burning of wastes should be considered in the study area to ease the risks associated with these pollutants on public health.

Ambient Air Quality Monitoring Studies in Four Specific Location of Tamilnadu, India

2019 ◽  
pp. 677-683
Author(s):  
Mageshkumar P ◽  
Ramesh S ◽  
Angu Senthil K
Keyword(s):  
Air Quality ◽  
Quality Index ◽  
High Volume ◽  
Ambient Air ◽  
Quality Parameters ◽  
Air Quality Index ◽  
Gaseous Pollutants ◽  
Ambient Air Quality ◽  
Air Sampler

A comprehensive study on the air quality was carried out in four locations namely, Tiruchengode Bus Stand, K.S.R College Campus, Pallipalayam Bus Stop and Erode Government Hospital to assess the prevailing quality of air. Ambient air sampling was carried out in four locations using a high volume air sampler and the mass concentrations of PM10, PM2.5, SO2, NOX and CO were measured. The analyzed quality parameters were compared with the values suggested by National Ambient Air Quality Standards (NAAQS). Air quality index was also calculated for the gaseous pollutants and for Particulate Matters. It was found that PM10 concentration exceeds the threshold limits in all the measured locations. The higher vehicular density is one of the main reasons for the higher concentrations of these gaseous pollutants. The air quality index results show that the selected locations come under moderate air pollution.

scholarly journals AMBIENT AIR QUALITY STATUS OF DEWAS INDUSTRIAL AREA OF MADHYA PRADESH, INDIA

2020 ◽  
pp. 4-12
Author(s):  
Reeta Kori ◽  
Alok Saxena ◽  
Harish Wankhade ◽  
Asad Baig ◽  
Ankita Kulshreshtha ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Quality Index ◽  
Ambient Air ◽  
Industrial Area ◽  
Madhya Pradesh ◽  
Air Quality Index ◽  
Particulate Phase ◽  
Ambient Air Quality ◽  
Quality Status

A study has been conducted to assess the ambient air quality status of Dewas industrial area of Madhya Pradesh, India. Total nine locations were selected in Dewas industrial area for ambient air quality monitoring. The eleven pollutants mainly particulate matter less than 10 µ size (PM10), particulate matter less than 2.5 µ size (PM2.5), nitrogen dioxide (NO2), sulphur dioxide (SO2), ozone (O3), ammonia (NH3), benzene (C6H6), benzo (a) Pyrene (BaP) – particulate phase, lead (Pb), Arsenic (As) and Nickel (Ni) were monitored during different four quarters from April 2019 to March 2020. The study revealed that average concentration of gaseous pollutants viz, NO2, SO2, O3, NH3, C6H6 in ambient air were well within standard limits at all selected locations, however concentration of particulate matter (PM10, PM2.5) and heavy metals (Pb & Ni) except As level were found exceeding the National Ambient Air Quality Standards (NAAQS) 2009, India at few monitoring locations. Benzo (a) Pyrene (BaP) –particulate phase in ambient air was not detected during this study. Ambient air Quality Index was found to be moderate (115.56-198.36) at six locations and satisfactory (17.60-94.94) at three locations in Dewas industrial area. Overall ambient Air Quality Index of Dewas industrial area was observed, satisfactory to moderate during this study w.r.t. Air Quality Index. KEY WORDS: Industrial Area, Ambient Air, Air Pollutants, Air Quality Index

scholarly journals Assessment of AIR Quality Index for Delhi region: A comparison between odd-even policy 2019 and Lock Down Period.

2021 ◽  
Author(s):  
Chesta Dhingra
Keyword(s):  
Air Quality ◽  
Wind Speed ◽  
Ambient Temperature ◽  
Quality Index ◽  
Winter Season ◽  
Air Quality Index ◽  
Machine Learning Algorithms ◽  
Accurate Estimation ◽  
Pm10 And Pm2.5 ◽  
The Impact

The aim behind doing this research is to analyse the impact of odd-even policy andlockdown implementation on the air quality index of Delhi by doing the case study on the fourregions Ashok Vihar, Anand Vihar, Dwarka and R.K. Puram. The data is been collected fromDPCC and the main parameters we looked for are PM10 and PM2.5. In which we find out that.highest levels of the pollutants PM10 and PM2.5 been observed during the time of odd-evenpolicy implementation for the year 2019 (04 November 2019- 15 November 2019) whereasduring the lockdown period (23 March 2020-31st August 2020) a great decline in pollutantlevels is been detected. This we further try to correlate with the spatial variations of Delhiregion and able to discern that meteorological parameters (Ambient Temperature, RelativeHumidity, Wind Speed and Solar Radiations) in respect with seasonal variations have a majorinfluence on PM 10 and PM 2.5 levels. During the winter season both the parameters PM10& PM2.5 are touching the peak because of the impact of three major meteorological parametersAmbient Temperature, Wind Speed and Solar Radiation and during the monsoon season airquality conditions are quite favourable because of Ambient Temperature and Wind Speedparameters. In the end we use the ensembled machine learning algorithms like Random Forestand Extra trees regressor to have an accurate estimation of PM2.5 levels for all the four regionsof Delhi and perceived that these ensembled learning techniques are better than other machinelearning algorithms like Neural Networks, Linear regression and SVMs. The Random Forestand Extra trees regressor models give the R2value 0.75 and 0.78 respectively for estimation ofPM2.5; R2 value is a statistical measurement which explains the variance of dependent variablebased on the independent variables of a regression model.

scholarly journals Temporal analysis of air pollutants in the most affected monsoon region

2021 ◽  
Vol 23 (1) ◽  
pp. 229
Author(s):  
Omar Kairan ◽  
Nur Nasehah Zainudin ◽  
Nurul Hasya Mohd Hanafiah ◽  
Nur Emylia Arissa Mohd Jafri ◽  
Fukayhah Fatiha @Suhami ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Air Pollutants ◽  
Monsoon Season ◽  
Secondary Data ◽  
Ambient Air ◽  
Temporal Analysis ◽  
Quality Standard ◽  
Temporal Variations ◽  
Air Pollutant

Air pollution has become an issue at all rates in the world. In Malaysia, there is a system is known as air quality index (API) used to indicate the overall air quality in the country where the air pollutants include or the new ambient air quality standard are sulphur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3) and particulate matter with size less than 10 (PM10). The concentration levels of the air pollutants were said to be affected by the monsoon changes. Therefore, this study is conducted to examine the existence of temporal variations of each air pollutant then identify the differences of each air pollutants concentration in temporal variations. This study uses secondary data where data that has been retrieved from the Department of Environment (DOE) where it is data of air pollution specifically for Kota Bharu, kelantan records. Hierarchical agglomerative cluster analysis was conducted to group monthly air quality. As a conclusion, the study can conclude that the five air pollutants grouped into several different monthly clusters mostly representing the two main monsoon seasons. Mostly air pollutant varied accordingly towards the monsoon season. During the southwestern monsoon, air pollutant concentration tends to higher compare to the northeastern monsoon with mostly due to meteorological factors.

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