Air Quality Patterns Research Articles

Environmental Pasts/Environmental Futures in Post-Socialist Europe

This contribution focuses on the limits of European Union programmes and accession practices on environmental policies and performance in Central and Eastern Europe. In particular, we document some of the ways in which state socialist and post-socialist environmental conditions, practices and policies are shaping, and in turn being shaped by, the path of accession and integration. We focus on the diverse and changing patterns of air, water and soil quality in Central and Eastern Europe, the contested nature of new environmental policies, the environmental consequences of economic change, and the sustainability of emerging environmental regimes. The contribution concludes with several questions about the consequences of new state membership for future EU environmental policies.

Modeling the internal dynamics of energy and mass transfer in an imperfectly mixed ventilated airspace.

The present paper outlines a modeling approach, which has been developed to model the internal dynamics of heat and moisture transfer in an imperfectly mixed ventilated airspace. The modeling approach, which combines the classical heat and moisture balance differential equations with the use of experimental time-series data, provides a physically meaningful description of the process and is very useful for model-based control purposes. The paper illustrates how the modeling approach has been applied to a ventilated laboratory test room with internal heat and moisture production. The results are evaluated and some valuable suggestions for future research are forwarded. The modeling approach outlined in this study provides an ideal form for advanced model-based control system design. The relatively low number of parameters makes it well suited for model-based control purposes, as a limited number of identification experiments is sufficient to determine these parameters. The model concept provides information about the air quality and airflow pattern in an arbitrary building. By using this model as a simulation tool, the indoor air quality and airflow pattern can be optimized.

Sodar mixing height estimates and air pollution characteristics over a Mediterranean big city

Sodar systems are progressively used for quantitative and qualitative profile information on the atmospheric structure parameters. However, there is still a need for well‐established relations between atmospheric physics parameters and air quality patterns, especially in urban environments. In this respect it is of importance to investigate the correlations among specific atmospheric quantities and air pollution patterns. It is the purpose of this paper to study correlations between the Sodar produced mixing height using the most recent and accurate methods, and O3, NOx and CO concentrations recorded by the Athens air quality monitoring network, during selected meteorological conditions. The continuous mixing height monitoring allows for deeper investigation of air pollution characteristics, especially during the transitional periods of the day. The obtained results indicate that there is good correlation between the pollutants concentrations and the mixing height especially during episode days. Furthermore, it is indicated that there is a strong dependence between the rate of increase of the mixing height and the concentration levels in the early morning hours as well as during the Atmospheric Boundary Layer (ABL) collapse in the afternoon. These results are of importance for urban air pollution modelling, which has recently attracted the attention of many research groups.

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.

Studies of air quality predictors based on neural networks

In recent years, urban air pollution has emerged as an acute problem because of its negative effect on health and living conditions. Regional air quality problems, in general, are linked to violations of specified air quality standards. The current study aims to find neural network based air quality predictors, which can work with a limited number of datasets and are robust enough to handle data with noise and errors. A number of available variations of neural network models, such as the Recurrent Network Model (RNM), the Change Point Detection Model with RNM (CPDM), the Sequential Network Construction Model (SNCM), the Self Organising Feature Model (SOFM), and the Moving Window Model (MWM), were implemented using MATLAB software for predicting air quality. Developed models were run to simulate and forecast based on the annual average data for 15 years from 1985 to 1999 for seven parameters, viz. VOC, NOx, CO, SO2, PM10, PM2.5 and NH3 for one county of California, USA. The models were fitted with first nine years of data to predict data for remaining six years. The models, in general, could predict air quality patterns with modest accuracy. However, the SOFM model performed extremely well in comparison with the other models for predicting long-term (annual) data.

Estudo das partículas totais em suspensão e metais associados em áreas urbanas

This work aims at the study of the air quality determination regarding the total suspended particles (TSP) and the associated metals in the counties of Charqueadas and Sapucaia do Sul at the state of Rio Grande do Sul. The TSP samples were collected using high volume samplers and the analysis of the metallic elements was accomplished through ICP-AES. The results revealed that the TSP concentrations, found in the two studied regions, have exceded the current air quality patterns established by the Brazilian Legislation. They also revealed high levels of several of the elements being attributed to the presence of anthropogenic sources. The correlation between meteorological data (speed and wind direction) and TSP concentrations were significant and revealed strong influence in particle dispersion.

Optimal design of air quality networks detecting warning and alert conditions

A statistical method is presented to determine the optima design of air quality networks detecting warning and alert levels. A simulation model is used to describe temporal and spatial variations of atmospheric pollutants; air quality patterns serve as the database of the procedure to design the network. Only the sites exceeding warning and alert levels, at different meteorological scenarios, are considered as potential monitoring stations. For the selection of the optima set, spatial and temporal representativity criteria are introduced; accordingly, the optima set provides a complete representativity of the space and time considered. The method is applied to the Mestre urban area, in Venice district, for the carbon monoxide pollutant.

Short-term effects of ambient oxidant exposure on mortality: a combined analysis within the APHEA project. Air Pollution and Health: a European Approach.

The Air Pollution and Health: a European Approach (APHEA) project is a coordinated study of the short-term effects of air pollution on mortality and hospital admissions using data from 15 European cities, with a wide range of geographic, sociodemographic, climatic, and air quality patterns. The objective of this paper is to summarize the results of the short-term effects of ambient oxidants on daily deaths from all causes (excluding accidents). Within the APHEA project, six cities spanning Central and Western Europe provided data on daily deaths and NO2 and/or O3 levels. The data were analyzed by each center separately following a standardized methodology to ensure comparability of results. Poisson autoregressive models allowing for overdispersion were fitted. Fixed effects models were used to pool the individual regression coefficients when there was no evidence of heterogeneity among the cities and random effects models otherwise. Factors possibly correlated with heterogeneity were also investigated. Significant positive associations were found between daily deaths and both NO2 and O3. Increases of 50 micrograms/m3 in NO2 (1-hour maximum) or O3 (1-hour maximum) were associated with a 1.3% (95% confidence interval 0.9-1.8) and 2.9% (95% confidence interval 1.0-4.9) increase in the daily number of deaths, respectively. Stratified analysis of NO2 effects by low and high levels of black smoke or O3 showed no significant evidence for an interaction within each city. However, there was a tendency for larger effects of NO2 in cities with higher levels of black smoke. The pooled estimate for the O3 effect was only slightly reduced, whereas the one for NO2 was almost halved (although it remained significant) when two pollutant models including black smoke were applied. The internal validity (consistency across cities) as well as the external validity (similarities with other published studies) of our results on the O3 effect support the hypothesis of a causal relation between O3 and all cause daily mortality. However, the short-term effects of NO2 on mortality may be confounded by other vehicle-derived pollutants. Thus, the issue of independent NO2 effects requires additional investigation.

Personal exposure to nitrogen dioxide: relationship to indoor/outdoor air quality and activity patterns

Personal NO/sub 2/ exposures and indoor and outdoor concentrations were measured for nearly 350 individuals in the Portage, WI, area. Concentrations in homes with gas stoves averaged 18 ..mu..g/m/sup 3/ higher in the summer (median indoor/outdoor ratio 2.4) and 36 ..mu..g/m/sup 3/ (median indoor/outdoor ratio 3.2) higher in the winter than outdoor levels. Personal exposures were closely related to indoor averages for households with gas stoves (r = 0.85 summer, r = 0.87 winter) and with electric stoves (r = 0.68 summer, r = 0.61 winter); more than 65% of the average day was spent at home while about 15% was spent outdoors in summer and less than 5% in winter. The association between personal exposure and outdoor levels of NO/sub 2/ was weakest during the winter for both gas (r = 0.20) and electric (r = 0.28) stove groups. The measures of exposure and time allocation indicate that there is a wide range of variability in personal exposures to NO/sub 2/ that may not be adequately accounted for by simple stratifications based on cooking fuel type. 46 references, 7 tables.

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.

Methodology for designing air quality monitoring networks: II. Application to Las Vegas, Nevada, for carbon monoxide

An objective methodology presented in a companion paper (Liu et al., 1986) for determining the optimum number and disposition of ambient air quality stations in a monitoring network for carbon monoxide is applied to the Las Vegas, Nevada, area. The methodology utilizes an air quality simulation model to produce temporally-varying air quality patterns for each of a limited number of meteorological scenarios representative of the region of interest. These air quality patterns in turn serve as the data base in a two-step procedure for the identification and ranking of the most desirable monitoring locations (step 1) and the removal of redundancies in spatial coverage among the desired locations (step 2.)The performance of the air quality simulation model, a key element in the design methodology, was evaluated in the Las Vegas area in a special field measurement program. In the Las Vegas demonstration for carbon monoxide, 19 stations covering concentration maxima and 3 stations covering background concentrations in rural areas were identified and ranked. A 10-station network, for example, consisting of 7 stations for peak average concentrations and 3 stations for background concentrations, was selected for a desired minimum detection capability of 50% of concentration variations. Networks with fewer stations would be selected if smaller minimum detection capabilities of concentration variations are acceptable, and vice versa. Background stations could, of course, be deleted for networks with the sole purpose of discerning peak concentrations.

Optimization of ambient air quality monitoring networks

A method has been developed to obtain a joint solution to the problem of optimum number and configuration of ambient air quality monitors, on the principles of spatial correlation analysis and the minimum spanning tree. The interest in this case is to represent the patterns of regional air quality, at a minimum of an overlap of information. This methodology is extended to account for the uncertainties in air quality simulations and also to incorporate the probabilities of occurrence. As an illustration to these methodologies, an example of Taipei City, Taiwan has been considered.

Visibility in California

A comprehensive study is conducted of visibility in California using prevailing visibility measurements at 67 weather stations in conjunction with data on particulate concentrations and meteorology. The weather station visibility data, when handled with special techniques that account for the nature of visibility reporting practices, prove to be of very good quality for the purposes of most of the analyses that are attempted. It is found that the most important meteorological parameters with respect to visibility are relative humidity, temperature, and special weather events (especially fog). A detailed isopleth map of visibility within California, when compared with earlier work on nationwide visibility, reveals that California experiences far more severe and complex spatial gradients in visibility than those observed anywhere else in the U.S. Two major pockets of heavy man-made visibility impact in California are the Los Angeles basin and the San Joaquin Valley. The spatial, seasonal, and diurnal patterns of visibility are found to be readily explainable in terms of corresponding patterns in emissions, air quality, and meteorology. Regression analyses relating visibility to relative humidity and aerosol concentrations produce high levels of correlation and physically reasonable regression coefficients; these analyses indicate that secondary aerosols are major contributors to visibility reduction in California. An analysis of long-term visibility trends from 1949 to 1976 reveals several interesting features in historical visibility changes for California.

Dependence of Air Quality in a Remote Location on Local and Mesoscale Transports: A Case Study

Abstract The results of a field study utilizing ground-based and aircraft measurements of meteorological parameters and several air pollutants are described for two summer periods in the vicinity of Yosemite National Park, California. These results are related to observed air quality and atmospheric circulation patterns in neighboring parts of the state and to transport by the local mountain-valley wind system. The conclusion is reached that maximum air quality degradation in the study area does not occur during persistent periods of large-scale stagnation, but occurs as the result of transport from area sources up to 200 km away by the typical extended sea breeze circulation which develops following such a period.

Design of an optimum air monitoring network for exposure assessments

Nonlinear programming techniques are frequently used to design optimum monitoring networks. These mathematically rigorous techniques are difficult to implement or cumbersome when considering other design criteria. This paper presents a more pragmatic approach to the design of an optimal monitoring network to estimate human exposure to hazardous air pollutants. In this approach, an air quality simulation model is used to produce representative air quality patterns, which are then combined with population patterns to obtain typical exposure patterns. These combined patterns are used to determine ‘figures of merit’ for each potential monitoring site, which are used to identify and rank the most favorable sites. The spatial covariance structure of the air quality patterns is used to draw a ‘sphere of influence’ around each site to identify and eliminate redundant monitoring sites. This procedure determines the minimum number of sites required to achieve the desired spatial coverage. This methodology was used to design an optimal ambient air monitoring network for assessing population exposure to hazardous pollutants in the southeastern Ohio River valley.