Articles de revues : « MEGACITY DELHI »

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Das, Chhandita, et Priyanka Tripathi. « Delhi : New Literatures of the Megacity ». AAG Review of Books 9, n^o 4 (2 octobre 2021) : 23–25. http://dx.doi.org/10.1080/2325548x.2021.1960035.

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Tickell, Alex, et Ruvani Ranasinha. « Delhi : New writings on the megacity ». Journal of Postcolonial Writing 54, n^o 3 (4 mai 2018) : 297–306. http://dx.doi.org/10.1080/17449855.2018.1461977.

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Priya, Sharma, et Midha Neha. « Potential Water Balance using Rainwater : An Analysis of Delhi, Megacity in India ». Journal of Environmental Science and Pollution Research 7, n^o 1 (26 février 2021) : 447–50. http://dx.doi.org/10.30799/jespr.211.21070102.

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Delhi is one of the most water stressed cities in the world. This study aimed to explore the potential of Rainwater Harvesting (RWH) as an alternative source of the water supply for Delhi. Mass curve method has been used to understand the feasibility of RWH, indicating that an average roof of 60 m2 in Delhi will collect 3,64,800 L of water in a year for an average family size of five people. The present study assumed that financial constraints, erratic rainfall, unclear legal guidelines, poor public perception, and a lack of commitment from the politicians are possible challenges.

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Singh, Ajit, et Sagnik Dey. « Influence of aerosol composition on visibility in megacity Delhi ». Atmospheric Environment 62 (décembre 2012) : 367–73. http://dx.doi.org/10.1016/j.atmosenv.2012.08.048.

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Balha, Akanksha, Bramha Dutt Vishwakarma, Suneel Pandey et Chander Kumar Singh. « Predicting impact of urbanization on water resources in megacity Delhi ». Remote Sensing Applications : Society and Environment 20 (novembre 2020) : 100361. http://dx.doi.org/10.1016/j.rsase.2020.100361.

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Guttikunda, Sarath K., et Rahul Goel. « Health impacts of particulate pollution in a megacity—Delhi, India ». Environmental Development 6 (avril 2013) : 8–20. http://dx.doi.org/10.1016/j.envdev.2012.12.002.

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Bikkina, Srinivas, August Andersson, Elena N. Kirillova, Henry Holmstrand, Suresh Tiwari, A. K. Srivastava, D. S. Bisht et Örjan Gustafsson. « Air quality in megacity Delhi affected by countryside biomass burning ». Nature Sustainability 2, n^o 3 (25 février 2019) : 200–205. http://dx.doi.org/10.1038/s41893-019-0219-0.

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Rai, Suresh Chand. « Water Management for a Megacity : National Capital Territory of Delhi ». Water Resources Management 25, n^o 9 (17 mars 2011) : 2267–78. http://dx.doi.org/10.1007/s11269-011-9807-0.

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Kumar, S., N. Garg, B. S. Chauhan, C. Gautam, T. Chand, M. P. George et K. S. Jayachandran. « Effect of lockdown amid second wave of COVID-19 on environmental noise scenario of the megacity Delhi, India ». Journal of the Acoustical Society of America 152, n^o 3 (septembre 2022) : 1317–36. http://dx.doi.org/10.1121/10.0013827.

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This paper analyzes the impact of second wave of COVID-19 lockdown on environmental noise levels of 25 sites in Delhi city and compares the noise scenario during pre-lockdown, lockdown, and post-lockdown periods. The study utilized the noise monitoring data acquired from 25 real-time ambient noise monitoring stations, installed by the Delhi Pollution Control Committee, Delhi, at various sites throughout Delhi city. A significant reduction of up to 10 and 3 dB(A) in day and night equivalent noise levels, respectively, had been observed during the lockdown period as compared to the pre-lockdown and post-lockdown periods. The study also revealed that only nine sites, including four industrial and five commercial zone sites, complied with the ambient noise standards during lockdown period, and no silence or residential zone sites complied with the ambient noise standards even during the lockdown period. A roadmap for environmental noise management and control is suggested. The study also reports the community's perception toward the change in acoustic environment of Delhi city during the lockdown period by conducting an environmental noise perception survey. The present study should be helpful in devising noise control action plans and policy interventions for environmental noise management and control in the metropolitan city Delhi, India.

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Yadav, Neha, et Chhemendra Sharma. « Spatial variations of intra-city urban heat island in megacity Delhi ». Sustainable Cities and Society 37 (février 2018) : 298–306. http://dx.doi.org/10.1016/j.scs.2017.11.026.

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Nagpure, Ajay S., Ketki Sharma et Bhola R. Gurjar. « Traffic induced emission estimates and trends (2000–2005) in megacity Delhi ». Urban Climate 4 (juillet 2013) : 61–73. http://dx.doi.org/10.1016/j.uclim.2013.04.005.

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Chowdhury, Sourangsu, Sagnik Dey, Sachchida Nand Tripathi, Gufran Beig, Amit Kumar Mishra et Sumit Sharma. « “Traffic intervention” policy fails to mitigate air pollution in megacity Delhi ». Environmental Science & ; Policy 74 (août 2017) : 8–13. http://dx.doi.org/10.1016/j.envsci.2017.04.018.

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Sharma, S. K., T. K. Mandal, A. Sharma, Srishti Jain et Saraswati. « Carbonaceous Species of PM2.5 in Megacity Delhi, India During 2012–2016 ». Bulletin of Environmental Contamination and Toxicology 100, n^o 5 (7 mars 2018) : 695–701. http://dx.doi.org/10.1007/s00128-018-2313-9.

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Gurjar, B. R., J. A. van Aardenne, J. Lelieveld et M. Mohan. « Emission estimates and trends (1990–2000) for megacity Delhi and implications ». Atmospheric Environment 38, n^o 33 (octobre 2004) : 5663–81. http://dx.doi.org/10.1016/j.atmosenv.2004.05.057.

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Biswal, Akash, Vikas Singh, Leeza Malik, Geetam Tiwari, Khaiwal Ravindra et Suman Mor. « Spatially resolved hourly traffic emission over megacity Delhi using advanced traffic flow data ». Earth System Science Data 15, n^o 2 (8 février 2023) : 661–80. http://dx.doi.org/10.5194/essd-15-661-2023.

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Abstract. This paper presents a bottom-up methodology to estimate multi-pollutant hourly gridded on-road traffic emission using advanced traffic flow and speed data for Delhi. We have used the globally adopted COPERT (Computer Programme to Calculate Emissions from Road Transport) emission functions to calculate the emission as a function of speed for 127 vehicle categories. At first, the traffic volume and congestion (travel time delay) relation is applied to model the 24 h traffic speed and flow for all the major road links of Delhi. The modelled traffic flow and speed shows an anti-correlation behaviour having peak traffic and emissions in morning–evening rush hours. We estimated an annual emission of 1.82 Gg for PM (particulate matter), 0.94 Gg for BC (black carbon), 0.75 Gg for OM (organic matter), 221 Gg for CO (carbon monoxide), 56 Gg for NOx (oxides of nitrogen), 64 Gg for VOC (volatile organic compound), 0.28 Gg for NH3 (ammonia), 0.26 Gg for N2O (nitrous oxide) and 11.38 Gg for CH4 (methane) for 2018 with an uncertainty of 60 %–68 %. The hourly emission variation shows bimodal peaks corresponding to morning and evening rush hours and congestion. The minimum emission rates are estimated in the early morning hours whereas the maximum emissions occurred during the evening hours. Inner Delhi is found to have higher emission flux because of higher road density and relatively lower average speed. Petrol vehicles dominate emission share (>50 %) across all pollutants except PM, BC and NOx, and within them the 2W (two-wheeler motorcycles) are the major contributors. Diesel-fuelled vehicles contribute most of the PM emission. Diesel and CNG (compressed natural gas) vehicles have a substantial contribution in NOx emission. This study provides very detailed spatiotemporal emission maps for megacity Delhi, which can be used in air quality models for developing suitable strategies to reduce the traffic-related pollution. Moreover, the developed methodology is a step forward in developing real-time emission with the growing availability of real-time traffic data. The complete dataset is publicly available on Zenodo at https://doi.org/10.5281/zenodo.6553770 (Singh et al., 2022).

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Roy, Tania. « Non-Renewable Resources : The Poetics and Politics of Vivan Sundaram’s Trash ». Theory, Culture & ; Society 30, n^o 7-8 (7 octobre 2013) : 265–76. http://dx.doi.org/10.1177/0263276413503690.

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This article approaches the recent work of pre-eminent Indian conceptual artist Vivan Sundaram, Trash (2008), as a supplement to dominant representational practices of, and within, the Indian megacity. Re-purposing tropes that motivate both popular and specialist discourses, Sundaram’s recent ensemble rehearses the discursive construction of the megacity-as-waste, by representing an urban totality through elaborate, ordered arrangements of garbage. Working collaboratively with waste-pickers who are members of the non-governmental organization Chintan: Environmental and Research Action Group in New Delhi, the artist sorts, re-assembles and scales the found-objects of Trash into detailed models of a monumental urban landscape. Through a close reading of its formal aspects, the entry examines Trash’s reflection on logics of planned obsolescence which govern both the work as well as fantasies of economic nationalism premised on dualistic images of the global/mega-city.

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Choudhary, Arti, Pradeep Kumar, Anuradha Shukla, Siddhartha Singh et Abhay Kumar Singh. « Characterization of Trace Gases and Green House Gas in Megacity New Delhi ». EPJ Web of Conferences 237 (2020) : 03008. http://dx.doi.org/10.1051/epjconf/202023703008.

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Air pollution and climate change is serious environmental concern due to its visible negative impact on human health. Around 14 Indian cities are placed among top 20 most polluted cities of the world. Trace gas like O3, NOx, CO and CO2 are important pollutants which is associated with human health, climate change and adverse effect on growth and yield of crops. Stratospheric O3 absorbs ultraviolet light and prevents it from reaching to the ground. Greenhouse effect of O3 and CO2 is prominent, O3 in upper troposphere and ranked 3rd for its radiative potential after the carbon dioxide and methane. The amount of O3 generated by photochemical reaction of air pollutants is much larger than the inflow from the stratosphere. This is indicating that trace gases and GHG are generated by anthropogenic activities. It is significantly high in urban area like megacity Delhi as compared to rural area due to excessive anthropogenic activity. The ground level measurements of surface trace gas like O3, NOx, CO and CO2 were conducted in Delhi-Mathura road near traffic intersection for year 2017, January to December. The daily mean concentration of O3, NOx, CO and CO2 were 23.11±17.26ppb (range 58.38 to 6.42ppb), 26.41±4.24ppb (ranges 48.14 to 24.09ppb), 1.56±4.24ppm (ranges 6.6 to 0.69ppm) and 342.54±33.49 (ranges 508.23 to 323.33ppm), respectively. The mixing ratios of O3 were highest of 32ppbv and lowest 17ppbv during the pre-monsoon and monsoon seasons, respectively. While the mixing ratios of both CO and NOx showed highest and lowest values during the winter and monsoon seasons, respectively. The analysis concluded seasonality of O3, CO and NOx were also governed by the long-range transport, mainly with the summer and winter monsoon circulations over the Indian subcontinent. The mixing ratios of CO and NOx show strong correlations during winter and pre-monsoon seasons, while poor correlation in the monsoon season. The mixing ratios of CO and NOx decreased with the increase in wind speed, while O3 tended to increase with the wind speed.

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Guttikunda, Sarath K., et Bhola R. Gurjar. « Role of meteorology in seasonality of air pollution in megacity Delhi, India ». Environmental Monitoring and Assessment 184, n^o 5 (29 juin 2011) : 3199–211. http://dx.doi.org/10.1007/s10661-011-2182-8.

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Gani, Shahzad, Sahil Bhandari, Sarah Seraj, Dongyu S. Wang, Kanan Patel, Prashant Soni, Zainab Arub, Gazala Habib, Lea Hildebrandt Ruiz et Joshua S. Apte. « Submicron aerosol composition in the world's most polluted megacity : the Delhi Aerosol Supersite study ». Atmospheric Chemistry and Physics 19, n^o 10 (22 mai 2019) : 6843–59. http://dx.doi.org/10.5194/acp-19-6843-2019.

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Abstract. Delhi, India, routinely experiences some of the world's highest urban particulate matter concentrations. We established the Delhi Aerosol Supersite study to provide long-term characterization of the ambient submicron aerosol composition in Delhi. Here we report on 1.25 years of highly time-resolved speciated submicron particulate matter (PM1) data, including black carbon (BC) and nonrefractory PM1 (NR-PM1), which we combine to develop a composition-based estimate of PM1 (“C-PM1” = BC + NR-PM1) concentrations. We observed marked seasonal and diurnal variability in the concentration and composition of PM1 owing to the interactions of sources and atmospheric processes. Winter was the most polluted period of the year, with average C-PM1 mass concentrations of ∼210 µg m−3. The monsoon was hot and rainy, consequently making it the least polluted (C-PM1 ∼50 µg m−3) period. Organics constituted more than half of the C-PM1 for all seasons and times of day. While ammonium, chloride, and nitrate each were ∼10 % of the C-PM1 for the cooler months, BC and sulfate contributed ∼5 % each. For the warmer periods, the fractional contribution of BC and sulfate to C-PM1 increased, and the chloride contribution decreased to less than 2 %. The seasonal and diurnal variation in absolute mass loadings were generally consistent with changes in ventilation coefficients, with higher concentrations for periods with unfavorable meteorology – low planetary boundary layer height and low wind speeds. However, the variation in C-PM1 composition was influenced by temporally varying sources, photochemistry, and gas–particle partitioning. During cool periods when wind was from the northwest, episodic hourly averaged chloride concentrations reached 50–100 µg m−3, ranking among the highest chloride concentrations reported anywhere in the world. We estimated the contribution of primary emissions and secondary processes to Delhi's submicron aerosol. Secondary species contributed almost 50 %–70 % of Delhi's C-PM1 mass for the winter and spring months and up to 60 %–80 % for the warmer summer and monsoon months. For the cooler months that had the highest C-PM1 concentrations, the nighttime sources were skewed towards primary sources, while the daytime C-PM1 was dominated by secondary species. Overall, these findings point to the important effects of both primary emissions and more regional atmospheric chemistry on influencing the extreme particle concentrations that impact the Delhi megacity region. Future air quality strategies considering Delhi's situation in both a regional and local context will be more effective than policies targeting only local, primary air pollutants.

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Bhandari, Sahil, Shahzad Gani, Kanan Patel, Dongyu S. Wang, Prashant Soni, Zainab Arub, Gazala Habib, Joshua S. Apte et Lea Hildebrandt Ruiz. « Sources and atmospheric dynamics of organic aerosol in New Delhi, India : insights from receptor modeling ». Atmospheric Chemistry and Physics 20, n^o 2 (22 janvier 2020) : 735–52. http://dx.doi.org/10.5194/acp-20-735-2020.

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Abstract. Delhi, India, is the second most populated city in the world and routinely experiences some of the highest particulate matter concentrations of any megacity on the planet, posing acute challenges to public health (World Health Organization, 2018). However, the current understanding of the sources and dynamics of PM pollution in Delhi is limited. Measurements at the Delhi Aerosol Supersite (DAS) provide long-term chemical characterization of ambient submicron aerosol in Delhi, with near-continuous online measurements of aerosol composition. Here we report on source apportionment based on positive matrix factorization (PMF), conducted on 15 months of highly time-resolved speciated submicron non-refractory PM1 (NR-PM1) between January 2017 and March 2018. We report on seasonal variability across four seasons of 2017 and interannual variability using data from the two winters and springs of 2017 and 2018. We show that a modified tracer-based organic component analysis provides an opportunity for a real-time source apportionment approach for organics in Delhi. Phase equilibrium modeling of aerosols using the extended aerosol inorganics model (E-AIM) predicts equilibrium gas-phase concentrations and allows evaluation of the importance of the ventilation coefficient (VC) and temperature in controlling primary and secondary organic aerosol. We also find that primary aerosol dominates severe air pollution episodes, and secondary aerosol dominates seasonal averages.

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Singh, Vikas, Saroj Kumar Sahu, Amit P. Kesarkar et Akash Biswal. « Estimation of high resolution emissions from road transport sector in a megacity Delhi ». Urban Climate 26 (décembre 2018) : 109–20. http://dx.doi.org/10.1016/j.uclim.2018.08.011.

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Sharma, S. K., Prerita Agarwal, T. K. Mandal, S. G. Karapurkar, D. M. Shenoy, S. K. Peshin, Anshu Gupta et al. « Study on Ambient Air Quality of Megacity Delhi, India During Odd–Even Strategy ». MAPAN 32, n^o 2 (9 janvier 2017) : 155–65. http://dx.doi.org/10.1007/s12647-016-0201-5.

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Gani, Shahzad, Sahil Bhandari, Kanan Patel, Sarah Seraj, Prashant Soni, Zainab Arub, Gazala Habib, Lea Hildebrandt Ruiz et Joshua S. Apte. « Particle number concentrations and size distribution in a polluted megacity : the Delhi Aerosol Supersite study ». Atmospheric Chemistry and Physics 20, n^o 14 (22 juillet 2020) : 8533–49. http://dx.doi.org/10.5194/acp-20-8533-2020.

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Abstract. The Indian national capital, Delhi, routinely experiences some of the world's highest urban particulate matter concentrations. While fine particulate matter (PM2.5) mass concentrations in Delhi are at least an order of magnitude higher than in many western cities, the particle number (PN) concentrations are not similarly elevated. Here we report on 1.25 years of highly time-resolved particle size distribution (PSD) data in the size range of 12–560 nm. We observed that the large number of accumulation mode particles – that constitute most of the PM2.5 mass – also contributed substantially to the PN concentrations. The ultrafine particle (UFP; Dp<100 nm) fraction of PNs was higher during the traffic rush hours and for daytimes of warmer seasons, which is consistent with traffic and nucleation events being major sources of urban UFPs. UFP concentrations were found to be relatively lower during periods with some of the highest mass concentrations. Calculations based on measured PSDs and coagulation theory suggest UFP concentrations are suppressed by a rapid coagulation sink during polluted periods when large concentrations of particles in the accumulation mode result in high surface area concentrations. A smaller accumulation mode for warmer months results in an increased UFP fraction, likely owing to a comparatively smaller coagulation sink. We also see evidence suggestive of nucleation which may also contribute to the increased UFP proportions during the warmer seasons. Even though coagulation does not affect mass concentrations, it can significantly govern PN levels with important health and policy implications. Implications of a strong accumulation mode coagulation sink for future air quality control efforts in Delhi are that a reduction in mass concentration, especially in winter, may not produce a proportional reduction in PN concentrations. Strategies that only target accumulation mode particles (which constitute much of the fine PM2.5 mass) may even lead to an increase in the UFP concentrations as the coagulation sink decreases.

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Jain, Suresh, Preeti Aggarwal, Prateek Sharma et Prashant Kumar. « Vehicular exhaust emissions under current and alternative future policy measures for megacity Delhi, India ». Journal of Transport & ; Health 3, n^o 3 (septembre 2016) : 404–12. http://dx.doi.org/10.1016/j.jth.2016.06.005.

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Parween, M., AL Ramanathan et N. J. Raju. « Waste water management and water quality of river Yamuna in the megacity of Delhi ». International Journal of Environmental Science and Technology 14, n^o 10 (13 mars 2017) : 2109–24. http://dx.doi.org/10.1007/s13762-017-1280-8.

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Babu, Saginela Ravindra, N. Narasimha Rao, S. Vijaya Kumar, Surender Paul et Shantanu Kumar Pani. « Plausible Role of Environmental Factors on COVID-19 Transmission in the Megacity Delhi, India ». Aerosol and Air Quality Research 20, n^o 10 (2020) : 2075–84. http://dx.doi.org/10.4209/aaqr.2020.06.0314.

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Lorenzen, G., C. Sprenger, T. Taute, Asaf Pekdeger, A. Mittal et G. Massmann. « Assessment of the potential for bank filtration in a water-stressed megacity (Delhi, India) ». Environmental Earth Sciences 61, n^o 7 (5 février 2010) : 1419–34. http://dx.doi.org/10.1007/s12665-010-0458-x.

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Mahato, Susanta, Swades Pal et Krishna Gopal Ghosh. « Effect of lockdown amid COVID-19 pandemic on air quality of the megacity Delhi, India ». Science of The Total Environment 730 (août 2020) : 139086. http://dx.doi.org/10.1016/j.scitotenv.2020.139086.

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Mishra, Manisha, et Umesh C. Kulshrestha. « Spatio-Temporal Variation of Atmospheric Gaseous and Particulate Reactive Nitrogen over Northern India ». Current World Environment Special Issue, n^o 1 (16 juin 2021) : 53–67. http://dx.doi.org/10.12944/cwe.16.special-issue1.05.

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The present study reports spatio-temporal distribution pattern of major gaseous (NH3 and NO2) and particulate water soluble total nitrogen (pWSTN) in the ambient air to explore the seasonal variation, major interactions and dominating sources. Considering the major hotspot of atmospheric reactive nitrogen (N) emission, three sites in Indo-Gangetic plain (IGP) were selected based on different local source parameters. Results have shown that gas phase reactive N contribute up to 90% of total analyzed reactive N, where NH3 imparted highest at all the three sites. Prayagraj, a fast growing urban site, has shown highest concentrations of NH3 (72.0 μg m−3), followed by Madhupur rural site (57.7 μg m−3) and Delhi, an urban megacity site (35.8 μg m−3). As compared to previous studies conducted at different sites of IGP, NH3 concentrations were reported to be the highest at the former two sites. However, unlike NH3, NO2 levels were recorded lower at Madhupur (3.1 μg m−3) and Prayagraj (9.4 μg m−3) sites as compared to Delhi (13.4 μg m−3). Similarly, pWSTN concentrations were in the order of Madhupur (6.6 μg m−3) < Prayagraj (10.0 μg m−3) < Delhi (10.1 μg m−3). A strong correlation of NO2 with pWSTN at urban sites has shown the crucial role of NO2 in the formation of nitrogenous aerosols. Significant spatial variation can be attributed to varying local emission sources ranging from microbial emission from improper sewage treatment and open waste dumping at Prayagraj, agricultural activities at Madhupur and vehicular exhausts at Delhi site.

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Garg, S., S. L. Sahdev, N. Mahajan et N. Goel. « Driving through sustainable systems : a Study of Air Quality Index of Delhi during COVID-19 Pandemic ». IOP Conference Series : Earth and Environmental Science 1084, n^o 1 (1 octobre 2022) : 012018. http://dx.doi.org/10.1088/1755-1315/1084/1/012018.

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Abstract The impact of lockdown during covid-19 pandemic on air quality in terms of pollution was investigated in the Delhi/NCR region in this study. The National Air Quality Index (NAQI) uses air quality data for six pollutant measures (PM10, PM2.5, SO2, CO, NO2 and O3) from monitoring stations across the megacity to demonstrate the spatial pattern of air quality before and during the lockdown period due to pandemic. The objective of this study is to investigate the interrelationship among the various parameters the Pearson’s correlation analysis was conducted. The results found were able to demonstrate that during lockdown air quality was significantly improved. It was also found that among other pollutants, level of NO2 and CO have also declined during- lockdown phase. It was observed that during this period of lockdown, the air quality index on maximum number of days was found to be good and satisfactory in Delhi that was the clear indication of an improvement in air quality due to a reduction in pollution and emissions of vehicles and industries. It can be implemented to further work on parameters to improve the air quality in future.

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Jørgensen, Rikke Bramming, Urban Kjellen et Øystein Moen. « Organizational Strategies to Manage Expatriate Worries about Pollution Levels in Megacities ». International Journal of Business and Management 11, n^o 1 (18 décembre 2015) : 39. http://dx.doi.org/10.5539/ijbm.v11n1p39.

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<p style="margin: 0cm 0cm 4pt; text-align: justify; line-height: 12pt; mso-line-height-rule: exactly;">The purpose of this paper is to analyse how a large European infrastructure developer responded to expatriate worries about high outdoor pollution levels in the Indian megacity Delhi. We present an exploratory case study obtained from a three months project with close university/company interaction, both with the head office in Oslo Norway and the Delhi office. Fact assessment showed that pollution levels are high and rising, with significant expected increase in asthma, cardiac diseases and mortality in the winter months. The results show that the employees compare home office environment with the Delhi office, and compare the company actions plans with other companies’ problem solving initiatives. Cost considerations were not important in the development of the response plan but in the implementation phase (specific decisions) and the results further shows that the characteristics of the internal process are important. We present a company response plan to a real-life situation, and this plan could be used by other companies as well. From the company perspective, the paper points towards a challenging issue of similar or dissimilar handling of local employees versus expatriates. Destination characteristics such as air pollution have attained limited focus in expatriate research, and a major contribution of this paper is to present facts and possible solutions as well as comments on future research needs.</p>

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Shukla, Komal, Nikhil Dadheech, Prashant Kumar et Mukesh Khare. « Regression-based flexible models for photochemical air pollutants in the national capital territory of megacity Delhi ». Chemosphere 272 (juin 2021) : 129611. http://dx.doi.org/10.1016/j.chemosphere.2021.129611.

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Mohan, Manju, Shweta Bhati, Archana Sreenivas et Pallavi Marrapu. « Performance Evaluation of AERMOD and ADMS-Urban for Total Suspended Particulate Matter Concentrations in Megacity Delhi ». Aerosol and Air Quality Research 11, n^o 7 (2011) : 883–94. http://dx.doi.org/10.4209/aaqr.2011.05.0065.

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Thamban, Navaneeth Meena, Vipul Lalchandani, Varun Kumar, Suneeti Mishra, Deepika Bhattu, Jay G. Slowik, Andre S. H. Prevot, Rangu Satish, Neeraj Rastogi et Sachchida N. Tripathi. « Evolution of size and composition of fine particulate matter in the Delhi megacity during later winter ». Atmospheric Environment 267 (décembre 2021) : 118752. http://dx.doi.org/10.1016/j.atmosenv.2021.118752.

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Arunkumar, M., et S. Dhanakumar. « Ambient Fine Particulate Matter Pollution Over the Megacity Delhi, India : An Impact Of COVID-19 Lockdown ». Current Science 120, n^o 2 (25 janvier 2021) : 304. http://dx.doi.org/10.18520/cs/v120/i2/304-312.

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Mahato, Susanta, et Swades Pal. « Revisiting air quality during lockdown persuaded by second surge of COVID-19 of megacity Delhi, India ». Urban Climate 41 (janvier 2022) : 101082. http://dx.doi.org/10.1016/j.uclim.2021.101082.

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Kumar, Prashant, B. R. Gurjar, A. S. Nagpure et Roy M. Harrison. « Preliminary Estimates of Nanoparticle Number Emissions from Road Vehicles in Megacity Delhi and Associated Health Impacts ». Environmental Science & ; Technology 45, n^o 13 (juillet 2011) : 5514–21. http://dx.doi.org/10.1021/es2003183.

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Singh, Vikas, Akash Biswal, Amit P. Kesarkar, Suman Mor et Khaiwal Ravindra. « High resolution vehicular PM10 emissions over megacity Delhi : Relative contributions of exhaust and non-exhaust sources ». Science of The Total Environment 699 (janvier 2020) : 134273. http://dx.doi.org/10.1016/j.scitotenv.2019.134273.

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Gupta, Medhavi, et Manju Mohan. « Validation of WRF/Chem model and sensitivity of chemical mechanisms to ozone simulation over megacity Delhi ». Atmospheric Environment 122 (décembre 2015) : 220–29. http://dx.doi.org/10.1016/j.atmosenv.2015.09.039.

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Ghude, Sachin D., S. L. Jain, B. C. Arya, G. Beig, Y. N. Ahammed, Arun Kumar et B. Tyagi. « Ozone in ambient air at a tropical megacity, Delhi : characteristics, trends and cumulative ozone exposure indices ». Journal of Atmospheric Chemistry 60, n^o 3 (juillet 2008) : 237–52. http://dx.doi.org/10.1007/s10874-009-9119-4.

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Mukherjee, Tanmoy, Acharya Asutosh, Satyendra K. Pandey, Lian Yang, Partha P. Gogoi, Annu Panwar et V. Vinoj. « Increasing Potential for Air Pollution over Megacity New Delhi : A Study Based on 2016 Diwali Episode ». Aerosol and Air Quality Research 18, n^o 9 (2018) : 2510–18. http://dx.doi.org/10.4209/aaqr.2017.11.0440.

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42

Mohan, Manju, Subhan K. Pathan, Kolli Narendrareddy, Anurag Kandya et Sucheta Pandey. « Dynamics of Urbanization and Its Impact on Land-Use/Land-Cover : A Case Study of Megacity Delhi ». Journal of Environmental Protection 02, n^o 09 (2011) : 1274–83. http://dx.doi.org/10.4236/jep.2011.29147.

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43

Verma, Nidhi, et S. M. Shiva Nagendra. « Long-term trend analysis of criteria pollutants in megacity of Delhi : Failure or success of control policies ». Urban Climate 45 (septembre 2022) : 101254. http://dx.doi.org/10.1016/j.uclim.2022.101254.

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Joshi, Pallavi, Santu Ghosh, Sagnik Dey, Kuldeep Dixit, Rohit Kumar Choudhary, Harshal Ramesh Salve et Kalpana Balakrishnan. « Impact of acute exposure to ambient PM2.5 on non-trauma all-cause mortality in the megacity Delhi ». Atmospheric Environment 259 (août 2021) : 118548. http://dx.doi.org/10.1016/j.atmosenv.2021.118548.

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Shukla, Komal, Prashant Kumar, Gaurav S. Mann et Mukesh Khare. « Mapping spatial distribution of particulate matter using Kriging and Inverse Distance Weighting at supersites of megacity Delhi ». Sustainable Cities and Society 54 (mars 2020) : 101997. http://dx.doi.org/10.1016/j.scs.2019.101997.

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46

Budhiraja, Bakul, Girish Agrawal et Prasad Pathak. « Urban heat island effect of a polynuclear megacity Delhi – Compactness and thermal evaluation of four sub-cities ». Urban Climate 32 (juin 2020) : 100634. http://dx.doi.org/10.1016/j.uclim.2020.100634.

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Sharma, S. K., T. K. Mandal, A. Sharma, Saraswati et Srishti Jain. « Seasonal and annual trends of carbonaceous species of PM10 over a megacity Delhi, India during 2010–2017 ». Journal of Atmospheric Chemistry 75, n^o 3 (septembre 2018) : 305–18. http://dx.doi.org/10.1007/s10874-018-9379-y.

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Mohan, Manju, et Swagata Payra. « Influence of aerosol spectrum and air pollutants on fog formation in urban environment of megacity Delhi, India ». Environmental Monitoring and Assessment 151, n^o 1-4 (1 avril 2008) : 265–77. http://dx.doi.org/10.1007/s10661-008-0268-8.

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49

Agrawal, Vedant. « Lockdown and COVID 19 : It’s Effect on Behaviour of People and Mental Affection in Corona ». Psychology and Education Journal 58, n^o 2 (4 février 2021) : 795–802. http://dx.doi.org/10.17762/pae.v58i2.1912.

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Résumé :

Amidst the Coronavirus pandemic, a crosscountry lockdown is constrained in India from the outset for three weeks from 24th Walk to fourteenth April 2020 and connected up to third May 2020. As a result of the compelled constraints, tainting level in metropolitan territories the country over fundamentally blocked simply inside couple of days which spellbind discussions regarding lockdown to be the solid elective measures to be completed for controlling air pollution. The current article over the long haul worked on this going to see the air quality circumstance amidst the lockdown time span coherently with exceptional reference to the megacity Delhi. With the guide of air quality data of seven poison limits (PM10, PM2.5, SO2, NO2, CO, O3 and NH3) for 34 checking stations spread over the megacity we have used Public Air Quality File (NAQI) to show the spatial illustration of air quality in pre and during-lockdown stages. The results demonstrated that during lockdown air quality is in a general sense improved. Among the picked poisons, centralizations of PM10 and PM2.5 have seen most noteworthy diminishing (>50%) interestingly with the pre-lockdown stage. Interestingly with the latest year (for instance 2019) during the said time interval the diminishing of PM10 and PM2.5 is as high as about 60% and 39% independently. Among various poisons, NO2 (−52.68%) and CO (−30.35%) level have in like manner diminished during-lockdown stage. About 40% to half improvement in air quality is recognized not long after four days of beginning lockdown. About 54%, 49%, 43%, 37% and 31% diminishing in NAQI have been seen in Focal, Eastern, Southern, Western and Northern bits of the megacity. For the most part, the examination is accepted to be an important improvement to the regulatory bodies since it showed the tainting source control can choke the air quality. Brief such source control in a suitable stretch of time may recover the atmosphere.

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Kuldip Yawale. « The effect of lockdown on the outcomes of COVID-19 ». International Journal of Research in Pharmaceutical Sciences 11, SPL1 (21 décembre 2020) : 1792–97. http://dx.doi.org/10.26452/ijrps.v11ispl1.4197.

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Résumé :

In the midst of the Coronavirus pandemic, a cross country lockdown is forced in India at first for three weeks from 24th Walk to fourteenth April 2020 and reached out up to third May 2020. Because of the constrained limitations, contamination level in urban areas the nation over radically hindered just inside a couple of days which polarize conversations with respect to lockdown to be the strong elective measures to be actualized for controlling air contamination. The current article, in the long run, chipped away at this heading to view the air quality situation in the midst of the lockdown time frame logically with uncommon reference to the megacity Delhi. With the guide of air quality information of seven toxin boundaries (PM10, PM2.5, SO2, NO2, CO, O3 and NH3) for 34 checking stations spread over the megacity, we have utilized Public Air Quality File (NAQI) to show the spatial example of air quality in pre and during-lockdown stages. The outcomes showed that during lockdown air quality is fundamentally improved. Among the chose toxins, centralizations of PM10 and PM2.5 have seen the greatest decrease (>50%) in contrast with the pre-lockdown stage. In contrast with the most recent year (for example 2019) during the said time span, the decrease of PM10 and PM2.5 is as high as about 60% and 39% separately. Among different toxins, NO2 (−52.68%) and CO (−30.35%) level have likewise decreased during-lockdown stage. About 40% to half improvement in air quality is distinguished soon after four days of starting lockdown. About 54%, 49%, 43%, 37% and 31% decrease in NAQI have been seen in Focal, Eastern, Southern, Western and Northern pieces of the megacity. Generally, the investigation is believed to be a valuable enhancement to the administrative bodies since it indicated the contamination source control could constrict the air quality. Brief such source control in an appropriate time span may recuperate the climate.

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