Modelling air pollution for epidemiologic research--part II: predicting temporal variation through land use regression

Over recent years land use regression (LUR) has become a frequently used method in air pollution exposure studies, as it can model intra-urban variation in pollutant concentrations at a fine spatial scale. However, very few studies have used the LUR methodology to also model the temporal variation in air pollution exposure. The aim of this study is to estimate annual mean NO₂ and PM₁₀ concentrations from 1996 to 2008 for Greater Manchester using land use regression models. The results from these models will be used in the Manchester Asthma and Allergy Study (MAAS) birth cohort to determine health effects of air pollution exposure.The Greater Manchester LUR model for 2005 was recalibrated using interpolated and adjusted NO₂ and PM₁₀ concentrations as dependent variables for 1996-2008. In addition, temporally resolved variables were available for traffic intensity and PM₁₀ emissions. To validate the resulting LUR models, they were applied to the locations of automatic monitoring stations and the estimated concentrations were compared against measured concentrations.The 2005 LUR models were successfully recalibrated, providing individual models for each year from 1996 to 2008. When applied to the monitoring stations the mean prediction error (MPE) for NO₂ concentrations for all stations and years was -0.8 μg/m³ and the root mean squared error (RMSE) was 6.7 μg/m³. For PM₁₀ concentrations the MPE was 0.8 μg/m³ and the RMSE was 3.4 μg/m³.These results indicate that it is possible to model temporal variation in air pollution through LUR with relatively small prediction errors. It is likely that most previous LUR studies did not include temporal variation, because they were based on short term monitoring campaigns and did not have historic pollution data. The advantage of this study is that it uses data from an air dispersion model, which provided concentrations for 2005 and 2010, and therefore allowed extrapolation over a longer time period.     

Use of slow filtration columns to assess oxygen respiration, consumption of dissolved organic carbon, nitrogen transformations, and microbial parameters in hyporheic sediments

Biogeochemical processes mediated by microorganisms in river sediments (hyporheic sediments) play a key role in river metabolism. Because biogeochemical reactions in the hyporheic zone are often limited to the top few decimetres of sediments below the water-sediment interface, slow filtration columns were used in the present study to quantify biogeochemical processes (uptakes of O2, DOC, and nitrate) and the associated microbial compartment (biomass, respiratory activity, and hydrolytic activity) at a centimetre scale in heterogeneous (gravel and sand) sediments. The results indicated that slow filtration columns recreated properly the aerobic-anaerobic gradient classically observed in the hyporheic zone. O2 and NO3- consumptions (256 +/- 13 microg of O2 per hour and 14.6 +/- 6.1 microg of N-NO3- per hour) measured in columns were in the range of values measured in different river sediments. Slow filtration columns also reproduced the high heterogeneity of the hyporheic zone with the presence of anaerobic pockets in sediments where denitrification and fermentation processes occurred. The respiratory and hydrolytic activities of bacteria were strongly linked with the O2 consumption in the experimental system, highlighting the dominance of aerobic processes in our river sediments. In comparison with these activities, the bacterial biomass (protein content) integrated both aerobic and anaerobic processes and could be used as a global microbial indicator in our system. Finally, slow filtration columns are an appropriate tool to quantify in situ rates of biogeochemical processes and to determine the relationship between the microbial compartment and the physico-chemical environment in coarse river sediments.     

Effects of copper, pH and hardness on the critical swimming performance of rainbow trout (Salmo gairdneri Richardson)

Critical swimming velocities of Salmo gairdneri at 12°C were determined in different combinations of copper; pH and hardness. Measurements were made after exposure for 0.5, 5, 10, and 30 days. When copper was not applied, hardness, pH and exposure time had no appreciable effect on critical performance. Copper had the greatest effect on swimming performance at 5 days of exposure. At pH 7.5–8.0, recovery from the initial depression was complete after 10 days of exposure, but critical swimming performance did not return to control levels in pH 6.0 treatments. For any given hardness, copper had a greater effect on critical speed at low than at high pH. A given copper treatment had a more pronounced effect at low than at high hardness.No distinction could be made among total, soluble, or extractable copper but predicted concentrations of 6 specific cupric ions varied with pH and hardness. Of these copper species, only Cu²⁺ and CuOH⁺ were found to be related significantly to critical performance.Oxygen consumption of trout was determined in different combinations of copper and pH. In the presence of copper the maximum oxygen consumption decreased and the energy expenditure for a given swimming speed increased.The above observations are discussed in relation to reported toxic actions of copper.     

The Options Available for Ammonia Removal at Davyhulme Sewage-Treatment Works

Davyhulme sewage-treatment works, which serves the Manchester drainage area, is one of the lagest in the UK. The dry-weather flow is 300 000 m³/d, and the plant receives a wide range of industrial effluents. The works has been identified as a major source of pollution in the Mersey estuary, with an average discharge of 6500 kg ammonia/day. As part of its initiative to improve the Mersey estuary, North West Water intends to reduce the daily ammonia load from Davyhulme to about 1000 kg/d by 1995. In order to assess the capabilities of both conventional and novel processes to achieve this degree of ammonia removal, a number of on-site pilot plants were established. This paper reports on the pilot-plant studies and the selection of process options. Recommendations with regard to design parameters and final process selection are given.     

Modification of Polycaproamide Composites Based on 1H,1H,13H-rihydroperfluorotridecan-1-ol and Montmorillonite

Fibre Chemistry - Modification of polycaproamide by 1H,1H,13H-trihydroperfluorotridecan-1-ol immobilized on montmorillonite produced an F-containing polymer composite. The structure of the...     

Gas-Phase Treatment of Dump Tailings from Metallurgical Plants in Nitrating Media to Enhance Nickel Extraction

Theoretical Foundations of Chemical Engineering - A new approach to the processing of the dump waste product stored in the tailings dumps of the nickel production enterprise Punda Gourda (Cuba) has...     

Design and manufacture of high-filling-efficiency microfluidic devices

In this study, we proposed an efficient method for mass production of high-filling-efficiency microfluidic devices. Precision machining was the main process of device fabrication. The commercially available SolidWorks software was adopted for structure design. Unigraphics software was then used to simulate the machining process. The simulated tooling file was then loaded into a CNC milling machine for mold production. The fabricated metal mold was used for pouring polydimethylsiloxane (PDMS) to obtain high-filling-efficiency microfluidic structures. Finally, plasma-assisted packaging was conducted to tightly bind the PDMS microfluidic structure to the glass substrate. Experimental results showed that the additional semicircular filling structure and expended fill-entry structure can efficiently enhance filling efficiency of the microchannel device. The incubation well array can be completely filled at a relatively short filling time. The proposed highly efficient filling microfluidic device possesses advantages, such as feasibility for mass production and cost effectiveness.     

Evaluation of grinding wheel loading phenomena by using acoustic emission signals

In the industrial manufacturing field, machining is a major process. Machining operations involve grinding, drilling, milling, turning, pressing, molding, and so on. Among these operations, grinding is the most precise and complicated process. The surface condition of the grinding wheel plays an important role in grinding performance, and the identification of grinding wheel loading phenomena during the grinding process is critical. Accordingly, this present study describes a measurement method based on the acoustic emission (AE) technique to characterize the loading phenomena of a Si₂O₃ grinding wheel for the grinding mass production process. The proposed measurement method combines the process-integrated measurement of AE signals, offline digital image processing, and surface roughness measurement of the ground workpieces for the evaluation of grinding wheel loading phenomena. The experimental results show that the proposed measurement method provides a quantitative index from the AE signals to evaluate the grinding wheel loading phenomena online for the grinding mass production process, and this quantitative index is determined via some experiments in advance in the same grinding environment to help the monitoring and controlling of the grinding process.     

Research on quality improvement of the cross section cut by abrasive water jet based on secondary cutting

A manufacturing system comprises production processes and building services, both of which are supplied by different energy carriers as well as raw materials and water. These resources interact according to complex relationships and are converted into products for sale and waste flows. Holistic resource accounting allows the analyst to consider the dynamic relationships between these components, including the strong interdependence between energy and water, which has been called the energy-water nexus. Exergy analysis is a method that accounts for mass and both the quantity and quality of energy, while allowing analysis on a common basis, and for this reason, it is used increasingly to analyse resource consumption in manufacturing systems; however, it has rarely been used to consider water flows alongside energy and material flows. The main contribution of this paper is the presentation of modelling water flows in terms of exergy in the context of sustainable manufacturing. Using this technique in combination with previously developed exergy-based methods, the result is a truly holistic resource accounting method for factories based on exergy analysis that incorporates water flows. The method is illustrated using a case study of a food factory in which a 4.1% reduction in resource use is shown to be possible by employing anaerobic digester in an effluent water treatment process. The benefits of this technology option would have been underestimated compared to the benefits of waste heat capture if an analysis based on mass and energy balances alone had been used. The scientific value of this paper is the demonstration of the relatively high exergy content of effluent flows, which should therefore be regarded as potentially valuable resources. The analytical method presented is therefore of value to a wide range of industries beyond the food industry.