What caused severe air pollution episode of November 2016 in New Delhi?

Abstract. Anthropogenic fossil fuel (FF) combustion, biomass burning (BB) and desert dust are the main sources of air pollutants around the globe but are particularly intensive and important for air quality in Asia in spring. In this study, we investigate the vertical distribution, transport characteristics, source contribution and meteorological feedback of these aerosols in a unique pollution episode that occurred in eastern Asia based on various measurement data and modeling methods. In this episode, the Yangtze River Delta (YRD) in eastern China experienced persistent air pollution, dramatically changing from secondary fine particulate pollution to dust pollution in late March 2015. The Eulerian and Lagrangian models were conducted to investigate the vertical structure, transport characteristics and mechanisms of the multi-scale, multisource and multiday air pollution episode. The regional polluted continental aerosols mainly accumulated near the surface, mixed with dust aerosol downwash from the upper planetary boundary layer (PBL) and middle–lower troposphere (MLT), and further transported by large-scale cold fronts and warm conveyor belts. BB smoke from Southeast Asia was transported by westerlies around the altitude of 3 km from southern China, was further mixed with dust and FF aerosols in eastern China and experienced long-range transport over the Pacific. These pollutants could all be transported to the YRD region and cause a structure of multilayer pollution there. These pollutants could also cause significant feedback with MLT meteorology and then enhance local anthropogenic pollution. This study highlights the importance of intensive vertical measurement in eastern China and the downwind Pacific Ocean and raises the need for quantitative understanding of environmental and climate impacts of these pollution sources.

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MITIGATION OF CROP RESIDUE BURNING INDUCED AIR POLLUTION IN NEW DELHI – A REVIEW

International Journal of Engineering Applied Sciences and Technology ◽

10.33564/ijeast.2020.v05i08.045 ◽

2020 ◽

Vol 5 (8) ◽

Author(s):

Gopalakrishnan Srinivasan ◽

Arumugam Abirami

Keyword(s):

Air Pollution ◽

Crop Residue ◽

Crop Residues ◽

Residue Management ◽

New Delhi ◽

Municipal Solid Wastes ◽

Crop Residue Burning ◽

Short Time ◽

Indian Industries ◽

Stubble Burning

The atmosphere of New Delhi during the months of October to the January next year (every year) remains critical due to factors such as stubble burning in the nearby state of Punjab, air pollution rising out of Diwali fireworks and the smog during December and January. Stubble burning is the intentional incineration of paddy / any other field stubbles by farmers after the harvest. It is usually done to eliminate pests such as rats, crickets and hoppers. The availability of short time between rice harvesting and sowing of wheat is the most important reason for burning of crop residues. Also yield and quality of wheat gets severely affected if there is delay in sowing. Since the time gap is very limited (about 3 – 4 weeks) between rice and wheat, burning of crop residues is preferred since it is the quickest and easiest solution for the farmers. According to reports, New Delhi, Noida and Ghaziabad recorded a peak Air Quality Index (AQI) of around 480 – 490 in the month of November 2019. Health effects of air pollution include respiratory diseases, skin and eye irritation and other ailments. An important factor is shortage of labor contributing to burning of rice straw. Apart from stubble burning, farmers burn wood for domestic cooking, removal of municipal solid wastes and accidental / intentional wildfires. Use of combined harvester – Happy Seeder machine is a profitable and less labour-intensive management of rice residue. Yet many farmers still have the perception that there are no alternative solutions for crop residue management. Besides Happy Seeder machine, there are other machines such as rotavator, reaper binder and no-till seed drill that can be alternatives for crop residue burning. In 2019 – 20, the Punjab government disbursed a certain amount to farmers for not burning stubble as compensation, yet many farmers adopted the stubble burning process. Other measures such as adoption of villages by Confederation of Indian Industries, MoU with institutes for wast

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Analyzing the basic meteorological aspects of a particulate air pollution episode over the industrial area of Northwestern Greece during the November of 2009

Global NEST Journal ◽

10.30955/gnj.001015 ◽

2013 ◽

Vol 15 (2) ◽

pp. 241-253 ◽

Cited By ~ 2

Keyword(s):

Air Pollution ◽

Particulate Matter ◽

Wind Field ◽

Lower Troposphere ◽

Airborne Particulate Matter ◽

Radical Change ◽

Industrial Area ◽

Lower Atmosphere ◽

Horizontal Wind ◽

Pollution Episode

The complex terrain basin of Amyntaio – Ptolemais – Kozani in Western Macedonia of Greece is an area characterized by increased industrial activity and therefore it demands continuous and assiduous environmental monitoring. A prolonged particulate matter air pollution episode was recorded in the area during November 2009. Basic meteorological aspects are analyzed, during the episode period. Daily and hourly PM10 and PM2.5 concentration measurements were used along with surface and lower atmosphere hourly meteorological parameters from 13 measuring stations. The observational data were supported by data produced by the meteorological component of an air pollution model. The overall analysis showed that the episode was primarily the result of the synoptic setting of the middle and lower troposphere. An Omega blocking pattern which gradually transformed to a high-over-low pattern prevailed over central and southern Europe during the episode’s period. The examination of the vertical wind field in the lower troposphere and appropriate stability indices, revealed a continuous absence of significant convection. The weak horizontal wind field near the surface and the reduced mixing height combined with the lack of synoptic forcing resulted in the trapping of the pollutants in the lower troposphere and the recording of increased airborne particulate matter concentrations. The radical change of the synoptic setting in the first days of December marked the end of the episode.

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Understanding Public Response to Air Quality Using Tweet Analysis

Social Media + Society ◽

10.1177/2056305119867656 ◽

2019 ◽

Vol 5 (3) ◽

pp. 205630511986765

Author(s):

Supraja Gurajala ◽

Suresh Dhaniyala ◽

Jeanna N. Matthews

Keyword(s):

Air Pollution ◽

Air Quality ◽

Machine Learning Algorithms ◽

Mitigation Measures ◽

Quality Data ◽

Public Health Issue ◽

New Delhi ◽

Public Response ◽

Pollution Levels ◽

Adverse Health Effects

Poor air quality is recognized as a major risk factor for human health globally. Critical to addressing this important public-health issue is the effective dissemination of air quality data, information about adverse health effects, and the necessary mitigation measures. However, recent studies have shown that even when public get data on air quality and understand its importance, people do not necessarily take actions to protect their health or exhibit pro-environmental behaviors to address the problem. Most existing studies on public attitude and response to air quality are based on offline studies, with a limited number of survey participants and over a limited number of geographical locations. For a larger survey size and a wider set of locations, we collected Twitter data for a period of nearly 2 years and analyzed these data for three major cities: Paris, London, and New Delhi. We identify the three hashtags in each city that best correlate the frequency of tweets with local air quality. Using tweets with these hashtags, we determined that people’s response to air quality across all three cities was nearly identical when considering relative changes in air pollution. Using machine-learning algorithms, we determined that health concerns dominated public response when air quality degraded, with the strongest increase in concern being in New Delhi, where pollution levels are the highest among the three cities studied. The public call for political solutions when air quality worsens is consistent with similar findings with offline surveys in other cities. We also conducted an unsupervised learning analysis to extract topics from tweets in Delhi and studied their evolution over time and with changing air quality. Our analysis helped extract relevant words or features associated with different air quality–related topics such as air pollution policy and health. Also, the topic modeling analysis revealed niche topics associated with sporadic air quality events, such as fireworks during festivals and the air quality impact on an outdoor sport event. Our approach shows that a tweet-based analysis can enable social scientists to probe and survey public response to events such as air quality in a timely fashion and help policy makers respond appropriately.

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