Influence of urban form on air quality: The combined effect of block typology and urban planning indices on city breathability.

Urban morphology affects airflow, causing pollutant accumulation within the urban canopy. Urban planning can regulate urban form by applying such strategies as defining urban block typology and stipulating urban indices. Consequently, urban planning can contribute to a healthy environment. In this context, modeling pollutant dispersion can assist urban planning decisions. Nonetheless, there is a lack of studies investigating the combined impact of urban block typology and urban indices on air quality. Therefore, this study aims to analyze the impact of these combined strategies on pollutant dispersion. Using computational fluid dynamics techniques, we investigated three combinations of urban indices (floor area ratio, surface coverage, and height) for three urban block typologies (single-block, detached building, and central courtyard). A total of nine urban configurations were distributed into three sets of urban index values for the three block typologies, namely "basic cases," "1-cases," and "2-cases." We used the Unsteady Reynolds-Averaged Navier-Stokes equations and the κ-ω SST turbulence model for the numerical simulations. The validation was conducted using wind tunnel experimental data. To assess city breathability at pedestrian height we used five parameters: pollutant concentration, the mean age of air, net escape velocity, and pollutant mass fluxes. The results showed that both strategies (i.e., block typology and urban indices) affect urban air quality. However, the performance of a block typology depends on the urban index values. For instance, in the "2-cases," decreasing the surface coverage by increasing the building's height improved ventilation efficiency in all typologies. Nonetheless, this strategy changed the performance ranking of the "basic cases." In "basic cases" the single-block typology had the best performance; in the "2-cases," the courtyard typology performed best. Although the courtyard typology improved air quality inside the patio, the outdoor areas displayed more pollutant concentration. Finally, general orientations to developing urban planning strategies were formulated.

Exposure and dose assessment of school children to air pollutants in a tropical coastal-urban area.

This study estimates exposure and inhaled dose to air pollutants of children residing in a tropical coastal-urban area in Southeast Brazil. For that, twenty-one children filled their time-activities diaries and wore the passive samplers to monitor NO2. The personal exposure was also estimated using data provided by the combination of WRF-Urban/GEOS-Chem/CMAQ models, and the nearby monitoring station. Indoor/outdoor ratios were used to consider the amount of time spent indoors by children in homes and schools. The model's performance was assessed by comparing the modelled data with concentrations measured by urban monitoring stations. A sensitivity analyses was also performed to evaluate the impact of the model's height on the air pollutant concentrations. The results showed that the mean children's personal exposure to NO2 predicted by the model (22.3 µg/m3) was nearly twice to those measured by the passive samplers (12.3 µg/m3). In contrast, the nearest urban monitoring station did not represent the personal exposure to NO2 (9.3 µg/m3), suggesting a bias in the quantification of previous epidemiological studies. The building effect parameterisation (BEP) together with the lowering of the model height enhanced the air pollutant concentrations and the exposure of children to air pollutants. With the use of the CMAQ model, exposure to O3, PM10, PM2.5, and PM1 was also estimated and revealed that the daily children's personal exposure was 13.4, 38.9, 32.9, and 9.6 µg/m3, respectively. Meanwhile, the potential inhalation daily dose was 570-667 µg for PM2.5, 684-789 µg for PM10, and 163-194 µg for PM1, showing to be favourable to cause adverse health effects. The exposure of children to air pollutants estimated by the numerical model in this work was comparable to other studies found in the literature, showing one of the advantages of using the modelling approach since some air pollutants are poorly spatially represented and/or are not routinely monitored by environmental agencies in many regions.

A review on the role of dispersion and receptor models in asthma research.

There is substantial evidence that air pollution exposure is associated with asthma prevalence that affects millions of people worldwide. Air pollutant exposure can be determined using dispersion models and refined with receptor models. Dispersion models offer the advantage of giving spatially distributed outdoor pollutants concentration while the receptor models offer the source apportionment of specific chemical species. However, the use of dispersion and/or receptor models in asthma research requires a multidisciplinary approach, involving experts on air quality and respiratory diseases. Here, we provide a literature review on the role of dispersion and receptor models in air pollution and asthma research, their limitations, gaps and the way forward. We found that the methodologies used to incorporate atmospheric dispersion and receptor models in human health studies may vary considerably, and several of the studies overlook features such as indoor air pollution, model validation and subject pathway between indoor spaces. Studies also show contrasting results of relative risk or odds ratio for a health outcome, even using similar methodologies. Dispersion models are mostly used to estimate air pollution levels outside the subject's home, school or workplace; however, very few studies addressed the subject's routines or indoor/outdoor relationships. Conversely, receptor models are employed in regions where asthma incidence/prevalence is high or where a dispersion model has been previously used for this assessment. Road traffic (vehicle exhaust) and NOx are found to be the most targeted source and pollutant, respectively. Other key findings were the absence of a standard indicator, shortage of studies addressing VOC and UFP, and the shift toward chemical speciation of exposure.

Deconstruction of annoyance due to air pollution by multiple correspondence analyses.

Annoyance caused by air pollution is a matter of public health as it can cause stress and ill-health and affect quality of life, among other burdens. The aim of this study is to apply the multiple correspondence analyses (MCA) technique as a differential tooling to explore relationships between variables that can influence peoples' behaviour concerning annoyance caused by air pollution. Data were collected through a survey on air pollution, environmental issues and quality of life. Face-to-face survey studies were conducted in two industrialized urban areas (Vitoria in Brazil and Dunkirk in France). These two regions were chosen as their inhabitants often report feeling annoyed by air pollution, and both regions have similar industrial characteristics. The results showed a progressive correspondence between levels of annoyance and other active variables in the "air pollution" factor group: as the levels of annoyance increased, the levels of the other qualitative variables (importance of air quality, perceived exposure to industrial risk, assessment of air quality, perceived air pollution) also increased. Respondents who reported feeling annoyed by air pollution also thought that air quality was very important and were very concerned about exposure to industrial risks. Furthermore, they often assessed air quality as horrible, and they could frequently perceive air pollution by dust, odours and decreased visibility. The results also showed a statistically significant association between occurrence of allergies and high levels of annoyance.

The role of receptor models as tools for air quality management: a case study of an industrialized urban region.

Evidence suggesting the association between the atmospheric particulate matter (PM) and health problems stress the need for the establishment of policies and actions aiming the improvement of air quality. As a start point, the knowledge of the main PM contributors is fundamental. Receptor models are frequently used for the identification and apportionment of local sources, nevertheless, some features of these models must be considered. For instance, whether the region has sources with similar chemical profiles and/or whether there is source temporal or spatial similarity, which can generate collinearity, affecting the sensibility of the models. In this work, it is presented some study of cases showing some strengths of the chemical mass balance model (CMB), such as to infer specific sources acting over specific locations in a same region, and its weaknesses for separating collinear sources. Besides, this work shows some study of cases reporting that the identification of specific PM markers (organic, inorganic, and crystallographic) and determined in the receptor samples can lead to better sources separation and improvements in the interpretation of the results using positive matrix factorization model. This work also highlights for the importance of the information provided by receptor models, in which should be carefully considered by the environmental agencies for decision-making concerning air quality management.

Use of inorganic and organic markers associated with their directionality for the apportionment of highly correlated sources of particulate matter.

Particulate matter source identification using receptor models is one of the tools applied in air quality management. These models have limitations such as the collinearity effects, hindering their application and interpretation. Positive Matrix Factorization (PMF) models use chemical markers for the definition of likely sources, leaving to users the factors interpretation. This can lead to biased interpretations, as chemical species can be markers for several sources, particularly when there is source similarity. The Region of Greater Vitória, located southeast of Brazil, is a complex site in which similar industrial activities are installed, such as a pelletizing plant and a steel plant, that produce iron pellets and sinter, both iron-agglomerates with similar chemical profiles. To minimize the effects of collinearity between those sources, a new PMF approach is proposed by using inorganic and organic chemical species and the directionality of pollutant using wind roses. The proposed methodology determines the following consolidated markers: elemental carbon (EC) and organic carbon (OC) for vehicular sources; chloride (Cl) and sodium (Na) for sea salt; iron (Fe) for industrial sources. This association was possible by identifying the directionality of the chemical species. Cl a typical sea salt marker also attributed to industrial sintering activities. Some PMF factors showed high OC loadings, a typical marker for both vehicular exhaust and coal burning. The definition of the most appropriate sources for those factors was only possible due to the assessment of the pollutant roses. Pollutant roses generally showed that higher concentrations of potassium (K), a marker of biomass burning, was predominantly associated with winds from an industrial park, and are most likely associated with sintering emissions. Results showed that combining both organic and inorganic markers with the pollutant roses for identification of the directionality of predominant sources improved the interpretation of PMF factor numbers in source apportionment studies.

Resonant Synchrotron X-ray Diffraction determines markers for iron-rich atmospheric particulate matter in urban region.

Particulate matter driven health problems are strongly associated with its chemical composition. Despite the benefits of using source apportionment models for air quality management, limitations such as collinearity effects, restrict their application or compromise the accurate separation of sources, particularly for particulate matter with similar chemical profiles. Receptors models also depend on the operator expertise to appropriately classified sources, a subjective process that can lead to biased results. For highly correlated sources, the identification of specific markers is still the best way to achieve proper source apportionment. In this study, Resonant Synchrotron X-ray Diffraction has been applied to the analysis of atmospheric particles to determine markers for industrial and vehicular sources in the Region of Greater Vitória, Brazil. Total suspended particulate matter, PM10, and PM2.5 samples were analyzed by Resonant Synchrotron X-ray Diffraction showing high levels of iron-based crystalline phases. In comparison to the use of chemical elemental species, the identification of the crystalline phases provided an enhanced approach to classify specific iron-based source markers. For this study, α-Fe2O3 was identified with iron-based sources such as iron ore, pelletizing, and sintering; metallic Fe was inferred with blast furnaces and steelmaking; FeS2 was correlated with coal deposits; and K2Fe2O4 was associated to sintering emissions. Elemental carbon with different X-ray diffraction patterns enabled the differentiation of industrial and vehicular sources. The attribution of crystal rather than elemental composition in the identification of sources improves the accuracy of source apportionment studies.

Trends in analytical techniques applied to particulate matter characterization: A critical review of fundaments and applications.

Epidemiological studies have shown the association of airborne particulate matter (PM) size and chemical composition with health problems affecting the cardiorespiratory and central nervous systems. PM also act as cloud condensation nuclei (CNN) or ice nuclei (IN), taking part in the clouds formation process, and therefore can impact the climate. There are several works using different analytical techniques in PM chemical and physical characterization to supply information to source apportionment models that help environmental agencies to assess damages accountability. Despite the numerous analytical techniques described in the literature available for PM characterization, laboratories are normally limited to the in-house available techniques, which raises the question if a given technique is suitable for the purpose of a specific experimental work. The aim of this work consists of summarizing the main available technologies for PM characterization, serving as a guide for readers to find the most appropriate technique(s) for their investigation. Elemental analysis techniques like atomic spectrometry based and X-ray based techniques, organic and carbonaceous techniques and surface analysis techniques are discussed, illustrating their main features as well as their advantages and drawbacks. We also discuss the trends in analytical techniques used over the last two decades. The choice among all techniques is a function of a number of parameters such as: the relevant particles physical properties, sampling and measuring time, access to available facilities and the costs associated to equipment acquisition, among other considerations. An analytical guide map is presented as a guideline for choosing the most appropriated technique for a given analytical information required.

Source apportionment of settleable particles in an impacted urban and industrialized region in Brazil.

Settleable particulate matter (SPM), especially coarser particles with diameters greater than 10 µm, has been found culprit of high deposition rates in cities affected by hinterland industrial activities. This is the case of Metropolitan Region of Vitoria (MRV), Espirito Santo, Brazil where industrial facilities are located within the urban sprawl and building constructions are intense. Frequent population complaints to the environmental protection agency (IEMA) throughout the years have triggered monitoring campaigns to determine SPM deposition rates and source apportionment. Eight different locations were monitored throughout the MRV, and SPM was quantified and chemically characterized. Sources profiles were defined either by using US EPA SPECIATE data or by experimental analysis. Atmospheric fallout in the MRV ranged between 2 and 20g/(m2 30-day), with only one monitoring station ranging from 6-10 g/(m2 30-day). EC, OC, Fe, Al, and Si were found the main constituents of dry deposition in the region. Source apportionment by the chemical mass balance (CMB) model determined that steel and iron ore pelletizing industries were the main contributor to one of the eight locations whereas resuspension, civil construction, and vehicular sources were also very important contributors to the other stations. Quarries and soil were also considered expressive SPM sources, but at the city periphery. CMB model could differentiate contributions from six industrial source groups: thermoelectric; iron ore, pellet, and pellet furnaces; coal coke and coke oven; sintering, blast furnace, and basic oxygen furnace; and soil, resuspension, and vehicles. However, the CMB model was unable to differentiate between iron ore and pellet stockpiles which are present in both steel and iron ore pelletizing industries. Further characterization of source and SPM might be necessary to aid local authorities in decision-making regarding these two industrial sources.

Association between the concentration of fine particles in the atmosphere and acute respiratory diseases in children.

OBJECTIVE: To analyze the association between fine particulate matter concentration in the atmosphere and hospital care by acute respiratory diseases in children. METHODS: Ecological study, carried out in the region of Grande Vitória, Espírito Santo, in the winter (June 21 to September 21, 2013) and summer (December 21, 2013 to March 19, 2014). We assessed data of daily count for outpatient care and hospitalization by respiratory diseases (ICD-10) in children from zero to 12 years in three hospitals in the Region of Grande Vitória. For collecting fine particulate matter, we used portable samplers of particles installed in six locations in the studied region. The Generalized Additive Model with Poisson distribution, fitted for the effects of predictor covariates, was used to evaluate the relationship between respiratory outcomes and concentration of fine particulate matter. RESULTS: The increase of 4.2 µg/m3 (interquartile range) in the concentration of fine particulate matter increased in 3.8% and 5.6% the risk of medical care or hospitalization, respectively, on the same day and with six-day lag from the exposure. CONCLUSIONS: We identified positive association between outpatient care and hospitalizations of children under 12 years due to acute respiratory diseases and the concentration of fine particulate matter in the atmosphere. OBJETIVO: Analisar a associação entre a concentração de material particulado fino na atmosfera e atendimento hospitalar por doenças respiratórias agudas em crianças. MÉTODOS: Estudo ecológico, realizado na Região da Grande Vitória, ES, no inverno (21 de junho a 21 de setembro de 2013) e no verão (21 de dezembro de 2013 a 19 de março de 2014). Foram avaliados dados de contagem diária de atendimentos ambulatoriais e hospitalizações por doenças respiratórias (CID-10) em crianças de zero a 12 anos em três hospitais da Região da Grande Vitoria. Para a coleta de material particulado fino foram utilizados amostradores portáteis de partículas instalados em seis locais na região estudada. O Modelo Aditivo Generalizado com distribuição de Poisson, ajustado para efeitos das covariáveis preditoras, foi utilizado para avaliar a relação entre os desfechos respiratórios e a concentração de material particulado fino. RESULTADOS: O incremento de 4,2 µg/m3 (intervalo interquartílico) na concentração de material particulado fino aumentou em 3,8% e 5,6% o risco de atendimento ou internação, respectivamente, no mesmo dia e com seis dias de defasagem da exposição. CONCLUSÕES: Foi identificada associação positiva entre atendimentos ambulatoriais e hospitalizações de crianças com até 12 anos devido a doenças respiratórias agudas e a concentração de material particulado fino na atmosfera.

Impact assessment of odours emitted by a wastewater treatment plant.

Complaints from the Domingos Martins population about sewage odours in the city made the district attorney order an impact assessment of the odours emitted by the city wastewater treatment plant (WWTP). This study comprised various techniques, models and population surveys. In 2007, an odour emission model proved that the main hydrogen sulphide emitter was the aeration tank of the WWTP (13.5 g h(-1)) and such emissions, according to CALPUFF model, should be perceived in the whole Domingos Martins city centre area. In this area, 58% of those interviewed were annoyed by the WWTP odours. However, in 2009, the odour monitoring panel recorded few odour occurrences. A second population survey showed that hereafter only 20% of those interviewed were annoyed by the WWTP emissions. Odour emission and dispersion models run with 2010 data proved a drastic reduction of the WWTP aeration tank emissions and consequently the city centre was not bothered by WWTP emissions anymore. The odour emission reduction was due to the modification of the WWTP aeration tank system. Despite the odour emission reduction, houses located southeast of the WWTP were still annoyed by sewage odours. However, in this part of the town, other sources of sewage odours have been found.

Volatilization of hydrogen sulfide from a quiescent surface.

Air-water mass transfer of hydrogen sulfide from a shallow tank with a quiescent surface under the influence of weak wind stress on the water surface was studied numerically using a two-dimensional model. The flow field in the tank was investigated using a computational code based on a finite volume, which is used to numerically solve momentum, mass and continuity conservation equations. The results show that water phase flow field is strongly dependent on the wind-induced surface velocity and the aspect ratio of the tank. Based on the numerical study, the liquid-side mass transfer coefficient is correlated with Reynolds number (R(e)), tank aspect ratio (AR) and Schmidt number (S(c)). Overall mass transfer coefficient (K(L)) values extend further downstream as the R(e) number increases.

Mathematical modelling of hydrogen sulphide emission and removal in aerobic biofilters comprising chemical oxidation.

Four different empirical expressions have been compared for estimating the removal of hydrogen sulphide (H(2)S) from wastewater by chemical oxidation during its treatment in an aerated biofilter. The relative importance of this removal process is considered in a mass balance proposed by an emission model. Two of the four models investigated were able to predict the mean H(2)S removed fraction within a confidence interval of 95% and they demonstrated good agreement with experimental data. Biodegradation and oxidation were the two main removal mechanisms in the biofilter whereas stripping and volatilization made only minor contributions. However they can be of significance when the emission rates are calculated.