A Three-Year Analysis of Toxic Benzene Levels and Associated Impact in Ploieşti City, Romania

This study examines the levels of benzene and the potential health impact during three years of continuous monitoring (2019-2021), including the COVID-lockdown period from 2020 in a city that is an important Romanian center for petroleum refining and associated product manufacturing. The dataset contains benzene, toluene, NOx, PM10 concentrations, and meteorological factors monitored by six automatic stations from the national network of which four are in the city and two outside. Special attention was given to the benzene dynamics to establish patterns related to the health impact and leukemia. An assessment of the exposure was performed using EPA's ExpoFIRST v. 2.0 for computing the inhalation Average Daily Dose (ADD) and Lifetime Average Daily Dose (LADD). The health impact was estimated based on several indicators such as lifetime cancer risk (LCR), Hazard Quotient (HQ), Disability-Adjusted Life Years (DALY), and Environmental burden of disease (EBD). Overall, the annual average of all stations was almost similar between years i.e., 3.46 in 2019, 3.41 in 2020, and 3.63 µg/m3 in 2021, respectively. The average of all stations during the lockdown period was 2.67 µg/m3, which was lower than the multiannual average of the 2019-2021 period, i.e., 3.5 µg/m3. Significant correlations were present between benzene and other pollutants such as NOx (r = 0.57), PM10 fraction (r = 0.70), and toluene (r = 0.69), and benzene and temperature (r = -0.46), humidity (r = 0.28), and wind speed (r = -0.34). Regarding the ADD, in all scenarios, the most affected age categories are small children, despite a lower outdoor exposure time. From birth to <70 years, the ADD varied depending on the exposure scenario resulting in 3.27 × 10-4, 5.6 × 10-4, and 4.04 × 104 mg/kg-day, and 3.95 × 10-4, 10.6 × 10-4, and 6.76 × 10-4 mg/kg-day for the LADD, respectively. The Integrated Lifetime Cancer Risk (ILTCR) values were 14.1 × 10-5 in winter, 9.04 × 10-5 in spring, 8.74 × 10-5 in summer, and 10.6 × 10-4 in autumn. The ILTCR annual averages were 1.08 × 10-4 (2019), 1.07 × 10-4 (2020), 1.04 × 10-4 (2021), and 1.06 × 10-4 for the entire period. The resulting ILTCR values point out very risky conditions, with the annual averages reaching the definite cancer risk category. The corresponding burden based on the DALY's loss due to leukemia in Ploieşti was estimated at 0.291 (2 μg/m3 benzene), 0.509 (3.5 μg/m3 benzene), 0.582 (4 μg/m3 benzene), and 0.873 DALYs per 100,000 inhabitants (6 μg/m3 benzene), respectively. The current study provides useful insights for a better understanding of the exposure levels to benzene and associated health impact in Ploieşti despite the limitations determined by the data hiatus and incomplete or missing information regarding the health impact.

Liaison between exposure to sub-micrometric particulate matter and allergic response in children from a petrochemical industry city

The study examines the association between exposure to sub-micrometric Particulate Matter (PM₁) and allergic response in a group of sensitive young children (age: 2-10 years) from Ploiesti city, Romania. The city is the only urban agglomeration in Europe surrounded by four oil refineries. A panel study was conducted by collecting medical information from children with respiratory illnesses and atopy (n = 135). Hot Spot Analysis revealed the areas of the city that are susceptible to high levels of PM₁. We found a close interaction between exposure to PM₁ outdoor concentrations and various physiological changes and clinical symptoms in children including triggering of allergic reactions, rhinitis, alteration of lung function, upper and lower respiratory tract symptoms, and bronchial asthma. During the 2-year study period, the incidence of hospitalizations was 40.7%. Strong correlations (p < 0.001) were observed between the PM₁ exposure and hospitalizations, and exposure and Immunoglobulin E (IgE). PM₁ exposure was also correlated with eosinophils (p < 0.05). Another positive correlation was observed between hospitalizations and IgE levels (p < 0.05). The mean results of tested indicators were as follows: wheezing (5.3, 95% CI (1.4-1.8); Coeff. of var. (CV) = 30%), IgE (382, 95% CI (349-445); CV = 102%), and EO% (5.3, 95% CI (3.3-4.2); CV = 69.5%). We can conclude that exposure to PM₁ influenced the frequency of wheezing episodes, increased hospitalizations, and the levels of allergic blood indicators in children, especially in infants and pre-schoolers. CAPSULE: Exposure to sub-micrometric particles (PM₁) influences the frequency of wheezing episodes, hospitalizations, and the levels of allergic blood indicators in children, especially in infants and pre-schoolers.

A Complex Analysis Employing ARIMA Model and Statistical Methods on Air Pollutants Recorded in Ploiesti, Romania

Air pollution is an everyday issue, very relevant to public authorities, requiring control and monitoring to provide data for decision-making policies. The objective of this study was to evaluate the air quality in Ploiesti city, Romania and to observe the advantages and limitations of the some statistical methods used in forecasting air quality. Data for six air quality parameters collected at monitoring stations in Ploiesti during the 2013 year were statistically analyzed. Principal component analysis (PCA) was used to provide a relevant description in factors that can be explained in terms of different sources of air pollution. The measured pollutants data were statistically analyzed using the auto-regressive integrated moving average (ARIMA) method in order to assess the efficiency of using this method in forecasting the environmental air quality. The results revealed that ARIMA method has some limitations and do not produce satisfactory results for certain air pollutants such as PM10 and CO, even the forecasted period is short. By comparison, the ARIMA model obtained for NOx , NO2 , or O3 time series, provides good results, with relative errors around 5%.

Fine Particulate Matter in Urban Environments: A Trigger of Respiratory Symptoms in Sensitive Children

The overall objective of this research was to study children’s respiratory illness levels in Targoviste (Romania) in relationship to the outdoor concentrations of airborne particulate matter with an aerodynamic diameter below 2.5 µm (PM_2.5). We monitored and analysed the PM_2.5 concentrations according to a complex experimental protocol. The health trial was conducted over three months (October–December 2015) and required the active cooperation of the children’s parents to monitor carefully the respiratory symptoms of the child, i.e., coughing, rhinorrhoea, wheezing, and fever, as well as their outdoor program. We selected the most sensitive children (n = 25; age: 2–10 years) with perturbed respiratory health, i.e., wheezing, asthma, and associated symptoms. The estimated average PM_2.5 doses were 0.8–14.5 µg·day⁻¹ for weekdays, and 0.4–6.6 µg·day⁻¹ for the weekend. The frequency and duration of the symptoms decreased with increasing age. The 4- to 5-year old children recorded the longest duration of symptoms, except for rhinorrhoea, which suggested that this age interval is the most vulnerable to exogenous trigger agents (p < 0.01) compared to the other age groups. PM_2.5 air pollution was found to have a direct positive correlation with the number of wheezing episodes (r = 0.87; p < 0.01) in November 2015. Monitoring of wheezing occurrences in the absence of fever can provide a reliable assessment of the air pollution effect on the exacerbation of asthma and respiratory disorders in sensitive children.

Quantifying the impact of PM2.5 and associated heavy metals on respiratory health of children near metallurgical facilities

The aim of this study was to link the concentrations of particulate matter with an aerodynamic diameter below 2.5 μm (PM2.5) and associated heavy metals with occurrence of wheezing and hospitalizations due to wheezing in 111 children who live near metallurgical plants in Targoviste City, Romania. A group of 72 children with high levels of immunoglobulin E (IgE) and eosinophils, as well as frequent wheezing episodes, was geolocated on digital thematic maps. Monitoring campaigns and medical assessments were performed over two consecutive years (2013-2014). The multiannual average concentrations of PM2.5 ranged from 4.6 to 22.5 μg m(-3), up to a maximum value of 102 μg m(-3). Significant correlations (p < 0.01) were observed between the locations of the children with respiratory issues and the PM2.5 multiannual average (r = 0.985) and PM2.5 maximum (r = 0.813). Fe, Ni, Cd, and Cr were the main marker elements of the emissions from steel production and metal-working facilities in the Targoviste area. The results support the hypothesis that increased PM2.5 levels directly influence wheezing symptom and asthma attacks in the analyzed group. IgE, eosinophils, and wheezing episodes may be considered key indicators with which to evaluate the adverse effects of PM2.5 air pollution on children's health.

Using wavelet-feedforward neural networks to improve air pollution forecasting in urban environments

The paper presents the screening of various feedforward neural networks (FANN) and wavelet-feedforward neural networks (WFANN) applied to time series of ground-level ozone (O3), nitrogen dioxide (NO2), and particulate matter (PM10 and PM2.5 fractions) recorded at four monitoring stations located in various urban areas of Romania, to identify common configurations with optimal generalization performance. Two distinct model runs were performed as follows: data processing using hourly-recorded time series of airborne pollutants during cold months (O3, NO2, and PM10), when residential heating increases the local emissions, and data processing using 24-h daily averaged concentrations (PM2.5) recorded between 2009 and 2012. Dataset variability was assessed using statistical analysis. Time series were passed through various FANNs. Each time series was decomposed in four time-scale components using three-level wavelets, which have been passed also through FANN, and recomposed into a single time series. The agreement between observed and modelled output was evaluated based on the statistical significance (r coefficient and correlation between errors and data). Daubechies db3 wavelet-Rprop FANN (6-4-1) utilization gave positive results for O3 time series optimizing the exclusive use of the FANN for hourly-recorded time series. NO2 was difficult to model due to time series specificity, but wavelet integration improved FANN performances. Daubechies db3 wavelet did not improve the FANN outputs for PM10 time series. Both models (FANN/WFANN) overestimated PM2.5 forecasted values in the last quarter of time series. A potential improvement of the forecasted values could be the integration of a smoothing algorithm to adjust the PM2.5 model outputs.