Rajiv Ganguly

High resolution spatial and temporal mapping of traffic-related air pollutants.

Vehicle traffic is one of the most significant emission sources of air pollutants in urban areas. While the influence of mobile source emissions is felt throughout an urban area, concentrations from mobile emissions can be highest near major roadways. At present, information regarding the spatial and temporal patterns and the share of pollution attributable to traffic-related air pollutants is limited, in part due to concentrations that fall sharply with distance from roadways, as well as the few monitoring sites available in cities. This study uses a newly developed dispersion model (RLINE) and a spatially and temporally resolved emissions inventory to predict hourly PM2.5 and NOx concentrations across Detroit (MI, USA) at very high spatial resolution. Results for annual averages and high pollution days show contrasting patterns, the need for spatially resolved analyses, and the limitations of surrogate metrics like proximity or distance to roads. Data requirements, computational and modeling issues are discussed. High resolution pollutant data enable the identification of pollutant “hotspots”, “project-level” analyses of transportation options, development of exposure measures for epidemiology studies, delineation of vulnerable and susceptible populations, policy analyses examining risks and benefits of mitigation options, and the development of sustainability indicators integrating environmental, social, economic and health information.

Dispersion Modeling of Traffic-Related Air Pollutant Exposures and Health Effects Among Children with Asthma in Detroit, Michigan

Vehicular traffic is a major source of ambient air pollution in urban areas. Traffic-related air pollutants, including carbon monoxide, nitrogen oxides, particulate matter less than 2.5 μm in diameter, and diesel exhaust emissions, have been associated with adverse human health effects, especially in areas near major roads. In addition to emissions from vehicles, ambient concentrations of air pollutants include contributions from stationary sources and background (or regional) sources. Although dispersion models have been widely used to evaluate air quality strategies and policies and can represent the spatial and temporal variation in environments near roads, the use of these models in health studies to estimate air pollutant exposures has been relatively limited. This paper summarizes the modeling system used to estimate exposures in the Near-Roadway Exposure and Urban Air Pollutant Study, an epidemiological study that examined 139 children with asthma or symptoms consistent with asthma, most of whom lived near major roads in Detroit, Michigan. Air pollutant concentrations were estimated with a hybrid modeling framework that included detailed inventories of mobile and stationary sources on local and regional scales; the RLINE, AERMOD, and CMAQ dispersion models; and monitored observations of pollutant concentrations. The temporal and spatial variability in emissions and exposures over the 2.5-year study period and at more than 300 home and school locations was characterized. The paper highlights issues with the development and understanding of the significance of traffic-related exposures through the use of dispersion models in urban-scale exposure assessments and epidemiology studies.

Effect of geocoding errors on traffic-related air pollutant exposure and concentration estimates

Exposure to traffic-related air pollutants is highest very near roads, and thus exposure estimates are sensitive to positional errors. This study evaluates positional and PM2.5 concentration errors that result from the use of automated geocoding methods and from linearized approximations of roads in link-based emission inventories. Two automated geocoders (Bing Map and ArcGIS) along with handheld GPS instruments were used to geocode 160 home locations of children enrolled in an air pollution study investigating effects of traffic-related pollutants in Detroit, Michigan. The average and maximum positional errors using the automated geocoders were 35 and 196 m, respectively. Comparing road edge and road centerline, differences in house-to-highway distances averaged 23 m and reached 82 m. These differences were attributable to road curvature, road width and the presence of ramps, factors that should be considered in proximity measures used either directly as an exposure metric or as inputs to dispersion or other models. Effects of positional errors for the 160 homes on PM2.5 concentrations resulting from traffic-related emissions were predicted using a detailed road network and the RLINE dispersion model. Concentration errors averaged only 9%, but maximum errors reached 54% for annual averages and 87% for maximum 24-h averages. Whereas most geocoding errors appear modest in magnitude, 5% to 20% of residences are expected to have positional errors exceeding 100 m. Such errors can substantially alter exposure estimates near roads because of the dramatic spatial gradients of traffic-related pollutant concentrations. To ensure the accuracy of exposure estimates for traffic-related air pollutants, especially near roads, confirmation of geocoordinates is recommended.

Application of urban street canyon models for predicting vehicular pollution in an urban area in Dublin, Ireland

The relative performance of two atmospheric dispersion models STREET and OSPM is assessed using measured CO and NOx data obtained adjacent to an urban street canyon. This paper in particular, evaluates the performance of STREET, a mathematical model, to determine its suitability as an alternative to the OSPM model, which is a more elaborate numerical model. The performances of the models are tested using composite emission factors calculated as per the speed conditions present on the study site. Two different versions of CEF were used depending upon the speed of the vehicles during daytime and nighttime.

Biomedical Waste Generation and Management in Public Sector Hospital in Shimla City

Biomedical waste disposal is very important due to its infectious nature. Proper management of biomedical waste is necessary for maintaining good human health and environment. Biomedical Waste (Management and Handling) rules 1998 under the Environmental Protection Act, 1986 have been passed by government of India which is to be followed strictly to avoid menace. The purpose of the article is to differentiate between the Biomedical Waste Management practices such as collection, storage, transportation, and disposal along with the generation of biomedical waste undertaken in major public and private sector hospitals in Shimla city. A cross-sectional study and semi-structured interview considering the various biomedical waste management practices and personnel handling of the biomedical waste undertaken in the major public and private sector hospitals in Shimla city through detailed analysis and questionnaire prepared will be used for the purpose of study. The study will quantify the actual values and unveil the difference that lie in management procedures followed by these hospitals in Shimla. The present paper presents some initial findings of the questionnaire analysis carried out in a major public hospital in Shimla.

Comparative Account of Carbon Footprints of Burning Gasoline and Ethanol

Abstract Now days, climate change is one of the tangible issues that have to be solved to avoid major environmental consequences in the near future. Melting of glaciers, rising of sea levels, occurrence of drastic storm and drought conditions, and annual increase in global temperatures are some of the examples of climate change consequences due to the Greenhouse Gas (GHG) emissions by vehicles. The transportation sector is one of the major contributors of GHG emissions from man-made activities which accounts for approximately 14% of emissions globally. Ethanol is one of the transportation fuels as an alternative to the exhausting fossil fuel, gasoline. In view of growing concern about climate change, the analysts analyzing the potential impact of new transportation fuels on climate change for long-term usage are framing certain recommendations to combat the deleterious effects of climate change. This chapter provides an overview of carbon footprints, GHG emissions, climate change, and IPCC recommendations on gasoline and ethanol usage as a transportation fuel.

Indexing method for assessment of pollution potential of leachate from non-engineered landfill sites and its effect on ground water quality

Dumping of solid waste in a non-engineered landfill site often leads to contamination of ground water due to leachate percolation into ground water. The present paper assesses the pollution potential of leachate generated from three non-engineered landfill sites located in the Tricity region (one each in cities of Chandigarh, Mohali and Panchkula) of Northern India and its possible effects of contamination of groundwater. Analysis of physico-chemical properties of leachate from all the three landfill sites and the surrounding groundwater samples from five different downwind distances from each of the landfill sites were collected and tested to determine the leachate pollution index (LPI) and the water quality index (WQI). The Leachate Pollution Index values of 26.1, 27 and 27.8 respectively for landfill sites of Chandigarh (CHD), Mohali (MOH) and Panchkula (PKL) cities showed that the leachate generated are contaminated. The average pH values of the leachate samples over the sampling period (9.2 for CHD, 8.97 for MOH and 8.9 for PKL) show an alkaline nature indicating that all the three landfill sites could be classified as mature to old stage. The WQI calculated over the different downwind distances from the contamination sites showed that the quality of the groundwater improved with an increase in the downwind distance. Principal component analysis (PCA) carried out established major components mainly from natural and anthropogenic sources with cumulative variance of 88% for Chandigarh, 87.1% for Mohali and 87.8% for Panchkula. Hierarchical cluster analysis (HCA) identifies three distinct cluster types for the groundwater samples. These clusters corresponds to a relatively low pollution, moderate pollution and high pollution regions. It is suggested that all the three non-engineered landfill sites be converted to engineered landfill sites to prevent groundwater contamination and also new sites be considered for construction of these engineered landfill sites as the present dumpsites are nearing the end of their lifespan capacity.

Application of Rain Water Harvesting Scheme in Shimla Region

Rainwater harvesting is an innovative and a suitable alternative approach of water supply that can be used by anyone. Rainwater harvesting captures, diverts, and stores rainwater for later use. It is a well known fact that during summer season there is a huge scarcity of water in northern regions of India and as such implementing rainwater harvesting would be beneficial because it would reduce demand on existing water supply reduces run-off, erosion, and also contamination of surface water. A rainwater harvesting system can range in size and complexity. All systems have basics components, which include a catchment surface, conveyance system, storage, distribution, and treatment. As such, we discuss in this paper about the prospects and possibilities of rainwater harvesting in Shimla region of Himachal Pradesh, which experience water shortages in summer periods due to increase in population and also climatic conditions. The result of our study shows that judicious storing of rain water all round the year and not only summer can be stored without incurring any significant losses. Further, the study shows that the sanitation water requirements for a family can be met for two months with storage of rainwater for one single month only. Further, the construction pattern of houses in Shimla (sloped roof structures) already provides an advantage in storing rainwater efficiently. The non-dimensional design parameters can be applied for any place which experiences a scarcity of water. The paper also presents a simple benefit-cost ratio for the designed rainwater harvesting system.

Performance evaluation of a general finite line source model for NOx concentrations obtained from a motorway in Ireland

The relative performance of a general finite line source model (GFLSM) is assessed using measured NOx concentrationsobtained adjacent to an urban motorway using CEF and HEF. The predicted concentrations are compared with monitored concentrations obtained over a continuous sampling period of one year. Statistical and graphical analyses of the monitored and modelled data are employed to evaluate model performance. It is observed that the values predicted by the GFLSM generally agree well with the monitored data. The effect of background concentrations on model performance is studied and anovel way of defining background concentrations leading to improved model performance of the model is suggested.