Sensitivity of two dispersion models (AERMOD and ISCST3) to input parameters for a rural ground-level area source

As of December 2006, the American Meteorological Society/U.S. Environmental Protection Agency (EPA) Regulatory Model with Plume Rise Model Enhancements (AERMOD-PRIME; hereafter AERMOD) replaced the Industrial Source Complex Short Term Version 3 (ISCST3) as the EPA-preferred regulatory model. The change from ISCST3 to AERMOD will affect Prevention of Significant Deterioration (PSD) increment consumption as well as permit compliance in states where regulatory agencies limit property line concentrations using modeling analysis. Because of differences in model formulation and the treatment of terrain features, one cannot predict a priori whether ISCST3 or AERMOD will predict higher or lower pollutant concentrations downwind of a source. The objectives of this paper were to determine the sensitivity of AERMOD to various inputs and compare the highest downwind concentrations from a ground-level area source (GLAS) predicted by AERMOD to those predicted by ISCST3. Concentrations predicted using ISCST3 were sensitive to changes in wind speed, temperature, solar radiation (as it affects stability class), and mixing heights below 160 m. Surface roughness also affected downwind concentrations predicted by ISCST3. AERMOD was sensitive to changes in albedo, surface roughness, wind speed, temperature, and cloud cover. Bowen ratio did not affect the results from AERMOD. These results demonstrate AERMOD's sensitivity to small changes in wind speed and surface roughness. When AERMOD is used to determine property line concentrations, small changes in these variables may affect the distance within which concentration limits are exceeded by several hundred meters.     

Comparison of vehicle activity and emission inventory between Beijing and Shanghai

Vehicle emission inventory is a critical element for air quality study. This study created systemic methods to establish a vehicle emission inventory in Chinese cities. The methods were used to obtain credible results of vehicle activity in Beijing and Shanghai. On the basis of the vehicle activity data, the International Vehicle Emission model is used to establish vehicle emission inventories. The emissions analysis indicates that 3 t of particulate matter (PM), 199 t of nitrogen oxides (NO(x)), 192 t of volatile organic compounds (VOCs), and 2403 t of carbon monoxide (CO) are emitted from on-road vehicles each day in Beijing, whereas 4 t of PM, 189 t of NO(x), 113 t of VOCs, and 1009 t of CO are emitted in Shanghai. Although common features were found in these two cities (many new passenger cars and a high taxi proportion in the fleet), the emission results are dissimilar because of the different local policy regarding vehicles. The method to quantify vehicle emission on an urban scale can be applied to other Chinese cities. Also, knowing how different policies can lead to diverse emissions is beneficial knowledge for other city governments.     

Molecular tools for bathing water assessment in Europe: Balancing social science research with a rapidly developing environmental science evidence-base

The use of molecular tools, principally qPCR, versus traditional culture-based methods for quantifying microbial parameters (e.g., Fecal Indicator Organisms) in bathing waters generates considerable ongoing debate at the science–policy interface. Advances in science have allowed the development and application of molecular biological methods for rapid (~2 h) quantification of microbial pollution in bathing and recreational waters. In contrast, culture-based methods can take between 18 and 96 h for sample processing. Thus, molecular tools offer an opportunity to provide a more meaningful statement of microbial risk to water-users by providing near-real-time information enabling potentially more informed decision-making with regard to water-based activities. However, complementary studies concerning the potential costs and benefits of adopting rapid methods as a regulatory tool are in short supply. We report on findings from an international Working Group that examined the breadth of social impacts, challenges, and research opportunities associated with the application of molecular tools to bathing water regulations.     

Face mask and medical waste generation in the City of Baguio,Philippines: its current management and GHG footprint

Journal of Material Cycles and Waste Management - The daily use of facemask to prevent virus transmission increases the negative effect on the environment because of improper waste disposal. Due to...     

Zinc removal from synthetic waters using magnetite/graphene oxide composites

The removal of heavy metals from wastewater has become a global challenge, which demands the continuous study of efficient and low-cost treatment alternatives such as adsorption. In this research, the removal of zinc was evaluated using batch adsorption processes with nonconventional materials such as graphene oxide (GO), magnetite (MG), and their composites (GO:MG), formulated with three weight ratios (2:1, 1:1, and 1:2). Graphene was synthesized by the modified Marcano method, using pencil lead graphite as a precursor. MG and the composites were synthesized by chemical coprecipitation of ferrous sulfate and ferric chloride. The materials were characterized by Raman and Fourier transform infrared spectroscopies, scanning electron microscopy, X-ray diffraction, and the Brunauer–Emmett–Teller method to determine the functional groups, microstructural and morphological characteristics, and specific surface area. Batch adsorption tests were carried out to optimize the adsorbent dose and contact time with zinc solutions of 10 ppm. Zinc adsorption reached equilibrium at 2 h, with an optimal dose between 0.25 and 1.0 g/L. The maximum zinc removal efficiencies/adsorption capacities were 98.6%/165.6, 83.4%/47.6, 83.5%/21.9, 72.8%/19.9, and 82.2%/9.25 mg/g using GO, 2GO:1MG, 1GO:1MG, 1GO:2MG, and MG, respectively. Furthermore, the analysis of the isotherm and adsorption kinetics models determined that the adsorption processes using MG and the composites fit the Sips and pseudo-second-order models.     

Synergistic Techniques for Better Understanding and Classifying the Environmental Structure of Landscapes

The desire to capture natural regions in the landscape has been a goal of geographic and environmental classification and ecological land classification (ELC) for decades. Since the increased adoption of data-centric, multivariate, computational methods, the search for natural regions has become the search for the best classification that optimally trades off classification complexity for class homogeneity. In this study, three techniques are investigated for their ability to find the best classification of the physical environments of the Mt. Lofty Ranges in South Australia: AutoClass-C (a Bayesian classifier), a Kohonen Self-Organising Map neural network, and a k-means classifier with homogeneity analysis. AutoClass-C is specifically designed to find the classification that optimally trades off classification complexity for class homogeneity. However, AutoClass analysis was not found to be assumption-free because it was very sensitive to the user-specified level of relative error of input data. The AutoClass results suggest that there may be no way of finding the best classification without making critical assumptions as to the level of class heterogeneity acceptable in the classification when using continuous environmental data. Therefore, rather than relying on adjusting abstract parameters to arrive at a classification of suitable complexity, it is better to quantify and visualize the data structure and the relationship between classification complexity and class homogeneity. Individually and when integrated, the Self-Organizing Map and k-means classification with homogeneity analysis techniques also used in this study facilitate this and provide information upon which the decision of the scale of classification can be made. It is argued that instead of searching for the elusive classification of natural regions in the landscape, it is much better to understand and visualize the environmental structure of the landscape and to use this knowledge to select the best ELC at the required scale of analysis.     

Spatial and Temporal Variations in Trace Metal Concentrations in the Cockle, Austrovenus Stutchburyi from Otago, New Zealand

This is the first comprehensive study of sources of variation in metal concentrations within the whole tissues of a shallow burrowing, filter-feeding intertidal clam, Austrovenus stutchburyi. Samples were collected from 12 sites in April, August, November and February in 1993–1994 in the vicinity of Otago Harbour and Peninsula, New Zealand. Total tissue trace metal concentrations (μg g⁻¹ dry weight) were measured in individual animals for the essential metals : Mn, Cu, Zn, Ni and the non-essential Cr using trace-metal clean acid-digestion and ICP-OAES techniques. Average metal concentrations were 3–60 μg g⁻¹ for Cu, 40–118 μg g⁻¹ for Zn, 2–12 μg g⁻¹ for Mn, 5–35 μg g⁻¹ for Ni and 1–44 μg g⁻¹ for Cr. These levels decreased with body weight and differed amongst sites except for Cr in February (mid-summer). Highest concentrations occurred at sites close to a city (Dunedin) and within the central harbour region although the Cu, Zn, Ni and Cr concentrations did not correlate with the environmental gradient or season. At one coastal site, samples of both the blue mussel Mytilus galloprovincialis and cockles gave similar trends in trace metal levels. These results suggest that the cockle could be a useful trace metal biomonitor within NZ estuaries.     

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.     

The influence of sampling protocol on nonmethane hydrocarbon mixing ratios

The effect of sampling protocol on ambient air hydrocarbon mixing ratios was examined on eight sampling days in Los Angeles during 2007 and 2008. Four protocols, which were based on previously published multi-city urban hydrocarbon studies in the United States, were compared and differences were quantified. Whole air canister samples were collected and analyzed for nonmethane hydrocarbons (NMHCs). Differing sampling protocols resulted in large differences in mixing ratios, up to an order of magnitude, for certain NMHCs on the same sampling day. However, the magnitude of the variability between NMHC levels obtained by the four protocols was not consistent throughout the eight sampling days. It was found that sampling time, followed by sampling location, had the greatest influence on the magnitude of the mixing ratio. Ratios between hydrocarbons, often used in urban studies to gain information on emission sources, also varied depending on the protocol used. Comparison of absolute NMHC mixing ratios collected in urban environments using differing sampling protocols should be made with care.