Rashmi S. Patil

A GENERAL FINITE LINE SOURCE MODEL FOR VEHICULAR POLLUTION PREDICTION

Abstract A simple General Finite Line Source Model (GFLSM), based on the Gaussian diffusion equation is formulated so that it could be used for any orientation of wind direction with roadway and also does not have the infinite line source constraint of the General Motors (GM) model. The GFLSM is also modified to predict particulate concentrations by incorporating some simple corrections. The GFLSM, along with some other models viz. GM, CALINE-3 and HIWAY-2, has been applied to predict carbon monoxide (CO) concentrations near two traffic junctions in Bombay city. Staistical analysis of the predicted and observed (coilected by Municipal Corporation of Greater Bombay) CO levels reveals that the GFLSM performs better than other models when the line source is relatively finite in length. The modified GFLSM for particulates along with the GM model has been evaluated against the data base prepared by the New York State Department of Environmental Conservation and it is observed that the new model gives satisfactory results.

A comparison of water quality indices for coastal water.

Abstract The present article discusses and compares five different water quality indices, viz arithmetic water quality index, multiplicative water quality index, unweighted arithmetic water quality index, unweighted multiplicative water quality index, and Harkins water quality index, which were considered for characterizing the coastal water quality at the Jawaharlal Nehru Port Trust, Bombay, India. Dissolved oxygen, pH, biochemical oxygen demand (BOD), temperature, suspended solid, and turbidity were used as the parameters of water quality indices. The value function graphs used for above-mentioned variables were developed using harbour water quality standards and aquatic life. The product moment correlation coefficients for various water quality indices were determined using the SPSS software package to evaluate correlation among various indices. It was found that the unweighted arithmetic water quality index was higher than weighted arithmetic water quality index while the multiplicative water quality index was lower than unweighted multiplicative water quality index. All the indices were well correlated with each other except Harkins water quality index. The Harkins water quality index was different from other water quality indices. The comparison of different form of indices showed that the multiplicative water quality index was the most suitable water quality index for coastal waters.

Monitoring of Daily Integrated Exposure of Outdoor Workers to Respirable Particulate Matter in an Urban Region of India

It is more and more recognised that an estimation of the exposure of the population to air pollutants is more relevant than the ambient air quality, since it gives a better indication of health risk. Outdoor workers in an urban region are generally of low income status and are exposed to higher levels of both indoor and outdoor air pollution. Hence respondents from this population subgroup have been selected for this study. Outdoor workers are divided into two categories, viz. traffic constables and casual outdoor workers like watchmen, roadside shopkeepers etc. Most of the respondents are from the lower income group. Each respondent is monitored for a continuous 48-hour period. The sampling frequency is once a week.The study region is situated in the north-west part of the Greater Mumbai Municipal Corporation. It can be classified as industrial cum residential area. The daily integrated exposure of the outdoor workers consists of two major micro-environments, viz. occupational and indoor residential.A personal air sampler was used along with a cyclone to measure levels of Respirable Particulate Matter (RPM). The cyclone has a 50% removal efficiency for particle diameter of 5 μm. Paired samples of PM10 (ambient) and RPM (personal) were collected to establish the correlation between them. The average 24-hour integrated exposure to RPM was 322 μg/m3 and exceeded the corresponding PM10 level observed at the nearest Ambient Air Quality Monitoring Station by a factor of 2.25. The 90% confidence interval for this exposure is 283–368 μg/m3. This study clearly demonstrates that the daily integrated exposure and therefore the health risk of outdoor workers in an urban area is significantly more serious than that indicated by ambient air quality data.

Cluster analysis of Delhi's ambient air quality data

The purpose of this study was to study the spatial patterns of ambient air quality in Delhi in the absence of extensive datasets needed for space-time modeling. A spatial classification was attempted on the basis of ambient air quality data of nine years (1998 is latest year for which published data were available) for three criteria pollutants--nitrogen dioxide, sulfur dioxide, and suspended particulate matter. Monitoring stations take 24-hour samples twice a week. Published monthly average concentration data were used in this study. A hierarchical agglomerative algorithm using the average linkage between groups method and the Euclidean distance metric was used. Cluster analysis indicated that till 1998, by and large, two distinct classes existed. The results of cluster analysis prompted an investigation of systematic biases in the monitored data. No statistically significant differences in the mean concentration of all pollutants were observed between stations belonging to different land-use types (residential and industrial). This fact would be useful, if and when the authorities consider modifying the network or expanding it in Delhi. The results also support the recommendation that Delhi have a uniform standard across all areas. This study has provided a methodology for Indian researchers and practitioners to do an exploratory study of spatial patterns of air pollution and data quality issues in Indian cities using the National Ambient Air Quality Monitoring System data.

Chemical mass balance model for source apportionment of aerosols in Bombay.

Aerosol samples collected within an industrial region of Bombay were analyzed for elemental concentrations using inductively coupled plasma emission spectroscopy, ultraviolet/visible spectrophotometry and X-ray fluorescence spectroscopy. Nineteen elements were selected as tracers of identified sources of aerosol in the region. The U.S. EPA chemical mass balance model was employed for source apportionment. Seven major source types were identified and the performance of the model was evaluated at different sampling locations. Model results were unsatisfactory at highly polluted sites in the study regions. It was found that U.S. EPA source profiles are not suitable for such regions in India and site-specific source profiles should be used in the application of chemical mass balance for source apportionment.

Emissions of gaseous and particulate pollutants in a port and harbour region in India

Ports can generate large quantity of pollutants in the atmosphere due to various activities like loading and unloading,transportation, and construction operations. Determination of the character and quantity of emissions from individual sources is an essential step in any project to control and minimize the emissions.In this study a detailed emission inventory of total suspendedparticulate matter (TSP), particulate matter less than 10 μm(PM10), sulfur dioxide (SO2) and nitrogen oxides (NOx) for a port and harbour project near Mumbai is compiled. Results show that the total annual average contributions of TSP and PM10 from all the port activitieswere 872 and 221 t yr-1, respectively. Annual average emissions of gaseous pollutants SO2 and NOxwere 56 and 397 t yr-1, respectively, calculatedby using emission factors for different port activities. The maximum TSP emission (419 t yr -1) was from paved roads, while the least (0.4 t yr-1) was from bulk handling activity. The maximum PM10 emission (123 t yr-1) was from unpaved roads and minimum (0.2 t yr-1) from bulk handling operations. Similarly the ratio of TSP and PM10 emission was highest (5.18) from paved roads and least (2.17) from bulk handling operations. Regression relation was derivedfrom existing emission data of TSP and PM10 from variousport activities. Good correlation was observed between TSP andPM10 having regression coefficient >0.8.

Characterization and Proinflammatory Response of Airborne Biological Particles from Wastewater Treatment Plants

Wastewater contains a variety of microorganisms, and unit operations in the plants could release these biological components into the air environment. These airborne biological particles could have adverse health effects on plant workers and the downwind population. This study provides a first report on the concentration and characterization of the airborne biological particles in six wastewater treatment plants in Mumbai, India. The study indicates that 49% and 27% of the samples exceed, respectively, the exposure limit for airborne endotoxin and bacteria in occupational settings. Endotoxin was identified as the single most important component of the particulate matter responsible for induction of proinflammatory indicator (tumor necrosis factor-α) in in vitro assay. Identification of several clinically important bacterial species in the samples suggests that the workers at the treatment plant are exposed to opportunistic and infectious bacteria. Principal component analysis was used to identify the groups among the bacterial species which serves as the signature for transport study. Analysis also shows that the component related to spore-forming bacteria is present in all samples.

Influence of meteorological factors on air pollution concentration for a coastal region in India

A long-term study of measurement of concentration of NOx, SO2 and TSP pollutants have been done in a port and harbour region in India. Monthly measurements of gaseous and particulate pollutants were made at six monitoring stations from January 1997 to December 2000. Meteorological data was also simultaneously collected. In this study, the relationship between monitored ambient air quality data and meteorological factors, such as wind speed, temperature, is statistically analysed, using the SPSS package. The monthly mean concentrations of NOx, SO2 and TSP were in the range of 19.5–59.0 µg/m³, 8.6–51.3 µg/m³ and 88.2–199.3 µg/m³, respectively. The results show that TSP is strongly correlated with NOx and SO2 with a correlation coefficient of 0.83 and 0.82, respectively. The correlation coefficients for TSP, NOx, and SO2 with wind are –0.78, –0.78, and –0.88, respectively.

Particulate Respiratory Dose to Indian Women from Domestic Cooking

Particulate mass size distributions were measured during cooking and non-cooking periods in three Indian urban household kitchens with Liquefied Petroleum Gas as fuel. Based on the measured mass size distributions, fraction of particulate deposition in the respiratory system were calculated for a healthy Indian female using a deterministic lung deposition model. Respiratory physiological data of Indian women were collected from the published data. These physiological parameters were incorporated in the model to determine the particulate deposition in the respiratory system. The cooking generated very high concentration of particles 4 to 5 times more than the non-cooking background periods. Particulate size distributions in both cooking and non-cooking periods showed bimodal characteristics. Cooking process generated particles predominantly in accumulation mode (0.1–0.3 μ m) whereas during non-cooking periods particulates are found in coarse mode (1.0–2.0 μ m). Also, during frying process, the particulates were found to have a predominant coarser/droplet mode 0.7–1.0 μ m. The highest deposition was observed in pulmonary region during cooking periods. The study shows that the daily particulate dose to the urban Indian women from domestic cooking is comparable with the dose resulting from outdoor particulate exposure.

A long-term study of oxides of nitrogen, sulphur dioxide, and ammonia for a port and Harbor region in India

Abstract A long-term study of oxides of nitrogen (NO x ), sulphur dioxide (SO2), and ammonia (NH3) has been performed in a port and harbor region in India from 01 1997 to 12 2000. Meteorological data was also collected to establish the correlation with gaseous pollutants concentrations. Monthly mean concentrations of NO x were in the range of 19.5–59.0 µg/m3 and were observed to be highest during winter season. Monthly mean concentrations of SO2 were in the range of 8.6–51.3 µg/m3 and were observed to be highest during winter season. The concentrations of SO2 increased gradually from 18.8 µg/m3 in 1997 to 33.3 µg/m3 in 2000. This may be attributed to the increase in port activities and ship traffic, which had an annual growth of about 15%. Monthly mean concentrations of NH3 were in the range of 87.1–235.1 µg/m3 and the maximum concentration was observed during post-monsoon season. It may be concluded that NO x and SO2 have their maximum values during winter season while NH3 has a maximum value during post-monsoon season. Statistical analysis was carried out for air pollutant data for the period 1997–2000 and correlation between gaseous pollutants (NO x , SO2, NH3) and meteorological parameters (temperature and wind speed) was estimated. NH3 was found to be weakly correlated with NO x (0.46), strongly correlated with SO2 (0.75) and negatively correlated with wind speed (−0.60). The highest correlation (0.87) was observed between SO2 and NO x because of common sources. A strong negative correlation was found between wind speed and gaseous pollutants. The above finding is also supported by monitoring results that when the wind velocity doubled, the concentrations of pollutants decreased sharply to about a half. Regression analysis showed that relationship among NO x , SO2, wind speed, and temperature was moderate to strong while that among NH3, wind speed, and temperature was poor. Hence regression equations could be developed for predicting NO x and SO2 concentrations.