My_Atmos: Novel Method to Analyse Ultrafine Particles Using an Artificial Intelligence Approach

This presentation will discuss the used of an artificial intelligent method namely the ‘stochastic boosted regression trees’ (BRT) approach that uses an algorithm that applied to an air pollution data namely particle number count concentrations ([PNC]), an ultrafine particles data and particulate matter data case study in United Kingdom and Malaysia. The development of the BRT model involves determining the model algorithm settings of the main model input parameters (learning rate, number of trees and interaction depth) that were tested using the R software (version 3.02) by choosing a10-fold cross-validation approach with combination of lr 0.05 and tc 5 of training set for BRT models. It was found, that the coefficient of determination (R2) value for the BRT best iteration models were above 0.60 for [PNC] in urban environment. The fine and course particle number (FPNC and CPNC) were found to be 0.75 and 0.72 respectively for one of coastal dataset while R2 value of 0.78 and 0.85 were obtained for Malaysia data. Further investigated were performed to rank factor influenced. It was found, that Carbon monoxide (30.28 %) gas and followed by temperature (16.81%) and wind direction (16.4%) were found the high factor influenced PM10 in urban environment. The interaction index (H-index) between parameters to concentration of pollutants were also examined graphically and in numerical form (H-Index). It was found that the H-Index between parameters 0.3 to 0.4 indicated that the BRT technique able to explain the science of air pollution. The consistent results to produce the best model from the best iteration, able to rank the best parameters that influence most to the concentration of predictor and able to predict interaction between variables premise BRT as one of the method or tools to analyse air pollution data

The individual as the key-stakeholder of Next Generation Infrastructure: Defining the social value of transport infrastructure in the United Kingdom

The idea of social value has arisen from the psychological approach, and more specifically it is based on the principle of “independence of irrelevant alternatives” from the game theory introduced by Luce and Raiffa1. According to this, each alternative situation has an utility/value for the individual, which is a function of the features of the alternative situation and of the features of the individual who makes the choice. Beyond that, it assumed that the individual, who makes the choice, has a clear and measurable knowledge of the value, which each choice provides. Although even after the evaluation of each choice, it is a tentative situation regarding the choice of the individual. In other words, there is an element of possibility. Under the same principle of Luce and Raiffa, the possibility of a choice is in direct ratio to its value. The above mentioned assumptions constitute the “strict utility choice mode”. The exponential form of the value function is achieved by simple transformations of the “strict utility choice mode”,where X and S have a linear correlation. The exponential functions of the total value have a sigmoid form relative to the linear function of the value of the possible choice. This means that the exponential function may have a sigmoid form relative to the X-axis or Y-axis, based on the defined axes and values. The key challenge addressed is a quantitative sense of value, when the perceptions of value are qualitative. To measure social value quantitatively is challenging, since it is observed that pricing systems are “not based primarily on the users’ identity or activity”, but on the ability and willingness of the final user to pay. The social value gained by the individual is difficult to calculate, since it is defined by human behaviour and human needs. According to Maslow's Hierarchy of Needs, these needs belong to specific groups with specific hierarchy. Maslow developed value (utility) curves of each category of need relative to the age of the individual. The sum of the curves gives an almost sigmoid curve. Winters et al. created a Transportation Hierarchy of Needs and they found the following transport hierarchy of needs: [1] safety and security, [2] time, [3] societal acceptance, [4] cost and [5] comfort and convenience. This research studied value as something holistically affected by all the above factors (time, cost, comfort and convenience, safety and security), without considering their ranking, by asking individuals representative of the UK’s demography to evaluate the social value of eight transport modes (walking, cycling, rail, bus, car, taxi, water and air) and each factor for each mode with a questionnaire survey. The hypothesis tested is that the value to the individual, collectively, from the aforementioned factors should have an almost sigmoid curve, which was verified

Transport Infrastructure Interdependencies with Energy, Water, Waste and Communication Infrastructure in the United Kingdom

The role of infrastructure interdependencies is challenging due to the complexity and dynamic environment of all infrastructures and vital for critical infrastructure systems. There is an ongoing debate about the value of the benefits of the five national infrastructure sectors (energy, water, transport, waste and communication) in the UK and how they interact in terms of social, economic and environmental wellbeing (Hall et al., 2016, p.10; iBUILD, 2015; Liveable Cities, 2015; National Infrastructure Plan, 2013). This study focuses only on one of the three aforementioned values, the economic value. The hypothesis tested is whether the transport sector is economically complemented by the energy, water and waste sectors and economically substituted by the communication sector. The authors use the process analysis “networks and cohorts”, an analysis that uses tables, diagrams, models and networks of interactions along with organizational linkages (Hill, 1993). Of interest for this study in particular is the grand total of all revenues (capital value) which create incomes into other sectors and creates dependencies. This, by definition, is the Gross Value Added. The last five symmetric (product by product) Input-Output tables of gross value added are used: 2010, 2005, 1995, 1990 and 1984 (Office for National Statistics, 2015). The theory underpinning the hypothesis was verified and one mathematical equation was developed based on the historical data of the gross value added by the value created in millions of pounds (£m) from the other critical sectors to transport

Next Generation Infrastructure Interdependencies: An economic deterministic model of transport interdependencies in the United Kingdom

The role of infrastructure interdependencies is challenging due to the complexity and dynamic environment of all infrastructures and vital for critical infrastructure systems. There is an ongoing debate about the value of the benefits of the five national infrastructure sectors (energy, water, transport, waste and communication) in the UK and how they interact in terms of social, economic and environmental wellbeing , . This study focuses only on one of the three aforementioned values, the economic value. The hypothesis tested is whether the transport sector is economically complemented by the energy, water and waste sectors and economically substituted by the communication sector1. The authors use the process analysis “networks and cohorts”, an analysis that uses tables, diagrams, models and networks of interactions along with organizational linkages . Of interest for this study in particular is the grand total of all revenues (capital value) which create incomes into other sectors and creates dependencies. This, by definition, is the Gross Value Added. The last five symmetric (product by product) Input-Output tables of gross value added are used: 2010, 2005, 1995, 1990 and 1984 . The theory underpinning the hypothesis was verified and one mathematical equation was developed based on the historical data of the gross value added by the value created in millions of pounds (£m) from the other critical sectors to transport

Developing pathways to low carbon land based passenger transport in Great Britain by 2050

The key aim of this paper is to examine strategic pathways to low carbon personal transport in Britain and to compare these with the current trajectory of transport policy. A 2050 baseline was established using trend information, forecasts and best evidence from the literature on response to policy intervention. A range of strategies are tested including: technological development, pricing, public transport and soft measures. We conclude that even dramatic technological advance cannot meet the more stringent targets for carbon reduction in the absence of considerable behavioural change. The most promising combinations of measures involve clear price signals to encourage both a reduction in the use of motorised transport and the development and purchase of more efficient vehicles; decarbonisation of public transport and facilitating measures to enhance access whilst reducing the need for motorised travel

What is a sustainable level of CO2 emissions from transport activity in the UK?

The paper reports on the development of UK transport targets for CO2 emissions for 2050. Five key studies containing future carbon emissions scenarios for the UK were used to establish targets for overall reductions in emissions to achieve stabilisation at 550 ppm and 450 ppm of atmospheric CO2. Two approaches were used to consider the proportion of total emissions that would be attributable to transport in the future: 26% of total emissions as now and an increase to 41% of total emissions in line with forecasts. The overall targets and expected contributions from transport were used to derive target emissions for the transport sector to be achieved by 2050, which ranged from 8.2 MtC to 25.8 MtC. Even the weakest of these targets represents a considerable reduction from current emissions levels

Infrastructure Management: Development of a Business Model for Transport Infrastructure Interdependencies Management

There is ongoing debate about the value of the benefits of infrastructure systems (specifically those of energy, water & wastewater, transport, waste, and communications) and how to prioritize infrastructure investments to encompass considerations of social, economic and environmental wellbeing. The use of the term ‘infrastructure system’ is related to interdependencies. Infrastructure systems operating in different countries and cities are interrelated in different ways, but all have a strong relationship to ‘transport’ – there is a cost and a utility associated with movement. Infrastructure systems are ultimately created to serve individuals, who place a value on them. In order to explore all forms of value realisation – what is commonly termed a business model – the relationship between an individual and the transport system needs to be established. The hypothesis being tested in this paper is that it is possible to identify both the full range of value interdependencies required, and hence to establish a robust business model, for transport infrastructure interdependencies management in terms of social, economic and environmental wellbeing with the other four national infrastructure sectors in the UK (see above). Different research methods were used for each type of value: economic and environmental value were analysed through Pearson correlation coefficient of secondary data, social value was analysed through statistical analysis (mean, median, mode) of primary data. The new business model challenges the monodirectional value creation of more traditional business models by considering the interdependent bidirectional value creation

The Environmental Value of Sustainable Transport Infrastructure

The climate change threat to humanity challenges the creation of sustainable transport infrastructure based on the triptych of balancing and maximising environmental, economic and social value. A piece of infrastructure may be created in a sustainable manner, but may be then subsequently used unsustainably, that would not be sustainable. In other words, sustainable transport infrastructure is linked with the use of the most sustainable transport choices. Environmental value may be defined by the natural and anthropogenic factors and elements which interact with and influence the natural ecosystem, quality of life, and human health and well-being. Emissions are a widely accepted way by the Food and Agriculture Organization of the United Nations to “calculate” environmental damaging actions. Emissions address the production of pollutants and the placement of waste into the environment. The target is to reduce the use of transport modes with high environmental impact (e.g. cars) and replace them with transport modes with low or no environmental impact (e.g. public transport, walking, cycling). The hypothesis tested is that each individual should be able to understand which transport mode is the most sustainable and investigate whether each individual will accept the use of alternative options that consume less energy and generate fewer emissions. The methodology used was statistical inference. The hypothesis regarding the individuals’ understanding was verified with some deviations and a table with the environmental infrastructure interdependencies was developed based on EXIOBASE 3 database using the emissions generated from each transport sector for comparison purposes