Multi-objective optimization of air quality monitoring

A new method for multi-objective optimization of air quality monitoring systems based on satellite remote sensing of the troposphere is described in this work. The technique uses atmospheric turbidity as surrogate for air pollution loading. Through inverse chemical modeling and ancillary information the respective patterns of primary gaseous and particle pollutants are inferred. The optimization algorithm uses the resulting maps of ambient air pollution as input. It focuses on the gain of information with regard to human exposure to high pollution, potential impact on cultural heritage, compliance to ambient air quality standards, monitoring key point and area source emissions, as well as on the associated cost. Application of the method in Brescia, Italy showed its significant potential for improving the cost-effectiveness of air quality monitoring networks at the urban and regional scales.     

Indoor air quality during renovation actions: a case study

A temporary renovation activity releases considerably high concentrations of particulate matter, viable and non-viable, into air. These pollutants are a potential contributor to unacceptable indoor air quality (IAQ). Particulate matter and its constituents lead, sulfate, nitrate, chloride, ammonium and fungi as well as fungal spores in air were evaluated in a building during renovation action. Suspended dust was recorded at a mean value of 6.1 mg m(-3) which exceeded the Egyptian limit values for indoor air (0.15 mg m(-3)) and occupational environments (5 mg m(-3)). The highest particle frequency (23%) of aerodynamic diameter (dae) was 1.7 microm. Particulate sulfate (SO(4)(2-)), nitrate (NO(3)(-)), chloride (Cl(-)), ammonium (NH(4)(+)) and lead components of suspended dust averaged 2960, 28, 1350, 100 and 13.3 microg m(-3), respectively. Viable fungi associated with suspended dust and that in air averaged 1.11 x 10(6) colony forming unit per gram (cfu g(-1)) and 92 colony forming unit per plate per hour (cfu p(-1) h(-1)), respectively. Cladosporium(33%), Aspergillus(25.6%), Alternaria(11.2%) and Penicillium(6.6%) were the most frequent fungal genera in air, whereas Aspergillus(56.8%), Penicillium(10.3%) and Eurotium(10.3%) were the most common fungal genera associated with suspended dust. The detection of Aureobasidium, Epicoccum, Exophiala, Paecilomyces, Scopulariopsis, Ulocladium and Trichoderma is an indication of moisture-damaged building materials. Alternaria, Aureobasidium, Cladosporium, Scopulariopsis and Nigrospora have dae > 5 microm whereas Aspergillus, Penicillium and Verticillium have dae < 5 microm which are suited to penetrate deeply into lungs. Particulate matter from the working area infiltrates the occupied zones if precautionary measures are inadequate. This may cause deterioration of IAQ, discomfort and acute health problems. Renovation should be carefully designed and managed, in order to minimize degradation of the indoor and outdoor air quality.     

A water quality monitoring network design methodology for the selection of critical sampling points: Part II

In order to resolve the spatial component of the design of a water quality monitoring network, a methodology has been developed to identify the critical sampling locations within a watershed. This methodology, called Critical Sampling Points (CSP), focuses on the contaminant total phosphorus (TP), and is applicable to small, predominantly agricultural-forested watersheds. The CSP methodology was translated into a model, called Water Quality Monitoring Station Analysis (WQMSA). It incorporates a geographic information system (GIS) for spatial analysis and data manipulation purposes, a hydrologic/water quality simulation model for estimating TP loads, and an artificial intelligence technology for improved input data representation. The model input data include a number of hydrologic, topographic, soils, vegetative, and land use factors. The model also includes an economic and logistics component. The validity of the CSP methodology was tested on a small experimental Pennsylvanian watershed, for which TP data from a number of single storm events were available for various sampling points within the watershed. A comparison of the ratios of observed to predicted TP loads between sampling points revealed that the model's results were promising.     

Optimal redesign of groundwater quality monitoring networks: a case study

Assessment and redesign of water quality monitoring networks is an important task in water quality management. This paper presents a new methodology for optimal redesign of groundwater quality monitoring networks. The measure of transinformation in discrete entropy theory and the transinformation–distance (T–D) curves are used to quantify the efficiency of sampling locations and sampling frequencies in a monitoring network. The existing uncertainties in the T–D curves are taken in to account using the fuzzy set theory. The C-means clustering method is also used to classify the study area to some homogenous zones. The fuzzy T–D curve of the zones is then used in a multi-objective hybrid genetic algorithm-based optimization model. The proposed methodology is utilized for optimal redesign of monitoring network of the Tehran aquifer in the Tehran metropolitan area, Iran.     

Short-term variation in air quality associated with firework events: a case study

The effect of fireworks on air quality was assessed from the ambient concentrations of various air pollutants (SO2, NO2, PM10 and TSP) during Diwali festival in Hisar city (India), in November 1999. The extensive use of fireworks was found to be related to short-term variation in air quality. During the festival the concentration of SO2 was observed to be increased approximately 10-fold at few sites, whereas the concentrations of NO2, PM10 and TSP increased 2-3 times, compared to the data collected on a typical winter day in December 1999. The maximum NO2 concentration was observed a day after the festival. The diurnal pattern of the above pollutants showed a slight increase in the night. The levels of these pollutants observed during Diwali were found to be moderately high, which can be associated with serious health impacts.     

Optimizing water quality monitoring networks using continuous longitudinal monitoring data: a case study of Wen-Rui Tang River, Wenzhou, China

Identification of representative sampling sites is a critical issue in establishing an effective water quality monitoring program. This is especially important at the urban-agriculture interface where water quality conditions can change rapidly over short distances. The objective of this research was to optimize the spatial allocation of discrete monitoring sites for synoptic water quality monitoring through analysis of continuous longitudinal monitoring data collected by attaching a water quality sonde and GPS to a boat. Sampling was conducted six times from March to October 2009 along a 6.5 km segment of the Wen-Rui Tang River in eastern China that represented an urban-agricultural interface. When travelling at a velocity of ～2.4 km h(-1), this resulted in water quality measurements at ～20 m interval. Ammonia nitrogen (NH(4)(+)-N), electrical conductivity (EC), dissolved oxygen (DO), and turbidity data were collected and analyzed using Cluster Analysis (CA) to identify optimal locations for establishment of long-term monitoring sites. The analysis identified two distinct water quality segments for NH(4)(+)-N and EC and three distinct segments for DO and turbidity. According to our research results, the current fixed-location sampling sites should be adjusted to more effectively capture the distinct differences in the spatial distribution of water quality conditions. In addition, this methodology identified river reaches that require more comprehensive study of the factors leading to the changes in water quality within the identified river segment. The study demonstrates that continuous longitudinal monitoring can be a highly effective method for optimizing monitoring site locations for water quality studies.     

The design of cost-effective air quality monitoring networks

A statistical measure of information content is used as a means for assessing the effectiveness of a particular monitoring network configuration. This measure is directly related to the precision with which the network can estimate the level of air quality in the region. Each potential site in the network can contribute to an increase in the overall precision of the estimate. The amount of increase is determined by the degree of dependence, displayed by observed pollutant concentrations, between potential sites.A statistical procedure is used to combine the observed pollution dynamics and the measurement network in order to assess network effectiveness. An iterative application of this procedure leads to the design of the most effective network subject to a specified budget constraint.     

Assessment of environmental impact on air quality by cement industry and mitigating measures: a case study

In this study, environmental impact on air quality was evaluated for a typical Cement Industry in Nigeria. The air pollutants in the atmosphere around the cement plant and neighbouring settlements were determined using appropriate sampling techniques. Atmospheric dust and CO₂ were prevalent pollutants during the sampling period; their concentrations were recorded to be in the range of 249–3,745 mg/m³ and 2,440–2,600 mg/m³, respectively. Besides atmospheric dust and CO₂, the air pollutants such as NO _x , SO _x and CO were in trace concentrations, below the safe limits approved by FEPA that are 0.0062–0.093 mg/m³ NO _x , 0.026 mg/m³ SO _x and 114.3 mg/m³ CO, respectively. Some cost-effective mitigating measures were recommended that include the utilisation of readily available and low-cost pozzolans material to produce blended cement, not only could energy efficiency be improved, but carbon dioxide emission could also be minimised during clinker production; and the installation of an advance high-pressure grinding rolls (clinker–roller-press process) to maximise energy efficiency to above what is obtainable from the traditional ball mills and to minimise CO₂ emission from the power plant.     

Microbiological monitoring of air quality in a university canteen: an 11-year report

Over the past decade, an increased tendency to consume meals at dining facilities outside the home has been highlighted; moreover, meals supplied in food businesses have been involved in many foodborne disease outbreaks. Therefore, microbial air contamination in food processing facilities could be a concern and an increase of microbial loads could represent a risk factor, especially for the potential contamination of foods due to undesirable spoiling and pathogenic bacteria. In this paper, the results of an 11-year microbiological monitoring of air quality in a university canteen are reported. The study, which started in the year 2000, was performed within a hazard analysis and critical control point (HACCP) plan implementation of a canteen that produces about 1,000 meals a day in order to verify the effectiveness of corrective actions on the indoor air quality. The primary food preparation room, the kitchen, and three cold rooms underwent air sampling by using a calibrated impaction sampler. Our investigation detected a general and progressive improvement in the air quality of the canteen since the beginning of the study, thus suggesting the appropriateness of the corrective action undertaken during the HACCP implementation program.     

Methodology for designing air quality monitoring networks: I. Theoretical aspects

An objective methodology is presented for determining the number and disposition of ambient air quality stations in a monitoring network for the primary purpose of compliance with air quality standards. The methodolgy utilizes a data base with real or simulated data from an air quality dispersion model for application with a two-step process for ascertaining the optimal monitoring network. In the first step, the air quality patterns in the data base are collapsed into a single composite pattern through a figure-of-merit (FOM) concept. The most desirable locations are ranked and identified using the resultant FOM fields. In the second step the network configuration is determined on the basis of the concept of spheres of influence (SOI) developed from cutoff values of spatial correlation coefficients between potential monitoring sites and adjacent locations. The minimum number of required stations is then determined by deletion of lower-ranked stations whose SOIs overlap. The criteria can be set to provide coverage of less than some fixed, user-provided percentage of the coverage of tha SOIs of the higher ranked stations and for some desired level of minimum detection capability of concentration fluctuations.The methodology is applied in a companion paper (McElroy et al., 1986) to the Las Vegas, Nevada, metropolitan area for the pollutant carbon monoxide.Although the research described in this article has been funded wholly or in part by the United States Environmental Protection Agency through Contract No. 68-03-2446 to Systems Applications, Inc., it has not been subjected to Agency review and therefore does not necessarily reflect the views of the Agency and no official endorsement should be inferred.     

Design of on-line river water quality monitoring systems using the entropy theory: a case study

The design of a water quality monitoring network is considered as the main component of water quality management including selection of the water quality variables, location of sampling stations and determination of sampling frequencies. In this study, an entropy-based approach is presented for design of an on-line water quality monitoring network for the Karoon River, which is the largest and the most important river in Iran. In the proposed algorithm of design, the number and location of sampling sites and sampling frequencies are determined by minimizing the redundant information, which is quantified using the entropy theory. A water quality simulation model is also used to generate the time series of the concentration of water quality variables at some potential sites along the river. As several water quality variables are usually considered in the design of water quality monitoring networks, the pair-wise comparison is used to combine the spatial and temporal frequencies calculated for each water quality variable. After selecting the sampling frequencies, different components of a comprehensive monitoring system such as data acquisition, transmission and processing are designed for the study area, and technical characteristics of the on-line and off-line monitoring equipment are presented. Finally, the assessment for the human resources needs, as well as training and quality assurance programs are presented considering the existing resources in the study area. The results show that the proposed approach can be effectively used for the optimal design of the river monitoring systems.     

Air pollution exposure monitoring and estimating. Part I. Integrated air quality monitoring system

This paper presents an integrated exposure monitoring system, based on an expansion of existing air quality monitoring systems using dispersion modelling. The system allows: (1) identifying geographical areas whose inhabitants are most exposed to ambient pollution; (2) identifying how many people in an area are exposed to concentrations of pollution exceeding air quality guidelines; (3) describing the exposure of population subgroups (e.g. children); (4) planning pollution abatement measures and quantifying their effects; (5) establishing risk assessment and management programs, and (6) investigating the short- and long-term effects of both pollutants and pollution sources on public health. The effect of pollution is rarely very large and in order to discover it, exposure estimation must provide data that reflects both spatial and temporal variations. Estimates of pollution exposure are obtained using an integrated approach that combines results of measurements from monitoring programs with dispersion calculations. These values can serve as estimates for individual short-term or long-term exposure. The grouped data allows the expression of ambient pollution concentrations as the spatial distribution of estimates such as the mean or 98th percentile of such compounds as SO2, O3, NO2, PM10 and PM2.5. This integrated approach has been combined into a single software package, AirQUIS.     

Cokriging optimization of monitoring network configuration based on fuzzy and non-fuzzy variogram evaluation

A number of optimization approaches regarding monitoring networkdesign and sampling optimization procedures have been reported inthe literature. Cokriging Estimation Variance (CEV) is a usefuloptimization tool to determine the influence of the spatial configuration of monitoring networks on parameter estimations. Itwas used in order to derive a reduced configuration of a nitrateconcentration monitoring well network. The reliability of the reduced monitoring configuration suffers from the uncertainties caused by the variographer's choices and several inherent assumptions. These uncertainties can be described considering thevariogram parameters as fuzzy numbers and the uncertainties by means of membership functions.Fuzzy and non-fuzzy approaches were used to evaluate differencesamong well network configurations. Both approaches permitted estimates of acceptable levels of information loss for nitrate concentrations in the monitoring network of the aquifer of the Plain of Modena, Northern Italy. The fuzzy approach was found torequire considerably more computational time and numbers of wellsat comparable level of information loss.     

The use of multivariate statistical methods for optimization of the surface water quality network monitoring in the Paraopeba river basin,Brazil

This study sought to evaluate and propose adjustments to the water quality monitoring network of surface freshwaters in the Paraopeba river basin (Minas Gerais, Brazil), using multivariate statistical methods. A total of 13,560 valid data were analyzed for 19 water quality parameters at 30 monitoring sites, over a period of 5 years (2008–2013). The cluster analysis grouped the monitoring sites in eight groups based on similarities of water quality characteristics. This analysis made it possible to detect the most relevant monitoring stations in the river basin. The principal components analysis associated with non-parametric tests and the analysis of violation of the standards prescribed by law, allowed for identifying the most relevant parameters which must be maintained in the network (thermotolerant coliforms, total manganese, and total phosphorus). The discharge of domestic sewage and industrial wastewater, that from mining activities and diffuse pollution from agriculture and pasture areas are the main sources of pollution responsible for the surface water quality deterioration in this basin. The BP073 monitoring site presents the most degraded water quality in the Paropeba river basin. The monitoring sites BP094 and BP092 are located geographically close and they measure similar water quality, so a possible assessment of the need to maintain only one of the two in the monitoring network is suggested. Therefore, multivariate analyses were efficient to assess the adequacy of the water quality monitoring network of the Paraopeba river basin, and it can be used in other watersheds.     

Continuous high-frequency monitoring of estuarine water quality as a decision support tool: a Dublin Port case study

High-frequency, continuous monitoring using in situ sensors offers a comprehensive and improved insight into the temporal and spatial variability of any water body. In this paper, we describe a 7-month exploratory monitoring programme in Dublin Port, demonstrating the value of high-frequency data in enhancing knowledge of processes, informing discrete sampling, and ultimately increasing the efficiency of port and environmental management. Kruskal–Wallis and Mann–Whitney tests were used to show that shipping operating in Dublin Port has a small–medium effect on turbidity readings collected by in situ sensors. Turbidity events are largely related to vessel activity in Dublin Port, caused by re-suspension of sediments by vessel propulsion systems. The magnitudes of such events are strongly related to water level and tidal state at vessel arrival times. Crucially, measurements of Escherichia coli and enterococci contamination from discrete samples taken at key periods related to detected turbidity events were up to nine times higher after vessel arrival than prior to disturbance. Daily in situ turbidity patterns revealed time-dependent water quality “hot spots” during a 24-h period. We demonstrate conclusively that if representative environmental assessment of water quality is to be performed at such sites, sampling times, informed by continous monitoring data, should take into account these daily variations. This work outlines the potential of sensor technologies and continuous monitoring, to act as a decision support tool in both environmental and port management.     

Application of water quality indices and analysis of the surface water quality monitoring network in semiarid North-Central Chile

Surface water quality has increasing importance worldwide and is particularly relevant in the semiarid North-Central Chile, where agriculture and mining activities are imposing heavy pressure on limited water resources. The current study presents the application of a water quality index in four watersheds of the 29°-33°S realm for the period 1999-2008, based on the Canadian Council of Ministers for the Environment approach and the Chilean regulation for irrigation water quality. In addition, two modifications to the index are tested and a comprehensive characterization of the existing monitoring network is performed through cluster analysis. The basins studied show fairly good water quality in the overall, specially the Limarí basin. On the other hand, the lower index values were obtained for the headwaters of Elqui, associated with the El Indio mining district. The first modification of the indicator (i.e., to consider parameters differentially according to their effect on human health or the environment) did not produce major differences with respect to the original index, given the generally good water quality. The second modification (i.e., to consider as threshold values the more restrictive figures derived from a set of regulations) yielded important differences in the indicator values. Finally, an adequate characterization of the monitoring network was obtained. The results presented spatial coherence and the information can be used as a basis for the optimization of the monitoring network if required.     

Global air quality monitoring: Trends and levels of sulphur dioxide and suspended particulate matter in selected urban areas

An overview is presented of the development and ongoing activities of the WHO/UNEP air quality monitoring project. The project started in 1973 and is part of the Global Environmental Monitoring System. An analysis of the sulphur dioxide and suspended particulate matter is also included. The results show that the annual mean concentration for sulphur dioxide has decreased since 1973; for suspended particulate matter, however, a gradual increase is observed since 1976.     

Emission of isoprene from common Indian plant species and its implications for regional air quality

Isoprene is most dominant volatile organic compounds (VOC) emitted by many plants. In this study 40 common Indian plant species were examined for isoprene emission using dynamic flow through enclosure chamber technique. Isoprene emission rates of plants species were found to vary from undetectable to 69.5 microg g(-1) h(-1) (Madhuca latifolia). Besides, an attempt has been made to evaluate suitability of 80 common Indian plant species for planting programmes. Out of 80 species, 29 species were moderate to high emitters (10 to < or =25 microg g(-1) h(-1)), 12 species were low emitter emitters (1 to < or =10 microg g(-1) h(-1)) and remaining 39 species were found to be negligible or non emitters (<1 microg g(-1) h(-1)) of isoprene. About 50% plant species selected for planting programmes in India were found to be moderate to high emitters of isoprene.     

Evaluating a Canadian regional air quality model using ground-based observations in north-eastern Canada and United States

The simulated concentrations from a numerical 3-dimensional regional air quality model (MC2AQ) are compared to those of ground-based observations in north-eastern Canada and the United States. The model has oxidant chemistry for both inorganic and organic species and deposition routines driven online by a mesoscale compressible community meteorological model (MC2). A standard emission inventory of anthropogenic, natural and biogenic sources for the year 1990 for 21 atmospheric trace species was used in the simulation. The model was run for July 1999, because of the occurrence of a high ozone episode and the availability of the monitoring data for surface O3, SO2, NO, NO2 and NOx. The comparisons during the episode show that the model performs quite well for predicting concentrations and diurnal variations of the surface ozone. The predictions for other gaseous species show some discrepancies with observations, but they are consistent with the results from other models evaluated in the literature. The uncertainties in the emission inventory for these species might be the main causes of the discrepancies. Further studies are needed to improve the predictability of SO and NOx, especially as the model is developed to include particulate matter formation as a result of these gaseous precursors.