Mukesh Khare

The Lancet Commission on pollution and health

Philip J Landrigan, Richard Fuller, Nereus J R Acosta, Olusoji Adeyi, Robert Arnold, Niladri (Nil) Basu, Abdoulaye Bibi Baldé, Roberto Bertollini, Stephan Bose-O’Reilly, Jo Ivey Boufford, Patrick N Breysse, Thomas Chiles, Chulabhorn Mahidol, Awa M Coll-Seck, Maureen L Cropper, Julius Fobil, Valentin Fuster, Michael Greenstone, Andy Haines, David Hanrahan, David Hunter, Mukesh Khare, Alan Krupnick, Bruce Lanphear, Bindu Lohani, Keith Martin, Karen V Mathiasen, Maureen A McTeer, Christopher J L Murray, Johanita D Ndahimananjara, Frederica Perera, Janez Potočnik, Alexander S Preker, Jairam Ramesh, Johan Rockström, Carlos Salinas, Leona D Samson, Karti Sandilya, Peter D Sly, Kirk R Smith, Achim Steiner, Richard B Stewart, William A Suk, Onno C P van Schayck, Gautam N Yadama, Kandeh Yumkella, Ma Zhong

Modelling of vehicular exhausts – a review

Abstract A review of the air pollution studies carried out to study the dispersion of vehicular exhaust emissions (VEEs) has been made. The review includes the modelling studies in the domain, primarily, of analytical modelling – deterministic mathematical models and numerical models, and statistical models. Various model performance evaluation and comparative assessment studies have also been discussed. Further, the studies conducted to model VEEs at the urban road intersection and urban street canyons have also been reviewed.

Line source emission modelling

Abstract Line source emission modelling is an important tool in control and management of vehicular exhaust emissions (VEEs) in urban environment. The US Environmental Protection Agency and many other research institutes have developed a number of line source models (LSMs) to describe temporal and spatial distribution of VEEs on roadways. Most of these models are either deterministic and/or statistical in nature. This paper presents a review of LSMs used in carrying out dispersion studies of VEEs, based on deterministic, numerical, statistical and artificial neural network techniques. The limitations associated with deterministic and statistical approach are also discussed.

Urban air quality management-A review

Urban air quality management plan (UAQMP) is an effective and efficient tool employed in managing acceptable urban air quality. However, the UAQM practices are specific to a country’s needs and requirements. Majority of the developed countries have full–fledged UAQMP with a regulatory management framework. However, developing countries are still working in formulating the effective and efficient UAQMPs to manage their deteriorating urban air environment. The first step in the process of formulation of UAQMP is to identify the air quality control regions based on ambient air quality status and second, initiate a time bound program involving all stakeholders to develop UAQMPs. The successful implementation of UAQMPs depends on the strength of its key components, e.g. goal/objective, monitoring network, emission inventory, air quality modeling, control strategies and public participation. This paper presents a comprehensive review on UAQMPs, being implemented worldwide at different scales e.g., national (macro), city (medium), and local (micro).

Performance evaluation of general finite line source model for Delhi traffic conditions

Abstract The applicability of General Finite Line Source Model (GFLSM), based on the Gaussian diffusion equation, was assessed by comparing predicted CO concentrations with the measured values obtained from the experiments conducted by Central Pollution Control Board (CPCB), New Delhi, India at three traffic intersections in the Delhi city. Using the CPCB data, a Delhi Finite Line Source Model (DFLSM) has been developed by modifying the GFLSM, considering the existing traffic and meteorological conditions in the Delhi city. The predicted and observed CO concentration data reveals that the DFLSM model works more accurately for the existing traffic and meteorological conditions in the Delhi city in comparison to the GFLSM.

Application of extreme value theory for predicting violations of air quality standards for an urban road intersection

Abstract Extreme value theory (EVT) has been used for making predictions of the expected number of violations of the National Ambient Air Quality Standards (NAAQS) as prescribed by the Central Pollution Control Board (CPCB), India, for hourly- and eight-hourly average carbon monoxide(CO) concentration for an Air Quality Control Region (AQCR) comprising of an urban road intersection. Almost 100% contribution to the CO pollution in the region is due to vehicular traffic. The parameters of the extreme value distribution (EVD) have been estimated by four methods viz. method of moments, maximum likelihood, least square fit and Gumbels fitting method. Least square fit and Gumbels method gave the best fit and predictions. A comparison of the predicted violations of NAAQS and the exceedence of the maximum pollution concentration with that of the observed data suggests that the theory performs satisfactorily for the extreme air pollution events.

Statistical behavior of carbon monoxide from vehicular exhausts in urban environments

Abstract Air pollutant concentrations are essentially random variables and can be well described by statistical distribution models. The statistical distribution models are, therefore, useful tools in predicting the distribution of air pollutant concentrations. The statistical distributional form, fitting to the concentrations data, is based upon several factors, i.e. source types, pollutant types, emission patterns, meteorological conditions, and averaging times [Taylor, J.A., Jakeman, A.J., Simpson, R.W., 1986. Modeling distributions of air pollutant concentrations – I: identification of statistical models. Atmospheric Environment 20 (9), 1781–1789]. The statistical characteristics of dispersion of air pollutants in the atmosphere are represented by successive random dilution process [Ott, W.R., 1995. Environmental Statistics and Data Analysis. Lewis publishers]. This process may, however, differ depending upon the location of pollutant dispersion, i.e. near roadways, at intersections or in street canyons. Further, the distributional form may also differ. Several investigators, in the past, presumed lognormal distribution (LND) for the air quality data. While, a few found other distributional form when carried out the actual data analysis. The present paper develops the statistical distribution model fitting to carbon monoxide (CO) concentrations for the heterogeneous traffic pattern at the urban hotspots in Delhi, India. Three years of 1-h average CO concentration data (from 1997 to 1999), at the traffic intersection and near a roadway, are examined using goodness-of-fit tests for the suitable statistical distributional form. The results showed that the log logistic distribution model (LLD) best fit the CO concentration data at both the intersection and the roadway. It can therefore be deduced that ‘heterogeneity in traffic’ and ‘emission patterns’ may be affecting the statistical distributional form significantly.

PRINCIPAL COMPONENT ANALYSIS OF URBAN TRAFFIC CHARACTERISTICS AND METEOROLOGICAL DATA

Abstract Principal component analysis (PCA) is used to analyze one-year traffic, emission and meteorological data for an urban intersection in the Delhi. The 1997 data include meteorological, traffic and emission variables. In urban intersections the complexities of site, traffic and meteorological characteristic may result in a high cross correlation among the variables. In such situations, PCA can provide an independent linear combination of the variables. Here it is used to analyze 1, 8 and 24 h average emission, traffic and meteorological data. It shows that four principal components for the 24 h average have the highest loadings for traffic and emission variables with a strong correlation between them. PC loadings for the 1 and 8 h data indicate the least variation among them.

Model vehicle movement system in wind tunnels for exhaust dispersion studies under various urban street configurations

Abstract The exhaust dispersion in the close vicinity of urban roadways and intersections takes place under the joint influence of natural and vehicle-induced turbulence. The physical simulation studies of vehicular exhaust using wind tunnels have shown high potential to understand complex dispersion mechanisms. One of the vital components of simulation in the environmental wind tunnel (EWT) is the design of model vehicle movement system (MVMS). An efficient design of MVMS is a foremost requirement for carrying out exhaust dispersion studies in the EWT, otherwise it may adversely affect the atmospheric boundary layer. Therefore, an attempt has been made to critically review the previously used MVMS in exhaust dispersion studies. Further, sophisticated MVMS with real traffic situation for urban streets at various configurations has been designed and developed. The MVMS for urban streets and intersection has been successfully operated for variable traffic volume and speed as seen in real life situation. In addition, multi-lane traffic for two-way urban roads has also been successfully operated. The dispersion results revealed that the traffic induced turbulence at low wind condition causes considerable amount of pollutant reduction in urban street canyon surrounded by high-rise buildings.

Indoor exploratory analysis of gaseous pollutants and respirable particulate matter at residential homes of Delhi, India

Abstract Biomass fuels are frequently used as a source of domestic energy in developing countries that may cause indoor air pollution. This study presents indoor and outdoor combustion pollutants (CO and NO x ) and respirable particulate matter–RSPM (PM 10 , PM 2.5 and PM 1.0 ) concentrations measured during winter and summer seasons in 8 homes in Delhi, India. CO 2 concentrations have been used to measure the outdoor airflow rates. This study further investigates variations in indoor/outdoor concentrations of the pollutants as a result of various activities in commercial (Site I) and institutional areas (Site II). The institutional area has been considered as the control site. Monitoring has been conducted at each site for 3 days in a week in both summer and winter seasons to investigate the diurnal variations of pollutant concentrations. Then, the I/O ratios have also been estimated. The correlation analysis of indoor pollutant concentrations with outdoor concentrations has been carried out. Winter/Summer (W/S) ratios have also been calculated and a two tailed t–test has been used to determine whether the winter and summer mean concentrations are significantly higher. The I/O ratios for PM 10 , PM 2.5 and PM 1.0 at Site I homes, in winter season, have been found to be 1.43±0.84, 2.72±1.94 and 3.21±2.39, respectively. I/O ratio for CO has been found to be 2.99±2.19 in winters at Site I. The linear regression analysis results have revealed that usage of biomass fuels for cooking has increased the concentrations of RSPM and CO indoors, considerably in winter. W/S ratios for RSPM have also been found to be higher than 1.0 at almost all the homes indicating that the concentration of RSPM is higher in winter season. Regression analysis results indicated that the major sources for RSPM and CO exist indoors and that is principally, cooking using the biomass as fuels and also cleaning of homes manually, particularly at commercial site (NZM site). The results of this study also suggest that the indoor RSPM concentrations are mainly composed of the finer range of particles.