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.     

Ecologically Functional Floodplains: Connectivity,Flow Regime,and Scale1

Opperman, Jeffrey J., Ryan Luster, Bruce A. McKenney, Michael Roberts, and Amanda Wrona Meadows, 2010. Ecologically Functional Floodplains: Connectivity, Flow Regime, and Scale. Journal of the American Water Resources Association (JAWRA) 46(2):211-226. DOI: 10.1111/j.1752-1688.2010.00426.x Abstract: This paper proposes a conceptual model that captures key attributes of ecologically functional floodplains, encompassing three basic elements: (1) hydrologic connectivity between the river and the floodplain, (2) a variable hydrograph that reflects seasonal precipitation patterns and retains a range of both high and low flow events, and (3) sufficient spatial scale to encompass dynamic processes and for floodplain benefits to accrue to a meaningful level. Although floodplains support high levels of biodiversity and some of the most productive ecosystems on Earth, they are also among the most converted and threatened ecosystems and therefore have recently become the focus of conservation and restoration programs across the United States and globally. These efforts seek to conserve or restore complex, highly variable ecosystems and often must simultaneously address both land and water management. Thus, such efforts must overcome considerable scientific, technical, and socioeconomic challenges. In addition to proposing a scientific conceptual model, this paper also includes three case studies that illustrate methods for addressing these technical and socioeconomic challenges within projects that seek to promote ecologically functional floodplains through river-floodplain reconnection and/or restoration of key components of hydrological variability.     

Factors Influencing Prymnesium parvum Population Dynamics During Bloom Initiation: Results from In-lake Mesocosm Experiments1

Roelke, Daniel L., Leslie Schwierzke, Bryan W. Brooks, James P. Grover, Reagan M. Errera, Theodore W. Valenti, Jr., and James L. Pinckney, 2010. Factors Influencing Prymnesium parvum Population Dynamics During Bloom Initiation: Results from In-Lake Mesocosm Experiments. Journal of the American Water Resources Association (JAWRA) 46(1):76-91. DOI: 10.1111/j.1752-1688.2009.00392.x Abstract: The alga Prymnesium parvum forms large fish-killing blooms in many Texas lakes. In some of these lakes, however, P. parvum occurs but does not develop blooms. In this study, we investigated factors that may influence bloom initiation by conducting a series of in-lake experiments involving mixing of waters from Lake Whitney, which has a history of P. parvum blooms, with waters from Lake Waco where no blooms have occurred. In all experiments, the addition of Lake Waco waters resulted in a poorer performance of P. parvum. Various experimental treatments and field data show that differences in grazing, pathogens, nutrients, and salts between the two lakes were not likely factors that contributed to this observation. Industrial and agricultural contaminants, allelochemicals and algicidal chemicals were not measured as a part of this research. However, anthropogenic contaminants other than nutrients were not observed at levels exceeding water quality standards in Lake Waco in recent years. On the other hand, nuisance cyanobacteria are common in Lake Waco, where Microcystis sp. and Anabaena sp. were abundant during the initiation of our experiments, both taxa are known to produce chemicals with allelopathic properties. In addition, the emergent field of algal-heterotrophic bacteria interactions suggests that chemicals produced by heterotrophic bacteria should not be overlooked. Further research focusing on the chemical interactions between cyanobacteria and P. parvum, as well as the potential role of algicidal bacteria, in the initiation of P. parvum blooms is necessary, as it may be important to the management of these blooms.     

Source apportionment of wintertime secondary organic aerosol during the California regional PM10/PM2.5 air quality study

The UCD/CIT air quality model with the Caltech Atmospheric Chemistry Mechanism (CACM) was used to predict source contributions to secondary organic aerosol (SOA) formation in the San Joaquin Valley (SJV) from December 15, 2000 to January 7, 2001. The predicted 24-day average SOA concentration had a maximum value of 4.26 μg m^?3 50 km southwest of Fresno. Predicted SOA concentrations at Fresno, Angiola, and Bakersfield were 2.46 μg m^?3, 1.68 μg m^?3, and 2.28 μg m^?3, respectively, accounting for 6%, 37%, and 4% of the total predicted organic aerosol. The average SOA concentration across the entire SJV was 1.35 μg m^?3, which accounts for approximately 20% of the total predicted organic aerosol. Averaged over the entire SJV, the major SOA sources were solvent use (28% of SOA), catalyst gasoline engines (25% of SOA), wood smoke (16% of SOA), non-catalyst gasoline engines (13% of SOA), and other anthropogenic sources (11% of SOA). Diesel engines were predicted to only account for approximately 2% of the total SOA formation in the SJV because they emit a small amount of volatile organic compounds relative to other sources. In terms of SOA precursors within the SJV, long-chain alkanes were predicted to be the largest SOA contributor, followed by aromatic compounds. The current study identifies the major known contributors to the SOA burden during a winter pollution episode in the SJV, with further enhancements possible as additional formation pathways are discovered.     

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.     

Theoretical versus observed gas-particle partitioning of carbonyl emissions from motor vehicles

A state-of-the-science thermodynamic model describing gas-particle absorption processes was used to predict the gas-particle partitioning of mixtures of approximately 60 carbonyl compounds emitted from low-emission gasoline-powered vehicles, three-way catalyst gasoline-powered vehicles, heavy-duty diesel vehicles under the idle-creep condition (HDDV idle), and heavy-duty diesel vehicles under the five-mode test (HDDV 5-mode). Exhaust was diluted by a factor of 120-580 with a residence time of approximately 43 sec. The predicted equilibrium absorption partitioning coefficients differed from the measured partitioning coefficients by several orders of magnitude. Time scales to reach equilibrium in the dilution sampling system were close to the actual residence time during the HDDV 5-mode test and much longer than the actual residence time during the other vehicle tests. It appears that insufficient residence time in the sampling system cannot uniformly explain the failure of the absorption mechanism to explain the measured partitioning. Other gas-particle partitioning mechanisms (e.g., heterogeneous reactions, capillary adsorption) beyond the simple absorption theory are needed to explain the discrepancy between calculated carbonyl partitioning coefficients and observed partitioning. Both of these alternative partitioning mechanisms imply great challenges for the measurement and modeling of semi-volatile primary organic aerosol (POA) species from motor vehicles. Furthermore, as emitted particle concentrations from newer vehicles approach atmospheric background levels, dilution sampling systems must fundamentally change their approach so that they use realistic particle concentrations in the dilution air to approximately represent real-world conditions. Samples collected with particle-free dilution air yielding total particulate matter concentrations below typical ambient concentrations will not provide a realistic picture of partitioning for semi-volatile compounds.     

Simulating the fine and coarse inorganic particulate matter concentrations in a polluted megacity

A three dimensional chemical transport model (PMCAMx) is applied to the Mexico City Metropolitan Area (MCMA) in order to simulate the chemical composition and mass of the major PM₁ (fine) and PM_1–10 (coarse) inorganic components and determine the effect of mineral dust on their formation. The aerosol thermodynamic model ISORROPIA-II is used to explicitly simulate the effect of Ca, Mg, and K from dust on semi-volatile partitioning and water uptake. The hybrid approach is applied to simulate the inorganic components, assuming that the smallest particles are in thermodynamic equilibrium, while describing the mass transfer to and from the larger ones. The official MCMA 2004 emissions inventory with improved dust and NaCl emissions is used. The comparison between the model predictions and measurements during a week of April of 2003 at Centro Nacional de Investigacion y Capacitacion Ambiental (CENICA) “Supersite” shows that the model reproduces reasonably well the fine mode composition and its diurnal variation. Sulfate predicted levels are relatively uniform in the area (approximately 3 μg m^?3), while ammonium nitrate peaks in Mexico City (approximately 7 μg m^?3) and its concentration rapidly decreases due to dilution and evaporation away from the urban area. In areas of high dust concentrations, the associated alkalinity is predicted to increase the concentration of nitrate, chloride and ammonium in the coarse mode by up to 2 μg m^?3 (a factor of 10), 0.4 μg m^?3, and 0.6 μg m^?3 (75%), respectively. The predicted ammonium nitrate levels inside Mexico City for this period are sensitive to the physical state (solid versus liquid) of the particles during periods with RH less than 50%.     

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.     

Influence of regional development policies and clean technology adoption on future air pollution exposure

Future air pollution emissions in the year 2030 were estimated for the San Joaquin Valley (SJV) in central California using a combined system of land use, mobile, off-road, stationary, area, and biogenic emissions models. Four scenarios were developed that use different assumptions about the density of development and level of investment in transportation infrastructure to accommodate the expected doubling of the SJV population in the next 20 years. Scenario 1 reflects current land-use patterns and infrastructure while scenario 2 encouraged compact urban footprints including redevelopment of existing urban centers and investments in transit. Scenario 3 allowed sprawling development in the SJV with reduced population density in existing urban centers and construction of all planned freeways. Scenario 4 followed currently adopted land use and transportation plans for the SJV. The air quality resulting from these urban development scenarios was evaluated using meteorology from a winter stagnation event that occurred on December 15th, 2000 to January 7th 2001. Predicted base-case PM2.5 mass concentrations within the region exceeded 35 μg m^?3 over the 22-day episode. Compact growth reduced the PM2.5 concentrations by ～1 μg m^?3 relative to the base-case over most of the SJV with the exception of increases (～1 μg m^?3) in urban centers driven by increased concentrations of elemental carbon (EC) and organic carbon (OC). Low-density development increased the PM2.5 concentrations by 1–4 μg m^?3 over most of the region, with decreases (0.5–2 μg m^?3) around urban areas. Population-weighted average PM2.5 concentrations were very similar for all development scenarios ranging between 16 and 17.4 μg m^?3. Exposure to primary PM components such as EC and OC increased 10–15% for high density development scenarios and decreased by 11–19% for low-density scenarios. Patterns for secondary PM components such as nitrate and ammonium ion were almost exactly reversed, with a 10% increase under low-density development and a 5% decrease under high density development. The increased human exposure to primary pollutants such as EC and OC could be predicted using a simplified analysis of population-weighted primary emissions. Regional planning agencies should develop thresholds of population-weighted primary emissions exposure to guide the development of growth plans. This metric will allow them to actively reduce the potential negative impacts of compact growth while preserving the benefits.