Air cargo strategies

Introduction about a research project which categorized cargo airline’s strategy from a sample of 47 airlines from all over the world, using cluster analysis methodology to identify 7 different cargo strategies: 1) Cargos stars, 2) Large Pax wide-body operators, 3) Carpet sellers, 4) Premium air cargo operators, 5) Strong regionals, 6) Basic cargo operators and 7) Huge americans. For a successful Istanbul cargo hub he recommended to have a strong long haul passenger home cargo carrier with cargo strategy in place and focus on the growing parts of cargo as e-commerce.Dr. Dewulf, yaptığı bir araştırmada dünyadaki 47 havayolu şirketinden veriler toplayarak “küme analizi” yöntemiyle toplamda 7 farklı kargo stratejisi tanımlamıştır: 1) Kargo yıldızları, 2) Büyük yolculu geniş-gövdeli operatörler, 3) Halı satıcıları, 4) Ayrıcalıklı kava kargo operatörleri, 5) Güçlü bölgesel taşıyıcılar, 6) Temel kargo operatörleri ve 7) Büyük amerikalılar. İstanbul’un başarılı bir hava kargo merkezi olabilmesi için, iyi bir kargo stratejisiyle uzun menzilli yolcu ve kargo taşıyıcılığının birlikte yapılması gerektiğini ve kargo taşımacılığı için e-ticaretin gelişen bölümlerine ağırlık verilmesi gerektiğini vurguladı

The use of life cycle assessment as an early R&D decision tool: bottlenecks and potential solutions

At an ever increasing rate innovative chemistry and technology platforms are reshaping manufacturing environments to become factories of the future as being more productive, lean and flexible. The use of Life Cycle Assessment (LCA) in early process development phases has been challenged many times to assess whether or not this willingness to strive for innovation is an environmentally sustainable one. This paper provides general solutions to two major bottlenecks in applying LCA in R&D decision trees; (1) the lack of sufficient process data in early development phases and (2) the lack of knowledge on the effect of scale and learning on the environmental sustainability of a chemical product or process. The first issue is tackled with the use of multiple linear regression modeling, while for the second bottleneck the concept of deriving experience curves is proposed and illustrated. While this paper has taken a step in the direction of including LCA as a decision making tool in early process development phases, it stresses that more research should be conducted especially on Sustainable Supply Chain Management (SSCM), since it makes little sense to optimize in-house production without a proper procurement and Supply Chain Management (SCM)

Dynamic assessment of exposure to air pollution using mobile phone data

Background: Exposure to air pollution can have major health impacts, such as respiratory and cardiovascular diseases. Traditionally, only the air pollution concentration at the home location is taken into account in health impact assessments and epidemiological studies. Neglecting individual travel patterns can lead to a bias in air pollution exposure assessments. Methods: In this work, we present a novel approach to calculate the daily exposure to air pollution using mobile phone data of approximately 5 million mobile phone users living in Belgium. At present, this data is collected and stored by telecom operators mainly for management of the mobile network. Yet it represents a major source of information in the study of human mobility. We calculate the exposure to NO2 using two approaches: assuming people stay at home the entire day (traditional static approach), and incorporating individual travel patterns using their location inferred from their use of the mobile phone network (dynamic approach). Results: The mean exposure to NO2 increases with 1.27 mu g/m(3) (4.3 %) during the week and with 0.12 mu g/m(3) (0.4 %) during the weekend when incorporating individual travel patterns. During the week, mostly people living in municipalities surrounding larger cities experience the highest increase in NO2 exposure when incorporating their travel patterns, probably because most of them work in these larger cities with higher NO2 concentrations. Conclusions: It is relevant for health impact assessments and epidemiological studies to incorporate individual travel patterns in estimating air pollution exposure. Mobile phone data is a promising data source to determine individual travel patterns, because of the advantages (e.g. low costs, large sample size, passive data collection) compared to travel surveys, GPS, and smartphone data (i.e. data captured by applications on smartphones)

A preliminary field trial to compare control techniques for invasive Berberis aquifolium in Belgian coastal dunes

Non-native Berberis aquifolium is an invasive species in Belgian coastal dunes. With its strong clonal growth through suckers, this evergreen shrub outcompetes native species and affects dune succession. To prevent further secondary spread and mitigate its impact, there was an urgent need for knowledge on the effectiveness of control measures, both at the plant and habitat level. Here, we report on a first control experiment. Individual B. aquifolium clones were subjected to one of four treatments (manual uprooting, foliar herbicide application, stem cutting followed by herbicide or salt application), with regrowth being measured up to one year after treatment. We analyzed the relationship between kill rate, treatment, dune area, plant volume and number of plant stems using a generalized linear model. Berberis aquifolium plants proved most susceptible to foliar herbicide application (5% glyphosate solution), resulting in 88% (64%-97%) of the clones dying after treatment. The predicted kill rate decreased with an increasing number of stems under all treatments. We discuss the limitations of our experiment and the potential for actual field application of the different treatments. We present some guidelines for future control that may become further refined as experience builds up and we provide some recommendations for tackling invasive alien species in Atlantic dune ecosystems

Streamlining life cycle assessments: an emerging need for simplification

At an ever increasing rate innovative chemistry and technology platforms are reshaping manufacturing environments to become factories of the future by being more productive, lean and flexible. The use of Life Cycle Assessment (LCA) in early process development phases has been challenged many a time to assess whether or not this willingness to strive for innovation is an environmentally sustainable one, often due to a lack of process data. This study takes the streamlining of LCA one step further and proposes an optimal complexity of modelled product systems in terms of their optimal set of predictor variables. Out of more than 2,800 Basic Operations (BOs) in pharmaceutical synthesis steps, candidate predictor variables were identified to forecast the environmental burden (in this case natural resource consumption) of a production step per unit of output. By means of backwards stepwise linear regression modelling, combinations of candidate predictors were tested and evaluated based on their predictive power (R²) and the model uncertainty. It was proven that at least the amount of organic solvents used, the molar efficiency and the time duration of the synthesis step should be included in the model (R² = 0.87) as being the most significant predictor variables. Including additional predictors however imposes no guarantee to contribute to the predictive power and eventually weakens the model interpretation and its simplicity. The results of the study were evaluated in the light of the product-specific versus product group approach debate. Should LCAs be generalized to such an extent that an extensively diversified product group is to be represented with an averaged burden, while fairly simplified and streamlined methods can represent product-specific impact assessments with a reasonable need for data, time and knowledge? The trade-off between simplicity and accuracy will be dealt with quantitatively in the oral presentation. Ideally, an organization should be able to derive its environmental impacts from readily available Enterprise Resource Planning (ERP) data, linking supply chains back to the cradle of resource extraction, excluding the need for an approximation with product group averages. While this study has taken a step in that direction, more research should be conducted especially on how efforts towards sustainable development should be addressed with care to valorise them efficiently in the supply chain and its sectors, beyond any company borders