Trend Analysis of Long-Term MSW Leachate Characteristics

2018 ◽  
pp. 143-153
Author(s):  
Tamru Tesseme ◽  
Sumedha Chakma
Keyword(s):  
Trend Analysis ◽  
Leachate Characteristics

Estimation and Long-term Trend Analysis of Surface Solar Radiation in Antarctica: A Case Study of Zhongshan Station

2021 ◽  
Author(s):  
Zhaoliang Zeng ◽  
Zemin Wang ◽  
Minghu Ding ◽  
Xiangdong Zheng ◽  
Xiaoyu Sun ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Trend Analysis ◽  
Surface Solar Radiation ◽  
Term Trend ◽  
Zhongshan Station ◽  
Long Term Trend

scholarly journals Techniques for analyses of trends in GRUAN data

2015 ◽  
Vol 8 (4) ◽  
pp. 1673-1684 ◽  
Author(s):  
G. E. Bodeker ◽  
S. Kremser
Keyword(s):  
Measurement Uncertainty ◽  
Trend Analysis ◽  
Global Climate ◽  
Regional Climate ◽  
Added Value ◽  
Least Squares Regression ◽  
Target Uncertainty ◽  
Reference Quality ◽  
Measurement Uncertainties

Abstract. The Global Climate Observing System (GCOS) Reference Upper Air Network (GRUAN) provides reference quality RS92 radiosonde measurements of temperature, pressure and humidity. A key attribute of reference quality measurements, and hence GRUAN data, is that each datum has a well characterized and traceable estimate of the measurement uncertainty. The long-term homogeneity of the measurement records, and their well characterized uncertainties, make these data suitable for reliably detecting changes in global and regional climate on decadal time scales. Considerable effort is invested in GRUAN operations to (i) describe and analyse all sources of measurement uncertainty to the extent possible, (ii) quantify and synthesize the contribution of each source of uncertainty to the total measurement uncertainty, and (iii) verify that the evaluated net uncertainty is within the required target uncertainty. However, if the climate science community is not sufficiently well informed on how to capitalize on this added value, the significant investment in estimating meaningful measurement uncertainties is largely wasted. This paper presents and discusses the techniques that will need to be employed to reliably quantify long-term trends in GRUAN data records. A pedagogical approach is taken whereby numerical recipes for key parts of the trend analysis process are explored. The paper discusses the construction of linear least squares regression models for trend analysis, boot-strapping approaches to determine uncertainties in trends, dealing with the combined effects of autocorrelation in the data and measurement uncertainties in calculating the uncertainty on trends, best practice for determining seasonality in trends, how to deal with co-linear basis functions, and interpreting derived trends. Synthetic data sets are used to demonstrate these concepts which are then applied to a first analysis of temperature trends in RS92 radiosonde upper air soundings at the GRUAN site at Lindenberg, Germany (52.21° N, 14.12° E).

Long-term particle measurements in Finnish Arctic: Part II – Trend analysis and source location identification

2014 ◽  
Vol 88 ◽  
pp. 285-296 ◽  
Author(s):  
James R. Laing ◽  
Philip K. Hopke ◽  
Eleanor F. Hopke ◽  
Liaquat Husain ◽  
Vincent A. Dutkiewicz ◽  
...  
Keyword(s):  
Trend Analysis ◽  
Source Location ◽  
Particle Measurements ◽  
Location Identification

Abstract P35: The Trend of Stroke Rehabilitation Utilization Between 2014- 2019 in a Community Based Study

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Daniel Uhm ◽  
Esther Olasoji ◽  
Alexis N Simpkins ◽  
Carolyn Geis ◽  
Keyword(s):  
Clinical Practice ◽  
Trend Analysis ◽  
Significant Proportion ◽  
Inpatient Rehabilitation ◽  
Outpatient Rehabilitation ◽  
Rehabilitation Services ◽  
Institutional Review ◽  
Ischemic Attack ◽  
Over Time

Introduction: Stroke is the leading cause of long-term disability in adults, resulting in significant impairments in motor, sensory, and/ or cognitive that often requires continued rehabilitation services, which vary from intensive acute inpatient rehabilitation to outpatient rehabilitation services. Efforts to reduce disability have advanced rapidly over the past several years. Our data analysis was undertaken to assess whether recent changes in clinical practice have impacted the proportion of stroke patients receiving inpatient versus outpatient rehabilitation over time between 2014-2019 at our institution, which serves a diverse mix of rural, suburban, and urban populations. Methods: Our Institutional Review Board approved retrospective stroke database, including adult patients discharged to receive rehabilitation services data from 2014-2019, was used for analysis. Cochran-Armitage trend analysis was used to assess for differences type of rehabilitation services used over time and regression analysis was used to identify clinical factors associated with discharge type over time. Results: A total of 3467 patients were included in the analysis, 50% woman, 1% Asian, 20% Black, 75% White, 4% undetermined race, 17% intracerebral hemorrhage, 65% ischemic stroke, 11% subarachnoid hemorrhage, 3% transient ischemic attack, 3% other cerebrovascular disease. In this community population, 65% were discharged to inpatient rehab. Trend analysis demonstrated a significant increase in the proportion of patients being discharged home with rehab services, p<.0001. In comparison to those discharged home, patients discharged to rehab were older (odds ratio (OR) 1.02, confidence interval (CI) 1.02-1.03), with a higher NIHSS (OR 1.16, CI 1.14-1.18), discharged in 2014 (OR 1.72, CI 1.23-2.39) or 2016 (OR 1.46, CI 1.05-2.05) versus 2019. There was no association with race, gender, or discharge in 2015, 2017, or 2018. Discussion: Our findings demonstrate the community impact of recent changes in clinical practice guidelines for stroke. The increasing trend of home discharges is encouraging, but the significant proportion of those still not discharged home suggests there is still more work to be done to reduce stroke associated disability in adults.

Long-term trend analysis of heavy metal content and translocation in soils

Geoderma ◽  
1986 ◽  
Vol 38 (1-4) ◽  
pp. 195-207 ◽  
Author(s):  
H.W. Schmitt ◽  
H. Sticher
Keyword(s):  
Heavy Metal ◽  
Trend Analysis ◽  
Metal Content ◽  
Heavy Metal Content ◽  
Term Trend ◽  
Long Term Trend

scholarly journals Inter-annual and seasonal trends of vegetation condition in the Upper Blue Nile (Abay) Basin: dual-scale time series analysis

2015 ◽  
Vol 6 (2) ◽  
pp. 617-636 ◽  
Author(s):  
E. Teferi ◽  
S. Uhlenbrook ◽  
W. Bewket
Keyword(s):  
Trend Analysis ◽  
Sustainable Land Use ◽  
Integrated Analysis ◽  
Positive Trend ◽  
Blue Nile ◽  
Seasonal Trends ◽  
Modis Ndvi ◽  
Vegetation Condition ◽  
Gimms Ndvi

Abstract. A long-term decline in ecosystem functioning and productivity, often called land degradation, is a serious environmental challenge to Ethiopia that needs to be understood so as to develop sustainable land use strategies. This study examines inter-annual and seasonal trends of vegetation cover in the Upper Blue Nile (UBN) or Abbay Basin. The Advanced Very High Resolution Radiometer (AVHRR)-based Global Inventory, Monitoring, and Modeling Studies (GIMMS) normalized difference vegetation index (NDVI) was used for long-term vegetation trend analysis at low spatial resolution. Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data (MOD13Q1) were used for medium-scale vegetation trend analysis. Harmonic analyses and non-parametric trend tests were applied to both GIMMS NDVI (1981–2006) and MODIS NDVI (2001–2011) data sets. Based on a robust trend estimator (Theil–Sen slope), most parts of the UBN (~ 77 %) showed a positive trend in monthly GIMMS NDVI, with a mean rate of 0.0015 NDVI units (3.77 % yr−1), out of which 41.15 % of the basin depicted significant increases (p < 0.05), with a mean rate of 0.0023 NDVI units (5.59 % yr−1) during the period. However, the MODIS-based vegetation trend analysis revealed that about 36 % of the UBN showed a significant decreasing trend (p < 0.05) over the period 2001–2011 at an average rate of 0.0768 NDVI yr−1. This indicates that the greening trend of the vegetation condition was followed by decreasing trend since the mid-2000s in the basin, which requires the attention of land users and decision makers. Seasonal trend analysis was found to be very useful to identify changes in vegetation condition that could be masked if only inter-annual vegetation trend analysis was performed. Over half (60 %) of the Abay Basin was found to exhibit significant trends in seasonality over the 25-year period (1982–2006). About 17 and 16 % of the significant trends consisted of areas experiencing a uniform increase in NDVI throughout the year and extended growing season, respectively. These areas were found primarily in shrubland and woodland regions. The study demonstrated that integrated analysis of inter-annual and intra-annual trends based on GIMMS and MODIS enables a more robust identification of changes in vegetation condition.

scholarly journals Total ozone trends and variability during 1979–2012 from merged datasets of various satellites

2013 ◽  
Vol 13 (11) ◽  
pp. 30407-30452 ◽  
Author(s):  
W. Chehade ◽  
J. P. Burrows ◽  
M. Weber
Keyword(s):  
Heat Flux ◽  
Solar Cycle ◽  
Trend Analysis ◽  
Total Ozone ◽  
Montreal Protocol ◽  
The Other ◽  
The Arctic ◽  
Eddy Heat Flux ◽  
Other Hand

Abstract. The study presents a~long term statistical trend analysis of total ozone datasets obtained from various satellites. A multi-variate linear regression was applied to annual mean zonal mean data using various natural and anthropogenic explanatory variables that represent dynamical and chemical processes which modify global ozone distributions in a changing climate. The study investigated the magnitude and zonal distribution of the different atmospheric chemical and dynamical factors to long-term total ozone changes. The regression model included the equivalent effective stratospheric chlorine (EESC), the 11 yr solar cycle, the Quasi-Biennial Oscillation (QBO), stratospheric aerosol loading describing the effects from major volcanic eruptions, the El Niño/Southern Oscillation (ENSO), the Arctic and Antarctic Oscillation (AO/AAO), and accumulated eddy heat flux (EHF), the latter representing changes due to the Brewer–Dobson circulation. The total ozone column dataset used here comprises the SBUV/TOMS/OMI merged data (1979–2012) MOD V8.0, the SBUV/SBUV-2 merged V8.6 and the merged GOME/SCIAMACHY/GOME-2 (GSG) WFDOAS merged data (1995–2012). The trend analysis was performed for twenty six 5° wide latitude bands from 65° S to 65° N, the analysis explained most of the ozone variability. The results show that QBO dominates the ozone variability in the tropics (±7 DU) while at higher latitudes, the dynamical indices, AO/AAO and eddy heat flux, have substantial influence on total ozone variations by up to ±10 DU. Volcanic aerosols are only prominent during the eruption periods and these together with the ENSO signal are more evident in the Northern Hemisphere. The signature of the solar cycle is evident over all latitudes and contributes about 10 DU from solar maximum to solar minimum. EESC is found to be a main contributor to the long-term ozone decline and the trend changes after the end of 1990s. A positive significant trend in total ozone columns is found after 1997 (between 1 and 8.2 DU decade−1) which points at the slowing of ozone decline and the onset of ozone recovery. The EESC based trends are compared with the trends obtained from the statistical piecewise linear trend (PWLT or hockey stick) model with a turnaround in 1997 to examine the differences between both approaches. Similar and significant pre-turnaround trends are observed. On the other hand, our results do indicate that the positive PWLT turnaround trends are larger than indicated by the EESC trends, however, they agree within 2-sigma, thus demonstrating the success of the Montreal Protocol phasing out of the ozone depleting substances (ODS). A sensitivity study is carried out by comparing the regression results, using SBUV MOD 8.0 merged time series (1979–2012) and a merged dataset combining TOMS/SBUV (1979–June 1995) and GOME/SCIAMACHY/GOME-2 ("GSG") WFDOAS (Weighting Function DOAS) (July 1995–2012) as well as SBUV/SBUV-2 MOD 8.6 (1979–2012) in the regression analysis in order to investigate the uncertainty in the long-term trends due to different ozone datasets and data versions. Replacing the late SBUV merged data record with GSG data (unscaled and adjusted) leads to very similar results demonstrating the high consistency between satellite datasets. However, the comparison of the new SBUV merged Mod V8.6 with the V8.0 data showed somewhat smaller sensitivities with regard to several proxies, however, the EESC and PWLT trends are very similar. On the other hand, the new MOD 8.6 data in the PWLT model revealed a~reduced ODS related upward trend after 1997.

Evaluating temporal consistency of long-term global NDVI datasets for trend analysis

2015 ◽  
Vol 163 ◽  
pp. 326-340 ◽  
Author(s):  
Feng Tian ◽  
Rasmus Fensholt ◽  
Jan Verbesselt ◽  
Kenneth Grogan ◽  
Stephanie Horion ◽  
...  
Keyword(s):  
Trend Analysis ◽  
Temporal Consistency
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