Lead, zinc, and chromium concentrations in acidic headwater streams in Sweden explained by chemical, climatic, and land-use variations

Abstract. Long-term data series (1996–2009) for eleven acidic headwater streams (< 10 km2) in Sweden were analyzed to determine factors controlling concentrations of trace metals. In-stream chemical data as well climatic, flow, and deposition chemistry data were used to develop models predicting concentrations of chromium (Cr), lead (Pb), and zinc (Zn). Data were initially analyzed using partial least squares to determine a set of variables that could predict metal concentrations across all sites. Organic matter (as absorbance) and iron related positively to Pb and Cr, while pH related negatively to Pb and Zn. Other variables such as conductivity, manganese, and temperature were important as well. Multiple linear regression was then used to determine minimally adequate prediction models which explained an average of 35% (Cr), 52% (Zn), and 72% (Pb) of metal variation across all sites. While models explained at least 50% of variation in the majority of sites for Pb (10) and Zn (8), only three sites met this criterion for Cr. Investigation of variation between site models for each metal revealed geographical (altitude), chemical (sulfate), and land-use (silvaculture) influences on predictive power of the models. Residual analysis revealed seasonal differences in the ability of the models to predict metal concentrations as well. Expected future changes in model variables were applied and results showed the potential for long-term increases (Pb) or decreases (Zn) for trace metal concentrations at these sites.

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Trace metal concentrations in acidic, headwater streams in Sweden explained by chemical, climatic, and land use variations

Biogeosciences Discussions ◽

10.5194/bgd-9-1793-2012 ◽

2012 ◽

Vol 9 (2) ◽

pp. 1793-1828 ◽

Cited By ~ 1

Author(s):

B. J. Huser ◽

J. Fölster ◽

S. Köhler

Keyword(s):

Land Use ◽

Trace Metal ◽

Predictive Power ◽

Prediction Models ◽

Headwater Streams ◽

Data Series ◽

Seasonal Differences ◽

Metal Concentrations ◽

Term Data

Abstract. Long term data series (1996–2009) for eleven acidic, headwater streams (<10 km2) in Sweden were analyzed to determine factors controlling concentrations of trace metals. In-stream chemical data as well climatic, flow, and deposition chemistry data were used to develop models predicting concentrations of chromium (Cr), lead (Pb), and zinc (Zn). Data were initially analyzed using partial least squares to determine a set of variables that could predict metal concentrations across all sites. Organic matter (as absorbance) and iron related positively to Pb and Cr while pH related negatively to Pb and Zn. Other variables such as conductivity, manganese, and temperature were important as well. Multiple linear regression was then used to determine minimally adequate prediction models which explained an average of 35% (Cr), 52% (Zn), and 72% (Pb) of metal variation across all sites. While models explained at least 50% of variation in the majority of sites for Pb (10) and Zn (8), only three sites met this criterion for Cr. Investigation of variation between site models for each metal revealed geographical (altitude), chemical (sulfate), and land use (silvaculture) influences on predictive power of the models. Residual analysis revealed seasonal differences in the ability of the models to predict metal concentrations as well. Expected future changes in model variables were applied and results showed the potential for long term increases (Pb) or decreases (Zn) for trace metal concentrations at these sites.

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Diel, lunar and seasonal vertical migration in the deep western Gulf of Mexico evidenced from a long-term data series of acoustic backscatter

Progress In Oceanography ◽

10.1016/j.pocean.2021.102562 ◽

2021 ◽

pp. 102562

Author(s):

Laura Ursella ◽

Sara Pensieri ◽

Enric Pallàs-Sanz ◽

Sharon Z. Herzka ◽

Roberto Bozzano ◽

...

Keyword(s):

Gulf Of Mexico ◽

Vertical Migration ◽

Acoustic Backscatter ◽

Data Series ◽

Term Data

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The projected impacts of smart decline on urban runoff contamination levels

Computational Urban Science ◽

10.1007/s43762-021-00002-1 ◽

2021 ◽

Vol 1 (1) ◽

Author(s):

Rui Zhu ◽

Galen Newman

Keyword(s):

Land Use ◽

Green Infrastructure ◽

Prediction Models ◽

Stormwater Runoff ◽

Baseline Scenario ◽

Vacant Land ◽

Smart Decline ◽

Contamination Levels ◽

Indirect Impacts

AbstractThere has been mounting interest about how the repurposing of vacant land (VL) through green infrastructure (the most common smart decline strategy) can reduce stormwater runoff and improve runoff quality, especially in legacy cities characterized by excessive industrial land uses and VL amounts. This research examines the long-term impacts of smart decline on both stormwater amounts and pollutants loads through integrating land use prediction models with green infrastructure performance models. Using the City of St. Louis, Missouri, USA as the study area, we simulate 2025 land use change using the Conversion of Land Use and its Effects (CLUE-S) and Markov Chain urban land use prediction models and assess these change’s probable impacts on urban contamination levels under different smart decline scenarios using the Long-Term Hydrologic Impact Assessment (L-THIA) performance model. The four different scenarios are: (1) a baseline scenario, (2) a 10% vacant land re-greening (VLRG) scenario, (3) a 20% VLRG scenario, and (4) a 30% VLRG scenario. The results of this study illustrate that smart decline VLRG strategies can have both direct and indirect impacts on urban stormwater runoff and their inherent contamination levels. Direct impacts on urban contamination include the reduction of stormwater runoff and non-point source (NPS) pollutants. In the 30% VLRG scenario, the annual runoff volume decreases by 11%, both physical, chemical, and bacterial pollutants are reduced by an average of 19%, compared to the baseline scenario. Indirect impacts include reduction of the possibility of illegal dumping on VL through mitigation and prevention of future vacancies.

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Dobson, Brewer, ERA-40 and ERA-Interim original and merged total ozone data sets – evaluation of differences: a case study, Hradec Králové (Czech), 1961–2010

Earth System Science Data ◽

10.5194/essd-4-91-2012 ◽

2012 ◽

Vol 4 (1) ◽

pp. 91-100 ◽

Cited By ~ 5

Author(s):

K. Vaníček ◽

L. Metelka ◽

P. Skřivánková ◽

M. Staněk

Keyword(s):

Ozone Depletion ◽

Total Ozone ◽

Montreal Protocol ◽

Data Series ◽

Data Sets ◽

Missing Measurements ◽

Seasonal Differences ◽

Ozone Data

Abstract. Homogenized data series of total ozone measurements taken by the regularly and well calibrated Dobson and Brewer spectrophotometers at Hradec Králové (Czech) and the data from the re-analyses ERA-40 and ERA-Interim were merged and compared to investigate differences between the particular data sets originated in Central Europe, the Northern Hemisphere (NH) mid-latitudes. The Dobson-to-Brewer transfer function and the algorithm for approximation of the data from the re-analyses were developed, tested and applied for creation of instrumentally consistent and completed total ozone data series of the 50-yr period 1961–2010 of observations. This correction has reduced the well-known seasonal differences between Dobson and Brewer data below the 1% calibration limit of the spectrophotometers. Incorporation of the ERA-40 and ERA-Interim total ozone data on days with missing measurements significantly improved completeness and reliability of the data series mainly in the first two decades of the period concerned. Consistent behaviour of the original and corrected/merged data sets was found in the pre-ozone-hole period (1961–1985). In the post-Pinatubo (1994–2010) era the data series show seasonal differences that can introduce uncertainty in estimation of ozone recovery mainly in the winter-spring season when the effect of the Montreal Protocol and its Amendments is expected. All the data sets confirm substantial depletion of ozone also in the summer months that gives rise to the question about its origin. The merged and completed data series of total ozone will be further analyzed to quantify chemical ozone losses and contribution of natural atmospheric processes to the ozone depletion over the region. This case study points out the importance of selection and evaluation of the quality and consistency of the input data sets used in estimation of long-term ozone changes including recovery of the ozone layer over the selected areas. Data are available from the PANGAEA database at doi:10.1594/PANGAEA.779819.

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Analysis of Trends in the FireCCI Global Long Term Burned Area Product (1982–2018)

Fire ◽

10.3390/fire4040074 ◽

2021 ◽

Vol 4 (4) ◽

pp. 74

Author(s):

Gonzalo Otón ◽

José Miguel C. Pereira ◽

João M. N. Silva ◽

Emilio Chuvieco

Keyword(s):

Time Series ◽

Temporal Trends ◽

European Space Agency ◽

Eastern Africa ◽

Burned Area ◽

Data Series ◽

Short Term ◽

The Impact ◽

Term Data

We present an analysis of the spatio-temporal trends derived from long-term burned area (BA) data series. Two global BA products were included in our analysis, the FireCCI51 (2001–2019) and the FireCCILT11 (1982–2018) datasets. The former was generated from Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m reflectance data, guided by 1 km active fires. The FireCCILT11 dataset was generated from Land Long-Term Data Record data (0.05°), which provides a consistent time series for Advanced Very High Resolution Radiometer images, acquired from the NOAA satellite series. FireCCILT11 is the longest time series of a BA product currently available, making it possible to carry out temporal analysis of long-term trends. Both products were developed under the FireCCI project of the European Space Agency. The two datasets were pre-processed to correct for temporal autocorrelation. Unburnable areas were removed and the lack of the FireCCILT11 data in 1994 was examined to evaluate the impact of this gap on the BA trends. An analysis and comparison between the two BA products was performed using a contextual approach. Results of the contextual Mann-Kendall analysis identified significant trends in both datasets, with very different regional values. The long-term series presented larger clusters than the short-term ones. Africa displayed significant decreasing trends in the short-term, and increasing trends in the long-term data series, except in the east. In the long-term series, Eastern Africa, boreal regions, Central Asia and South Australia showed large BA decrease clusters, and Western and Central Africa, South America, USA and North Australia presented BA increase clusters.

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Government expenditure in New Zealand since 1935: a preliminary reassessment

Policy Quarterly ◽

10.26686/pq.v13i2.4664 ◽

2017 ◽

Vol 13 (2) ◽

Author(s):

Matthew Gibbons

Keyword(s):

New Zealand ◽

Comparative Studies ◽

Government Expenditure ◽

Data Series ◽

Optimal Size ◽

Economic Issue ◽

Size Of Government ◽

Expenditure Data ◽

Term Data

The optimal size of government is an important political and economic issue. However, because no long-term government expenditure series has official standing, New Zealand is often a missing case in comparative studies of government expenditure (Castles, 1998). Although government expenditure data is available from 1972 on Treasury’s website (New Zealand Treasury, 2016), the most widely used data before 1972 is a ‘consolidated’ long-term data series, on Statistics New Zealand’s website, which uses data from a number of sources and is published with strong disclaimers.

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