Pore-scale modeling of dispersion in disordered porous media

We employ a direct pore-level model of incompressible flow that uses the modified moving particle semi-implicit (MMPS) method. The model is capable of simulating both unsteady- and steady-state flow directly in microtomography images of naturally-occurring porous media. We further develop this model to simulate solute transport in disordered porous media. The governing equations of flow and transport at the pore level, i.e., Navier-Stokes and convection-diffusion, are solved directly in the pore space mapped by microtomography techniques. Three naturally-occurring sandstones are studied in this work. We verify the accuracy of the model by comparing the computed longitudinal dispersion coefficients against the experimental data for a wide range of Peclet numbers, i.e., 5×10(-2)相似文献   

Geostatistical Assessment of the Impact of World War I on the Spatial Occurrence of Soil Heavy Metals

Previous research showed a regional Cu enrichment of 6 mg kg⁻¹ in the top soil of the Ypres war zone (Belgium), caused by corrosion of WWI shell fragments. Further research was required since in addition to Cu, also As, Pb, and Zn were used during the manufacturing of ammunition. Therefore, an additional data collection was conducted in which the initial Cu data set was tripled to 731 data points and extended to eight heavy metals (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) which permitted (1) to evaluate the environmental impact of the heavy metals at a regional scale and (2) to assess their regional spatial occurrence by performing an optimized geostatistical modeling. The results showed no pollution at a regional scale, but sometimes locally concentrations exceeded the soil sanitation threshold, especially for Cu, Pb, and Zn. The spatial patterns of Ni and Cr were related to variations in soil texture whereas the occurrences of Cu and Pb were clearly linked to WWI activities. This difference in spatial behavior was confirmed by an analysis of coregionalization.     

Particulate matters and gaseous pollutants in indoor environment and Association of ultra-fine particulate matters (PM1) with lung function

Environmental Science and Pollution Research - Real-time particulate matters (PM1, PM2.5, PM4, PM7, PM10, and TSP) with AEROCET 531S (USA), gaseous pollutants (NO2 and TVOC) with Aeroquel 500 gas...     

Green Synthesis of Silver Nanoparticles and Study of Their Antimicrobial Properties

One of the major disadvantages of polymers when used in food-contact applications is that they are very susceptible to microbial attack. On the other hand, silver nanoparticles have received increased attention as novel antimicrobial agents. Therefore, the introduction of silver nanoparticles into conventional polymers results in new materials with improved properties. In this investigation, colloidal silver nanoparticles using an environmentally friendly procedure were synthesized. An aqueous solution of AgNO₃ was used as a silver precursor with ‘green’ reducing agents either different types of honey, or β-d-glucose. In the first case, different pH values, as well as the addition of poly(ethylene glycol), PEG were studied, while in the latter, the effect of reduction time in the presence of PEG with various average molecular weights was examined. Properties of the nanoparticles were measured using X-Ray diffraction, UV–Vis and FTIR spectroscopy. Using honey it seems that spherical particles are produced with the smaller average particle size obtained at pH 8.5. Use of honey has the advantage of being a natural product, although its main drawback is that its composition varies and it cannot be predefined to result in reproducible results. Use of β-d-glucose results in stable silver nanoparticles with small average particle size after 24 h reduction. The addition of low molecular weight PEG seems to be beneficial in the production of stable nanoparticles. Finally, the antimicrobial activity of the nanoparticles produced was investigated at different concentrations on both Gram positive and negative bacteria, such as Bacillus cereus, Bacillus subtilis, Escherichia coli and Staphylococcus aureus.     

Application of multivariate statistical analysis in the pollution and health risk of traffic-related heavy metals

This study aims to analyse the heavy metal pollutants in Jeddah, the second largest city in the Gulf Cooperation Council with a population exceeding 3.5 million, and many vehicles. Ninety-eight street dust samples were collected seasonally from the six major roads as well as the Jeddah Beach, and subsequently digested using modified Leeds Public Analyst method. The heavy metals (Fe, Zn, Mn, Cu, Cd, and Pb) were extracted from the ash using methyl isobutyl ketone as solvent extraction and eventually analysed by atomic absorption spectroscopy. Multivariate statistical techniques, principal component analysis (PCA), and hierarchical cluster analysis were applied to these data. Heavy metal concentrations were ranked according to the following descending order: Fe > Zn > Mn > Cu > Pb > Cd. In order to study the pollution and health risk from these heavy metals as well as estimating their effect on the environment, pollution indices, integrated pollution index, enrichment factor, daily dose average, hazard quotient, and hazard index were all analysed. The PCA showed high levels of Zn, Fe, and Cd in Al Kurnish road, while these elements were consistently detected on King Abdulaziz and Al Madina roads. The study indicates that high levels of Zn and Pb pollution were recorded for major roads in Jeddah. Six out of seven roads had high pollution indices. This study is the first step towards further investigations into current health problems in Jeddah, such as anaemia and asthma.     

Analysis of cost–benefit in life-cycle of plastic solid waste: combining waste flow analysis and life cycle cost as a decision support tool to the selection of optimum scenario

Millions of tons of plastic are consumed annually in the world due to its significant characteristics such as durability, flexibility, and low weight. High consumption has made plastic one of the most important municipal solid waste compounds, the quantity of which has increased in recent decades. Plastic solid wastes are known as a threat to the environment, and its efficient management in various aspects such as cost–benefit requires decision-making tools. This study was assessing the cost–benefit of plastic solid waste management by development of an economic model, and definition of different scenarios to change plastic solid waste management status. The results showed that 8971 tons of plastic solid waste were generated annually in the studied city. The plastic solid wastes were finally transferred to either recycling or landfilling site through 5 identified routes. 83 percent of the total recycled plastic solid waste was due to post-separation routes, and only 7.7 percent of the total plastic solid waste was recycled from the source separation route. The economic comparison of scenarios showed that with the aggregation of post-separation routes, the net revenue of plastic solid waste management increases by 334,000 euro per year while increasing the public participation and the ratio of source separation route raises net revenue by 875,000 euro per year, which was the best economic condition among the scenarios. Using life cycle cost method and it’s respected developed economic model truly satisfied the conditions of both, the current plastic solid waste management and the alternative scenarios, and hence can be adopted as a tool for decision-making.

     

Survey on awareness and attitudes of secondary school students regarding plastic pollution: implications for environmental education and public health in Sharjah city,UAE

Environmental Science and Pollution Research - Since the industrial revolution in the 1800s, plastic pollution is becoming a global reality. This study aims to assess knowledge and attitude about...     

Spatial and Temporal Evaluation of Hydrological Response to Climate and Land Use Change in Three South Dakota Watersheds

This study analyzed changes in hydrology between two recent decades (1980s and 2010s) with the Soil and Water Assessment Tool (SWAT) in three representative watersheds in South Dakota: Bad River, Skunk Creek, and Upper Big Sioux River watersheds. Two SWAT models were created over two discrete time periods (1981‐1990 and 2005‐2014) for each watershed. National Land Cover Datasets 1992 and 2011 were, respectively, ingested into 1981‐1990 and 2005‐2014 models, along with corresponding weather data, to enable comparison of annual and seasonal runoff, soil water content, evapotranspiration (ET), water yield, and percolation between these two decades. Simulation results based on the calibrated models showed that surface runoff, soil water content, water yield, and percolation increased in all three watersheds. Elevated ET was also apparent, except in Skunk Creek watershed. Differences in annual water balance components appeared to follow changes in land use more closely than variation in precipitation amounts, although seasonal variation in precipitation was reflected in seasonal surface runoff. Subbasin‐scale spatial analyses revealed noticeable increases in water balance components mostly in downstream parts of Bad River and Skunk Creek watersheds, and the western part of Upper Big Sioux River watershed. Results presented in this study provide some insight into recent changes in hydrological processes in South Dakota watersheds. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Scenario‐Based and Scenario‐Neutral Assessment of Climate Change Impacts on Operational Performance of a Multipurpose Reservoir

Scenario‐based and scenario‐neutral impacts assessment approaches provide complementary information about how climate change‐driven effects on streamflow may change the operational performance of multipurpose dams. Examining a case study of Cougar Dam in Oregon, United States, we simulated current reservoir operations under scenarios of plausible future hydrology. Streamflow projections from the CGCM3.1 general circulation model for the A1B emission scenario were used to generate stochastic reservoir inflows that were then further perturbed to simulate a potentially drier future. These were then used to drive a simple reservoir model. In the scenario‐based analysis, we found reservoir operations are vulnerable to climate change. Increases in fall and winter inflow could lead to more frequent flood storage, reducing flexibility to store incoming flood flows. Uncertainty in spring inflow volume complicates projection of future filling performance. The reservoir may fill more or less often, depending on whether springs are wetter or drier. In the summer, drawdown may occur earlier to meet conservation objectives. From the scenario‐neutral analysis, we identified thresholds of streamflow magnitude that can predict climate change impacts for a wide range of scenarios. Our results highlight projected operational challenges for Cougar Dam and provide an example of how scenario‐based and scenario‐neutral approaches may be applied concurrently to assess climate change impacts.