Green accounting and sustainability of the Peruvian metal mining sector

This paper estimates the true economic income of Peru’s metal mining sector for the period 1992–2006, using a model of green economic income based on Hamilton (2000). The total depletion of natural capital caused by metal mining is calculated by estimating, on the one hand, the depreciation of mining resources (using the Hotelling rent approach) and, on the other, the environmental degradation provoked by metal mining activities. The results show that the total loss of natural capital represents between 31% and 51% of the metal mining GDP and between 2% and 4.9% of Peru’s GDP. On the other hand, correcting the usual GDP measure produced by the traditional National Account System (NAS) for the total loss of natural capital caused by mining activities shows that the GDP traditional measure overestimated by 51–64% the true economic income generated by Peruvian's metal mining sector during the period 1992–2006. The importance of the generation, taxation, and disposition of mining economic rents for Peru’s sustainable development in the future is also discussed.     

The evolution of the Canadian mining industry: The role of regulatory punctuation

In this study, we analyze the evolution of Canada's mining industry from 1929 to 2006, focussing on the determinants of the number of firms in the industry and why this number changed over that period. Most empirical studies of industry evolution have focused on manufacturing industries that share similar structural characteristics. Perhaps because of this, extant models of industry evolution tend to ignore industry-specific and national-specific factors that can cause atypical trajectories, that is, heterogeneous industry evolution. Initial inspection of the Canadian mining industry shows that it is atypical in that it exhibits “negative skew” over time in the number of firms rather than the typical “positive skew.” We review two dominant theoretical approaches to industry evolution: the density-dependence theory and variants of industrial organization economics. We also consider possible sources of industry evolution heterogeneity, focussing particularly on “regulatory punctuation”. Using Canadian mining data, we find that the traditional models do not fully explain the changes in population size in Canada's mining industry. As a result, we introduce a number of hybrid models. The results from these hybrid models suggest that Canadian-specific regulatory punctuations, particularly the introduction of significant new taxes, environmental legislation, and incentives have shaped the trajectory of mining firm participation.     

Degradation of Phenolic Resin by Tremetes versicolor

A phenolic resin that is used as syntan in leather manufacturing was degraded using Tremetes versicolor. On degradation of this resin for eight days, the reduction in biochemical oxygen demand (BOD), chemical oxygen demand (COD) and total organic carbon (TOC) were 65.11, 76.66 and 72.94% respectively. It was found from the infra red (IR) spectra of the samples that up to seven days the aromaticity was not perturbed however there were reductions in BOD and COD. Addition of co-substrate starch, brought about reduction in BOD, COD and TOC by 85.36, 91.93 and 89.98% respectively. After eight days, there observed a disturbance in the aromatic ring. The enzyme was extracted and assayed for polyphenol oxidase and laccase. Polyphenol oxidase activity and laccase activity of the crude enzyme were found to be 31.4 and 1.67 U/mL. On ammonium sulfate precipitation and dialysis, the polyphenol oxidase activity and laccase activity were enhanced by 1.5- and 3.2-folds respectively.     

Monitoring Regional Riparian Forest Cover Change Using Stratified Sampling and Multiresolution Imagery1

Claggett, Peter R., Judy A. Okay, and Stephen V. Stehman, 2010. Monitoring Regional Riparian Forest Cover Change Using Stratified Sampling and Multiresolution Imagery. Journal of the American Water Resources Association (JAWRA) 46(2):334-343. DOI: 10.1111/j.1752-1688.2010.00424.x Abstract: The Chesapeake Bay watershed encompasses 165,760 km² of land area with 464,098 km of rivers and streams. As part of the Chesapeake Bay restoration effort, state and federal partners have committed to restoring 26,000 miles (41,843 km) of riparian forest buffers. Monitoring trends in riparian forest buffers over large areas is necessary to evaluate the efficacy of these restoration efforts. A sampling approach for estimating change in riparian forest cover from 1993/1994 to 2005 was developed and implemented in Anne Arundel County, Maryland, to exemplify a method that could be applied throughout the Bay watershed. All stream reaches in the county were stratified using forest cover change derived from Landsat imagery. A stratified random sample of 219 reaches was selected and forest cover change within the riparian buffer of each sampled reach was interpreted from high-resolution aerial photography. The estimated footprint of gross change in riparian forest cover (i.e., the sum of gross gain and gross loss) for the county was 1.83% (SE = 0.22%). Stratified sampling taking advantage of a priori knowledge of locations of change proved to be a practical and efficient protocol for estimating riparian forest buffer change at the county scale and the protocol would readily extend to much broader scale monitoring.     

Effects of acetaminophen in <Emphasis Type="Italic">Brassica juncea</Emphasis> L. Czern.: investigation of uptake,translocation, detoxification,and the induced defense pathways

Purpose  

Besides classical organic pollutants and pesticides, pharmaceuticals and their residues have nowadays become recognized as relevant environmental contaminants. The risks of these chemicals for aquatic ecosystems are well known, but information about the pharmaca-plant interactions and metabolic pathways is scarce. Therefore, we investigate the process of uptake of acetaminophen (N-Acetyl-4-aminophenol) by Brassica juncea, drug-induced defense responses and detoxification mechanisms in different plant parts.     

Aerosol speciation and mass prediction from toluene oxidation under high NOx conditions

A kinetically based gas-particle partitioning box model is used to highlight the importance of parameter representation in the prediction of secondary organic aerosol (SOA) formation following the photo-oxidation of toluene. The model is initialized using experimental data from York University's indoor smog chamber and provides a prediction of the total aerosol yield and speciation. A series of model sensitivity experiments were performed to study the aerosol speciation and mass prediction under high NO_x conditions (VOC/NO_x = 0.2). Sensitivity experiments indicate vapour pressure estimation to be a large area of weakness in predicting aerosol mass, creating an average total error range of 70 μg m^?3 (range of 5–145 μg m^?3), using two different estimation methods. Aerosol speciation proved relatively insensitive to changes in vapour pressure. One species, 3-methyl-6-nitro-catechol, dominated the aerosol phase regardless of the vapour pressure parameterization used and comprised 73–88% of the aerosol by mass. The dominance is associated with the large concentration of 3-methyl-6-nitro-catechol in the gas-phase. The high NO_x initial conditions of this study suggests that the predominance of 3-methyl-6-nitro-catechol likely results from the cresol-forming branch in the Master Chemical Mechanism taking a significant role in secondary organic aerosol formation under high NO_x conditions. Further research into the yields and speciation leading to this reaction product is recommended.     

Modeling effects of traffic and landscape characteristics on ambient nitrogen dioxide levels in Connecticut

An integrated exposure model was developed that estimates nitrogen dioxide (NO(2)) concentration at residences using geographic information systems (GIS) and variables derived within residential buffers representing traffic volume and landscape characteristics including land use, population density and elevation. Multiple measurements of NO(2) taken outside of 985 residences in Connecticut were used to develop the model. A second set of 120 outdoor NO(2) measurements as well as cross-validation were used to validate the model. The model suggests that approximately 67% of the variation in NO(2) levels can be explained by: traffic and land use primarily within 2 km of a residence; population density; elevation; and time of year. Potential benefits of this model for health effects research include improved spatial estimations of traffic-related pollutant exposure and reduced need for extensive pollutant measurements. The model, which could be calibrated and applied in areas other than Connecticut, has importance as a tool for exposure estimation in epidemiological studies of traffic-related air pollution.     

Ground-level ozone in the Pearl River Delta region: Analysis of data from a recently established regional air quality monitoring network

The ambient air quality monitoring data of 2006 and 2007 from a recently established Pearl River Delta (PRD) regional air quality monitoring network are analyzed to investigate the characteristics of ground-level ozone in the region. Four sites covering urban, suburban, rural and coastal areas are selected as representatives for detailed analysis in this paper. The results show that there are distinct seasonal and diurnal cycles in ground-level ozone across the PRD region. Low ozone concentrations are generally observed in summer, while high O₃ levels are typically found in autumn. The O₃ diurnal variations in the urban areas are larger than those at the rural sites. The O₃ concentrations showed no statistically significant difference between weekend and weekdays in contrast to the findings in many other urban areas in the world. The average ozone concentrations are lower in urban areas compared to the sites outside urban centers. Back trajectories are used to show the major air-mass transport patterns and to examine the changes in ozone from the respective upwind sites to a site in the center of the PRD (Wanqingsha). The results show higher average ozone concentrations at the upwind sites in the continental and coastal air masses, but higher 1 h-max O₃ concentrations (by 8–16 ppbv) at the center PRD site under each of air-mass category, suggesting that the ozone pollution in the PRD region exhibits both regional and super-regional characteristics.     

Equilibration time scales of organic aerosol inside thermodenuders: Evaporation kinetics versus thermodynamics

The interpretation of thermodenuder (TD) data often relies on the assumption that thermodynamic equilibrium is reached inside the instrument. We modeled the evaporation of three organic aerosol types (adipic acid, α-pinene SOA and aged OA) inside a thermodenuder with a mass transfer model, and calculated equilibration time scales for these systems at realistic conditions. The equilibrium times varied from less than a second to several hours, decreasing with increasing aerosol concentrations, decreasing particle sizes, decreasing volatilities and increasing mass accommodation coefficients. The results indicate that generally TDs measure particle evaporation rates rather than equilibria, and time-dependent modeling of the evaporation is usually needed to interpret the data. Measurements at varying residence times and temperatures, on the other hand, are desirable to investigate the equilibration of the studied aerosol and decouple the kinetic effects from the effects caused by the thermodynamic properties of the aerosol. Organic aerosol is likely to be further from equilibrium under typical field conditions compared with laboratory data. When determining the aerosol properties from TD data, assuming incorrectly equilibrium results in under-prediction of the vaporization enthalpy of the evaporating species. Similar under-estimation is predicted if multicomponent aerosols are approximated with single-component properties.     

Comparison of land-use regression models between Great Britain and the Netherlands

Land-use regression models have increasingly been applied for air pollution mapping at typically the city level. Though models generally predict spatial variability well, the structure of models differs widely between studies. The observed differences in the models may be due to artefacts of data and methodology or underlying differences in source or dispersion characteristics. If the former, more standardised methods using common data sets could be beneficial. We compared land-use regression models for NO₂ and PM_10, developed with a consistent protocol in Great Britain (GB) and the Netherlands (NL).Models were constructed on the basis of 2001 annual mean concentrations from the national air quality networks. Predictor variables used for modelling related to traffic, population, land use and topography. Four sets of models were developed for each country. First, predictor variables derived from data sets common to both countries were used in a pooled analysis, including an indicator for country and interaction terms between country and the identified predictor variables. Second, the common data sets were used to develop individual baseline models for each country. Third, the country-specific baseline models were applied after calibration in the other country to explore transferability. The fourth model was developed using the best possible predictor variables for each country.A common model for GB and NL explained NO₂ concentrations well (adjusted R² 0.64), with no significant differences in intercept and slopes between the two countries. The country-specific model developed on common variables for NL but not GB improved the prediction.The performance of models based upon common data was only slightly worse than models optimised with local data. Models transferred to the other country performed substantially worse than the country-specific models. In conclusion, care is needed both in transferring models across different study areas, and in developing large inter-regional LUR models.