Extension of the EUROS Integrated Air Quality Model to Fine Particulate Matter by Coupling to CACM/MADRID 2

The European Operational Smog (EUROS) integrated air quality modelling system has been extended to model fine particulate matter (PM). From an extended literature study, the Caltech Atmospheric Chemistry Mechanism and the Model of Aerosol Dynamics, Reaction, Ionisation and Dissolution were selected and recently coupled to EUROS. Currently, modelling of mass and chemical composition of aerosols in two size fractions (PM_2.5 and PM_10–2.5) is possible. The chemical composition is expressed in terms of seven components: ammonium, nitrate, sulphate, elementary carbon, primary inorganic compounds, primary organic compounds and secondary organic compounds. Calculated PM₁₀ concentrations and chemical composition are presented for two summer months of the year 2003 (1 July to 31 August).     

Metals, non-metals and PCB in electrical and electronic waste--actual levels in Switzerland

The chemical composition of waste of small electrical and electronic equipment (s-WEEE), a rapidly growing waste stream, was determined for selected metals (Cu, Sb, Hg etc.) and non-metals (Cl, Br, P) and PCBs. During a 3-day experiment, all output products and the s-WEEE input mass flows in a WEEE recycling plant were measured. Only output products were sampled and analyzed. Material balances were established, applying substance flow analysis (SFA). Transfer coefficients for the selected substances were also determined. The results demonstrate the capability of SFA to determine the composition of the highly heterogeneous WEEE for most substances with rather low uncertainty (2 sigma +/- 30%). The results confirm the growing importance of s-WEEE regarding secondary resource metals and potential toxic substances. Nowadays, the thirty times smaller s-WEEE turns over larger flows for many substances, compared to municipal solid waste. Transfer coefficient results serve to evaluate the separation efficiency of the recycling process and confirm--with the exception of PCB and Hg--the limitation of hand-sorting and mechanical processing to separate pollutants (Cd, Pb, etc.) out of reusable fractions. Regularly applied SFA would serve to assess the efficacy of legislative, organizational and technical measures on the WEEE.     

Source identification and apportionment of PM2.5 and PM2.5−10 in iron and steel scrap smelting factory environment using PMF,PCFA and UNMIX receptor models

To identify the potential sources responsible for the particulate matter emission from secondary iron and steel smelting factory environment, PM_2.5 and PM_2.5?10 particles were collected using the low-volume air samplers twice a week for a year. The samples were analyzed for the elemental and black carbon content using x-ray fluorescence spectrometer and optical transmissometer, respectively. The average mass concentrations were 216.26, 151.68, and 138. 62 μg/m³ for PM_2.5 and 331.36, 190.01, and 184.60 μg/m³ for PM_2.5?10 for the production, outside M1 and outside M2 sites, respectively. The same size resolved data set were used as input for the positive matrix factorization (PMF), principal component factor analysis (PCFA), and Unmix (UNMIX) receptor modeling in order to identify the possible sources of particulate matter and their contribution. The PMF resolved four sources with their respective contributions were metal processing (33 %), e-waste (33 %), diesel emission (22 %) and soil (12 %) for PM_2.5, and coking (50 %), soil (29 %), metal processing (16 %) and diesel combustion (5 %) for PM_2.5?10. PCFA identified soil, metal processing, Pb source, and diesel combustion contributing 45, 41, 9, and 5 %, respectively to PM_2.5 while metal processing, soil, coal combustion and open burning contributed 43, 38, 12, and 7 %, respectively to the PM_2.5?10. Also, UNMIX identified metal processing, soil, and diesel emission with 43, 42 and 15 % contributions, respectively for the fine fraction, and metal processing (71 %), soil (21 %) and unidentified source (1 %) for the coarse fraction. The study concluded that metal processing and e-waste are the major sources contributing to the fine fraction while coking and soil contributed to the coarse fraction within the factory environment. The application of PMF, PCFA and UNMIX receptor models improved the source identification and apportionment of particulate matter drive in the study area.     

Effect of some heavy metals and soil humic substances on the phytochelatin production in wild plants from silver mine areas of Guanajuato, Mexico

Phytochelatins (PCs) were determined in the wild plants, focusing on their relationship with the levels of heavy metals and humic substances (HS) in soil. Ricinus communis and Tithonia diversifolia were collected from several sites in Guanajuato city (Mexico), which had long been the silver and gold mining center. The analysis of PCs in root extracts was carried out by liquid chromatography (derivatization with monobromobimane). Total Ag, Cd, Cu and Pb in plant roots and in soil samples, as well as soil HS were determined. The association of metals with HS in soils was evaluated by size exclusion chromatography (SEC) with UV and ICP-MS detection. The results obtained revealed the induction of PCs in R. communis but not in T. diversifolia. The levels of Cd and Pb in plant roots presented strong positive correlation with PC-2 (r = 0.9395, p = 0.005; r = 0.9573, p = 0.003, respectively), indicating that these two metals promote PCs induction in R. communis. On the other hand, the inverse correlation was found between soil HS and metal levels in roots of R. communis (Cu > Pb > Cd > Ag), in agreement with the decreasing affinity of these metals to HS. Importantly, the inverse correlation between soil HS and plant PC-2 was observed (r = −0.7825, p = 0.066). These results suggest that metals strongly bound to HS could be less bioavailable to plants, which in turn would limit their role in the induction of PCs. Indeed, the SEC elution profiles showed Pb but not Cd association with HS and the correlation between metal in soil and PC-2 in plant was statistically significant only for Cd (r = 0.7857, p = 0.064). Based on these results it is proposed that the role of heavy metals in PCs induction would depend on their uptake by R. communis, which apparently is controlled by the association of metals with soil HS. This work provides further evidence on the role of environmental conditions in the accumulation of heavy metals and phytochelatin production in plants.     

The effect of low molecular weight chelators on iron chelation and free radical generation as studied by ESR measurement

The purpose of this work was to improve our current knowledge of the non-enzymatic mechanisms involved in brown rot fungal decay of wood, but also to improve our understanding of chelator-mediated reactions that may occur in other biological systems where low pH conditions may prevail. Several key steps (iron chelation and reduction) during early non-enzymatic wood decay processes have been studied by using electron spin resonance (ESR). It has been proposed that low molecular weight chelators as well as Fenton reagents are involved in brown rot decay, at least in early non-enzymatic stages. In this work, the binding between a catecholate model chelator and ferric iron was studied by ESR spectroscopy. The effects of the model chelator, Fenton reagents, as well as the reaction conditions on free radical generation were also studied using ESR spin-trapping techniques. The results indicate: (1) The relative quantity of the chelator-iron complex can be determined by measurement of the intensities of the characteristic g = 4.3 ESR signal. (2) The effects of the chelator:iron ratio, the pH, and other reaction parameters on the hydroxyl radical generation in a Fenton type system can be determined using ESR spin-trapping techniques. (3) Data support the hypothesis that superoxide radicals are involved in chelator-mediated Fenton processes.     

The evolution of cheating and selfish behavior

Summary We examine the necessary conditions for the spread of genes that determine selfish and cheating behaviors and the rate of spread of these genes through structured populations, in order to address the question of the invadability of altruistic systems by anti-social mutations. We find that, although cheaters always have a higher relative fitness than altruists within groups, population structures which permit the evolution of altruism also preclude invasion by anti-social mutations. These results are related to a discussion by Hamilton (1971) concerning the limits to the evolution of altruistic and selfish behaviors.