Reviewing the carbon footprint analysis of hotels: Life Cycle Energy Analysis (LCEA) as a holistic method for carbon impact appraisal of tourist accommodation

This study discusses the potential for Life Cycle Assessment (LCA) to be utilized for the environmental assessment of tourism accommodation facilities, and their contribution to global carbon footprint. To demonstrate the viability of employing LCA in the hotel sector, its simplified derivative, Life Cycle Energy Analysis (LCEA), is applied to two tourism accommodation facilities in Poole, Dorset (UK) to quantify their CO₂ emissions. The results indicate that the reviewed hotels are less energy and carbon-intense than the tourism accommodation establishments reported in the literature. This may indirectly imply the continuous progress of hotel’s energy efficiency over time. The implications of the current energy use practices in the reviewed hotels are discussed and suggestions are made on how to further improve the energy performance and therefore cut the carbon footprint. Recommendations for hotel management and policy-making are developed to reduce the energy and carbon intensity of the hotel industry. A method for energy and carbon footprint analysis of outsourced laundries and breakfast services is also proposed.     

Comparison of Point Estimation Techniques in the Spatial Analysis of Radium-226, Radium-228 and Potassium-40 in Soil

Many environmental surveys require the implementation of estimation techniques to determine the spatial distribution of the variable being investigated. Traditional methods of interpolation and estimation, for example, inverse distance squared and triangulation often ignore features of the data set such as anisotropy which may have a significant impact on the quality of the estimates produced. Geostatistical techniques may offer an improved method of estimation by modelling the spatial continuity of the variable using semi-variogram analysis. The theoretical model fitted to the semi-variogram is then used in the assignation of weighting factors to the samples surrounding the location to be estimated. This paper outlines the results of a comparison between three common estimation methods, polygonal, triangulation and inverse distance squared and a geostatistical method, in the estimation of soil radionuclide activities. The geostatistical estimation method known as kriging performed best over a range of parameters used to test the performance of the methods. Kriging exhibited the best correlation between actual and estimated values, the narrowest error distribution and the lowest overall estimation error. Polygonal estimation was best at reproducing the data set distribution. Conditional bias was evident in all the methods, low values being over-estimated and high values being under-estimated.     

Potential for childhood lead poisoning in the inner cities of Australia due to exposure to lead in soil dust

This article presents evidence demonstrating that the historical use of leaded gasoline and lead (Pb) in exterior paints in Australia has contaminated urban soils in the older inner suburbs of large cities such as Sydney and Melbourne. While significant attention has been focused on Pb poisoning in mining and smelting towns in Australia, relatively little research has focused on exposure to Pb originating from inner-city soil dust and its potential for childhood Pb exposures. Due to a lack of systematic blood lead (PbB) screening and geochemical soil Pb mapping in the inner cities of Australia, the risks from environmental Pb exposure remain unconstrained within urban population centres.     

Site Sampling and Treatability Studies for Demonstration of WasteChem’s Asphalt Encapsulation Technology Under EPA’s SITE Program

ABSTRACT

Exposures from indoor environments are a major issue for evaluating total long-term personal exposures to the fine fraction (<2.5μm in aerodynamic diameter) of particulate matter (PM). It is widely accepted in the indoor air quality (IAQ) research community that biocontamination is one of the important indoor air pollutants. Major indoor air biocontaminants include mold, bacteria, dust mites, and other antigens. Once the biocontaminants or their metabolites become airborne, IAQ could be significantly deteriorated. The airborne biocontaminants or their metabolites can induce irritational, allergic, infectious, and chemical responses in exposed individuals.

Biocontaminants, such as some mold spores or pollen grains, because of their size and mass, settle rapidly within the indoor environment. Over time they may become nonviable and fragmented by the process of desiccation. Desiccated nonviable fragments of organisms are common and can be toxic or allergenic, depending upon the specific organism or organism component. Once these smaller and lighter fragments of biological PM become suspended in air, they have a greater tendency to stay suspended. Although some bioaerosols have been identified, few have been quantitatively studied for their prevalence within the total indoor PM with time, or for their affinity to penetrate indoors.

This paper describes a preliminary research effort to develop a methodology for the measurement of nonvi-able biologically based PM, analyzing for mold and ragweed antigens and endotoxins. The research objectives include the development of a set of analytical methods and the comparison of impactor media and sample size, and the quantification of the relationship between outdoor and indoor levels of bioaerosols. Indoor and outdoor air samples were passed through an Andersen nonviable cascade impactor in which particles from 0.2 to 9.0 um were collected and analyzed. The presence of mold, ragweed, and endotoxin was found in all eight size ranges. The presence of respirable particles of mold and pollen found in the fine particle size range from 0.2 to 5.25 um is evidence of fragmentation of larger source particles that are known allergens.     

Changes in sewage sludge carbon forms along a treatment stream

The behaviour and fate of macronutrients and pollutants in sewage sludge applied to the land are affected by the chemical composition of the sludge organic matter, which in turn is influenced by both sewage source and by sewage treatment processes. In this study, (13)C nuclear magnetic resonance (NMR) spectroscopy was used to characterise the organic matter of sludges collected at three different points along the treatment stream of a municipal sewage works with a domestic catchment. Sludge at the first point, an undigested liquid (UL) sludge, had a substantially different composition to the anaerobically digested (AD) and dewatered sludge cake (DC) materials, which were similar to each other. In particular, the UL sludge contained more alkyl C than the AD or DC sludges. All three sludges were found to contain mobile alkyl C that is poorly observed using the cross polarisation (CP) technique, necessitating the use of the less sensitive, but more quantitatively reliable direct polarisation (DP) technique to obtain accurate distributions of C types.     

Quantifying the effect of buffer zones,crop areas and spatial aggregation on the externalities of genetically modified crops at landscape level

The development of genetically modified (GM) crops has led the European Union (EU) to put forward the concept of ‘coexistence’ to give farmers the freedom to plant both conventional and GM varieties. Should a premium for non-GM varieties emerge in the market, ‘contamination’ by GM pollen would generate a negative externality to conventional growers. It is therefore important to assess the effect of different ‘policy variables’ on the magnitude of the externality to identify suitable policies to manage coexistence. In this paper, taking GM herbicide tolerant oilseed rape as a model crop, we start from the model developed in Ceddia et al. [Ceddia, M.G., Bartlett, M., Perrings, C., 2007. Landscape gene flow, coexistence and threshold effect: the case of genetically modified herbicide tolerant oilseed rape (Brassica napus). Ecol. Modell. 205, pp. 169–180] use a Monte Carlo experiment to generate data and then estimate the effect of the number of GM and conventional fields, width of buffer areas and the degree of spatial aggregation (i.e. the ‘policy variables’) on the magnitude of the externality at the landscape level. To represent realistic conditions in agricultural production, we assume that detection of GM material in conventional produce might occur at the field level (no grain mixing occurs) or at the silos level (where grain mixing from different fields in the landscape occurs). In the former case, the magnitude of the externality will depend on the number of conventional fields with average transgenic presence above a certain threshold. In the latter case, the magnitude of the externality will depend on whether the average transgenic presence across all conventional fields exceeds the threshold. In order to quantify the effect of the relevant ‘policy variables’, we compute the marginal effects and the elasticities. Our results show that when relying on marginal effects to assess the impact of the different ‘policy variables’, spatial aggregation is far more important when transgenic material is detected at field level, corroborating previous research. However, when elasticity is used, the effectiveness of spatial aggregation in reducing the externality is almost identical whether detection occurs at field level or at silos level. Our results show also that the area planted with GM is the most important ‘policy variable’ in affecting the externality to conventional growers and that buffer areas on conventional fields are more effective than those on GM fields. The implications of the results for the coexistence policies in the EU are discussed.