Assessment of an accidental vapour cloud explosion: Lessons from the Indian Oil Corporation Ltd. accident at Jaipur,India

On 29 October 2009, at 19:30 IST, a devastating vapour cloud explosion occurred in a large fuel storage area at the Indian Oil Corporation (IOC) Depot in Jaipur, India, generating significant blast pressure. As a consequence of this explosion, the entire installation was destroyed, buildings in the immediate vicinity were heavily damaged, and windowpane breakages were found up to 2 km from the terminal. The IOC estimated that the total loss from the fire and explosion was approximately INR 2800 million.Ironically, as a storage site, the Jaipur terminal was not highly congested, and thus was not considered to have adequate potential for a vapour cloud explosion (VCE). Nevertheless, the prima facie evidences indicate that this was a case of VCE. Therefore, the main objective of this study is to quantify the potential overpressures due to vapour cloud explosions (VCEs) using the Process Hazard Analysis DNV Norway based PHAST 6.51 Software. The results are validated by the extent of the damage that had occurred. The estimation of the VCE shows that a maximum 1.0 bar overpressure was generated in the surrounding area. The initial assessment of the accident data roughly estimates the release mode, time, and amount of vaporized fuel. A more accurate estimate has been obtained by modelling the dispersion of vapour clouds in the surrounding atmosphere, which reveals trends and relationships for the occurrence of vapour cloud explosions.     

Human health risks in megacities due to air pollution

This study evaluates the health risks in megacities in terms of mortality and morbidity due to air pollution. A new spreadsheet model, Risk of Mortality/Morbidity due to Air Pollution (Ri-MAP), is used to estimate the excess numbers of deaths and illnesses. By adopting the World Health Organization (WHO) guideline concentrations for the air pollutants SO₂, NO₂ and total suspended particles (TSP), concentration-response relationships and a population attributable-risk proportion concept are employed. Results suggest that some megacities like Los Angeles, New York, Osaka Kobe, Sao Paulo and Tokyo have very low excess cases in total mortality from these pollutants. In contrast, the approximate numbers of cases is highest in Karachi (15,000/yr) characterized by a very high concentration of total TSP (～670 μg m^?3). Dhaka (7000/yr), Beijing (5500/yr), Karachi (5200/yr), Cairo (5000/yr) and Delhi (3500/yr) rank highest with cardiovascular mortality. The morbidity (hospital admissions) due to Chronic Obstructive Pulmonary Disease (COPD) follows the tendency of cardiovascular mortality. Dhaka and Karachi lead the rankings, having about 2100/yr excess cases, while Osaka-Kobe (～20/yr) and Sao Paulo (～50/yr) are at the low end of all megacities considered. Since air pollution is increasing in many megacities, and our database of measured pollutants is limited to the period up to 2000 and does not include all relevant components (e.g. O₃), these numbers should be interpreted as lower limits. South Asian megacities most urgently need improvement of air quality to prevent excess mortality and morbidity due to exceptionally high levels of air pollution. The risk estimates obtained from Ri-MAP present a realistic baseline evaluation for the consequences of ambient air pollution in comparison to simple air quality indices, and can be expanded and improved in parallel with the development of air pollution monitoring networks.     

Role of meteorology in seasonality of air pollution in megacity Delhi,India

The winters in megacity Delhi are harsh, smoggy, foggy, and highly polluted. The pollution levels are approximately two to three times those monitored in the summer months, and the severity is felt not only in the health department but also in the transportation department, with regular delays at airport operations and series of minor and major accidents across the road corridors. The impacts felt across the city are both manmade (due to the fuel burning) and natural (due to the meteorological setting), and it is hard to distinguish their respective proportions. Over the last decade, the city has gained from timely interventions to control pollution, and yet, the pollution levels are as bad as the previous year, especially for the fine particulates, the most harmful of the criteria pollutants, with a daily 2009 average of 80 to 100 μg/m³. In this paper, the role of meteorology is studied using a Lagrangian model called Atmospheric Transport Modeling System in tracer mode to better understand the seasonality of pollution in Delhi. A clear conclusion is that irrespective of constant emissions over each month, the estimated tracer concentrations are invariably 40% to 80% higher in the winter months (November, December, and January) and 10% to 60% lower in the summer months (May, June, and July), when compared to annual average for that year. Along with monitoring and source apportionment studies, this paper presents a way to communicate complex physical characteristics of atmospheric modeling in simplistic manner and to further elaborate linkages between local meteorology and pollution.     

Potential health risks due to toxic contamination in the ambient environment of certain Indian states

Toxic or hazardous substances pose two types of risks in the environment, namely `short-term or acute risk' and `long-termor chronic risk'. The short-term risk is associated with the one-time acute exposure to potentially hazardous substancesaccidentally released in the environment, whereas the long-termrisk is resulted from continuous exposure to potentially harmfulsubstances present in different environmental media. This articledeals with the assessment of potential health risks related to certain carcinogens and non-carcinogens (e.g. cadmium, chromiumand nickel) present in three environmental media, viz. air, waterand food in different Indian states (regions). Appropriate dose-response models have been identified and used for this purpose with the assumptions and input data as per the Indian context. Mean values of ambient air concentration levels of Cd,Cr and Ni have been used to estimate the individual and societalrisks of extra cancer in different states of India. The hazardquotients and hazard index representing the non-carcinogenic chronic health effects caused by chromium and cadmium due to their long-term exposure through water and food have also beenestimated. The risk results have been compared with the diseasesurveillance data. A definite correlation between the estimatedrisk results and the reported number of lung cancer cases and chronic liver diseases have been observed in different regions. As a matter of fact, it is not possible to derive precise risk estimates due to various uncertainties included both in availabledata and in the models which are used to calculate potency factors and effective concentration. However, average risk levelsas estimated and presented in this article are quite useful forplanning purposes.     

Seasonal trends,meteorological impacts,and associated health risks with atmospheric concentrations of gaseous pollutants at an Indian coastal city

This study presents surface ozone (O₃) and carbon monoxide (CO) measurements conducted at Bhubaneswar from December 2010 to November 2012 and attempts for the very first time a health risk assessment of the atmospheric trace gases. Seasonal variation in average 24 h O₃ and CO shows a distinct winter (December to February) maxima of 38.98?±?9.32 and 604.51?±?145.91 ppbv, respectively. O₃ and CO characteristics and their distribution were studied in the form of seasonal/diurnal variations, air flow patterns, inversion conditions, and meteorological parameters. The observed winter high is likely due to higher regional emissions, the presence of a shallower boundary layer, and long-range transport of pollutants from the Indo-Gangetic Plain (IGP). Large differences between daytime and nighttime O₃ values during winter compared to other seasons suggest that photochemistry is much more active on this site during winter. O₃ and CO observations are classified in continental and marine air masses, and continental influence is estimated to increase O₃ and CO by up to 20 and 120 ppbv, respectively. Correlation studies between O₃ and CO in various seasons indicated the role of CO as one of the O₃ precursors. Health risk estimates predict 48 cases of total premature mortality in adults due to ambient tropospheric O₃ during the study period. Comparatively low CO concentrations at the site do not lead to any health effects even during winter. This study highlights the possible health risks associated with O₃ and CO pollution in Bhubaneswar, but these results are derived from point measurements and should be complemented either with regional scale observations or chemical transport models for use in design of mitigation policies.     

A risk-based model to establish threshold planning quantities of hazardous substances

The Threshold Planning Quantity (TPQ) is the minimum quantity of any hazardous substance stored or processed at an industry that can pose a defined level of risk up to a certain distance from the industrial premises should an accidental release occur. These are recommended by the concerned government departments of the respective countries. Often, concerned regulatory authorities focus on simple screening tools to prescribe TPQs of hazardous chemicals rather than on more detailed technical aspects. This is illustrated with the help of TPQs presently administered in India, which are followed based on Control of Industrial Major Accident Hazard regulations of the United Kingdom. In this paper, the risk ranking matrix (RRM) approach is described to evaluate the recommended TPQs and prescribe these for some extremely hazardous chemicals (EHS) commonly used in industries. The RRM presented here is unique in the sense that various acceptable risk criteria are reviewed to appropriately rank the risk potential and provide suitability criteria in terms of individual risk factors and geosocietal risk factors (GSRF). Based on this concept, an attempt has been made to develop a risk-based model to determine the TPQs of various EHS (acrolein, ammonia, chlorine, hydrogen fluoride, and phosgene).     

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.