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India is home to some of the most polluted cities on the planet. The worsening air quality in most of the cities has gone to an extent of causing severe impact on human health and life expectancy. An early warning system where people are alerted well before an adverse air quality episode can go a long way in preventing exposure to harmful air conditions. Having such system can also help the government to take better mitigation and preventive measures. Forecasting systems based on machine learning are gaining importance due to their cost-effectiveness and applicability to small towns and villages, where most complex models are not feasible due to resource constraints and limited data availability. This paper presents a study of air quality forecasting by application of statistical models. Three statistical models based on autoregression (AR), moving average (MA), and autoregressive integrated moving average (ARIMA) models were applied to the datasets of PM2.5 concentrations of Delhi and Bengaluru, and forecasting was done for 1-day-ahead and 7-day-ahead time frames. All three models forecasted the PM2.5 reasonably well for Bengaluru, but the model performance deteriorated for the Delhi region. The AR, MA, and ARIMA models achieved mean absolute percentage error (MAPE) of 10.82%, 7.94%, and 8.17% respectively for forecast of 7 days and MAPE of 7.35%, 5.62%, and 5.87% for 1-day-ahead forecasts for Bengaluru. For the Delhi region, the model gave an MAPE of 27.82%, 24.62%, and 27.32% for the AR, MA, and ARIMA models respectively in the 7-day-ahead forecast, and 24.48%, 23.53%, and 23.72% respectively for 1-day-ahead forecast. The analysis showed that ARIMA model performs better in comparison to the other models but performance varies with varying concentration regimes. Study indicates that other topographical and meteorological parameters need to be incorporated to develop better models and account for the effects of these parameters in the study. [ABSTRACT FROM AUTHOR]

The present study intends to use machine learning (ML) and deep learning (DL) models to forecast PM2.5 concentration at a location in Delhi. For this purpose, multi-layer feed-forward neural network (MLFFNN), support vector machine (SVM), random forest (RF) and long short-term memory networks (LSTM) have been applied. The air pollutants, e.g., CO, Ozone, PM10, NO, NO2, NOx, NH3, SO2, benzene, toluene, as well as meteorological parameters (temperature, wind speed, wind direction, rainfall, evaporation, humidity, pressure, etc.), have been used as inputs in the present study. Moreover, this is one of the first papers that employ aerodynamic roughness coefficient as an input parameter for the prediction of PM2.5 concentration. The result of the study shows that the LSTM model with index of agreement (IA) 0.986, root mean square error (RMSE) 21.510, Nash–Sutcliffe efficiency index (NSE) 0.945, (coefficient of determination)R2 0.945, and (correlation coefficient)R 0.972 is the best performing technique for the prediction of PM2.5 followed by MLFFNN, SVM, and RF models. The sensitivity analysis for the LSTM model reported that PM10, wind speed, NH3, and benzene are the key influencing parameters for the estimation of PM2.5. The findings in this work suggest that the LSTM could advance in PM2.5 forecasting and thus would be useful for developing fine-scale, state-of-the-art air pollution forecasting models. [ABSTRACT FROM AUTHOR]

In this paper, a 2-D turbulent closure model, based on the pollutant mass conservation equation, is adopted to estimate the local and background pollutants in the predominant wind direction for the stable atmosphere during winter mornings. The background concentration of pollutants can severely affect the regional pollution level, and its monitoring is a challenging task. Here, the turbulent closure model is employed across three cities in India, viz., Patiala, Delhi, and Agra, to estimate SO2 and NOx concentration along the predominant wind direction to demonstrate the potential of numerical models. The direction of the prevailing wind in this area during January 2003 was NNW (330°). Patiala is followed by Delhi and then Agra in the predominant wind direction. The sensitivity analysis of surface temperature on pollutant concentration reveals that concentration would increase by its square as temperature dips. So, during low or no horizontal wind, pollution episodes will be inevitable. Thus, the pollution hotspots are also identified in these three cities. Delhi had a high pollution load. So, the impact of local pollution in Delhi, through dispersion, was found significant in Agra. NOx hot spots (exceed the 30 μg/m3 limit) are found all across Delhi, except IGI Airport and two other locations. However, no SO2 hotspot (exceed the 60 μg/m3 limit) is found in Delhi. The proposed model output is verified with the WRF-CFD model results. Compared to the WRF-CFD model, the proposed model has overestimated NOx and SO2 concentration maximum by 14.4% and 23.5%, respectively. The overestimation occurred primarily due to ignoring atmospheric chemical reactions (e.g., acid condensation, etc.) for which the atmospheric factors were not so conducive. [ABSTRACT FROM AUTHOR]

Novel machine learning models (MLMs) using the seasonal indexing approach that captures the variation in air quality caused due to meteorological changes have been used to provide short-term, real-time forecasts of PM2.5 concentration for one of the most polluted air quality control regions (AQCR) in the capital city of Delhi. Two MLMs—multi-linear regression and random forest—have been developed for using time series data for 1-h and 24-h average PM2.5 concentration. Short-term, real-time forecasts have been made using the developed models. Various model performance evaluation indices indicate satisfactory model performance. R2 values for the hourly and daily models varied between 0.95 and 0.72 and between 0.76 and 0.68 for the 1st to 5th h/day, respectively. The lagged values of PM2.5 concentration (persistence) and the hourly and daily indices are the most influential variables for the forecasts for immediate time steps. In contrast, seasonal indices become more important with the forecasting time horizon. The developed models can be used for making short-term, real-time air quality forecasts and issuing a warning when the pollution levels go beyond acceptable limits. [ABSTRACT FROM AUTHOR]

Air pollution has become a growing problem in megacities and large urban areas through out the globe, and transportation is recognized as the major source of air pollution in many cities, especially in developing countries. Contribution of automobiles is reported in the range of 40 to 80% of the total air pollution. The challenge facing megacities is how to reduce the adverse environmental impacts and other negative effects of transportation without giving up the benefits of mobility. The dilemma becomes most pressing under conditions of rapid urban growth, which is likely to increase travel demand significantly. The paper is aimed at understanding the problem of vehicular pollution vis-a-vis ambient air quality for a highly traffic affected megacity, Delhi, wherein, the contribution of transport sector was estimated to be as high as 72%. An effort has been made to review and evaluate the benefits (in terms of improved air quality) of the technological interventions/policies adopted for vehicular pollution control in Delhi. It also highlights the outcome of the efforts and suggests further improvements thereon. The importance of public participation and awareness are also discussed. The paper focuses on deriving the benefits of the implementation of management strategies, supported by scientific and technical data/interpretation, so that the people can realize and participate in the government's endeavor for clean city drive in a more effective manner. [ABSTRACT FROM AUTHOR]

This paper describes the development of artificial neural network (ANN) based carbon monoxide (CO) persistence (ANNCOP) models to forecast 8-h average CO concentration using 1-h maximum predicted CO data for the critical (winter) period (November–March). The models have been developed for three 8-h groupings of 10 p.m. to 6 a.m., 6 a.m. to 2 p.m. and 2–10 p.m., at two air quality control regions (AQCRs) in Delhi city, representing an urban intersection and an arterial road consisting heterogeneous traffic flows. The result indicates that time grouping of 2–10 pm is dominantly affected by inversion conditions and peak traffic flow. The ANNCOP model corresponding to this grouping predicts the 8-h average CO concentrations within the accuracy range of 68–71%. The CO persistence values derived from ANNCOP model are comparable with the persistence values as suggested by the Environmental Protection Agency (EPA), USA. This work demonstrates that ANN based model is capable of describing winter period CO persistence phenomena. [ABSTRACT FROM AUTHOR]

Air pollution is one of the major environmental problems in India, affecting health of thousands of ‘urban’ residents residing in mega cities. The need of the day is to evolve an ‘effective’ and ‘efficient’ air quality management plan (AQMP) encompassing the essential ‘key players’ and ‘stakeholders.’ This paper describes the formulation of an AQMP for mega cities like Delhi in India taking into account the aforementioned key ‘inputs.’ The AQMP formulation methodology is based on past studies of Longhurst et al., ( Atmospheric Environment, 30, 3975–3985, 1996); Longhurst & Elsom, ((1997). Air Pollution-II, Vol. 2 (pp. 525–532)) and Beatti et al., ( Atmospheric Environment, 35, 1479–1490, 2001). 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. [ABSTRACT FROM AUTHOR]

A number of policy measures have been activated in India in order to control the levels of air pollutants such as particulate matter, sulphur dioxide (SO2) and nitrogen dioxide (NO2). Delhi, which is one of the most polluted cities in the world, is also going through the implementation phase of the control policies. Ambient air quality data monitored during 2000 to 2003, at 10 sites in Delhi, were analyzed to assess the impact of implementation of these measures, specifically fuel change in vehicles. This paper presents the impact of policy measures on ambient air quality levels and also the source apportionment. CO and NO2 concentration levels in ambient air are found to be associated with the mobile sources. The temporal variation of air quality data shows the significant effect of shift to CNG (Compressed Natural Gas) in vehicles. [ABSTRACT FROM AUTHOR]

Every year at the onset of winter season (October–November), crop residue/parali/stubble burning starts in Punjab and Haryana, leading to heavy air pollution in Delhi, and adversely affecting human and environmental health. During this time, the combination of unfavourable meteorological conditions, additional emissions from stubble burning, and firework activities in this area causes the air quality to further deteriorate. In this study, we have attempted to understand the influence of parali and firecracker incidents on air pollutants' variability over Delhi during the last three years (2020 to 2022). For this purpose, daily average particulate matter and gaseous pollutants data were fetched from the Central Pollution Control Board (CPCB), and daily total fire counts and fire radiative power (FRP) data were retrieved from NASA's Fire Information for Resource Management System (FIRMS). A bigger area of severe burning is suggested by higher FRP values and higher fire counts in the middle of November in all the years considered. Three years satellite-based FIRMS data over Punjab and Haryana show the highest number of active fire counts in 2021 (n = 80,505) followed by 2020 (n = 75,428), and 2022 (n = 49,194). More than 90% parali burning incidents were observed in Punjab state only despite the considerable variability in numbers among the years. The significant effect of parali burning was seen on pollutant concentration variability. As the number of fire count increases or decreases in Punjab and Haryana, there is a corresponding increase or decrease in the particulate matter concentration with a time lag of few days (1 to 2 days). The trend in backward air mass trajectories suggests that the variable response time of pollutants' concentration is due to local and distant sources with different air mass speeds. Our estimates suggest that stubble burning contributes 50–75% increment in PM2.5 and 40 to 45% increase in PM10 concentration between October and November. A good positive correlation between PM2.5, PM10, NOX, and CO and fire counts (up to 0.8) suggests a strong influence of stubble burning on air quality over Delhi. Furthermore, the firecracker activities significantly increase the concentration of particulate matter with ~100% increment in PM2.5 and ~55% increment in PM10 mass concentrations for a relatively shorter period (1 to 2 days). [ABSTRACT FROM AUTHOR]

The present study envisions the influences of land use dynamics on the spatial trend of groundwater depth levels over a period of two decades in the south region of NCT Delhi, India. The findings have inferred that among five major LULC categories, built-up has shown a sprawling trend (+2.17 km2/year) from the north, northeastern, and central portions to the confined patches observed in the south and southwest fringes of South Delhi from 2001 to 2021. Likewise, vegetation class has also witnessed significant increment (+1.91 km2/year) to the peripheral boundary, i.e., southern, southwest/eastern fringes, and central portions under recent initiatives of city forests, plantation drives, and urban green spaces programs. On the contrary, a negative rate of change has been observed in fallow land (−2.78 km2/year), agriculture (−1.22 km2/year), and water bodies (−0.07 km2/year). LULC transition matrix has also showed prominent conversion of fallow land into vegetation and built-up class, and change of vegetation into built-up, and fallow land category. Subsequently, corresponding LULC maps have been superimposed with long-term trends of groundwater depth levels (as spatial contours). For entire South Delhi region, depth to water levels ranged from 2.02 to 66.45 meters below ground level (mbgl) where shallower depths followed a negative trend and remain persistent throughout the time period in north and northeastern fringes. Higher fluctuations in groundwater depletion with positive trends directly get influenced with allied land use transitions such as a steady increase in built-up area and steeper depth levels (> 40 mbgl) as observed in central, southwestern, and southern parts. Moreover, buffer peripheries in the proximity of groundwater monitoring stations viz., Hauz Khas, Pushp Vihar, Jamali, Gadaipur, and Bhatti Kalan have observed deeper groundwater levels allied to built-up expansion. Thus, groundwater depletion trends can be ascribed to the incessant conversion of recharging areas into impervious zones along with uneven distribution of groundwater usage and supply. Conversely, expanding vegetative land has also shown improved groundwater depth levels. Therefore, land use influences must be managed in the long run for ensuring sustainable management of groundwater resources. [ABSTRACT FROM AUTHOR]

Studying the spatiotemporal variability of pollutants is necessary to identify the pollution hotspots with high health risk and enable the agencies to implement pollution abatement strategies in a targeted manner. Present study reports the spatio-temporal variability and health risk assessment (HRA) of PM2.5 (Particulate matter with aerodynamic diameter <2.5μm) and NO2 over IGP from 2019-2021. The HRA is expressed as passively smoked cigarettes (PSC) for four different health outcomes i.e., low birth weight (LBW), percentage decreased lung function (DLF) in school aged children, lung cancer (LC), and cardiovascular mortality (CM). The findings confirm very high PM2.5 and NO2 mass concentrations and high health risk over middle IGP and Delhi as compared to upper and lower IGP. Within Delhi, north Delhi region is the most polluted and at highest risk as compared to central and south Delhi. The health risk associated with PM2.5 over IGP is highest for DLF, equivalent to 21.63 PSCs daily, followed by CM (11.69), LBW (8.27) and LC (6.94). For NO2, the health risk is highest for DLF (3.09 PSCs) and CM (2.95), followed by LC (1.47) and LBW (1.04). PM2.5 and NO2 concentrations, along with the associated health risks, are highest during the post-monsoon and winter seasons and lowest during the monsoon season. [ABSTRACT FROM AUTHOR]

Stubble burning is an emerging environmental issue in Northern India, which has severe implications for the air quality of the region. Although stubble burning occurs twice during a year, first during April–May and again in October–November due to paddy burning, the effects are severe during October–November months. This is exacerbated by the role of meteorological parameters and presence of inversion conditions in the atmosphere. The deterioration in the atmospheric quality can be attributed to the emissions from stubble burning which can be perceived from the changes observed in land use land cover (LULC) pattern, fire events, and sources of aerosol and gaseous pollutants. In addition, wind speed and wind direction also play a role in changing the concentration of pollutants and particulate matter over a specified area. The present study has been carried out for the states of Punjab, Haryana, Delhi, and western Uttar Pradesh to study the influence of stubble burning on the aerosol load of this region of Indo-Gangetic Plains (IGP). In this study, the aerosol level, smoke plume characteristics, long-range transport of pollutants, and affected areas during October–November from year 2016 to 2020 were examined over the Indo-Gangetic Plains (Northern India) region by the satellite observations. By MODIS-FIRMS (Moderate Resolution Imaging Spectroradiometer-Fire Information for Resource Management System) observations, it was revealed that there was an increase in stubble burning events with the highest number of events being observed during the year 2016 and then a decrease in the number of events in subsequent years from 2017 to 2020. MODIS observations revealed a strong AOD gradient from west to east. The prevailing north-westerly winds assist the spread of smoke plumes over Northern India during the peak burning season of October to November. The findings of this study might be used to expand on the atmospheric processes that occur over northern India during the post-monsoon season. The pollutant, smoke plume features, and impacted regions of biomass-burning aerosols in this region are critical for weather and climate research, especially given the rising trend in agricultural burning over the previous two decades. [ABSTRACT FROM AUTHOR]

Methane is an important greenhouse gas, which constitutes minimum 90% of automotive grade compressed natural gas (CNG) used in India. The use of CNG as automotive fuel has been implemented in almost all major tier I to tier III cities of the country. Delhi, the capital city of India, has world largest CNG-fuelled public transport system. The cylinders fitted to the CNG-fuelled vehicles are required to be subjected to hydrostatic stretch test every 3 years at Government of India approved CNG cylinder testing stations, as mandated under Rule 35 of Gas Cylinders Rules, 2016. During the testing of cylinders, CNG present in the cylinders are discharged in the atmosphere at the degassing point of CNG testing stations. This study estimates annual methane emissions from the CNG cylinder testing stations of Delhi. The annual average methane emission from the CNG cylinder testing stations of Delhi was found to be 30.8 tons during the year 2019. The uncertainties in the emission estimate are also identified and discussed. [ABSTRACT FROM AUTHOR]

The rise in urbanization has led to an increase in dust pollution which is hazardous to the health of living beings. The role of roadside plant species in intercepting particulate matter and improving air quality is well reported. Hence, this study was carried out to determine the ability of various plant species to intercept atmospheric dust and withstand the abiotic stress triggered by dust deposition. In the present investigation, three sites (viz., control, commercial, and industrial) differing in anthropogenic activities and vegetation were selected. Sixteen plant species entailing both trees and shrubs that are commonly occurring at all three sites were selected to estimate their dust interception capacity (DIC). The impact of dust pollution on foliage biochemistry and their tolerance in winter and summer seasons were analyzed. Based on biochemical, biological, and socio-economic parameters, air pollution tolerance index (APTI) and anticipated performance index (API) were evaluated. Both dust load and DIC were found to be two times higher in winter than in the summer season. Terminalia arjuna, Ficus benghalensis, and Plumeria alba were the best dust accumulators, while Prosopis juliflora accumulated least. The highest DIC was observed at the industrial site, for Terminalia arjuna (0.025 mg/cm2/d) in winter and Plumeria alba (0.023 mg/cm2/d) in the summer season. Photosynthetic pigments showed a negative correlation with dust load, while pH, ascorbic acid, electrolytic leakage (E.L.), and proline content showed a positive correlation. In the present study, APTI and API values were highest for Ficus religiosa, Ficus benghalensis, Alstonia scholaris, Dalbergia sissoo, and Terminalia arjuna. Such plant species with wide canopy, large and rough leaf surface area with perforated veins are found to be more suitable and, hence, recommended for the development of greenery to improve air quality in urban areas like Delhi. [ABSTRACT FROM AUTHOR]

The accent of the present study is determination of Urban Aerosol Pollution Island (UAPI) intensity and spatial variability in particulate matter concentration (PM10 and PM2.5) over Delhi. For analysis, the hourly concentration dataset of PM2.5 and PM10 from January 2019 to December 2020 was obtained from ten air quality monitoring stations of Delhi. Additionally, UAPI Index has been calculated to assess the intensity of particulate pollution. The daily, monthly, and annual variations in the trends of PM10, PM2.5, and UAPI index along with related meteorological parameters have been analyzed. Particulate pollution peaked majorly during two seasons, i.e., summer and winter. The highest concentration of PM10 was observed to be 426.77 µg/m3 while that of PM2.5 was observed to be 301.91 µg/m3 in January 2019 for traffic-affected regions. During winters, higher PM2.5 concentration was observed which can be ascribed to increased local emissions and enhanced secondary particle formations. While the increase in PM10 concentrations led to an increment in pollution episodes during summers over most of the sites in Delhi. The UAPI index was found to be declining in 2020 over traffic affected regions (77.92 and 27.22 for 2019 and 2020, respectively) as well as in the background regions (64.91 and 19.80 for 2019 and 2020, respectively) of Delhi. Low traffic intensity and reduced pollutant emission could have been responsible for the reduction of UAPI intensity in the year 2020. The result indicates that lockdown implemented to control the COVID-19 outbreak led to an unexpected decrease in the PM10 pollution over Delhi. [ABSTRACT FROM AUTHOR]

Correct and effective performance evaluation of wastewater treatment plants is a tough task because of the complex biological, physico-chemical, and biochemical processes and associated variables affecting their performance. Conventionally, the efficiency of sewage treatment plants (STPs) are obtained using some index relating pollutant removal efficiency with energy used or costs. These indicators consider only one variable at a time. This leads to incorrect assessment of efficiency, which in turn could adversely affect decision-making of the regulatory authorities. The data envelope analysis (DEA) method utilizes a Linear programming technique which can handle multiple input/output variables without requiring the cost function. This makes it an appropriate tool for assessing the relative efficiency of treatment plants. The present study assess the efficiency of 30 STPs in Delhi, India, using the tolerance-based DEA model utilizing the variable return of scale (VRS). The uncertainty was incorporated into the model using the tolerance measure. The model is solved using the "Add on" option in spreadsheet toolbox of excel solver. Results reveal that out of the 30 plants considered for the study, 6 are performing well (20%). Further, it was observed that a slight change in the input data leads to instability of the efficiency results. Lastly, the ranking is used to determine the treatment plant with best efficiency under all scenarios for the larger period of the year. Such studies will help in chalking out the best management practices that could be adopted by other regulatory authorities. [ABSTRACT FROM AUTHOR]

The present study investigates the reduction in nitrogen dioxide (NO2) levels using satellite-based (Sentinel-5P TROPOMI) and ground-based (Central Pollution Control Board) observations of 2020. The lockdown duration, monthly, seasonal and annual changes in NO2 were assessed comparing the similar time period in 2019. The study also examines the role of atmospheric parameters like wind speed, air temperature, relative humidity, solar radiation and atmospheric pressure in altering the monthly and annual values of the pollutant. It was ascertained that there was a mean reduction of ~ 61% (~ 66.5%), ~ 58% (~ 51%) in daily mean NO2 pollution during lockdown phase 1 when compared with similar period of 2019 and pre-lockdown phase in 2020 from ground-based (satellite-based) measurements. April month with ~ 57% (~ 57%), summer season with ~ 48% (~ 32%) decline and an annual reduction of ~ 20% (~ 18%) in tropospheric NO2 values were observed (p < 0.001) compared to similar time periods of 2019. It was assessed that the meteorological parameters remained almost similar during various parts of the year in 2019 and 2020, indicating a negligent role in reducing the values of atmospheric pollution, particularly NO2 in the study area. It was concluded that the halt in anthropogenic activities and associated factors was mainly responsible for the reduced values in the Delhi conglomerate. Similar work can be proposed for other pollutants to holistically describe the pollution scenario as an aftermath of COVID-19-induced lockdown. [ABSTRACT FROM AUTHOR]

Atmospheric concentrations of polycyclic aromatic hydrocarbons (PAHs) in Delhi were evaluated to study particulate PAHs profiles during the different seasons of 2003. Samples of urban suspended particulate matter were collected during January 2003 to December 2003 at three locations (Okhla, Dhaulakuan and Daryaganj), using a high volume sampler provided with glass fiber filters. Samples were analyzed using the gas chromatography technique. The annual average concentrations of total PAHs were found as 1,049.3 ng/m3 at Okhla, 1,344.37 ng/m3 at Daryaganj, and 1,117.14 ng/m3 at Dhaulakuan. The seasonal average concentrations were found to be maximum in winter and minimum during the monsoon season. Principal Component Analysis (PCA) of the data was also carried out and the results indicate that diesel and gasoline driven vehicles are the principal sources of PAHs at all the three sites under investigation. Other sources might come from stationary combustion sources such as cooking fuel combustion and industrial emission. [ABSTRACT FROM AUTHOR]

The River Yamuna in Delhi region, the National Capital Territory (NCT) of India, carries potentially toxic metals such as Cr, Pb, Mn, Mg, Hg, Fe and Zn. These contaminants are discharged mainly from industrial wastes, agricultural and household activities and domestic sewage. A total of 12 stations (2.5 to 3.5 km apart from each other) were selected for the study, covering the upstream and downstream areas of river Yamuna in Delhi. The investigated sites were evaluated for significant difference between upstream and downstream locations of river Yamuna in three different time periods (June, October, February). Metal contamination were measured in water, sediments (2 μm) and nearby agriculture soil of the river Yamuna, and found with high metal loads as compared with the international standards, chiefly in the downstream sites as the river flows through the Delhi stretch. The multivariate statistical analysis revealed spatial and temporal variations in the metal concentrations which suggest seasonal variation and common point source of some metals while different sources of other metals. The contamination of the river water and adjoining agriculture soils points towards possible entry of these metals into the food chain. The study indicates that considering the current status of metal pollution, the surface water is not in good conditions for use as drinking purpose because of the high concentrations of few potentially toxic metals. Our study recommends regular monitoring of toxic metals in Yamuna river water and sediments, strict ban on the domestic, agriculture and industrial waste disposal for the restoration of the river to its natural state. [ABSTRACT FROM AUTHOR]

Land use and land cover changes over 1973–2017 period in peripheral Delhi were mapped based on digital classification of satellite data and their driving forces ascertained. Urban area expanded and agricultural area diminished at annual rates of 38.6% and 2.1%, respectively, during the 1973–2017 period. Urban expansion occurred more in scrub and sparse vegetation areas than in cultivated lands or ponds. Loss of cultivated land happened mostly due to abandonment of cropping and tree planting in farmhouses developed by the urban elites. Improvement in the state of forests in terms of their expansion as well as densification offsets their loss due to urbanisation, encroachment and logging. The increment in the green cover was due to strict enforcement of compensatory afforestation/forest conservation law, growing demand of ecotourism, emergence of tree-clad farmhouses and increased environmental awareness and surveillance. This research will help in comprehending policies favouring sustainable urban development. [ABSTRACT FROM AUTHOR]

Delhi is one of the most polluted cities in the world. The generation of aerosols in the lower atmosphere of the city is mainly due to a large amount of natural dust advection and sizable anthropogenic activities. The compositions of organic compounds in aerosols are highly variable in this region and need to be investigated thoroughly. Twenty-four-hour sampling to assess concentrations of n-alkanes (ng/m) in PM was carried out during January 2015 to June 2015 at Indira Gandhi Delhi Technical University for Women (IGDTUW) Campus, Delhi, India. The total average concentration of n-alkanes, 243.7 ± 5.5 ng/m, along with the diagnostic tools has been calculated. The values of CPI, CPI, and CPI for the whole range of n-alkanes series, petrogenic n-alkanes, and biogenic n-alkanes were 1.00, 1.02, and 1.04, respectively, and C were at C and C. Diagnostic indices and curves indicated that the dominant inputs of n-alkanes are from petrogenic emissions, with lower contribution from biogenic emissions. Significant seasonal variations were observed in average concentrations of n-alkanes, which is comparatively higher in winter (187.4 ± 4.3 ng/m) than during the summer season (56.3 ± 1.1 ng/m). [ABSTRACT FROM AUTHOR]

The study deals with the combined contribution of polycyclic aromatic hydrocarbons (PAHs) and metals to health risk in Delhi soils. Surface soils (0-5 cm) collected from three different land-use regions (industrial, flood-plain and a reference site) in Delhi, India over a period of 1 year were characterized with respect to 16 US Environmental Protection Agency priority PAHs and five trace metals (Zn, Fe, Ni, Cr and Cd). Mean annual ∑PAH concentrations at the industrial and flood-plain sites (10,893.2 ± 2826.4 and 3075.4 ± 948.7 μg/kg, respectively) were ~15 and ~4 times, respectively, higher than reference levels. Significant spatial and seasonal variations were observed for PAHs. Toxicity potentials of industrial and flood-plain soils were ~88 and ~8 times higher than reference levels. Trace metal concentrations in soils also showed marked dependencies on nearness to sources and seasonal effects. Correlation analysis, PAH diagnostic ratios and principal component analysis (PCA) led to the identification of sources such as coal and wood combustion, vehicular and industrial emissions, and atmospheric transport. Metal enrichment in soil and the degree of soil contamination were investigated using enrichment factors and index of geoaccumulation, respectively. Health risk assessment (incremental lifetime cancer risk and hazard index) showed that floodplain soils have potential high risk due to PAHs while industrial soils have potential risks due to both PAHs and Cr. [ABSTRACT FROM AUTHOR]

The present study proposed to investigate the atmospheric distribution, sources, and inhalation health risks of polycyclic aromatic hydrocarbons (PAHs) in a tropical megacity (Delhi, India). To this end, 16 US EPA priority PAHs were measured in the inhalable fraction of atmospheric particles (PM; aerodynamic diameter, ≤10 μm) collected weekly at three residential areas in Delhi from December 2008 to November 2009. Mean annual 24 h PM levels at the sites (166.5-192.3 μg m) were eight to ten times the WHO limit. Weekday/weekend effects on PM and associated PAHs were investigated. ΣPAH concentrations (sum of 16 PAHs analyzed; overall annual mean, 105.3 ng m; overall range, 10.5-511.9 ng m) observed were at least an order of magnitude greater than values reported from European and US cities. Spatial variations in PAHs were influenced by nearness to traffic and thermal power plants while seasonal variation trends showed highest concentrations in winter. Associations between ΣPAHs and various meteorological parameters were investigated. The overall PAH profile was dominated by combustion-derived large-ring species (85-87 %) that were essentially local in origin. Carcinogenic PAHs contributed 58-62 % to ΣPAH loads at the sites. Molecular diagnostic ratios were used for preliminary assessment of PAH sources. Principal component analysis coupled with multiple linear regression-identified vehicular emissions as the predominant source (62-83 %), followed by coal combustion (18-19 %), residential fuel use (19 %), and industrial emissions (16 %). Spatio-temporal variations and time-evolution of source contributions were studied. Inhalation cancer risk assessment showed that a maximum of 39,780 excess cancer cases might occur due to lifetime inhalation exposure to the analyzed PAH concentrations. [ABSTRACT FROM AUTHOR]

Cities across the globe are considered as major anthropogenic sources of greenhouse gases (GHG), yet very few efforts has been made to monitor ambient concentration of GHG in cities, especially in a developing country like India. Here, variations in the ambient concentrations of carbon dioxide (CO) and methane (CH) in residential, commercial, and industrial areas of Delhi are determined from fortnightly daytime observations from July, 2008 to March, 2009. Results indicate that the average daytime ambient concentration of CO varied from 495 to 554 ppm in authorized residential areas, 503 to 621 ppm in the slums or jhuggies in the unauthorized residential areas, 489 to 582 ppm in commercial areas, and 512 to 568 ppm in industrial areas with an average of 541 ± 27 ppm. CH concentration varied from 652 to 5,356 ppbv in authorized residential areas, 500 to15,220 ppbv in the unauthorized residential areas, 921 to 11,000 ppbv in the commercial areas, and 250 to 2,550 ppbv in the industrial areas with an average of 3,226 ± 1,090 ppbv. A low mid-afternoon CO concentration was observed at most of the sites, primarily due to strong biospheric photosynthesis coupled with strong vertical mixing. [ABSTRACT FROM AUTHOR]

The exploration, exploitation, and unscientific management of groundwater resources in the National Capital Territory (NCT) of Delhi, India have posed a serious threat of reduction in quantity and deterioration of quality. The objective of the study is to determine the groundwater quality and to assess the risk of groundwater pollution at Najafgarh, NCT of Delhi. The groundwater quality parameters were analyzed from the existing wells of the Najafgarh and the thematic maps were generated using geostatistical concepts. Ordinary kriging and indicator kriging methods were used as geostatistical approach for preparation of thematic maps of the groundwater quality parameters such as bicarbonate, calcium, chloride, electrical conductivity (EC), magnesium, nitrate, sodium, and sulphate with concentrations equal or greater than their respective groundwater pollution cutoff value. Experimental semivariogram values were fitted well in spherical model for the water quality parameters, such as bicarbonate, chloride, EC, magnesium, sodium, and sulphate and in exponential model for calcium and nitrate. The thematic maps of all the groundwater quality parameters exhibited an increasing trend of pollution from the northern and western part of the study area towards the southern and eastern part. The concentration was highest at the southernmost part of the study area but it could not reflect correctly the groundwater pollution status. The indicator kriging method is useful to assess the risk of groundwater pollution by giving the conditional probability of concentrations of different chemical parameters exceeding their cutoff values. Thus, risk assessment of groundwater pollution is useful for proper management of groundwater resources and minimizing the pollution threat. [ABSTRACT FROM AUTHOR]

Water quality monitoring exercise was carried out with water quality index (WQI) method by using water characteristics data for bore wells and a water treatment plant in Delhi city from December 2006 to August 2007. The water treatment plant received surface water as raw water, and product water is supplied after treatment. The WQI is used to classify water quality as excellent, good, medium, bad, and very bad. The National Sanitation Foundation WQI procedure was used to calculate the WQI. The index ranges from 0 to 100, where 100 represents an excellent water quality condition. Water samples were collected monthly from a bore well in Nehru Camp (site 1), a bore well in Sanjay Gandhi pumping station (site 2), and water treatment plant in Haiderpur (site 3). Five parameters were analyzed, namely, nitrate, pH, total dissolved solids, turbidity, and temperature. We found that the WQI was around 73–80 in site 3, which corresponds to “good,” and it decreased to 54.32–60.19 and 59.93–70.63 in site 1 and site 2, respectively, indicating that these bore wells were classified as “medium” quality. [ABSTRACT FROM AUTHOR]

The study illustrates the utility of STREAM II as a modeling package to determine the pollution load due to organic matter in the River Yamuna during its course through the National Capital Territory that is Delhi, India. The study was done for a period from 1995–2005. Model simulates the dissolved oxygen and biochemical oxygen demand parameters in a two-dimensional fashion by performing the numerical solution to a set of differential equations representing aquatic life with the help of Crank–Nicholson finite difference method. The model was simulated and calibrated through the field water-quality primary data and the secondary data which were taken from Central Pollution Control Board. The main reasons for the high river pollution is increasing population of Delhi and other states, leading to generation of huge amounts of domestic sewage into the river Yamuna. The model gave a good agreement between calibrated and observed data, thus, actualizing the validity of the model. However, discrepancies noticed during model calibrations were attributed to the assumptions adopted in the model formulation and to lack of field data. [ABSTRACT FROM AUTHOR]

Physical, chemical and microbiological efficiencies of Sewage Treatment Plants (STPs) located in Delhi’s watershed in context of different treatment technologies employed in these plants have been determined. There were in all seventeen STPs treating domestic wastewater which were studied over a period of 12 months. These STPs were based on Conventional Activated sludge process (ASP), Extended aeration (Ex. Aeration), physical, chemical and biological removal treatment (BIOFORE) and oxidation pond treatment process. Results suggests that except “Mehrauli” STP which was based on Extended aeration process and “Oxidation pond”, effluents from all other STPs exceeded FC standard of 103 MPN/100 ml for unrestricted irrigation criteria set by National river conservation directorate (NRCD). Actual integrated efficiency (IEa) of each STP was evaluated and compared with the standard integrated efficiency (IEs) based upon physical, biological and microbiological removal efficiencies depending upon influent sewage characteristics. The best results were obtained for STPs employing extended aeration, BIOFORE and oxidation pond treatment process thus can be safely used for irrigation purposes. [ABSTRACT FROM AUTHOR]

Urban areas are facing increasing fog frequencies that may result due to increased air pollution emanating from variety of sources. The increased pollution levels may lead to the atmospheric reactions resulting into the formation of secondary pollutants that may also lead to increased aerosol number concentrations (ANC) in the atmosphere. This could cause enhanced water aerosols in the presence of favourable meteorological conditions and high relative humidity. This study deals with the atmospheric pollution and visibility during winter season of megacity Delhi in order to assess the relationship between the two specifically during fog episodes. Thus, this study analyses the levels of air pollutants, aerosol spectrum and meteorological conditions during one week each in the winter season of the years 2004 and 2006 in order to have an improved understanding of their role in fog formation in mega-city Delhi. More than 300 h of measurements which included episodes of dense, thick and moderate fogs of about 25 h, were studied. The measurements cover most of the accumulation mode and greater size spectrum of aerosols. Thus, the analysis is performed for the entire period, specifically, before the fog sets up, during and afterwards. In general, the relatively small variations in number concentration show larger variations in visibility prior and post dense fog formation than during dense fog episodes. Preliminary analysis of monthly averaged RSPM (Respirable Suspended particulate Matter or PM10) concentration values for four winter months for a period of 6 years (1996–2001) and visibility did not show a good correlation with total occurrences of fog. However, daily averaged RSPM concentration showed a good correlation with the occurrences of thick fog. Diurnal variation of Sulfur-dioxide and Nitrogen dioxide were found to have inverse relationship with visibility during fog which may be due to formation of secondary pollutants such as sulfate and to a lesser extent nitrates. Amongst, the daily averaged concentrations of all the criteria pollutants, RSPM was found to be best correlated with the fog in comparison to other pollutants. [ABSTRACT FROM AUTHOR]

Scanning electron microscopy-energy dispersive X-ray analysis (SEM-EDX) was used to understand the differences in morphology, elemental composition and particle density of aerosols in different five size ranges to further investigate the potential sources as well as transport of pollutants from/at a much polluted and a very clean area of Delhi. Aerosol samples were obtained in five different size ranges viz. ≥10.9, 10.9–5.4, 5.4–1.6, 1.6–0.7 and ≤0.7 μm from a considerably very clean and a much polluted area of Delhi. It was observed that at polluted area most of the particles irrespective of size are of anthropogenic origin. At clean area, in coarse size fractions particles are of natural origin while in fine size range the presence of anthropogenic particles suggests the transport of particles from one area to the other. [ABSTRACT FROM AUTHOR]

The use of alternative fuel is considered to be an effective measure to improve the urban air quality. Concerned over deteriorating air quality in Delhi, the Delhi government initiated different measures including stringent emission norms, improved fuel quality and above all introduction of cleaner fuel-CNG in public transport system. The entire city bus fleet was converted to CNG mode by 2002. The present study reports the comparative assessment of the status of air quality with respect to PM10 and PAH before and after the introduction of CNG in public transport system in Delhi. The study has been carried out for two different time periods: first in the year 1998 and second in the year 2004. Following the total conversion of public transport system to CNG in 2002, Post-CNG data indicate a sharp reduction of 51–74% in the PM10 concentration and 58–68% in the TPAH concentration as compared to the Pre-CNG data. [ABSTRACT FROM AUTHOR]

Mass size distributions of total suspended particulate matter (TSPM) was measured from Sep 2002 to April 2003 in indoor kitchen environments of five locations in Jawaharlal Nehru University (JNU), New Delhi, with the help of a high volume cascade impactor. Particulate matters were separated in five different size ranges, i.e. >10.9 μm, 10.9–5.4 μm, 5.4–1.6 μm, 1.6–0.7 μm and <0.7 μm. The particle size distribution at various sites appears to follow uni-modal trend corresponding to fine particles i.e. size range <0.7 μm. The contributions of fine particles are estimated to be approximately 50% of TSPM and PM10.9, while PM10.9 comprises 80% of TSPM. Good correlations were observed between various size fractions. Regression results reveal that TSPM can adequately act as a surrogate for PM10.9 and fine particles, while PM10.9 can also act as surrogate for fine particles. The concentrations of heavy metals are found to be dominantly associated with fine particles. However, the concentration of some metals and their size distribution, to some extent is also site specific (fuel type used). [ABSTRACT FROM AUTHOR]

The study focuses on assessing the status of respiratory morbidity in Delhi over a four years period from 2000–2003. An attempt was made to investigate the role of important pollutants (SO2, NO2, SPM and RSPM) and various meteorological factors (temperature minimum & maximum, relative humidity at 0830 and 1730 hrs. and wind speed) in being responsible for respiratory admissions on account of COPD, asthma and emphysema. The study showed that winter months had greater exposure risk as pollutants often get trapped in the lower layers of atmosphere resulting in high concentrations. Statistical analysis revealed that two pollutants have significant positive correlation with the number of COPD cases viz., SPM ( r = 0.474; p < 0.01) and RSPM ( r = 0.353; p < 0.05), while a meteorological factor temperature (minimum) has a significant negative correlation ( r = −0.318; p < 0.05) with COPD. Stepwise multiple regression analysis was performed for COPD as dependent variable and R2 value of 0.33 was obtained indicating that SPM and RH(1730) were able to explain 33 percent variability in COPD. The partial correlation of SPM and RH(1730) on COPD was higher than any other combination and therefore they can be regarded as important contributing variables on COPD. [ABSTRACT FROM AUTHOR]

The variability of pollutants is an important factor in determining human exposure to the chemicals. This study presents the result of investigation of variability of Volatile organic compounds (VOCs) in urban area of Delhi, capital of India. Fifteen locations, in five categories namely residential, commercial, industrial, traffic intersections and petrol pump were monitored for one year every month during peak hours in morning and evening. Measurement focused on target VOCs as defined by USEPA. Variability was divided into measurement, spatial, temporal and temporal–spatial interaction components. Temporal component along with temporal–spatial interaction were found to be the major contributors to the variability of measured VOC concentrations. Need of continuous monitoring to capture short–term peak concentration and averages is evident. [ABSTRACT FROM AUTHOR]

The levels of Suspended Particulate Matter (SPM) and heavy metals viz. Pb, Cd, Cr, Ni and Fe were measured. Aerosol samples from four different locations in Delhi were collected by High-volume samplers for a period of one year from July 1997 June 1998. Metal concentration was determined by Atomic Absorption Spectrometry. The annual average concentration of SPM in Delhi was found to be 416.34 ± 223 μg m-3. The atmospheric aerosol samples were highly enriched with elements viz. Pb and Cd, which originate from various human activities like transportation and industrial processes. Principal Component Analysis (PCA) showed vehicular traffic and industrial emission as the major contributors of metals. The annual average concentration of Pb did not exceed the national standard of 0.75 μg m-3. [ABSTRACT FROM AUTHOR]

The noise status of growing urban centres of the country are very much required to develop acoustic design and planning guidelines for various land use classification. An attempt in this direction has been made by measuring noise equivalent levels for cities like Delhi, Jamshedpur, Dehradun and Nagpur. The choice of Ldn (Day–Night noise level) which is a better descriptor of noise quality provides an interesting status of noise in these urban centres. It has been observed that maximum percentage of areas in Delhi and Jamshedpur fall under moderately severe to very severe noisy conditions as compared to Dehradun and Nagpur on the noise rating scale. Ways and means are also considered for mitigation of noise. [ABSTRACT FROM AUTHOR]

The objective of this study was to obtain preliminary evidence of metal-based nanoparticle (NP) occurrence in Delhi (India). Six sampling locations (inlets and outlets of two different municipal wastewater treatment plants (WWTPs), groundwater, and river water) were collected in three independent sampling events. Microscopic analysis (TEM) found majority (40%) of the particles ranged between 150 and 200 nm followed by particles of size 100-150 nm (22%) at the inlet of WWTP, while at outlet, 90% of the particles were < 100 nm. Compared with the outlet of the WWTPs, particles at the inlet were found to be greater than 40%. Intensity-based particle size distribution (PSD) revealed particle size at influent in the range of 210 nm, while at effluent, particle size for both WWTPs ranged < 100 nm. Particles of size between 100 and 200 nm were found to get removed from both the treatment plants and thus making it evident that NP gets settled or adsorbed in sludge. Spectral analysis (EDX) further confirmed the presence of metals such as Al, As, Ag, Mn, Fe, Ti, and Zn at different weight percentages. Overall, findings of this study confirmed the presence of metal-based engineered NPs (ENPs) from anthropogenic sources and it cannot also be ruled out the possible formation of NPs within the wastewater from natural minerals. Moreover, to solve definitive clues for ascertaining the sources of NPs in complex samples, more sophisticated research techniques, such as inductively coupled plasma-mass spectrometry (ICP-MS) in combination with field flow fractionation, single-particle ICP-MS, and radio-labeling in combination or in single should be considered. [ABSTRACT FROM AUTHOR]