An empirical analysis of the influence of urban form on household travel and energy consumption

Using the 2001 National Household Travel Survey (NHTS) data, this paper empirically examines the effects of urban land use characteristics on household travel and transportation energy consumption in the Baltimore metropolitan area. The results of regression analysis show that different built environment measures lead to substantially different findings regarding the importance of urban form in influencing travel behavior. Among the built environment variables used in the analysis, accessibility provides much more explanatory power than density, design and diversity measures. Moreover, this study explores approaches to modeling the connection between urban form and household transportation energy consumption. Applying Structural Equation Models (SEMs), we found that urban form does not have a direct effect either on VMT or on vehicle energy consumption. The indirect effect, however, is significant and negative, which suggests that urban form affects household travel and energy consumption through other channels. In addition, household socio-economic characteristics, such as gender and number of vehicles, and vehicle characteristics also show significant relationships between VMT and energy consumption. This empirical effort helps us understand the major data and methodology challenges.     

Optimization of machining processes from the perspective of energy consumption: A case study

One of the primary objectives of sustainable manufacturing is to minimize energy consumption in its manufacturing processes. A strategy of energy saving is to adapt new materials or new processes; but its implementation requires radical changes of the manufacturing system and usually a heavy initial investment. The other strategy is to optimize existing manufacturing processes from the perspective of energy saving. However, an explicit relational model between machining parameters and energy cost is required; while most of the works in this field treat the manufacturing processes as black or gray boxes. In this paper, analytical energy modeling for the explicit relations of machining parameters and energy consumption is investigated, and the modeling method is based on the kinematic and dynamic behaviors of chosen machine tools. The developed model is applied to optimize the machine setup for energy saving. A new parallel kinematic machine Exechon is used to demonstrate the procedure of energy modeling. The simulation results indicate that the optimization can result in 67% energy saving for the specific drilling operation of the given machine tool. This approach can be extended and applied to other machines to establish their energy models for sustainable manufacturing.     

Synthesising carbon emission for mega-cities: A static spatial microsimulation of transport CO2 from urban travel in Beijing

Developing low carbon cities is a key goal of 21st century planning, and one that can be supported by a better understanding of the factors that shape travel behaviour, and resulting carbon emissions. Understanding travel based carbon emissions in mega-cities is vital, but city size and often a lack of required data, limits the ability to apply linked land use, transport and tactical transport models to investigate the impact of policy and planning interventions on travel and emissions. Here, we adopt an alternative approach, through the development of a static spatial microsimulation of people’s daily travel behaviour. Using Beijing as a case study, we first derive complete activity-travel records for 1026 residents from an activity diary survey. Then, using the 2000 population census data at the sub-district level, we apply a simulated annealing algorithm to create a synthetic population at fine spatial scale for Beijing and spatially simulate the population’s daily travel, including trip distance and mode choice at the sub-district scale. Finally, we estimate transport CO₂ emission from daily urban travel at the disaggregate level in urban Beijing.     

Quality of location-based crowdsourced speed data on surface streets: A case study of Waze and Bluetooth speed data in Sevierville,TN

Obtaining accurate speed and travel time information is a challenge for researchers, geographers, and transportation agencies. In the past, traffic data were usually acquired and disseminated by government agencies through fixed-location sensors. High costs, infrastructure demands, and low coverage levels of these sensor devices require agencies and researchers to look beyond the traditional approaches. With the emergence of smartphones and navigation apps, location-based and crowdsourced Big Data are receiving increased attention. In this regard, location-based big data (LocBigData) collected from probe vehicles and road users can be used to provide speed and travel time information in different locations. Examining the quality of crowdsourced data is essential for researchers and agencies before using them. This study assessed the quality of Waze speed data from surface streets and conducted a case study in Sevierville, Tennessee. Typically, examining the quality of these data in surface streets and arterials is more challenging than freeways data. This research used Bluetooth speed data as the ground truth, which is independent of Waze data. In this study, three steps of methodology were used. In the first step, Waze speed data was compared to Bluetooth data in terms of accuracy, mean difference, and distribution similarity. In the second step, a k-means algorithm was used to categorize Waze data quality, and a multinomial logistics regression model was performed to explore the significant factors that impact data quality. Finally, in the third step, machine learning techniques were conducted to predict the data quality in different conditions. The result of the comparison showed a similar pattern and a slight difference between datasets, which verified the quality of Waze speed data. The statistical model indicates that that Waze speed data are more accurate in peak hours than in night hours. Also, the traffic speed, traffic volume, and segment length have a significant association on the accuracy of Waze data on surface streets. Finally, the result of machine learning prediction showed that a KNN method performed the highest prediction accuracy of 84.5% and 82.9% of the time for training and test datasets, respectively. Overall, the study results suggest that Waze speed data is a promising data source for surface streets.     

Estimation of methane and nitrous oxide emissions from biomass waste in China:A case study in Hebei Province

Crop residue,animal manure and MSW are selected as representative biomass waste.Greenhouse gas emissions from treatment and disposal process of biomass waste in Hebei province are estimated for the period from 2002 to 2007,using the methodologies recommended by the Intergovernmental Panel on Climate Change.Greenhouse gas emission was about 10 Mt CO2-equivalent annually.About 6% of greenhouse gas emission came from open burning of crop residue,74% from management system of animal manure,and 20% from MSW disp...     

A prediction approach of SLM based on the ensemble of metamodels considering material efficiency,energy consumption,and tensile strength

Journal of Intelligent Manufacturing - As a rapid developing additive manufacturing (AM) technology, selective laser melting (SLM) provides a promising way for intelligent manufacturing. The SLM...     

Simulating the urban spatial structure with spatial interaction: A case study of urban polycentricity under different scenarios

Polycentric urban development is gaining momentum in both scholarly research and real-life practice. This brings new demand for planning support systems to simulate and analyse the urban spatial structure in terms of polycentricity under various urban policy scenarios. With the help of emerging urban data, urban simulation techniques, and network science, this study proposes a workflow to simulate the urban spatial structure with spatial interaction as a part of the planning support system. Using Singapore as a case study, this study has explored the resulting urban spatial structure with four employment distribution strategies. The results suggest that planning practices impact urban spatial structure and its spatial interaction by redistributing urban morphological elements, such as employment in this study. Also, our results show that the physical urban spatial structure and spatial interaction are closely related. These results reinforce the role of urban planning practice to achieve a more sustainable and coherent urban built environment. Through this empirical evidence, our workflow exemplifies the potential of the planning support system to help urban planners and governments understand their urban policy regarding urban polycentricity.     

Simulation of safety-critical,real-time Java: A case study of dynamic analysis of scoped memory consumption

For critical, real-time applications, scoped memory management in Real-Time Specification for Java (RTSJ) achieves a level of predictability not found in applications that use garbage collection techniques. However, a scoped memory model creates new challenges for developers. First, the reference rules between scopes constrain the design of the application’s memory model. Second, there is no abstract model for scoped memory that can be applied to different applications. Third, deciding on the appropriate number of scopes and which objects or threads should be allocated into those scopes are not straightforward tasks and require tools to assist. This paper presents a simulation of a railway control system executed on the Sun RTS2.2 virtual machine; it illustrates how simulation of critical safety real-time applications in Java can be used to investigate the implementation of possible scoped memory design models and their memory consumption in multi-threaded environments. The simulation demonstrates that a developer is able to compare and choose the most appropriate scoped memory design model that achieves the least memory footprint. Results showed that the memory design model with a higher number of scopes achieved the least memory footprint. However, the number of scopes per se does not always indicate a satisfactory memory footprint; choosing the right objects/threads to be allocated into scopes is an important factor to be considered.     

Modeling and forecasting of daily online-user movement in instant messaging based on the elliptic-orbit model: A case study for China

Instant Messaging (IM) has been an effective, popular and important mode for immediate communication in the digital age. Then analysis of daily user-online movement in IM is increasingly important for its significant effect on information propagation, commercial operation, resource allocation and maintenance management. In this study, the so-called elliptic orbit model is proposed to describe daily user-online movement in IM by mapping its time-series into the polar coordinates to establish the elliptic orbit model, in which each 24-hour movement is depicted as one elliptic orbit. Experiments in the most popular IM service in China called the Tencent QQ and result analysis indicate potentiality of the proposed method. It is shown that the daily 24-hour user-online movement in IM is well described by the elliptic orbit model, which provides a vivid approach for modeling and predicting daily user-online movement in IM in a concise and intuitive way.     

Investigating spatial variation in the relationships between NDVI and environmental factors at multi-scales: a case study of Guizhou Karst Plateau,China

Knowing the spatial relationships between the normalized difference vegetation index (NDVI) and environmental variables is of great importance for monitoring rocky desertification. This article investigated the spatially non-stationary relationships between NDVI and environmental factors using geographically weighted regression (GWR) at multi-scales. The spatial scale-dependency of the relationships between NDVI and environmental factors was identified by scaling the bandwidth of the GWR model, and the appropriate bandwidth of the GWR model for each variable was determined. All GWR models represented significant improvements of model performance over their corresponding ordinary least squares (OLS) models. GWR models also successfully reduced the spatial autocorrelations of residuals. The spatial relationships between NDVI and environmental factors significantly varied over space, and clear spatial patterns of slope parameters and local coefficient of determination (R ²) were found from the results of the GWR models. The study revealed detailed site information on the different roles of related factors in different parts of the study area, and thus improved the model ability to explain the local situation of NDVI.     

电化学CO2气体传感器的制备及评价

采用空心氧化铝陶瓷管作为衬底,制备了以NASICON材料为固体电解质,Li2CO3-BaCO3二元碳酸共晶混合物为辅助电极的固体电解质的管式CO2传感器,对传感器电极材料进行分析表征并对传感器性能进行了测试。结果表明元件均对CO2气体具有良好的线性响应。当工作电压为6V时,加热温度约为550℃左右时,元件表现出很好的灵敏度特性,其灵敏度值能与由能斯特方程得到的理论值较好的符合。     

基于热调度消纳风电的户式相变蓄热电采暖热容量研究

传统研究方法在研究户式相变蓄热电采暖热容量时,准确性很低。为了解决这一问题,基于热调度消纳风电提出了一种新的户式相变蓄热电采暖热容量研究方法,首先通过系统备用功率分析了热电模式下户式相变蓄热系统接纳风电能力,进而给出了风电供热调度模型,该模型根据显热蓄热热容量,潜能蓄热热容量和化学反应蓄热三种户式相变蓄热方式进行电采暖热容量研究。与传统研究方法进行实验对比,结果表明,给出的方法准确率可以达到99.82%,传统的研究方法准确率为90.53%,所提方法误差率更小,具有更广阔的发展空间。     

Agent-based modelling of the spatial pattern of leisure visitation in forests: A case study in Wallonia,south Belgium

The leisure use of forests is a fast growing sector in European tourism. The difficulties in monitoring real usage pattern have hindered communications in tourism, conservation and public health in forested areas. In this study, we present an agent-based model to approximate forest visit patterns at the regional level, based on the visitor, residential and forest attributes. The model was then adapted locally for Wallonia, south Belgium, to predict the daily distribution of forest visits and visitor flows. The results suggest high visit rates in urban forests. In highly attractive forests that are distant from major cities, the visit rates may greatly respond to the visitor-level and environmental changes. Future empirical investigations are encouraged to build a cross-contextual understanding on visitors' decision-making mechanisms and to identify how these mechanisms may be influenced by environmental factors operating at different spatio-temporal levels.     

Impacts of landscape structure on surface urban heat islands: A case study of Shanghai, China

Urbanization is taking place at an unprecedented rate around the world, particularly in China in the past few decades. One of the key impacts of rapid urbanization on the environment is the effect of urban heat island (UHI). Understanding the effects of landscape pattern on UHI is crucial for improving the ecology and sustainability of cities. This study investigated how landscape composition and configuration would affect UHI in the Shanghai metropolitan region of China, based on the analysis of land surface temperature (LST) in relation to normalized difference vegetation index (NDVI), vegetation fraction (Fv), and percent impervious surface area (ISA). Two Landsat ETM+ images acquired on March 13 and July 2, 2001 were used to estimate LST, Fv, and percent ISA. Landscape metrics were calculated from a high spatial resolution (2.5 × 2.5 m) land-cover/land-use map. Our results have showed that, although there are significant variations in LST at a given fraction of vegetation or impervious surface on a per-pixel basis, NDVI, Fv, and percent ISA are all good predictors of LST on the regional scale. There is a strong negative linear relationship between LST and positive NDVI over the region. Similar but stronger negative linear relationship exists between LST and Fv. Urban vegetation could mitigate the surface UHI better in summer than in early spring. A strong positive relationship exists between mean LST and percent ISA. The residential land is the biggest contributor to UHI, followed by industrial land. Although industrial land has the highest LST, it has limited contribution to the overall surface UHI due to its small spatial extend in Shanghai. Among the residential land-uses, areas with low- to-middle-rise buildings and low vegetation cover have much high temperatures than areas with high-rise buildings or areas with high vegetation cover. A strong correlation between the mean LST and landscape metrics indicates that urban landscape configuration also influences the surface UHI. These findings are helpful for understanding urban ecology as well as land use planning to minimize the potential environmental impacts of urbanization.     

Satellite- and ground-based measurements of CO2 over the Indian region: its seasonal dependencies,spatial variability,and model estimates

ABSTRACT

The present study demonstrates the distribution of carbon dioxide (CO₂) concentration over the Indian region and the surrounding oceanic regions during 2009–2012, using measurements from satellites viz., Greenhouse Gases Observing Satellite (GOSAT) and Atmospheric Infrared Sounder, Carbon Tracker (CT) model simulations and flask measurements from two Indian stations Sinhagad (SNG) (73°45′ E, 18°21′36″ N) and Cape Rama (CRI) (73°54′ E, 15°6′ N). The concentration of CO₂ is observed to be maximum during pre-monsoon and shows a decreasing phase during the post-monsoon season. In a regional scale, it is found that Indo-Gangetic Plain and northern India have relatively higher concentrations compared to the other regions. The probability distribution of the concentration differences shows that for most of the time, the differences lie between ±3 ppmv between GOSAT and CT. The comparison between the CO₂ flask measurements over SNG and CRI with respect to that of GOSAT and CT clearly reveals that the differences in CO₂ are as high as 10 ppmv between the ground- and satellite-based measurements. Further, we utilized the Lagrangian model FLEXible PARTicle (FLEXPART) to understand the source?receptor relationship over CRI, SNG, and over the equatorial Indian Ocean (IO). The source contributions from the northern and eastern continental regions of the Indian region are found to be more influential over SNG compared to CRI. It is also found from simulations that the equatorial IO has less influence from the continental source and therefore has a reduced seasonal variability compared to the other regions considered in the present study.     

基于灰色等维新息模型的能耗预测研究及应用

灰色系统理论将随机过程看成灰色过程,利用数据表面杂乱但整体有序的特点,挖掘潜在的本质规律.根据灰色系统理论的思想,在分析了传统GM(1,1)模型的基础上提出了改进的等维新息预测模型,利用Matlab强大的算法功能,实现了改进的等维新息灰色预测模型算法.通过对能耗预测的实例分析,并采用残差和后验差方法对预测的精度进行检验,验证了程序的准确性和可靠性,使得预测的精度得到有效的提高.     

Deformation retrieval in large areas based on multibaseline DInSAR algorithm: a case study in Cangzhou,northern China

The DInSAR technique with a multibaseline is becoming popular nowadays to investigate slow urban deformation. In this paper, we focus on deformation retrieval in large areas, including urban and suburban areas. Based on the multibaseline DInSAR algorithm proposed by Mora, three extensions are derived. First, least‐squares adjustment and error‐controlling methods are used to obtain stable deformation velocity and height error estimations. The least‐squares QR factorizaiton algorithm is emphasized to solve large, linear, and sparse functions. Second, a new complex network is presented to limit noise effects on the Delaunay triangular network. Third, by combining complex and Delaunay networks, large‐area deformation is investigated, from centre urban areas to suburban areas. The enhanced algorithm is performed to investigate the subsidence of Cangzhou, Hebei province (northern China) during 1993–1997 by using 9 ERS SLC data. The experimental results show serious subsidence in the region and are validated by levelling data and groundwater wells data. Compared with levelling data, the estimation errors of linear deformation velocity in urban areas are in the range of (?2, 2) mm year^?1, and in suburban areas, the errors are in the range of (?26, 15) mm year^?1, which is sufficiently feasible to determine the status of subsidence relative to the maximum deformation velocity of about ?100 mm year^?1. The subsidence centres in urban areas are consistent with the spatial distribution of groundwater wells, which provides evidence that groundwater overexploitation is the main cause of subsidence in Cangzhou. The closure of wells will be a good way to control subsidence in the future.     

Modelling water dynamics with DNDC and DAISY in a soil of the North China Plain: A comparative study

The performance of the DNDC and Daisy model to simulate the water dynamics in a floodplain soil of the North China Plain was tested and compared. While the DNDC model uses a simple cascade approach, the Daisy model applies the physically based Richard's equation for simulating water movement in soil. For model testing a three years record of the soil water content from the Dong Bei Wang experimental station near Beijing was used. There, the effect of nitrogen fertilization, irrigation and straw removal on soil water and nitrogen dynamics was investigated in a three factorial field experiment applying a split-split-plot design with 4 replications. The dataset of one treatment was used for model testing and calibration. Two other independent datasets from further treatments were employed for validating the models. For both models, the simulation results were not satisfying using default parameters. After parameter optimisation and the use of site-specific van Genuchten parameters, however, the Daisy model performed well. But, for the DNDC model, parameter optimisation failed to improve the simulation result. Owing to the fact that many biological processes such as plant growth, nitrification or denitrification depend strongly on the soil water content, our findings bring us to the conclusion that the site-specific suitability of the DNDC model for simulating the soil water dynamics should be tested before further simulation of other processes.     

A key study on spatial source distribution of PM2.5 based on the airflow trajectory model

Most methods and technologies on particulate matter with an aerodynamic diameter of less than 2.5 µm (PM_2.5) source apportionment are carried out from the microscopic view with a focus on its chemistry composition. This research is an attempt to analyse the influence of airflow motion on the emission, transport, diffusion, and dissipation of PM_2.5 particles, and explore spatial source distribution at the macro view in the Pearl River Delta (PRD). Spatial source distribution can be achieved through combining the temporal and spatial distribution of satellite-based PM concentration with the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model. This research first retrieves high-resolution ground-level PM_2.5 concentrations based on the latest Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol product (MOD04/MYD04, 3 km, C006), using an improved semi-empirical model. Then an approach based on the HYSPLIT model is proposed to identify spatial source distribution and it is applied to a typical incident as an example. Further analysis is applied to all typical incidents that occurred in 2013 in the PRD. Verification results of satellite-based PM_2.5 show this method has an improved precision (r = 0.76, N = 701, RMSE = 18.49 µg m^–3) over a model, which only conducts humidity correction and vertical correction (r = 0.67, N = 701, RMSE = 20.24 µg m^–3). An analysis of the incident that occurred between 5 March 2013 and 10 March 2013 shows that the high PM_2.5 concentrations in this incident came from local sources. Local circulation extended the polluted range and clear air blowing from the southern sea was the key external reason for a reduction from the high concentration. Further statistical results of all of the typical events occurring in 2013 demonstrate that the main cause of high concentrations of PM_2.5 particles is primarily from local sources and regional transport. There was no obvious extra-regional source. This is different from other heavily haze-polluted areas (Jing-Jin-Tang district (JJT), Yangtze River Delta (YRD)) in China. The result of our study could play an important role in the future work about regional joint governance.