Different splitting techniques with application to air pollution models

Splitting techniques are commonly used when large-scale models, which appear in different fields of science and engineering, are treated numerically. Four types of splitting procedures are defined and discussed. The problem of the choice of a splitting procedure is investigated. Several numerical tests, by which the influence of the splitting errors on the accuracy of the results is studied, are given. It is shown that the splitting errors decrease linearly when (1) the splitting procedure is of first order and (2) the splitting errors are dominant. Three examples for splitting procedures used in all large-scale air pollution models are presented. Numerical results obtained by a particular air pollution model, Unified Danish Eulerian Model (UNI-DEM), are given and analysed.

Impact of future climate changes on high pollution levels

Changes in climate variability as well as changes in extreme weather and climate events in the 20th century, especially those that took place during the last two to three decades of the 20th century, have been discussed in many recent scientific publications. Attempts to project the results of such studies in the future have been made under different assumptions. In this paper, we have chosen one of the well-known scenarios predicting changes of the climate in the world during the last 30 years of the 21st century. This scenario is used, together with several general predictions related to the future climate, to produce three climatic scenarios. The derived climatic scenarios are used to calculate predictions for future pollution levels in Denmark and in Europe by applying the Unified Danish Eulerian Model (UNI-DEM), on a space domain containing the whole of Europe.

Towards a holistic modelling framework for embodied carbon and waste in the building lifecycle

As the building industry proceeds in the direction of low impact buildings, research attention is being drawn towards the reduction of carbon dioxide emission and waste. Starting from design and construction to operation and demolition, various building materials are used throughout the whole building lifecycle involving significant energy consumption and waste generation. Building Information Modelling (BIM) is emerging as a tool that can support holistic design-decision making for reducing embodied carbon and waste production in the building lifecycle. This study aims to establish a framework for assessing embodied carbon and waste underpinned by BIM technology. On the basis of current research review, the framework is considered to include functional modules for embodied carbon computation. There are a module for waste estimation, a knowledge-base of construction and demolition methods, a repository of building components information, and an inventory of construction materials’ energy and carbon. Through both static 3D model visualisation and dynamic modelling supported by the framework, embodied energy (carbon), waste and associated costs can be analysed in the boundary of cradle-to-gate, construction, operation, and demolition. The proposed holistic modelling framework provides a possibility to analyse embodied carbon and waste from different building lifecycle perspectives including associated costs. It brings together existing segmented embodied carbon and waste estimation into a unified model, so that interactions between various parameters through the different building lifecycle phases can be better understood. Thus, it can improve design-decision support for optimal low impact building development. The applicability of this framework is anticipated being developed and tested on industrial projects in the near future.

Predicting microbial pollution concentrations in UK rivers in response to land use change

The Water Framework Directive has caused a paradigm shift towards the integrated management of recreational water quality through the development of drainage basin-wide programmes of measures. This has increased the need for a cost-effective diagnostic tool capable of accurately predicting riverine faecal indicator organism (FIO) concentrations. This paper outlines the application of models developed to fulfil this need, which represent the first transferrable generic FIO models to be developed for the UK to incorporate direct measures of key FIO sources (namely human and livestock population data) as predictor variables. We apply a recently developed transfer methodology, which enables the quantification of geometric mean presumptive faecal coliforms and presumptive intestinal enterococci concentrations for base- and high-flow during the summer bathing season in unmonitored UK watercourses, to predict FIO concentrations in the Humber river basin district. Because the FIO models incorporate explanatory variables which allow the effects of policy measures which influence livestock stocking rates to be assessed, we carry out empirical analysis of the differential effects of seven land use management and policy instruments (fiscal constraint, production constraint, cost intervention, area intervention, demand-side constraint, input constraint, and micro-level land use management) all of which can be used to reduce riverine FIO concentrations. This research provides insights into FIO source apportionment, explores a selection of pollution remediation strategies and the spatial differentiation of land use policies which could be implemented to deliver river quality improvements. All of the policy tools we model reduce FIO concentrations in rivers but our research suggests that the installation of streamside fencing in intensive milk producing areas may be the single most effective land management strategy to reduce riverine microbial pollution.

Impacts of pollution and climate change on ombrotrophic Sphagnum species in the UK: analysis of uncertainties in two empirical niche models

A significant challenge in the prediction of climate change impacts on ecosystems and biodiversity is quantifying the sources of uncertainty that emerge within and between different models. Statistical species niche models have grown in popularity, yet no single best technique has been identified reflecting differing performance in different situations. Our aim was to quantify uncertainties associated with the application of 2 complimentary modelling techniques. Generalised linear mixed models (GLMM) and generalised additive mixed models (GAMM) were used to model the realised niche of ombrotrophic Sphagnum species in British peatlands. These models were then used to predict changes in Sphagnum cover between 2020 and 2050 based on projections of climate change and atmospheric deposition of nitrogen and sulphur. Over 90% of the variation in the GLMM predictions was due to niche model parameter uncertainty, dropping to 14% for the GAMM. After having covaried out other factors, average variation in predicted values of Sphagnum cover across UK peatlands was the next largest source of variation (8% for the GLMM and 86% for the GAMM). The better performance of the GAMM needs to be weighed against its tendency to overfit the training data. While our niche models are only a first approximation, we used them to undertake a preliminary evaluation of the relative importance of climate change and nitrogen and sulphur deposition and the geographic locations of the largest expected changes in Sphagnum cover. Predicted changes in cover were all small (generally <1% in an average 4 m2 unit area) but also highly uncertain. Peatlands expected to be most affected by climate change in combination with atmospheric pollution were Dartmoor, Brecon Beacons and the western Lake District.

Abundance and diversity of wild bees along gradients of heavy metal pollution

1. Wild bees are one of the most important groups of pollinators in the temperate zone. Therefore, population declines have potentially negative impacts for both crop and wildflower pollination. Although heavy metal pollution is recognized to be a problem affecting large parts of the European Union, we currently lack insights into the effects of heavy metals on wild bees. 2. We investigated whether heavy metal pollution is a potential threat to wild bee communities by comparing (i) species number, (ii) diversity and (iii) abundance as well as (iv) natural mortality of emerging bees along two independent gradients of heavy metal pollution, one at Olkusz (OLK), Poland and the other at Avonmouth (AVO), UK. We used standardized nesting traps to measure species richness and abundance of wild bees, and we recorded the heavy metal concentration in pollen collected by the red mason bee Osmia rufa as a measure of pollution. 3. The concentration of cadmium, lead and zinc in pollen collected by bees ranged from a background level in unpolluted sites [OLK: 1·3, 43·4, 99·8 (mg kg−1); AVO: 0·8, 42·0, 56·0 (mg kg−1), respectively] to a high level on sites in the vicinity of the OLK and AVO smelters [OLK: 6·7, 277·0, 440·1 (mg kg−1); AVO: 9·3, 356·2, 592·4 (mg kg−1), respectively]. 4. We found that with increasing heavy metal concentration, there was a steady decrease in the number, diversity and abundance of solitary, wild bees. In the most polluted sites, traps were empty or contained single occupants, whereas in unpolluted sites, the nesting traps collected from 4 to 5 species represented by up to ten individuals. Moreover, the proportion of dead individuals of the solitary bee Megachile ligniseca increased along the heavy metal pollution gradient at OLK from 0·2 in uncontaminated sites to 0·5 in sites with a high concentration of pollution. 5. Synthesis and applications. Our findings highlight the negative relationship between heavy metal pollution and populations of wild bees and suggest that increasing wild bee richness in highly contaminated areas will require special conservation strategies. These may include creating suitable nesting sites and sowing a mixture of flowering plants as well as installing artificial nests with wild bee cocoons in polluted areas. Applying protection plans to wild pollinating bee communities in heavy metal-contaminated areas will contribute to integrated land rehabilitation to minimize the impact of pollution on the environment.

Synthesis and evaluation of lipophilic BTBP ligands for An/Ln separation in nuclear waste treatment: the effect of alkyl substitution on extraction properties and implications for ligand design

Four new 6,6′-bis(1,2,4-triazin-3-yl)-2,2′-bipyridine (BTBP) ligands, which contain either additional alkyl groups on the pyridine rings or seven-membered aliphatic rings attached to the triazine rings, have been synthesized, and the effects of the additional alkyl substitution in the 4- and 4′-positions of the pyridine rings on their extraction properties with LnIII and AnIII cations in simulated nuclear waste solutions have been studied. The speciation of ligand 13 with some trivalent lanthanide nitrates was elucidated by 1H NMR spectroscopic titrations and ESI-MS. Although 13 formed both 1:1 and 1:2 complexes with LaIII and YIII, only 1:2 complexes were observed with EuIII and CeIII. Quite unexpectedly, both alkyl-substituted ligands 12 and 13 showed lower solubilities in certain diluents than the unsubstituted ligand CyMe4-BTBP. Compared to CyMe4-BTBP, alkyl-substitution was found to decrease the rates of metal-ion extraction of the ligands in both 1-octanol and cyclohexanone. A highly efficient (DAm > 10) and selective (SFAm/Eu > 90) extraction was observed for 12 and 13 in cyclohexanone and for 13 in 1-octanol in the presence of a phase-transfer agent. The implications of these results for the design of improved extractants for radioactive waste treatment are discussed.