A. Air Action Plan
Air Action Plan are set of measures and initiatives that the State Governments and Departments along with the inclusion of NGOs and CSOs undertake to provide a clean and healthy environment to the citizens as envisaged in the Constitution of India.
The comprehensive plan of Delhi covers the National Capital Region cities also. National Capital Region covers few cities of Haryana and Uttar Pradesh
The Department of Environment, Government of Delhi and Delhi Pollution Control Committee have submitted, there Air Action Plan in compliance with the National Green Tribunal.
The Action Plan covers:
New Initiatives by Delhi Government:
As the capital of the country Delhi was approved to be one of the first cities to get a smart city makeover. The New Delhi Municipal Council (NDMC) was selected as a Smart City under the Smart City Mission under the Smart City Mission of Government of India. In July, 2016, a Special Purpose Vehicle as mandated by Smart City Mission was incorporated as NDMC Smart City Limited (NDMC SCL).
The NDMC SCL is undertaking various projects as Area Based Development and Pan City Smart Solutions as envisaged under the SCM. The focus of NDMC SCL is to be the best-in-class Capital City to provide the highest quality of life to all its citizens and visitors and to be the most economically competitive business ecosystem while being sensitive towards the environment.
The Area Based Development Projects consisted of New Delhi City Centre, consisting of Connaught Place and contiguous surrounding areas. Various Area Based Development Projects are implemented under 3 different categories:
The Pan-city Projects leverages information and communication interventions in basic infrastructure to improve liveability and transform NDMC towards its stated vision of being the world’s benchmark capital city. It addresses the issues of water, power, education, healthcare, and governance by utilizing M2M (Machine to Machine) and Internet of Things technologies. Various Pan City Development Projects are implemented under 5 different categories:
B. Monitoring Network of the city
Delhi has been equipped with 40 Continuous Ambient Air Quality Monitoring Stations which have been installed by Central Pollution Control Board, Delhi Pollution Control Committee and Ministry of Earth Sciences, Government of India.
The monitoring data is available on the CPCB website and DPCC website
Manual Air Quality Data – https://cpcb.nic.in/manual-monitoring/
Automatic Air Quality Data – https://app.cpcbccr.com/ccr/#/caaqm-dashboard-all/caaqm-landing
Ambient Air Quality Data – Delhi NCR – https://cpcb.nic.in/ambient-aq-data-delhi-ncr/
Real Time ambient Air Quality Data, Delhi Pollution Control Committee – http://www.dpccairdata.com/dpccairdata/display/index.php
CPCB also does Special Monitoring during Diwali and during the period even Odd – Even vehicle scheme is enforced.
They have also monitored the impact of Lockdown and Janta Curfew on Air Pollution
C. Government Policies, Acts, Laws, Press Release
It is the Principal Act enacted in pursuance of the Stockholm Declaration, 1972 for prevention, control, and abatement of Air Pollution. They were amended in 1987 giving the Pollution Control Boards more authority and power.
Rules were enacted to support the Principal Act in better management and control of Air Pollution
2.State Acts, Policies, Laws and Press Release
The Central Pollution Control Board framed and submitted a Graded Response Action Plan (GRAP) for different categories of National Air Quality Index (AQI) as directed by the Supreme Court in its order dated November 10, 2016 in the case MC Mehta vs. Union of India (W.P.(C) No. 13029/ 1985)
The GRAP divides AQI into four categories: Moderate to Poor, very poor, Severe and Severe+ Emergency which elaborates the actions that must be taken by Delhi and NCR (Uttar Pradesh, Haryana, and Rajasthan) according to the pollution levels in the respective states. The purpose of the GRAP is for Delhi and NCR (States) to take effective steps to combat public health emergencies and keep the general public informed and updated on the level of air pollution.
D. State and National Set Standards
Ambient air quality refers to the condition or quality of air surrounding us in the outdoors. National Ambient Air Quality Standards are the standards for ambient air quality set by Central Pollution Control board (CPCB) that is applicable nationwide. The CPCB has been conferred this power by the Air (Prevention and Control of Pollution) Act, 1981.
 https://www.sci.gov.in/jonew/ropor/rop/all/859124.pdf (M.C. Mehta vs. Union of India, Writ Petition (Civil) No. 13029/ 1985) order dated 10th November, 2016.
This comprehensive study is based on an integrated approach involving all major factors influencing urban air quality management. Quantification of these sources would help in ranking them and formulating appropriate control strategies and management options.
A comprehensive air quality management would need three basic requirements viz. assessment of ambient air quality levels, preparation of emission inventory and conducting source apportionment analysis. The major objectives of the study are:
By comparing the existing emissions inventories for Delhi or NCR, this study aims to explain the differences in these estimates. To detail these differences, the study focuses on PM10 and PM2.5 in transport, industries, power plants, road dust, and construction – the five major contributing sectors. An emissions inventory uses the bottom-up method and forms the basis for a source apportionment study. A dispersion model is used to calculate the distribution of pollution using the emissions inventory and meteorological data as input parameters.
To improve the understanding of air pollution and formulation of policy, several changes are necessary. Information on sampling frame and sample details needs to be transparent. Uncertainty should be quantified to explain the spread of observations for a sector. Multiple-year inventories would capture the dynamic nature of air pollution and enable accurate, real-time information. Common regulatory guidelines would help in building robust inventories. Source apportionment based on emissions inventories and dispersion modelling should be reconciled with receptor modelling to enable convergence between the modelling and measurement approaches.
Study was carried out for source apportionment of PM2.5 and PM10 concentrations in Delhi-National capital region (NCR) using two modelling-based approaches. The first approach relied upon monitoring and chemical characterization of PM2.5 and PM10 samples. The chemically speciated samples along with source profiles were fed into the receptor model to derive source contributions. In the second approach, source-wise emission inventory, along with meteorological inputs and boundary conditions were fed into a dispersion model to simulate PM10 and PM2.5 concentrations. The modelled concentrations were compared with actual observations for validation. The validated model has been used to carry out source sensitivity to derive source contributions and future projections of PM2.5 and PM10 concentrations. Finally, various interventions have been tested which can reduce the pollutant concentrations in future years.
Source apportionment of particulate matter (PM10) measurements taken in Delhi, India between January 2013 and June 2014 was carried out using two receptor models, principal component analysis with absolute principal component scores (PCA/APCS) and UNMIX. The results were compared with previous estimates generated using the positive matrix factorization (PMF) receptor model to investigate each model’s source-apportioning capability. All models used the PM10 chemical composition (organic carbon (OC), elemental carbon (EC), water soluble inorganic ions (WSIC), and trace elements) for source apportionment.
The UNMIX model resolved five sources (soil dust (SD), vehicular emissions (VE), secondary aerosols (SA), a mixed source of biomass burning (BB) and sea salt (SS), and industrial emissions (IE)). The PCA/APCS model also resolved five sources, two of which also included mixed sources (SD, VE, SD+SS, (SA+BB+SS) and IE). The PMF analysis differentiated seven individual sources (SD, VE, SA, BB, SS, IE, and fossil fuel combustion (FFC)). All models identified the main sources contributing to PM10 emissions and reconfirmed that VE, SA, BB, and SD were the dominant contributors in Delhi.
Chemical characterization of PM2.5 [organic carbon, elemental carbon, water soluble inorganic ionic components, and major and trace elements] was carried out for a source apportionment study of PM2.5 at an urban site of Delhi, India from January, 2013, to December, 2014. The annual average mass concentration of PM2.5 was 122 ± 94.1 µg m−3. Strong seasonal variation was observed in PM2.5 mass concentration and its chemical composition with maxima during winter and minima during monsoon. A receptor model, positive matrix factorization (PMF) was applied for source apportionment of PM2.5 mass concentration. The PMF model resolved the major sources of PM2.5 as secondary aerosols (21.3 %), followed by soil dust (20.5 %), vehicle emissions (19.7 %), biomass burning (14.3 %), fossil fuel combustion (13.7 %), industrial emissions (6.2 %) and sea salt (4.3 %).
The paper/infograph is an attempt to analyse the sources of air pollution in Delhi. The paper/infograph analyses the Air quality trend from 2006-2018, and lays out basic information on what are particulate matter, what constitutes particulate matter etc.
Source apportionment of total suspended particulate matter (TSPM) and associated heavy metals has been carried out for the city of Delhi using the Chemical Mass Balance Model, Version 8 (CMB8), as well as principle component analysis (PCA) of SPSS (Varimax Rotated Factor Matrix method) in coarse- and fine-size mode. Results obtained by CMB8 indicate the dominance of vehicular pollutants (62%), followed by crustal dust (35%) in the fine size range; while in the coarse size range crustal dust dominated (64%) over vehicular pollution (29%). Little contribution from paved-road dust and industrial sources was observed. Results of PCA (or factor analysis) reveal two major sources (vehicular and crustal re-suspension) in both coarse and fine size ranges. The correlations of factors (sources) with the metals show that in the coarse size range the dominant source is crustal re-suspension (68%) followed by vehicular pollution (23%). However, this is reversed in the case of the fine size range factor analysis where vehicular pollution (86%) dominated over crustal re-suspension (10%).
Source apportionment using chemical mass balance (CMB) model was carried using a data set of 360 four hourly samples collected at 15 locations of five categories namely residential, commercial, industrial, traffic intersections and petrol pumps during August 2001–July 2002 in Delhi. The results indicate that emissions from diesel internal combustion engines dominate in Delhi. Vehicular exhaust and evaporative emissions also contribute significantly to VOCs in ambient air. Emission of VOCs associated with sewage sludge was also found to contribute to VOCs in Delhi’s air. This points to the fact that open defecation and leaking sewage manholes are a problem in all categories of locations.
B. Pervious Year Trend
The present investigation shows that the burning of firecrackers, sparkles etc. in huge amounts has a substantial impact on increase in the concentration of criteria air pollutants especially PM10 and PM2.5 and that of trace gases (CO, SO2, NO2 and NH3) components over all six study areas. Vehicular emission remains the most prominent source of air pollution at all the six locations undergone the study and second major one during the Diwali festival night. The most prominent source of criteria air pollutants is burning of various types of firecracker during the Diwali festival night throughout the city aggravating the concentration of pollutants in the ambient air already coming from exhaust emissions
The sector-wise emission trends of the criteria pollutants CO, NOx, SO2, PM10 during 2000-2010 in Delhi. It has been found that CO is mainly emitted from transport and domestic sector. Major contribution of NOx comes from transport followed by power plants and domestic sector respectively and has followed an increasing trend during 2000-2010.
Transport sector emission inventory for megacity Delhi has been developed for the period 2000–2005 to quantify vehicular emissions and evaluate the effect of relevant policy reforms on total emissions of various air pollutants like CO2, CO, HC, NOx, TSP, SO2, Pb and VOC’s over the years to assist in future policy formulations. Emission factor and vehicle utilization factor based approach as recommended by IPCC (2006) have been used for estimating emissions. CO level were found to increase continuously during the study period, other pollutants like CO2, TSP, NOx and SO2 declined in the initial years, which clearly seem to be the result of stricter emission norms and compressed natural gas conversion of public transport. The levels of NOx and TSP did not show appreciable rise during the study period, which is an indicator of CNG effectiveness as an alternative fuel. However, two-wheelers population were found to be a major contributor towards the air pollution load.
Urban Emission has been continuously updating their Delhi air Pollution Trends. They have done yearly and monthly trends from 2006 onwards.
A. City-specific studies
This work presents an analysis of road transportation in Delhi region with focus on energy demand and carbon dioxide (CO2) emissions. The study has considered five scenarios for the year 2021; one business as usual, and four future alternative scenarios, with 2007 as the reference year.
The alternative scenarios have been developed by considering the introduction of six policy interventions, namely; construction of integrated mass rapid transit system (IMRTS), fixed bus speed, hike in parking fees, fuel efficiency, stringent emission norms, and increase in the occupancy of private vehicles. the current study shows that shift to public transport use would not will merely be sufficient to reduce energy demand, oil use and carbon emissions from passenger transport in urban areas of developing countries.
IIT – Kanpur did a comprehensive study for the Department of Environment and Delhi Pollution Control Committee on Air Pollution and Green House Gases. The study has five major components air quality measurements, emission inventory, air quality modelling, control options and action plan.
The concentrations of organic carbon (OC), elemental carbon (EC), water soluble inorganic ionic components (WSIC), and major & trace elements of PM10 were studied in Delhi, an urban site of the Indo Gangetic Plain (IGP), India during January 2013 to June 2014. Positive PMF provides that the major source of PM10 are soil dust (22.7%) followed by secondary aerosols (20.5%), vehicle emissions (17.0%), fossil fuel burning (15.5%), biomass burning (12.2%), industrial emissions (7.3%) and sea salts (4.8%) at the observational site of Delhi.
Over the past years the development and urbanization in Delhi has led to increase in air pollution. The study and research has used data mining to analyze the existing trends in air pollution in Delhi and make prediction about the future. The data mining techniques used are linear regression and multilayer perceptron. We have seen the trends of various air pollutants like sulphur dioxide (SO2), nitrogen dioxide (NO2), particulate matter (PM), carbon monoxide (CO), ozone (O3). By using the above techniques, we have observed that there will be an increase in amount of PM 10 by 45.9% in coming years. However, amount of CO and NO 2 may show slight increase due to increasing number of 2 wheelers on road. The other pollutants like SO 2 may show decrease due to usage of non-sulphur fuel and stringent pollution control measures.
High resolution concentrations of nitric oxide (NO), nitrogen dioxide (NO2), oxides of nitrogen (NOx), and Ozone (O3) were measured at a urban site (urban background) in New Delhi, India for a period of two years from September 2010 to August 2012. The analysis suggests that [OX] concentrations were about six times higher with winds originating from the Northwest direction (NW) compared to those from the East.
Between late 1980s and 2014, the Greater Delhi region has witnessed an increase in vehicular fleet, four sets of emission standards, and changes in engine technology and fuel usage. This paper presents and evaluate these measures on on-road vehicle exhaust emissions under four counterfactual scenarios – (a) no penetration of 4-stroke (4S) 2-wheelers (2Ws) (b) no introduction of compressed natural gas (CNG) (c) no implementation of emission standards post 2000 and (d) no dual emission standards (supply of better fuel in the metropolitan areas and a grade lower for the rest).
The study reviews 16 studies out of which only carried out inventory of PM2.5 emissions and establishing link of particulate matter and health effects in terms of morbidity and mortality, estimation of PM2.5 emissions is an important step in understanding the contribution of road transport sector. The summary shows that there is some variance in the emission estimates between studies. The transport sector plays an integral role in the movement of passengers and freight through the city. The contribution of vehicle exhaust emissions to the ambient pollution is substantial and needs more positive interventions for future emission control.
The study aims to present a source apportionment of PM10 has been done using positive matrix factorization at an urban site of Delhi, India based on the chemical compositions of PM10 collected during January 2010 to December 2011. The concentration of PM10 and its chemical components including organic carbon (OC), elemental carbon (EC), water soluble inorganic ionic components (WSIC) and major and trace elements showed strong seasonal cycle with maxima during winter and minima during monsoon. In this process, chemical composition of the PM10 mass was reconstructed using IMPROVE equation from the observed elemental composition. The highest contribution comes from particulate organic matter (24%) to the estimated average values of PM10 apart from other components e.g., soil/crustal matter (16%), ammonium sulphate (7%), ammonium nitrate (6%), aged sea salt (5%) and light absorbing carbon (4%). Positive Matrix Factorization (PMF) analysis quantified the sector wise contribution from the secondary aerosols (21.7%), soil dust (20.7%), fossil fuel combustion (17.4%), vehicle emissions (16.8%), and biomass burning (13.4%) to PM10 mass at the observational site of Delhi.
This study evaluates the human health risks in Indian National Capital Territory of Delhi (NCT Delhi) in terms of mortality and morbidity due to air pollution. The spreadsheet model, Risk of Mortality/Morbidity due to Air Pollution (Ri–MAP) was used to evaluate the direct health impacts of various criteria air pollutants present in various districts of NCT Delhi during the period 1991 to 2010. District–wise analysis shows that North West district is having the highest number of mortality and morbidity cases continuously after 2002, moreover least excess number of cases was observed for New Delhi district. It is observed that New Delhi district has the least excess number of cases of mortality/morbidity, possibly attributable to the lower population of New Delhi. It is found that higher ambient concentrations of SPM and NOX are responsible for excess number of mortality and morbidity in various districts of megacity Delhi.
The study attempts to compile a decadal emission inventory of emission from transport sector in Delhi. The emissions of all the pollutants except for SO2 have shown an increasing trend during the decade.
Water‐soluble organic carbon (WSOC) is a major constituent (~ 20–80%) of the total organic carbon aerosol over the Indian subcontinent during the dry winter season. The study presents radiocarbon constraints on the biomass versus fossil sources of WSOC in PM2.5 for the 2010/2011 winter period for the megacity Delhi.
Radiocarbon‐based source apportionment of carbonaceous aerosols during the winter season of 2010–2011 demonstrated that biomass combustion is a major source of WSOC in the megacity despite its numerous fossil air pollution sources. WSOC in Delhi is more depleted in C isotope compared to background sites in West India and over the Indian Ocean, which is consistent with expected isotope signature of nonaged and/or slightly aged aerosols. Light absorption properties of WSOC in Delhi exhibit large temporal variability, which are comparable to those previously reported for megacity Beijing. These findings emphasize that biomass combustion WSOC also has a small positive forcing component next to its well‐recognized contribution to the indirect climate effect.
The study was conducted in Delhi between 2008 and 2011, at seven monitoring stations, the daily average of particulate matters PM2.5 and PM10. The bulk of the pollution is due to motorization, power generation, and construction activities. A multi-pollutant emissions inventory for the National Capital Territory of Delhi, covering the main district and its satellite cities – Gurgaon, Noida, Faridabad, and Ghaziabad. For the base year 2010, we estimate emissions (to the nearest 000’s) of 63,000 tons of PM2.5, 114,000 tons of PM10, 37,000 tons of sulfur dioxide, 376,000 tons of nitrogen oxides, 1.42 million tons of carbon monoxide, and 261,000 tons of volatile organic compounds. The GIS based spatial inventory coupled with temporal resolution of 1 h, was utilized for chemical transport modeling using the ATMoS dispersion model.
The paper provides an evidence-based insight into the status of air pollution in Delhi and its effects on health and control measures instituted. The urban air database released by the World Health Organization in September 2011 reported that Delhi has exceeded the maximum PM10 limit by almost 10-times. Vehicular emissions and industrial activities were found to be associated with indoor as well as outdoor air pollution in Delhi. Studies on air pollution and mortality from Delhi found that all-natural-cause mortality and morbidity increased with increased air pollution. Delhi has taken several steps to reduce the level of air pollution in the city during the last 10 years. However, more still needs to be done to further reduce the levels of air pollution.
Present study deals with the statistical analysis of long-term ground level ozone (O3) trend and the influence of meteorological variables on its variation over Delhi, India. Daily mean and maximum of O3 and meteorological data, obtained from India Meteorological Department, were arranged for the period of 9 years (1998–2006). Results indicate a significant increasing trend with annual increase of 1.13 % for O3 mean and 3 % for O3 maximum. Annual deseasonalized trend for seasonal cycle shows bimodal oscillations. About 43 % of O3 variation was explained by the selected meteorological factors and rest of variation attributed to factors like emission of precursor gases, pollutant transport, policy changes, etc. Among the three tested regression models, performance of Model 2 with variable temperature, wind speed, and visibility was found to be best that resulted in lowering of O3 trend. Large variability (23 %) was explained by the variable visibility depicted that the emission of primary pollutants not only provides the precursor gases but also control the local photochemical reactions.
The study characterises the ambient inhalable particles (PM10, aerodynamic diameter ≤10 μm) with respect to 8 major and trace metals (Fe, Mn, Cd, Cu, Ni, Pb, Zn and Cr) at three residential areas of Delhi. Pollution assessment in residential areas is important since outdoor air quality has a major influence on indoor pollution. Population residence time is also highest in residential areas which results in greater exposure. The study is a holistic view of the distribution, spatio–temporal variation and source apportionment of metallic species at some residential areas of Delhi along with an estimation of possible health risks to the exposed population.
The role of meteorology is studied using a Lagrangian model called Atmospheric Transport Modeling System in tracer mode to better understand the seasonality of pollution in Delhi. A clear conclusion is that irrespective of constant emissions over each month, the estimated tracer concentrations are invariably 40% to 80% higher in the winter months (November, December, and January) and 10% to 60% lower in the summer months (May, June, and July), when compared to annual average for that year. Along with monitoring and source apportionment studies, this paper presents a way to communicate complex physical characteristics of atmospheric modelling in simplistic manner and to further elaborate linkages between local meteorology and pollution.
The study shows seven-year data of hourly surface ozone concentration is analyzed to study diurnal cycle, trends, excess of ozone levels above threshold value and cumulative ozone exposure indices at a tropical megacity, Delhi. The ozone levels clearly exhibit a diurnal cycle, like what has been found in other urban places. A sharp increase in the ozone levels during forenoon and a sharp decrease in the early afternoon can be observed. The present surface ozone levels in the city are high enough to exceed “Critical Levels” which are safe for human health, vegetation, and forest. The human health threshold was exceeded for up to 45 days per year.
The paper applies the Long-range Energy Alternatives Planning (LEAP) system for modeling the total energy consumption and associated emissions from the household sector of Delhi. Energy consumption under different sets of policy and technology options are analyzed for a time span of 2001–2021 and emissions of carbon dioxide (CO2), carbon monoxide (CO), methane (CH4), non-methane volatile organic compounds (NMVOCs), nitrogen oxides (NOx), nitrous oxide (N2O), total suspended particulates (TSP) and sulfur dioxide (SO2) are estimated. Different scenarios are generated to examine the level of pollution reduction achievable by application of various options.
This paper uses spectral methods to analyze changes in air quality at a single monitoring site in Delhi since 2000. Power spectral density calculations of daily concentration data for particulate matter (PM10), carbon monoxide (CO), oxides of nitrogen (NOx) and oxides of sulfur (SOx) reveal the presence of trends and periodic oscillations for all the pollutants. The sharp drop in both the trend and amplitude of the seasonal cycle of CO coincides with the switch to Compressed Natural Gas (CNG) as a fuel for Delhi’s public transport fleet. Observed changes in SOx and PM10 concentrations were most likely caused by sources unrelated to vehicular traffic.
A study of the source contribution of atmospheric particulate matter and associated heavy metal concentrations using chemical mass balance model Version 8 (CMB8) in coarse and fine size mode has been carried out for the city of Delhi. Urban particles were collected using a five-stage impactor at six sites in three different seasons, viz. winter, summer, and monsoon in the year 2001. Five samples from each site in each season were collected. The results obtained indicate the dominance of vehicular pollutants in fine size mode, whilst the contribution in coarse mode to some extent is site specific but largely due to vehicular pollution and, soil and crustal dust. Seasons also play an important role but in coarse size fraction only.
The paper describes the formulation of an AQMP for mega cities like Delhi in India considering the key ‘inputs.’ The AQMP formulation methodology is based on past studies of Longhurst. Further, the vulnerability analysis (VA) has been carried out to evaluate the stresses due to air pollution in the study area. The VA has given the vulnerability index (VI) of ‘medium to high’ and ‘low’ at urban roadways/intersections and residential areas, respectively.
The Air Quality Index (AQI) is an index for reporting daily air quality. A study on the annual and seasonal variations of Air Quality Index over a period of 9 years (1996–2004) based on daily averaged concentration data of criteria air pollutants has been conducted for Delhi. An attempt has been made to quantify the changes in the AQI on annual and seasonal (winter, summer, monsoon and post monsoon) basis for 9 years. Measurements for the seven monitoring sites
in Delhi were analysed and trends were also compared amongst these sites. the areas which are farthest from metro route viz., Siri-fort, Nizamuddin, Janakpuri etc. did not record declining AQI in 2003 onwards as happened with stations closer to Metro route such as Ashok Vihar and ITO. An attempt has been made to quantify the reasons that lead to the changes in the values of the AQI.
Ambient concentrations of carbon monoxide (CO), nitrogen oxides (NOx), sulfur dioxide (SO2), and total suspended particulates (TSP) were measured from January 1997 to November 1998 in the center of downtown New Delhi, India. The data consist of 24-h averages of SO2, NOx, and TSP as well as 8 and 24-h averages of CO. The measurements were made to characterize air pollution in the urban environment of New Delhi and assist in the development of an air quality index.
The study assessed chronic respiratory morbidity by (a) prevalence of chronic respiratory symptoms (i.e., chronic cough, phlegm, breathlessness, and wheezing) and airway diseases (i.e., chronic obstructive pulmonary disease/chronic bronchitis and bronchial asthma); and (b) lung function results in asymptomatic non-smoking subjects in the two pollution zones. A multiple logistic regression identified the determinants of chronic symptoms. Smoking, male sex, increasing age, and lower socioeconomic status were strong independent risk factors for occurrence of chronic respiratory symptoms. In the comparison of non-smoking residents of lower- and higher-pollution zones—stratified according to socioeconomic levels and sex—chronic cough, chronic phlegm, and dyspnoea (but not wheezing) were significantly more common in the higher-pollution zone in only some of the strata. Furthermore, prevalence rates of bronchial asthma, chronic obstructive pulmonary disease, and chronic bronchitis among residents in the two pollution zones were not significantly different. Nonetheless, lung function of asymptomatic non-smokers was consistently and significantly better among both male and female residents of the lower-pollution zone.
This paper reports the results of a study relating levels of particulate matter to daily deaths in Delhi, India, between 1991 and 1994. It also assesses the damaging effects they have on human health, these effects include premature death as well as increases in the incidence of chronic heart and lung diseases.
The paper reports some unusual winter diurnal ozone trends and speculates the possible reasons. Measurements of ozone (O3) and oxides of nitrogen (NOx) were carried out at six sites in Delhi during the winter months of 1993. Concentrations of ozone and NOx varied between 34 and 126 ppbv and 32 and 272 ppbv, respectively. Interestingly, ozone exhibited initial high levels during morning hours which subsequently declined to lower levels around noon. However, during evening hours a delayed build-up of ozone was observed which is a departure from earlier studies.
The prime objective of the study was to arrive at an optimal transport policy which limits the future growth of fuel consumption as well as air pollution. A simple model of passenger transport in the city of Delhi has been developed using a computer-based software called—Long Range Energy Alternatives Planning (LEAP) and the associated Environmental Database (EDB) model. The hierarchical structure of LEAP represents the traffic patterns in terms of passenger travel demand, mode (rail/road), type of vehicle and occupancy (persons per vehicle). Transport database in Delhi together with fuel consumption values for the vehicle types, formed the basis of the transport demand and energy consumption calculations.
Greenpeace India, released a report, which analyses PM10 annual average recorded for 280 cities. The report concluded that Delhi is the most polluted city among the 280 cities analysed.
On November 3rd, 2018 a Giant Lung replica were installed at The Sri Ganga Ram Hospital, in order to showcase the severity of the issue and bring awareness to the impact of air pollution on healthy lungs. This campaign was launched by Help Delhi Breathe, the Lung Care Foundation and the Sri Ganga Ram Hospital. The replica of lungs has been made by Jhtakaa, a Bangalore based non-profit organisation, that is active within the clean air movement.
The outcome of the installation of the Lungs were they turned black within three days of installation, this indicates that how bad the quality of air is and badly it affects the human lungs.
A. Urban Local Bodies notification on Air.
B. Communication Portal for local government (e – governance)
C. Public engagement activities.
A. CAST Study
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A. Way Forward
B. Tool Kit