High frequency monitoring of the coastal marine environment using the MAREL buoy

The MAREL Iroise data buoy provides physico-chemical measurements acquired in surface marine water in continuous and autonomous mode. The water is pumped 1.5 m from below the surface through a sampling pipe and flows through the measuring cell located in the floating structure. Technological innovations implemented inside the measuring cell atop the buoy allow a continuous cleaning of the sensor, while injection of chloride ions into the circuit prevents biological fouling. Specific sensors for temperature, salinity, oxygen and fluorescence investigated in this paper have been evaluated to guarantee measurement precision over a 3 month period. A bi-directional link under Internet TCP-IP protocols is used for data, alarms and remote-control transmissions with the land-based data centre. Herein, we present a 29 month record for 4 parameters measured using a MAREL buoy moored in a coastal environment (Iroise Sea, Brest, France). The accuracy of the data provided by the buoy is assessed by comparison with measurements of sea water weekly sampled at the same site as part of SOMLIT (Service d'Observation du Milieu LIToral), the French network for monitoring of the coastal environment. Some particular events (impact of intensive fresh water discharges, dynamics of a fast phytoplankton bloom) are also presented, demonstrating the worth of monitoring a highly variable environment with a high frequency continuous reliable system.     

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.     

Sharing the geo-Referenced Results of Climate Change Impact Research

The Prairie Adaptation Research Collaborative (PARC) has implemented an Internet Map Server (IMS) at the PARC web site (www.parc.ca) to 1) disseminate the geo-referenced results of PARC sponsored research on climate change impacts and adaptation, and 2) address data, information and knowledge management within the PARC network of researchers and partners. PARC facilitates interdisciplinary research on adaptation to the impacts of climate change in the Canadian Prairie Provinces. The web site is intended as a platform for sharing information and encouraging discussion of climate change impacts and adaptation. The IMS enables scientists and stakeholders to apply simple climate change scenarios to geo-referenced biophysical and social data, and dynamically create maps that display the geographic distribution of potential impacts of climate change. With a limited capacity for spatial analysis, most geo-processing and the climate impact modeling is done offline within a GIS environment. The IMS will serve the output from climate impact models, such that the model results can be customized by the web site user and be most readily applied to the planning and analysis of adaptation strategies.     

Linking Land Cover and Water Quality in New York City’S Water Supply Watersheds

The Catskill/Delaware reservoirs supply 90% of New York City’s drinking water. The City has implemented a series of watershed protection measures, including land acquisition, aimed at preserving water quality in the Catskill/Delaware watersheds. The objective of this study was to examine how relationships between landscape and surface water measurements change between years. Thirty-two drainage areas delineated from surface water sample points (total nitrogen, total phosphorus, and fecal coliform bacteria concentrations) were used in step-wise regression analyses to test landscape and surface-water quality relationships. Two measurements of land use, percent agriculture and percent urban development, were positively related to water quality and consistently present in all regression models. Together these two land uses explained 25 to 75% of the regression model variation. However, the contribution of agriculture to water quality condition showed a decreasing trend with time as overall agricultural land cover decreased. Results from this study demonstrate that relationships between land cover and surface water concentrations of total nitrogen, total phosphorus, and fecal coliform bacteria counts over a large area can be evaluated using a relatively simple geographic information system method. Land managers may find this method useful for targeting resources in relation to a particular water quality concern, focusing best management efforts, and maximizing benefits to water quality with minimal costs.The United States Environmental Protection Agency through its Office of Research and Development funded and managed the research described here. It has been subjected to Agency’s administrative review and approved for publication as an EPA document.     

A Spatial Model to Estimate Habitat Fragmentation and Its Consequences on Long-Term Persistence of Animal Populations

The increasing use of the landscape by humans has led to important diminutions of natural surfaces. The remaining patches of wild habitat are small and isolated from each other among a matrix of inhospitable land-uses. This habitat fragmentation, by disabling population movements and stopping their spread to new habitats, is a major threat to the survival of numerous plant and animal species. We developed a general model, adaptable for specific species, capable of identifying suitable habitat patches within fragmented landscapes and investigating the capacity of populations to move between these patches. This approach combines GIS analysis of a landscape, with spatial dynamic modeling. Suitable habitat is identified using a threshold area to perimeter ratio. Potential movement pathways of species between habitat patches are modeled using a cellular automaton. Habitat connectivity is estimated by overlaying habitat patches with movement pathways. The maximum potential population is calculated within and between connected habitat patches and potential risk of inbreeding within meta-populations is considered. The model was tested on a sample map and applied to scenario maps of predicted land-use change in the Peoria Tri-county region (IL). It (1) showed area of natural area alone was insufficient to estimate the consequences on animal populations; (2) underscored the necessity to use approaches investigating the effect of land-use change spatially through the landscape and the importance of considering species-specific life history characteristics; and (3) highlighted the model's potential utility as an indicator of species likelihood to be affected negatively by land-use scenarios and therefore requiring detailed investigation.     

Formation and Emission of N2O and CH4 from Compost Heaps of Organic Household Waster

Composting can be a source of N₂O andCH₄ production. In this investigation, differentcompost heaps of organic household waste weremonitored with the focus on potential formation ofCH₄ and N₂O in the heaps and emission ofthese gases from the heaps. The studied compost heapshad different compost ages, turning intervals andcompost sizes. The analysed compost gases containedbetween 1–3421 L of N₂O-N L^-1 and 0–470 mL of CH₄ L^-1. The emission rates ofN₂O and CH₄ from the compost heaps werebetween 1–1464 mg N₂O m^-2 day^-1 and0–119 000 mg CH₄ m^-2 day^-1. These verylarge differences in compost gas composition andemission indicate the importance of compostmanagement. The results also give an understanding ofwhere in the composting process an increasing emissionof N₂O and CH₄ can occur.     

Assessing the Effects of Atmospheric Ethylene on Epinasty and Tuber Yield of Potato (Solanum Tuberosum L.) Near Polyethylene Manufacturing Plants

A multi-year programme was performed to assess the effects of atmospheric ethylene on potato (Solanum tuberosum L.) in the vicinity of polyethylene manufacturing plants. There was a strong temporal variation of the hourly ethylene concentrations measured close to the sources from 1982 through 1991. Growing seasonal means exceeded 12 g m^–3 ethylene, the threshold for phytotoxic effects under laboratory conditions. Young test plants of potato showed an epinastic response to enhanced levels of ethylene. This response was reversible and did not occur when atmospheric ethylene was not detected. Based on hourly observations for the growing seasons of 1984 through 1991, epinasty occurred on average during circa 5% of the growing season and varied from circa 1% in 1985 to circa 18% in 1991. At night, ethylene concentrations were higher and epinasty was more frequent than during daylight hours. The intermittent exposures to ethylene did not affect tuber yield for the growing seasons of 1982 through 1990. The occurrence of epinasty indicated that ethylene exposure levels in the vicinity of the industrial sources might be sufficiently high to affect sensitive plants.     

Accumulation of metals in the soil of an overland flow wastewater treatment system

Accumulation of Co, Cu, Cr, Mo, Ni, Pb and Zn was evaluated in a soil profile of an overland flow system used for the post-treatment of urban wastewater. A pilot version of the overland flow system received urban wastewater from five up-flow anaerobic filters filled with bamboo (Bambusa tuldoides) rings. The anaerobic effluent was applied as feed over 18 months at rates varying from 7 to 28 L min(-1), to a vegetated slope length covered with Tifton 85 (Cynodon) sp. grass. Soil and plant samples were collected in triplicate from the top to the bottom of the slope. In addition, the soils were sampled at the depths 0-20 and 20-40 cm. The metal concentrations found in the overall system were compared to those obtained in a control area located at the beginning of the slope onto which nothing was applied. A month of monitoring the urban wastewater of Limeira City (S?o Paulo State, Brazil) showed a drastic change in metals concentration due to the irregular discharge of industrial waste. This irregular discharge introduces Cr, Cu, Ni, Pb and Zn into the system used to treat domestic wastewater. The mass balance indicates the accumulation of metals in the soil and the translocation to the plants; also that they could be evapotranspirated, percolated and discharged.     

Application of intrawell testing of RCRA groundwater monitoring data when no upgradient well exists

A statistical quality control approachto detect changes in groundwater quality from aregulated waste unit is described. The approachapplies the combined Shewhart-CUSUM control chartmethodology for intrawell comparison of analyteconcentrations over time and does not require anupgradient well. A case study from the U.S.Department of Energy's Hanford Site is used forillustration purposes. This method is broadlyapplicable in groundwater monitoring programs wherethere is no clearly defined upgradient location, thegroundwater flow rate is exceptionally slow, or wherea high degree of spatial variability exists inparameter concentrations. This study also indicatesthat the use of the Data Quality Objectives (DQO)process can assist in designing an efficient andcost-effective groundwater monitoring plan to achievethe optimum goal of both low false positive and lowfalse negative rates (high power).