Traffic Stations Research Articles

Antimony speciation as geochemical tracer for anthropogenic emissions of atmospheric particulate matter

The chemical composition of atmospheric particulate matter (PM) has been studied at the cities of Cordoba and Granada (South of Spain) between 2007 and 2013, considering urban background, traffic and industrial monitoring stations. The results of Principal Component Analysis (PCA) indicated that geochemical anomalies observed in the ambient air of Cordoba (mainly Cu, Zn, Pb and Cd) are closely related to the geochemical profile obtained from fugitive metallurgy emissions of brass industries. These findings have been confirmed performing an Sb speciation analysis of PM10 samples, which allowed to distinguish between Sb(III) and Sb(V). The percentage of Sb(V) in PM10 found in the traffic station of Granada was 64–69%. At Cordoba, the percentage of Sb(V) was found to be higher (73–77%) at both urban background and traffic stations, indicating a possible second source of Sb in the PM of this city. The PM10 samples from the industrial station of Cordoba showed a 85–86% of Sb(V). A similar percentage (84–88%) of Sb(V) was found for the fugitive emissions of the brass industries, confirming this industrial source of Sb. These results show that Sb speciation can be a useful geochemical tracer to identify anthropogenic sources (traffic and industrial) emissions of PM.

UFP and BC at a mid-sized city in Po valley, Italy: Size-resolved partitioning between primary and newly formed particles

In Po valley (Northern Italy) concentrations of particulate matter (PM) often exceed air quality standards, and road traffic is reported as one of the main sources of pollution. This study investigates the size resolved particle number concentration and size distribution at one rural station, one urban station and one traffic station. The measured size-resolved particle number concentration has been reduced by means of cluster analysis to four particle size fractions (cluster 1: 7–29 nm, cluster 2: 29–95 nm, cluster 3: 95–264 nm, and cluster 4: 264–10,000 nm) based on their behavior in atmosphere according to common time patterns. The primary emissions from traffic are evaluated based on black carbon (BC) and size-resolved particle number concentration data, considering separately single size intervals and providing cluster-resolved information on primary and newly formed particle concentration. Particles directly emitted by vehicle exhaust exhibit similar numbers for the clusters 1 to 3 while newly formed particles mainly occurs in cluster 1. Furthermore, diurnal variation of directly emitted particles is found to closely follow the BC levels, while the trend of newly formed particles varies according to air temperature, solar radiation and particle pollution levels. The results release that in Po valley the variations of particle number levels do not always reflect the variation of road traffic emissions in urban areas as the large availability of anthropogenic precursors can favor summertime nucleation events with region-wide extension.

Modelagem matemática aplicada no planejamento de pesquisa de tráfego rodoviário

O planejamento estratégico do setor de transportes indica as principais diretrizes para investimentos em infraestrutura de maneira a combater, por exemplo, o aumento dos custos associados aos deslocamentos. Com isso, torna-se relevante, minimamente, o conhecimento relativo aos volumes médios diários de tráfego nas rodovias, cargas transportadas, origem e destino de viagens. Estes dados são obtidos por meio de pesquisas de contagem volumétrica e classificatória e de origem e destino. Atualmente, o Departamento Nacional de Infraestrutura de Transportes (DNIT) planeja uma nova pesquisa nacional de tráfego em 300 pontos de pesquisa. Historicamente, o Exército Brasileiro (EB) tem apoiado esta atividade por meio de suas Organizações Militares (OM). Sendo assim, este artigo apresenta um modelo matemático para localização-alocação de OM a postos de pesquisa rodoviária, considerando as características operacionais (capacidade e disponibilidade) e locacionais (abrangência de atendimento) de cada OM. Além disso, foram avaliados cenários simulados que permitem avaliar a aplicação do modelo em diferentes combinações de parâmetros.

Analysis and prediction of $$\mathrm{PM}_{10}$$ PM 10 concentration levels in Tunisia using statistical learning approaches

Over the past years, the health impact of airborne particulate matter $$\mathrm{PM}_{10}$$ has become a very topical subject. Thereby, a lot of research effort in the environmental sciences goes towards the modeling and the prediction of ambient $$\mathrm{PM}_{10}$$ concentrations. In this paper, we are interested in the statistical classification of the daily mean $$\mathrm{PM}_{10}$$ concentration in Tunisia according to the authority regulation. We consider two monitoring stations: a big industrial station and a traffic station. The main goal of this work is to determine the pertinent predictors of $$\mathrm{PM}_{10}$$ concentration within a nonlinear multiclass framework. To do this, we used two popular statistical learning methods; the support vector machines (SVM) and the random forests (RF). The statistical results obtained on the real datasets, show that RF outperform SVM for the purpose of variable selection even with a reduced number of observations compared to the number of explicative variables. It was also demonstrated that the $$\mathrm{PM}_{10}$$ concentration measured yesterday is the most relevant predictor of its present-day value. Moreover, we found that the more delayed values of $$\mathrm{PM}_{10}$$ concentration may be crucial to get an accurate prediction.

Platinum in salt marsh sediments: Behavior and plant uptake

Platinum is one of the least abundant elements in the earth crust with an average concentration of 0.51ngg−1, but its use in several human activities (mainly automobile catalytic converters) is leading its enrichment in surface sediments. Whereas, previous studies have assessed the Pt behavior in soils from urban areas, natural systems are still poorly studied.Accordingly, this study is aimed to characterize the behavior of the Pt released to coastal environments in sediments, ascertain the role of vegetation on the biogeochemistry of this element and assess the transference of Pt into the biological compartments. Several sediment cores were sampled in salt marshes (in unvegetated and vegetated areas) of the Tagus Estuary under different traffic pressure. Platinum concentration was analyzed in solid sediment, interstitial water and roots, leaves and stems of Sarcocornia fruticosa, a typical plant in south European salt marshes. In addition, interpretative parameters (e.g. redox potential, dissolved oxygen, pH, total reduced sulfur species, salinity and dissolved Fe and Mn in interstitial waters) were determined to better understand the biogeochemical cycle of Pt in salt marsh sediments.Although surface enrichment of Pt exists in the sediments at Low Traffic Station (2.8ngg−1), the highest enrichment was found at High Traffic Station where concentration was, in some cases, up to 40ngg−1, linked to traffic emissions. However, dissolved Pt in interstitial waters (from 0.14 to 0.70ngL−1) did not show this superficial maximum. This dissimilarity points out the unreactivity of traffic-borne Pt and the dissolution/precipitation cycle of natural Pt linked to Mn and O2 cycle, depending on the redox conditions, highly controlled by the vegetation. Platinum concentration in roots (0.9±0.6ngg−1) is reflecting the Pt concentration in the interstitial waters in each moment, even though at the two peaks of dissolved Pt (up to 2.5ngL−1) found at deeper layers, reflecting a low bioaccumulation. However, results pointed that a different Pt species (with different bioavailability) may exist in both stations. Besides, Pt mean value in stems and leaves (0.04±0.05ngg−1) indicates a low translocation of Pt from the roots to aerial parts.Therefore, the role of vegetation is fundamental on the geochemical behavior of Pt in sediments, due to the control of the redox conditions by roots in the surrounding sediments (between the O2 release and the organic matter degradation) and leading to Pt species of varying bioavailability.

A wavelet-based approach applied to suspended particulate matter time series in Portugal

This study intends to analyse the particulate matter (PM) levels in Portugal (mainland and islands) throughout a 3-year period. Although a decreasing trend has been observed, the WHO guidelines for the PM10 and PM2.5 annual mean concentrations have been exceeded in all monitoring stations. Most inland urban, rural and suburban sites follow a pronounced seasonal variation with much higher values in winter than in summer. Lower levels and a weak seasonal variability were registered in the two urban background stations of Madeira Island, which are permanently under the influence of clean air masses over the Atlantic. Receiving long-range transported pollution, rural stations located in mountain sites presented an opposite seasonal pattern, with higher levels in summer. Diurnal profiles were also analysed and compared between stations. A mining process was also carried out, consisting in the application of multi-scale wavelet transforms, data pattern identification using cluster analysis and examination of the contribution to the total variance/covariance of the time series per wavelet scale for all stations. Groups of stations exhibiting similar variance/covariance profiles were identified. One group contains urban and rural stations with diurnal and daily time scales. Urban background stations located in the island of Madeira constitute another cluster, corresponding to higher wavelet scales (lower periodicity phenomena). One traffic station in the Oporto metropolitan area was grouped with a suburban/industrial station of central Portugal, suggesting the need for reclassification in what concerns the type of environmental influence.

Modelling the dispersion of particle numbers in five European cities

Abstract. We present an overview of the modelling of particle number concentrations (PNCs) in five major European cities, namely Helsinki, Oslo, London, Rotterdam, and Athens, in 2008. Novel emission inventories of particle numbers have been compiled both on urban and European scales. We used atmospheric dispersion modelling for PNCs in the five target cities and on a European scale, and evaluated the predicted results against available measured concentrations. In all the target cities, the concentrations of particle numbers (PNs) were mostly influenced by the emissions originating from local vehicular traffic. The influence of shipping and harbours was also significant for Helsinki, Oslo, Rotterdam, and Athens, but not for London. The influence of the aviation emissions in Athens was also notable. The regional background concentrations were clearly lower than the contributions originating from urban sources in Helsinki, Oslo, and Athens. The regional background was also lower than urban contributions in traffic environments in London, but higher or approximately equal to urban contributions in Rotterdam. It was numerically evaluated that the influence of coagulation and dry deposition on the predicted PNCs was substantial for the urban background in Oslo. The predicted and measured annual average PNCs in four cities agreed within approximately ≤ 26 % (measured as fractional biases), except for one traffic station in London. This study indicates that it is feasible to model PNCs in major cities within a reasonable accuracy, although major challenges remain in the evaluation of both the emissions and atmospheric transformation of PNCs.

Routing Algorithm of Concentric Excursions for ITS Communication

In the modern society, intelligent transportation builds on the basic of real-time wireless communication with vast information. Only by adding and upgrading the high-costed equipment to keep the speed of communication with the development of the transportation is far from enough (1) . Thus, to make full use of the present equipment to achieve higher speed of information transmission is a practical and challenging project. The Routing Algorithm of this paper is taking the Traffic Management Center as the center. Starting from the center and covering all the traffic management station, we can get the best path program under multi-limits with the help of the combination Algorithm of Shortest Path Algorithms and Concentric Excursions. A lot of constraints has been taken into consideration so as to make the result preciser. The result of multiple experiments has testified the feasibility and efficiency of the algorithm even under the great information content. �

A Statistical Model to Assess Air Quality Levels at Urban Sites

A multivariate analysis was performed in the city of Florence (Italy) to investigate the influence of road traffic and meteorology on air pollution levels at urban traffic stations. Focussing on main traffic-related pollutants (CO, NO, NO2, NO x and PM10), two typical urban road configurations were analysed: a street canyon and an open road. In addition to traffic flows, basic meteorological parameters were considered: wind speed, air temperature and relative humidity. The influence of all drivers by period of the year and day of the week was analysed with correlation analysis, while a statistical model was developed to predict concentrations at traffic stations by using predictors as urban background concentrations, traffic flows and a site-specific constant. Trained on a 1-year period (2008), the model was validated over an independent 1-year period (2007). The highest correlation of urban traffic concentrations was found vs. background concentrations, markedly for PM10 (r = 0.85–0.87). The influence of road traffic was the highest for NO2 (r = 0.51–0.58) and the lowest for PM10 (r = 0.36–0.40). Urban-scale poor advection conditions proved to affect PM10 peak levels more significantly than local traffic increase. For all pollutants, good forecasting capability was achieved by the developed statistical model, generally performing better at the street canyon (r = 0.79–0.86) than at the open road (r = 0.72–0.82).

Differences in Benzene Patterns Among Traffic and Industrial Areas and a Prediction Model for Benzene Rates Based on NO x Values

Exposure to benzene has been associated with multiple severe impacts on health. This notwithstanding, at most monitoring stations, benzene is not monitored on a regular basis. Data were used from two different monitoring stations located on the eastern Mediterranean coast: (1) a traffic monitoring station in Tel Aviv located in an urban region with heavy traffic and (2) a general air quality monitoring station in Haifa Bay located in Israel’s main industrial region. At each station, hourly, daily, monthly, seasonal, and annual data of benzene, NO x , mean temperature, relative humidity, inversion level, and temperature gradient were analyzed over 3 years: 2008, 2009, and 2010. A prediction model for benzene rates based on NO x levels (which are monitored regularly) was developed to contribute to a better estimation of benzene. The severity of benzene pollution was found to be considerably higher at the traffic monitoring station than at the general air quality station, despite the location of the latter in an industrial area. Hourly, daily, monthly, seasonal, and annual patterns have been shown to coincide with anthropogenic activities (traffic), the day of the week, and atmospheric conditions. A strong correlation between NO x and benzene allowed the development of a prediction model for benzene rates based on NO x , the day of the week, and the month. The model succeeded in predicting the benzene values throughout the year. The prediction model suggested in this study might be useful for identifying potential risk of benzene in other urban environments.

The Problem Of Imputation Of The Missing Data From The Continuous Counts Of Road Traffic

AbstractMissing traffic data is an important issue for road administration. Although numerous ways can be found to impute them in foreign literature (inter alia, the most effective method, that is Box-Jenkins models), in Poland, still only proven and simplified methods are applied. The article presents the analyses including an assessment of the completeness of the existing traffic data and works related to the construction of SARIMA model. The study was conducted on the basis of hourly traffic volumes, derived from the continuous traffic counts stations located in the national road network in Poland (Golden River stations) from the years 2005 – 2010. As a result, the proposed model was used to impute the missing data in the form of SARIMA (1.1,1)(0,1,1)168. The newly developed model can be used effectively to fill in the missing required days of measurement for estimating AADT by AASHTO method. In other cases, due to its accuracy and laboriousness of the process, it is not recommended.

Modelling street level PM<sub>10</sub> concentrations across Europe: source apportionment and possible futures

Abstract. Despite increasing emission controls, particulate matter (PM) has remained a critical issue for European air quality in recent years. The various sources of PM, both from primary particulate emissions as well as secondary formation from precursor gases, make this a complex problem to tackle. In order to allow for credible predictions of future concentrations under policy assumptions, a modelling approach is needed that considers all chemical processes and spatial dimensions involved, from long-range transport of pollution to local emissions in street canyons. Here we describe a modelling scheme which has been implemented in the GAINS integrated assessment model to assess compliance with PM10 (PM with aerodynamic diameter <10 μm) limit values at individual air quality monitoring stations reporting to the AirBase database. The modelling approach relies on a combination of bottom up modelling of emissions, simplified atmospheric chemistry and dispersion calculations, and a traffic increment calculation wherever applicable. At each monitoring station fulfilling a few data coverage criteria, measured concentrations in the base year 2009 are explained to the extent possible and then modelled for the past and future. More than 1850 monitoring stations are covered, including more than 300 traffic stations and 80% of the stations which exceeded the EU air quality limit values in 2009. As a validation, we compare modelled trends in the period 2000–2008 to observations, which are well reproduced. The modelling scheme is applied here to quantify explicitly source contributions to ambient concentrations at several critical monitoring stations, displaying the differences in spatial origin and chemical composition of urban roadside PM10 across Europe. Furthermore, we analyse the predicted evolution of PM10 concentrations in the European Union until 2030 under different policy scenarios. Significant improvements in ambient PM10 concentrations are expected assuming successful implementation of already agreed legislation; however, these will not be large enough to ensure attainment of PM10 limit values in hot spot locations such as Southern Poland and major European cities. Remaining issues are largely eliminated in a scenario applying the best available emission control technologies to the maximal technically feasible extent.

Large Sections Peak Traffic Flow Subway Station Simulation Modeling

This paper, three subway lines converge site meet a change to the peak time for passenger flow analysis, with the analysis of passenger flow field physical statistics, image processing technology to guide passenger flow data, analysis of local area biggest traffic speed and density, traffic dynamics theory, the application of mathematical software Matlab, establish mathematical model.

Child exposure to indoor and outdoor air pollutants in schools in Barcelona, Spain

Proximity to road traffic involves higher health risks because of atmospheric pollutants. In addition to outdoor air, indoor air quality contributes to overall exposure. In the framework of the BREATHE study, indoor and outdoor air pollution was assessed in 39 schools in Barcelona. The study quantifies indoor and outdoor air quality during school hours of the BREATHE schools. High levels of fine particles (PM2.5), nitrogen dioxide (NO2), equivalent black carbon (EBC), ultrafine particle (UFP) number concentration and road traffic related trace metals were detected in school playgrounds and indoor environments. PM2.5 almost doubled (factor of 1.7) the usual urban background (UB) levels reported for Barcelona owing to high school-sourced PM2.5 contributions: [1] an indoor-generated source characterised mainly by organic carbon (OC) from organic textile fibres, cooking and other organic emissions, and by calcium and strontium (chalk dust) and; [2] mineral elements from sand-filled playgrounds, detected both indoors and outdoors. The levels of mineral elements are unusually high in PM2.5 because of the breakdown of mineral particles during playground activities. Moreover, anthropogenic PM components (such as OC and arsenic) are dry/wet deposited in this mineral matter. Therefore, PM2.5 cannot be considered a good tracer of traffic emissions in schools despite being influenced by them. On the other hand, outdoor NO2, EBC, UFP, and antimony appear to be good indicators of traffic emissions. The concentrations of NO2 are 1.2 times higher at schools than UB, suggesting the proximity of some schools to road traffic. Indoor levels of these traffic-sourced pollutants are very similar to those detected outdoors, indicating easy penetration of atmospheric pollutants. Spatial variation shows higher levels of EBC, NO2, UFP and, partially, PM2.5 in schools in the centre than in the outskirts of Barcelona, highlighting the influence of traffic emissions. Mean child exposure to pollutants in schools in Barcelona attains intermediate levels between UB and traffic stations.

Modelling NO<sub>2</sub> concentrations at the street level in the GAINS integrated assessment model: projections under current legislation

Abstract. NO2 concentrations at the street level are a major concern for urban air quality in Europe and have been regulated under the EU Thematic Strategy on Air Pollution. Despite the legal requirements, limit values are exceeded at many monitoring stations with little or no improvement in recent years. In order to assess the effects of future emission control regulations on roadside NO2 concentrations, a downscaling module has been implemented in the GAINS integrated assessment model. The module follows a hybrid approach based on atmospheric dispersion calculations and observations from the AirBase European air quality database that are used to estimate site-specific parameters. Pollutant concentrations at every monitoring site with sufficient data coverage are disaggregated into contributions from regional background, urban increment, and local roadside increment. The future evolution of each contribution is assessed with a model of the appropriate scale: 28 × 28 km grid based on the EMEP Model for the regional background, 7 × 7 km urban increment based on the CHIMERE Chemistry Transport Model, and a chemical box model for the roadside increment. Thus, different emission scenarios and control options for long-range transport as well as regional and local emissions can be analysed. Observed concentrations and historical trends are well captured, in particular the differing NO2 and total NOx = NO + NO2 trends. Altogether, more than 1950 air quality monitoring stations in the EU are covered by the model, including more than 400 traffic stations and 70% of the critical stations. Together with its well-established bottom-up emission and dispersion calculation scheme, GAINS is thus able to bridge the scales from European-wide policies to impacts in street canyons. As an application of the model, we assess the evolution of attainment of NO2 limit values under current legislation until 2030. Strong improvements are expected with the introduction of the Euro 6 emission standard for light duty vehicles; however, for some major European cities, further measures may be required, in particular if aiming to achieve compliance at an earlier time.

Regional Accessibility Analysis for Digital Urban Planning Based on GIS

China has been going through urbanization, and foreign experiences show that urbanization would finally lead to integrated planning and development of region. In regional planning, traffic network is an important aspect, which affects the impact of cities. However, in traditional accessibility analysis, only traffic lines are taken into consideration, while the influence of stations is ignored. This lead to the actual problems that traffic facilities cannot play the roles designed in regional planning when they are really constructed. Therefore, firstly, two rank traffic networks system are proposed, and different traffic networks with the normalization costs are combined to analyse the accessibility of the cities. Secondly, a new accessibility analysis method to get arrival domain for a city is proposed, which take not only the traffic lines but the traffic stations into consideration. Finally, the Jing-Jin-Ji Region is taken as an instance to show the effect of the new method.

Practice of Skin Cancer Prevention among Road Traffic Police Officers in Malaysia

The objective of this study was to determine the practice of skin cancer prevention among Malaysian road traffic police officers. This cross-sectional study involved 202 Malaysian Road Police Traffic officers. Inclusion criteria were those officers who work wearing white uniform regulating traffic. The survey took place at the Police Traffic Station, Jln Tun H.S. Lee, Kuala Lumpur, the main Head Quarters of Malaysian's Traffic Department where almost 600 police traffic officers are employed. The police traffic officers are given the task to take care of the traffic from the main office of the police station, then, according to the task, the officers drive to their given location for their duty. Each task is approved by the Chief Traffic Inspector of Kuala Lumpur. Data collected in this study were analyzed using SPSS 13, with the T-test for univariate analysis and multiple linear regression for multivariate analysis. A total of 202 road traffic police officers participated. The majority were older than 30 years of age, male, Malay, married, with secondary education, with monthly income more than 2000 Ringgit Malaysia (66.3%, 91.1%, 86.6%, 84.7%, 96%, 66.3%; respectively). Regarding the practice of skin cancer prevention, 84.6% of the study participants were found to wear hats, 68.9% sunglasses and 85.6% clothing that covering most of the body but only 16.9% used a sunscreen when they were outdoors. When analysis of the factors that influenced the practice of skin cancer prevention was performed, univariate analysis revealed that gender, age and monthly income significantly influenced the practice of skin cancer prevention. For multivariate analysis, gender, monthly income and race significantly influenced the practice of using sunscreen among road traffic police officers (p<0.001, p=0.019, p=0.027; respectively). The practice of skin cancer prevention among the traffic police officers showed good practices in terms of wearinga hat, sun glasses and clothing that covers most of the body. However, the study revealed a poor practice of the use of sunscreen. The factors that influence the practice of sunscreen use were found to be gender, income, and race. The study suggests that more awareness campaign among traffic police officers is needed. Providing sunscreen for free for police traffic officers should be considered by the Police authorities.

Oxidative stress on land snail Helix aspersa as a sentinel organism for ecotoxicological effects of urban pollution with heavy metals

The oxidative stress in the digestive gland of the land snail Helix aspersa was considered as a bioindicator for atmospheric pollution with heavy metals from several industries and vehicular traffic in Kafr El-Zayat city. Regional means of heavy metals concentration of all sites were 0.71, 7.09, 0.71, 2.68, 41.44 and 18.01mgkg−1 wet mass for Cd, Mn, Ni, Pb, Zn and Cu, respectively. In addition, the highest values of Cd concentrations were found 1.22 and 1.73mgkg−1 wet mass in S1 (Potato International Center) and S4 (The Nile bank), respectively. Lactate dehydrogenase (D-LDH(and recorded lipid peroxidation (LPO) levels were significantly high in S1 and S2 (Traffic station). On the other hand, the highest activity of catalase (CAT) was found in S2 (194.04% of control), while the activity of glutathione peroxidase (GPx) reached the highest significant value in S1.As a matter of fact, glutathione-S-transferase (GST) and glutathione reductase (GR) activities were significantly higher in polluted sites than in reference zone. In contrast, the glutathione (GSH) concentration of exposed animals showed significant decrease in all sites, with the lowest value in S1 (57.61% of control). However, metallothioneins concentration (MT) showed no significant difference in all sites except in S1 which accounted for 127.81% of control. Therefore, the overall results of this study showed the importance of H. aspersa as a sentinel organism for biomonitoring the biologic impact of atmospheric pollution in urban areas.

Analysis of the Relationship between Land Use, Development, and Construction near a Rail Traffic Station and Passenger Flow Volume: The Case of Tianjin Metro Line 1

Tianjin Metro Line 1 opened to traffic in June 2006 and has now been in operation for seven years. During this time, Tianjin has grown and developed rapidly, and is facing land use, construction, and traffic challenges. This paper takes 20 stations along Tianjin Metro Line 1 as its research objects, and engages in field research and collection of essential materials and data to analyze the relationship between land use, development, and construction near the stations of Tianjin Metro Line 1 on the one hand and passenger flow volume on the other. On this basis, it offers suggestions for the further development of Tianjins rail network, including effective land utility mode and important facilities around the rail station that can increase passenger flow volume, improve land value and promote mutually benign development of both rail traffic and urban land.

Correlation between lead and iron in children's blood in Jordan

A total of 200 Jordanian children were classified into two groups: 100 Fe replete and 100 Fe deficient with ages ranging between 3.0 and 12.0 years (6.9 ± 2.7 years). All participants were chosen according to proper selection criteria followed by the sample collection: the samples were analyzed for hemoglobin and red blood cells; ferritin, an immunoassays-based instrument; and levels of Pb, Cu, and Zn. There were no significant differences between genders regarding Fe-deficiency (p = 0.57 and χ2 = 0.33), with a significant association of younger individuals (3.0–9.1 years) with Fe-deficiency (p < 0.05 and χ2 = 22.7).In addition, there is a significant positive correlation between Fe-deficiency with blood levels of Pb, Cu, and Zn (p < 0.05), (r = 0.43, 0.35, and 0.42, respectively) as compared to control group, this findings supported, by comparing the levels of the examined metals in both groups, in individuals whom close to heavy metals source (highway traffic or oil gas station), and found that the mean of the heavy metals level in close Fe-deficient group higher than in close Fe-replete group.