Analysis Of Long-term Monitoring Data Research Articles

Proposals of guidance values for surface contamination by antineoplastic drugs based on long term monitoring in Czech and Slovak hospitals and pharmacies.

The exposures to hazardous antineoplastic drugs (AD) represent serious risks for health care personnel but the exposure limits are not commonly established because of the no-threshold effects (genotoxic action, carcinogenicity) of many ADs. In this study, we discussed and derived practically applicable technical guidance values (TGV) suitable for management of AD risks. The long-term monitoring of surface contamination by eight ADs was performed in pharmacies and hospitals in the Czech Republic and Slovak Republic in 2008-2021; in total 2,223 unique samples were collected repeatedly in 48 facilities. AD contamination was studied by LC-MS/MS for cyclophosphamide, ifosfamide, methotrexate, irinotecan, paclitaxel, 5-fluorouracil and gemcitabine and by ICP-MS for total Pt as a marker of platinum-based ADs. The study highlighted importance of exposure biomarkers like 5-fluorouracil and especially carcinogenic and persistent cyclophosphamide, which should be by default included in monitoring along with other ADs. Highly contaminated spots like interiors of laminar biological safety cabinets represent a specific issue, where monitoring of contamination does not bring much added value, and prevention of staff and separated cleaning procedures should be priority. Rooms and surfaces in health care facilities that should be virtually free of ADs (e.g., offices, kitchenettes, daily rooms) were contaminated with lower frequency and concentrations but any contamination in these areas should be carefully examined. For all other working places, i.e., majority of areas in pharmacies and hospitals, where ADs are being prepared, packaged, stored, transported, or administered to patients, the study proposes a generic TGV of 100 pg/cm2. The analysis of long-term monitoring data of multiple ADs showed that the exceedance of one TGV can serve as an indicator and trigger for improvement of working practices contributing thus to minimizing of unintended exposures and creating a safe work environment.

Leading Factors of the Dynamics of Lake Ecosystems under a Changing Nutrient Load: Analysis of Long-Term Monitoring Data of Naroch Lakes

Leading Factors of the Dynamics of Lake Ecosystems under a Changing Nutrient Load: Analysis of Long-Term Monitoring Data of Naroch Lakes

Intelligent analysis of subbase strain based on a long-term comprehensive monitoring

The irreversible development of road subbase strain under long-term loading may result in emergency in the foundation of transportation infrastructure systems, and thus the corresponding analysis is of great importance to the safe of society and economy. To improve the resilience of transportation infrastructure systems, the analysis of subbase strain, aiming for an accurate and reliable prediction, is of necessity for transportation engineers. Traditional methods mainly include mathematical and statistical regression analysis solely based on the monitoring stress/strain data. To analyze the monitoring data more comprehensively and more accurately, we conducted an intelligent analysis of subbase strain based on a long-term monitoring and deep learning approaches, which comprehensively considers the environment conditions (temperature, water content, pressure, etc.), the mechanical responses of other structural layers, etc. The comprehensive monitoring system was installed on the section from Nancun to Shiyingmen of 108 National Highway in Beijing in 2012, including asphalt strain sensors, embedded three-dimensional strain sensors, temperature sensors, osmotic pressure sensors, and others. In this study, the long-term road monitoring data of the eight years from 2012 to 2020 was used for analysis. The traditional Random Forest (RF) method and three kinds of deep learning models, including Long-Short Term Memory neural network (LSTM) model, Bidirectional LSTM-Convolution Neural Network (BiLSTM-CNN) model and Temporal Convolution Network (TCN) model, were employed to analyze the development of subbase strain. Test results showed that deep learning methods for the analysis of long-term monitoring data is better than that uses the traditional machine learning algorithm, in which the prediction accuracy of RF is 70.15%, the prediction accuracy of LSTM method is 76.94%, the prediction accuracy of TCN is 90.46%, and the predication accuracy of BiLSTM-CNN is 94.57%. Finally, sensitivity analysis of the TCN model has been performed to examine the impact of timesteps on evaluation metrics. The study could serve reference to predict the development of subbase strain in engineering projects.

Factors that most determine the dynamics of lake ecosystems under changing nutrient load: analysis of long-term monitoring data of Naroch lakes

Factors that most determine the dynamics of lake ecosystems under changing nutrient load: analysis of long-term monitoring data of Naroch lakes

Forecasting a 2-methylisoborneol outbreak in a brackish lake.

2-Methylisoborneol (2-MIB) is the primary cause of the earthy and musty odor produced by cyanobacteria, which deteriorates the quality of fishery products and tap water. Despite the need for controlling outbreaks, few studies have been conducted on 2-MIB in brackish lakes, where capture fisheries are active. This study examined the association between water quality and the outbreak of 2-MIB in a brackish lake using statistical analysis of long-term monitoring data and developed forecasting models for 2-MIB outbreaks. We investigated Lake Ogawara, which is a brackish lake with a cool-temperate climate in Japan, where 2-MIB outbreaks frequently occur between August and December. Logistic regression analyses were performed using the outbreak or non-outbreak of 2-MIB (2-MIB(+ / -)) as the dependent variable and water quality parameters as the independent variables. The results suggested that the density of 2-MIB-producing cyanobacteria was higher when (1) dissolved inorganic nitrogen concentrations were low under the relaxation of phosphorus limitation and/or (2) salinity or micronutrient concentrations were high. In addition, we successfully developed forecasting models with a high predictive power that determined 2-MIB(+ / -) in August-December using only two water quality parameters: dissolved inorganic phosphate and pH in April and total nitrogen/total phosphorous and salinity in May.

Seasonal Variations in Specific Resistivity in the Upper Layers of the Earth Crust

To predict the effects of strong earthquakes, it is important to know the soil characteristics. The accepted methods for such assessment ignore the fact that soils properties can vary greatly throughout the year. This is apparently due to the lack of data required for such consideration. In this paper, based on an analysis of long-term monitoring data by vertical electric sounding (VES) in a stationary array with a large number of spacing, we analyze seasonal variations in specific resistivity at different near-surface depths of a section in the area of the Peter the Great Range in Tajikistan. Based on long-term precision daily measurement data, a horizontally four-layered model of the geoelectric section was constructed. The amplitude of seasonal variations in the specific resistivity in each layer was estimated as the ratio of the standard deviation of the seasonal variation to the mean interannual specific resistivity. In the upper part of the section (depth 0–1.5 m), the amplitude of the seasonal variation reaches 20%, and its shape agrees well with the seasonal variation of the apparent resistivity at small spacings. In the second (depth 1.5–10 m) and third (depth 10–66 m) layers, the amplitude of the seasonal wave decreases rapidly, being less than 1% in the third layer. In the fourth layer (depth from 66 m or more), this amplitude again increases, reaching 2%. The difference between the maximum and minimum values of the seasonal wave (i.e., its range) reaches 7%. One possible explanation for such a high amplitude of seasonal variations in specific resistivity at depths of hundreds of meters is the presence of a deep aeration zone with annual regulation of the level and salinity of groundwater. The results should be taken into account in exploration geophysics, in engineering surveys, and in accounting for soil properties when predicting the possible consequences of strong seismic impacts.

Thermal comfort condition assessment in test buildings with different heating/cooling systems and wall envelopes

The main aim of this study is a comprehensive analysis of long-term monitoring data of thermal comfort and discomfort parameters in small identical test buildings equipped with different heating/cooling systems. Calculations of PPD index expressed the human perception of thermal comfort and such discomfort factors like draught rate and vertical air temperature difference are provided for the room in winter season running three different heating systems – electric heater, air-air heat pump and air-water heat pump, as well as for the summer cooling with split type air conditioning systems. It is shown that the type of heating/cooling system and its working regime has a significant impact on thermal comfort conditions in the room. Recommendations for the optimal operating regimes and choice of the heating system from the thermal comfort point of view are provided.

Assessment of a monumental masonry bell-tower after 2016 Central Italy seismic sequence by long-term SHM

The response of the San Pietro monumental bell-tower located in Perugia, Italy, to the 2016 Central Italy seismic sequence is investigated, taking advantage of the availability of field data recorded by a vibration-based SHM system installed in December 2014 to detect earthquake-induced damages. The tower is located about 85 km in the NW direction from the epicenter of the first major shock of the sequence, the Accumoli Mw6.0 earthquake of August 24th, resulting in a small local PGA of about 30 cm/s2, whereby near-field PGA was measured as 915.97 cm/s2 (E–W component) and 445.59 cm/s2 (N–S component). Similar PGA values also characterized the two other major shocks of the sequence (Ussita Mw5.9 and Norcia Mw6.5 earthquakes of October 26th and 30th, respectively). Despite the relatively low intensity of such earthquakes in Perugia, the analysis of long-term monitoring data clearly highlights that small permanent changes in the structural behavior of the bell-tower have occurred after the earthquakes, with decreases in all identified natural frequencies. Such natural frequency decays are fully consistent with what predicted by non-linear finite element simulations and, in particular, with the development of microcracks at the base of the columns of the belfry. Microcracks in these regions, and in the rest of tower, are however hardly distinguishable from pre-existing ones and from the physiological cracking of a masonry structure, what validates the effectiveness of the SHM system in detecting earthquake-induced damage at a stage where this is not yet detectable by visual inspections.

Analysis of long-term monitoring data of PV module with SiOx-based anti-reflective patterned protective glass

The PV modules are inevitably installed outdoors and receive direct sunlight. Therefore, protective glass or film is required to protect the surface of the PV module from the wind, rain, snow and dust, and other environments. However, the incident light is reflected from the surfaces of these protective layers, resulting in a considerable efficiency loss. In this study, we developed a moth-eye structure with HSQ using a direct-transfer printing process to fabricate anti-reflective coatings on the protective glass. In addition, we also conducted long-term field tests to monitor and measure the impact of the fabricated anti-reflective structures and durability against environmental factors. The transmittance of the glass substrate increased to 95.0% as a result of the fabricated SiOx-based moth-eye patterns. In addition, the PV module with the moth-eye-patterned protective glass generated 7.88% more electricity compared to that without the moth-eye-patterned glass during 1-year field test.

Experimental Research of Thermal Comfort Conditions in Small Test Buildings with Different Types of Heating

The aim of this study is detailed analysis of long-term monitoring data of thermal comfort conditions and energy efficiency in small test buildings equipped with different heating systems. Calculations of PPD index and local thermal discomfort factors are provided for the test buildings during three weeks of heating season. It is shown that the type of heating system has influence not only on heating energy need, but also on thermal comfort conditions in the room.

Sete Cidades and Furnas lake eutrophication (São Miguel, Azores): Analysis of long-term monitoring data and remediation measures

Eutrophication of lakes in the Azores archipelago (Portugal) has been described since the 80s, and due to water quality deterioration several remediation methodologies were applied. Long-term monitoring data on water quality from Sete Cidades and Furnas lakes (São Miguel island) were analyzed in order to address that the success of the ongoing policy reverses their eutrophic status. Sete Cidades lake (4.46km2), made by two branches (so-called Green and Blue lakes), has a water volume equal to 58×106m3 and a depth in the range between 24 and 28.5m. Furnas lake (1.87km2) has a volume equal to 14×106m3 and a maximum depth of 15m.In Sete Cidades lake mean water temperature and pH range respectively between 13.4°C to 17.7°C and 7.04 to 8.06. Instead, mean temperature in Lake Furnas ranges between 16.6°C and 17.2°C, with a pH between 7.36 and 7.84. Mean water conductivity shows that both lakes correspond to very diluted waters, with values between 98.1 and 136.5μS/cm. Water chemistry is influenced by the monomictic character of the lakes, as anoxic environment in the hypolimnion due to O2 consumption during the summer, when stratification prevents mixing along the water column, explains sharp increase in TP, TN, N-ammoniacal, Mn and Fe.Major-ion content is rather constant along time, with some seasonal fluctuations, despite a decrease in SO4 observed in Sete Cidades lake which is suggested to be a result of runoff diversion, a result also shown by the decrease of the molal ratio TN/TP in both studied lakes. Nevertheless, the application of the trophic state index (TSITP) does not suggest an improvement in what concerns trophic status, which is explained by the internal P-loading, a source that have to be managed by environmental authorities in the near future in order to revert eutrophication.

Statistical analysis of long-term monitoring data for persistent organic pollutants in the atmosphere at 20 monitoring stations broadly indicates declining concentrations.

During recent decades concentrations of persistent organic pollutants (POPs) in the atmosphere have been monitored at multiple stations worldwide. We used three statistical methods to analyze a total of 748 time series of selected POPs in the atmosphere to determine if there are statistically significant reductions in levels of POPs that have had control actions enacted to restrict or eliminate manufacture, use and emissions. Significant decreasing trends were identified in 560 (75%) of the 748 time series collected from the Arctic, North America, and Europe, indicating that the atmospheric concentrations of these POPs are generally decreasing, consistent with the overall effectiveness of emission control actions. Statistically significant trends in synthetic time series could be reliably identified with the improved Mann-Kendall (iMK) test and the digital filtration (DF) technique in time series longer than 5 years. The temporal trends of new (or emerging) POPs in the atmosphere are often unclear because time series are too short. A statistical detrending method based on the iMK test was not able to identify abrupt changes in the rates of decline of atmospheric POP concentrations encoded into synthetic time series.

New approach to trophic state assessement of running waters in Poland

The problem of eutrophication has, since the 1970s, reached a global scale and become a problem of princi- pal importance due to its negative consequences, which could result in the total loss of biospheric functions of aquatic ecosystems, and also their economic role. The increasing intensity of eutrophication processes and their specificity in various types of waters requires the development of special methods of control and protection of aquatic ecosystems. As a result of the high dynamism of eutrophication and its dependence on different factors (hydrological, hydrody- namic, hydrobiological, morphological, edaphic and climatic conditions), the assessment of trophic status in order to control and manage this process is very complicated. The evaluation of the consequences of anthropogenic eu- trophication and the scale of its development can be provided only on the basis of systematic observation during a multi-annual period. Careful analysis of the state of knowledge on the issues related to eutrophication, especially the methods of trophic status assessment, have allowed us to conclude that at present there is no universal methodology for the assessment of the surface water trophic level, while the existing methods have various shortcomings, which reduce the reliability of the results and complicate the development of appropriate technical, organizational and legal protection measures. A critical analysis of trophic status assessment approaches for different categories of waters has also allowed us to state that there is no an appropriate method for the assessment of the trophic status of running waters, since almost all existing assessment methods are developed for lakes and coastal areas. This paper presents an original approach elaborated for the assessment of the trophic state of running waters based on the statistical analysis of long-term monitoring data and numerical criterion ITS, which allows for a simple and low-cost monitoring of eutrophication suitable for the solving of different application tasks in the field of surface water protection.

Improved Analysis of Long-Term Monitoring Data Demonstrates Marked Regional Declines of Bat Populations in the Eastern United States

Bats are diverse and ecologically important, but are also subject to a suite of severe threats. Evidence for localized bat mortality from these threats is well-documented in some cases, but long-term changes in regional populations of bats remain poorly understood. Bat hibernation surveys provide an opportunity to improve understanding, but analysis is complicated by bats' cryptic nature, non-conformity of count data to assumptions of traditional statistical methods, and observation heterogeneities such as variation in survey timing. We used generalized additive mixed models (GAMMs) to account for these complicating factors and to evaluate long-term, regional population trajectories of bats. We focused on four hibernating bat species – little brown myotis (Myotis lucifugus), tri-colored bat (Perimyotis subflavus), Indiana myotis (M. sodalis), and northern myotis (M. septentrionalis) – in a four-state region of the eastern United States during 1999–2011.Our results, from counts of nearly 1.2 million bats, suggest that cumulative declines in regional relative abundance by 2011 from peak levels were 71% (with 95% confidence interval of ±11%) in M. lucifugus, 34% (±38%) in P. subflavus, 30% (±26%) in M. sodalis, and 31% (±18%) in M. septentrionalis. The M. lucifugus population fluctuated until 2004 before persistently declining, and the populations of the other three species declined persistently throughout the study period. Population trajectories suggest declines likely resulted from the combined effect of multiple threats, and indicate a need for enhanced conservation efforts. They provide strong support for a change in the IUCN Red List conservation status in M. lucifugus from Least Concern to Endangered within the study area, and are suggestive of a need to change the conservation status of the other species. Our modeling approach provided estimates of uncertainty, accommodated non-linearities, and controlled for observation heterogeneities, and thus has wide applicability for evaluating population trajectories in other wildlife species.

Hypoxia‐induced shifts in nitrogen and phosphorus cycling in Chesapeake Bay

We investigated interactions between hypoxia and nutrient cycling in Chesapeake Bay using quantitative analysis of long‐term monitoring data covering the periods 1965‐1980 and 1985‐2007. The data included vertical water column profiles of temperature, salinity, NH+4, PO3‐4, and O2, as well as rates of total nitrogen (TN) and total phosphorus (TP) loading to the bay from the Susquehanna River. We investigated the hypothesis that a doubling of the volume of hypoxic (O2 < 62.5 µmol L−1) water generated per unit TN load in the past 25 yr is related to enhanced water‐column and sediment recycling of NH+4 and PO3‐4 under low O2, and that this increased nutrient recycling creates a feedback that further generates hypoxia. We found that bottom water in the upper bay region, where seasonal hypoxia first develops, was enriched in NH+4 and PO3‐4 relative to other regions. Evidence of the positive feedback effect of low O2 on nutrient recycling was found in the fact that bottom‐water pools of NH+4 and PO3‐;4 per unit TN and TP loading, respectively, were significantly and positively related to hypoxic volume in upper bay regions during June. Similarly, NH+4 pools generated per unit TN load were significantly higher during 1985‐2007, when hypoxic volume had been approximately doubled, relative to 1965‐1980. This positive feedback effect on nutrient recycling may help to explain the persistence of extensive hypoxia in June, even during years of reduced N loading.

A high‐resolution portrait of the annual dynamics of photochemical and non‐photochemical quenching in needles of Pinus sylvestris

Partitioning of excitation energy between photochemical quenching (PQ) and non-photochemical quenching (NPQ) processes is constantly adjusted in the leaf in order to preserve the photosynthetic energy balance. Adjustments in PQ and NPQ often result from a combination of different temporal components that can be simplified into reversible and sustained components. While reversible PQ and NPQ are relatively well understood, the controls behind the sustained components of PQ and NPQ, or the interaction between sustained and reversible NPQ, remain elusive. In this study, I used a full year of high-resolution chlorophyll fluorescence (ChlF) data obtained with a Monitoring-PAM fluorometer (Walz, Effeltrich, Germany) in needles of boreal Pinus sylvestris in situ to quantitatively analyse the dynamics and interaction between temporal components of NPQ and PQ and their control by the environment. To enable the estimation of sustained and reversible components of PQ and NPQ, a number of key ChlF parameters were reviewed and adapted to the analysis of long-term monitoring data. Overall, NPQ was drastically enhanced during winter via the accumulation of sustained NPQ in a process regulated by air temperature. Reversible NPQ retained some functionality even at temperatures well below zero and was not inhibited by the presence of sustained NPQ per se but by low temperatures alone. This suggests that temporal NPQ components co-operate in an additive rather than complementary fashion, conferring additional flexibility to the photoprotective role of NPQ. Finally, the potential of the sustained photochemical quenching parameter (qL(s) ) to track photoinhibition in situ was discussed.

Community surveys through space and time: testing the space–time interaction in the absence of replication

In order to test hypotheses about changes in the environment induced by man, including climatic change, ecologists are sampling portions of the environment repeatedly across time. This paper describes a method for testing a space-time interaction in repeated ecological survey data, when there is no replication at the level of individual sampling units (sites). This methodological development is important for the analysis of long-term monitoring data, including systems under anthropogenic influence. In these systems, an interaction may indicate that the spatial structure of community composition has changed in the course of time or that the temporal evolution is not the same at all sites. This paper describes ANOVA models corresponding to the steps leading to a solution to the problem, which is based on the representation of space and time by principal coordinates of neighbor matrices (PCNM eigenfunctions) in the ANOVA. Numerical simulations showed that ANOVA Model 5 was the model of choice for the analysis of the space-time interaction because it always had correct rates of Type I error, and its power was always equal to or higher than those of other possible models of analysis. If the hypothesis of absence of interaction is not rejected, one cannot conclude that a change has occurred in the spatial structure of the response data across time; one should follow the ordinary rules of two-way ANOVA if testing the significance of the main factors is of interest. If the hypothesis of absence of interaction is rejected, one should model the spatial structure of each time period in a separate way. One can also conduct a single test involving a separate model of the spatial structure for each time period. This paper presents two applications to real ecological data.

Selection of indicator species for State of the Environment reporting: A case study from New Zealand

Indicator species approaches are widely used in conservation as a shortcut to measuring attributes of species and ecosystems. A variety of indicator species concepts are in use and are applicable to a range of situations. Indicator species are increasingly being used in environmental reporting to evaluate trends in environmental attributes quantitatively. We use the most recent State of the Environment report from New Zealand as a case study to evaluate: (1) how indicator species concepts are being applied to environmental reporting and (2) the selection of individual species as indicators. At present indicator species used in environmental reporting in New Zealand reflect biases in national monitoring data towards forest-dwelling, terrestrial vertebrates that are vulnerable to predation by introduced mammals. Scientific literature generally supports links between selected taxa and the aspect of ecosystem health they are purported to indicate, but their roles as long-term indicators of environmental health have yet to be evaluated. A primary goal of State of the Environment reporting is to set a benchmark against which environmental outcomes can be monitored over time; thus it is recognized that taxa reported should represent a broader range of environmental attributes. However, selection of taxa for environmental reporting is severely constrained by limited national species monitoring data. A strategic approach to national measurement, storage and analysis of long-term monitoring data is required to support selection of representative species for environmental reporting. We support current initiatives to select taxa for future measurement and reporting in an objective, transparent manner and recommend that they encompass representation of: (1) taxonomic diversity, (2) ecosystem types, (3) key environmental pressures and (4) threat status.

Assessing the impact of climate variation on survival in vertebrate populations

The impact of the ongoing rapid climate change on natural systems is a major issue for human societies. An important challenge for ecologists is to identify the climatic factors that drive temporal variation in demographic parameters, and, ultimately, the dynamics of natural populations. The analysis of long-term monitoring data at the individual scale is often the only available approach to estimate reliably demographic parameters of vertebrate populations. We review statistical procedures used in these analyses to study links between climatic factors and survival variation in vertebrate populations. We evaluated the efficiency of various statistical procedures from an analysis of survival in a population of white stork, Ciconia ciconia, a simulation study and a critical review of 78 papers published in the ecological literature. We identified six potential methodological problems: (i) the use of statistical models that are not well-suited to the analysis of long-term monitoring data collected at the individual scale; (ii) low ratios of number of statistical units to number of candidate climatic covariates; (iii) collinearity among candidate climatic covariates; (iv) the use of statistics, to assess statistical support for climatic covariates effects, that deal poorly with unexplained variation in survival; (v) spurious detection of effects due to the co-occurrence of trends in survival and the climatic covariate time series; and (vi) assessment of the magnitude of climatic effects on survival using measures that cannot be compared across case studies. The critical review of the ecological literature revealed that five of these six methodological problems were often poorly tackled. As a consequence we concluded that many of these studies generated hypotheses but only few provided solid evidence for impacts of climatic factors on survival or reliable measures of the magnitude of such impacts. We provide practical advice to solve efficiently most of the methodological problems identified. The only frequent issue that still lacks a straightforward solution was the low ratio of the number of statistical units to the number of candidate climatic covariates. In the perspective of increasing this ratio and therefore of producing more robust analyses of the links between climate and demography, we suggest leads to improve the procedures for designing field protocols and selecting a set of candidate climatic covariates. Finally, we present recent statistical methods with potential interest for assessing the impact of climatic factors on demographic parameters.

Assessing the Influence of Climate Variability on Atmospheric Concentrations of Polychlorinated Biphenyls Using a Global-Scale Mass Balance Model (BETR-Global)

We introduce a new global-scale multimedia contaminant fate model (the Berkeley-Trent Global Model; BETR-Global) that integrates global climate data from the National Centers for Environmental Prediction (NCEP). BETR-Global represents the global environment as a connected set of 288 multimedia regions on a 15 degrees grid. We evaluate the model by simulating the global fate and transport of seven PCB congeners over a 70 year period and find satisfactory agreement between model output and observations of atmospheric PCB concentrations at 11 long-term monitoring stations in the Northern Hemisphere. We demonstrate the use of the model as a tool for understanding global pollutant dynamics by examining the hypothesis that variability in global-scale climate conditions, as reflected bythe North Atlantic Oscillation (NAO), influences atmospheric PCB concentrations in the Northern Hemisphere. We estimate that the maximum variability in atmospheric PCB concentrations attributable to NAO variability is approximately a factor of 2. The influence of variability in the NAO on PCB concentrations in air is most likely to be observed in the winter and spring at monitoring sites in Northern Europe and the Arctic. Analysis of long-term monitoring data from 11 sites shows some statistically significant relationships between NAO indices and atmospheric PCB concentrations during the winter and spring. Giving consideration to competing factors that influence atmospheric PCB concentrations, longer time series of monitoring data are required to fully evaluate the modeling results and to improve our understanding of the role of climate variability on the long-term fate of persistent semivolatile pollutants.