Assessment of the causal relationship between air quality of Delhi and neighbouring cities using Granger causality network
Introduction: The present work addresses the temporal characteristics of air pollution in Delhi and the surrounding five cities during the years 2019 and 2020. Further, we have addressed the hypothesis whether air pollution of a particular city is affected by its neighboring cities. Materials and...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Tehran University of Medical Sciences
2024-01-01
|
| Series: | Journal of Air Pollution and Health |
| Subjects: | |
| Online Access: | https://japh.tums.ac.ir/index.php/japh/article/view/575 |
| _version_ | 1797359848013168640 |
|---|---|
| author | Sachin Budakoti |
| author_facet | Sachin Budakoti |
| author_sort | Sachin Budakoti |
| collection | DOAJ |
| description |
Introduction: The present work addresses the temporal characteristics of air pollution in Delhi and the surrounding five cities during the years 2019 and 2020. Further, we have addressed the hypothesis whether air pollution of a particular city is affected by its neighboring cities.
Materials and methods: To test the hyopthesis we have used the Granger causality test to detect the causal relationship (feedback) between the air pollution of Delhi and its neighbouring cities. Initially we have checked whether the Air Quality Index (AQI) time series are stationary and integrated of the same order. This involved employing a unit root test, specifically Augmented Dickey Fuller (ADF) test followed by Granger causality test.
Results: From the descriptive statistical analysis, it is observed that there is a significant reduction in the air pollution across six cities during the year 2020. From causality network, it is observed that bidirectional and unidirectional causal links exists for 2019 and only unidirectional causal links exists for 2020. Air pollution of Delhi is strongly influencing the air pollution of Gurugram city in the year 2019 evident from the higher values of Indegree (0.7) for Gurugram city and high value of outdegree (0.85) for Delhi city. Unidirectional causal links observed from Gurugram city in 2020, whereas unidirectional causal links observed from Delhi, Gurugam and Lucknow cities in 2019. Network in 2020, consists of lesser number of causal links (5), in comparison to the network in 2019, that comprises of more number of causal links (12) that indicates the impact of lockdown on air quality due to COVID-19.
Conclusion: Air pollution of highly polluted cities affects the cities with low air pollution. Present work helps the policymakers to implement the effective mitigation and measures to control the air pollution at regional scale.
|
| first_indexed | 2024-03-08T15:30:42Z |
| format | Article |
| id | doaj.art-a5754f7ccb9d4d9caea9b251ce104f70 |
| institution | Directory Open Access Journal |
| issn | 2476-3071 |
| language | English |
| last_indexed | 2024-03-08T15:30:42Z |
| publishDate | 2024-01-01 |
| publisher | Tehran University of Medical Sciences |
| record_format | Article |
| series | Journal of Air Pollution and Health |
| spelling | doaj.art-a5754f7ccb9d4d9caea9b251ce104f702024-01-10T06:10:30ZengTehran University of Medical SciencesJournal of Air Pollution and Health2476-30712024-01-018410.18502/japh.v8i4.14540Assessment of the causal relationship between air quality of Delhi and neighbouring cities using Granger causality networkSachin Budakoti0IIT Bombay Introduction: The present work addresses the temporal characteristics of air pollution in Delhi and the surrounding five cities during the years 2019 and 2020. Further, we have addressed the hypothesis whether air pollution of a particular city is affected by its neighboring cities. Materials and methods: To test the hyopthesis we have used the Granger causality test to detect the causal relationship (feedback) between the air pollution of Delhi and its neighbouring cities. Initially we have checked whether the Air Quality Index (AQI) time series are stationary and integrated of the same order. This involved employing a unit root test, specifically Augmented Dickey Fuller (ADF) test followed by Granger causality test. Results: From the descriptive statistical analysis, it is observed that there is a significant reduction in the air pollution across six cities during the year 2020. From causality network, it is observed that bidirectional and unidirectional causal links exists for 2019 and only unidirectional causal links exists for 2020. Air pollution of Delhi is strongly influencing the air pollution of Gurugram city in the year 2019 evident from the higher values of Indegree (0.7) for Gurugram city and high value of outdegree (0.85) for Delhi city. Unidirectional causal links observed from Gurugram city in 2020, whereas unidirectional causal links observed from Delhi, Gurugam and Lucknow cities in 2019. Network in 2020, consists of lesser number of causal links (5), in comparison to the network in 2019, that comprises of more number of causal links (12) that indicates the impact of lockdown on air quality due to COVID-19. Conclusion: Air pollution of highly polluted cities affects the cities with low air pollution. Present work helps the policymakers to implement the effective mitigation and measures to control the air pollution at regional scale. https://japh.tums.ac.ir/index.php/japh/article/view/575Air quality index (AQI); COVID-19; Granger causality; Indegree; Outdegree |
| spellingShingle | Sachin Budakoti Assessment of the causal relationship between air quality of Delhi and neighbouring cities using Granger causality network Journal of Air Pollution and Health Air quality index (AQI); COVID-19; Granger causality; Indegree; Outdegree |
| title | Assessment of the causal relationship between air quality of Delhi and neighbouring cities using Granger causality network |
| title_full | Assessment of the causal relationship between air quality of Delhi and neighbouring cities using Granger causality network |
| title_fullStr | Assessment of the causal relationship between air quality of Delhi and neighbouring cities using Granger causality network |
| title_full_unstemmed | Assessment of the causal relationship between air quality of Delhi and neighbouring cities using Granger causality network |
| title_short | Assessment of the causal relationship between air quality of Delhi and neighbouring cities using Granger causality network |
| title_sort | assessment of the causal relationship between air quality of delhi and neighbouring cities using granger causality network |
| topic | Air quality index (AQI); COVID-19; Granger causality; Indegree; Outdegree |
| url | https://japh.tums.ac.ir/index.php/japh/article/view/575 |
| work_keys_str_mv | AT sachinbudakoti assessmentofthecausalrelationshipbetweenairqualityofdelhiandneighbouringcitiesusinggrangercausalitynetwork |