Selection and evaluation of air pollution exposure indicators based on geographic areas

Size-resolved particle emission factors of vehicular traffic derived from urban eddy covariance measurements

Road traffic is one of the major sources of atmospheric particles in urban areas. Modelling the contribution of this source to urban pollution requires reliable estimates of emission factors possibly resolved in size. In this work, size-resolved particle emission factors (EFs) of the mixed vehicle fleet were measured in the urban area of Lecce (south-eastern Italy). The approach used is based on vertical fluxes measured with eddy-covariance, counting of vehicles, and estimation of footprints. Results show that the average EF in number (range 0.009-3 μm) was 2.2*10¹⁴ #/Veh km, being dominated by ultrafine particles (D_p < 0.25 μm) due to exhaust emissions. EF number size distribution decreases with particle size. A reduction of more than four orders of magnitude was observed at D_p ≅ 0.9 μm. EF mass size distribution reaches a maximum around D_p ≅ 0.3 μm then decreases until D_p ≅ 0.9 μm. For larger particles EF in mass increases for the influence of non-exhaust emissions. Average emission factor of PM₁ was 56 mg/Veh Km and that of PM_2.5 was 63 mg/Veh Km. A comparison of measurements taken in 2010 and 2015 in the same area shows a decreasing trend of the average total EF in number of about 56%, likely as a consequence of the increased use of new generation vehicles following more restrictive limits for particle emissions.

Characterization of exposure in epidemiological studies on air pollution from biodegradable wastes: Misclassification and comparison of exposure assessment strategies

The assignment of exposure is one of the main challenges faced by environmental epidemiologists. However, misclassification of exposures has not been explored in population epidemiological studies on air pollution from biodegradable wastes. The objective of this study was to investigate the use of different approaches for assessing exposure to air pollution from biodegradable wastes by analyzing (1) the misclassification of exposure that is committed by using these surrogates, (2) the existence of differential misclassification (3) the effects that misclassification may have on health effect estimates and the interpretation of epidemiological results, and (4) the ability of the exposure measures to predict health outcomes using 10-fold cross validation. Four different exposure assessment approaches were studied: ammonia concentrations at the residence (Metric I), distance to the closest source (Metric II), number of sources within certain distances from the residence (Metric IIIa,b) and location in a specific region (Metric IV). Exposure-response models based on Metric I provided the highest predictive ability (72.3%) and goodness-of-fit, followed by IV, III and II. When compared to Metric I, Metric IV yielded the best results for exposure misclassification analysis and interpretation of health effect estimates, followed by Metric IIIb, IIIa and II. The study showed that modelled NH₃ concentrations provide more accurate estimations of true exposure than distances-based surrogates, and that distance-based surrogates (especially those based on distance to the closest point source) are imprecise methods to identify exposed populations, although they may be useful for initial studies.

High resolution spatial and temporal mapping of traffic-related air pollutants

Vehicle traffic is one of the most significant emission sources of air pollutants in urban areas. While the influence of mobile source emissions is felt throughout an urban area, concentrations from mobile emissions can be highest near major roadways. At present, information regarding the spatial and temporal patterns and the share of pollution attributable to traffic-related air pollutants is limited, in part due to concentrations that fall sharply with distance from roadways, as well as the few monitoring sites available in cities. This study uses a newly developed dispersion model (RLINE) and a spatially and temporally resolved emissions inventory to predict hourly PM_2.5 and NO_x concentrations across Detroit (MI, USA) at very high spatial resolution. Results for annual averages and high pollution days show contrasting patterns, the need for spatially resolved analyses, and the limitations of surrogate metrics like proximity or distance to roads. Data requirements, computational and modeling issues are discussed. High resolution pollutant data enable the identification of pollutant “hotspots”, “project-level” analyses of transportation options, development of exposure measures for epidemiology studies, delineation of vulnerable and susceptible populations, policy analyses examining risks and benefits of mitigation options, and the development of sustainability indicators integrating environmental, social, economic and health information.

Poluição ambiental, residência materna e baixo peso ao nascer

Estudo caso-controle, que objetivou analisar os fatores de risco associados ao baixo peso ao nascer de recém-nascidos de mães de Rio Grande-RS residentes nas proximidades da área industrial. Foram entrevistadas mães que deram à luz nas maternidades do município, durante os meses de abril a novembro de 2003. A amostra compreendeu 138 casos e 409 controles. Foi realizada análise estatística bivariada e multivariada. O Baixo Peso ao Nascer (BPN) manteve-se associado positivamente com natimortos prévios, BPN prévios, presença de hipertensão arterial durante a gestação e ameaça de aborto durante a gravidez atual. Foi possível identificar os principais fatores de risco a que estão expostas as gestantes e que interferem no peso ao nascer de seus filhos, os quais vêm somar-se àqueles decorrentes de uma maior exposição a poluentes, por residirem próximo às indústrias.

Synthesizing bioaccumulation data from the German metals in mosses surveys and relating them to ecoregions

The European Heavy Metals in Mosses Surveys measure and map environmental concentrations of metals at more than 7000 sites in Europe. In Germany, moss samples were taken at 592 sites in 1990, at 1026 sites in 1995, and at 1028 sites in 2000, where up to 40 metals were measured each time. This article is about how to calculate multi-metal indices from the site- and metal-specific monitoring data and how to link them with the natural regions (ecoregions) of Germany. The ecoregions were calculated with surface data on natural vegetation, elevation, soil texture and climate by means of Classification and Regression Trees (CART). The ecoregions were mapped by GIS and superimposed on a map of multi-metal bioaccumulation indices calculated by means of geostatistics and percentile statistics from the monitoring data. These indices integrate the concentrations of 8 metals measured in 1990, 1995, and 2000 or 12 metals from the 1995 and 2000 surveys, respectively, and the ecoregionalisation enables their geostatistical estimates to be grouped into 21 ecological land categories. This two-step aggregation revealed that, from 1990 to 2000, the multi-metal metal accumulation declined up to 80%, varying with the ecoregions. Based on the multi-metal accumulation index hot spots, the metal accumulation was mapped, ecoregionalised, and suggested for further ecotoxicological assessment. Thus, the approach helps to assess the metal bioaccumulation within ecoregions in a comprehensive and holistic manner over time, space, and metals. This data aggregation is of importance for the environmental reporting in Germany and within the framework of the international environmental information systems. Furthermore, ecoregions may help to plan and optimize monitoring networks. Because monitoring should measure and estimate not only the environmental concentrations of substances but also their impacts on ecoregions, the number of monitoring sites should be proportional to the areas covered by the ecoregions and located according to their spatial variation.

Relationship of Indoor, Outdoor and Personal Air (RIOPA) study: study design, methods and quality assurance/control results

The Relationship of Indoor, Outdoor and Personal Air (RIOPA) Study was undertaken to evaluate the contribution of outdoor sources of air toxics, as defined in the 1990 Clean Air Act Amendments, to indoor concentrations and personal exposures. The concentrations of 18 volatile organic compounds (VOCs), 17 carbonyl compounds, and fine particulate matter mass (PM(2.5)) were measured using 48-h outdoor, indoor and personal air samples collected simultaneously. PM2.5 mass, as well as several component species (elemental carbon, organic carbon, polyaromatic hydrocarbons and elemental analysis) were also measured; only PM(2.5) mass is reported here. Questionnaires were administered to characterize homes, neighborhoods and personal activities that might affect exposures. The air exchange rate was also measured in each home. Homes in close proximity (<0.5 km) to sources of air toxics were preferentially (2:1) selected for sampling. Approximately 100 non-smoking households in each of Elizabeth, NJ, Houston, TX, and Los Angeles, CA were sampled (100, 105, and 105 respectively) with second visits performed at 84, 93, and 81 homes in each city, respectively. VOC samples were collected at all homes, carbonyls at 90% and PM(2.5) at 60% of the homes. Personal samples were collected from nonsmoking adults and a portion of children living in the target homes. This manuscript provides the RIOPA study design and quality control and assurance data. The results from the RIOPA study can potentially provide information on the influence of ambient sources on indoor air concentrations and exposure for many air toxics and will furnish an opportunity to evaluate exposure models for these compounds.

Évaluation de l’exposition à la pollution atmosphérique liée au trafic routier dans les études épidémiologiques : une revue de littérature

BACKGROUND

Automobile exhaust is a major source of air pollution in urban areas. To study health effects of traffic exhaust fumes epidemiologists need specific tools in order to achieve a precise assessment of human exposure to traffic air pollution (TAP) and avoid misclassification. The aim of this review is to study the different ways of assessing human exposure to TAP in epidemiological studies dealing with short-term or long-term health effects of TAP.

METHODS

After presenting the different designs and goals of the studies mentioned above, this review focuses on methods of assessing exposure to TAP and their different associated health endpoints.

RESULTS

To assess exposure to TAP, most published studies have used more or less complex exposure indices. Several teams have used residence location and its proximity to traffic, traffic counts, or a combination of both. More recently, some authors have developed mathematical dispersion models and statistical regression models.

DISCUSSION

Our analysis shows that reliable and validated tools would be needed to assess accurately human exposure to TAP. This can only be achieved with statistical regression models and mathematical dispersion models. Although such methods may be difficult to implement, their use can be facilitated by adding a geographic information system.