Spatiotemporal modelling of ozone distribution in the State of California

This paper is concerned with the spatiotemporal mapping of monthly 8-h average ozone (O₃) concentrations over California during a 15-years period. The basic methodology of our analysis is based on the spatiotemporal random field (S/TRF) theory. We use a S/TRF decomposition model with a dominant seasonal O₃ component that may change significantly from site to site. O₃ seasonal patterns are estimated and separated from stochastic fluctuations. By means of Bayesian Maximum Entropy (BME) analysis, physically meaningful and sufficiently detailed space–time maps of the seasonal O₃ patterns are generated across space and time. During the summer and winter months the seasonal O₃ concentration maps exhibit clear and progressively changing geographical patterns over time, suggesting the existence of relationships in accordance with the typical physiographic and climatologic features of California. BME mapping accuracy can be superior to that of other techniques commonly used by EPA; its framework can rigorously assimilate useful data sources that were previously unaccounted for; the generated maps offer valuable assessments of the spatiotemporal O₃ patterns that can be helpful in the identification of physical mechanisms and their interrelations, the design of human exposure and population health models, and in risk assessment. As they focus on the seasonal patterns, the maps are not contingent on short-time and locally prevalent weather conditions, which are of no interest in a global and non-forecasting framework. Moreover, the maps offer valuable insight about the space–time O₃ concentration patterns and are, thus, helpful for disentangling the influence of explanatory factors or even for identifying some influential ones that could have been otherwise overlooked.     

Quantifying road dust resuspension in urban environment by Multilinear Engine: A comparison with PMF2

Atmospheric PM pollution from traffic comprises not only direct emissions but also non-exhaust emissions because resuspension of road dust that can produce high human exposure to heavy metals, metalloids, and mineral matter. A key task for establishing mitigation or preventive measures is estimating the contribution of road dust resuspension to the atmospheric PM mixture. Several source apportionment studies, applying receptor modeling at urban background sites, have shown the difficulty in identifying a road dust source separately from other mineral sources or vehicular exhausts. The Multilinear Engine (ME-2) is a computer program that can solve the Positive Matrix Factorization (PMF) problem. ME-2 uses a programming language permitting the solution to be guided toward some possible targets that can be derived from a priori knowledge of sources (chemical profile, ratios, etc.). This feature makes it especially suitable for source apportionment studies where partial knowledge of the sources is available.In the present study ME-2 was applied to data from an urban background site of Barcelona (Spain) to quantify the contribution of road dust resuspension to PM₁₀ and PM_2.5 concentrations. Given that recently the emission profile of local resuspended road dust was obtained (Amato, F., Pandolfi, M., Viana, M., Querol, X., Alastuey, A., Moreno, T., 2009. Spatial and chemical patterns of PM₁₀ in road dust deposited in urban environment. Atmospheric Environment 43 (9), 1650–1659), such a priori information was introduced in the model as auxiliary terms of the object function to be minimized by the implementation of the so-called “pulling equations”.ME-2 permitted to enhance the basic PMF solution (obtained by PMF2) identifying, beside the seven sources of PMF2, the road dust source which accounted for 6.9 μg m^?3 (17%) in PM₁₀, 2.2 μg m^?3 (8%) of PM_2.5 and 0.3 μg m^?3 (2%) of PM₁. This reveals that resuspension was responsible of the 37%, 15% and 3% of total traffic emissions respectively in PM₁₀, PM_2.5 and PM₁. Therefore the overall traffic contribution resulted in 18 μg m^?3 (46%) in PM₁₀, 14 μg m^?3 (51%) in PM_2.5 and 8 μg m^?3 (48%) in PM₁. In PMF2 this mass explained by road dust resuspension was redistributed among the rest of sources, increasing mostly the mineral, secondary nitrate and aged sea salt contributions.     

Tethered balloon-based soundings of ozone,aerosols, and solar radiation near Mexico City during MIRAGE-MEX

A tethered balloon sampling system was used to measure vertical profiles of ozone, particles, and solar radiation in the atmospheric boundary layer on the northern edge of Mexico City, in March 2006 as part of the Megacity Impact on Regional and Global Environment-Mexico experiment. Several commercial sensors, designed for surface applications, were deployed on a tethered balloon platform.Profiles indicate that for these 3 scalars the boundary layer (surface up to 700 m) was well mixed in the period 10:00–16:00 LST. Good agreement was observed for median surface and balloon ozone and particle number concentrations. For most profiles, the surface deposition of ozone was not significant compared to median profile concentrations. Particle number concentration (0.3, 0.5, 1.0 and 5.0 μm) also showed little variation with attitude. Radiatprofiles showed a monotonic increase in diffuse radiation from the maximum altitude of profiles to the surface. Consequently, it was inferred that surface measurements of these likely were representative of lower boundary layer values during this time period.     

Characterization and sources assignation of PM2.5 organic aerosol in a rural area of Spain

The results from a year-long study of the organic composition of PM2.5 aerosol collected in a rural area influenced by a highway of Spain are reported. The lack of prior information related to the organic composition of PM2.5 aerosol in Spain, concretely in rural areas, led definition of the goals of this study. As a result, this work has been able to characterize the main organic components of atmospheric aerosols, including several compounds of SOA, and has conducted a multivariate analysis in order to assign sources of particulate matter. A total of 89 samples were taken between April 2004 and April 2005 using a high-volume sampler. Features and abundance of n-alkanes, polycyclic aromatic hydrocarbons (PAHs), alcohols and acids were separately determined using gas chromatography/mass spectrometry and high performance liquid chromatography analysis. The Σn-alkane and ΣPAHs ranged from 3 to 81 ng m^?3 and 0.1 to 6 ng m^?3 respectively, with higher concentrations during colder months. Ambient concentrations of Σalcohols and Σacids ranged from 21 to 184 ng m^?3 and 39 to 733 ng m^?3, respectively. Also, several components of secondary organic aerosol have been quantified, confirming the biogenic contribution to ambient aerosol. In addition, factor analysis was used to reveal origin of organic compounds associated to particulate matter. Eight factors were extracted accounting more than 83% of the variability in the original data. These factors were assigned to a typical high pollution episode by anthropogenic particles, crustal material, plant waxes, fossil fuel combustion, temperature, microbiological emissions, SOA and dispersion of pollutants by wind action. Finally, a cluster analysis was used to compare the organic composition between the four seasons.     

Assessment of source apportionment by Positive Matrix Factorization analysis on fine and coarse urban aerosol size fractions

This study was conducted in order to investigate the differences observed in source profiles in the urban environment, when chemical composition parameters from different aerosol size fractions are subjected to factor analysis. Source apportionment was performed in an urban area where representative types of emission sources are present. PM₁₀ and PM₂ samples were collected within the Athens Metropolitan area and analysed for trace elements, inorganic ions and black carbon. Analysis by two-way and three-way Positive Matrix Factorization was performed, in order to resolve sources from data obtained for the fine and coarse aerosol fractions. A difference was observed: seven factors describe the best solution in PMF3 while six factors in PMF2. Six factors derived from PMF3 analysis correspond to those described by the PMF2 solution for the fine and coarse particles separately. These sources were attributed to road dust, marine aerosol, soil, motor vehicles, biomass burning, and oil combustion. The additional source resolved by PMF3 was attributed to a different type of road dust. Combustion sources (oil combustion and biomass burning) were correctly attributed by PMF3 solely to the fine fraction and the soil source to the coarse fraction. However, a motor vehicle's contribution to the coarse fraction was found only by three-way PMF. When PMF2 was employed in PM₁₀ concentrations the optimum solution included six factors. Four source profiles corresponded to the previously identified as vehicles, road dust, biomass burning and marine aerosol, while two could not be clearly identified. Source apportionment by PMF2 analysis based solely on PM₁₀ aerosol composition data, yielded unclear results, compared to results from PMF2 and PMF3 analyses on fine and coarse aerosol composition data.     

Analysis of cloud and precipitation chemistry at Whiteface Mountain,NY

Federal and state programs over the past two decades have resulted in the reduction of emissions of precursors of acid rain. Concomitant with these changes, measured concentrations of acidity in precipitation and in watersheds have shown a downward trend or improvement. However, another pathway for these precursors is through cloud and fog events that often tend to occur at high-elevation regions affecting the fauna and flora as well. In this study we report on long-term measurements of cloud water and precipitation chemistry made from 1994 onwards at a high-elevation location, Whiteface Mountain NY, in the northeastern United States. Trends and inter-relationship between the ions were examined along with ambient SO₂ measurements and Adirondack lakes chemistry data.     

Gender (in)difference in private offices: A holistic approach for assessing satisfaction and personalization

This research is a combination of gender studies, which highlights differences between men and women, and workplace research, which focuses on the performances that are assumed to affect employee satisfaction. The study proposes a multi-dimensional assessment model that enables consideration of several workplace issues in tandem. Focusing on user satisfaction, the first part of the study is a holistic approach concerned with technical, functional and behavioral variables that provides a broad understanding about gender (in)differences. Personalization, the core issue of the second part of the study, is measured through personal display items, autonomous behavior and office layout preferences of men and women employees. The findings indicate the presence of significant gender differences in terms of satisfaction felt with regard to the behavioral variables. The results also support previous findings indicating that men and women use different personal display items in order to personalize their offices. More women were diagnosed to be changing their room layout on a temporary basis whereas men and women were evidenced for having similar attitudes in making permanent changes and in preferring an office layout for themselves. The findings suggest that gender difference is still a valid subject in workplace research although the differences may not be as sharp as the conventional gender difference myth claims, implying a better understanding of the issues that differently satisfy men and women.     

Vegetation and outdoor recess time at elementary schools: What are the connections?

Empirical and anecdotal evidence suggests that landscapes with more vegetation have a positive impact on children's focus, attention, and cognitive development. In school, children are able to regain focus, suppress impulses, and pay attention in class longer after exposure to natural settings. Because children spend much of their time in school, the amount and types of vegetation on school grounds may influence their development. Public elementary schools in the Commonwealth of Virginia (N = 988) were surveyed to examine correlations between school ground vegetation and outside recess. The number of trees on school grounds, the size of the school grounds, and the presence of sports fields were modestly correlated with greater outside recess time. These correlations support common sense because sports fields facilitate supervised play and larger school grounds provide space for sports fields and playgrounds and additional opportunities for free play. More trees on school grounds provide a welcoming environment for students and teachers, and encourage outside play. These results may help school personnel design and maintain school grounds that increase outdoor recess time.     

Urbanization and its impact on groundwater: a remote sensing and GIS-based assessment approach

The perils of unplanned urbanization and increasing pressure of human activities on hydro-geomorphologic system often result in modification of the existing recharge mechanism, which leads to many environmental consequences. In the present research, an attempt has been made to investigate the applicability of remote sensing and geographical information system (GIS) in dealing with spatial and temporal variability of dynamic phenomena, like urbanization and its impact on groundwater. This paper covers primarily, quantitative and qualitative impacts of urban growth on the behavior of aquifer in Ajmer city (India). Urban growth of the Ajmer city in last 17 years has been estimated from the satellite images. Database related to urbanization and groundwater has been created in GIS. Groundwater recharge has been computed using a water balance approach known as Water Level Fluctuation Methodology. Recharge estimation methodology has been implemented in GIS to introduce the spatial variability of hydro-geological characteristics. Further, temporal and spatial variations in groundwater quality and quantity have been correlated with urban growth using overlay analysis in GIS. The study reveals a general decline in water table and quality with urbanization. Further, remote sensing and GIS technologies have been found useful in assessment of spatial and temporal phenomena of urbanization and its impact on groundwater system.     

An imprecise fuzzy risk approach for water quality management of a river system

Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA) problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max–min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga–Bhadra river system in India.