Measurement and modeling of particulate matter concentrations: Applying spatial analysis and regression techniques to assess air quality.

This paper presented the levels of PM2.5 and PM10 in different stations at the city of Sabzevar, Iran. Furthermore, this study was an attempt to evaluate spatial interpolation methods for determining the PM2.5 and PM10 concentrations in the city of Sabzevar. Particulate matters were measured by Haz-Dust EPAM at 48 stations. Then, four interpolating models, including Radial Basis Functions (RBF), Inverse Distance Weighting (IDW), Ordinary Kriging (OK), and Universal Kriging (UK) were used to investigate the status of air pollution in the city. Root Mean Square Error (RMSE), Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE) were employed to compare the four models. The results showed that the PM2.5 concentrations in the stations were between 10 and 500 µg/m3. Furthermore, the PM10 concentrations for all of 48 stations ranged from 20 to 1500 µg/m3. The concentrations obtained for the period of nine months were greater than the standard limits. There was difference in the values of MAPE, RMSE, MBE, and MAE. The results indicated that the MAPE in IDW method was lower than other methods: (41.05 for PM2.5 and 25.89 for PM10). The best interpolation method for the particulate matter (PM2.5 and PM10) seemed to be IDW method. •The PM10 and PM2.5 concentration measurements were performed in the period of warm and risky in terms of particulate matter at 2016.•Concentrations of PM2.5 and PM10 were measured by a monitoring device, environmental dust model Haz-Dust EPAM 5000.•Interpolation is used to convert data from observation points to continuous fields to compare spatial patterns sampled by these measurements with spatial patterns of other spatial entities.

Antibacterial activity of amino- and amido- terminated poly (amidoamine)-G6 dendrimer on isolated bacteria from clinical specimens and standard strains.

Background: Nanoscale poly (amidoamine) dendrimers have been investigated for their biological demands, but their antibacterial activity has not been widely discovered. Thus, the sixth generation of poly (amidoamine) dendrimer (PAMAM-G6) was synthesized and its antibacterial activities were evaluated on Gram-negative bacteria; P. aeruginosa, E. coli, A. baumannii, S. typhimurium, S. dysenteriae, K. pneumoniae, P. mirabilis, and Gram-positive bacteria, and S.aureus and B. subtilis, which were isolated from different clinical specimens and standard strains of these bacteria. Methods: In this study, 980 specimens including urine (47%), blood (27%), sputum (13%), wounds (8%), and burns (5%) were collected from clinical specimens of 16 hospitals and clinics in city of Sabzevar, Iran. Then, the target bacteria were isolated and identified using standard methods. Minimum inhibitory concentration and minimum bactericidal concentrations against Gram-positive and Gram-negative bacteria were determined according to guidelines described by clinical and laboratory standards institute (CLSI). Standard discs were prepared using 0.025, 0.25, 2.5, and 25 µg/mL concentrations of PAMAM-G6 on Mueller-Hinton agar plates to determinate the zone of inhibition. The cytotoxicity of PAMAM-G6 dendrimer was evaluated in HCT116 cells by MTT assay. Results: The most important isolated bacteria were E. coli (23.65%), S. aureus (24.7%), P. aeruginosa (10.49%), B. subtilis (7.7%), S. typhimurium (8.87%), A. baumannii (7.02%), K. pneumoniae (7.1%), P. mirabilis (6.46%), and S. dysenteriae (3.6%). Moreover, it was found that poly (amidoamine)-G6 exhibited more antibacterial efficacy on standard strains than isolated bacteria from clinical samples (p<0.05). The cytotoxicity of PAMAM-G6 to the cells showed that cytotoxicity depended on the concentration level and exposure time. Conclusion: The PAMAM-G6 dendrimer showed a positive impact on the removal of dominant bacterial isolated from clinical specimens and standard strains.

Mortality and morbidity due to exposure to outdoor air pollution in Mashhad metropolis, Iran. The AirQ model approach.

In the past two decades, epidemiological studies have shown that air pollution is one of the causes of morbidity and mortality. In this study the effect of PM10, PM2.5, NO2, SO2 and O3 pollutants on human health among the inhabitants of Mashhad has been evaluated. To evaluate the health effects due to air pollution, the AirQ model software 3.3.2, developed by WHO European Centre for Environment and Health, was used. The daily data related to the pollutants listed above has been used for the short term health effects (total mortality, cardiovascular and respiratory mortality, hospitalization due to cardiovascular and respiratory diseases, chronic obstructive pulmonary disease and acute myocardial infarction). PM2.5 had the most health effects on Mashhad inhabitants. With increasing in each 10µg/m3, relative risk rate of pollutant concentration for total mortality due to PM10, PM2.5, SO2, NO2 and O3 was increased of 0.6%, 1.5%, 0.4%, 0.3% and 0.46% respectively and, the attributable proportion of total mortality attributed to these pollutants was respectively equal to 4.24%, 4.57%, 0.99%, 2.21%, 2.08%, and 1.61% (CI 95%) of the total mortality (correct for the non-accident) occurred in the year of study. The results of this study have a good compatibly with other studies conducted on the effects of air pollution on humans. The AirQ software model can be used in decision-makings as a useful and easy tool.

Ecological risk assessment of heavy metal (HM) pollution in the ambient air using a new bio-indicator.

The aim of this descriptive-analytical study was to measure the concentration of heavy metals (HMs) in the leaf and bark of Ulmus carpinifolia as new biological indicators, and the ecological risk assessment of these metals in the ambient air. To achieve these goals, 48 sampling locations were selected in the city and concentration of four HMs-zinc (Zn), copper (Cu), lead (Pb), and cadmium (Cd)-was measured in the mentioned indicator using atomic absorption spectroscopy method. After this, ecological risk assessment, source appointment, and spatial distribution were conducted. In this regard, the enrichment factor (EF), potential ecological risk factor (E r), potential ecological risk index (RI), correlation coefficient (r), and other indices were calculated. The results showed that the concentration of HMs in the leaf and bark in ascending order is as Cd