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• Used CT scanning and image processing technique to investigate pervious concrete. • Investigated the characteristics and calculated the equivalent diameter of pores. • Investigated the influence of the size of clogging particle and pores on clogging. • Optimized the design of pervious concrete to avoid clogging. Pervious concrete is one of the permeable pavement materials, which can improve the traffic safety and road environment. However, the clogging problem of pervious concrete is considered as a potential common deficient of the permeable pavement that causes severe loss of the ecological function. Generally, the main cause of clogging is the interlocking of the pores with clogging particles. Therefore, addressing the problem of clogging needs to explore the influence of pore characteristics and clogging particles on the pervious concrete. This study determined the equivalent diameter of pores through CT scanning and image processing using an algorithm code to calculate the geometry properties of the open and closed pores. Moreover, the variation of permeability after clogging has been analyzed. The experimental results showed that the pore size could determine whether clogging particles can block or pass through the pores or not, which is closely related to the clogging degree. Finally, the new findings can help engineers and designers to optimize the design of pervious concrete to forwardly avoid or mitigate the clogging problem, which has a promising realistic signification for permeable pavement design and maintenance. [ABSTRACT FROM AUTHOR]

Contract time is the maximum time allowed in the contract for the completion of the project scope of work. The allowed time must be enough for adequate completion and yet not too long that it delays the use of the project. The current practice of determining contract time relies heavily on completed plans and specifications. However, there is always the need to come up with contract time at different project phases when the plans and specifications are not yet complete. The objective of this research is to evaluate a conceptual method for determination of contract time using linear regression and the predictive quality of such method based on different project types. A predictive conceptual method will serve a purpose, especially when there is not enough time or information to develop a detailed schedule. The development of a linear regression based on Bromilow's Time-Cost (BTC) model could enhance state department of transportation (DOT) ability to make informed decisions on project feasibility and contract time. The ability to make such decision could save the agencies time and money. Based on the projects evaluated, the findings indicate that contract value (amount paid at completion) alone is not a good indicator of the contract time. The research suggests that a better predictor of contract duration could be arrived using standardized project types. In addition to cost, such classification will include project dimensions such as construction type, system type, material type, project location, complexity category, traffic control category, environmental assessment, and other factors. [ABSTRACT FROM AUTHOR]

Summary: An effective path planner is critical for autonomous traversal of unmanned ground vehicles (UGVs) in harsh environments. This paper describes a novel path planning method considering Bézier curves and a two-layer planning framework. In the two-layer framework, a road centerline (RCL) estimator located on the upper layer works as a global planner to obtain the local target for the bottom local planner. The RCL is estimated from a series of candidate Bézier curves based on a safety criterion. In the bottom layer, an optimal trajectory planner and a speed planner make up the local planner to obtain the desired steering turning angle and linear speed. The criteria for optimal trajectory selection are designed for comfortable driving. Road safety is considered in the speed planner for robust driving. Three sets of simulations are used to evaluate and quantify the relative performance of variations of our path planning algorithm. The proposed path planning method is implemented on a modified Polaris RZR 800 UGV, too. Two experiments based on this UGV are set up in the country road environment to demonstrate the viability of the proposed method. [ABSTRACT FROM AUTHOR]

• Road and roadside environment and risk perception are two factors affect speed limit credibility. • Credible speed limit can be set based on drivers' subjective and objective measurements. • A new five indicators can be used for deciding credible speed limit in a given road environment. • It provide a valid methodology to evaluate credibility which can be adopt for further research. • Curved road and road with cycle lane need lower speed limit because of potential risk presented. • Setting credible speed limit will help bring more compliance with speed limit. • Improving the credibility of the speed limit is better for speed management. There is now a body of literature on speed limit credibility, particularly in connection with speed management under the overall umbrella of "Safe Systems". However, there is rather little empirical work on the underlying factors that determine the credibility of speed limits and on how to enhance credibility for a given type of road. The study reported here aimed to investigate how factors such as road layout and the roadside environment together with drivers' perception of risk affect speed limit credibility. It also aimed to provide a measurement of speed limit credibility and how to set more credible speed limits to improve drivers' speed compliance. A picture questionnaire and a driving simulator in an automated condition in a simulator were adopted to obtain the measurements. The results suggest that certain road layout and environment features influence speed limit credibility. The research results show that five new indicators can be used as a reference for deciding on a credible speed limit in a given road environment: the most common choice of speed limit by drivers; the highest credible rating score value; indication of comfort with speed in automated driving; risk rating in the range from feeling safe to very safe; arousal indicated by skin conductance. Applying these indicators makes it possible to determine a limit that is credible for most motorists in a given road environment. Improving the credibility of a speed limit will lead to better speed management overall. [ABSTRACT FROM AUTHOR]

• Attitudes have stronger associations with bicycling to school than environments. • Active travel interventions are more likely to reduce chauffeuring than student driving. • Shorter distances and better travel environments associate with more walking and bicycling to high school. Although active travel to school for primary school students has been widely studied, research into the determinants of teenage active travel to school is noticeably lacking. Understanding the determinants of teen active travel to school is important given that teenage travel may have implications for the formation of habits that carry over to adulthood. We present evidence linking travel to school with bicycling attitudes and with road environments on plausible paths to school using data from a large cross-sectional survey of students at three high schools in Northern California. Results suggest that the relationship between attitudes and bicycling are stronger than the relationship between road environments and bicycling. Students' perceived social pressure to bicycle has a particularly strong association with bicycling. Hypothetical intervention scenarios suggest that students would walk and bicycle to school at substantially greater rates if they had better road environments for walking and bicycling, shorter distances to school, and more positive bicycling attitudes. [ABSTRACT FROM AUTHOR]

• Drivers' responses to silent automation failures were examined. • All drivers responded to all automation failures, despite no take-over requests. • NDRT engagement during automation resulted worse take-over behaviour. • More lane excursions, longer take-overs, and different distributions of visual attention. • Driver monitoring can detect drivers' attention to the driving task in automation. The aim of this study was to understand driver responses to "silent" failures in automated driving, where automation failed during a simulator drive, without a take-over warning. The effect of a visual non-driving related task (NDRT) and a road-based vigilance task presented drivers' take-over response and visual attention was also investigated. Currently, automated driving systems face a number of limitations that require control to be handed back to the driver. Much of the research to date has focused on explicit take-over requests (ToRs) and shows that drivers struggle to resume control safely, exacerbated by disengagement from the driving task, for instance, due to the presence of NDRTs. However, little is known about whether, and how, drivers will respond to more subtle automation failures that come without a warning, and how this is affected by NDRT engagement. Thirty participants drove a simulated automated drive in two conditions, which had 6 silent automation failures each (3 on a Curve, 3 in a Straight), with no ToRs. In one condition, drivers were required to constantly monitor the road, which was enforced by a road-based vigilance task (VMS Only). In the other, drivers performed an additional visual NDRT, requiring them to divide their attention (VMS + Arrows). Results showed that, in both conditions, all drivers eventually detected and responded to all silent automation failures. However, engaging in an additional NDRT during automation resulted in significantly more lane excursions and longer take-over times. Adding a visual NDRT not only changed the distribution of drivers' visual attention before and after the failure but also how they divided their attention between information on the road environment and the human–machine interface, which provided information on automation status. These results provide support for how driver monitoring systems may be used to detect drivers' visual attention to the driving task and surroundings, and used as a tool for encouraging driver intervention, when required. [ABSTRACT FROM AUTHOR]

• Greater feeling of risk at a given speed has an influence on feeling that speed limit is too high (less credible). • As drivers feel more risk in a given road environment, they might decrease their driving speed and obey the speed limit. • As the speed limit is more credible, drivers are more compliant with the speed limit. More credible speed limit can make speeding drivers slow down, especially extreme offenders. • For practical implications for road design, the research has provided advice to local highway authorities on matching credible speed limit to rural single carriageway infrastructure for potential safety improvement for road users. Driving speed is an important factor in road safety. Speed limit compliance is not only affected by the speed limit credibility, but is also related to driver's risk perception. This study investigates the relationship between the factors of risk perception, speed limit credibility and speed limit compliance for a given rural single carriageway road and roadside environment. Speed limit credibility, subjective risk perception and compliance with the speed limit were measured separately. To be specific, speed limit credibility was measured by speed limit rating score using a picture questionnaire. Subjective risk perception was measured by risk rating in an automated car driving simulator for a given speed and road environment. Speed limit compliance was measured by percentage of driving time spent below the speed limit in a simulated manual driving task with a given speed limit and road environment. Multilevel regression and logistic regression analysis demonstrate that risk perception has a positive influence on compliance with the speed limit. Credibility of speed limit has a positive influence on speed limit compliance. Risk perception has a negative influence on speed limit credibility. The research results can be used for guiding speed limit design and speed management. [ABSTRACT FROM AUTHOR]

This study developed and evaluated a visual approach to promoting environmental health literacy about highway pollution. The Interactive Map of Chinatown Traffic Pollution was the centerpiece of a communication approach designed to make complex scientific information about traffic-related air pollution comprehensible to Chinese immigrants with limited English proficiency. The map enabled visualization of the spatial distribution of ultrafine particles (less than 100 nanometers in diameter), a toxic and invisible form of air pollution, in Boston Chinatown. A university-community partnership enabled design of intergenerational training sessions aimed toward empowering community members to take health-promoting actions that reduce exposure to ultrafine particulate pollution. A mixed methods approach was taken to evaluation. Nine high school youth learned to use the map and then tutored adults recruited from English as a Second Language (ESL) classes and from a community workshop. Seventy-three of these adults completed a pre-post survey measuring change in three domains: pollution knowledge, attitudes toward environmental issues, and self-efficacy in using maps. Adult participants demonstrated statistically significant improvements in all three domains (Wilcoxon signed-rank test, all p < 0.01). Seventeen adults and nine youth participated in interviews. Interview participants reported adjusting daily routines to reduce exposure to pollution. [ABSTRACT FROM AUTHOR]

Abstract Most existing 3D object recognition methods still suffer from low descriptiveness and weak robustness although remarkable progress has made in 3D computer vision. The major challenge lies in effectively mining high-level 3D shape features. This paper presents a high-level feature learning framework for 3D object recognition through fusing multiple 2D representations of point clouds. The framework has two key components: (1) three discriminative low-level 3D shape descriptors for obtaining multi-view 2D representation of 3D point clouds. These descriptors preserve both local and global spatial relationships of points from different perspectives and build a bridge between 3D point clouds and 2D Convolutional Neural Networks (CNN). (2) A two-stage fusion network, which consists of a deep feature learning module and two fusion modules, for extracting and fusing high-level features. The proposed method was tested on three datasets, one of which is Sydney Urban Objects dataset and the other two were acquired by a mobile laser scanning (MLS) system along urban roads. The results obtained from comprehensive experiments demonstrated that our method is superior to the state-of-the-art methods in descriptiveness, robustness and efficiency. Our method achieves high recognition rates of 94.6%, 93.1% and 74.9% on the above three datasets, respectively. [ABSTRACT FROM AUTHOR]

Accurate acquisition of drivable area and obstacle information on field road is an important research for automatic navigation of intelligent agricultural machinery based on machine vision. In order to accurately identify field roads and its surrounding environment, an image semantic segmentation model of field road scene was proposed based on DCN (dilated convolutional neural network). Field roads in hilly regions are often twisted, windy and rolling, and occluded by different types of crops along both sides and many kinds of obstacles on the roads. Based on the analysis of image features of field roads in hilly regions, the field road scenes were divided into 11 categories in this paper: background, road, pedestrian, vegetation, sky, construction, livestocks, obstacle, pond, soil and pole. Based on a traditional FCN (fully convolutional neural network) of VGG-16 structure, the front-end module and context aggregation module in DCN were put forward by removing the part that wasn’t conducive to pixel prediction and restructuring a higher prediction-accuracy front-end module. The front-end module was improved based on the VGG-16. The pooling 4 and pooling 5 layers in VGG-16 were removed, and the three convolutions in Conv-5 were replaced by dilated convolution with expansion coefficient of 2, and the convolution Fc6 layer was changed to dilated convolution with an expansion coefficient of 4 to keep the receptive field unchanged. At the same time, the padding operation in the VGG-16 was deleted. The context module was a cascade of void convolution layers with different expansion coefficients and the first six layers were dilated convolutions with expansion coefficients of 1, 1, 2, 4, 8 and 16, respectively. Also two context module structure, namely Basic and Large, were proposed. The parameters of the constructed DCN could be initialized using the traditional VGG-16 network and produced higher resolution output. Then the two-stage training method was adopted to solve the problems of long training time and difficult convergence. In CAFFE (convolutional architecture for fast feature embedding) deep learning framework, the improved network models were constructed and compared with the classical FCN-8s network model. The FCN-8s network model, the network model constructed only with front-end module, and that with both the front-end module and context module (Basic and Large structure were used respectively) network model were tested. The adaptability of the network model constructed with both Front-end and context module with Large network to shadowed road images was verified better, namely the evaluation index of PA (statistical pixel accuracy), MPA (category average accuracy) and MIoU (mean intersection over union) of which were the highest. FCN-8s network model were the lowest in the evaluation index. Then the network model constructed with both Front-end and context module with Large network was used as the semantic segmentation model for field road scene. The MIoU of it was 73.4% in unshadowed road test dataset and it was only decreased by 0.2 percentage points in shadowed road test dataset. Moreover, the PA and MPA in unshadowed road test dataset and shadowed road test dataset were almost the same, respectively. The results showed that the improved model in this paper had good adaptability to the shadow disturbance of field road scenes in hilly regions. The proposed model has good generalization and robustness, which realizes the prediction of pixel level of field road image in hilly regions, and provides basic support for the autonomous navigation and obstacle avoidance of agricultural machines on field roads. [ABSTRACT FROM AUTHOR]

In this paper an on-road network of monitoring stations for the air quality is organized in order to provide data with high spatial resolution in a wide urban area. On this purpose a dedicated experimental set-up was developed in order to be installed on board of DHL courier vans. The monitoring station is completely automated and transmit continuously environmental data and positions during the daily route of the van. In order to aggregate data, the city map is partitioned into a grid of 1 km². The system is tested by comparing average concentrations with those of a fixed monitoring station. [ABSTRACT FROM AUTHOR]

Abstract An estimated 2.2 billion people in 108 countries are expected to survive on multidimensional poverty and almost 1.5 billion out of 2.2 billion people survived on or less than US$1.25 a day. This review highlights the concept of a green economy that promotes an attractive green revolution to the present economic crises affecting developing countries for sustainable economic and environmental improvement. Green roads and highways can reduce the emissions released from fossil fuels and greenhouse gases if constructed with carbon neutral materials. Thus, carbon neutral materials used for the construction of green roads and highways can absorb temperature and excess emissions released by the vehicles because of their neutralities. This is because of the massive quantity of natural aggregates used during construction. Problems associated with green roads and highways made from carbon neutral materials are incompatibles with land use, geology, topography, substructure, landscape, rainfall, and other physical features. Therefore, physical features, geology, landscape, transportation, and development substructures were measured as crucial problems for national development. Most of the approaches used in this study are based on the context of a green economy and the development of green roads and highways. The USA possesses the highest GDP per capita of US$52,194.90 and Bangladesh possesses the lowest GDP per capita of US$1029.60. This implies that the GDP for USA is 50.70 times higher than that of Bangladesh. The study highlights positive solutions to the above global challenges. It can be concluded that global challenges will be addressed through the concept of green revolutions. Highlights • To introduce carbon neutral materials for reduction of greenhouse gases in the construction industry. • To discover an attractive alternative to the present economic crises affecting developing countries. • To assess the degree of living standards and environmental vulnerabilities for sustainable life. [ABSTRACT FROM AUTHOR]

In this paper, the applicability of ground-based synthetic aperture radar (GB-SAR) as an early warning system for landslide monitoring is discussed. The effectiveness of the differential interferometric SAR (DInSAR) technique used in GB-SAR depends strongly on the geography of the monitored location. Therefore, an assessment of the system compatibility to select the most appropriate remote monitoring method is essential prior to any hardware implementation. In the preliminary part of this study, a 3D model was created using a LiDAR survey, and proposed locations for GB-SAR installation were examined. A 3D simulation was carried out to estimate the illumination from each of the proposed GB-SAR locations. The proposed model increased the efficiency of the GB-SAR positioning by minimising installation cost and time. Hardware configuration parameters, such as platform height, maximum range, and the direction and view angle of the radar line of sight were estimated by considering the optimum reflected power and ground illumination. Unlike on flat terrain, deployment of GB-SAR in a mountainous area is challenging because of surface anomalies and continuous changes in meteorological parameters, such as atmospheric temperature, pressure and relative humidity. In this study, the experimental site was located 3 km from the Aso volcano, and the weather conditions in the Aso caldera became a critical factor in accurately estimating the interferometric phase. The presence of atmospheric artefacts also compromises the applicability of the classical DInSAR technique. Here, we minimised the atmospheric phase screen by estimating the optimum data acquisition interval from GB-SAR monitoring under extreme weather conditions. The developed methodologies were then used to design a new landslide early warning system that measures real-time displacement over an area of 1 km2 within 10 s of scanning. This fully automatic monitoring system updates every 15 min and presents displacement information in a 3D interface. The system we have developed has been deployed for continuous monitoring of the mountainous environment of a road reconstruction site in Minami-Aso, Kumamoto, Japan where a large-scale landslide was triggered following the Kumamoto earthquake in 2016. [ABSTRACT FROM AUTHOR]

A robust control algorithm for tracking a wheeled mobile robot navigating in a pre-planned path while passing through the road’s roundabout environment is presented in this article. The proposed control algorithm is derived from both the kinematic and dynamic modelling of a non-holonomic wheeled mobile robot that is driven by a differential drive system. The road’s roundabout is represented in a grid map and the path of the mobile robot is determined using a novel approach, the so-called laser simulator technique within the roundabout environment according to the respective road rules. The main control scheme is experimented in both simulation and experimental study using the resolved-acceleration control and active force control strategy to enable the robot to strictly follow the predefined path in the presence of disturbances. A fusion of the resolved-acceleration control–active force control controller with Kalman Filter has been used empirically in real time to control the wheeled mobile robot in the road’s roundabout setting with the specific purpose of eliminating the noises. Both the simulation and the experimental results show the capability of the proposed controller to track the robot in the predefined path robustly and cancel the effect of the disturbances. [ABSTRACT FROM AUTHOR]

Roadworks take place frequently on existing roads in New Zealand. The adverse effects of poor road conditions and reduced road width due to the presence of a work zone on the safety of road users and workers at the work zone have been a matter of concern. Several studies have been conducted to examine the risk factors contributing to the occurrence of road crashes in work zones in different countries. Slow-moving and stopped vehicles near work zones have been found to be the primary cause of crashes and casualties in the work zones. Excessive speed of passing traffic has also been recognized as a crucial factor contributing to work zone related crashes in New Zealand. This study examined the effect of possible risk factors contributing to severe injury and fatality in work zone related crashes in New Zealand. A multinomial logistic regression model was established to determine the association between crash severity and factors such as road environment, vehicle attributes, driver behavior, and crash circumstances, based on the information available on 453 road crashes during the period from 2008 to 2013. The results indicated that the time period, vehicle involvement, and presence of vulnerable road users were the factors that determined the crash severity in work zones. This implies that improvements are required in traffic control and management measures in work zones to enhance road safety in the long run. [ABSTRACT FROM AUTHOR]

Abstract K-nearest neighbor (KNN) query algorithm based on road network plays an important role in location based service, which had been widely used in intelligent transportation, roadside assistance and other fields. However, as road network density increases and the number of points of interest increases, query efficiency decreases sharply.In order to improve the query efficiency, we adopted the MapReduce parallel computing framework to complete the query of K neighbor moving objects by designing Map, Reduce, Combiner and other functions. Before the start of the query, the road network was divided into pieces, and each fragment was calculated. The final K-nearest neighbor moving objects were obtained by aggregating the calculated results of each slice to realize the parallel optimization of KNN algorithm based on road network. The experimental results showed that the performance of parallel KNN algorithm based on MapReduce was better than that of serial KNN query algorithm in large-scale road network environment and the larger K value of query request. [ABSTRACT FROM AUTHOR]

While developing the projects for the construction of new and reconstruction of the existing roads, there is a probability of using privately owned land. In these cases, the mechanism of alienation of the private land plots is used to meet the public needs. Among the list of social needs, in the first place, there is a need for the land plots during construction, major repairs, reconstruction and maintenance of transport infrastructure objects, in particular roads. While designing the road construction and reconstruction projects, the technical-economic and transport-operational characteristics of the design object should be determined in conjunction with the protection of the environment and the rational use of natural resources. The article deals with the issues of assessing the impact of the road construction on the environment and the measures to reduce the level of pollution of the environment by introducing the environmental, technological, sanitary-technical and organizational measures. [ABSTRACT FROM AUTHOR]

The ‘road-effect zone’ is a concept developed to describe the impact of road construction on the surrounding area. Although many aspects of the road-effect zone have been investigated, the road-effect zone on soil properties (pH, bulk density, soil moisture, electrical conductivity, organic matter (%), C (%), total N (%), available Na, Ca, Mg, P, and K), light regimes (leaf area index and canopy cover), and a Raunkiaer’s life-form classification of plants remains poorly understood, especially in oriental beech (Fagus orientalis Lipsky) forests. Hence, the main aims of this research were to estimate the extent of the road-effect zone and to identify the main environmental changes due to forest roads. Specifically, we aimed to evaluate road-effects on: (1) the composition of herbaceous species and tree regeneration (up to 100 m distance from the forest road); (2) the light regime; and (3) soil properties, potentially related to changes in ecosystem functions and composition. We observed that forest roads can have significant impacts on soil, stand characteristics, and vegetation composition. The estimated road-effect zone extended up to 30 m from the road edge. Landscape planners should be aware that road-effect zones can potentially influence the ecology and environmental conditions of an area up to 30 m from the road edge. [ABSTRACT FROM AUTHOR]

Abstract Over the last decade, various rating systems and indicators have been proposed for evaluating or certifying roadway sustainability. However, there is no systematic method for the roadway projects to adopt the indicators of the rating systems to enhance sustainability for certification. This study developed a strategy for adopting indicators in a roadway rating system for sustainability certification. First, the framework and rules for prioritizing the indicators were established from literature review. Then, carbon emissions, costs, and the difficulties of employing the indicators were analyzed in a roadway case study. Finally, the priorities for adopting the indicators were determined. The results revealed that the indicators with higher score–unit ratios should have higher priorities in the project. By using the developed framework, the simultaneous analysis of multiple dimensions enables appropriate investigation into roadway sustainability problems. The score–unit ratio is a simple but effective metric to evaluate whether a project has incorporated appropriate indicators to enhance sustainability. Highlights • A strategy framework is proposed to adopt indicators for sustainability certification. • The framework helps engineers design and construct green roadways. • The framework looks at multi-dimensions to address sustainability issues of roadways. • This study goes beyond CO 2 e calculations to develop further applications. [ABSTRACT FROM AUTHOR]

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Highlights • Road developments have pervasive effects on seed dispersal and plant recruitment. • Seed (nut) dispersal effectiveness was greater nearer the road. • Consequently, high densities of trees and regeneration occurred closer to roads. • Contrary to these benefits, nut dispersal distances were shorter closer to roads. • Ever-expanding effect of roads may cause profound changes in plant communities. Abstract Currently, 43% of the world's terrestrial surface is within five kilometres of a road, and therefore understanding how road networks impact species and ecosystem processes is highly relevant to applied conservation ecology. Among various effects on wildlife, roads can disrupt the interaction between plants and their animal-mediated seed dispersers, compromising plant community composition and regeneration. Here, using the Chinese beech (Fagus engleriana) nut-rodent system, we quantified the extent to which rodent functions on seed dispersal were modified in habitats adjacent to roads. Compared to transects 200 m from the road, we observed approximately nine times greater seed dispersal effectiveness at transects 10 m proximity to the road and six times greater at 100 m from the road. Associated with this, high densities of seedlings, saplings and mature trees occurred closer to the road, suggesting that the road effect zone may facilitate plant recruitment. However, road proximity resulted in shorter nut dispersal distances, which did not support a benefit to plant recruitment. These counteractive effects may be caused by modified rodent behaviour in the vicinity of the road, and also by effects on rodent distribution and activity in relation to road-side habitat structure and environmental pressure. Crucially, no tagged seeds were dispersed across the road, implying that it imposed a barrier effect on animal-mediated seed dispersal and plant recruitment. We conclude that the ever-expanding effect of roads on zoochorous seed dispersal may ultimately cause profound changes in the structure of plant communities across diverse ecosystems, on a global scale. [ABSTRACT FROM AUTHOR]

Particulate matter (PM) originated by road transport constitutes an urgent task for megacities and pedestrians are supposed to be the first batch of innocent victims that exposed to and inhaled the polluted air. Footbridges have become a promising resolution to land tension, the location and design of them should be more considered in order to provide a more desirable walking system to pedestrians. In this study, three groups of PM [i.e., 0.3-0.9 μm (sub-fine), 0.9-2.5 μm (fine) and 2.5-10 μm (coarse)] were measured at different traffic scenario related footbridges (i.e., upstream of the on-ramp, downstream of the on-ramp, and signalized intersection) along an urban artery in Hong Kong, and their traffic volume composition, multifractality and cross-correlation behavior were investigated thereafter. Multifractal detrended fluctuation analysis and multifractal detrended fluctuation cross-correlation analysis were used simultaneously to quantify the persistency of different PM groups and interaction between them. The results indicate that although the particle concentration at intersection above footbridges presents the lowest, it has the highest emission rate and the strongest multifractality and cross-correlation behavior, especially the finer ones. Hence, it is suggest that the nature ventilation style of footbridges should avoid to be built above the signalized intersection due to the long persistency of particles and active interaction between different particle groups. [ABSTRACT FROM AUTHOR]

Abstract Understanding of the ecology of infected animals facilitates disease risk assessment and is also crucial for wildlife conservation. Relatively little is known about the spatial distribution of infected wild mammals in relation to environmental factors. In neighboring Mediterranean ecosystems 250 European brown hares (Lepus europaeus) were collected and examined with RT-PCR to detect European Brown Hare Syndrome Virus (EBHSV). Multivariate statistics and Geographical Information System (GIS) analysis were applied to estimate spatial patterns of biotic and abiotic factors and human activities as determinants of EBHSV positivity. Hare population abundance was estimated using faeces counts and belt drive censuses. The study showed that EBHSV infected hares had widespread distribution even in isolated areas. However, EBHSV infection prevalence was higher in areas with higher hare abundance, closer to paved road networks and at lower altitudes. The risk map revealed the potential distribution of EBHSV-infected hares. This study shows that host abundance and landscape influence the ecology of the disease, a finding that should be taken into account in future studies. The management of harvest and restocking of hares is also discussed for population conservation. [ABSTRACT FROM AUTHOR]

In order to understand the variation of air quality and the concentration of atmospheric particulates in Chengdu Second Ring Road renovation project, this paper starts to investigate the surrounding residents' opinions on the influenced environment and their daily lives via questionnaires. Then the study numerically simulates the change rule of atmospheric particulates in terms of time and space by using the Gaussian dispersion- deposition model and the compartment model. The optimized scientific scheme is selected by the improved fuzzy analytical hierarchy process (FAHP) to help decision making for the future urban reconstructions. Finally, the reduced emissions of atmospheric particulates are measured when the improvement scheme is provided. According to the study, it can be concluded that the concentration of atmospheric particulates increases rapidly in central Chengdu city during the renovation project, which results in worsening air quality in Chengdu during March 2012 to March 2013. Taking related measures on energy saving and emission reduction can effectively reduce the concentration of atmospheric particulates and promote economic, environmental and social coordination. [ABSTRACT FROM AUTHOR]

Local Government Authorities (LGAs) are typically responsible for roads outside a country’s strategic road network. LGAs play a key role therefore in facilitating the reduction of emissions from road traffic in urban areas, and must engage in emissions modelling to assess the impact(s) of transport interventions. Previous research has identified a requirement for road traffic Emissions Models (EMs) that balance capturing the impact on emissions of vehicle dynamics (e.g. due to congestion) against in-use practicality. This study developed such an EM through investigating the prediction of network-level carbon dioxide (CO 2 ) emissions based on readily available data generated by Inductive Loop Detectors (ILDs) installed as part of Urban Traffic Control (UTC) systems. Using Southampton, UK as a testbed, 514 GPS driving patterns (1 Hz speed-time profiles) were collected from 49 drivers of different vehicle types and used as inputs to an Instantaneous EM to calculate accurate vehicle emissions. In parallel, concurrent data were collected from ILDs crossed by vehicles during their journeys. Statistical analysis was used to examine relationships between traffic variables derived from the ILD data (predictor variables) and accurate emissions (outcome variable). Results showed that ILD data (when used in conjunction with categorisation of vehicle types) can form the basis for a practical road traffic CO 2 EM that outperforms the next-best alternative EM available to LGAs, with mean predictions found to be 2% greater than proxy real-world values. [ABSTRACT FROM AUTHOR]

This paper presents an analysis of data from a wind tunnel (Heist et al., 2009) conducted to study dispersion of emissions from three depressed roadway configurations; a 6 m deep depressed roadway with vertical sidewalls, a 6 m deep depressed roadway with 30° sloping sidewalls, and a 9 m deep depressed roadway with vertical sidewalls. The width of the road at the bottom of the depression is 36 m for all cases. All these configurations induce complex flow fields, increase turbulence levels, and decrease surface concentrations downwind of the depressed road compared to those of the at-grade configuration. The parameters of flat terrain dispersion models are modified to describe concentrations measured downwind of the depressed roadways. In the first part of the paper, a flat terrain model proposed by van Ulden (1978) is adapted. It turns out that this model with increased initial vertical dispersion and friction velocity is able to explain the observed concentration field. The results also suggest that the vertical concentration profiles of all cases under neutral conditions are best explained by a vertical distribution function with an exponent of 1.3. In the second part of the paper, these modifications are incorporated into a model based on the RLINE (Snyder et al., 2013) line-source dispersion model. While this model can be adapted to yield acceptable estimates of near-surface concentrations (z < 6 m) measured in the wind tunnel, the Gaussian vertical distribution in RLINE, with an exponent of 2, cannot describe the concentration at higher elevations. Our findings suggest a simple method to account for depressed highways in models such as RLINE and AERMOD through two parameters that modify vertical plume spread. [ABSTRACT FROM AUTHOR]

Efforts to protect nature are facing a growing crisis, one that often revolves around the burgeoning impacts of roads and other infrastructure on biodiversity and ecosystems. Potential solutions are possible but they will involve serious trade-offs and the confrontation of deep misconceptions. Here, I identify some time-critical tactics to aid scientists in informing and influencing the global infrastructure debate. [ABSTRACT FROM AUTHOR]

On-road mobile sources play a significant role in air quality modeling and these models require gridded, hourly emission inputs. Due to its geographical and meteorological diversity and stringent air quality regulations, California state always poses big challenge for air quality modelers and policy makers. At the same time, the impact of ambient temperature on vehicle emissions has been well researched in the past few decades and it is vital to prepare a reliable on-road gridded emission inventory for air quality modeling. This technical paper introduces a gridding method that takes temperature impacts into account, calculates emissions from grid-level to county, and attempts to quantify the likely effects of such a bottom-up, temperature sensitive approach on a gridded on-road emission inventory. To provide confidence in the proposed SMOKE-EMFAC method, a detailed analysis was carried out to compare the results with the default EMFAC output, and the results were within ±1%. Applying detailed grid level temperatures, we also found that criteria pollutant distributions are sensitive to them, and they are in accordance with previous US-EPA study. The proposed method could be very useful while testing different complex emission regulations and policies due to its inherent flexibility. [ABSTRACT FROM AUTHOR]

The concentration of heavy metals in urban road-deposited sediments (RDS) can be used as an indicator for environmental pollution. Thus, their occurrence has been studied in whole road dust samples as well as in size fractions obtained by sieving. Because of the limitations of size separation by sieving little information is available about heavy metal concentrations in the road dust size fractions <20 μm. In this study air classification was applied for separation of dust size fractions smaller than 20 μm from RDS collected at different times during the year. The results showed only small seasonal variations in the heavy metals concentrations and size distribution. According to the Geoaccumulation Index the pollution of the road dust samples deceased in the following order: Sb » As > Cu ≈ Zn > Cr > Cd ≈ Pb ≈ Mn > Ni > Co ≈ V. For all heavy metals the concentration was higher in the fine size fractions compared to the coarse size fractions, while the concentration of Sr was size-independent. The enrichment of the heavy metals in the finest size fraction compared to the whole RDS <200 μm was up to 4.5-fold. The size dependence of the concentration decreased in the following order: Co ≈ Cd > Sb > (Cu) ≈ Zn ≈ Pb > As ≈ V » Mn. The approximation of the size dependence of the concentration as a function of the particle size by power functions worked very well. The correlation between particle size and concentration was high for all heavy metals. The increased heavy metals concentrations in the finest size fractions should be considered in the evaluation of the contribution of road dust re-suspension to the heavy metal contamination of atmospheric dust. Thereby, power functions can be used to describe the size dependence of the concentration. [ABSTRACT FROM AUTHOR]

With expanding infrastructure, roads which as a main method of transport in inland areas have been increasing rapidly in developing countries. Their interconnectedness determines a city’s sustainability. To avoid using excessive indicators, this paper takes the Wu’an city as a study area to propose a system to assess the development of the road network that focuses on two indicators: one is the service ability which indicates the value of roads, and the other is landscape connectivity which is used to measure the roads influence on the environment. The results reveal that the density or length of roads is not the exclusive indicator used to determine service ability, while reasonable and effective road networks are also crucial elements. So the construction of roads should be explicit about the service objective. And the landscape connectivity used in this study not only reflects the effects of roads on ecological land but also recognizes important patches (whose landscape connectivity is high). According to the visible landscape connectivity changes, it’s demonstrated that road is interrelated with landscape connectivity. Where the road is, there will be worse landscape fragmentation and connectivity, especially in the neighboring areas. As the results show that the obvious impacts variations of landscape connectivity are almost focused on the habitat adjacent to the roads. The study also demonstrates how the results of such an analysis vary with species traits (dispersal capabilities) and shows that the probability of connectivity which contributes to the overall landscape connectivity increases with larger dispersal distances. It is suggested that a reasonable scale should be considered when measuring these influences. Our study provides a useful diagnosis and helpful information for assessing the road networks. This analysis can be further applied to judge whether road construction is worthy enough so as to promote the sustainable development of road transportation by creating a balance between the service ability and the influence on the ecological system. [ABSTRACT FROM AUTHOR]

In this paper, selecting 3 levels and 6 factors with an orthogonal test approach to investigate the stability of roadway surrounding rock under dynamic disturbance. The intuitive analysis results show that the main factors that affect the roadway deformation is period, followed by the location, lateral pressure coefficient, amplitude and buried depth,while the elastic modulus has a relatively small effect on it. With the increase of amplitude, period, depth and lateral pressure coefficient, the deformation of the roadway intensifies. With the increase of elastic modulus, the roadway deformation is first increases and then decreases. The farther the focal position, the smaller the roadway deformation. Combined with the engineering geological conditions of No. 11 Mine, using the micro-seismic monitoring curve to simulate the surrounding rock stability of No. 21222 interconnection, results show that the amplitude gradually decreases with the increase of the distance from the source. [ABSTRACT FROM AUTHOR]

The article discusses how building roads with wastes can deliver a heap of performance as well as environmental benefits. Topics discussed are the views of Fred Parrett on the use of waste material in the roads; chemical laws in European Union that made all chemical substances to be registered and assigned a CAS number before their use and road repairs; and challenges in designing an appropriate asphalt mixture for a chosen application in roads.

Linear infrastructures, one of several forms of land-use, are a major driver of biodiversity loss. Roads impact populations at many levels, with direct road mortality and barrier effect contributing to decreased population abundance, higher isolation and subdivision, and therefore to increased extinction risk. In this paper, we compared the effect of road mortality and of the barrier effect on population isolation, persistence and size, and assessed the interaction of these effects with dispersal. We used a spatially explicit, process-based model of population dynamics in landscapes fragmented by varying levels of road density. We modelled a barrier effect independently from road mortality by varying the probability with which individuals avoid crossing roads. Both road mortality and the barrier effect caused population isolation. While road mortality alone had stronger negative effects than the barrier effect without extra mortality, the latter also resulted in decreased population size. Yet, road avoidance could, in some cases, rescue populations from extinction. Populations with a large dispersal distance were more negatively affected as road mortality increased. However, when there was no road mortality they maintained larger sizes than populations with a short dispersal distance. Our results highlight the much higher relative importance of road mortality than the barrier effect for population size and persistence, and the importance of assessing relevant species traits for effective long-term transportation planning and conservation management. Our model can be used in species-specific situations and with real landscape configurations in applications such as conservation planning. [ABSTRACT FROM AUTHOR]

The effect of road location on natural and landscape elements is presented in this paper. Special care was focused on nature conservation areas located along three proposed road variants. Landscape metrics as a supplemental tool for selection of the most environmentally friendly road variant were here examined. The matrix method was used to analyse the potential negative effect of the road on the nature and landscape. Landscape metrics were found to be a very useful supplemental tool to evaluate the potential negative effect of the planned road on the environment. Moreover, based on our study we can also clearly relate this element to the effect on nature conservation elements. One of the most important features is the possibility to calculate certain metrics based on existing land use information without the need for field analyses, as well as obtaining specific values, which may be more objective than visual landscape assessment. [ABSTRACT FROM AUTHOR]

Winter chemical road maintenance has a significant negative influence on the environment. The application of chemical de-icing salts affects the trees growing near the road. Sodium and chlorine ions which are washed out into the environment are absorbed by the ambient vegetation; the increased concentration of these ions has a negative influence on the vegetation health. The determination of sodium and chlorine ions content in assimilative organs of conifers is used as a bioindicator of the impacts of winter chemical maintenance. The presented research paper evaluates the influence of the contamination potential on these ions content in needles of the Norway spruce ( Picea abies ). This species of spruce was chosen because of its abundant occurrence and heightened sensitivity towards salinization. The study was conducted in the north of the Czech Republic in the Liberec Region. To assess the damage potential of the winter chemical road maintenance, samples of the Norway spruce first- and second-year needles were collected and the sodium and chlorine ions concentrations were determined. At the same time, the research assessed the contamination potential of the region and the health condition of the analysed spruce trees. The results of ions concentrations (Na, Cl) were evaluated depending on four factors: the contamination potential, the health of the tree, the distance from the road and the age of the needles. Based on the evaluation of the results, a scale with framework concentration values was designed. This scale can be used for practical assessment of the degree of contamination. [ABSTRACT FROM AUTHOR]

The ongoing technological transformation, socially accepted and corresponding to the requirements, becomes relevant for regional development. Understanding this development requires an insight into the related driving forces. One of those, which has induced both direct and indirect changes to land use, and accelerated the urban growth, is the construction of motorways. Many studies have analysed the impact of motorway construction on changes in the landscape structure and urban land cover as well as in biological and landscape diversity, but relatively less attention has been paid to determining the impact of the infrastructure development on agricultural land and sustainable development of rural areas. We are of the opinion that applying hypotheses on infrastructure development (motorway construction) as a driving force derived from a case study can be a way of holding a more integrative view on regional sustainable development of rural areas, and can contribute to choosing the best variant of a motorway route. The aim of the paper is to present a theoretical framework and methodology for analysing the impact of a motorway on agricultural land and regional sustainable development. The change of land features and a decrease in their income value were determined by means of a simplified method. In the initial stage, it analyses the route of the motorway axis and determines the starting parameters, taking into account the width of the roadway, the category of lands taken over for the construction of the motorway, the layout (distribution) of plots, and the arrangement of existing roads and designed viaducts. The initial parameters were selected in order to ultimately enable the evaluation of the impact of the construction of the motorway on four main directions as well as the determination of the role of individual factors distinguished in this impact. The analysis provides a scientific basis for the understanding of sustainable development of rural areas and its protection in the spatial planning processes on local and regional levels. Establishing the changes of farms' value is necessary, among other things, to determine compensations for the losses caused by the motorway construction. It should be performed at the stage of elaborating the detailed design of the motorway, or immediately after completing the investment process. [ABSTRACT FROM AUTHOR]

Metals are indicators of contamination by anthropic activities, such as road traffic. To assess the extent of the metal contamination, more comprehensive studies analyzing different environmental matrices, such as soils, dust, and plants, collected in different sites that are potential sources of these pollutants along the highways, must be prioritized. Samples of soils, dust, and plants were collected alongside the highways of Brazil at 20 sites selected in strategic locations of metal accumulation (Cr, Pb, Zn, As, and Sb) or different situations of the high ways during two rain conditions (wet and dry weeks of sampling): nearby gutters and water supplies, tolls, petrol stations, a federal road police station, and areas associated with agriculture (yearly culture planting upstream of the highway). The geoaccumulation index (metal concentration in the sample of interest/background) varied from 0 to 6, and the decreasing order of contamination by metals during the wet and dry periods were, respectively: Zn > As > Pb = Sb > Cr and Zn > As > Pb > Cr > Sb. In the soils near the highways, the highest concentrations of metals were as follows (mg kg−1): As = 15.6, Cr = 81.9, Pb = 39.7, Sb = 5.0, and Zn = 379.3. The highest amounts of these elements in the most superficial layer in soils indicated their addition through atmospheric emissions. The most prominent metal was Sb, whose concentration was greater than the quality limits for soils. The concentration of Sb in soils was higher in the wet week than in the dry week. The emissions from road traffic promoted the increase in metals in the dust on the track, especially Zn and Pb. The highest metal concentrations in grasses (Brachiaria) were found in the roots, except for Sb and Zn, which suggests leaf absorption of atmospheric deposition. Metal contamination was widespread in all studied matrices along the highways. [ABSTRACT FROM AUTHOR]

Roads and trails bring deteriorating changes in the structure and composition of forests. The present study investigated the impact of roads and trails on floral diversity and structure of Ganga Choti forest, Kashmir. Phytosociological attributes using systematic quadrate sampling were recorded and analyzed using multivariate ordination techniques including Principal Component Analysis and Cluster Analysis. The total number of species found in the area was 101 belonging to 47 plant families. The dominant family was Poaceae followed by Labiateae, Asteraceae and Rosaceae. The dominant species of the area included Pinus wallichiana, Abies pindrow, Viburnum grandiflorum, Sarcococca saligna, Poa alpina, Fragaria nubicola, Onychium japonicum and Poa pratensis. The dominant life form was Hemicryptophyte (31.68 %), whereas leaf spectra class was Microphyll (30.69 %). The average diversity value was 3.39 with a maximum of 3.71 at the control site and 3.08 at the disturbed site. Average tree density was 505/ha with a maximum of 680/ha at the control site and a minimum of 330/ha at the disturbed site. Intense deforestation was indicated by a stump density value of 330/ha. Results revealed that roads and trails have adversely affected the composition and structure of vegetation with high pressure on keystone tree species. Disturbed sites showed lower values of diversity indices, species richness and regeneration synchronized with high deforestation, overgrazing, erosion and increased frequency of invasive species. The study area needs immediate attention of the management for conservation of local forests by minimizing the impacts of roads and trails. [ABSTRACT FROM AUTHOR]

A decade after the implementation of the Plan for the Area of Influence of the BR 163 - Santarém- Cuiabá Highway, defined as strategic by the federal government for the socioeconomic and environmental development of the Amazon, we tried to show in this article results observed through the economic dynamics in the cities of Santarém, Itaituba, Novo Progresso and Sinop, in the states of Pará and Mato Grosso. These cities integrate, in strategic positions, the design of the great multimodal transport corridor in which the highway was transformed. State investments in infrastructure, associated with private enterprise, are especially aimed at the mining and agribusiness sectors, which are very attractive to the transnational interests of the globalized economy, which have promoted profound social and environmental impacts on the road. The approach places actions that began with the BR-163 Plan, the Growth Acceleration Program, PAC I and II, and the Investment Logistics Program (PIL), to show how these instruments are at the service of a developmental logic that is based on colonial relations. We revisit analyzes of the postcolonial field, as well as demographic, deforestation and economic production, to understand the social conflicts that have been aggravating in recent processes, in the multiple frontiers that intersect in BR-163. [ABSTRACT FROM AUTHOR]

Mobile LiDAR Scanning (MLS) can collect 3-dimensional (3D) road and road-related geospatial information accurately and efficiently. Pole-like objects located in road environment are important street furniture and they are necessary information in road inventory and road mapping. The automatic detection and classification of pole-like road objects from mobile LiDAR data can greatly reduce the cost and improve the efficiency. This paper provides a complete workflow for the detection and classification of pole-like road objects from mobile LiDAR data in motorway environment. The major workflow includes three steps: data preprocessing, pole-like road objects detection and pole-like road objects classification. In data preprocessing step, ground points are removed by an automatic ground filtering algorithm, and then off-ground points are clustered into segments and the overlapped segments containing pole-like road objects are further separated through an iterative min-cut based segmentation approach. In detection step, filters utilizing both prior and shape information are used to detect the target objects. In classification step, features of objects are calculated and classified using Random Forest classifier. Our method was tested on two datasets scanned in motorway environment, and the results showed that the Matthews correlation coefficient of the two datasets in detection step was 93.7% and 95.9% respectively and the overall accuracy of the two datasets in classification step was 96.5% and 97.9% respectively. [ABSTRACT FROM AUTHOR]

Motorways are often seen as intrusive to both landscape and soundscape, and recent studies on multisensory perception suggest that an integrated assessment of the environmental impacts is necessary. This paper investigates the effects of traffic condition, distance to road and background landscape on the perceived integrated impact of noise and visual intrusion of motorways, and explores if noise exposure can be a powerful indicator for the perceived integrated impact. Six traffic conditions, consisting of three levels of noise emission × two levels of heavy good vehicle percentage in traffic composition, two types of background landscape and three distances to road, were designed as experimental scenarios, and created using computer visualisation and edited audio recordings. A laboratory experiment was carried out to obtain ratings of perceived environmental quality of each experimental scenario. The results show that traffic volume as expressed by noise emission level strongly influenced the perceived integrated impact, whereas traffic composition did not make noticeable differences. Distance to road was the second most influential factor, followed by background landscape. A regression model using noise level at receiver position and type of background landscape as independent variables was developed and can explain about a quarter of the variation in the perceived integrated impact. [ABSTRACT FROM AUTHOR]

As interest grows in eco-friendly green transportation systems, transportation management agencies have focused on effectively mitigating vehicle emissions. Extensive research has been conducted to enhance the performance of transportation systems in terms of environmental compatibility. A novel feature of this study includes considering crash occurrences when analyzing near-freeway air quality. This study quantifies the impact of traffic crashes on vehicle emissions and the associated near-freeway air quality. Both crash data and vehicle detection systems (VDS) data, which were obtained in 2012 from a Korean freeway located in a densely populated urban area, were used to determine the impact of traffic crashes on near-freeway air quality. MOVES and CALPUFF were adopted to estimate freeway emissions and air dispersion for crash-involved and crash-free traffic conditions. The contributing factors that affect the severity of emission dispersion were identified by regression analyses. Results show a community near freeways within a 1-km radius of crash locations was affected by traffic-related air pollution exposure. The regression analyses also showed crash characteristics, and weather characteristics affect traffic-related air pollution exposure areas. Finally, this study proposed traffic-related public health strategies to mitigate air pollutants generated from crash occurrences on freeways. [ABSTRACT FROM AUTHOR]

Roads have a pervasive multi-faceted influence on ecosystems, including pronounced impacts on wildlife movements. In recognition of the scale-transcending impacts of transportation infrastructure, ecologists have been encouraged to extend the study of barrier impacts from individual roads and animals to networks and populations. In this study, we adopt an analytical representation of road networks as mosaics of landscape tiles, separated by roads. We then adapt spatial capture-recapture analysis to estimate the propensity of wildlife to stay within the boundaries of the road network tiles (RNTs) that hold their activity centres. We fit the model to national non-invasive genetic monitoring data for brown bears Ursus arctos in Sweden and show that bears had up to 73% lower odds of using areas outside the network tile of their home range centre, even after accounting for the effect of natural barriers (major rivers) and the decrease in utilization with increasing distance from a bear's activity centre. Our study highlights the pronounced landscape-level barrier effect on wildlife mobility and, in doing so, introduces a novel and flexible approach for quantifying contemporary fragmentation from the scale of RNTs and individual animals to transportation networks and populations. [ABSTRACT FROM AUTHOR]

As one of the largest energy consumers, the transport sector generated direct and indirect emissions which significantly affect the environment, accounting for approximately one-third of the total carbon emissions. While the major impacts are from transport energy use and emissions, very few studies attempted to examine the impacts from transport infrastructure, especially at a city or country level. This paper, taking Shenzhen in China (a fast developing megacity) as the case study, is specially designed to quantify the carbon footprint of the urban roads by using streamlined life cycle assessment method. For given years (ranged from 2004 to 2013), various activities of urban roads (e.g. newly planned road construction, maintenance of road in use, and road renovation and demolition) have been examined in this study. The results show that the total carbon footprint from urban roads in Shenzhen was 260 (±20) thousand tons CO 2 e in 2013. The major contributor was the materials use (embodied impact) from newly constructed roads, which accounts for 52.3% of the total carbon footprint, followed by the maintenance stage (24.3%). The eco-design process of road construction plays a vital role in achieving the effective carbon footprint reduction. These findings help to better understand the carbon footprint from urban roads in megacities, and provide useful inputs for policy making process in terms of identifying carbon reduction opportunities for the transport sector. In addition, the methodologies are useful for the quantification of carbon footprint in other cities of China and beyond. [ABSTRACT FROM AUTHOR]