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.

The present work aimed to assess the ambient levels of air pollution with particulate matter for both mass concentrations and number of particles for various fractions in Ploiesti city during the lockdown period determined by the COVID-19 pandemic (March–June 2020). The PM10 continuously monitored data was retrieved from four air quality automatic stations that are connected to the Romanian National Network for Monitoring Air Quality and located in the city. Because no other information was available for other more dangerous fractions, we used monitoring campaigns employing the Lighthouse 3016 IAQ particle counter near the locations of monitoring stations assessing size-segregated mass fraction concentrations (PM0.5, PM1, PM2.5, PM5, PM10, and TPM) and particle number concentration (differential Δ) range between 0.3 and 10 microns during the specified timeline between 8.00 and 11.00 a.m., which were considered the morning rush hours interval. Interpolation maps estimating the spatial distribution of the mass concentrations of various PM fractions and particle number concentration were drawn using the IDW algorithm in ArcGIS 10.8.2. Regarding the particle count of 0.5 microns during the lockdown, the smallest number was recorded when the restriction of citizens’ movement was declared (24 March 2020), which was 5.8-times lower (17,301.3 particles/cm³) compared to a common day outside the lockdown period (100,047.3 particles/cm³). Similar results were observed for other particle sizes. Regarding the spatial distribution of the mass concentrations, the smaller fractions were higher in the middle of the city and west (PM0.5, PM1, and PM2.5) while the PM10 was more concentrated in the west. These are strongly related to traffic patterns. The analysis is useful to establish the impact of PM and the assessment of urban exposure and better air quality planning. Long-term exposure to PM in conjunction with other dangerous air pollutants in urban aerosols of Ploiesti can lead to potential adverse effects on the population, especially for residents located in the most impacted areas.

Biochar activation is achieved by removing tar formed in the pores during the thermal treatment of biomass, thereby increasing pore volume. This process typically involves entraining tar with steam at elevated temperatures for extended durations. In this study, a reduction in lignin content in grape seeds through partial solubilization, prior to thermal treatment, is proposed. Initially, grape seeds were treated with a basic sodium sulfide solution, followed by conditioning with either phosphoric acid or zinc chloride and then drying and calcination. The synthesized adsorbents were characterized using scanning electron microscopy (SEM), textural analysis, Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and evaluation of toluene adsorption capacity. Textural analysis indicated that conditioning with phosphoric acid or zinc chloride increased the specific surface area of biochar by over 20%, with a higher increase observed for phosphoric acid treatment. The toluene adsorption capacity of the adsorbents was assessed in a continuous fixed-bed system. Biochar pretreated with ZnCl₂ exhibited an adsorption capacity of 0.11 cm³ of toluene per gram, while biochar pretreated with phosphoric acid demonstrated a capacity of 0.14 cm³ per gram. These results indicate that preliminary delignification of grape seed biomass maintains its adsorption capacity of toluene at levels comparable to other adsorbents, despite a lower activation temperature.

In this study, a novel magnetic nanocatalyst based on tin ferrite (SnFe₂O₄) was synthesized via a chemical co-precipitation method and thoroughly characterized using XRD, SEM, TGA-DTG, BET, FTIR, and FTIR-pyridine techniques. The catalyst exhibited high crystallinity, a mesoporous structure with a specific surface area of 79.7 m²/g, and well-defined Lewis and Brønsted acid sites. Its catalytic performance was assessed in the esterification of glycerol with acetic acid to produce monoacetin (MAG), diacetin (DAG), and triacetin (TAG). A Box–Behnken experimental design was employed to evaluate the influence of temperature, catalyst loading, and the acetic-acid-to-glycerol molar ratio on product distribution and glycerol conversion. Statistical analysis and regression modeling revealed excellent predictive accuracy (R² > 0.99), confirming the robustness of the model. Optimal reaction conditions (110 °C, 2 wt.% catalyst, and AA/GLY ratio of 3.6) yielded a maximum glycerol conversion of 93.2% and a combined DAG and TAG yield of ~59.1%. These results demonstrate the high efficiency and selectivity of the synthesized SnFe₂O₄ catalyst, making it a promising candidate for sustainable glycerol valorization.

This study investigates the synthesis of biodiesel from three vegetable oils with significantly different chemical compositions. Based on the properties of these biodiesel samples, a method was proposed to estimate the density of petrodiesel–biodiesel blends using an artificial neural network (ANN). The ANN employed in this research consisted of 10 neurons. The experimental data showed a high correlation, indicating effective training and precise estimations in relation to the provided training data. The accuracy of the estimations was evaluated by comparing the blending densities determined through the method presented in this study with the mean of three estimations generated by the neural network. The deviation between the determined and estimated values ranged from 4.1 to 25.2 kg/m³, which is attributable to the limited size of the training database. Most errors fell between −7.1% and 3.8%, with the lowest error being observed for petrodiesel–Brassica carinata biodiesel blends. Excellent correlations for both training and validation data were obtained (R = 0.99 and R = 0.98) for blends incorporating palm and Brassica carinata biodiesel. The estimation method using neural networks proposed in this paper can be effectively adapted for other mixtures and to estimate additional blending properties, accommodating each user’s needs.

1-butanethiol, a volatile mercaptan that is harmful and has a persistent odor, was adsorbed from a gaseous stream onto granulated activated carbon (AC) that was doped with Cu, Fe, and Zn oxides. The adsorbents were prepared by precipitating salts of the respective metals using an ammonia solution, along with the inclusion of an anti-caking agent known as Pluronic-123. Characterization of the three prepared adsorbents was conducted using electron microscopy (SEM), textural analysis, thermogravimetric analysis, FTIR, and XRD. The study’s results indicate that the adsorbents exhibit different textural characteristics and variations in the size and shape of the metal oxide clusters deposited on the activated carbon. These differences also led to variations in the adsorption capacity for 1-butanethiol among the three adsorbents.