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Monitoring Network (monitoring + network)

Distribution by Scientific Domains

Mathematics and Statistics	63%
Life Sciences	10%

Selected Abstracts

Recent trends from Canadian permafrost thermal monitoring network sites

PERMAFROST AND PERIGLACIAL PROCESSES, Issue 1 2005
Sharon L. Smith
Abstract The Geological Survey of Canada (GSC), in collaboration with other government partners, has been developing and maintaining a network of active-layer and permafrost thermal monitoring sites which contribute to the Canadian Permafrost Monitoring Network and the Global Terrestrial Network for Permafrost. Recent results from the thermal monitoring sites maintained by the GSC and other federal government agencies are presented. These results indicate that the response of permafrost temperature to recent climate change and variability varies across the Canadian permafrost region. Warming of shallow permafrost temperatures of between 0.3 and 0.6°C per decade has occurred since the mid- to late 1980s in the central and northern Mackenzie region in response to a general increase in air temperature. No significant warming (less than 0.1°C per decade) of permafrost is observed in the southern Mackenzie valley. Warming of shallow permafrost of between 1.0 and 4.0°C per decade is also observed in the eastern and high Arctic, but this mainly occurred in the late 1990s. These trends in permafrost temperature are consistent with trends in air temperature observed since the 1970s. Local conditions however, influence the response of the permafrost thermal regime to these changes in air temperature. Copyright © 2005 John Wiley & Sons, Ltd. [source]

Testing for trends in the violation frequency of an environmental threshold in rivers

ENVIRONMETRICS, Issue 1 2009
Lieven Clement
Abstract Nutrient pollution in rivers is a common problem. It can provoke algae blooms which are related to increased fish mortality. To restore the water status, the regulator recently has promulgated more restrictive regulations. In Flanders for instance, the government has introduced several manure decrees (MDs) to restrict nutrient pollution. Environmental regulations are commonly expressed in terms of threshold levels. This provides a binary response to the decision maker. To handle such data, we propose the use of marginalised generalised linear mixed models. They provide valid inference on trends in the exceedance frequency. The spatio-temporal dependence of the river monitoring network is incorporated by the use of a latent variable. The temporal dependence is assumed to be AR(1) and the spatial dependence is derived from the river topology. The mean model contains a term for the trend and corrects for seasonal variation. The model formulation allows an assessment on the level of individual sampling locations and on a more regional scale. The methodology is applied to a case study on the river Yzer (Flanders). It assesses the impact of the MDs on the violation probability of the nitrate standard. A trend change is detected after the introduction of the second MD. Copyright © 2008 John Wiley & Sons, Ltd. [source]

Network bias in air quality monitoring design

ENVIRONMETRICS, Issue 7 2008
Nicola Loperfido
Abstract We develop a statistical model for the bias resulting from designing an air quality monitoring network with the aim of finding large values, and then using the data obtained in studies of health effects of air quality. Appropriate conditional distributions are shown to be well-known generalizations of the normal one. Theoretical results are applied to an ozone monitoring network in the state of Washington, USA. Copyright © 2008 John Wiley & Sons, Ltd. [source]

Analysis of air quality monitoring networks by functional clustering

ENVIRONMETRICS, Issue 7 2008
R. Ignaccolo
Abstract Air quality monitoring networks are important tools in management and evaluation of air quality. Classifying monitoring stations via homogeneous clusters allows e dentification of similarities in pollution, of representative sites, and of spatial patterns. Instead of summaries by statistical indicators, we propose to consider the air pollutant concentrations as functional data. We then classify using functional cluster analysis, where Partitioning Around Medoids (PAM) algorithm is embedded. The proposed data analysis approach is applied to the air quality monitoring network in Piemonte (Northern Italy); we consider the three more critical pollutants: NO2, PM10, and O3. Copyright © 2008 John Wiley & Sons, Ltd. [source]

Estimating the number of ozone peaks in Mexico City using a non-homogeneous Poisson model

ENVIRONMETRICS, Issue 5 2008
Jorge A. Achcar
Abstract In this paper, we consider the problem of estimating the number of times an air quality standard is exceeded in a given period of time. A non-homogeneous Poisson model is proposed to analyse this issue. The rate at which the Poisson events occur is given by a rate function ,(t), t,,,0. This rate function also depends on some parameters that need to be estimated. Two forms of ,(t), t,,,0 are considered. One of them is of the Weibull form and the other is of the exponentiated-Weibull form. The parameters estimation is made using a Bayesian formulation based on the Gibbs sampling algorithm. The assignation of the prior distributions for the parameters is made in two stages. In the first stage, non-informative prior distributions are considered. Using the information provided by the first stage, more informative prior distributions are used in the second one. The theoretical development is applied to data provided by the monitoring network of Mexico City. The rate function that best fit the data varies according to the region of the city and/or threshold that is considered. In some cases the best fit is the Weibull form and in other cases the best option is the exponentiated-Weibull. Copyright © 2007 John Wiley & Sons, Ltd. [source]

Comparing and contrasting some environmental and experimental design problems,

ENVIRONMETRICS, Issue 4 2001
R. J. Martin
Abstract Designing an unreplicated field trial essentially involves firstly selecting the plots for the check varieties, and secondly arranging the check varieties among these plots. Selecting the check plots appears to be very similar to choosing sites for a monitoring network, or choosing sites in a region at which to take a sample. The problems appear to be even closer if spatial dependence is postulated, when another aim in choosing the sites is to allow efficient estimation of the dependence. In this paper, the designs of monitoring networks and spatial samples, and some related design problems, are considered to see if they have implications for the design of unreplicated field trials. Copyright © 2001 John Wiley & Sons, Ltd. [source]

Effects of urbanization on stream water quality in the city of Atlanta, Georgia, USA,

HYDROLOGICAL PROCESSES, Issue 20 2009
Norman E. Peters
Abstract A long-term stream water quality monitoring network was established in the city of Atlanta, Georgia during 2003 to assess baseline water quality conditions and the effects of urbanization on stream water quality. Routine hydrologically based manual stream sampling, including several concurrent manual point and equal width increment sampling, was conducted ,12 times annually at 21 stations, with drainage areas ranging from 3·7 to 232 km2. Eleven of the stations are real-time (RT) stations having continuous measures of stream stage/discharge, pH, dissolved oxygen, specific conductance, water temperature and turbidity, and automatic samplers for stormwater collection. Samples were analyzed for field parameters, and a broad suite of water quality and sediment-related constituents. Field parameters and concentrations of major ions, metals, nutrient species and coliform bacteria among stations were evaluated and with respect to watershed characteristics and plausible sources from 2003 through September 2007. Most constituent concentrations are much higher than nearby reference streams. Concentrations are statistically different among stations for several constituents, despite high variability both within and among stations. Routine manual sampling, automatic sampling during stormflows and RT water quality monitoring provided sufficient information about urban stream water quality variability to evaluate causes of water quality differences among streams. Fecal coliform bacteria concentrations of most samples exceeded Georgia's water quality standard for any water-usage class. High chloride concentrations occur at three stations and are hypothesized to be associated with discharges of chlorinated combined sewer overflows, drainage of swimming pool(s) and dissolution and transport during rainstorms of CaCl2, a deicing salt applied to roads during winter storms. One stream was affected by dissolution and transport of ammonium alum [NH4Al(SO4)2] from an alum-manufacturing plant; streamwater has low pH (<5), low alkalinity and high metals concentrations. Several trace metals exceed acute and chronic water quality standards and high concentrations are attributed to washoff from impervious surfaces. Published in 2009 by John Wiley & Sons, Ltd. [source]

Extracting bird migration information from C-band Doppler weather radars

IBIS, Issue 4 2008
HANS VAN GASTEREN
Although radar has been used in studies of bird migration for 60 years, there is still no network in Europe for comprehensive monitoring of bird migration. Europe has a dense network of military air surveillance radars but most systems are not directly suitable for reliable bird monitoring. Since the early 1990s, Doppler radars and wind profilers have been introduced in meteorology to measure wind. These wind measurements are known to be contaminated with insect and bird echoes. The aim of the present research is to assess how bird migration information can be deduced from meteorological Doppler radar output. We compare the observations on migrating birds using a dedicated X-band bird radar with those using a C-band Doppler weather radar. The observations were collected in the Netherlands, from 1 March to 22 May 2003. In this period, the bird radar showed that densities of more than one bird per km3 are present in 20% of all measurements. Among these measurements, the weather radar correctly recognized 86% of the cases when birds were present; in 38% of the cases with no birds detected by the bird radar, the weather radar claimed bird presence (false positive). The comparison showed that in this study reliable altitudinal density profiles of birds cannot be obtained from the weather radar. However, when integrated over altitude, weather radar reflectivity is correlated with bird radar density. Moreover, bird flight speeds from both radars show good agreement in 78% of cases, and flight direction in 73% of cases. The usefulness of the existing network of weather radars for deducing information on bird migration offers a great opportunity for a European-wide monitoring network of bird migration. [source]

Real-time forecasting of photosmog episodes: the Naples case study

JOURNAL OF CHEMOMETRICS, Issue 7 2001
A. Riccio
Abstract In this paper we analysed the ozone time series data collected by the local monitoring network in the Naples urban area (southern Italy) during the spring/summer period of 1996. Our aim was to identify a reliable and effective model that could be used for the real-time forecasting of photosmog episodes. We studied the applicability of seasonal autoregressive integrated moving average models with some exogenous variables (ARIMAX) to our case study. The choice of exogenous variables,temperature, [NO2]/[NO] ratio and wind speed,was based on physical reasoning. The forecasting performance of all models was evaluated with data not used in model development, by means of an array of statistical indices: the comparison between observed and forecast means and standard deviations; intercept and slope of a least squares regression of forecast variable on observed variable; mean absolute and root mean square errors; and 95% confidence limits of forecast variable. The assessment of all models was also based on their tendency to forecast critical episodes. It was found that the model using information from the temperature data set to predict peak ozone levels gives satisfactory results, about 70% of critical episodes being correctly predicted by the 24,h ahead forecast function. Copyright © 2001 John Wiley & Sons, Ltd. [source]

Statistical methods for regular monitoring data

JOURNAL OF THE ROYAL STATISTICAL SOCIETY: SERIES B (STATISTICAL METHODOLOGY), Issue 5 2005
Michael L. Stein
Summary., Meteorological and environmental data that are collected at regular time intervals on a fixed monitoring network can be usefully studied combining ideas from multiple time series and spatial statistics, particularly when there are little or no missing data. This work investigates methods for modelling such data and ways of approximating the associated likelihood functions. Models for processes on the sphere crossed with time are emphasized, especially models that are not fully symmetric in space,time. Two approaches to obtaining such models are described. The first is to consider a rotated version of fully symmetric models for which we have explicit expressions for the covariance function. The second is based on a representation of space,time covariance functions that is spectral in just the time domain and is shown to lead to natural partially nonparametric asymmetric models on the sphere crossed with time. Various models are applied to a data set of daily winds at 11 sites in Ireland over 18 years. Spectral and space,time domain diagnostic procedures are used to assess the quality of the fits. The spectral-in-time modelling approach is shown to yield a good fit to many properties of the data and can be applied in a routine fashion relative to finding elaborate parametric models that describe the space,time dependences of the data about as well. [source]

Monitoring terrestrial mammals in the UK: past, present and future, using lessons from the bird world

MAMMAL REVIEW, Issue 1-2 2004
JESSAMY E. BATTERSBY
ABSTRACT 1.,A monitoring network for UK terrestrial mammals, the Tracking Mammals Partnership, is currently being set up to provide a coordinated programme to collect surveillance and monitoring data. 2.,Monitoring UK mammals is important for a number of reasons including: setting conservation priorities; measuring the effects of conservation management; managing populations of problem species and the sustainable use of game species; assessing the effects of agriculture and other human activities; providing evidence for the need for policy change; and because of obligations under intergovernmental treaties and national legislation. 3.,The bird world, largely but not solely through the work carried out by the British Trust for Ornithology, has provided a useful model for mammal surveillance and some important lessons in setting up and running a UK wide multispecies monitoring programme. 4.,Lessons include the importance: of annual monitoring; of long-term data sets of population indices rather than absolute population sizes; and of the use of volunteers in data collection. 5.,Two scoping studies have been carried out to assess the feasibility and costs of setting up a mammal surveillance and monitoring network and the survey methods that could be used for different species. 6.,The Tracking Mammals Partnership, comprising 23 organizations, has the remit of implementing the recommendations of the scoping studies. There are a number of programmes operating within the Partnership including the National Dormouse Monitoring Programme, the National Bat Monitoring Programme and the Breeding Bird Survey Mammal Monitoring. There are also a number of pilot schemes being tested. 7.,Reports on the population trend data collected should enable more informed policy and management decisions concerning UK mammal species. [source]

Permafrost thermal state in the polar Northern Hemisphere during the international polar year 2007,2009: a synthesis

PERMAFROST AND PERIGLACIAL PROCESSES, Issue 2 2010
Vladimir E. Romanovsky
Abstract The permafrost monitoring network in the polar regions of the Northern Hemisphere was enhanced during the International Polar Year (IPY), and new information on permafrost thermal state was collected for regions where there was little available. This augmented monitoring network is an important legacy of the IPY, as is the updated baseline of current permafrost conditions against which future changes may be measured. Within the Northern Hemisphere polar region, ground temperatures are currently being measured in about 575 boreholes in North America, the Nordic region and Russia. These show that in the discontinuous permafrost zone, permafrost temperatures fall within a narrow range, with the mean annual ground temperature (MAGT) at most sites being higher than ,2°C. A greater range in MAGT is present within the continuous permafrost zone, from above ,1°C at some locations to as low as ,15°C. The latest results indicate that the permafrost warming which started two to three decades ago has generally continued into the IPY period. Warming rates are much smaller for permafrost already at temperatures close to 0°C compared with colder permafrost, especially for ice-rich permafrost where latent heat effects dominate the ground thermal regime. Colder permafrost sites are warming more rapidly. This improved knowledge about the permafrost thermal state and its dynamics is important for multidisciplinary polar research, but also for many of the 4 million people living in the Arctic. In particular, this knowledge is required for designing effective adaptation strategies for the local communities under warmer climatic conditions. Copyright © 2010 John Wiley & Sons, Ltd. [source]

Development of a new wind-rose for the British Isles using radiosonde data, and application to an atmospheric transport model

THE QUARTERLY JOURNAL OF THE ROYAL METEOROLOGICAL SOCIETY, Issue 621 2006
A. J. Dore
Abstract A six-hourly dataset of radiosonde ascents spanning a ten-year period from four stations in the British Isles has been used to generate a set of wind frequency roses and wind speed roses for the pressure level range 950,900 hPa. The wind frequency rose showed close agreement with the long-term series of the Jenkinson classification scheme. Small but significant inter-station and interannual variations were observed. Seasonal analysis of the data revealed the higher incidence of north-easterlies during spring months whilst the stronger wind speeds associated with the winter months were also evident. The use of a harmonic mean was found to be appropriate for calculating a directionally dependent wind speed for use in an atmospheric transport model. A harmonic mean wind speed value of 7.5 m s,1 was generated from the entire dataset, the same as that which has previously been used in other transport models. This is also the same value as the ,optimized wind speed' that was generated by Singles et al. The radiosonde wind frequency rose and wind speed rose were input to the FRAME atmospheric transport model. This resulted in an improved correlation with measurements of SO2 concentrations from a national monitoring network when compared to a model simulation using the earlier dataset of Jones. Copyright © 2006 Royal Meteorological Society [source]

Analysis of air quality monitoring networks by functional clustering

A dynamic process convolution approach to modeling ambient particulate matter concentrations

ENVIRONMETRICS, Issue 1 2008
Catherine A. Calder
Abstract Elevated levels of particulate matter (PM) in the ambient air have been shown to be associated with certain adverse human health effects. As a result, monitoring networks that track PM levels have been established across the United States. Some of the older monitors measure PM less than 10 µm in diameter (PM10), while the newer monitors track PM levels less than 2.5 µm in diameter (PM2.5); it is now believed that this fine component of PM is more likely to be related to the negative health effects associated with PM. We propose a bivariate dynamic process convolution model for PM2.5 and PM10 concentrations. Our aim is to extract information about PM2.5 from PM10 monitor readings using a latent variable approach and to provide better space-time interpolations of PM2.5 concentrations compared to interpolations made using only PM2.5 monitoring information. We illustrate the approach using PM2.5 and PM10 readings taken across the state of Ohio in 2000. Copyright © 2007 John Wiley & Sons, Ltd. [source]

Using spatial models and kriging techniques to optimize long-term ground-water monitoring networks: a case study

ENVIRONMETRICS, Issue 5-6 2002
Kirk Cameron
Abstract In a pilot project, a spatial and temporal algorithm (geostatistical temporal,spatial or GTS) was developed for optimizing long-term monitoring (LTM) networks. Data from two monitored ground-water plumes were used to test the algorithm. The primary objective was to determine the degree to which sampling, laboratory analysis, and/or well construction resources could be pared without losing key statistical information concerning the plumes. Optimization of an LTM network requires an accurate assessment of both ground-water quality over time and trends or other changes in individual monitoring wells. Changes in interpolated concentration maps over time indicate whether ground-water quality has improved or declined. GTS separately identifies temporal and spatial redundancies. Temporal redundancy may be reduced by lengthening the time between sample collection. Spatial redundancy may be reduced by removing wells from the network which do not significantly impact assessment of ground-water quality. Part of the temporal algorithm in GTS involves computation of a composite temporal variogram to determine the least redundant overall sampling interval. Under this measure of autocorrelation between sampling events, the lag time at which the variogram reaches a sill is the sampling interval at which same-well measurements lack correlation and are therefore non-redundant. The spatial algorithm assumes that well locations are redundant if nearby wells offer nearly the same statistical information about the underlying plume. A well was considered redundant if its removal did not significantly change: (i) an interpolated map of the plume; (ii) the local kriging variances in that section of the plume; and (iii) the average global kriging variance. To identify well redundancy, local kriging weights were accumulated into global weights and used to gauge each well's relative contribution to the interpolated plume map. By temporarily removing that subset of wells with the lowest global kriging weights and re-mapping the plume, it was possible to determine how many wells could be removed without losing critical information. Test results from the Massachusetts Military Reserve (MMR) indicated that substantial savings in sampling, analysis and operational costs could be realized by utilizing GTS. Annual budgetary savings that would accrue were estimated at between 35 per cent and 5 per cent for both LTM networks under study.Copyright © 2002 John Wiley & Sons, Ltd. [source]

Comparing and contrasting some environmental and experimental design problems,

Hierarchical Models in Environmental Science

INTERNATIONAL STATISTICAL REVIEW, Issue 2 2003
Christopher K. Wikle
Summary Environmental systems are complicated. They include very intricate spatio-temporal processes, interacting on a wide variety of scales. There is increasingly vast amounts of data for such processes from geographical information systems, remote sensing platforms, monitoring networks, and computer models. In addition, often there is a great variety of scientific knowledge available for such systems, from partial differential equations based on first principles to panel surveys. It is argued that it is not generally adequate to consider such processes from a joint perspective. Instead, the processes often must be considered as a coherently linked system of conditional models. This paper provides a brief overview of hierarchical approaches applied to environmental processes. The key elements of such models can be considered in three general stages, the data stage, process stage, and parameter stage. In each stage, complicated dependence structure is mitigated by conditioning. For example, the data stage can incorporate measurement errors as well as multiple datasets with varying supports. The process and parameter stages can allow spatial and spatio-temporal processes as well as the direct inclusion of scientific knowledge. The paper concludes with a discussion of some outstanding problems in hierarchical modelling of environmental systems, including the need for new collaboration approaches. Résumé Les systèmes environnementaux sont complexes. Ils incluent des processus spatio-temporels trés complexes, interagissant sur une large variété d'échelles. II existe des quantités de plus en plus grandes de données sur de tels processus, provenant des systèmes d'information géographiques, des plateformes de télédétection, des réseaux de surveillance et des modèles informatiques. De plus, il y a souvent une grande variété de connaissance scientifique disponible sur de tels systémes, depuis les équations différentielles partielles jusqu'aux enquétes de panels. II est reconnu qu'il n'est généralement pas correct de considerer de tels processus d'une perspective commune. Au contraire, les processus doivent souvent étre examinés comme des systèmes de modèles conditionnels liés de manière cohérente. Cet article fournit un bref aperçu des approches hiérachiques appliquées aux processus environnementaux. Les éléments clés de tels modèles peuvent étre examinés à trois étapes principales: l'étape des donnèes, celle du traitement et celle des paramètres. A chaque étape, la structure complexe de dépendance est atténuée par le conditionnement. Par exemple, le stade des données peut incorporer des erreurs de mesure ainsi que de multiples ensembles de données sous divers supports. Les stades du traitement et des paramétres peuvent admettre des processus spatiaux et spatio-temporels ainsi que l'inclusion directe du savoir scientifique. L'article conclut par une discussion de quelques problèmes en suspens dans la modélisation hiérarchique des systèmes environnementaux, incluant le besoin de nouvelles approches de collaboration. [source]