Combined scanning electron microscopy and image analysis to investigate airborne submicron particles: a comparison between personal samplers

Field evaluation of personal sampling methods for multiple bioaerosols

Ambient bioaerosols are ubiquitous in the daily environment and can affect health in various ways. However, few studies have been conducted to comprehensively evaluate personal bioaerosol exposure in occupational and indoor environments because of the complex composition of bioaerosols and the lack of standardized sampling/analysis methods. We conducted a study to determine the most efficient collection/analysis method for the personal exposure assessment of multiple bioaerosols. The sampling efficiencies of three filters and four samplers were compared. According to our results, polycarbonate (PC) filters had the highest relative efficiency, particularly for bacteria. Side-by-side sampling was conducted to evaluate the three filter samplers (with PC filters) and the NIOSH Personal Bioaerosol Cyclone Sampler. According to the results, the Button Aerosol Sampler and the IOM Inhalable Dust Sampler had the highest relative efficiencies for fungi and bacteria, followed by the NIOSH sampler. Personal sampling was performed in a pig farm to assess occupational bioaerosol exposure and to evaluate the sampling/analysis methods. The Button and IOM samplers yielded a similar performance for personal bioaerosol sampling at the pig farm. However, the Button sampler is more likely to be clogged at high airborne dust concentrations because of its higher flow rate (4 L/min). Therefore, the IOM sampler is a more appropriate choice for performing personal sampling in environments with high dust levels. In summary, the Button and IOM samplers with PC filters are efficient sampling/analysis methods for the personal exposure assessment of multiple bioaerosols.

Capillary electrophoresis characterization of molecularly imprinted polymer particles in fast binding with 17β-estradiol

Molecularly imprinted polymer (MIP) submicron particles were synthesized, using either ethylene glycol dimethacrylate or trimethylolpropane trimethacrylate as a cross-linker, specifically for recognition of 17β-estradiol (E2). HPLC with fluorescence detection (HPLC-FD) results showed that 90(±5)% of E2 bound onto these particles after 2 min of incubation, and 96(±3)% after long equilibrium. The binding capacity was 8(±3) μmol/g for MIP particles prepared using ethylene glycol dimethacrylate, and 33-43(±8) μmol/g for using trimethylolpropane trimethacrylate. CE separation of MIP and non-imprinted polymer particles was successful when 50 mM borate buffer (pH 8.5) containing 0.005% w/v EOTrol™ LN in reverse polarity (-30 kV) was used. The electrophoretic mobilities of MIP and non-imprinted polymer particles, together with dynamic light scattering measurement of particle sizes, allowed for an estimation of their surface charges. Automated injection of E2 and particles in mixture set a lower limit of 20(±1) s on incubation time for the study of fast binding kinetics. The presence of E2 and bisphenol A (BPA) together tested the selectivity of MIP particles, when the two compounds competed for available binding cavities or sites. Addition of E2 after BPA confirmed E2 occupation of the specific binding cavities, via displacement of BPA.

Determination of illicit drugs in seized materials: role of sampling and analysis in estimation of measurement uncertainty

The determination of illicit active ingredients in seized materials, in order to assess penal or administrative offences, is routinely carried out in many forensic toxicology laboratories. This paper presents main features of the protocol adopted in the Authors' laboratory for the above investigations. In particular, sampling and analysis are considered as the same measurement process quantifying their combined contribution to overall measurement uncertainty. Aspects concerning representative sampling in the case of single and multiple items are discussed. The effects of material heterogeneity are considered by analyzing separately distinct primary samples taken from different parts of the sampling target. Possible errors due to particles dimension that could arise when sub-sampling are also considered. Analytical precision, bias and other matrix effects are studied in order to quantify the component of the overall measurement uncertainty associated to the analysis of prepared test samples. Typical scenarios arising when measurement results are used to assess compliance with specification limits are also discussed revealing the crucial role of measurement uncertainty.