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The purpose of this paper is an investigation of driving behaviour and impacts on emissions at two traffic junctions.

A signalised junction and a roundabout in Edinburgh have been selected. An instrumented car has been used and a GPS to monitor driving activities as well as a gas analyser to monitor the vehicle's emissions during the evening peak hour.

Vehicles’ emissions are affected by a large number of factors including characteristics of the engine and the vehicle, characteristics of the road, the fuel used and driving behaviour.

Different methods and approaches have been used to investigate the behaviour of vehicles at various traffic junctions. The main aim, however, has mostly been to reduce travel times as well as traffic delays and queues at the junction. Consideration of environmental impacts has also been made, but often as a by‐product of congestion reduction and not as a main aim.

With the pressing need for environmental conservation, regulatory authorities are actively looking for measures to prevent global warming. In the proposed inventory model for deteriorating items, demand is dependent on the selling price and green technology investment (or carbon reduction investment) for the green product (GP), as well as an investment in price-based preservation technology to slow down the pace of deterioration. Furthermore, emission reduction measures are put in place to reduce carbon emissions (CEs).

The current study executed a thorough literature review to determine how to improve supply chain management performance. Furthermore, assumptions are made to fill research gaps, and a mathematical model is created to address the problem mentioned above. To collect the data, the available inventory literature was reviewed. Additionally, numerical illustrations and sensitivity analyses are presented to emphasize the model's robustness.

The research indicates that it is more prudent to invest in preservation technology based on its selling price in order to control the rate of deterioration. In addition, the proposed model facilitates the management of deteriorated waste through salvage trading and emission reduction investment. The findings validate sustainable practices with a 20.86% increase in profit and a 21.4% decrease in CEs, thereby signifying environmental and economic benefits.

The proposed model enhances understanding of the impact of investments in price-based preservation technology and carbon reduction efforts on consumer perceptions of their intention to purchase GPs. Moreover, the study provides valuable insights by identifying important recommendations for policymakers regarding areas that require further investigation. This guideline can help identify both current and unexplored gaps, enabling researchers to direct future research efforts toward producing new products.

In 2009, Newsweek published a report in which they ranked the 500 largest US companies and the 100 largest global companies based on its environmental performance measures (http://greenrankings2009.newsweek.com/). This ranking is referred to as Newsweek’s Green Ranking. Included in this ranking is information about water and air pollution, solid waste disposal, toxic wastes, carbon emissions, and enforcement actions. The question we are addressing in this study is how well it measures pollution performance? The question is relevant to environmental accounting/reporting since it is part of a dilemma yet to be answered: Aggregated environmental indices/scores are easy for average information users to percept, while specific information may not be preserved when it is aggregated into the overall score(s).

Specifically, we examine whether Newsweek’s Green Ranking is correlated with pollution measures based on Toxics Release Inventory (TRI) in order to determine how valid or reliable Newsweek’s Green Ranking is – in other words, how much Newsweek’s Green Ranking can explain the pollution by the toxic releases. We find that there is no significant correlation between Newsweek’s Green Ranking and the TRI measures except for the firms in the utilities industry. Concluding that on one measure, which we consider a very important one, there is no justification for the overall Green Ranking Score presented by Newsweek. However, in Newsweek’s three-part score the element that is termed the Environmental Impact Score captures pollution performance measured based on TRI. The contrast between the overall ranking and performance ranking indicates that a composite index that incorporates hard performance and soft measures can dilute the information carried by performance data.

Logistics companies are compelled to improve their efficiency and the environmental performance by introducing the green concept in their operations. The main purpose of the paper is to have continuous monitoring and tracking of logistics operations to enhance the green performance.

This research uses a case study approach. It illustrates a monitoring system to digitize the logistics activities by sending real-time GPS data to the server and capture the surrounding pictures with the help of the internet of things (IoTs) based camera. Data generated through digitization is mathematically analyzed for ensuring a green logistic system. The alerts due to the halts, help in keeping a check on fuel consumption, carbon emissions and security of logistics. Performance indicators such as carbon emissions and the value of travel time saving (VTTS) are selected for the study.

The findings of the study show that the actual travel time and distances are higher than the estimated travel time and distances. It also reveals that actual travel routes with diversions involve a considerably higher amount of carbon emissions during all sample travels. The results indicate a considerable saving in terms of carbon emissions, time and cost savings by effective practices of Green Logistics in Monitoring system (MSGL). These findings can help the top management of logistics companies in formulating effective strategies for technology applications in logistic operations to ensure green performance.

The study has been carried out under certain set of conditions, which may vary depending upon the organizations. Also certain more environmental dimensions for performance monitoring can be used as a future scope of study. Further studies also need to be carried out to widen the scope of the MSGL model at a global level rather than only at local level.

Any organization which deploys transportation as part of their activity can use this MSGL model and then do the mathematical analysis to reduce the CO₂ emissions, reduce the time and extra cost. The value of this study lies in the fact that government is trying different methods and models to reduce pollution. This MSGL should be made compulsory by the government as a part of their policies for environment of the country.

Construction activities, particularly related to transportation, have a considerable impact on the environment and air quality. This paper aims to present a geographic information systems (GIS) and computer‐aided design (CAD)‐based approach for visualizing, communicating and analysing greenhouse gas (GHG) emissions resulting from construction activities.

A methodology using GIS is developed to graphically represent spatial aspects of construction. The approach adopted involves use of a 3D model developed in CAD environment, which was synchronized with a construction schedule stored in Excel spreadsheets. GIS environment is used to link spatial and scheduling information relevant to GHG emissions from construction activities. A baseline was created to enable effective monitoring of construction emissions.

The presented GIS model has the potential to enhance visualisation of distribution and dynamic variations of GHG emissions and could help stakeholders better analyse and understand how construction activities impact the environment.

This paper presents a novel method of graphically presenting GHG and other hazardous air emissions from construction activities using a GIS‐based approach. The paper presents the result of comparing the 3D surface representation of simulated estimated and actual construction emissions to show the impact of construction activities on the environment to support the engineering analysis and decision‐making process.

Purpose — In this paper we describe a total design data collection method (expanding the definition of the usual “total design” terminology used in typical household travel surveys) to emphasize the need to describe individual and group behaviors embedded within their spatial, temporal, and social contexts.

Methodology/approach — We first offer an overview of recently developed modeling and simulation applications predominantly in North America followed by a summary of the data needs in typical modeling and simulation modules for statewide and regional travel demand forecasting. We then proceed to describe an ideal data collection scheme with core and satellite survey components that can inform current and future model building. Mention is also made to the currently implemented California Household Travel Survey that brings together multiple agencies, modeling goals, and data collection component surveys.

Findings — The preparation of this paper involved reviewing emerging transportation modeling approaches and paradigms, policy questions, and behavioral issues and considerations that are important in the multimodal transportation planning context. It was found that many of the questions being asked of policy makers in the transportation domain require a deep understanding of the interactions and constraints under which individuals make activity-travel choices, the learning processes at play, and the attitudes and perceptions that shape ways in which people adjust their travel behavior in response to policy interventions. Based on the work, it was found that many of the traditional travel survey designs are not able to provide the comprehensive data needed to estimate activity-based model systems that truly capture the full range of behavioral considerations and phenomena of importance.

Originality/value of paper — This paper offers a review of the emerging transportation modeling approaches and behavioral paradigms of importance in activity-based travel demand forecasting. The paper discusses how traditional travel survey designs are inadequate to meet the data needs of emerging modeling approaches. Based on a review of all of the data needs and new data collection methods that are making it possible to observe a full range of human behaviors, the paper offers a total survey data collection design that brings together many different surveys and data collection protocols. The core household travel survey is augmented by a full slate of special purpose surveys that together yield a rich behavioral database for activity-based microsimulation modeling. The paper is a valuable reference for transportation planners and modelers interested in developing data collection enterprises that will feed the next generation of transportation models.

This paper explains the modelling of emission in real world onboard measurement under local driving condition for engine size 1000cc and 600cc for motorcycles in Edinburgh. Impact of instantaneous speed, acceleration on emission have been investigated on the air quality management area (AQMA) in Edinburgh. Emission directly observed from the analyser have been converted from ppm and % unit into gm/sec by using the fuel consumption estimates and carbon mass balance equation Finally average emission factors for CO, HC, and NOX along the corridor have been estimated on time based (gm per second) and distance based (gm/km). Since emissions are primarily affected by speed, therefore a correlation between emission factors and speed have been developed. Onboard emission measurements have advantages to collect the emission data into different driving cycle i.e. vehicle operating modes (idling cruise, acceleration, and deceleration). This has been further investigated by developing the relationship between time spent in these modes and emission. These types of models are suitable, in sustainable development of transportation system, traffic demand management, signal coordination, and environment friendly application for Intelligent Transportation System (ITS).

This paper investigates how a regulator pursuing social welfare maximization designs an optimal subsidy scheme to stimulate technology innovation in the presence of a consumer green premium. Specifically, the authors solve the following questions: (1) Does the consumers' green premium affect the design of the subsidy scheme? (2) How should the firm choose a green technology innovation strategy under the optimal subsidy scheme? (3) Does technology innovation bring higher social welfare and lower environmental impact?

The authors first develop a game model to explore the impact of subsidy schemes on social welfare without considering technology innovation. Then the authors investigate two innovation strategies, in-house innovation and external introduction, under the optimal subsidy scheme. Finally, they illustrate the optimal choices of innovation strategy for the firm, consumers and regulators.

The results reveal that the subsidy scheme will not always increase social welfare, which depends on the environmental improvement coefficient of the unit green level. The optimal subsidy level increases with the green premium, but it is not related to the size of the consumer green segment. Moreover, the success rate of in-house innovation will raise the optimal green level, but the company benefits from an increased success rate of in-house innovation only when the green segment is large enough. The green segment size and external green level jointly determine the choice of technology innovation strategy.

This research is the first to analyze this problem while considering the green demand and subsidy scheme simultaneously as drivers of a firm's technology innovation, thereby providing new managerial implications for decisions by the regulator and firms.