Medium-sized Urban Areas Research Articles

Relative impact of on-road vehicular and point-source industrial emissions of air pollutants in a medium-sized Andean city

Cities in emerging countries are facing a fast growth and urbanization; however, the study of air pollutant emissions and its dynamics is scarce, making their populations vulnerable to potential effects of air pollution. This situation is critical in medium-sized urban areas built along the tropical Andean mountains. This work assesses the contribution of on-road vehicular and point-source industrial activities in the medium-sized Andean city of Manizales, Colombia. Annual fluxes of criteria pollutants, NMVOC, and greenhouse gases were estimated. Emissions were dominated by vehicular activity, with more than 90% of total estimated releases for the majority of air pollutants. On-road vehicular emissions for CO (43.4 Gg/yr) and NMVOC (9.6 Gg/yr) were mainly associated with the use of motorcycles (50% and 81% of total CO and NMVOC emissions respectively). Public transit buses were the main source of PM10 (47%) and NOx (48%). The per-capita emission index was significantly higher in Manizales than in other medium-sized cities, especially for NMVOC, CO, NOx and CO2. The unique mountainous terrain of Andean cities suggest that a methodology based on VSP model could give more realistic emission estimates, with additional model components that include slope and acceleration. Food and beverage facilities were the main contributors of point-source industrial emissions for PM10 (63%), SOx (55%) and NOx (45%), whereas scrap metal recycling had high emissions of CO (73%) and NMVOC (47%). Results provide the baseline for ongoing research in atmospheric modeling and urban air quality, in order to improve the understanding of air pollutant fluxes, transport and transformation in the atmosphere. In addition, this emission inventory could be used as a tool to identify areas of public health exposure and provide information for future decision makers.

The Role of Medium-sized Cities for Global Tropospheric Ozone Levels

Brazilian medium-sized cities are those showing highest growing rates in the last decades, above 3% annually. To call attention to the consequences of such strong urban growth on air quality, measurements of ozone concentrations were comparatively performed in Londrina (a growing medium-sized city), Curitiba (a big city) and São Paulo (a megacity). Particularly to the cities of Londrina and São Paulo, both are located at similar latitude (–23.5). Surprisingly, the findings of this study indicated that, there are periods of the year in which the average ozone concentration measured in Londrina can be even higher than those found in large urban areas like São Paulo. The average ozone concentrations at three medium cities are close to those found in São Paulo. It is suggested that the local meteorological conditions (temperature, cloud cover, relative humidity and wind speed), as well as the local chemical regime, could explain the differences in the observed ozone concentrations. As the number of medium-sized urban areas is increasing around the world, especially in South America, special attention should be given by policy makers when defining new air quality monitoring networks and the regulation of new areas planned for the purpose of industrial development.

Development of Improved Trip Attraction Rates for Small and Medium-Sized Travel Demand Models

Accurate data are essential for the development of robust and valid travel demand models to support the planning activities of metropolitan planning organizations (MPOs). The Travel Survey Program of the Texas Department of Transportation (DOT) includes workplace travel surveys to develop trip attraction rates for travel demand modeling activities. This paper reports the findings of a research study that developed a comprehensive database of workplace travel surveys conducted by the Texas DOT over the past 13 years. The final master database contained data from more than 63,000 trips at more than 5,100 establishments across 15 urban areas in Texas. Trip attraction rates for three trip purposes (home-based work, home-based nonwork, and non-home based) were calculated from these data, with segmentation according to establishment type, urban area size, and the population density of the traffic analysis zone in which the establishment was located. Trip attraction rates were calculated for person trips and auto trips. One of the key findings from this study was that the trip attraction rates varied across area types and indicated that population density contributed to the trip attraction characteristics of workplace establishments. The findings of this research can be used by MPOs of all sizes—especially those serving small and medium-sized urban areas—to improve travel demand models by providing more improved trip attraction rates for a variety of contexts.

The simple, efficient, elegant, and effective model (SE3M) of land use and transportation

Integrated land use/transportation forecasting models add significant policy and infrastructure alternatives analysis capabilities to the urban planning process. Historically, the financial, time, and staff requirements to develop one of these models has put them beyond the reach of most small- to medium-sized urban areas. The purpose of this paper is to present the large zone economic submodel of SE3M, an integrated model – founded upon economic base theory and bid-rent theory – that is reasonably accurate, yet simpler in form, function, and implementation than competing models. The US territory of Guam is used as the case study/proof of concept implementation for this model framework. The submodel presented here was validated against a horizon year with known data for zonal level population and employment totals together with control totals for the island as a whole. The model was able – across two base years and one validation, horizon year – to locate all jobs and a high percentage of the population on each zone on the island.

CLASS: A DSS for the Analysis and the Simulation of Urban Freight Systems

The complexity of methods and models for the investigation of urban freight systems has pushed researchers to develop decision support systems (DSS) for the analysis and simulation of the effects of city logistics measures and the effects of exogenous scenario changes, as land-use, demographic and socio-economic characteristics. In fact, today these types of systems provide to support decision-makers to understand and simulate the structure of freight urban system and to compute some indicators that compared with target and benchmarking values allow to identify its level of service. Such a DSS, named CLASS (City Logistics Analysis and Simulation Support System), has been recently proposed and in this paper some advancements are presented. Then, two application examples for the simulation of urban freight transport in a large urban area and the assessment of freight distribution activity location in a medium size urban area are presented.

City logistics long-term planning: simulation of shopping mobility and goods restocking and related support systems

The growing necessity to improve city sustainability and liveability has pushed local administrators to look also at medium/long-term city logistics measures, such as land-use governance policies. In order to assess long-term scenarios, it is necessary to have models and methods able to take into account the effects on shopping mobility and goods restocking, generated by these classes of measures (e.g. relocation of shopping zones). Besides, we have to consider that modifications of shopping attitudes, deriving from changes of demographic and socio-economic characteristics of end consumers, can impact on purchasing behaviour and hence on restocking mobility. This paper discusses a number of issues related to the simulation of medium/long-term scenarios and presents a system of models that consider shopping mobility and restocking jointly. The presented shopping demand models, in combination with urban restocking models, are implemented within a simulation support system named City Logistics Analysis and Simulation Support System and are used to assess the effects on the freight restocking due to demographic and socio-economic variations including some hypotheses on new land-use development governance measures in a medium-size urban area. The main results confirm the modelling goodness and, at the same time, demonstrate that changes in demographic and socio-economic characteristics could cause relevant effects, in particular increasing car use in shopping mobility. The growing e-shopping could limit the negative effects of these changes, but the impacts of home deliveries have to be considered. The relocation of commercial and logistics centres, closer to the residential distribution, could drive a different restocking pattern with a consequent reduction in freight vehicle mobility. Anyway, this reduction is not very relevant and therefore further city logistics measures have to be implemented.

A system of models to forecast the effects of demographic changes on urban shop restocking

End-consumer choices in relation to type of retail outlet impact upon shopping travel frequency and mode, and hence on freight distribution flows for restocking shops. The characteristics of the restocking process, in terms of delivery size, delivery frequency, freight vehicle type and so on, are strictly related to the size of commercial activities to be restocked. Since end-consumer choices depend on end-consumer characteristics, such as age, gender and occupation, which change over time in an urban area, changes in such characteristics impact upon the nature of freight restocking. In city logistics analysis, in order to forecast the future characteristics of freight distribution in an urban area, a system of models is required that allows shopping mobility and freight restocking distribution to be considered in an integrated approach, with shopping demand models that take end-consumer characteristics into account. This paper discusses a number of issues related to the transportation impacts of shopping attitudes on urban freight distribution. It focuses on the factors that mainly influence freight distribution: quantity and choices of retail type (including e-shopping). After an analysis of state-of-the-art shopping mobility demand modelling, a new system of models for simulating shopping choices is presented. The models were obtained by using surveys carried out in Rome where more than 300 families were interviewed. Jointly with urban restocking models, they were used to assess the effects on freight restocking under a future scenario when demographic changes occur in a medium-size urban area. The results indicate that effects of demographic changes on shop restocking flows can be significant. For example, the shifting of middle aged adults into later age could result in an increase in shopping trips to nearby shops, mainly to small and medium-size retail outlets. This could lead to a consequent increase in car-kms. Further, expectation of an increase in e-shopping could reduce consumer trips. However, new measures able to promote consolidation for making home deliveries more efficient should be investigated.

A coarse-grained parallel approach for seismic damage simulations of urban areas based on refined models and GPU/CPU cooperative computing

Refined models and nonlinear time-history analysis have been important developments in the field of urban regional seismic damage simulation. However, the application of refined models has been limited because of their high computational cost if they are implemented on traditional central processing unit (CPU) platforms. In recent years, graphics processing unit (GPU) technology has been developed and applied rapidly because of its powerful parallel computing capability and low cost. Hence, a coarse-grained parallel approach for seismic damage simulations of urban areas based on refined models and GPU/CPU cooperative computing is proposed. The buildings are modeled using a multi-story concentrated-mass shear (MCS) model, and their seismic responses are simulated using nonlinear time-history analysis. The benchmark cases demonstrate the performance-to-price ratio of the proposed approach can be 39 times as great as that of a traditional CPU approach. Finally, a seismic damage simulation of a medium-sized urban area is implemented to demonstrate the capacity and advantages of the proposed method.

Method to Determine Pedestrian Level of Service for the Overall Unsignalized Midblock Crossings of Road Segments

This paper aims at developing a pedestrian level of service (LOS) model for the overall unsignalized midblock crossings of road segments from the perspective of the pedestrian's perception of safety and convenience in Chinese midblock crossing environment. Firstly, the potential primary factors influencing pedestrian LOS at unsignalized midblock crosswalks were summarized from four respects: traffic conflicts, the distance between crosswalks, crossing facilities, and delay. Secondly, 948 participants’ real-time sense of safety and convenience when they were crossing the 30 selected unsignalized midblock crosswalks and the design and operational characteristics of the selected road segments were collected. The selected midblock crosswalks were typical of those prevalent in the medium-sized urban areas of China, and the participants of questionnaire survey covered a broad cross section of Chinese population of pedestrians. Finally, Pearson correlation analysis and stepwise regression analysis were carried out to develop pedestrian LOS model for the overall unsignalized midblock crossings of road segments. The results revealed that the factors significantly influencing pedestrian LOS of the overall unsignalized midblock crossings of road segments included volume of two-way motor vehicle, the distance between marked midblock crosswalks, and the distance between unmarked crosswalks. A reliable, statistically calibrated pedestrian LOS model was developed ( R2 = 0.80).

Analysis on leisure patterns of the pre-elderly adults

The purpose of study is to analyze how leisure activities affect the near elders’ preparation for successful and productive aging. To achieve the purpose of the study, this study was conducted in 2012 and the data was collected by using multi-stage stratified cluster random sampling method in the great city area (6 places), metropolitan area (7 places), medium-sized urban area (6 places), and rural area (6 places). Out of the total number of 1,000 copies of questionnaire distributed to pre-elders (Baby-boomers from 55 yr to 64 yr), 978 were collected and used for data analysis. According to the result, the more time, frequency and intensity in leisure and recreational participation, the higher the satisfaction level and the happiness level in their life. It means that leisure and recreational activities play an important role for their life. In other words, for pre-elders, leisure activities can be regarded as the important element for preparation of their old age. Therefore, the leisure and recreation for pre-elderly adults should not be recognized as a tool for improving the economic productivity but for reinforcing the recovery resilience.

Characterization of the origin of fine particulate matter in a medium size urban area in the Mediterranean

A multi-stage methodology for investigating particulate pollution is developed and implemented for the case study area of Patras, Greece. Initially a low cost particulate matter mass monitor was used to assess aerosol mass concentrations indicating that the city, despite its small size (population around 200,000) and lack of heavy industry, violates both the daily and annual European Union PM standards. Increased PM10 concentrations were observed during the winter but local vehicular traffic was estimated to account for only 12 ± 4% of the PM10 concentration on an annual basis. In the second stage, PM2.5 chemical composition was measured at the urban center and biomass burning was identified as a major PM source during the colder months. In the third stage, PM2.5 concentration and chemical composition was also followed at a mostly upwind rural site around 40 km from the city. The transported pollution was found to account for 50% of the PM2.5 during winter and for more than 70% during the rest of the year. Almost all of the sulfates and 40–90%, depending on the season, of the organic aerosol are transported to the city from other areas. In the last stage, an intensive campaign took place during winter in order to quantify PM sources during the most polluted period. Nighttime sharp increases of the aerosol levels were observed with organic aerosol levels exceeding 80 μg m−3. Local biomass combustion and fossil fuel emissions for domestic heating were responsible for these levels.

Deriving an Urban Climate Map in coastal areas with complex terrain in the Basque Country (Spain)

This works develops a methodology to analyze urban climate from an urban planning perspective and derive an Urban Climate Map (UC-Map). Calculations with spatial information layers, climate measurements and urban climate knowledge are used to evaluate thermal load and dynamic potential of the urban area. All the necessary information is grouped in five information layers (building volume, building surface fraction, green areas, ventilation paths and slopes). The method is applied to Bilbao (Spain), a medium-sized urban area located in complex terrain, and influenced by sea breeze and cold air drainage flow.The resulting UC-Map agrees with experimental data and shows the effects on thermal comfort of the interaction of different land use with regional climate. Local/regional ventilation systems characterized by diurnal and seasonal intensity variations turn out to be a very important aspect to reduce heat storage in Bilbao. Specific recommendations are included to improve and protect climate. This UC-Map is an important milestone in Spain since it is the first information tool that relates urban climate with urban planning. The methodology presented is simple to apply and can be adapted to other urban areas with similar characteristics to Bilbao.

PM10-PM2.5 time series and fractal analysis

Several epidemiological studies have shown an association between particulate air pollution and health effects. Suspended particulates and more specifically the inhalable PM10 fraction appear to cause respiratory health effects and heart diseases. Furthermore, particulate pollution is of paramount importance in areas with open-pit mines and especially when it is combined with raw lignite transfer and combustion in power stations through the suspension of particles and stack emissions, respectively. The penetration of particles into respiratory track is a function of the size of the particles and thus, it is more likely for the finer PM2.5 fraction to reach the deepest of the lugs. The fast economic growth the last decades has resulted in an increase of the sources of pollution not only in large metropolitan areas but also in medium-sized urban areas like the city of Kozani, Greece. It is the most densely populated city in the area of West Macedonia affected by urban particulate matter originated from local and stationary sources, from regional and long-range transport, and from street dust resuspension. Kozani is located a few kilometers away from lignite power stations that contribute to about 70% of the total electrical energy produced in Greece. Dust emissions seem to be the most serious problem in the area, as the measured ambient concentrations of suspended particles are at high levels and exceed local and international standards. In this study PM10 and PM2.5 concentrations are presented. The measurements have been carried out, from April to December 2002, by the Lab of Atmospheric Pollution and Environmental Physics (LAPEP) of Technological Education Institute of West Macedonia in the commercial centre of the city of Kozani. The temporal variation of PM10 and PM2.5 concentrations was studied and allowed a further insight on the factors affecting the measured ambient particulate levels. PM2.5 – PM10 correlation and PM2.5/PM10 ratios were investigated and compared to those in the literature together with the factors affecting their diurnal variation. The pollution levels were also detected in process of the experimental time series data by fractal dimension. Generally, fractal analysis is able to detect the data set complexity by scaling empirical data using threshold values. These values define the levels of air pollution episodes. The method presented in this study, is the transformation of PM10 and PM2.5 concentrations into a set of points whose dimension was estimated by box counting. This technique has estimated the fractal dimension of both the time series by the relationship between data variance and time scale.

Modelling Household Vehicle Ownership in Asian Medium-Sized Urban Area: A Case Study of Khon Kaen City, Thailand

Modelling Household Vehicle Ownership in Asian Medium-Sized Urban Area: A Case Study of Khon Kaen City, Thailand

Modelling Household Vehicle Ownership in Asian Medium-Sized Urban Area: A Case Study of Khon Kaen City, Thailand

Modelling Household Vehicle Ownership in Asian Medium-Sized Urban Area: A Case Study of Khon Kaen City, Thailand

Urban development and expenditure efficiency in the 2000–2006 regional operational program of Sardinia

The Sardinian regional operational program 2007–2013 concerning the European Regional Development Fund (ERDF) (2007–2013 ROP-ERDF) respects the rules of the ERDF on the investments for territorial cohesion since it promotes their regional geographic concentration. These investments are evenly shared between large- and medium-sized urban areas, and disadvantaged zones. This paper analyzes the investment policies implemented by the Sardinian Region through the 2000–2006 ERDF based part of the Regional Operational Program (2000–2006 ROP-ERDF), in order to assess their effectiveness, in terms of expense efficiency, for urban areas and disadvantaged zones. The assessment of the expenditure efficiency of the 2000–2006 ROP-ERDF is very important to address the policies of the 2007–2013 ROP-ERDF in terms of geographic concentration. The essay analyzes the results of the 2000–2006 ROP-ERDF, with reference to the expenditure efficiency of Sardinian cities, represented through a geographic information system, by means of a multinomial logit model. The essay proposes an analytical and interpretive approach which could be easily exported to other public planning processes, in order to define policies for territorial cohesion.

Hierarchical ordering of nests in a joint mode and destination choice model

This paper seeks to explore the relationship between mode and destination choice in an integrated nested choice model. A fundamental argument can be made that in certain circumstances, the ordering of choices should be reversed from the usual sequence of destination choice preceding mode choice. This results in a travel demand model where travelers are more likely to change destinations than to change transportation modes. For small and medium size urban areas, particularly in the United States, with less well developed public transit systems that draw few choice riders, this assumption makes much more sense than the traditional modeling assumptions. The models used in the new travel modeling system developed for Knoxville, Tennessee utilize this reversed ordering, with generally good results, which required no external tinkering in the logsum parameters.

Using Aggregated Federal Data to Model Freight in a Medium-Sized Community

In most urban areas, freight volumes are not explicitly considered in the transportation planning process. This is primarily due to the proprietary nature of freight data, causing any freight data that are released to be highly aggregated. This paper examines a multitiered methodology to utilize freight data from a federally available, highly aggregated source within an urban planning model to accurately model truck transportation. A case study is included that demonstrates the modeling methodology for a medium-sized urban area, complete with international port, and contains validation results of the freight transportation in the area.

TRANSIMS Implementation in Chittenden County, Vermont

To advance the state of the practice of travel forecasting, the federal government since 1992 has sponsored the development of the Transportation Analysis and Simulation System (TRANSIMS). The purpose of this paper is to describe and document experience with the implementation and calibration of the TRANSIMS model in Chittenden County, Vermont, a medium-sized urban area with a population of about 145,000. In developing the TRANSIMS model, participants in the study attempted to rely primarily on readily available data that would be easily accessible to most metropolitan planning organizations (MPOs) around the country. Following model development, several validation experiments were conducted to assess the extent to which the model after calibration replicated observed traffic counts. Preliminary sensitivity analyses were also performed to assess the sensitivity of the model results to changes in the random seed number and to evaluate the impact of changing pretimed signals to actuated controllers. The study demonstrates that the TRANSIMS Track-1 structure and the tools currently available in the model can be used to develop and calibrate a model that works reasonably well with a relatively modest effort for a small to medium-sized MPO. Moreover, for medium-sized areas with little to no congestion, the model does not appear to be sensitive to variations in the seed number, which should increase confidence in the model's results.

Evaluation of socio-spatial vulnerability of citydwellers and analysis of risk perception: industrial and seismic risks in Mulhouse

Abstract. Social vulnerability has been studied for years with sociological, psychological and economical approaches. Our proposition focuses on perception and cognitive representations of risks by city dwellers living in a medium size urban area, namely Mulhouse (France). Perception, being part of the social vulnerability and resilience of the society to disasters, influences the potential damage; for example it leads to adequate or inadequate behaviour in the case of an emergency. As geographers, we assume that the spatial relationship to danger or hazard can be an important factor of vulnerability and we feel that the spatial dimension is a challenging question either for better knowledge or for operational reasons (e.g. management of preventive information). We interviewed 491 people, inhabitants and workers, regularly distributed within the urban area to get to know their opinion on hazards and security measures better. We designed and mapped a vulnerability index on the basis of their answers. The results show that the social vulnerability depends on the type of hazard, and that the distance to the source of danger influences the vulnerability, especially for hazards with a precise location (industrial for example). Moreover, the effectiveness of the information campaigns is doubtful, as the people living close to hazardous industries (target of specific preventive information) are surprisingly more vulnerable and less aware of industrial risk.