Relating meteorological variables and trends in motor vehicle emissions to monthly urban carbon monoxide concentrations

A model which quantifies the relationship between the monthly time series for CO emissions, the monthly time series in ambient CO concentration, and meteorologically driven dispersion was developed. Fifteen cities representing a wide range of geographical and climatic conditions were selected. An eight-year time series (1984–1991 inclusive) of monthly averaged data were examined in each city. A new method of handling missing ambient concentration values which is designed to calculate city-wide average concentrations that follow the trend seen at individual monitor sites is presented. This method is general and can be used in other applications involving missing data. The model uses emissions estimates along with two meteorological variables (wind speed and mixing height) to estimate monthly averages of ambient air pollution concentrations. The model is shown to have a wide range of applicability; it works equally well for a wide range of cities that have very different temporal CO distributions. The model is suited for assessing long-term trends in ambient air pollutants and can also be used for estimating seasonal variations in concentration, estimation of trends in emissions, and for filling in gaps in the ambient concentration record.     

The changing nature of the 206Pb/207Pb isotopic ratio of lead in rainwater, atmospheric particulates, pine needles and leaded petrol in Scotland, 1982-1998

The inductively coupled plasma-mass spectrometry (ICP-MS)-determined 206Pb/207Pb ratio of 145 samples of rainwater collected at 25 locations around Scotland during December 1997 and January 1998 and at three longterm monitoring stations in the northeast, central belt and southeast of the country from November 1997 to December 1998 averaged 1.144+/-0.017 (1 s). This represents a significant increase from the mean value of 1.120+/-0.016 recorded for the long-term sites in 1989 1991, only partly attributable to a concomitant increase in the 206Pb/207Pb ratio of leaded petrol from 1.075+/-0.013 to 1.088+/-0.007. The rainwater 206Pb/207Pb data for the late 1990s also contrast markedly with the lower 206Pb/207Pb ratios found for pine needle and atmospheric particulate samples from Scotland (e.g. Glasgow: 1.085+/-0.012 in 1985-1986, 1.099+/-0.007 in 1991-1992), England and Western Europe in this study for the period 1982-1992 when emissions of lead to the atmosphere from petrol-engined vehicles in the UK were approximately 2-9 times higher. The observed change in the lead isotopic signature of rainwater predominantly reflects the impact of measures, such as the introduction and growing uptake of unleaded petrol, to reduce car exhaust emissions of lead to the atmosphere in the UK. Based on the rainwater data, source apportionment calculations suggest a general decline in the contribution of leaded petrol to atmospheric lead in Scotland from 53-61% in 1989-1991 to 32-45% in 1997-1998, with a corresponding decline in the urban environment from 84-86% to 48-58%.     

Optimizing carbon sequestration in commercial forests by integrating carbon management objectives in wood supply modeling

This paper provides a methodology for generating forest management plans, which explicitly maximize carbon (C) sequestration at the forest-landscape level. This paper takes advantage of concepts first presented in a paper by Meng et al. (2003; Mitigation Adaptation Strategies Global Change 8:371–403) by integrating C-sequestration objective functions in existing wood supply models. Carbon-stock calculations performed in Woodstock^TM (RemSoft Inc.) are based on C yields generated from volume table data obtained from local Forest Development Survey plots and a series of wood volume-to-C content conversion factors specified in von Mirbach (2000). The approach is used to investigate the impact of three demonstration forest-management scenarios on the C budget in a 110,000 ha forest in south-central New Brunswick, Canada. Explicit demonstration scenarios addressed include (1) maximizing timber extraction either by clearcut or selection harvesting for greatest revenue generation, (2) maximizing total C storage in the forest landscape and in wood products generated from harvesting, and (3) maximizing C storage together with revenue generation. The level of clearcut harvesting was greatest for scenario 1 (≥15 × 10⁴ m³ of wood and ≥943 ha of land per harvesting period), and least for scenario 2 (=0 m³ per harvesting period) where selection harvesting dominated. Because softwood saw logs were worth more than pulpwood ($60 m⁻³ vs. $40 m⁻³) and were strategic to the long-term storage of C, the production of softwood saw logs exceeded the production of pulpwood in all scenarios. Selection harvesting was generally the preferred harvesting method across scenarios. Only in scenario 1 did levels of clearcut harvesting occasionally exceed those of selection harvesting, mainly in the removal of old, dilapidated stands early in the simulation (i.e., during periods 1 through 3). Scenario 2 provided the greatest total C-storage increase over 80 years (i.e., 14 × 10⁶ Mg C, or roughly 264 Mg ha⁻¹) at a cost of $111 per Mg C due to lost revenues. Scenarios 3 and 1 produced reduced storage rates of roughly 9 × 10⁶ Mg C and 3 × 10⁶ Mg C, respectively; about 64% and 22% of the total, 80-year C storage calculated in scenario 2. The bulk of the C in scenario 2 was stored in the forest, amounting to about 76% of the total C sequestered.     

Network-based exploration and visualisation of ecological data

Networks – structured graphs consisting of sets of nodes connected by edges – provide a rich framework for data visualisation and exploratory analyses. Although rarely used for the visualisation of ecological data, networks are well suited to this purpose, including data that one might not normally think of as a network. We present a simple method for transforming a data matrix into network format, and show how this can be used as the basis for interactive exploratory analyses of ecological data.The method is demonstrated using a database of marine zooplankton samples acquired in the Southern Ocean. The network analyses revealed zooplankton community structures that are in good agreement with previously published results. Variations in community structure were observed to be related to the temporal and spatial pattern of sampling, as well as to physical environmental factors such as sea ice cover. The analyses also revealed a number of errors in the data, including taxon identification errors and instrument failures.The method allows the analyst to generate networks from different combinations of variables in the data set, and to examine the effects of varying parameters such as the scales of spatial, temporal, and taxonomic aggregation. This flexibility allows the analyst to rapidly gain a number of perspectives on the data and provides a powerful mechanism for exploration.     

A process-based model designed for filling of large data gaps in tower-based measurements of net ecosystem productivity

In this paper we present a simple hybrid gap-filling model (GFM) designed with a minimum number of parameters necessary to capture the ecological processes important for filling medium-to-large gaps in Flux data. As the model is process-based, the model has potential to be used in filling large gaps exhibiting a broad range of micro-meteorological and site conditions. The GFM performance was evaluated using “Punch hole” and extrapolation experiments based on data collected in west-central New Brunswick. These experiments indicated that the GFM is able to provide acceptable results (r² > 0.80) when >500 data points are used in model parameterization. The GFM was shown to address daytime evolution of NEP reasonably well for a wide range of weather and site conditions. An analysis of residuals indicated that for the most part no obvious trends were evident; although a slight bias was detected in NEP with soil temperature. To explore the portability of the GFM across ecosystem types, a transcontinental validation was conducted using NEP and ancillary data from seven ecosystems along a north-south transect (i.e., temperature–moisture gradient) from northern Europe (Finland) to the Middle East (Israel). The GFM was shown to explain over 75% of the variability in NEP measured at most ecosystems, which strongly suggests that the GFM maybe successfully applied to forest ecosystems outside Canada.     

Prenatal diagnosis of a new syndrome: Holoprosencephaly with hypokinesia

Markedly decreased fetal activity (akinesia/hypokinesia) is usually readily apparent to experienced mothers, and frequently this concern leads to attempts at prenatal diagnosis. We report prenatal diagnosis of two fetuses with congenital contractures, markedly decreased fetal movement, and microcephaly due to severe holoprosencephaly. Such familial recurrence to phenotypically normal parents suggests a newly recognized autosomal recessive or X-linked syndrome that is readily detectable by prenatal ultrasonography.     

STORM RUNOFF PREDICTION BASED ON A SPATIALLY DISTRIBUTED TRAVEL TIME METHOD UTILIZING REMOTE SENSING AND GIS1

ABSTRACT: In this study, remotely sensed data and geographic information system (GIS) tools were used to estimate storm runoff response for Simms Creek watershed in the Etonia basin in northeast Florida. Land cover information from digital orthophoto quarter quadrangles (DOQQ), and enhanced thematic mapper plus (ETM+) were analyzed for the years 1990, 1995, and 2000. The corresponding infiltration excess runoff response of the study area was estimated using the U.S. Department of Agriculture (USDA), Natural Resources Conservation Service Curve Number (NRCS‐CN) method. A digital elevation model (DEM)/GIS technique was developed to predict stream response to runoff events based on the travel time from each grid cell to the watershed outlet. A comparison of predicted to observed stream response shows that the model predicts the total runoff volume with an efficiency of 0.98, the peak flow rate at an efficiency of 0.85, and the full direct runoff hydrograph with an average efficiency of 0.65. The DEM/GIS travel time model can be used to predict the runoff response of ungaged watersheds and is useful for predicting runoff hydrographs resulting from proposed large scale changes in the land use.     

Spatial and temporal drivers of zoonotic pathogen contamination of an agricultural watershed

In regions where animal agriculture is prominent, such as southern Alberta, higher rates of gastrointestinal illness have been reported when compared with nonagricultural regions. This difference in the rate of illness is thought to be a result of increased zoonotic pathogen exposure through environmental sources such as water. In this study, temporal and spatial factors associated with bacterial pathogen contamination of the Oldman River, which transverses this region, were analyzed using classification and regression tree analysis. Significantly higher levels of fecal indicators; more frequent isolations of Campylobacter spp., Escherichia coli O157:H7, and Salmonella enterica spp.; and higher rates of detection of pig-specific Bacteroides markers occurred at downstream sites than at upstream sites, suggesting additive stream inputs. Fecal indicator densities were also significantly higher when any one of these three bacterial pathogens was present and where there were higher total animal manure units; however, occasionally pathogens were present when fecal indicator levels were low or undetectable. Overall, Salmonella spp., Campylobacter spp., and E. coli O157:H7 presence was associated with season, animal manure units, and total rainfall on the day of sampling and 3 d in advance of sampling. Several of the environmental variables analyzed in this study appear to influence pathogen prevalence and therefore may be useful in predicting water quality and safety and in the improvement of watershed management practices in this and other agricultural regions.