Methodological uncertainties in multi-regression analyses of middle-atmospheric data series

Multi-regression analyses have often been used recently to detect trends, in particular in ozone or temperature data sets in the stratosphere. The confidence in detecting trends depends on a number of factors which generate uncertainties. Part of these uncertainties comes from the random variability and these are what is usually considered. They can be statistically estimated from residual deviations between the data and the fitting model. However, interferences between different sources of variability affecting the data set, such as the Quasi-Biennal Oscillation (QBO), volcanic aerosols, solar flux variability and the trend can also be a critical source of errors. This type of error has hitherto not been well quantified. In this work an artificial data series has been generated to carry out such estimates. The sources of errors considered here are: the length of the data series, the dependence on the choice of parameters used in the fitting model and the time evolution of the trend in the data series. Curves provided here, will permit future studies to test the magnitude of the methodological bias expected for a given case, as shown in several real examples. It is found that, if the data series is shorter than a decade, the uncertainties are very large, whatever factors are chosen to identify the source of the variability. However the errors can be limited when dealing with natural variability, if a sufficient number of periods (for periodic forcings) are covered by the analysed dataset. However when analysing the trend, the response to volcanic eruption induces a bias, whatever the length of the data series. The signal to noise ratio is a key factor: doubling the noise increases the period for which data is required in order to obtain an error smaller than 10%, from 1 to 3-4 decades. Moreover, if non-linear trends are superimposed on the data, and if the length of the series is longer than five years, a non-linear function has to be used to estimate trends. When applied to real data series, and when a breakpoint in the series occurs, the study reveals that data extending over 5 years are needed to detect a significant change in the slope of the ozone trends at mid-latitudes.     

Epidemiology of tornado destruction in rural northern Bangladesh: risk factors for death and injury

The epidemiology of tornado-related disasters in the developing world is poorly understood. An August 2005 post-tornado cohort study in rural Bangladesh identified elevated levels of death and injury among the elderly (≥ 60 years of age) (adjusted odds ratio (AOR) = 8.9 (95 per cent confidence interval (CI): 3.9-20.2) and AOR = 1.6 (95 per cent CI: 1.4-1.8), respectively), as compared to 15-24 year-olds, and among those outdoors versus indoors during the tornado (AOR = 10.4 (95 per cent CI: 5.5-19.9) and AOR = 6.6 (95 per cent CI: 5.8-7.5), respectively). Females were 1.24 times (95 per cent CI: 1.15-1.33) more likely to be injured than males. Elevated risk of injury was significantly associated with structural damage to the house and tin construction materials. Seeking treatment was protective against death among the injured, odds ratio = 0.08 (95 per cent CI: 0.03-0.21). Further research is needed to develop injury prevention strategies and to address disparities in risk between age groups and between men and women.     

Polycyclic aromatic hydrocarbons (PAHs) in atmospheric urban area: monitoring on various types of sites

The air quality over the Toulouse urban area (France) is recorded daily by the regional "Midi-Pyrénées" atmospheric pollution measurements network (ORAMIP). Relevant data is collected from about 100 analysers spread over more than thirty stations. The regulations covering major indicators of atmospheric pollution (ozone, nitrogen dioxide, sulphur dioxide) have been updated in recent years to include additional compounds like polycyclic aromatic hydrocarbons (PAHs). The ORAMIP, in partnership with the ENSIACET has undertaken background PAH average concentration measurements over the urban agglomeration of Toulouse during spring 2006 for various types of sites (traffic, urban, industrial). The sampling was performed using a low volume air sampler equipped with quartz fiber filters and polyurethane foams For the two urban sites, total atmospheric concentrations between 12 and 20 ng/m(3) have been obtained, whereas for the industrial site the values averaged 22 ng/m(3). In addition, and regardless of site, the average concentrations of benzo[a]pyrene, at present the only regulated PAH, were always less than the 1 ng/m(3) limit.     

The Precision of Precipitation Chemistry Measurements in the Canadian Air and Precipitation Monitoring Network (CAPMoN)

Precision estimates are presented for precipitation chemistry and depth measurements made by the Canadian Air and Precipitation Monitoring Network (CAPMoN). The estimates were made for daily measurements of ion concentration and precipitation depth as well as for weekly, 28-day, seasonal and annual precipitation-weighted mean concentrations and depths. The data on which the estimates are based were collected from collocated samplers at five CAPMoN sites during the period 1985 to 1993. The data pairs from the collocated samplers were used to calculate the between-instrument error defined as 1/2 times the difference between the paired sample concentrations (or depths). For all of the ion concentrations and depths, the between-sampler errors were found not to be normally distributed, but the normality of the distributions improved with the length of the (volume-weighting) time period considered. A set of quantitative measures of overall network precision were derived in absolute (mg L^-1) and relative (%) units. These included the Modified Median Absolute Deviation (M.MAD), the P90% probability values and the Coefficient of Variation (CoV). The latter, defined as the percent ratio of the M.MAD to the median concentration (or depth), represents the relative precision at the center of the error and concentration (and depth) distributions. Based on the CoV values, the relative precision of the CAPMoN measurements was very high (better than 4%) for SO ₄ ^2- , NO ₃ ^- , pH, H⁺, NH ₄ ⁺ , sample depth and standard gauge depth, and not as high (between 10 and <35%) for Cl^-, Na⁺, Ca²⁺, Mg²⁺, and K⁺. The ions with the lowest median concentrations had the poorest relative precision since so many of the concentrations were at or near the analytical detection limit. Except for the sample and standard gauge depths, both the absolute and relative precision improved with the length of the precipitation-weighting period. Detailed statistical testing established that the precision of the daily measurements is dependent on a number of factors, the most dominant being sample depth and concentration, i.e., the absolute precision improves with increasing sample depth and decreasing concentration. The strength of these relationships diminished with the length of the precipitation-weighting period being considered. Laboratory-related sources of imprecision were found to account for less than 4% of the overall daily measurement imprecision for most species, while field-related sources of imprecision accounted for the balance. Specialized plots are shown which allow data users to estimate the absolute and relative precision at any concentration and depth value.     

A development in energy flow/barrier analysis

In this paper, the occupational accidents and their effects on people are modeled. The basis of energy flow/barrier analysis is used to define an accident as the impact of a hazardous agent on a target, as a result of failure of control and protective barriers. This definition is enhanced to include serial and parallel barriers and to distinguish energy barriers from target barriers. The barrier attributes are defined and used to create a quantitative scenario-building model. The probability and severity of various accidents are estimated, by studying barrier reliability and efficiency. This approach is used to develop and simulate accident scenarios and to calculate their consequences. This model can be used in complex systems for analyzing the risk and estimating the importance of barriers.     

A hydrological modeling framework for defining achievable performance standards for pesticides

This paper proposes a hydrological modeling framework to define achievable performance standards (APSs) for pesticides that could be attained after implementation of recommended management actions, agricultural practices, and available technologies (i.e., beneficial management practices [BMPs]). An integrated hydrological modeling system, Gestion Intégrée des Bassins versants à l'aide d'un Système Informatisé, was used to quantify APSs for six Canadian watersheds for eight pesticides: atrazine, carbofuran, dicamba, glyphosate, MCPB, MCPA, metolachlor, and 2,4-D. Outputs from simulation runs to predict pesticide concentration under current conditions and in response to implementation of two types of beneficial management practices (reduced pesticide application rate and 1- to 10-m-wide edge-of-field and/or riparian buffer strips, implemented singly or in combination) showed that APS values for scenarios with BMPs were less than those for current conditions. Moreover, APS values at the outlet of watersheds were usually less than ecological thresholds of good condition, when available. Upstream river reaches were at greater risk of having concentrations above a given ecological thresholds because of limited stream flows and overland loads of pesticides. Our integrated approach of "hydrological modeling-APS estimation-ecotoxicological significance" provides the most effective interpretation possible, for management and education purposes, of the potential biological impact of predicted pesticide concentrations in rivers.     

Land Use and Water Quality Along a Mekong Tributary in Northern Lao P.D.R.

Improving access to clean water has the potential to make a major contribution toward poverty reduction in rural communities of Lao P.D.R. This study focuses on stream water quality along a Mekong basin tributary, the Houay Xon that flows within a mountainous, mosaic land-use catchment of northern Lao P.D.R. To compare direct water quality measurements to the perception of water quality within the riparian population, our survey included interviews of villagers. Water quality was found to vary greatly depending on the location along the stream. Overall, it reflected the balance between the stream self-cleaning potential and human pressure on the riparian zone: (i) high bacteria and suspended load levels occurred where livestock are left to free-range within the riparian zone; (ii) very low oxygen content and high bacteriological contamination prevailed downstream from villages; (iii) high concentrations of bacteria were consistently observed along urbanized banks; (iv) low oxygen content were associated with the discharge of organic-rich wastewater from a small industrial plant; (v) very high suspended load and bacteria levels occurred during flood events due to soil erosion from steep cultivated hill slopes. Besides these human induced pollutions we also noted spontaneous enrichments in metals in wetland areas fed by dysoxic groundwater. These biophysical measurements were in agreement with the opinions expressed by the majority of the interviewees who reported poor and decreasing water quality in the Houay Xon catchment. Based on our survey, we propose recommendations to improve or maintain stream water quality in the uplands of northern Lao P.D.R.