Impact of Diwali celebrations on urban air and noise quality in Delhi City,India

A study was conducted in the residential areas of Delhi, India, to assess the variation in ambient air quality and ambient noise levels during pre-Diwali month (DM), Diwali day (DD) and post-Diwali month during the period 2006 to 2008. The use of fireworks during DD showed 1.3 to 4.0 times increase in concentration of respirable particulate matter (PM₁₀) and 1.6 to 2.5 times increase in concentration of total suspended particulate matter (TSP) than the concentration during DM. There was a significant increase in sulfur dioxide (SO₂) concentration but the concentration of nitrogen dioxide (NO₂) did not show any considerable variation. Ambient noise level were 1.2 to 1.3 times higher than normal day. The study also showed a strong correlation between PM₁₀ and TSP (R ² ≥ 0.9) and SO₂ and NO₂ (R ² ≥ 0.9) on DD. The correlation between noise level and gaseous pollutant were moderate (R ² ≥ 0.5). The average concentration of the pollutants during DD was found higher in 2007 which could be due to adverse meteorological conditions. The statistical interpretation of data indicated that the celebration of Diwali festival affects the ambient air and noise quality. The study would provide public awareness about the health risks associated with the celebrations of Diwali festival so as to take proper precautions.     

A comparative study of noise levels in some residential,industrial and commercial areas of Delhi

The measurements of noise levels in residential, industrial and commercial areas in the capital city of India, Delhi, were carried out in the month of March and April, 1992. Six sites in residential areas, four in industrial areas and nine in commercial areas were chosen, which were situated in different parts of Delhi. The results of statistical analysis of sound pressure levels show that commercial areas have the highest noise levels followed by industrial and residential areas. Spectral distribution of noise at octave band frequencies have also been presented for the above mentioned areas.     

Prediction of daily ground-level ozone concentration maxima over New Delhi

The pollution levels in New Delhi from industrial, residential, and transportation sources are continuously growing. As one of the major pollutants, ground-level ozone is responsible for various adverse effects on both humans and foliage. The present study aims to predict daily ground-level ozone concentration maxima over a site situated in New Delhi through neural networks (NN) and multiple-regression (MR) analysis. Although these methodologies are case and site specific, they are being developed and used widely. Therefore, to test these methodologies for New Delhi where no such study is available for ground-level ozone, six models have been developed based on NNs and MR using the same input data set. The changes in the performance capability of the two methods are sensitive to the selection of input parameters. The results are encouraging, and remarkable improvements in the performance of the models have been observed.     

Emissions of VOCs at Urban Petrol Retail Distribution Centres in India (Delhi and Mumbai)

Air pollution has assumed gigantic proportion killing almost half a million Asians every year. Urban pollution mainly comprises of emissions from buses, trucks, motorcycle other forms of motorized transport and its supporting activities. As Asia's cities continue to expand the number of vehicles have risen resulting in greater pollution. Fugitive emissions from retail distribution center in urban area constitute a major source. Petrol vapours escape during refueling adding pollutants like benzene, toluene, ethylbenzene and xylene to ambient air. This paper discusses a study on fugitive emissions of Volatile Organic Compounds (VOC) at some refueling station in two metropolitan cities of India, i.e., Mumbai and Delhi. Concentration of VOCs in ambient air at petrol retail distribution center is estimated by using TO-17 method. Concentration of benzene in ambient air in Delhi clearly shows the effect of intervention in use of petroleum and diesel fuel and shift to CNG. Chemical Mass Balance (CMB) model is used to estimate source contributions. At Delhi besides diesel combustion engines, refueling emissions are also major sources. At Mumbai evaporative emissions are found to contribute maximum to Total VOC (TVOC) concentration in ambient air.     

Surface ozone and meteorological condition in a single year at an urban site in central–eastern China

Surface ozone and some meteorological parameters were continuously measured from June 2003 to May 2004 at urban Jinan, China. The levels and variations of surface ozone were studied and the influences of meteorological parameters on ozone were analyzed. Annual and diurnal ozone variation patterns in Jinan both show a typical pattern for polluted urban areas. Daytime ozone concentrations in summer were the highest in the four seasons. However, during nighttime from 2100 to 0600 hours ozone concentrations in spring was higher than that in summer. Daily averaged ozone showed negative correlation with pressure and relative humidity and positive correlation with temperature, total solar radiation, sunshine duration and wind speed during the study period. Further studies show that, solar radiation is a primary influence factor for the daytime variations of ozone concentrations at this site; transport of pollutants by wind could enhance the pollution at this site; precipitation has a significant influence on decreasing surface ozone. A multi-day ozone episode from 16 to 21 June 2003 was observed at this site. Surface meteorological data analysis and backward trajectory computation show that the episode is associated with the influence of typhoon Soudelor, attributing to both local photochemical processes and transport of air pollutants from southeastern coastal region, especially Yangtze River Delta region.     

Study on concentration of ambient NH 3 and interactions with some other ambient trace gases

We present diurnal variation of ambient ammonia (NH₃) in relation with other trace gases (O₃, CO, NO, NO₂, and SO₂) and meteorological parameters at an urban site of Delhi during winter period. For the first time, ambient ammonia (NH₃) was monitored very precisely and continuously using ammonia analyzer, which operates on chemiluminescence method. NH₃ estimation efficiency of the chemiluminescence method (>90%) is much higher than the conventional chemical trapping method (reproducibility 4.5%). Ambient NH₃ concentration reaches its maxima (46.17 ppb) at night and minimum during midday. Result reveals that the ambient ammonia (NH₃) concentration is positively correlated with ambient NO (r ²?=?0.79) and NO₂ (r ²?=?0.91) mixing ratio and negatively correlated with ambient temperature (r ²?=???0.32). Wind direction and wind speed indicates that the nearby (~500 m NW) agricultural fields may be major source of ambient NH₃ at the observational site.     

Development of Noise Simulation Model for Stationary and Mobile Sources: A GIS-Based Approach

In the rapidly urbanizing country like India, the transportation sector is growing rapidly, which lead to overcrowded roads producing air and noise pollution. Noise of a particular region is influenced by the volume of traffic on the highway, in addition to other causative factors like existing infrastructure and industrial setup etc. In the present paper, a geographical information system (GIS)-based noise simulation model has been developed to generate noise levels in Versova region of Mumbai, India. The study area comprises effect of infrastructure, road network, traffic volume, and various mechanical components like sewage pumping station and wastewater treatment facility. Various meteorological parameters and effect of land use and land cover on noise attenuation are also considered in the model. In this way, commutative noise prediction for point as well as mobile sources has been presented in the study. GIS-based noise simulation has been calibrated with observed noise levels during day and night time with correlation of 0.84 and 0.74, respectively.     

Air Quality Assessment in Delhi: Before and After CNG as Fuel

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.     

Mann–Kendall trend of pollutants,temperature and humidity over an urban station of India with forecast verification using different ARIMA models

The purpose of the present research is to identify the trends in the concentrations of few atmospheric pollutants and meteorological parameters over an urban station Kolkata (22° 32′ N; 88° 20′ E), India, during the period from 2002 to 2011 and subsequently develop models for precise forecast of the concentration of the pollutants and the meteorological parameters over the station Kolkata. The pollutants considered in this study are sulphur dioxide (SO₂), nitrogen dioxide (NO₂), particulates of size 10-μm diameters (PM₁₀), carbon monoxide (CO) and tropospheric ozone (O3). The meteorological parameters considered are the surface temperature and relative humidity. The Mann–Kendall, non-parametric statistical analysis is implemented to observe the trends in the data series of the selected parameters. A time series approach with autoregressive integrated moving average (ARIMA) modelling is used to provide daily forecast of the parameters with precision. ARIMA models of different categories; ARIMA (1, 1, 1), ARIMA (0, 2, 2) and ARIMA (2, 1, 2) are considered and the skill of each model is estimated and compared in forecasting the concentration of the atmospheric pollutants and meteorological parameters. The results of the study reveal that the ARIMA (0, 2, 2) is the best statistical model for forecasting the daily concentration of pollutants as well as the meteorological parameters over Kolkata. The result is validated with the observation of 2012.     

Seasonal characteristics of SO2, NO2, and CO emissions in and around the Indo-Gangetic Plain

Anthropogenic emissions of sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and carbon monoxide (CO) exert significant influence on local and regional atmospheric chemistry. Temporal and spatial variability of these gases are investigated using surface measurements by the Central Pollution Control Board (India) during 2005–2009 over six urban locations in and around the Indo-Gangetic Plain (IGP) and supported using the satellite measurements of these gases. The stations chosen are Jodhpur (west of IGP), Delhi (central IGP), Kolkata and Durgapur (eastern IGP), Guwahati (east of IGP), and Nagpur (south of IGP). Among the stations studied, SO₂ concentrations are found to be the highest over Kolkata megacity. Elevated levels of NO₂ occur over the IGP stations of Durgapur, Kolkata, and Delhi. Columnar NO₂ values are also found to be elevated over these regions during winter due to high surface concentrations while columnar SO₂ values show a monsoon maximum. Elevated columnar CO over Guwahati during pre-monsoon are attributed to biomass burning. Statistically significant correlations between columnar NO₂ and surface NO₂ obtained for Delhi, Kolkata, and Durgapur along with very low SO₂ to NO₂ ratios (≤0.2) indicate fossil fuel combustion from mobile sources as major contributors to the ambient air over these regions.     

NARX神经网络模型在昆明市环境空气质量预测中的应用

神经网络模型作为一种重要的手段被广泛应用于数学计算、物理建模、水文模拟、环境预测、人工智能等研究领域。为验证神经网络模型在高原山地城市环境空气质量预测中的作用,以昆明市环境空气自动监测站气象因子和污染物浓度数据为基础,构建NARX神经网络模型,对污染物浓度进行预测。结果表明,基于NARX神经网络建立的预测模型具有很强的非线性动态描述能力,能够对环境空气6参数做出较为准确的预测,其预测浓度相对误差显著低于CMAQ、NAQPMS空气质量数值模式以及LSTM统计模型预测结果。优化后的NARX神经网络对污染物浓度变化趋势的预测较其他几个模式更为敏感。     

Accuracy of bottled drinking water label content

The accurate predictions of ground ozone concentrations are required for proper management, control, and making public warning strategies. Due to the difficulties in handling phenomenological models that are based on complex chemical reactions of ozone production, neural network models gained popularity in the last decade. These models also have some limitations due to problems of overfitting, local minima, and tuning of network parameters. In this study, the predictions of daily maximum ozone concentrations are attempted using support vector machines (SVMs). The comparison between the accuracy of SVM and neural network predictions is performed to evaluate their performance. For this, the daily maximum ozone concentration data observed during 2002–2004 at a site in Delhi is utilized. The models are developed using the available meteorological parameters. The results indicated the promising performance of SVM over neural networks in predicting daily maximum ozone concentrations.     

Preparation and Validation of Gridded Emission Inventory of Criteria Air Pollutants and Identification of Emission Hotspots for Megacity Delhi

Delhi is one of the many megacities struggling with punishing levels of pollution from industrial, residential, and transportation sources. Over the years, pollution abatement in Delhi has become an important constituent of state policies. In the past one decade a lot of policies and regulations have been implemented which have had a noticeable effect on pollution levels. In this context, air quality models provide a powerful tool to study the impact of development plans on the expected air pollution levels and thus aid the regulating and planning authorities in decision-making process. In air quality modeling, emissions in the modeling domain at regular interval are one of the most important inputs. From the annual emission data of over a decade (1990–2000), emission inventory is prepared for the megacity Delhi. Four criteria pollutants namely, CO, SO₂, PM, and NO _x are considered and a gridded emission inventory over Delhi has been prepared taking into account land use pattern, population density, traffic density, industrial areas, etc. A top down approach is used for this purpose. Emission isopleths are drawn and annual emission patterns are discussed mainly for the years 1990, 1996 and 2000. Primary and secondary areas of emission hotspots are identified and emission variations discussed during the study period. Validation of estimated values is desired from the available data. There is a direct relationship of pollution levels and emission strength in a given area. Hence, an attempt has been made to validate the emission inventory for all criteria pollutants by analyzing emissions in various sampling zones with the ambient pollution levels. For validation purpose, the geographical region encompassing the study area (Delhi) has been divided into seven emission zones as per the air quality monitoring stations using Voronoi polygon concept. Dispersion modeling is also used for continuous elevated sources to have the contributing emissions at the ground level to facilitate validation. A good correlation between emission estimates and concentration has been found. Correlation coefficient of 0.82, 0.77, 0.58 and 0.68 for CO, SO₂, PM and NO _x respectively shows a reasonably satisfactory performance of the present estimates.     

PM10 in the ambient air of Chandrapur coal mine and its comparison with other environments

This study compares the ambient air particulate matter (PM10) data of 15 different coal mine environments. For most of these mine environments, the monitoring was carried out by different researchers using respirable dust sampler (RDS) that separates PM10 by centrifugal inertial separation. At two sites — Padmapur and Ghugus (Chandrapur, Maharashtra, India) — mass inertial impaction-based sampler was used for PM10 monitoring. It is observed that the spatiotemporal average value of ambient air PM10 monitored using mass inertial impactor reports relatively higher values (240–372 μg/m³) compared to those monitored using RDS (<227 μg/m³). In order to realize the severity of mine area pollution, it is compared with PM10 values found in an urban area (Delhi, India). It is found that PM10 values in Delhi (using mass inertial impactor) are much higher (300–400 μg/m³) than those reported for the mine environment. The data seems to indicate that the mine environment is relatively cleaner than urban air and therefore raises doubt about the appropriateness of using either mass impactor or RDS for PM10 sampling.     

洛阳市大气污染特征与相关气象要素24小时变化分析

通过对洛阳市环境空气监测资料的统计,归纳出洛阳市区日内24小时环境空气污染变化特征,并结合同步气象观测资料综合分析,找出了二者之间的联系特征。引入气温日较差这一便于观测、预报的气象要素表征空气污染物垂直扩散特征,为今后进行污染预报提供了新的思路。     

Seasonal evaluation and spatial variability of suspended particulate matter in the vicinity of a large coal-fired power station in India—A case study

Coal combustion in the power sector gives rise to the emission of primary and secondary particulate pollutants. Since the emission of pollutants depends on coal quality and combustion technology, and given that transport, transformation and deposition of contaminants depend on regional climatic conditions, specific studies for the power stations is needed to evaluate their environmental impacts. Monitoring of ambient respirable suspended particulate matter (RSPM) and suspended particulate matter (SPM) levels around a large coal-fired power station in India was carried out. The specific objectives were the determination of spatial and seasonal variability in RSPM and SPM levels, and their relationship with meteorological parameters such as wind velocity and relative humidity. The results have shown a marked seasonal trend and spatial variability in RSPM and SPM levels in the study area. Higher concentrations of ambient RSPM and SPM were found in downwind monitoring stations compared to upwind direction. Ratios of RSPM to SPM and correlation coefficient values between RSPM and SPM along with meteorological parameters were also worked out. Relative humidity and wind velocity have shown an inverse relation with particulate deposition pattern.     

Characterization, Source Identification and Apportionment of Selected Metals in TSP in an Urban Atmosphere

To understand the metal distribution characteristics in the atmosphere of urban Islamabad, total suspended particulate (TSP) samples were collected on daily 12 h basis, at Quaid-i-Azam University campus, using high volume sampler. The TSP samples were treated with HNO₃/HClO₄ based wet digestion method for the quantification of eight selected metals; Fe, Zn, Pb, Mn, Cr, Co, Ni and Cd by FAAS method. The monitoring period ran from June 2001 to January 2002, with a total of 194 samples collected on cellulose filters. Effects of different meteorological conditions such as temperature, relative humidity, wind speed and wind direction on selected metal levels were interpreted by means of multivariate statistical approach. Enhanced metal levels for Fe (930 ng/m³), Zn (542 ng/m³) and Pb (210 ng/m³) were found on the mean scale while Mn, Cr, Co and Ni emerged as minor contributors. Statistical correlation study was also conducted and a strong correlation was observed between Pb-Cr (r=0.611). The relative humidity showed some significant influence on atmospheric metal distribution while other meteorological parameters showed weak relationship with TSP metal levels. Regarding the origin of sources of heavy metals in TSP, the statistical procedure identified three source profiles; automobile emissions, industrial/metallurgical units, and natural soil dust. The metal levels were also compared with those reported for other parts of the world which showed that the metal levels in urban atmosphere of Islamabad are in exceedence than those of European industrial and urban sites while comparable with some Asian sites.     

Impact of CNG implementation on PAHs concentration in the ambient air of Delhi: A comparative assessment of pre- and post-CNG scenario

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 PM(10) 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 PM(10) concentration and 58-68% in the TPAH concentration as compared to the Pre-CNG data.     

Vertical ozone variation in the lower troposphere of Delhi

Measurements of ozone in the urban environment of Delhi were carried out at ground level and heights of 23m, 51m, 117m and 153m at four different sites synoptically during 1989–90. A considerable ozone build up was observed all over Delhi and a significant vertical variation in its concentration was observed at all sites. At any given time O₃ levels were lowest at ground level and invariably increased with increasing distance from the ground.