Desert Water Harvesting to Benefit Wildlife: A Simple, Cheap, And Durable Sub-Surface Water Harvester for Remote Locations

A sub-surface desert water harvester was constructed in the sagebrush steppe habitat of south-central Idaho, U.S.A. The desert water harvester utilizes a buried micro-catchment and three buried storage tanks to augment water for wildlife during the dry season. In this region, mean annual precipitation (MAP) ranges between about 150–250 mm (6″–10″), 70% of which falls during the cold season, November to May. Mid-summer through early autumn, June through October, is the dry portion of the year. During this period, the sub-surface water harvester provides supplemental water for wildlife for 30–90 days, depending upon the precipitation that year. The desert water harvester is constructed with commonly available, “over the counter” materials. The micro-catchment is made of a square-shaped, 20 mL. “PERMALON” polyethylene pond liner (approximately 22.9 m × 22.9 m = 523 m²) buried at a depth of about 60 cm. A PVC pipe connects the harvester with two storage tanks and a drinking trough. The total capacity of the water harvester is about 4777 L (1262 U.S. gallons) which includes three underground storage tanks, a trough and pipes. The drinking trough is refined with an access ramp for birds and small animals. The technology is simple, cheap, and durable and can be adapted to other uses, e.g. drip irrigation, short-term water for small livestock, poultry farming etc. The desert water harvester can be used to concentrate and collect water from precipitation and run-off in semi-arid and arid regions. Water harvested in such a relatively small area will not impact the ground water table but it should help to grow small areas of crops or vegetables to aid villagers in self-sufficiency.     

Drainage Effects on Stream Nitrate-N and Hydrology in South-Central Minnesota (USA)

Excessive nitrate-N in south-central Minnesota ditches and streams is related to land-use change, and may be contributing to the development of the zone of hypoxia in the Gulf of Mexico. Intensive land-use (agricultural management) has progressively increased as subsurface drainage has improved crop productivity over the past 25 years. We have examined water at varying scales for delta18O and, nitrate-N concentrations. Additionally, analysis of annual peak flows, and channel geomorphic features provided a measure of hydrologic change. Laboratory and field results indicate that agricultural drainage has influenced riverine source waters, concentrations of nitrate-N, channel dimensions and hydrology in the Blue Earth River (BER) Basin. At the mouth of the BER shallow ground water comprises the largest source water component. The highest nitrate-N concentrations in the BER and tributaries typically occurred in May and June and ranged from 7-34 mg L(-1). Peak flows for the 1.01-2-yr recurrence intervals increased by 20-to-206% over the past 25 years. Geomorphic data suggest that small channels (ditches) were entrenched by design, whereas, natural that are disconnected from an accessible riparian corridor. Frequent access to a functioning riparian zone is important for denitrification.     

TPH-contaminated Mexican Refinery Soil: Health Risk Assessment and the First Year of Changes

The soil of a coastal Mexican refinery is quite contaminated, especially by hydrocarbons, with detected concentrations up to 130000 mg kg(-1) as TPHs (total petroleum hydrocarbons). The main sources of contamination are pipelines, valves, and old storage tanks, besides the land disposal of untreated hydrocarbon sediments derived from the cleaning of storage tanks. A health risk assessment (HRA) was carried out in order to measure the risk hazard indexes and clean-up standards for the refinery soil. HRA suggested the following actions to be taken: benzene concentrations must be reduced in eight of the 16 studied refinery zones to 0.0074-0.0078 mg kg(-1). Also, vanadium concentration must be reduced in two zones up to a concentration of 100 mg kg(-1). In only one of all of the studied zones, benzo(a)pyrene concentration must be reduced to 0.1 mg kg(-1). After 1 yr, TPHs showed a diminution of about 52%. Even though TPHs concentrations were variable, during 1999 the average concentrations were as much as 15.5 times the goal concentration. For year 2000, TPHs concentrations were only 7.4-fold the proposed value. For the 1999-2000 period, PAHs (polycyclic aromatic hydrocarbons) concentrations decreased by 82%. Some PAHs with 2, 3, 4, and 5 aromatic rings were removed up to 100% values.     

Effects of Roadway Crossings on Leaf Litter Processing and Invertebrate Assemblages in Small Streams

The effects of the Maine Turnpike (Interstate 95) on leaf litter processing were examined in five first- and second-order coastal plain streams in southern Maine, U.S.A. Invertebrate assemblages and red maple leaf softening and loss rates were compared at 53 stations arrayed upstream and downstream of the turnpike. Litter softening rate was not affected by the roadway. Litter loss rate was significantly faster at downstream stations (-0.0024 degree-day(-1)) than at upstream stations or at stations nearest the roadway, which were not different from each other (-0.0022 degree-day(-1)). Litter softening and loss rates were more strongly related to physical and chemical habitat variables than to shredder assemblage characteristics. Significant among-stream differences were observed in most community structural metrics and in biomass of important shredder taxa, but effects of the roadway were rarely consistent among streams. This is attributed in part to habitat variation, which was greater among streams than within streams. This study suggests that while the presence of the Maine Turnpike may influence stream water quality and habitat structure, the relatively subtle effects of roadway runoff and associated habitat modifications on stream ecosystem processes are masked by within- and among-stream variability in litter processing and leaf pack invertebrate assemblage structure.     

Development of an ombrotrophic peat bog (low ash) reference material for the determination of elemental concentrations

Given the increasing interest in using peat bogs as archives of atmospheric metal deposition, the lack of validated sample preparation methods and suitable certified reference materials has hindered not only the quality assurance of the generated analytical data but also the interpretation and comparison of peat core metal profiles from different laboratories in the international community. Reference materials play an important role in the evaluation of the accuracy of analytical results and are essential parts of good laboratory practice. An ombrotrophic peat bog reference material has been developed by 14 laboratories from nine countries in an inter-laboratory comparison between February and October 2002. The material has been characterised for both acid-extractable and total concentrations of a range of elements, including Al, As, Ca, Cd, Cr, Cu, Fe, Hg, Mg, Mn, Na, Ni, P, Pb, Ti, V and Zn. The steps involved in the production of the reference material (i.e. collection and preparation, homogeneity and stability studies, and certification) are described in detail.     

Organochlorine Pesticide Residues in Wheat and Drinking Water Samples from Jaipur, Rajasthan, India

The organochlorine pesticide contamination in dietary sources has caused serious threat to the human progeny. The present study was therefore conducted to evaluate the pesticide contamination in wheat flour and drinking water from Jaipur City, Rajasthan, India using Gas Chromatograph. All the wheat and water samples were found to be contaminated with various organochlorine pesticide residues of DDT and its metabolites, HCH and its isomers, heptachlor and its expoxide and aldrin. The amount of pesticide detected in wheat flour was higher than the permissible limits prescribed by WHO/FAO. In drinking water only a few pesticides exceeded the permissible limits. Seasonal variations of pesticides residues were also observed during the study period.     

Selection and Calibration of Numerical Modeling in Flow and Water Quality

Numerical modeling is frequently used in coastal engineering research and application. One possible issue associated with using this method however, is that initial outcomes might differ from expectation. Modeling manipulation addresses this issue by changing the initial parameters which in turn affects the final output results. The advancement of modeling techniques in recent years has seen a gradual but steady accruement of knowledge regarding the relationship between input parameters and possible outputs, which has resulted in improved accuracy and efficiency methods. The advancements within this field have predominantly occurred on an individual basis and as such lack standardisation. An expert numerical modeler may use this knowledge subconsciously, yet may not know how to convey it to the model users. This paper has been written to introduce a systematic intelligent coding schema designed to organise current coastal engineering modeling manipulation knowledge into a standardised format. This system is relevant to the development of appropriate strategies for improved accuracy and efficiency as well as model modification to simulate specific real phenomena in prototype application cases.     

膜、柱串联固相萃取-高效液相色谱法测定水中多环芳烃(PAHs)的研究

建立了用膜-柱串联固相萃取(SPE)技术,甲醇和水作为流动相进行梯度洗脱,紫外和荧光检测器串联的高效液相色谱法(HPLC)分析水中EPA优先监控的16种PAHs的方法.     

How and why is Aquatic Quality Changing at Nahanni National Park Reserve, nwt, Canada?

Nahanni National Park Reserve is located at southwestern NWT-Yukon border. One of the first UNESCO World Heritage sites, Nahanni lies within Taiga Cordillera and Taiga Shield Ecozones. Base and precious metal mining occurred upstream of Nahanni prior to park establishment. Nahanni waters, sediments, fish, and caribou have naturally elevated metals levels. Baseline water, sediment and fish tissue quality data were collected and analyzed throughout Nahanni during 1988–91 and 1992–97. These two programs characterized how aquatic quality variables are naturally varying in space and time, affected by geology, stream flow, seasonality, and extreme meteorological and geological events. Possible anthropogenic causes of aquatic quality change were examined. Measured values were compared to existing Guidelines and site-specific objectives were established.     

Using improved neural network model to analyze RSP,NOx and NO2 levels in urban air in Mong Kok,Hong Kong

As the health impact of air pollutants existing in ambient addresses much attention in recent years, forecasting of airpollutant parameters becomes an important and popular topic inenvironmental science. Airborne pollution is a serious, and willbe a major problem in Hong Kong within the next few years. InHong Kong, Respirable Suspended Particulate (RSP) and NitrogenOxides NO_x and NO₂ are major air pollutants due to thedominant diesel fuel usage by public transportation and heavyvehicles. Hence, the investigation and prediction of the influence and the tendency of these pollutants are ofsignificance to public and the city image. The multi-layerperceptron (MLP) neural network is regarded as a reliable andcost-effective method to achieve such tasks. The works presentedhere involve developing an improved neural network model, whichcombines the principal component analysis (PCA) technique and theradial basis function (RBF) network, and forecasting thepollutant levels and tendencies based in the recorded data. Inthe study, the PCA is firstly used to reduce and orthogonalizethe original input variables (data), these treated variables arethen used as new input vectors in RBF neural network modelestablished for forecasting the pollutant tendencies. Comparingwith the general neural network models, the proposed modelpossesses simpler network architecture, faster training speed,and more satisfactory predicting performance. This improvedmodel is evaluated by using hourly time series of RSP, NO_x and NO₂ concentrations collected at Mong Kok Roadside Gaseous Monitory Station in Hong Kong during the year 2000. By comparing the predicted RSP, NO_x and NO₂ concentrationswith the actual data of these pollutants recorded at the monitorystation, the effectiveness of the proposed model has been proven.Therefore, in authors' opinion, the model presented in the paper is a potential tool in forecasting air quality parameters and hasadvantages over the traditional neural network methods.