Prediction of ozone concentrations in Oporto city with statistical approaches

The performance of three statistical methods: time-series, multiple linear regression and feedforward artificial neural networks models were compared to predict the daily mean ozone concentrations. The study here reported was based on data from one urban site with traffic influences and one rural background site. The studies were performed for the year 2002 and the respective four trimesters separately. In the multiple linear regression and feedforward artificial neural network models, the concentrations of ozone, the concentrations of its precursors (nitrogen oxides) and some meteorological variables for one and two days before the prediction day were used as predictors. For the application of these models in the validation step, the inputs of ozone concentration for one and two days before were replaced by the ozone concentrations predicted by the models. The results showed that time-series modelling was not profitable. In the development step, similar performances were obtained with multiple linear regression and feedforward artificial neural network. Better performance indexes were achieved with feedforward artificial neural network models in validation step. Concluding, feedforward artificial neural network models were more efficient to predict ozone concentrations.     

Rainfall trends in twentieth century over Kerala,India

Attempts were made to study temporal variation in monthly, seasonal and annual rainfall over Kerala, India, during the period from 1871 to 2005. Longterm changes in rainfall determined by Man-Kendall rank statistics and linear trend. The analysis revealed significant decrease in southwest monsoon rainfall while increase in post-monsoon season over the State of Kerala which is popularly known as the “Gateway of summer monsoon”. Rainfall during winter and summer seasons showed insignificant increasing trend. Rainfall during June and July showed significant decreasing trend while increasing trend in January, February and April. Hydel power generation and water availability during summer months are the concern in the State due to rainfall decline in June and July, which are the rainiest months. At the same time, majority of plantation crops are likely to benefit due to increase in rainfall during the post-monsoon season if they are stable and prolonged.     

Analysis of air pollution data at a mixed source location using boosted regression trees

This paper explores the use of boosted regression trees to draw inferences concerning the source characteristics at a location of high source complexity. Models are developed for hourly concentrations of nitrogen oxides (NO_X) close to a large international airport. Model development is discussed and methods to quantify model uncertainties developed. It is shown that good explanatory models can be developed and further, allowing for interactions between model variables significantly improves the model fits compared with non-interacting models. Methods are used to determine which variables exert most influence over predicted concentrations and to explore the NO_X dependency for each. Model predictions are used to estimate aircraft take-off contributions to total concentrations of NO_X and determine how these predictions are affected by annual variations in meteorological conditions and runway use patterns. Furthermore, the results relating to the aircraft contributions to total NO_X concentration are compared with those from a more detailed independent field campaign. Finally, we find empirical evidence that plumes from larger aircraft disperse more rapidly from the point of release compared with smaller aircraft. The reasons for this behaviour and the implications are discussed.     

Effects of reduced contaminant loading on downgradient water quality in an idealized two-layer granular porous media

The following explores the issue of how reductions in contaminant loading to plumes will effect downgradient water quality. An idealized scenario of two adjacent layers of uniform geologic media, one transmissive and the other low permeability, is considered. A high concentration source, similar to a thin DNAPL pool, is introduced in the transmissive layer immediately above the low permeability layer. While the source is active, dissolved constituents are driven along the contact by advection and into the low permeability layer by transverse diffusion. Removing the source reverses the concentration gradient between the layers, driving back diffusion of contaminants from the low permeability layer. Laboratory studies involving four contaminants demonstrate that 15 to 44% of the introduced contaminant moves into the low permeability zone (along a distance of 87 cm in a sand tank) over a period of 25 days. The greatest movement of contaminants into the low permeability zone is seen with the contaminants with the greatest sorption coefficients. A unique two-dimensional analytical solution is developed for the two-layer scenario. Processes addressed include advection; transverse dispersion; adsorption and degradation in the transmissive zones; and diffusion, adsorption, and degradation in the low permeability layer. Laboratory data agree favorably with the analytical solutions. Collectively, the laboratory results and analytical solutions provide a basis for testing other modeling approaches that can be applied to more complex problems. A set of field-scale scenarios are considered using the analytical solutions. Results indicate that improvement in water quality associated with source removal diminish with distance downgradient of the source. Furthermore, contaminant degradation and contaminant adsorption in the stagnant zone are shown to be critical factors governing the timing and magnitude of downgradient improvements in water quality. For five of six scenarios considered, observed improvements in water quality 100 m downgradient of the source fall in the range of 1 to 2 orders of magnitude 15 years after complete source removal. The sixth scenario, involving a contaminant half-life of three years and no adsorption, shows greater than three order of magnitude improvements in downgradient water quality within one year of source removal.     

Presenting Triple-Wins? Assessing Projects That Deliver Adaptation,Mitigation and Development Co-benefits in Rural Sub-Saharan Africa

The concept of climate compatible development (CCD) is increasingly employed by donors and policy makers seeking ‘triple-wins’ for development, adaptation and mitigation. While CCD rhetoric is becoming more widespread, analyses drawing on empirical cases that present triple-wins are sorely lacking. We address this knowledge gap. Drawing on examples in rural sub-Saharan Africa, we provide the first glimpse into how projects that demonstrate triple-win potential are framed and presented within the scientific literature. We identify that development projects are still commonly evaluated in terms of adaptation or mitigation benefits. Few are framed according to their benefits across all three dimensions. Consequently, where triple-wins are occurring, they are likely to be under-reported. This has important implications, which underestimates the co-benefits that projects can deliver. A more robust academic evidence base for the delivery of triple-wins is necessary to encourage continued donor investment in activities offering the potential to deliver CCD.     

Feasibility of soil dust source apportionment by the pyrolysis-gas chromatography/mass spectrometry method

This study tested the feasibility of using pyrolysis (Py)-gas chromatography (GC)/mass spectrometry (MS) to obtain organic chemical species data suitable for source apportionment modeling of soil-derived coarse particulate matter (PM10) dust on ambient filters. A laboratory resuspension apparatus was used with known soils to generate simulated receptor filter samples loaded with approximately 0.4 mg of PM10 dust, which is within the range of mass loading on ambient filters. Py-GC/MS at 740 degrees C generated five times more resolvable compounds than were obtained with thermal desorption GC/MS at 315 degrees C. The identified compounds were consistent with literature from Py experiments using larger samples of bulk soils. A subset of 91 organic species out of the 178 identified Py products was used as input to CMB8 software in a demonstration of source apportionment using laboratory-generated mixtures simulating ambient filter samples. The 178 quantified organic species obtained by Py of soil samples is an improvement compared with the 38 organic species obtained by thermal desorption of soils and the four functionally defined organic fractions reported by thermal/ optical reflectance. Significant differences in the concentration of specific species were seen between samples from different sites, both geographically distant and close, using analysis of variance and cluster analysis. This feasibility study showed that Py-GC/MS can generate useful source profile data for receptor modeling and justifies continued method development.     

Acetylcholinesterase activity in the terrestrial snail Xeropicta derbentina transplanted in apple orchards with different pesticide management strategies

Apple orchards are highly manipulated crops in which large amounts of pesticides are used. Some of these pesticides lack target specificity and can cause adverse effects in non-target organisms. In order to evaluate the environmental risk of these products, the use of transplanted sentinel organisms avoids side-effects from past events and facilitate comparison of multiple sites in a short time. We released specimens of the terrestrial snail Xeropicta derbentina in each 5 of two kinds of apple orchards with either conventional or organic management strategies plus in a single abandoned orchard. After one month, individuals were retrieved in order to measure acetylcholinesterase (AChE) activity. Mean values of AChE activity were significantly reduced in all conventional apple orchards compared to the others. Results show that the measurement of biomarkers such as AChE inhibition in transplated X. derbentina could be useful in the environmental risk assessment of post-authorized pesticides.