Planned expansion of transportation infrastructure in Brazil has implications for the pattern of agricultural production and carbon emissions

High transportation costs have been a barrier to the expansion of agriculture in the interior of Brazil. To reduce transportation costs, Brazil launched the National Logistics Plan, aiming to expand its railway network by up to 91 % by 2035. Such a large-scale infrastructure investment raises concerns about its economic and environmental consequences. By combining geospatial estimation of transportation cost with a grid-resolving, multi-scale economic model that bridges fine-scale crop production with its trade and demand from national and global perspectives, we explore impacts of transportation infrastructure expansion on agricultural production, land use changes, and carbon emissions both locally and nationally in Brazil. We find that globally, the impacts on output and land use changes are small. However, within Brazil, the plan's primary impacts are impressive. PNL2035 results in the reduction of transportation costs by 8-23 % across states (depending on expansion's extent) in the interior Cerrado biome. This results in cropland expansion and increases in terrestrial carbon emissions in the Cerrado region. However, the increase in terrestrial carbon emissions in the Cerrado is offset by spillover effects elsewhere in Brazil, as crop production shifts away from the Southeast-South regions and accompanying change in the mix of transportation mode for farm products from roadway to more emission-efficient railway. Furthermore, we argue that the transportation infrastructure's impact on the enhanced mobility of labor and other agricultural inputs would further accentuate the regional shift in agricultural production and contribute to carbon emission mitigation. Upon its completion, PNL2035 is expected to result in the reduction of net national emissions by 1.8-30.7 million metric ton of CO2-equivalent, depending on the impacts on labor and purchased input mobility. We conclude that the omission of spillover effects due to infrastructure expansion can lead to misleading assessments of transport policies.

Towards energy conservation by constructing more transportation infrastructure?: An endogenous stochastic frontier analysis framework

Whether constructing more transportation infrastructure can be helpful for the achievement of energy conservation is a long-running and debatable issue. To answer this question, the relationship between transportation infrastructure and energy efficiency must first be clarified. Nonetheless, the existence of the endogeneity problem poses a challenge to defining the relationship. In this paper, an endogenous stochastic frontier analysis method is used to investigate the influence of transportation infrastructure on energy efficiency. Based on the prefecture-city level panel data in China, we find that after addressing the endogeneity problem, the impact of transportation infrastructure on energy efficiency increases dramatically. Moreover, this impact is more pronounced in small-scale cities compared to large and medium-scale cities. Regardless of the measurement of transportation infrastructure, instrumental variable, or production function form, we get the similar conclusions, demonstrating the robustness of our findings. Additional simulation analysis shows that the energy conservation potential would be 1222-2935 million kilowatt hours if the level of transportation infrastructure could be optimized. We recommend accelerating the transportation infrastructure construction, particularly in the small-scale cities so as to boost the energy efficiency and achieve energy conservation targets.

Carbon footprints across transport infrastructure development and industrial output in Pakistan

Over the past few decades, the development of transport infrastructure has attracted huge local and foreign direct investments to raise the overall industrial output in Pakistan. Meanwhile, the transport sector has emerged as one of the most emissions-intensive industrial sectors. Thus, this study is the first to investigate how Pakistan's transport infrastructure across four modes-roads, trains, ports, and airways-affects industrial value addition and carbon footprints in the country. By making use of the theoretical and empirical literature, the study builds carbon emission and economic output models to determine the economic and environmental sustainability of transport infrastructure development in the country. The empirical findings conclude long-term environmental sustainability issues in transportation infrastructure development. All means of transport infrastructure development have a significant positive impact on carbon dioxide emissions in the country. Only ports and highways, however, provide a positive contribution to industrial output. Additionally, population growth, capital, labor, and urbanization are positively linked with the industrial output and carbon dioxide emission in the country, whereas trade openness helps to offset the emission intensity to some extent. Given this evidence, we provide detailed policy implications by highlighting the significance of greener technologies under new transport-related infrastructure investment that addresses SDG-9.

Spatial effect of transportation infrastructure on regional circular economy: evidence from Guangdong-Hong Kong-Macao Greater Bay Area

Compared with the linear economy, the circular economy can solve the contradiction between social development and resource utilization, which has attracted wide attention. Although the relationship between transportation infrastructure and economic development has changed from traditional mode to spatial mode, the spatial effect of transportation infrastructure on regional circular economy is still unclear. By combining the policy changes for developing the circular economy in China, this study constructs a comprehensive index of circular economy development in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA). Based on the time and space development of the circular economy in GBA, we analyze the spatial effect of transportation infrastructure on it. The results show that the regional circular economy in GBA has developed, but has not been decoupled from economic development. The development of the regional circular economy presents a positive spatial spillover effect, which is beneficial to the building of the regional recycling market. The improvement of transportation infrastructure has a positive impact on the circular economy of neighboring cities, but it may have the risk of inhibiting the development of the local circular economy. These findings provide policy recommendations for urban planners to coordinate the development of transportation infrastructure and circular economy.

On transportation, economic agglomeration, and CO2 emissions in China, 2003-2017

This study analyzes the effects of transportation infrastructure on carbon emissions (CE) based on the level of urban economic agglomeration. For this purpose, 281 Chinese cities are considered during the period 2003-2017. A Moran's I index is used to assess the spatial distribution characteristics of transportation infrastructure and CE. In addition, a spatial Durbin model is employed to explore the spatial spillover effect of transportation infrastructure on CE. Furthermore, economic agglomeration is considered as a crucial transmission mechanism. The empirical results show that (1) a significant spatial autocorrelation exists between transportation infrastructure and CE. (2) Transportation infrastructure significantly aggravates CE, with the "neighboring effect" being surprisingly more potent than the "local effect." (3) Economic agglomeration is a valid transmission channel through which transportation infrastructure affects CE, the intensity of which varies with the level of economic agglomeration. Our recommendation is that policy-makers should pay attention to the development of local transportation, as well as their neighboring cities, and should accelerate the advancement of green transportation.

High-Speed railways and the spread of Covid-19

High-speed railways (HSRs) greatly decrease transportation costs and facilitate the movement of goods, services, and passengers across cities. In the context of the Covid-19 pandemic, however, HSRs may contribute to the cross-regional spread of the new coronavirus. This paper evaluates the role of HSRs in spreading Covid-19 from Wuhan to other Chinese cities. We use train frequencies in 1971 and 1990 as instrumental variables. Empirical results from gravity models demonstrate that one more HSR train originating from Wuhan each day before the Wuhan lockdown increases the cumulative number of Covid-19 cases in a city by about 10 percent. The empirical analysis suggests that other transportation modes, including normal-speed trains and airline flights, also contribute to the spread of Covid-19, but their effects are smaller than the effect of HSRs. This paper's findings indicate that transportation infrastructures, especially HSR trains originating from a city where a pandemic broke out, can be important factors promoting the spread of an infectious disease.

How does transportation infrastructure affect urban carbon emissions? an empirical study based on 286 cities in China

With the extensive and in-depth exploration of the relationship between municipal infrastructure and carbon emissions in prefecture-level cities, the implicit internal relationship with traffic has become increasingly profound. Based on the Spatial Dubin Model (SDM) and mediation effect theory, the affiliation mechanism of transportation infrastructure affecting carbon emissions was investigated using a panel dataset of 286 cities in China during a 15-year period from 2002 to 2017. The findings revealed that carbon emissions may cluster in space, especially in developed regions in China, which exhibit high-high aggregation, and transportation infrastructure, industrial structure, energy consumption, and the improvement in Internet of things information technology promote communication and flow between prefecture-level cities, but the nexus between traffic system and carbon emissions is nonlinear and endogenous, especially road infrastructure exacerbating peripheral urban carbon emissions through industrial agglomeration effects and tourism mobility effects as mediating factors. In terms of nationalized industrial distribution, the strategy for large-scale development of western China and the shift in economic and industrial focus to less developed prefecture-level cities fit with the empirical results of this study. Moreover, optimizing the industrial structure and developing clean energy could effectively mitigate carbon emissions. Policy-makers could also change residents' cultural consumption perceptions by promoting green tourism and government subsidies to achieve China's carbon neutrality policy goals.

Towards the automated large-scale reconstruction of past road networks from historical maps

Transportation infrastructure, such as road or railroad networks, represent a fundamental component of our civilization. For sustainable planning and informed decision making, a thorough understanding of the long-term evolution of transportation infrastructure such as road networks is crucial. However, spatially explicit, multi-temporal road network data covering large spatial extents are scarce and rarely available prior to the 2000s. Herein, we propose a framework that employs increasingly available scanned and georeferenced historical map series to reconstruct past road networks, by integrating abundant, contemporary road network data and color information extracted from historical maps. Specifically, our method uses contemporary road segments as analytical units and extracts historical roads by inferring their existence in historical map series based on image processing and clustering techniques. We tested our method on over 300,000 road segments representing more than 50,000 km of the road network in the United States, extending across three study areas that cover 42 historical topographic map sheets dated between 1890 and 1950. We evaluated our approach by comparison to other historical datasets and against manually created reference data, achieving F-1 scores of up to 0.95, and showed that the extracted road network statistics are highly plausible over time, i.e., following general growth patterns. We demonstrated that contemporary geospatial data integrated with information extracted from historical map series open up new avenues for the quantitative analysis of long-term urbanization processes and landscape changes far beyond the era of operational remote sensing and digital cartography.

Will improvements in transportation infrastructure help reduce urban carbon emissions?--motor vehicles as transmission channels

Achieving the "dual carbon" goal requires focusing on the issue of urban transportation carbon emissions. This study derives the mechanism of transportation infrastructure on urban carbon emissions and uses panel data from 284 cities in China from 2004 to 2017 as a basis for empirical analysis through the two-stage least squares method (2SLS). The results of the study show that the improvement of transportation infrastructure has a significant negative effect on the level of urban carbon emissions, and it is greater than the positive spillover of the increase in the number of motor vehicles on urban carbon emissions. Further, research has shown that improvement of transportation infrastructure has no significant impact on the purchase of motor vehicles; therefore, the transportation infrastructure will not affect the "induced traffic" through the purchase of motor vehicles, thereby further affecting the level of urban carbon emissions. The enlightenment of this article include the following: In urban planning and construction, attention should be paid to reducing urban carbon emissions by improving the construction of transportation infrastructure to help China achieve its carbon peak and carbon neutral goals at an early date.

Can transportation infrastructure reduce haze pollution in China?

Traffic emission is one of the main sources of haze pollution, but few studies have evaluated the dynamic impact and mechanism of transportation infrastructure on haze pollution based on a spatial perspective. This study selects the annual data of 30 provinces in China from 2000 to 2017 and uses a dynamic spatial Durbin model to study the dynamic impact of transportation infrastructure on haze pollution. The results show that transportation infrastructure has a significant spatial spillover effect on haze pollution, and the spatial spillover effect has regional heterogeneity. Specifically, whether long term or short term, highway traffic has a boosting effect on haze pollution, while railway traffic has an inhibitory effect on haze pollution. In addition, transportation infrastructure can affect haze pollution through three paths: expanding economic scale, promoting transformation of industrial structure, and promoting technological progress. At the regional level, the improvement of highway traffic density in eastern, central, and western regions will significantly increase haze pollution. The enhancement of railway traffic density has a significant inhibitory and boosting effect on haze pollution in central and western regions, respectively. For the eastern region, railway traffic construction can only restrain local haze pollution, but cannot exert the spatial spillover effect of railway traffic to reduce haze. The conclusions of this paper provide policy inspirations for giving full play to the haze reduction effect of transportation infrastructure and the development of green transportation.

JUE insight: Migration, transportation infrastructure, and the spatial transmission of COVID-19 in China

This paper evaluates the impacts of migration flows and transportation infrastructure on the spatial transmission of COVID-19 in China. Prefectures with larger bilateral migration flows and shorter travel distances with Hubei, the epicenter of the outbreak, experienced a wider spread of COVID-19. In addition, richer prefectures with higher incomes were better able to contain the virus at the early stages of community transmission. Using a spatial general equilibrium model, we show that around 28% of the infections outside Hubei province can be explained by the rapid development in transportation infrastructure and the liberalization of migration restrictions in the recent decade.

What factors impact pedestrian and cyclist fatalities? A state level analysis

Background

Pedestrian and bicyclist injuries and fatalities have increased since 2010 after a long downward trend. Trucks and SUVs, collectively called light trucks, have also increased in sales and size, which may affect pedestrians and bicyclists. Additionally, pedestrian and cyclist commuters vary by state and it has been speculated that an increase in such commuters may affect fatalities. Studying vulnerable road users can bestow clues on best practices for infrastructure and public health.

Methods

State level pedestrian and cyclist fatality data was obtained from the National Highway Transportation Safety Administration for 2018. Light truck registration by state was obtained from the Office of Highway Policy Information for 2018. Commuters who walk or bike to work were obtained from the American Community Survey from 2009 to 2011, from the latest Centers for Disease Control report. We performed multiple linear regression, accounting for total motor vehicle lane miles per 100 people, also obtained from the Office of Highway Policy Information for 2018. Multiple regression analysis was performed to assess predictors for pedestrian and cyclist fatalities with the predictors variables of light truck registration, lane miles per 100 people, and proportion of commuters who are vulnerable road users. Secondary analysis included simple linear regression of the predictor variables against each other.

Results

The multiple regression model, including proportion of light truck registration, lane miles per 100 people, and proportion of commuters who are vulnerable road users, accounted for 18% of the variability in the outcome variable (p = 0.03). An increased number of vulnerable road users were negatively associated with pedestrian and bicyclist fatality. Additionally, there appeared to be an association between motor vehicle lane miles per 100 people and proportion of light truck registrations that was also significant (p < 0.01).

Conclusion

The variables affecting vulnerable road user deaths are important to understand given their increased risk exposure on the road. This state level study identifies a potential protective variable with increased vulnerable road users being associated with a decrease in pedestrian and bicyclist death rates. Additionally, light truck proportions do not appear to have a significant effect on death rates.

Built environment and early infection of COVID-19 in urban districts: A case study of Huangzhou

Since COVID-19 spread rapidly worldwide, many countries have experienced significant growth in the number of confirmed cases and deaths. Earlier studies have examined various factors that may contribute to the contagion rate of COVID-19, such as air pollution, smoking, humidity, and temperature. As there is a lack of studies at the neighborhood-level detailing the spatial settings of built environment attributes, this study explored the variations in the size of the COVID-19 confirmed case clusters across the urban district Huangzhou in the city of Huanggang. Clusters of infectious cases in the initial outbreak of COVID-19 were identified geographically through GIS methods. The hypothetic relationships between built environment attributes and clusters of COVID-19 cases have been investigated with the structural equation model. The results show the statistically significant direct and indirect influences of commercial vitality and transportation infrastructure on the number of confirmed cases in an infectious cluster. The clues ch inducing a high risk of contagions have been evidenced and provided for the decision-making practice responding to the initial stage of possible severe epidemics, indicating that the local public health authorities should implement sufficient measures and adopt effective interventions in the areas and places with a high probability of crowded residents.

COP21 Roadmap: Do innovation, financial development, and transportation infrastructure matter for environmental sustainability in China?

The purpose of the present study is to explain the long-run and causal effects of innovation, financial development, and transportation infrastructure on CO₂ emissions using the combined cointegration and wavelet coherence approaches over the period from 1971 to 2018, while using economic growth as a control variable in the model. The outcomes of the Bayer-Hanck cointegration test show that there is an important cointegration equation among CO₂ emissions, innovation, financial development, transportation infrastructure, and real GDP. Moreover, the findings from a wavelet power spectrum reveal that there is a significant vulnerability in innovation, financial development, transportation infrastructure, and CO₂ emissions at different time frames and frequencies. Furthermore, the outcomes of wavelet coherence approach reveal that (i) Innovation is observed as a significant predictor of CO₂ emissions over the period from 2007 to 2013; (ii) In the long run, there are negative correlations between CO₂ emissions and financial development; (iii) Over the periods from 2000 to 2015, and from 1985 to 1989, transportation significantly causes CO₂ emissions. Our findings have substantial policy implications that suggest there is a need to strengthen innovation and transportation infrastructure to achieve environmental sustainability targets.

Numerical simulation of pollutant transport in soils surrounding subway infrastructure

With continued urbanization, public transport infrastructure, e.g., subways, is expected to be built in historically industrial areas. To minimize the transfer of volatile organic compounds and metalloids like arsenic from industrial areas into subway environments and reduce their impact on public health, the transport of pollutants in soil was simulated in this study. During numerical simulations of a contaminated site, the pollutant (arsenic) was transported from layers of higher to lower concentration, and concentration changes were particularly evident in the early simulation stages. The pollutant was transported in soil along the direction of groundwater flow and spread from the center to the periphery of the contaminated zone without inputs from pollution sources. After approximately 400 days, the concentration of all layers became uniform, with slow decreases occurring over time. The pollutant supply rate had a major influence on the pollutant diffusion distance. When other conditions were kept constant, higher supply rates resulted in longer diffusion distances. The simulation results show that a diaphragm wall of a certain depth can effectively control the diffusion of pollutants in soil. These results can be used to improve environmental assessments and remediation efforts and inform engineering decisions during the construction of urban infrastructure at sites affected by historical pollution.

A Different Trolley Problem: The Limits of Environmental Justice and the Promise of Complex Moral Assessments for Transportation Infrastructure

Transportation infrastructure tremendously affects the quality of life for urban residents, influences public and mental health, and shapes social relations. Historically, the topic is rich with social and political controversy and the resultant transit systems in the United States cause problems for minority residents and issues for the public. Environmental justice frameworks provide a means to identify and address harms that affect marginalized groups, but environmental justice has limits that cannot account for the mainstream population. To account for this condition, I employ a complex moral assessment measure that provides a way to talk about harms that affect the public.