Determination of the streses operating on a forest ecosystem demands the use of several bioindication methods. Air quality indicators were assessed from an inventory of forest decline based on the assessment of tree crowns and lichens. Photosynthetic pigments, ascorbic acid and major macro nutrients were studied in mountain pine (Pinus mugo Yurra) needles as indicators of physiological and biochemical stress. Analyses were carried out at selected forest plots and transects in predominantly unpolluted areas within Triglav National Park, Julian Alps, Slovenia. It was assumed that air pollutant input in forest ecosystems is of two kind, e.g. local from the air pollutin sources in the valleys on the North-West part of tha national park and transboundary source at high altitudes

Genotoxic compounds, as common contaminants of the air environment, are of interest in air pollution monitoring. There are several methods to determine the level of these contaminants in different localities, many of which may be difficult to access with the use of conventional active and passive samplers. In the present study, the needles Pinus mugo Turra and Picea abies were used to monitor sampling localities in Austria, Slovakia, and the Czech Republic. Needles were extracted and chemical analysis and the genotoxicity bioassay SOS chromotest were used to obtain complex information about the chemical mixture of pollutants present and their genotoxic effects. The SOS chromotest method was optimized by using a CPRG chromogenic substrate to reduce the false positive genotoxic effect of needle extracts. Pinus mugo Turra and Picea abies were identified as suitable passive sampling matrices for long-term air monitoring using the same plants sampled at the same time. The presented study brings an innovative method for the fast screening and identification of localities loaded by genotoxic active air contaminants.

Atmospheric deposition particles are fine-sized having a high adsorption capacity. Therefore, they can easily transfer the contamination to other areas. Plants can absorb certain pollutants using their leaves and then accumulate them in their biomass. In this study, the spatial and temporal variability of air pollution was assessed using pine needles as the bioindicators of atmospheric pollution. The magnetic susceptibility (MS) at low and high frequencies (χₗf, χₕf) and the concentration of selected heavy metals of pine needles (Pinus mugo) were estimated in order to address the possible relationships between needles’ MS and the heavy metal concentration in the city of Isfahan, central Iran. In addition, the relationship between the heavy metal concentration of pine needles and that of the atmospheric dust was examined using the published data. Tree pine needles were monthly sampled, from April to December 2015 (T1–T9), during 9 months, from 30 different sites in the Isfahan city. There were two treatments including washed + unwashed (WU) and washed + washed (WW). The heavy metal total concentrations including Zn, Fe, Cu, Co, Pb, and Ni were measured. The mean concentrations of Fe, Zn, Pb, Cu, Ni, and Co were 80.4, 3.9, 1.8, 1.4, 0.6, and 0.3 mg kg⁻¹, respectively. The results revealed that the concentration of heavy metals and MS in the pine needles followed the order Fe > Zn > Pb > Cu > Ni > Co. Also, the heavy metal concentration in the pine needles with different treatments had the following trend: WU > WW. It was shown that there was a significant correlation (p < 0.01) between the heavy metal concentrations and the leaf MS values of the pine needles and the concentration of heavy metals in atmospheric dust. Besides, similar trends were detected for the spatial variability of heavy metals and the pine needles’ MS. In general, it could be concluded that the biomagnetic approach could serve as a comparatively fast and low-cost method to detect highly polluted urban areas with selected heavy metals, particularly the areas which are under the influence of anthropogenic and other traffic-related sources.