Temporal and spatial statistical analysis of ambient air quality of Assam (India)

ABSTRACT

Present paper represents the spatio-temporal variation of air quality and performances of geostatistical tools for the identification of pollutants zone in various districts of Assam (India). Geographic Information System (GIS) and geostatistical analysis were utilized to estimate the spatio-temporal variations (2015–2017) of gaseous and particulate air pollutants. Data of 23 fixed monitoring stations were collected from the Central Pollution Control Board (CPCB). It was observed that SO₂ and NO_x concentrations are the major pollutants to the deterioration of air quality in Assam State. Exploratory data analysis was considered for the determination of spatial and temporal patterns of air pollutants. Air Quality index (AQI) was calculated based on the air pollutants and particulate matter. Radial Basis Function (RBF) interpolation techniques were used to analyze the spatial and temporal variation of air quality in Assam. Cross-validation is applied to evaluate the accuracy of interpolation methods in terms of Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Nash–Sutcliffe Equation (NSE) and Accuracy Factor (ACFT). In 2015, the high value of AQI portrayed in the central and northeast of the state. In 2016, the central and entire east of the study area was recorded the highest value of AQI. In 2017, it was observed that mostly the central part of the state recorded the high value of AQI. The spatio-temporal variation trend of air pollutants provides sound scientific basis for its management and control. This information of air pollution congregation would be valuable for urban planners and decision architects to efficiently administer air quality for health and environmental purposes.

Implications

Guwahati is one of the most polluted cities in India provided a novel evidence to find out the impact of air pollution. Present study has been suffered from several limitations, like (i) the daily or weekly concentration of air pollutants was not gained due to limited monitoring technique, (2) dearth of regular information of PM2.5 collection, which were not regularly connected. Present study is used to estimate the spatio-temporal variations (2015–2017) of gaseous and particulate air pollutants using GIS and spatial statistical approach. Probably, this is the first study to report the spatial and temporal variation of air quality distribution in Assam. Results showed there is a negative impact on the ambient air quality status of Assam. These industries and mining areas contribute significantly to the air pollution in this deltaic region. This district-wise information of air pollution congregation would be valuable for urban planners and decision architects to efficiently administer air quality for health and environmental purposes. The dissimilarity in geographical dissemination of the pollutant concentration has been more helpful in seasonal inevitability. Consequently, a continuous set of data and more parameters can be included to attain more reliable results.

Acknowledgments

We are very much thankful to Central Pollution Control Board, Indian for freely proving air quality data. The project has been funded by Science and Technology Project of Housing and Construction in Jiangsu Province (Grant no. 2018ZD240).

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Gouri Sankar Bhunia

Gouri Sankar Bhunia received his Ph.D. from the University of Calcutta, India, in 2015. His Ph.D. dissertation work focused on disease transmission modelling using geospatial technology. His research interests include health geography, environmental modeling, risk assessment, data mining, urban planning, and information retrieval using geospatial technology. He is an Associate Editor and on the editorial boards of three international journal in Health GIS and Geosciences. Currently, he is involved various Smart City Planning programme in India. He is also working as a visiting faculty in a private university of West Bengal. He has worked as a ‘Resource Scientist’ in Bihar Remote Sensing Application Centre, Patna (Bihar, India). He is the recipient of the Senior Research Fellow (SRF) from Rajendra Memorial Research Institute of Medical Sciences (ICMR, India) and has contributed to multiple research programs kala-azar disease transmission modeling, development of customized GIS software for kala-azar ‘risk’ and ‘non-risk’ area, and entomological study. He has published more than 60 paper in in reputed peer-reviewed national and international journal and three books in Springer.

Ding Ding

Ding Ding is doing Ph.D. from the Department of Architecture and Urban Design, Chinese Culture University, Taipei, Taiwan. He is also working in Jiangsu Baili Curtain Wall & Decoration engineering Co., Ltd., China.