Wood plays an important role in stream ecology and geomorphology. Previous studies of wood in rivers have quantifi ed spatial distributions but temporal dynamics remain poorly documented. The lack of such data is related to limitations of existing methods, especially when applied to large rivers. Five techniques are fi eld-tested to assess their utility for quantifying the temporal dynamics in rivers: repeated high-resolution aerial surveys, the measurement of wood physical characteristics as proxies for 14 C dating, passive and active radio frequency identifi cation (RFID) tags, radio transmitters, and video. The spatial distribution of wood is surveyed using aerial imagery with a resolution fi ner than 0·10 m. The estimation of temporal trends by repeated aerial-based surveys needs to consider vegetation growth and hiding. Wood residence times can be calculated using 14 C analysis, but the assessment of wood physical characteristics including decay status and wood density offers a cheaper, if less accurate, alternative. Wood resistance to penetration is tested but results are not signifi cant. Radio transmitters are reliable for multi-year (~5 year) surveys and can be detected at 800 m. Passive RFID tags are limited by a read range of 0·30 m but are reliable for longer term (>5 year) studies. Active RFID tags combine a moderate read range (10-300 m) and low cost with in-fl ood detection but require more testing. Video monitoring of wood passing on the surface of a river is successfully implemented. For a single fl ood on the Ain River (France), wood transport rates are an order of magnitude higher on the rising limb of the hydrograph than on the falling limb. Overall, the techniques improve the ability to gather the data needed to understand wood transfer processes and calibrate budgets of wood in rivers.
Purpose This study presents a procedure to differentiate the local and remote sources of particulate-bound polycyclic aromatic hydrocarbons (PAHs). Methods Data were collected during an extended PM 2.5 sampling campaign (2009)(2010) carried out for 1 year in Venice-Mestre, Italy, at three stations with different emissive scenarios: urban, industrial, and semirural background. Diagnostic ratios and factor analysis were initially applied to point out the most probable sources. In a second step, the areal distribution of the identified sources was studied by applying the discriminant analysis on factor scores. Third, samples collected in days with similar atmospheric circulation patterns were grouped using a cluster analysis on wind data. Local contributions to PM 2.5 and PAHs were then assessed by interpreting cluster results with chemical data.Results Results evidenced that significantly lower levels of PM 2.5 and PAHs were found when faster winds changed air masses, whereas in presence of scarce ventilation, locally emitted pollutants were trapped and concentrations increased. This way, an estimation of pollutant loads due to local sources can be derived from data collected in days with similar wind patterns. Long-range contributions were detected by a cluster analysis on the air mass back-trajectories. Results revealed that PM 2.5 concentrations were relatively high when air masses had passed over the Po Valley. However, external sources do not significantly contribute to the PAHs load. Conclusions The proposed procedure can be applied to other environments with minor modifications, and the obtained information can be useful to design local and national air pollution control strategies.
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