Chile's resource sectors

Chilean economic reforms, introduced in the 1970s and early 1980s, discarded decades of state intervention in the economy, but were accompanied by considerable economic pain and social stress from domestic and international sources. In the 1990s, Chile, supported by a competitive micro-economy, a stable macro-economy, strong linkages with the world economy and the return to democratic government, is exploiting its world-class resource sectors to propel economic growth in order to address social problems. However, the prospects for raising living standards in Chile and other resource-exporting developing countries are critically dependent on a favourable external environment.     

Rapidly locating and characterizing pollutant releases in buildings

Releases of airborne contaminants in or near a building can lead to significant human exposures unless prompt response measures are taken. However, possible responses can include conflicting strategies, such as shutting the ventilation system off versus running it in a purge mode or having occupants evacuate versus sheltering in place. The proper choice depends in part on knowing the source locations, the amounts released, and the likely future dispersion routes of the pollutants. We present an approach that estimates this information in real time. It applies Bayesian statistics to interpret measurements of airborne pollutant concentrations from multiple sensors placed in the building and computes best estimates and uncertainties of the release conditions. The algorithm is fast, capable of continuously updating the estimates as measurements stream in from sensors. We demonstrate the approach using a hypothetical pollutant release in a five-room building. Unknowns to the interpretation algorithm include location, duration, and strength of the source, and some building and weather conditions. Two sensor sampling plans and three levels of data quality are examined. Data interpretation in all examples is rapid; however, locating and characterizing the source with high probability depends on the amount and quality of data and the sampling plan.     

Monitoring and modeling of disinfection by-products (DBPs)

In the United States, the newly promulgateddisinfectant/disinfection by-product (D/DBP) regulationsforce water treatment utilities to be more concerned withfinished and distributed water qualities. In this study,monitoring of DBP formation was conducted from three Frenchwater treatment plants trying to assess DBP variationsthrough time and space. Compared to the in-plant totaltrihalomethanes (TTHM) levels, TTHM levels in thedistribution system increased from less than 150% to morethan 300%. Significant variations for TTHM and bromate(BrO₃ ^-) levels throughout the seasons were alsoobserved; generally higher levels in the summer and lowerlevels in the winter. Combining chemical DBP models(empirical power functional models) and hydraulicsimulations, DBPs including TTHM and BrO₃ ^- weresuccessfully simulated from the full-scale monitoring data,indicating that empirical DBP model can be a potential toolto access DBP formation in actual plants. This study alsoprovides the protocols to assess DBP simulations in thewater treatment systems.     

Peroxyacetyl nitrate (PAN) in the urban atmosphere

Peroxyacetyl nitrate (PAN) in air has been well known as the indicator of photochemical smog due to its frequent occurrences in Seoul metropolitan area. This study was implemented to assess the distribution characteristics of atmospheric PAN in association with relevant parameters measured concurrently. During a full year period in 2011, PAN was continuously measured at hourly intervals at two monitoring sites, Gwang Jin (GJ) and Gang Seo (GS) in the megacity of Seoul, South Korea. The annual mean concentrations of PAN during the study period were 0.64 ± 0.49 and 0.57 ± 0.46 ppb, respectively. The seasonal trends of PAN generally exhibited dual peaks in both early spring and fall, regardless of sites. Their diurnal trends were fairly comparable to each other. There was a slight time lag (e.g., 1 h) in the peak occurrence pattern between O₃ and PAN, as the latter trended to peak after the maximum UV irradiance period (16:00 (GJ) and 17:00 (GS)). The concentrations of PAN generally exhibited strong correlations with particulates. The results of this study suggest that PAN concentrations were affected sensitively by atmospheric stability, the wet deposition of NO₂, wind direction, and other factors.     

Kinetics of the oxidation of sucralose and related carbohydrates by ferrate(VI)

The kinetics of the oxidation of sucralose, an emerging contaminant, and related monosaccharides and disaccharides by ferrate(VI) (Fe(VI)) were studied as a function of pH (6.5-10.1) at 25°C. Reducing sugars (glucose, fructose, and maltose) reacted faster with Fe(VI) than did the non-reducing sugar sucrose or its chlorinated derivative, sucralose. Second-order rate constants of the reactions of Fe(VI) with sucralose and disaccharides decreased with an increase in pH. The pH dependence was modeled by considering the reactivity of species of Fe(VI), (HFeO(4)(-) and FeO(4)(2-)) with the studied substrates. Second-order rate constants for the reaction of Fe(VI) with monosaccharides displayed an unusual variation with pH and were explained by considering the involvement of hydroxide in catalyzing the ring opening of the cyclic form of the carbohydrate at increased pH. The rate constants for the reactions of carbohydrates with Fe(VI) were compared with those for other oxidant species used in water treatment and were briefly discussed.     

Source identification of particulate matter collected at underground subway stations in Seoul,Korea using quantitative single-particle analysis

Subway particle samples collected at four underground subway stations in Seoul, Korea were characterized by a single-particle analytical technique, low-Z particle electron probe X-ray microanalysis. To clearly identify indoor sources of subway particles, four sets of samples collected in tunnels, at platforms, near ticket offices, and outdoors were investigated. For the samples collected in tunnels, Fe-containing particles predominate, with relative abundances of 75–91% for the four stations. The amounts of Fe-containing particles decrease as the distance of sampling locations from the tunnel increases. In addition, samples collected at the platform in subway stations with platform screen doors (PSDs) that limit air-mixing between the platform and the tunnel showed marked decreases in relative abundances of Fe-containing particles, clearly indicating that Fe-containing subway particles are generated in the tunnel. PM₁₀ mass concentration levels are the highest in the tunnels, becoming lower as the distance of sampling locations from the tunnel increases. The extent of the decrease in PM₁₀ in stations with PSDs is also larger than that in stations without PSDs. The results clearly indicate that Fe-containing particles originating in tunnels predominate in the indoor microenvironment of subway stations, resulting in high indoor PM₁₀ levels, and that PSDs play a significant role in reducing Fe-containing particles at platforms and near ticket offices.     

Characteristics of aerosol types from AERONET sunphotometer measurements

By using observations from the Aerosol Robotic Network (AERONET), aerosol types are classified according to dominant size mode and radiation absorptivity as determined by fine-mode fraction (FMF) and single-scattering albedo (SSA), respectively. The aerosol type from anthropogenic sources is significantly different with regard to location and season, while dust aerosol is observed persistently over North Africa and the Arabian Peninsula. For four reference locations where different aerosol types are observed, time series and optical properties for each aerosol type are investigated. The results show that aerosol types are strongly affected by their sources and partly affected by relative humidity. The analysis and methodology of this study can be used to compare aerosol classification results from satellite and chemical transport models, as well as to analyze aerosol characteristics on a global scale over land for which satellite observations need to be improved.     

Long-term projections of non-fuel minerals: We were wrong,but why?

This article revisits global projections made in 1981 of eight metallic and fertilizer minerals for the year 2000. The principal objectives of the present study are to quantify the differences between the projected and observed levels of consumption for the year 2000 for eight of the 26 non-fuel minerals covered in the earlier study, and, then, to attempt to attribute these (often) large differences to the major determinants of minerals demand: income, technological, regulatory and other public policy changes, and changes in the recycling rates of the metallic minerals. The eight minerals are: aluminum, copper, iron, mercury, nickel, phosphate rock, potash and tin.This follow-up study begins with a discussion of the need for long-term projections of minerals. This section also includes a summary of the major determinants of the long-term demand for, and supply of, minerals, and a review of some of the earlier assessments of mineral needs and availability.Section 3 of the article begins with a short summary of the World Input–Output Model, the main methodological tool used in the earlier study that was developed by Prof. Wassily Leontief, the 1973 Nobel laureate in economics, and the way in which non-fuel minerals were represented in that system. This section also provides a summary of other global modeling efforts of non-fuel minerals that were carried out at a similar point in time for a similar interval.Section 4 presents the actual population, GDP and per capita GDP changes over the 1970–2000 time interval compared with the projected rates for these important determinants of mineral use, along with the projected and observed growth rates of minerals consumption for the eight non-fuel minerals included in this study. When the projections are compared to the observed global consumption rates for the year 2000, the differences range from +43% for nickel to +229% for potash.Section 5 discusses the apparent reasons for the differences between the projected and observed global consumption rates of these non-fuel minerals that include differences in the growth of GDP and GDP per capita, changes in recycling rates (for the metallic minerals), technological change, and regulatory or other public policy changes that have affected mineral use over the 30-year-interval ending in 2000.In light of the data and analysis presented in Sections sec# and sec#, the article concludes with some remarks, made almost a quarter of a century ago, by Prof. Leontief on the need and justification for long-term projections.