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Добірка наукової літератури з теми "DELHI POLLUTION"

Автор: Grafiati

Опубліковано: 11 вересня 2023

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Статті в журналах з теми "DELHI POLLUTION"

1

Kathuria, Vinish. "Vehicular pollution control in Delhi." Transportation Research Part D: Transport and Environment 7, no. 5 (September 2002): 373–87. http://dx.doi.org/10.1016/s1361-9209(02)00006-8.

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2

Aparnavi, P. "Public Perception Survey on Air Pollution in South Delhi." International Journal of Preventive, Curative & Community Medicine 04, no. 02 (April 7, 2018): 20–27. http://dx.doi.org/10.24321/2454.325x.201812.

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3

Rajpoot, Dr Subhadra, and Devang Pratap Singh. "Emerging Public Health Concern and Air Pollution: A Case Study of Delhi’s Air Pollution Governance." International Journal for Modern Trends in Science and Technology 6, no. 5 (May 26, 2020): 196–201. http://dx.doi.org/10.46501/ijmtst060530.

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Анотація:

Air Pollution is a major concern in today’s scenarios as it is leading to serious health hazards and also retrograding our environment. In recent times there has been a rapid increase in various health factors which has affected lives at a very vast scale. Talking about air pollution in cities like Delhi and other metro cities where air pollution is at its peak. Talking about Delhi which is sometimes also referred as ‘Gas Chamber’ has been a research model for managing risk and controlling air pollution in mounting and towards making Delhi's environment healthy. In this research paper we are trying to understand air pollution governance as a means of risk management. Delhi which follows multi-level governance where public health emergencies in recent times, keeping public trust doctrine as the conceptual basis to look at governance. Delhi traversing as National Capital Territory can be considered as a victim of the Air Pollution and its consequent impacts. The lack of integrated approach in Delhi for risk governance has made this process multifaceted and a challenging task. This study can enlighten us on emergence of public health concerns due to air pollution and its governance, keeping in consideration it has not kept an equal balance even with the backing of legislative measures and intervention of court laws. Due to increasing air pollution levels in the city, right to Life and right to a Healthy Environment are being violated from which the levels of air quality continues to be poor. Lastly for which good governance is required in order to reduce the same at this pandemic.

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4

a, Garima, Abhishek Kumar, Nandita Moitra, and K. S. Jayachandran. "ASSESSMENT OF WATER QUALITY OF RIVER YAMUNA USING POLLUTION INDICES." International Journal of Advanced Research 10, no. 09 (September 30, 2022): 443–51. http://dx.doi.org/10.21474/ijar01/15376.

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The river Yamuna is considered a crucial river in the Indo-Gangetic plain. Having 0.4 Percent of the catchment area in the National Capital Territory (NCT) of Delhi, it feeds about 70 per cent of the population of Delhi and hence, is a major source of dependency for NCT of Delhi. The water quality monitoring of River Yamuna is done by the Delhi Pollution Control Committee (DPCC), Delhi on monthly basis.The objective of the study is to investigate the water quality of the river in the Delhi stretch, for the period 2003-2021. The water quality data has been derived from experimental analysis at DPCC across seven monitoring stations and has been analysed in the present study. It has been revealed that pollutant load from urban local bodies and drains have a stronger impact on the water parameters after the Wazirabad in Delhi, resulting in deteriorated water quality and high-Water Quality Indices (WQI). Water Quality Index (WQI) for the year 2021 indicates that pollution in the river Yamuna increases during monsoon and post-monsoonperiods while during pre-monsoon it remains relatively low.The average pH of the river water ranges from 6 to 8 throughout the year. The comparative data reveals that dissolved oxygen (DO) at most of the sites (except Palla) is nil and, the values of BiochemicalOxygen Demand(BOD) and Chemical Oxygen Demand (COD) have been increasing tremendously, which is due to the unregulated discharge or dumping of sewage water from urban local bodies (ULB) in the river.

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5

Sharma, Akriti, Nishtha Hooda, Nidhi Rani Gupta, and Renu Sharma. "Impact of COVID-19 Lockdown on the Risk of Breast Cancer: A Case Study." IOP Conference Series: Earth and Environmental Science 1032, no. 1 (June 1, 2022): 012004. http://dx.doi.org/10.1088/1755-1315/1032/1/012004.

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Abstract Air pollution is among the world’s major environmental concerns. It remains a major health threat in India and is the leading environmental cause of morbidity in the country. There is considerable evidence that heavy and prolonged exposure to several air contaminants increases the cancer risk. The prevalence of breast cancer in citified environments with high exposure to air pollution has been seen to be elevated. Among various Indian cities, the Delhi cancer registry is having a high breast cancer incidence (28.6%). Owing to the recent and unprecedented global outbreak of coronavirus infectious disease (COVID-19), India is exploring every possible way of controlling its vigorous human transmission. Work from home culture is adopted so as to maintain social distancing during the lockdown. This momentary stoppage is substantially reducing the level of air pollution in several city areas across India dramatically. This paper (i) Overviews the breast cancer and air pollution association; (ii) Compiles the air quality data of Delhi monitored by CPCB during the COVID-19 pandemic lockdown time and compares it with pre-lockdown air quality data; (iii) Explores the reduced threat of breast cancer in Delhi during the nationwide lockdown. This work concluded that Air pollution serves a significant part in breast cancer occurrence. The countrywide lockdown in an attempt to prevent Covid-19 transmission has greatly improved the air quality of various Indian cities like Delhi. Also, with an unprecedented drop in rates of air pollution over Delhi, breast cancer occurrence may also decrease.

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6

Bhadauriya, S., N. Chaudhary, S. Mamatha, and S. S. Ray. "RELATIONSHIP BETWEEN RICE RESIDUE BURNING AND INCREASING AIR POLLUTION IN NORTH-WEST INDIA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (August 22, 2020): 1423–30. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-1423-2020.

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Abstract. Punjab and Haryana are two major Rice-producing states of India. They generate high amount of rice residue every year and these residues are burnt in the months of October and November to clear the fields for the next sowing, i.e. Wheat. Residue burning in these two states is considered to be a major factor for the pollution conditions persisting in Delhi, the capital of the country, during October and November. In this study, we aim to analyse the role of stubble burning on Pollution. The approach aimed at a) Determination of rice straw contingent to open burning in the states of Punjab and Haryana, b) Determine and quantify the air pollutant emissions from rice residue contingent to open burning and c) Compare them with the air pollution of Delhi. Also, in order to analyse the various reasons for the increasing pollution in Delhi, Aerosol Parameters like Aerosol Optical Depth, Angstrom Exponent and Single Scattering Albedo were also studied along with auxiliary data like Temperature, Wind Directions, Wind Trajectories, MODIS Fire Counts and CPCB Pollution Data. In this study, we found that not only residue burnings of Punjab and Haryana, but also dust storms from far beyond these states influence the pollution levels in Delhi, especially in the case of Particulate Matter less than 10.

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7

Lin, Yinzhen, Qile He, Jiatong Liu, and Jingning Wang. "Is Sharing Mobility a Solution to the Air Pollution Problem: Taking Delhi as an Example." Lecture Notes in Education Psychology and Public Media 5, no. 1 (May 17, 2023): 347–53. http://dx.doi.org/10.54254/2753-7048/5/20220563.

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The sharing economy is a social and economic system built around the sharing of resources. Advances in big data and online platforms in recent years have facilitated the growth of the sharing economy, resulted in some successful sharing model featured with sustainability. In this paper, we analyzed the pollution problem and situation of sharing EV market in Delhi to evaluate the feasibility of applying sharing mobility to the city. We refered to primary literatures and reports about the local condition in Delhi. According to our analysis, sharing mobility is not applicable in Delhi due to its detrimental air pollution and inadequate infrastructure.

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8

Parveen, Neha, Lubna Siddiqui, Md Nawaj Sarif, Md Safikul Islam, Nazreen Khanam, and Sk Mohibul. "Industries in Delhi: Air pollution versus respiratory morbidities." Process Safety and Environmental Protection 152 (August 2021): 495–512. http://dx.doi.org/10.1016/j.psep.2021.06.027.

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9

The Lancet Planetary Health. "Government indifference over air pollution crisis in Delhi." Lancet Planetary Health 1, no. 9 (December 2017): e348. http://dx.doi.org/10.1016/s2542-5196(17)30165-1.

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10

Varshney, C. K., and Maneesha Aggarwal. "Ozone pollution in the urban atmosphere of Delhi." Atmospheric Environment. Part B. Urban Atmosphere 26, no. 3 (September 1992): 291–94. http://dx.doi.org/10.1016/0957-1272(92)90004-c.

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Більше джерел

Дисертації з теми "DELHI POLLUTION"

1

Akbar, Sameer. "Particulate air pollution and respiratory morbidity in Delhi, India." Thesis, Imperial College London, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.268012.

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2

Saraswat, Arvind. "Air pollution in New Delhi, India : spatial and temporal patterns of ambient concentrations and human exposure." Thesis, University of British Columbia, 2015. http://hdl.handle.net/2429/56224.

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Urban air pollution is a major health and environmental concern worldwide, and the levels are extremely high in New Delhi, India. This research is focused on the spatial and temporal variability of air pollutant concentrations and its implications for population exposure in New Delhi. Since traffic is considered a significant source of air pollutants in urban environments, robust and multiple linear regression models were used to understand the impact of local traffic flow on ambient concentrations of PM₂.₅, CO, NO and NO₂ at a busy intersection. To elicit the spatiotemporal variability of PM₂.₅ and its constituents (black carbon and ultrafine particles), land use regression (LUR) models were developed. Separate morning and afternoon models were developed using 136 hours (39 sites), 112 hours (26 sites) and 147 hours (39 sites) of PM₂.₅, BC and UFPN data, respectively. Finally, to understand how spatiotemporal variations in PM₂.₅ concentrations impact population exposure, a probabilistic simulation framework was developed to integrate the PM₂.₅ LUR models with time-activity data obtained from a field survey. Regression models explained about 50–80% variability in hourly pollutant concentrations and localized traffic flow explained up to 19% of variability on that scale. Auto-rickshaw and truck flow had a higher influence on NO₂ and PM₂.₅ concentrations, respectively. Independent variables in the LUR models included population density, distance from major roads, and major and minor road lengths in buffers of different radii; measurements from a fixed continuous monitoring site were also used as independent variables in the PM₂.₅ and BC models. The temporal term explained most of the variability (63–77%) in PM₂.₅ and BC models compared to spatial variables (4–16%). Exposure simulations indicate that the estimated annual average PM₂.₅ exposure (109 µg m-³) was high compared to North American or European cities. PM₂.₅ exposures were highest during the winter months (~200 µg m-³) compared to the summer months (~50 µg m-³). Ignoring mobility (i.e. exposure during transport or at work/school locations), as is generally assumed in epidemiologic studies of long-term exposure, underestimated PM₂.₅ population exposure by about 11%.
Science, Faculty of
Resources, Environment and Sustainability (IRES), Institute for
Graduate

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3

Jablonski, Daniel. "AN ASSESSMENT OF CWA SECTION 303(d) PRIORITIZATION OF IMPAIRED WATER BODIES IN ILLINOIS." OpenSIUC, 2011. https://opensiuc.lib.siu.edu/theses/669.

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Water quality has been an issue of concern since the settlement of man and continues to be of great concern today in many locations around the world. In the United States, to address the issues of water pollution, the U.S. Congress passed the Clean Water Act (CWA) in 1972. This study examines the implementation and prioritization of impaired water bodies listed on the Illinois CWA section 303(d) list between 1992 and 2004. This study used the Delphi survey method to obtain opinions from water quality/management experts that reside in the state of Illinois. The goal of this study was to determine if a consensus could be reached amongst water quality experts on the severity of individual water pollutants for a given designated use of a water body by assigning weights, determining if any prioritization trends exist within the current Illinois 303(d) process, as well as identifying any shortcomings of the process and suggesting possible modes of improvement. The survey identified four major shortcomings of Illinois' current approach to water quality management: 1) limited funding and manpower, 2) lack of coordination/monitoring, 3) failure to regulate point sources, and 4) lack of biological monitoring. The survey respondents indicated that the entire state needs attention in terms of water quality improvement and that agriculture and urban runoff are the most important sources of water pollution and water body impairment. They rated the current prioritization system as being between "average" and "good" and identified that development of a weighting scheme could be feasible as long as it received adequate funding and adequate stakeholder support. The measure of consensus among respondents regarding weights for individual pollutants and designated uses varied significantly; however, the overwhelming majority of consensus values improved after participants were asked to revise their original responses in an effort to move towards central tendency in the distribution of assigned ranks.

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4

CHAUHAN, SUDESH KUMAR. "POLLUTION OF RIVER YAMUNA AND ITS CONTROL IN DELHI." Thesis, 2015. http://dspace.dtu.ac.in:8080/jspui/handle/repository/14320.

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Анотація:

The River Yamuna originates from the Yamunotri in the Himalayas. It finally merges with the Ganga and Underground Saraswati at Prayag in Allahabad. Enroute it runs for approximately 22 Km along Delhi. This river quenches the thirst of almost 60% population of Delhi and in return it is cursed to become a practically dead river, which can resemble more than drain than to river. In lower reaches its water is good for nothing. This is alarming situation towards the environment degradation as mentioned above. The objective of this project is to study the quality of River Yamuna, to identify the sources of pollution of River Yamuna and to suggest preventive measures for prevention of pollution in River Yamuna. The most alarming finding of the study is the total lack of dissolved oxygen in the entire reach (from wazirabad barrage to Okhla barrage), biochemical oxygen demand is more than limits at all the locations and unbelievably high coli forms count.
Dr. S.K. SINGH PROFESSOR AND HEAD DEPARTMENT OF CIVIL & ENVIRONMENAL ENGINEERING

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5

Jaiswal, Priyanka. "point and non-point source pollution in delhi watershed:quantification and management." Thesis, 2007. http://localhost:8080/iit/handle/2074/6216.

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SONI, RAJESH. "ESTIMATION OF VEHICULAR POLUTION LOAD IN DELHI AND IT’S CONTROL STRATEGIES." Thesis, 2007. http://dspace.dtu.ac.in:8080/jspui/handle/repository/17475.

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Delhi is a rapidly expanding mega city. Population and vehicle use continue to expand, with vehicles being the principal source of severe air pollution. And yet, vehicle ownership is still fraction of that in industrialized countries. In this work, we attempt to untangle the complexities of Delhi's transport sector, exploring what kind of a future is likely and how it might be altered. We analyzed historical data, estimated vehicle pollution load, and examined strategies to control vehicle pollution. One scenario representing a “business-as-usual” trajectory – is an extrapolation of present trends in Delhi, modified to reflect existing policies and commitments. This scenario results in dramatic increases in vehicle use, translating to about a fourfold increase in transport-related greenhouse gas (GHG) emissions between 2000 and 2020. The second scenario is premised on strong political and institutional leadership to enhance the economic, social, and environmental performance of Delhi's transportation system. Car use drops, and transit and bike use increase, there is major changes in the public transport system with the introduction of metro rail phase I and II. , Govt. is also planning to introduce High Capacity Buses and Mono rail. With the huge investment on road infrastructure and new technology development the pollution level is likely to come down. But even with this aggressive shift toward more environmental friendly transportation, GHG emissions may be more than double in the 20-year period. We observe that under any plausible scenario greenhouse gases will soar, but that the lower greenhouse gas path leads to far fewer emissions and much lower transport and energy costs.

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7

Khanna, Isha. "Chemical characterization and source apportionment pf pm 2.5 at kerbside locations in Delhi city." Thesis, 2017. http://localhost:8080/iit/handle/2074/7471.

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8

Singh, Gaurav. "Role of aerosols on cardiopulmonary functions of economically different groups of megacity Delhi and a town Hamirpur Himachal Pradesh." Thesis, 2018. http://eprint.iitd.ac.in:80//handle/2074/7947.

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9

KUMAR, AMRIT. "MAPPING OF URBAN TRAFFIC EMISSION AND ASSOCIATED HEALTH RISKS IN DELHI." Thesis, 2018. http://dspace.dtu.ac.in:8080/jspui/handle/repository/16503.

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Анотація:

The rapid urbanization and large-scale motorization inevitably bring challenges to the urban environment. Almost all large and mid-sized cities in India are facing problems of population increase, urban sprawl, traffic congestion, air pollution, and high-energy consumption. The profiling of a modern city is of huge importance to its competitiveness in the national and international context. In Delhi, however, mass motorization was introduced spontaneously because of rapid economic liberalization over the past two decades within the framework of a low-income country. Further, this megacity has heterogeneous kind of population, with varying socio-economic background and income levels. This mixed profile of the city is reflected in the different fleet composition across the transport corridors. Air pollution is considered as one of the prominent killer to human beings. Polluted air was responsible for 6.4 million deaths worldwide in 2015 out of which 2.8 million were contributed by household air pollution whereas 3.6 million from ambient air pollution and it is projected that by 2060, it may be increased to the figure of 6 to 9 million deaths per year. Non-communicable diseases account for 70% of air pollution deaths, and air pollution is a major, insufficiently appreciated cause of non communicable disease. Worldwide, air pollution was responsible for 24% of ischemic heart disease deaths, 21% of stroke deaths, 23% of lung cancer deaths and 19% of all cardiovascular deaths in 2015. Worldwide, Cardiovascular diseases are known to play major role for mortality and morbidity in South Asia between 1990 and 2020 and are currently a leading health problem in urban India too with 35% of total deaths due to health conditions. Vehicle emissions are not only degrading the ambient air quality of the atmosphere but also responsible for the morbidity and mortality cases of drivers, viii commuters and individuals living near major roadways. Study reported that the major health problem occurred on account of time travelled in traffic areas, the exposure duration of rush hours, and congestion of the traffic. The present research work is to encompass the assessment of concentration of different vehicular pollutants at different road transport corridors along with the estimation of the emission of pollutants from vehicles at selected transport corridors. In addition to this, GIS maps of identified pollutants namely CO, PM10, PM2.5, NOx, SOx and C6H6 were developed to estimate the spatial extent of impacts of these harmful pollutants. The questionnaire survey has also been undertaken to correlate public health issues with atmospheric pollutants if any, and providing suggestions and mitigation strategies for the better management of public health with reference to various pollutants. The study reveals that the vehicular pollution has gradually increasing in recent times. Delhi the capital city of India has distinctly been affected with highly hazards vehicular pollution levels. The present study has been undertaken aimed at pollution estimation at different transport corridors of Delhi city with a view to analyzing the changing traffic composition trends and its impacts on the levels of ambient air pollutants. From the study, it was found that Ring road (Safdarjung) had the highest concentration of CO and PM10 as 3,066 and 422 μg/m3 while Auchandi Road bore the lowest concentration of the same as 193 and 23 μg/m3. The maximum observed value of pollutants concentration were 363 μg/m3 of NOx at Maa Anandmayi Marg, 542 μg/m3 of PM2.5 at ISBT Flyover and 42μg/m3 of SOx at Nizamuddin Bridge respectively and the minimum observed values were as 24 μg/m3 at Pusa Road, 53 μg/m3 at Sansad Marg and 2 μg/m3 at Auchandi Road respectively. ix The assessment of human health risk regarding mortality and morbidity induced by multiple air pollutants prevailing at 36 transport corridors of the National Capital Territory (NCT) of Delhi, India. The study, covering PM10, PM2.5, SO2 and NO2, utilized the Risk of Mortality/Morbidity due to Air Pollution (Ri-MAP) model in a bid to assess the direct health impacts in the year 2016. The World Health Organization (WHO) guidelines were used to calculate mortality and morbidity for the population in 4 km2 grid sizes in the vicinity of all transport corridors and the results indicate that aggravated by the vehicular traffic, the excess number of mortality cases due to respiratory, cardiovascular, and the total mortality were studied at ISBT Flyover 365, 1399 and 2136 respectively. The very closed data were observed at Wazirabad Road 362, 1378 and 2096 caused by respiratory, cardiovascular, and the total mortality respectively. These two transport corridors also recorded a maximum number of excess cases of morbidity regarding hospital admission due to COPD (Chronic Obstructive Pulmonary Disease) and cardiovascular illness as 18979 and 4762 as well as 18969 and 4761 respectively. Further, excess numbers of cases were reported in 4 km2 grid sizes alongside the transport corridors throughout the megacity of Delhi, thereby presenting a very plausible scenario of traffic-induced human health risk in different residential and other areas. Similar studies with a more focused approach would help not only towards a better transport corridor planning but also help health institutions to be preferable to control excess number of such peculiar health cases in the city and elsewhere. Assessment of the GIS mapping of traffic induced air pollutants along various transport corridors in Delhi has been studied in this thesis. This part includes the classification of vehicular pollutants parameters into five distribution classes, i.e., low, x moderately low, moderate, moderately high, and high. Spatial maps have been developed using Kriging tool in ArcGIS environment for eleven districts covering 36 transport corridors of the city. The study demonstrated concentration of four of the six ambient air pollutants, namely, benzene, NOx, PM10 and PM2.5, with highest values in the range of 6.68-13.86 μg/m3, 294.10-362.57 μg/m3, 203.99-422 μg/m3 and 333.71 541.72 μg/m3 respectively along the corridors. Corresponding National Ambient Air Quality Standard (NAAQS) values were found to be grossly violated as reflected by benzene, NOx and PM concentrations having 2-5 times higher values. Remaining two (CO and SOx) were found to be within permissible limits, and most of them exhibited low levels of observed concentrations. The ambient air quality in south, central, east, and New Delhi areas were found to be in high and moderately high classes necessitating adequate control measures. A questionnaire survey was also conducted in the vicinity areas of selected locations, based on air quality and health risk assessment. This survey was aimed to investigate the understanding of public and their opinion about health effects being caused due to exposure to air pollution during their day to day activities in life. This interviewer assisted questionnaire was developed on the basis of thorough literature review. Respondents were chosen from nearby residential areas, pedestrians using the walkways, motorists, cyclists, rickshaw-pullers, shopkeepers, students, working labors along the transport corridors, vendors, traffic police, doctors etc. According to experiences of residents and commuters eye irritation, breathing difficulties, running nose and congested nose, sneezing bouts, throat irritation and headache were observed the major health effects. Eye irritation was found as one of the prominent health concern among the people who were in the age group of 26 to 50 years. In Delhi, most xi of the people spend their 6 to 10 hours (more than 48 %) time outside the home due to their work profile. After the analysis, it is observed that the emission, concentration and associated health risk are aggravated by the high vehicular density, and densely populated areas along the selected transport corridors. Most of such transport corridors were found to be under “severe” or “very poor” class according to Indian air quality index posing a direct health risk to the exposed population.

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10

VERMA, PIYUSH. "STATISTICAL ANALYSIS AND MODELLING OF NOISE POLLUTION IN DELHI DURING ODD-EVEN VEHICLE RATIONING PROGRAMME." Thesis, 2017. http://dspace.dtu.ac.in:8080/jspui/handle/repository/16080.

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Traffic noise is one of the most common problems in metro cities like Delhi which encounters this problem ever since the rising population and vehicle growth. Thus under section 2(a) of Air (Prevention and Control of Pollution) Act, 1981, noise has been defined as a pollutant. To combat air and noise pollution the Government of Delhi had launched a restrict and control measure process called odd-even vehicle rationing program in January’16 and April’16 which imposed a driving restriction based on the license number plate of the vehicle. In this present research, efforts have been made to evaluate noise pollution from the statistical study of noise parameters during odd-even program at selected sites against the limits prescribed under Ambient Air Quality Standards in respect of Noise by Ministry of Environment and Forests (The Noise Pollution, Regulation and Control, Rules 2000). A continuous 30 days noise data was taken from CPCB Real Time National Noise Monitoring Network during the month of April’16 which marks the beginning of second phase of odd-even vehicle rationing program. The aim of the study is to study its effectiveness and extent of violation. For the study, A-weighted hourly average for peak hours of during daytime and A-weighted daily average of was taken. The noise levels were undertaken for 30 days intervals from 1st April’16 to 30th April’16. The equivalent noise levels were statistically observed using various multiple statistics software. Noise Pollution level (NPL) and Traffic Noise Index (TNI) has been calculated from percentile noise levels to check the level of noise pollution at survey sites. Relative change in equivalent noise level for forecasted and actual data has been observed under the study. Additionally mathematical noise modeling has been done to predict the equivalent noise levels for odd-even program using equations of model. Statistical and mathematical analysis of the noise indices and equivalent noise level demonstrates the fall in noise pollution during odd-even program to a certain extent but still it is above the prescribed noise limits and the city continues to suffer severe noise pollution problems.

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Книги з теми "DELHI POLLUTION"

1

L, Cropper Maureen, and World Bank. Development Research Group., eds. The health effects of air pollution in Delhi, India. Washington, DC: World Bank, Development Research Group, 1997.

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2

S, Datta P. Groundwater situation in Delhi: Red alert. New Delhi: Nuclear Research Laboratory, Indian Agricultural Research Institute, 1999.

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3

India. Central Pollution Control Board., ed. Ambient air quality status and trends in Delhi, 1989-1993. Delhi: Central Pollution Control Board, 1997.

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4

Ambient air quality survey at major traffic intersections in Delhi. Delhi: Central Pollution Control Board, 1995.

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5

India. Central Pollution Control Board., ed. Ambient noise level and air quality status in Delhi during deepawali festival days 1999-2002. Delhi: Central Pollution Control Board, Ministry of Environment & Forests, Govt. of India, 2003.

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6

Epidemiological study on effect of air pollution on human health (adults) in Delhi. Delhi: PR Division, Central Pollution Control Board, Ministry of Environment & Forests, 2012.

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7

Dasgupta, Purnamita. Valuing health damages from water pollution in urban Delhi, India: A health production function approach. Delhi: Institute of Economic Growth, 2001.

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India. Central Pollution Control Board. and India. Central Ground Water Board., eds. Status of ground water quality and pollution aspects in NCT-Delhi: A collaborated study. Chandigarh: Central Ground Water Board, 2000.

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Division, India Central Pollution Control Board PR. Study on ambient air quality, respiratory symptoms and lung function of children in Delhi. Delhi: Central Pollution Control Board, Ministry of Environment & Forests, 2012.

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International Conference, Water Quality Management (2nd 2003 New Delhi, India). 2nd International Conference, Water Quality Management, 13-15 February, 2003, New Delhi, India: Proceedings. Edited by Mathur G. N, Chawla A. S. Dr, India. Central Board of Irrigation and Power., and Indian Committee on Large Dams. [New Delhi: Central Borad of Irrigation and Power, 2003.

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Частини книг з теми "DELHI POLLUTION"

1

Singh, Siddhartha, and S. K. Peshin. "Air Pollution Scenario over Delhi City." In Environment and Sustainable Development, 77–85. New Delhi: Springer India, 2013. http://dx.doi.org/10.1007/978-81-322-1166-2_6.

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Prabhakar, Ashish V. "The air pollution conundrum in Delhi." In Urbanization in the Global South, 225–41. London: Routledge India, 2021. http://dx.doi.org/10.4324/9781003093282-12.

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Sharma, Niraj, P. V. Pradeep Kumar, Anil Singh, and Rajni Dhyani. "Fuel Loss and Related Emissions Due to Idling of Motorized Vehicles at a Major Intersection in Delhi." In Environmental Pollution, 233–41. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5792-2_20.

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4

Somvanshi, Shivangi Saxena, Aditi Vashisht, Umesh Chandra, and Geetanjali Kaushik. "Delhi Air Pollution Modeling Using Remote Sensing Technique." In Handbook of Environmental Materials Management, 1–27. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-58538-3_174-1.

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Dholakia, Hem H., and Amit Garg. "Climate Change, Air Pollution and Human Health in Delhi, India." In Climate Change and Air Pollution, 273–88. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-61346-8_17.

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Kumari, Poonam, and Papiya Mandal. "Indoor Air Pollution at Restaurant Kitchen in Delhi NCR." In Lecture Notes in Civil Engineering, 159–65. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-6887-9_18.

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Akhtar, Aly, Sarfaraz Masood, Chaitanya Gupta, and Adil Masood. "Prediction and Analysis of Pollution Levels in Delhi Using Multilayer Perceptron." In Advances in Intelligent Systems and Computing, 563–72. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-3223-3_54.

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8

Mehrotra, Apurv, R. Jaya Krishna, and Devi Prasad Sharma. "Machine Learning Based Prediction of PM 2.5 Pollution Level in Delhi." In Advances in Computing and Intelligent Systems, 105–13. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-0222-4_9.

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Garnett, Emma, and Srishti Bhatnagar. "Figuring Out Exposure: Exploring Computational Environments and Personalisation in Interdisciplinary Air Pollution Research." In Figure, 197–219. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2476-7_10.

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AbstractAir pollution is often understood through a composition of different kinds of data that increasingly include personal exposure measurements. This chapter is based on our involvement in an interdisciplinary project in Delhi that is combining computational methods and embodied data to simultaneously map, know and respond to air pollution. We use the concept and method of figure, and specifically the figure of ‘the child with asthma’, to explore the tensions that emerge when participants are both objects (sensing bodies that measure air pollution) and subjects (knowing bodies that experience and respond to environmental exposures) of research. This dynamic relationship allows for different ways of figuring out exposure in public health, and thereby possibilities for approaching personalisation that go beyond individualised notions of risk and harm.

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Bisht, Manisha, and K. R. Seeja. "Air Pollution Prediction Using Extreme Learning Machine: A Case Study on Delhi (India)." In Proceedings of First International Conference on Smart System, Innovations and Computing, 181–89. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-5828-8_18.

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Тези доповідей конференцій з теми "DELHI POLLUTION"

1

DE VITO, LAURA, TIM CHATTERTON, ANIL NAMDEO, SHIVA NAGENDRA, SUNIL GULIA, SANJIV GOYAL, MARGARET BELL, et al. "AIR POLLUTION IN DELHI: A REVIEW OF PAST AND CURRENT POLICY APPROACHES." In AIR POLLUTION 2018. Southampton UK: WIT Press, 2018. http://dx.doi.org/10.2495/air180411.

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Kulshreshtha, P., and M. Khare. "A comparative study of indoor air pollution and its respiratory impacts in Delhi, India." In AIR POLLUTION 2010. Southampton, UK: WIT Press, 2010. http://dx.doi.org/10.2495/air100251.

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DHYANI, RAJNI, NIRAJ SHARMA, and MUKTI ADVANI. "ESTIMATION OF FUEL LOSS AND SPATIAL–TEMPORAL DISPERSION OF VEHICULAR POLLUTANTS AT A SIGNALIZED INTERSECTION IN DELHI CITY, INDIA." In AIR POLLUTION 2019. Southampton UK: WIT Press, 2019. http://dx.doi.org/10.2495/air190231.

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4

Sur, Soumyadeep, Rohit Ghosal, and Rittik Mondal. "Air Pollution Hotspot Identification and Pollution Level Prediction in the City of Delhi." In 2020 IEEE International Conference for Convergence in Engineering (ICCE). IEEE, 2020. http://dx.doi.org/10.1109/icce50343.2020.9290698.

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Khare, M., S. Nagendra, and S. Gulia. "Performance evaluation of air quality dispersion models at urban intersection of an Indian city: a case study of Delhi city." In AIR POLLUTION 2012. Southampton, UK: WIT Press, 2012. http://dx.doi.org/10.2495/air120221.

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Srivastava, Chavi, Shyamli Singh, and Amit Prakash Singh. "Estimation of Air Pollution in Delhi Using Machine Learning Techniques." In 2018 International Conference on Computing, Power and Communication Technologies (GUCON). IEEE, 2018. http://dx.doi.org/10.1109/gucon.2018.8675022.

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Taneja, Shweta, Nidhi Sharma, Kettun Oberoi, and Yash Navoria. "Predicting trends in air pollution in Delhi using data mining." In 2016 1st India International Conference on Information Processing (IICIP). IEEE, 2016. http://dx.doi.org/10.1109/iicip.2016.7975379.

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Ansari, Zeba Zarin, and S. V. Akhmatov. "IMPACTS OF WATER POLLUTION ON HUMAN HEALTH: A CASE STUDY OF DELHI." In Prirodopol'zovanie i ohrana prirody: Ohrana pamjatnikov prirody, biologicheskogo i landshaftnogo raznoobrazija Tomskogo Priob'ja i drugih regionov Rossii. Izdatel'stvo Tomskogo gosudarstvennogo universiteta, 2020. http://dx.doi.org/10.17223/978-5-94621-954-9-2020-39.

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Анотація:

Water is an essential element for all the existing living beings. About 70% of the Earth is covered by water. All human beings need fresh drinking water. Without water no life is ever imagined on this blue planet. But life becomes difficult when many lives have to live on polluted water. According to WHO, 80% diseases are waterborne. In Delhi, different types of toxic chemical discharge have different effects on humans causing diseases like bacterial, viral or parasitic. Therefore, it is recommended to focus daily on the water quality of Delhi from destructive events. So, the present paper defines condition of water pollution and their solutions in the given research area.

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Singh, Sparsh, Vidit Kumar, Zaid Ahmed, and Kajol Mittal. "Delhi Air Pollution Prediction: A Comparative Analysis using Time Series Forecasting." In 2023 International Conference on Disruptive Technologies (ICDT). IEEE, 2023. http://dx.doi.org/10.1109/icdt57929.2023.10151445.

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Bhardwaj, Ankit, Shiva Iyer, Yash Jalan, and Lakshminarayanan Subramanian. "Learning Pollution Maps from Mobile Phone Images." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/697.

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Анотація:

Air pollution monitoring and management is one of the key challenges for urban sectors, especially in developing countries. Measuring pollution levels requires significant investment in reliable and durable instrumentation and subsequent maintenance. On the other hand, there have been many attempts by researchers to develop image-based pollution measurement models which have shown significant results and established the feasibility of the idea. But, taking image-level models to a city-level system presents new challenges, which include scarcity of high-quality annotated data and a high amount of label noise. In this paper, we present a low-cost, end-to-end system for learning pollution maps using images captured through a mobile phone. We demonstrate our system for parts of New Delhi and Ghaziabad. We use transfer learning to overcome the problem of data scarcity. We investigate the effects of label noise in detail and introduce the metric of in-interval accuracy to evaluate our models in presence of noise. We use distributed averaging to learn pollution maps and mitigate the effects of noise to some extent. We also develop haze-based interpretable models which have comparable performance to mainstream models. With only 382 images from Delhi and Ghaziabad and single-scene dataset from Beijing and Shanghai, we are able to achieve a mean absolute error of 44 ug/m^3 in PM2.5 concentration on a test set of 267 images and an in-interval accuracy of 67% on predictions. Going further, we learn pollution maps with a mean absolute error as low as 35 ug/m^3 and in-interval accuracy as high as 74% significantly mitigating the image models' error. We also show that the noise in pollution labels emerging from unreliable sensing instrumentation forms a significant barrier to the realization of an ideal air pollution monitoring system. Our codebase can be found at https://github.com/ankitbha/pollution_with_images.

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