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.     

Integration of modeling,monitoring and laboratory observation to determine reasons for air quality violations

An attempt was made to explain ambient air quality violations in the vicinity of industrial plants. Micrometeorology, diffusion calculaations, ambient readings, and plant engineering data are all taken into consideration to ascertain whether the plant is or is not the principal offender.Scrutiny of hi-vol filters using scanning electron microscopy for particle size analysis and particle chemical make-up as an assessment technique is also described.Case histories using the above analytical techniques are discussed.Presented at the 16th National Conference on Energy and the Environment, May 23, 1979     

Development of baseline (air quality) data in Pakistan

During 2003–2004, SUPARCO, the Pakistan Space and Upper Atmosphere Research Commission has conducted a year long baseline air quality study in country’s major urban areas (Karachi, Lahore, Quetta, Rawalpindi, Islamabad and Peshawar). The objective of this study was to establish baseline levels and behavior of airborne pollutants in urban centers with temporal and spatial parameters. This study reveals that the highest concentrations of CO were observed at Quetta (14 ppm) while other pollutants like SO₂ (52.5 ppb), NO _x (60.75 ppb) and O₃ (50 ppb) were higher at Lahore compared to other urban centers like Karachi, Peshawar etc. The maximum particulate (TSP) and PM10 levels were observed at Lahore (996 ug/m³ and 368 ug/m³ respectively), Quetta (778 ug/m³, 298 ug/m³) and in Karachi (410 ug/m³, 302 ug/m³). In all major cities the highest levels were recorded at major intersections and variations were directly correlated with traffic density. These pollutants showed highest levels in summer and spring while lowest were observed in winter and monsoon. A data bank has been generated for future planning and air pollution impact studies.     

Water quality assessment by means of HFNI valvometry and high-frequency data modeling

The high-frequency measurements of valve activity in bivalves (e.g., valvometry) over a long period of time and in various environmental conditions allow a very accurate study of their behaviors as well as a global analysis of possible perturbations due to the environment. Valvometry uses the bivalve's ability to close its shell when exposed to a contaminant or other abnormal environmental conditions as an alarm to indicate possible perturbations in the environment. The modeling of such high-frequency serial valvometry data is statistically challenging, and here, a nonparametric approach based on kernel estimation is proposed. This method has the advantage of summarizing complex data into a simple density profile obtained from each animal at every 24-h period to ultimately make inference about time effect and external conditions on this profile. The statistical properties of the estimator are presented. Through an application to a sample of 16 oysters living in the Bay of Arcachon (France), we demonstrate that this method can be used to first estimate the normal biological rhythms of permanently immersed oysters and second to detect perturbations of these rhythms due to changes in their environment. We anticipate that this approach could have an important contribution to the survey of aquatic systems.     

Combined use of rapid bioassessment protocols and sediment quality triad to assess stream quality

Physical, chemical and biological conditions at five stations on a small southeastern stream were evaluated using the Rapid Bioassessment Protocols (RBP) and the Sediment Quality Triad (SQT) to assess potential biological impacts of a municipal wastewater treatment facility (WWTF) on downstream resources. Physical habitat, benthic macroinvertebrates and fish assemblages were impaired at Stations 1 and 2 (upstream of the WWTF), suggesting that the degraded physical habitat was adversely impacting the fish and benthic populations. The SQT also demonstrated that Stations 1 and 2 were degraded, but the factors responsible for the impaired conditions were attributed to the elevated concentrations of polycylclic aromatic hydrocarbons (PAHs) and metals (Mn, Pb) in the sediments. The source of contaminants to the upper reaches of the stream appears to be storm-water runoff from the city center. Increased discharge and stabilized base flow contributed by the WWTF appeared to benefit the physically-altered stream system. Although the two assessment procedures demonstrated biological impairment at the upstream stations, the environmental factors identified as being responsible for the impairment were different: the RBP provided insight into contributions associated with the physical habitat and the SQT contributed information on contaminants and sediment quality. Both procedures are important in the identification of physical and chemical factors responsible for environmental impairment and together they provide information critical to the development of appropriate management options for mitigation.     

A probabilistic methodology to assess the risk of groundwater quality degradation

An approach to assess the risk of groundwater quality degradation with regard to fixed standards, based on DisjunctiveKriging (DK) is presented. The DK allows one to evaluate the Conditional Probability (CP) of overriding a given threshold of concentration of a pollutant at a given time, and at a generic point in a consideredgroundwater system. The result of such investigation over the considered area can be plotted in form of maps of spatial risk. By repeating this analysis at different times, severalspatial riskmaps will be produced, one for each consideredtime. By means of non-parametric statistics, the temporal trendof the CPs can be evaluated at every point of the considered area. The trend index, assessed by means of a sort of classification of the trend values obtained as described above,can be superimposed on the most recent values of the spatialrisk (i.e.: the most recent values of probability). Consequentlya classification of the risk of groundwater quality degradationresults with which to weigh both the spatial distribution and thetemporal behaviour of the probability to exceed a given standardthreshold. The methodology has been applied to values of nitrateconcentration sampled in the monitoring well network of theModena plain, northern Italy. This area is characterised by intensive agricultural exploitation and hog breeding along withindustrial and civil developments. The influence of agriculture on groundwater results in a high nitrate pollution that limitsits use for potable purposes.     

Comparison of air quality data obtained from roof top,sidewalk and suburban areas

A comparison of air quality data obtained at a downtown roof top location, a surburban area, a main road curbside and adjacent to a major highway was conducted. The results of this study revealed that a reasonably good correlation between daily average concentrations at these locations can be established. For primary pollutants it was found that within the immediate release zone their average concentration is 3.5 to 4.0 times higher than at a close location but at roof top level. Total suspended particulate (TSP) concentration was found to increase by about 80%, and O₃ is reduced by about 25%. No significant difference was obtained between daily averages obtained at the city center location and the suburb site 5 km away.     

Sixteen-year air quality data analysis of a high environmental risk area in Southern Italy

The Brindisi area is characterized by the presence of industries with high environmental impact, located along its eastern border. Epidemiological studies have revealed several critical situations: two short-term (2003-2005) epidemiological studies have shown that PM(10) and NO(2) are adversely associated with daily hospital admissions: one of the two pointed to the associations with wind blowing from the southern, eastern and western sectors. This study aims to expand the time span of available air quality data in order to provide a more complete and extensive epidemiological study. Multi-year series (from 1992 to 2007) of SO(2), NO(2), and TSP concentration data are presented and analyzed. Data show a significant downward trend of SO(2) from 1992 to 2007, while for the TSP series, the downward trend is limited to the period 1992-1994. Marked seasonal trends are evident for all three pollutants, especially for NO(2) and TSP. The NO(2) series shows higher levels in winter. Inversely, the TSP series shows its maximum values during the summer months, associated with a moderate correlation with temperature and a poor correlation with other pollutants. Analysis of the series for wind sectors revealed the influence of the industrial site and of the harbor. The concentration series exhibit high concentration values and stronger correlations between them and with meteorology for wind blowing from the eastern sectors. Overall analysis supports the hypothesis of a different origin for TSP during the year and for different wind regimes and therefore possible size and chemical differences in TSP, which should be further investigated due to their health implications.     

Evaluation of marine outfall with three-dimensional hydrodynamic and water quality modeling

Numerical models are often used to evaluate the potential impact of human alternation of natural water bodies and to help the design of the alternation to mitigate its impacts. In the past decade, three-dimensional hydrodynamic and reactive transport modeling has matured from a research subject to a practical analysis technology. This paper presents a practical study in which a three-dimensional hydrodynamic and water quality model [hydrodynamic eutrophication model (HEM-3D)] was applied to determine the optimal location for treated wastewater discharged from marine outfall system in the Keelung harbor and the adjacent coastal sea. First, model validation was conducted with respect to surface elevation, current, and water quality variables measured in the Keelung harbor station and its coastal sea. The overall performance of the model was in qualitative agreement with the available field data. The model was then used to evaluate several scenarios of the locations from marine outfall system. Based on model simulation results, a location at the northeast of Ho-Ping Island was recommended for adoption because the environmental impact is smaller than any other alternative.

Use of biological indicators to assess water quality of the Ul River (Portugal)

Diatoms and macroinvertebrates have been extensively used as water quality indicators in Europe for the last two decades. In Portugal, the use of biological indicators to assess water quality in rivers has increased greatly. The aim of this work was to assess the water quality and ecological status of the Ul River in order to evaluate its ability for the establishment of a fluvial beach, using periphytic diatoms and macroinvertebrates as indicators. Four sites were selected along the Ul River. At each site, biological, physical, and chemical parameters were investigated. Epilithic diatoms and macroinvertebrates were sampled. The Specific Polluosensitivity Index and the Biological Diatom Index were applied to diatom data, while for macroinvertebrates, the Iberian Biological Monitoring Working Party (IBMWP) was used. According to the results obtained, it was possible to conclude that up to now, this river does not possess the ideal conditions for the establishment of a fluvial beach. We concluded that epilithic diatoms and macroinvertebrates provided consistent information on water quality assessment and can be used as biological indicators of the water quality in Ul River.     

Application of statistical modeling to optimize a coastal water quality monitoring program

The long-term water quality monitoring program implemented by the Massachusetts Water Resources Authority in 1992 is extensive and has provide substantial understanding of the seasonality of the waters in both Boston Harbor and Massachusetts Bay and the response to improvements in effluent quality and offshore transfer of the effluent in September 2000. The monitoring program was designed with limited knowledge of spatial and temporal variability and long-term trends within the system. This led to an extensive spatial and temporal sampling program. The data through 2003 showed high correlation within physical parameters measured (e.g., salinity, dissolved oxygen) and in biological measures such as chlorophyll fluorescence. To address the potential sampling redundancies in the measurement program, an assessment of the impact of reduced levels of monitoring on the ability to make water quality decisions was completed. The optimization was conducted by applying statistical models that took into account whether there was evidence of a seasonal pattern in the data. The optimization used model survey average readings to identify temporal fixed effects, model survey-average-corrected individual station readings to identify spatial fixed effects, corrected the individual station readings for temporal and spatial fixed effects and derived a correlation model for the corrected data, and applied the correlation model to characterize the correlation of annual average readings from reduced monitoring programs with true parameter levels. Reductions in the number of sampling stations were found less detrimental to the quality of the data for annual decision-making than reductions in the number of surveys per year, although there is less of a difference in this regard for dissolved oxygen than there is for chlorophyll. The analysis led to recommendations for a substantially lower monitoring effort with minimal loss of information. The recommendation supported an annual budget savings of approximately $183,000. Most of the savings was from fewer surveys as approximately $21,000 came from the reduction in the number of stations monitored from 21 to 7 and associated laboratory analytical costs.     

Extending the use of air quality indices to reflect effective population exposure

Although there are tendencies to develop a single common index which would describe an overall air quality status within an area, constructed from a choice of measurements of individual pollutants, indices describing individual pollutants themselves have several potentials which can be used in ways which are not possible with pollutant concentrations. On the case of Belgrade, Serbia, we investigated possibilities of using such indices for comparisons between pollutants, characterization of monitoring sites, and extending their use to include elements of population exposure. A methodology of adjusting the results obtained at monitoring stations located in severe pollution conditions, like street canyons, is proposed and used.     

Spatiotemporal variations in species diversity to assess environmental impacts on aquatic communities: The use of biomass data versus density data

This paper discusses various methods for calculating the minimum instream flows for the protection of aquatic life for the purpose of illustrating its increasing complexity. These procedures are the Montana method (Tennant, 1976); the wetted perimeter method (Collings, 1974; Cochnauer, 1976) and the IFIM method (Instream Flow Incremental Methodology; Bovee, 1982). An analysis is then made of some regionalisation criteria based on these methods, from which useful suggestions can be drawn for the development of a procedure to be applied to basins. A method is thus proposed for calculating the recommended flows for protecting the aquatic environment based on simple hydrological variables, such as Q_{7 10}, which can be estimated for a basin on the basis of area A and a Base Flow Index (BFI) which summarises its hydrogeological characteristics. This approach can be used when the field data necessary for more complex methods is not available. These require the defining of the environmental suitability of a watercourse for certain designated reference fish species, according to the flow and the morphology of the channel. The positive results of this approach were verified by Leonard (1990) and this methodology was applied to the Tiber river basin.     

Using multivariate statistical methods to assess the groundwater quality in an arsenic-contaminated area of Southwestern Taiwan

Groundwater is a major water resource in Southwestern Taiwan; hence, long-term monitoring of water quality is essential. The study aims to assess the hydrochemical characteristics of water in the arsenic-contaminated aquifers of Choushui River alluvial fan and Chianan Plain, Taiwan using multivariate statistical methods, namely, factor analysis (FA), cluster analysis (CA), and discriminant analysis (DA). Factor analysis is applied to reveal the processes controlling the hydrochemistry of groundwater. Cluster analysis is applied to spatially categorize the collected water samples based on the water quality. Discriminant analysis is then applied to elucidate key parameters associated with the occurrence of elevated As concentration (>10 μg L(-1)) in groundwater. Major water types are characterized as Na-Ca-Cl and Na-Mg-Cl in the Choushui River alluvial fan and Chianan Plain, respectively. Inorganic species of arsenic (As), particularly As(III), prevail in these two groundwater catchments, and their levels are higher in the Chianan Plain than in the Choushui River alluvial fan. Through FA, three factors, namely, the degree of salination, As reduction, and iron (Fe) reduction, are determined and denoted irrespective of some differences between the factorial compositions. Spatial distribution patterns of factors As reduction and Fe reduction imply that the redox zonation is delineated by As- and Fe-dominance zones separately. The results of CA demonstrate that three main groups can be properly explained by the factors extracted via FA. Three- (Fe(2+), Fe(3+), and NH (4) (+) ) and four-parameters (Fe(2+), Fe(3+), NH (4) (+) , and Ca(2+)) derived from discriminant analysis for Choushui River alluvial fan and Chianan Plain are elucidated as key parameters affecting the distribution of As-contained groundwater. The analytical results indicate that the reductive dissolution of Fe minerals is prerequisite for the mobilization of As, whereas the shift of redox condition from Fe- to As-reducing leads to the accumulation of dissolved As in this area.     

An approach to the assessment of the quality of environmental monitoring data

This paper reports an approach to the assessment of the validity of environmental monitoring data--a 'data filter'. The strategy has been developed through the UK National Marine Analytical Quality Control (AQC) Scheme for application to data collected for the UK National Marine Monitoring Plan, although the principles described are applicable more widely. The proposed data filter is divided into three components: Part A, 'QA/QC'--an assessment of the laboratory's practices in Quality Assurance/Quality Control; Part B, 'fitness for purpose'--an evaluation of the standard of accuracy that can be demonstrated by activities in (A), in relation to the intended application of the data; and Part C, the overall assessment on which data will be accepted as usable or rejected as being of suspect quality. A pilot application of the proposed approach is reported. The approach described in this paper is intended to formalise the assessment of environmental monitoring data for fitness for a chosen purpose. The issues important to fitness for purpose are discussed and assigned a relative priority order on which to judge the reliability/usefulness of monitoring data.     

Use of multiple indicators to assess the environmental quality of urbanized aquatic surroundings in San Luis,Argentina

Urbanization can cause significant changes in the integrity of fluvial ecosystems, which makes it necessary to assess environmental conditions of areas where population growth rates are high. A study of the environmental quality of Chorrillos River (San Luis-Argentina) and its tributaries was carried out in order to evaluate the potential effect of an urbanization gradient. Six sites were sampled along the main course and tributaries of the river. Urbanization variables were measured and included to calculate an Urbanization Index. Physical–chemical analyses were performed in water samples to evaluate water quality through the use of a simplified index of water quality (SIWQ). Plants, macroinvertebrates, and amphibians metrics were used to assess the biological state of the studied sites. The Urbanization Index varied significantly between sites and was significantly correlated to the SIWQ. However, no significant correlations were found between SIWQ and macroinvertebrates and amphibians variables. Water quality of Chorrillos River and its tributaries is good, but it is affected by anthropic influences as reflected by the declining of SIWQ values. Although biological sampling constitutes an important tool in the assessment of water quality of rivers, in this report biological results were not conclusive.     

Indoor air quality modeling for PM10, PM2.5, and PM1.0 in naturally ventilated classrooms of an urban Indian school building

Assessment of indoor air quality (IAQ) in classrooms of school buildings is of prime concern due to its potential effects on student??s health and performance as they spend a substantial amount of their time (6?C7 h per day) in schools. A number of airborne contaminants may be present in urban school environment. However, respirable suspended particulate matter (RSPM) is of great significance as they may significantly affect occupants?? health. The objectives of the present study are twofold, one, to measure the concentrations of PM₁₀ (<10  $\upmu $ m), PM_2.5 (<2.5  $\upmu $ m), and PM_1.0 (<1.0  $\upmu $ m) in naturally ventilated classrooms of a school building located near a heavy-traffic roadway (9,755 and 4,296 vehicles/hour during weekdays and weekends, respectively); and second, to develop single compartment mass balance-based IAQ models for PM₁₀ (NVIAQM_pm10), PM_2.5 (NVIAQM_pm2.5), and PM_1.0 (NVIAQM_pm1.0) for predicting their indoor concentrations. Outdoor RSPM levels and classroom characteristics, such as size, occupancy level, temperature, relative humidity, and CO₂ concentrations have also been monitored during school hours. Predicted indoor PM₁₀ concentrations show poor correlations with observed indoor PM₁₀ concentrations (R ² = 0.028 for weekdays, and 0.47 for weekends). However, a fair degree of agreement (d) has been found between observed and predicted concentrations, i.e., 0.42 for weekdays and 0.59 for weekends. Furthermore, NVIAQM_pm2.5 and NVIAQM_pm1.0 results show good correlations with observed concentrations of PM_2.5 (R ² = 0.87 for weekdays and 0.9 for weekends) and PM_1.0 (R ² = 0.86 for weekdays and 0.87 for weekends). NVIAQM_pm10 shows the tendency to underpredict indoor PM₁₀ concentrations during weekdays as it does not take into account the occupant??s activities and its effects on the indoor concentrations during the class hours. Intense occupant??s activities cause resuspension or delayed deposition of PM₁₀. The model results further suggests conductance of experimental and physical simulation studies on dispersion of particulates indoors to investigate their resuspension and settling behavior due to occupant??s activities/movements. The models have been validated at three different classroom locations of the school site. Sensitivity analysis of the models has been performed by varying the values of mixing factor (k) and newly introduced parameter R _c. The results indicate that the change in values of k (0.33 to 1.00) does not significantly affect the model performance. However, change in value of R _c (0.001 to 0.500) significantly affects the model performance.     

Assessment of microbiological indoor air quality in an Italian office building equipped with an HVAC system

The purpose of this study was to evaluate the level and composition of bacteria and fungi in the indoor air of an Italian office building equipped with a heating, ventilation and air conditioning (HVAC) system. Airborne bacteria and fungi were collected in three open-space offices during different seasons. The microbial levels in the outdoor air, supply air diffusers, fan coil air flow and air treatment unit humidification water tank were used to evaluate the influence of the HVAC system on indoor air quality (IAQ). A medium–low level of bacterial contamination (50–500 CFU/m³) was found in indoor air. Staphylococcus and Micrococcus were the most commonly found genera, probably due to human presence. A high fungal concentration was measured due to a flood that occurred during the winter. The indoor seasonal distribution of fungal genera was related to the fungal outdoor distribution. Significant seasonal and daily variation in airborne microorganisms was found, underlining a relationship with the frequency of HVAC system switching on/off. The results of this monitoring highlight the role of the HVAC system on IAQ and could be useful to better characterise bacterial and fungal population in the indoor air of office buildings.