Large-sized Cities Research Articles

Performance Evaluation of Machine Learning and Neural Network-Based Algorithms for Predicting Segment Availability in AIoT-Based Smart Parking

Finding an available parking place has been considered a challenge for drivers in large-size smart cities. In a smart parking application, Artificial Intelligence of Things (AIoT) can help drivers to save searching time and automotive fuel by predicting short-term parking place availability. However, performance of various Machine Learning and Neural Network-based (MLNN) algorithms for predicting parking segment availability can be different. To find the most suitable MLNN algorithm for the above mentioned application, this paper evaluates performance of a set of well-known MLNN algorithms as well as different combinations of them (i.e., known as Ensemble Learning or Voting Classifier) based on a real parking datasets. The datasets contain around five millions records of the measured parking availability in San Francisco. For evaluation, in addition to the cross validation scores, we consider resource requirements, simplicity and execution time (i.e., including both training and testing times) of algorithms. Results show that while some ensemble learning algorithms provide the best performance in aspect of validation score, they consume a noticeable amount of computing and time resources. On the other hand, a simple Decision Tree (DT) algorithm provides a much faster execution time than ensemble learning algorithms, while its performance is still acceptable (e.g., DT’s accuracy is less than 1% lower than the best ensemble algorithm). We finally propose and simulate a recommendation system using the DT algorithm. We have found that around 77% of drivers can not find a free spot in their selected destinations (i.e., street or segment) and estimated that the recommendation system, by introducing alternative closest vacant locations to destinations, can save, in total, 3500 min drivers searching time for 1000 parking spot requests. It can also help to reduce the traffic and save a noticeable amount of automotive fuel.

Does the opening of high-speed railways improve urban livability? Evidence from a quasi-natural experiment in China

With the spread of “urban disease”, urban livability has aroused common concern in academic circles at home and abroad. High-speed railway opening is substantially affecting the development of cities. Based on the data of 271 cities in China from 2005 to 2018, this paper applies the entropy method to calculate urban livability level, and then the difference-in-differences (DID) model and mediatory effect model are constructed to test the impact and mechanism of high-speed railway (HSR) opening on urban livability. The findings show that: (1) Overall, HSR opening has significantly improved urban livability by 13.04%. After alleviating the endogenous problem and conducting a series of robustness tests, the conclusions are still valid. (2) Mechanism analysis indicates that HSR opening improves urban livability by promoting economic growth, talent agglomeration and industrial structure upgrading. Among them, the industrial structure upgrading effect is the strongest, followed by talent agglomeration and economic growth. (3) The heterogeneity analysis shows that the promotion effect of HSR opening on urban livability is more significant in the central and western regions and large-sized cities. Accordingly, the feasible path to improve urban livability through HSR opening is proposed. Finally, in the face of the impact of the COVID-19 pandemic on the world economy, more channels to enhance urban livability are expected to cope with the future “the global talent war”.

Two decades of e-government diffusion among local governments in the United States

This study is the first to evaluate e-government diffusion among local governments in the United States over time. The diffusion rates of various types of e-government services are measured and analyzed over two decades. E-government surveys conducted by the International City/County Management Association (ICMA) from 2000 to 2011 provide an early trendline of e-government services offered, and an original two-wave panel survey was conducted in 2014 and 2019 collecting data, which extends this timeline and offers new ways to measure adoption in this later period. The panel survey includes the same 83 cities randomly selected from all cities with populations over 50,000, representing over 10% of medium and large size cities in the U.S.The findings of this study provide a clear picture that cities across the nation have increasingly adopted a wide set of e-gov services, with some reaching near complete diffusion. A total of 45 different e-government services are evaluated, with similar e-government services organized together into informational, interactive, multimedia, financial, and social media scaled variables for further analysis. Adoption and diffusion of e-government services have been neither steady nor uniform. However, from 2014 to 2019 the trend was clear: more cities offered more e-government services more consistently.The findings also offer insights into the characteristics of cities that have adopted e-government innovations earlier than others. Both greater population size and percent of residents with broadband access contribute in a statistically significant way to the number of e-gov services adopted, while other expected independent variables like economic measures of wealth do not. These findings contribute to a broader conversation about how the diffusion of e-government service adoption has changed over time and the extent to which that has affected the relationship between residents and their local governments throughout the first two decades of the 21st Century.

Can smart city construction improve urban ecological total factor energy efficiency in China? Fresh evidence from generalized synthetic control method

The smart city concept was proposed in the wave of “New Urbanism”. To improve the quality of urbanization, China has launched smart city construction since 2012. Taking 153 cities from China as the research sample, we evaluated the impact of smart city policy (SCP) on urban ecological total factor energy efficiency (ETFEE) using the generalized synthetic control method. The main results are as follows. (1) SCP significantly improves urban ETFEE after controlling the endogeneity and unobserved time-varying confounders, and this conclusion is strongly supported by multiple robustness tests. (2) There is a two-stage mediating mechanism through which SCP functions. Specifically, SCP promotes innovation by enhancing intelligence (including informatization, human capital, and technology), thereby improving urban ETFEE. (3) Public participation and market conditions play moderating effects, and they improve the contribution of SCP on urban ETFEE. (4) For heterogeneity, SCP plays a significant role in eastern cities, large-size cities, non-resource-based cities, and non-old industrial base cities, whereas it has little impact on other cities’ ETFEE. This study provides empirical evidence and policy insights for constructing smart cities in China and even other emerging economies.

Sleep and circadian rhythm characteristics in individuals from the general population during the French COVID-19 full lockdown.

SummaryThe full 2‐month lockdown to fight the coronavirus disease 2019 (COVID‐19) pandemic in 2020 led to substantial disruption of daily life and routines. The present study aimed to comprehensively identify the lockdown’s effects on sleep, daily rhythms and emotions of the French population. A survey was published online during the last week of the 2‐month full lockdown and 1,627 individuals completed the online survey. The survey was self‐administered and included standardised questionnaires. Sleep schedules were delayed during lockdown in more than half of the participants. New severe delayed sleep phase affected 10% of participants with sleep schedules delayed by ≥3 hr during the lockdown compared to before. A significant decrease in exposure to morning (p < 0.001) and evening natural light (p < 0.001), a significant increase in screen exposure time (with a significant screen exposure >3 hr during the evening for 45% of the participants during lockdown versus 18% before lockdown, p < 0.001), an increase in substance use for one‐quarter of participants, a poorer sleep quality in 56% of participants, and less regular sleep schedules in 48% of participants were observed. We also found a poorer sleep quality in women than men during lockdown (p = 0.004). The French full lockdown had a severe impact on sleep quality, sleep–wake rhythms, and sleep behaviours. The implementation of public health strategies for the prevention and care of sleep–wake cycles during lockdown are therefore essential.

The impact of macro-scale urban form on land surface temperature: An empirical study based on climate zone, urban size and industrial structure in China

While previous studies revealed that urban form optimization could alleviate the urban heat island (UHI) effect, empirical studies have often documented paradoxical conclusions on the impacts of urban form on land surface temperature (LST). To examine whether the effect of urban form on LST varies across cities, data on 266 Chinese cities are used to conduct OLS regression analyses. These cities are divided into three groups: cities in different climatic zones, cities with different urban area sizes, and cities with different industrial structures. The results show that, at the national scale, LST (in summer daytime) is negatively correlated with compactness, boundary complexity, and urban shape but positively correlated with contiguity. However, these effects are heterogeneous across cities. Specifically, contiguity exhibits a relatively stronger influence on LST in cities located in Temperate and Warm-temperate zones. Compactness and urban shape significantly impact LST in small-sized, medium-sized cities and megacities, while the effects are insignificant in large-sized cities. Polycentric shape for industrial cities elevates LST. Several practical policy implications for urban planning under different scenarios are proposed to ameliorate the UHI effect. This study could contribute to the alleviation of the UHI effect in regions whose climate characteristics and development levels are similar to those of China.

Impacts of socio-economic determinants, spatial distance and climate factors on the confirmed cases and deaths of COVID-19 in China.

This study is to assess the influences of climate, socio-economic determinants, and spatial distance on the confirmed cases and deaths in the raise phase of COVID-19 in China. The positive confirmed cases and deaths of COVID-19 over the population size of 100,000 over every 5 consecutive days (the CCOPSPTT and DOPSPTT for short, respectively) covered from 25th January to 29th February, 2020 in five city types (i.e., small-, medium-, large-, very large- and super large-sized cities), along with the data of climate, socio-economic determinants, spatial distance of the target city to Wuhan city (DW, for short), and spatial distance between the target city and their local province capital city (DLPC, for short) were collected from the official websites of China. Then the above-mentioned influencing factors on CCOPSPTT and DOPSPTT were analyzed separately in Hubei and other provinces. The results showed that CCOPSPTT and DOPSPTT were significantly different among five city types outside Hubei province (p < 0.05), but not obviously different in Hubei province (p > 0.05). The CCOPSPTT had significant correlation with socio-economic determinants (GDP and population), DW, climate and time after the outbreak of COVID-19 outside Hubei province (p < 0.05), while was only significantly related with GDP in Hubei province (p < 0.05). The DOPSPTT showed significant correlation with socio-economic determinants, DW, time and CCOPSPTT outside Hubei province (p < 0.05), while was significantly correlated with GDP and CCOPSPTT in Hubei province (p < 0.05). Compared with other factors, socio-economic determinants have the largest relative contribution to variance of CCOPSPTT in all studied cities (> 78%). The difference of DOPSPTT among cities was mainly affected by CCOPSPTT. Our results showed that influences of city types on the confirmed cases and death differed between Hubei and other provinces. Socio-economic determinants, especially GDP, have higher impact on the change of COVID-19 transmission compared with other factors.

Carbon dioxide (CO2) emissions from the service industry, traffic, and secondary industry as revealed by the remotely sensed nighttime light data

ABSTRACT Exploring carbon dioxide (CO2) emissions from human activities is essential for urban energy conservation and resource management. Remotely sensed nighttime lights from the Suomi NPP-VIIRS provide spatial consistency in and a low-cost way of revealing CO2 emissions. Although many researches have documented the feasibility of the Suomi NPP-VIIRS data for assessing CO2 emissions, few have systematically revealed the ability of nighttime lights for evaluating CO2 emissions from different industries, such as service industry CO2 emissions (SC), traffic CO2 emissions (TC), and secondary industry CO2 emissions (IC). Here, China was selected as the experimental subject, and we comprehensively explored the relationships between the nighttime lights and SC, TC, and IC, and investigated the factors mediating these relationships. We found that without considering other factors, the nighttime lights only revealed up to 51.2% of TC, followed by 41.7% of IC and 22.7% of SC. When controlling for city characteristic variables, the models showed that there were positive correlations between the Suomi NPP-VIIRS data and SC, IC, and TC, and that nighttime lights have an Inverted-U relationship with SC. The Suomi NPP-VIIRS data are more suitable for revealing SC, TC, and IC in medium-sized and large-sized cities than in small-sized cities and megacities.

Mapping the maximum extents of urban green spaces in 1039 cities using dense satellite images

Spatial data of urban green spaces (UGS) are critical for cities worldwide to evaluate their progress towards achieving the urban sustainable development goals on UGS. However, UGS maps at the global scale with acceptable accuracies are not readily available. In this study, we mapped UGS of all 1039 mid- and large-sized cities across the globe in 2015 with dense remote sensing data (i.e. 51 494 Landsat images) and Google Earth Engine (GEE) platform. Also, we quantified the spatial distribution and accessibility of UGS within the cities. By combining the greenest pixel compositing method and the percentile-based image compositing method, we were able to obtain the maximum extent of UGS in cities while better differentiating UGS from other vegetation such as croplands. The mean overall classification accuracy reached 89.26% (SD = 3.26%), which was higher than existing global land cover products. Our maps showed that the mean UGS coverage in 1039 cities was 38.46% (SD = 20.27%), while the mean UGS accessibility was 82.67% (SD = 22.89%). However, there was a distinctive spatial equity issue as cities in high-income countries had higher coverage and better accessibility than cities in low-income countries. Besides developing a protocol for large-scale UGS mapping, our study results provide key baseline information to support international endeavors to fulfill the relevant urban sustainable development goals.

Spatiotemporal Differentiation of Coupling and Coordination Relationship of Tourism–Urbanization–Ecological Environment System in China’s Major Tourist Cities

Determining the coupling development mode and evolution process of the tourism–urbanization–ecological environment system is of great significance in promoting high-quality and sustainable development of tourism and the urban economy. In this study, an evaluation index system of the tourism–urbanization–ecological environment system was established, and the spatiotemporal differentiation of the coupling and coordination relationship of the tourism–urbanization–ecological environment system was analyzed for 35 major tourist cities in China from 2009 to 2018. The results show that the comprehensive development indices of the tourism industry subsystem and urbanization subsystem of China’s major tourist cities have steadily increased. The comprehensive development indices of large-sized and medium-sized cities in the east are relatively high. From 2009 to 2018, the coordination degree and coupling degree of the tourism–urbanization–ecological environment’ system of 35 tourist cities showed an upward trend. The growth rate of the coupling coordination degree lags behind the growth rate of the coupling degree, and the overall system coordination level is still low. There are significant differences in the coupling degree and coupling coordination degree among the eastern, central, and western cities. This study offers both theoretical and practical implications for further equalizing the development level between the cities, as well as improving the overall coordination between the tourism industry, urbanization, and the ecological environment in China.

Does the E-commerce Transformation of Cities Promote Green and High-quality Development? Evidence from a Quasi-natural Experiment Based on National E-commerce Demonstration Cities

Based on the quasi-natural experiment of national e-commerce demonstration cities, this paper studies the influence of the construction of national e-commerce demonstration cities on the green and high-quality development of the city and its mechanism by using the “progressive” DID method. It is found that compared with non-state e-commerce demonstration cities, the construction of national e-commerce demonstration cities significantly promotes the green and high-quality development of cities. We also adopt identification strategies such as instrumental variable method, PSM-DID method and placebo test, and find that the conclusions are still valid. Further research shows that the positive promotion effect is more significant in the samples of large-sized cities and resource-based cities. It is found that national e-commerce demonstration cities promote the green and high-quality development of the city mainly through the three channels of industrial structure upgrading effect, economic agglomeration effect and transaction cost reduction effect.This paper has three main contributions: Firstly, from the perspective of e-commerce development, it examines the impact of national e-commerce demonstration city construction on green and high-quality development for the first time, and expands and deepens the existing academic literature on green development and environmental pollution factors. Secondly, it evaluates the policy effect and mechanism of China’s e-commerce demonstration cities from the perspective of urban green and high-quality development, verifies that the construction of national e-commerce demonstration cities has a promoting effect on the green and high-quality development of cities, and provides empirical guidance for the further promotion and improvement of this type of urban development model. Thirdly, it adopts the identification strategy of the post stations in the Ming Dynasty and the number of telephone sets per 10,000 people in 1984 as instrumental variables, which is helpful to effectively identify the causal relationship between the pilot policies of national e-commerce demonstration cities and the green and high-quality urban development.

Investigating Regional and Generational Heterogeneity in Low-Carbon Travel Behavior Intention Based on a PLS-SEM Approach

This study aims at reviewing whether regional and generational differences exist in behavior intention to adopt low-carbon travel modes. Based on 759 questionnaires collected from three cities (Zhenjiang, Suzhou, and Shanghai) with different population sizes in China, we develop a modified theory of planned behavior (MTPB) model framework integrating low-carbon transport policies, psychological aspects, personal norms, and travel habits. A more advanced partial least-square method of structural equation model (PLS-SEM) and a multiple-group analysis (MGA) model are applied to estimate the effects and heterogeneities of these factors on low-carbon travel behavior intention among three cities and four age groups. The results show that the roles of low-carbon policies, subjective norms, and personal norms on behavior intention of adopting low-carbon travel modes are more salient. The effect of low-carbon policy on behavior is much weaker than it is on intention, and it does not follow that such intention will often be followed up with action. There is regional and generational heterogeneity in terms of the influence on low-carbon travel behavior intention. In particular, the benefits of low-carbon policies are more remarkable in the middle-sized city, young adult group, and pre-older adult group. The low-carbon travel behavior intention in the large-sized city, junior-middle adult group, and senior-middle adult group are affected by subjective norms more easily. The large-sized city and young adult group have better personal norms in favor of low-carbon travel. The findings could provide helpful insights into developing heterogeneous transport policies to encourage different travelers to switch from auto to low-carbon travel modes.

Does the Construction and Operation of High-Speed Rail Improve Urban Land Use Efficiency? Evidence from China

The construction and operation of high-speed rail (HSR) has become an important policy for China to achieve efficiency and fairness and promote high-quality economic growth. HSR promotes the flow of production factors such as labor and capital and affects economic growth, and may further affect urban land use efficiency (ULUE). To explore the impact of HSR on ULUE, this paper uses panel data of 284 cities in China from 2005 to 2018, and constructs Propensity Score Matching-Differences in Differences model to evaluate the effect of HSR on ULUE. The result of entire China demonstrates that the HSR could significantly improves the ULUE. Meanwhile, this paper also considers the heterogeneity of results caused by geographic location, urban levels and scales. It demonstrates that the HSR has a significantly positive effect on ULUE of Eastern, Central China, and large-sized cities. However, in Western China, in medium-sized, and small-sized cities, the impact of HSR on ULUE is not significant. This paper concludes that construction and operation of HSR should be linked to urban development planning and land use planning. Meanwhile, the cities with different geographical locations and scales should take advantage of HSR to improve ULUE and promote urban coordinated development.

Effects of urban expansion on ecosystem health in Southwest China from a multi-perspective analysis

Effectively exploring the impact of urban expansion on ecosystem health has become a hot topic for sustainable development of cities. However, analyzing the relationship between urban expansion and ecosystem health from a multi-perspective view is relatively rare. Here, taking 438 cities in Southwest China as the study area, we attempted to quantify the relationship between urban expansion and ecosystem health, taking into account population density, economic structure, urban area size, and geological environment. First, the urban ecosystem health was assessed based on the vigor-organization-resilience-services framework. Second, we quantified urban expansion from three aspects: the intensity of expansion, growth modes and urban forms. Finally, the panel data analysis was used to focus on which aspects of urban expansion effect on ecosystem health. The result showed that when the intensity of urban expansion increased and the growth mode changed from edge-expansion type to outlying type, the ecosystem health experienced a significant decline. In addition, there was significant negative correlation between urban size and ecosystem health within all types of cities, except for the mega-scale cities (>100 km2). A regular and aggregated urban form was benefit for ecosystem health at the medium-sized (100–500 person·km−2) and large-sized cities (500–1000 person·km−2). Moreover, urban form complex had a significant negative impact on ecosystem health in industry cities (secondary industry accounts for more than 50%) than in the service cities (tertiary industry accounts for more than 50%). The ecosystem health of karst cities was more sensitive to the fragmentation of urban core than non-karst cities. These findings will help to further understand the influence mechanism of urban expansion on ecosystem health under different scenarios and could provide a scientific basis for formulating reasonable urban planning.

Seasonal occurrence and source analysis of pharmaceutically active compounds (PhACs) in aquatic environment in a small and medium-sized city, China

Pharmaceutically active compounds (PhACs) have been widely reported in most megacities in China but seldom in small and median-sized cities. The aim of this study is to investigate occurrence and distribution characteristics of PhACs in a typical small and medium-sized city in China and analyze their sources. 33 PhACs and 4 chiral drugs were selected for a four-season monitoring campaign in Wujin District, Jiangsu Province, a typical small and median-sized city, in 2018. PhACs concentration level in surface water, ranging from ng L−1 to μg L−1, was lower than in large-sized cities and areas in China. Impact from agricultural sources should be concerned in the study area: (1) Significant correlation between concentrations of antibiotics and NH4-N in surface water indicated the potential impact from agricultural sources (fishponds and livestock farms); (2) Government regulating measures on livestock and poultry farms since January 2018 have effectively decreased macrolides and lincosamides emissions into surface water. As for source analysis, CF/CBZ (Caffeine/Carbamazepine) was a feasible indicator to trace untreated wastewater and enantiomeric fraction values of metoprolol (MTP) were also suggested to be helpful for identifying untreated wastewater. The results of both two indicators indicated more input of untreated wastewater to surface water in the northeast area and upstream of Wuyi Canal. To our best knowledge, this is the first study to systematically analyze PhACs in aquatic environment for a small and medium-sized city in China.

A stream multimetric fish index in a large-sized city in south-eastern Brazil

Abstract: Aim Our study was carried out to develop a multimetric index suitable for urban wadeable streams in Sorocaba, a large-sized city from the Atlantic rainforest in south-eastern Brazil. Methods Twenty-seven stream stretches were selected for environmental and fish evaluation. Twenty ecological metrics were tested over an environmental gradient between the reference and degraded stretches. Candidate metrics were screened for range, responsiveness, and redundancy. We calculated a multimetric fish index (MFI) subdivided into five quality classes: reference ≥ 0.8, 0.6 ≤ good &lt; 0.8, 0.4 ≤ moderate &lt; 0.6, 0.2 ≤ poor &lt; 0.4, and bad &lt; 0.2. Results Four metrics were adequate for discriminating higher biotic quality from degraded stretches. Five stream stretches (18%) were classified as a reference or good, and 16 (60%) were poor or bad. Three reference stretches could be used for a hydromorphological restoration programme. Conclusion Our results indicated that biological integrity was altered, which was indicative of severe environmental degradation. Our study results may be useful for a management and restoration project of the Sorocaba/Médio Tietê hydrographic basin.

Gender and class distinction in travel behavior: evidence from India

Purpose This paper aims to examine the gender differences in various measures of travel behavior for a large-sized Indian city, taking into account the existing class differences. Design/methodology/approach Stratified random sampling technique is used to collect primary data for travel behavior. The collected data is then differentiated on the basis of socioeconomic characteristics and gender. Descriptive statistics are used for analysis. Findings The findings confirm that, women mostly walk and men use motorized vehicles. With an improvement in socioeconomic status, women switch over to public transport and men continue to ride motorized vehicles. While the number of women making everyday trips declines with a rise in socioeconomic status, the number of men rises. Research limitations/implications The study points out at the need for development of an adequate infrastructure of nonmotorized transport and public transport in the city which attends to not only the issue of environmental quality but also of women’s empowerment. Originality/value To the best of the authors’ knowledge, this is the first time a comprehensive analysis of differences in travel behavior between men and women on the basis of socioeconomic status is carried out in this region. This analysis will facilitate the policy makers in understanding the inconsistencies in transport demand between the two groups of population.

Long-term impacts of urbanization through population migration on China’s energy demand and CO2 emissions

Better modeling of urbanization trends helps improve our understanding of the potential range of future energy demands and carbon dioxide emissions in developing countries and make informed response strategies. This paper extends the current analytical structure by integrating the population migration process from rural to urban areas with the energy system into a systematic framework, within which a link between urbanization and energy service demands through direct and indirect effects is built. Taking China as a study case, the results show that approximately 333 million people from rural areas are expected to migrate to urban areas toward 2050, resulting in the expansion of large-sized cities and the rapid growth of future energy service demands. Without significant technological improvements, urbanization will lead to more than double and triple the current energy consumption levels by 2050 in the building and transport sectors, respectively, while energy consumption growth in the industry sector will be the largest due to the rising demand for materials through the indirect effect. As a result, urbanization in China will cause more than double the total primary energy demand and an 82% increase in the carbon dioxide emissions by 2050, compared with 2013. In response, major mitigation measures and the role of each sector in the low carbon urbanization transition have been identified. Non-fossil fuel power generation is the top mitigation strategy, which can contribute 40% to the total mitigation potential, while power sector and industrial sector play a key role in realizing an earlier peak for the whole country. The total capital investment needed in each period will cost less than 2.5% of the total gross domestic product (GDP). Therefore, this work highlights the importance of understanding urbanization impact on energy system through applying an integrated population-energy-environment analytical framework and synthesizing the urbanization and long-term low carbon strategies in developing countries which are under rapid urbanization process.

Efficiency evaluation of urban wastewater treatment: Evidence from 113 cities in the Yangtze River Economic Belt of China

To resolve the increasing water pollution crisis, scientifically evaluating the urban wastewater treatment efficiency (UWTE) is an essential prerequisite to ensure the success of any policies aiming to decrease water pollution. Using 113 city-level panel data in the Yangtze River Economic Belt (YREB)—the biggest economic belt in China, during 2008–2017, this study aims to evaluate the UWTE based on a Bootstrap-DEA and to measure the efficiency changes through a Malmquist index model. The results show that the overall UWTE is at a low level, evidenced by the fact the average efficiency score is 0.51 during 2008–2017, and no cities have an efficiency score equal to 1. The UWTE is in the trend of decreasing, which is mainly caused by the decline of technical progress change. 69.02% of cities are in the state of decreasing returns to scale. The UWTE shows considerable disparities both between regions and city sizes, with the highest efficiency score observed in the midstream area and large-sized cities, the lowest efficiency score observed in the downstream area and small-sized cities. The findings of this study are expected to have great practical significance for governing wastewater pollution.

Comparing social costs of public transport networks structured around an Open and Closed BRT corridor in medium sized cities

Abstract Bus Rapid Transit (BRT) has proven to be an effective and affordable transportation option for large-sized cities. In these cities, BRT is usually considered an effective complement or substitute for rail-based systems, playing a key role in complex multimodal networks with several massive transport corridors. More recently, medium-sized cities of less than 200,000 inhabitants have also considering implementing BRT as a means of mass transit. These cities usually need only a few of these massive transport corridors (often just one), and they must decide how to structure their services. This report discusses which of the two types of BRT-based networks is best for the social interest in the case of medium-sized cities: (1) Closed BRT, in which buses operating inside and outside the corridor are separated and have different designs, or (2) Open BRT, in which the same buses operate inside and outside the corridor, entering and exiting at different points along a route. To answer this question two models with different levels of detail in terms of a city’s characteristics were developed to represent both agency and user costs. In the first model a classic idealized city approach is addressed, while in the second model the problem is solved for the specific geographic characteristics and constraints of a real city. The results based on both models show that when it is optimally configured, Closed BRT networks offer mid-sized cities higher frequencies and lower waiting times. However, these benefits do not offset the cost associated with higher number of transfers that Closed BRT networks require, as compared to Open BRT networks. Transfers not only affect users due to the transferring experience, but also end up making the entire system slower. Overall, Open BRT shows significantly less Total Costs than Closed BRT in most of the scenarios that were analyzed.