Traffic Impacts of the COVID-19 Pandemic: Statewide Analysis of Social Separation and Activity Restriction

The COVID-19 pandemic resulted in significant social and economic impacts throughout the world. In addition to the health consequences, the impacts on travel behavior have also been sudden and wide ranging. This study describes the drastic changes in human behavior using the analysis of highway volume data as a representation of personal activity and interaction. Same-day traffic volumes for 2019 and 2020 across Florida were analyzed to identify spatial and temporal changes in behavior resulting from the disease or fear of it and statewide directives to limit person-to-person interaction. Compared to similar days in 2019, overall statewide traffic volume dropped by 47.5%. Although decreases were evident across the state, there were also differences between rural and urban areas and between highways and arterials both in terms of the timing and extent. The data and analyses help to demonstrate the early impacts of the pandemic and may be useful for operational and strategic planning of recovery efforts and for dealing with future pandemics.

Governing Rural Poverty on Urban Streets: Guangzhou's Management of Beggars in the Reform Era

This study investigates how discourses on panhandling intertwine with the governance of beggars on China's urban streets. It focuses on local policy implementation in Guangzhou city, led by the bureau of civil affairs along with its centres for "custody and repatriation” and "assistance stations.” The study aims to understand how the state regulates panhandling and engages with beggars in public spaces. Exploring the internal logic of the state's approach and how it has changed during the 40 years of reform, it also considers the junctures at which contradictions and conflicts arise. Based on fieldwork data (2011 to 2014) and the analysis of government documents, yearbooks, academic and mass media discourses, I argue that the state's treatment of panhandlers poses a conundrum as welfare measures conflict with control. While several layers of state regulation and actors contradict each other and create grey areas of state-induced informality, people who beg for alms are continuously criminalized and excluded from public space.

Wulumuqi Road

Old-style lilong housing (shikumen 石库门, ‘stone-framed gate') comprised row houses along lanes within a walled border, with a mixture of Western and Chinese design elements, the latter including a walled front courtyard. Dihua (‘enlighten and educate') was an alternative name for Ürümqi and was also the Qing Empire's description of its army's extermination campaign against the Zungar rebellion in one of the bloodiest wars of the eighteenth century. The area thus contrasts sharply with the dominant patterns of urban commercial and residential development in China of mid- or hig-hrise apartment buildings grouped within gated perimeter walls—a spatial form that has proved particularly conducive to administration and control. The fire was the latest in a series of outrages large and small in the wake of China's zero-Covid policy: suicides, those who died without access to emergency medical services, the 27 dead in a Guizhou bus crash while being transported to a quarantine site in September, the workers of Foxconn in Zhengzhou who escaped en masse from their appalling lockdown conditions in late October, the unemployed, the bankrupt, students prevented from leaving their campuses, and the many and varied deprivations of normal life.

Effects of COVID‐19 lockdown measures on nitrogen dioxide and black carbon concentrations close to a major Italian motorway

During the first half of 2020, the Italian government imposed several restrictions to limit the spread of the COVID‐19 pandemic: at the beginning of March, a heavy lockdown regime was introduced leading to a drastic reduction of traffic and, consequently, traffic‐related emissions. The aim of this study is to evaluate the effects of these restrictions on pollutant concentrations close to a stretch of the Italian A22 motorway lying in the Alpine Adige valley. In particular, the analysis focuses on measured concentrations of nitrogen dioxide (NO2) and black carbon (BC). Results show that, close to the motorway, NO2 concentrations dropped by around 45% during the lockdown period with respect to the same time period of the previous 3 years. The equivalent analysis for BC shows that the component related to biomass burning, mostly due to domestic heating, was not particularly affected by the restrictions, while the BC component related to fossil fuels, directly connected to traffic, plummeted by almost 60% with respect to the previous years. Since atmospheric concentrations of pollutants depend both on emissions and meteorological conditions, which can mask the variations in the emission regime, a random forest algorithm is also applied to the measured concentrations, in order to better evaluate the effects of the restrictions on emissions. This procedure allows for obtaining business‐as‐usual and meteorologically normalized time series of both NO2 and BC concentrations. The results derived from the random forest algorithm clearly confirm the drop in NO2 emissions at the beginning of the lockdown period, followed by a slow and partial recovery in the following months. They also confirm that, during the lockdown, emissions of the BC component due to biomass burning were not significantly affected, while those of the BC component related to fossil fuels underwent an abrupt drop.

China's Health Silk Road in the Middle East and North Africa amidst COVID-19 and a Contested World Order

The COVID-19 pandemic has offered China a unique opportunity for worldwide deployment of its longstanding health diplomacy, renamed the Health Silk Road (HSR), now an integral part of its Belt and Road Initiative. As a self-proclaimed South-South collaborator and developer,11Niall Duggan, ‘China's changing role in its all-weather friendship with Africa', In, Sebastian Harnisch, Sebastian Bersick, and Jörn-Carsten Gottwald (Eds). China's International Roles: Challenging or Supporting International Order? (Role Theory and International Relations) (London: Routledge, 2015), pp. 207-225..Beijing has assumed a leadership role, grounded in ‘moral realism', in the world's health governance. Beijing's health diplomacy has received acclaim in the Middle East and North Africa (MENA). However, the pandemic has exacerbated preexisting tensions between China, the United States (US) and European Union (EU). Western countries, wary of China's rising power, reacted resentfully, confirming underlying systemic rivalry. This article argues that the currently disputed, or shifting, world order accounts for the diametrically opposed reactions between the West and the MENA toward China's Health Silk Road.

Estimation of NO2 emission strengths over Riyadh and Madrid from space from a combination of wind-assigned anomalies and a machine learning technique

Nitrogen dioxide (NO2) air pollution provides valuable information for quantifying NOx (NOx = NO + NO2) emissions and exposures. This study presents a comprehensive method to estimate average tropospheric NO2 emission strengths derived from 4-year (May 2018–June 2022) TROPOspheric Monitoring Instrument (TROPOMI) observations by combining a wind-assigned anomaly approach and a machine learning (ML) method, the so-called gradient descent algorithm. This combined approach is firstly applied to the Saudi Arabian capital city of Riyadh, as a test site, and yields a total emission rate of 1.09×1026 molec. s-1. The ML-trained anomalies fit very well with the wind-assigned anomalies, with an R2 value of 1.0 and a slope of 0.99. Hotspots of NO2 emissions are apparent at several sites: over a cement plant and power plants as well as over areas along highways. Using the same approach, an emission rate of 1.99×1025 molec. s-1 is estimated in the Madrid metropolitan area, Spain. Both the estimate and spatial pattern are comparable with the Copernicus Atmosphere Monitoring Service (CAMS) inventory.Weekly variations in NO2 emission are highly related to anthropogenic activities, such as the transport sector. The NO2 emissions were reduced by 16 % at weekends in Riyadh, and high reductions were found near the city center and in areas along the highway. An average weekend reduction estimate of 28 % was found in Madrid. The regions with dominant sources are located in the east of Madrid, where residential areas and the Madrid-Barajas airport are located. Additionally, due to the COVID-19 lockdowns, the NO2 emissions decreased by 21 % in March–June 2020 in Riyadh compared with the same period in 2019. A much higher reduction (62 %) is estimated for Madrid, where a very strict lockdown policy was implemented. The high emission strengths during lockdown only persist in the residential areas, and they cover smaller areas on weekdays compared with weekends. The spatial patterns of NO2 emission strengths during lockdown are similar to those observed at weekends in both cities. Although our analysis is limited to two cities as test examples, the method has proven to provide reliable and consistent results. It is expected to be suitable for other trace gases and other target regions. However, it might become challenging in some areas with complicated emission sources and topography, and specific NO2 decay times in different regions and seasons should be taken into account. These impacting factors should be considered in the future model to further reduce the uncertainty budget.

Open Streets for Whom?

The COVID-19 pandemic has created opportunities for cities to close streets to automobile traffic in the name of public health. Although these interventions promise numerous benefits, neighborhood activists and scholars of color suggest they can perpetuate structurally racist inequities. In this Viewpoint, we implore planners and other city builders to think critically about the impact of these interventions by employing an environmental justice framework. Applying this framework in the open streets context exposes several potential paradoxes that arise. We conclude with a set of best practices that can help city builders transcend these paradoxes and extend this livability revolution to all.

The language of suppression: Muslims, migrant workers, and India's response to COVID-19

When a society faces a moment of crisis, its language can mirror, expose, and reinforce societal chaos and fault lines. As India came to terms with COVID-19, the coronavirus' impacts on different populations exposed and widened India's deep social, economic, and religious divides. This article studies the language of India's response to COVID-19 surrounding three major events that occurred in the early months of the pandemic: the janta curfew, the Tablighi Jamaat incident, and the migrant worker crisis. Through an analysis of media reports, speeches made by Prime Minister Narendra Modi, and representations on social media, we see how forms of linguistic trickery—silence, presuppositions, accommodations, othering, dog whistling, and povertyism—were used to suppress, harm, and marginalize two minority groups: Muslims and migrant workers. This article demonstrates how those in power use language to reflect, shape, and reinforce meaning, social hierarchies, and marginalization in a time of crisis. (Linguistic trickery, othering, silence, presupposition, accommodation, dog whistling, povertyism)

Potential of TROPOMI for understanding spatio-temporal variations in surface NO2 and their dependencies upon land use over the Iberian Peninsula

In orbit since late 2017, the Tropospheric Monitoring Instrument (TROPOMI) is offering new outstanding opportunities for better understanding the emission and fate of nitrogen dioxide (NO2) pollution in the troposphere. In this study, we provide a comprehensive analysis of the spatio-temporal variability of TROPOMI NO2 tropospheric columns (TrC-NO2) over the Iberian Peninsula during 2018–2021, considering the recently developed Product Algorithm Laboratory (PAL) product. We complement our analysis with estimates of NOx anthropogenic and natural soil emissions. Closely related to cloud cover, the data availability of TROPOMI observations ranges from 30 %–45 % during April and November to 70 %–80 % during summertime, with strong variations between northern and southern Spain. Strongest TrC-NO2 hotspots are located over Madrid and Barcelona, while TrC-NO2 enhancements are also observed along international maritime routes close the strait of Gibraltar, and to a lesser extent along specific major highways. TROPOMI TrC-NO2 appear reasonably well correlated with collocated surface NO2 mixing ratios, with correlations around 0.7–0.8 depending on the averaging time.We investigate the changes of weekly and monthly variability of TROPOMI TrC-NO2 depending on the urban cover fraction. Weekly profiles show a reduction of TrC-NO2 during the weekend ranging from -10 % to -40 % from least to most urbanized areas, in reasonable agreement with surface NO2. In the largest agglomerations like Madrid or Barcelona, this weekend effect peaks not in the city center but in specific suburban areas/cities, suggesting a larger relative contribution of commuting to total NOx anthropogenic emissions. The TROPOMI TrC-NO2 monthly variability also strongly varies with the level of urbanization, with monthly differences relative to annual mean ranging from -40 % in summer to +60 % in winter in the most urbanized areas, and from -10 % to +20 % in the least urbanized areas. When focusing on agricultural areas, TROPOMI observations depict an enhancement in June–July that could come from natural soil NO emissions. Some specific analysis of surface NO2 observations in Madrid show that the relatively sharp NO2 minimum used to occur in August (drop of road transport during holidays) has now evolved into a much broader minimum partly de-coupled from the observed local road traffic counting;this change started in 2018, thus before the COVID-19 outbreak. Over 2019–2021, a reasonable consistency of the inter-annual variability of NO2 is also found between both datasets.Our study illustrates the strong potential of TROPOMI TrC-NO2 observations for complementing the existing surface NO2 monitoring stations, especially in the poorly covered rural and maritime areas where NOx can play a key role, notably for the production of tropospheric O3.

Effective and Privacy-Preserving Estimation of the Density Distribution of LBS Users under Geo-Indistinguishability

With the widespread use of mobile devices, location-based services (LBSs), which provide useful services adjusted to users' locations, have become indispensable to our daily lives. However, along with several benefits, LBSs also create problems for users because to use LBSs, users are required to disclose their sensitive location information to the service providers. Hence, several studies have focused on protecting the location privacy of individual users when using LBSs. Geo-indistinguishability (Geo-I), which is based on the well-known differential privacy, has recently emerged as a de-facto privacy definition for the protection of location data in LBSs. However, LBS providers require aggregate statistics, such as user density distribution, for the purpose of improving their service quality, and deriving them accurately from the location dataset received from users is difficult owing to the data perturbation of Geo-I. Thus, in this study, we investigated two different approaches, the expectation-maximization (EM) algorithm and the deep learning based approaches, with the aim of precisely computing the density distribution of LBS users while preserving the privacy of location datasets. The evaluation results show that the deep learning approach significantly outperforms other alternatives at all privacy protection levels. Furthermore, when a low level of privacy protection is sufficient, the approach based on the EM algorithm shows performance results similar to those of the deep learning solution. Thus, it can be used instead of a deep learning approach, particularly when training datasets are not available.

Downtown Vibrancy Plan Complete Streets Project

During the Great Recession in 2009, the City of Salinas began receiving requests from stakeholders concerned with the city's downtown to evaluate the area's circulation and parking. While the initial intent was to improve mobility and manage parking, the focus of the plan expanded through an extensive outreach process. Residents expressed a desire for downtown to become the heart of the city, and a place to gather for civic and community events. Through this process, the plan evolved to include four major themes: Creating a Destination Downtown, Managing Parking Resources, Building the Heart of Salinas, and Stimulating Development Activity. The process, dubbed "The Road to Vibrancy," sought to construct a plan to capture and discuss aspirations, ideas, and concepts;develop and expand concepts jointly through workshops and meetings;debate and refine the Vibrancy Plan to ensure it was done right;and to gain broad-based support so that the plan can and will be implemented. The Vibrancy Plan was shaped heavily by public input through a robust planning process. In fact, nearly all the ideas and concepts presented in the plan were discovered through dialogue with residents, property owners, business owners, and others who shared their aspirations.

China's Belt and Road: Where to Now?

In a recent address, Chinese President Xi Jinping proposed a huge expansion of the BRI, sustained through dialogue, openness, and innovation among BRI participants.2 In place of confrontation, he envisaged cooperation, social and economic development, and bolstered intercultural exchanges.3 China's revitalized BRI would unshackle the transborder movement of capital, enhance infrastructure relationships, and enrich the productivity of BRI traffic globally.4 President Xi pronounced that wellfinanced and supported initiatives "along that path" would protect vital interests both domestically and globally.5 China's present dilemma is in ensuring that it expands its stature as the largest destination for foreign inbound investment (FDI) to offset the risk of losing access to foreign markets. Some developing states are avoiding the road because of fear of incurring debt loads.17 Others that are already on the road are limiting funding for roadwork to avoid increasing debts.18 Chinese banks are imposing higher interest rates on loans and providing shorter periods to repay them.19 The Group of Seven wealthiest Western states are constructing competitor roads and alternative sources of funding and terms of payment, highlighted by the EU's recently announced Global Gateway.20 American banks are competing strategically to counter the resourcing provided by the Asian Infrastructure Development Bank to fund BRI infrastructure development.21 Stern detractors depict China as constructing a controlled highway along which it restricts access, participation, and the right and manner of exit. In their portrayal, China's BRI operates as a directed highway along which it dictates travel according to laws of the road of its ordination and autocratic application.22 Far from eliciting cooperation from participating states and foreign investors, China's BRI plan, according to them, is to erode consent over the direction, length, and safety of the highway.23 At their most generous, critics envisage that China will reformulate Western liberal treaties of trade and investment into instruments of its self-empowerment that are formally attired in legal apparel.24 These criticisms compound already challenging economic and political roadblocks to BRI construction. The direction, pace, and scale of the BRI will be contingent on how China, in deliberation with its partner states, redresses functional and legal blockages on that road.32 China will be scrutinized on how well it can sustain its BRI as the global trailblazer that nurtures productivity along an infrastructure pathway that traverses target states with often distinct but also shifting needs.33 China will also be scrutinized on how well it can manage fluctuating costs and unexpected roadblocks along its BRI, resist fervent BRI competition from the West, and dissuade state partners from withdrawing.

Crowd Counting during a Pandemic to Find Out Community Response to Activity Restriction Policy Using Deep Learning

The pandemic has occurred globally, especially in Indonesia since March 2019. It has been almost 2 years since the danger of spreading the COVID-19 virus was still lurking. Every effort has been made by the government by providing information, counseling, vaccines, and even regulations that limit the level of crowds to a certain scale according to the level of COVID-19 sufferers for each region. Currently, in early 2022, community activities in the city of Malang are allowed to meet face-to-face, such as in the education or office sector. However, if you look at the streets of the Malang city area, you can still see that people are sometimes careless because of the declining death graph due to COVID19. In fact, the government still urges the public to continue implementing the health protocol in various activities and limits the scale of the crowd on certain days. The researcher observes the public's response to all regulations given by the government by detecting objects and crowd counting at two points in the Malang city area, namely Jalan Soekarno Hatta and the entrance to the Malang toll road. The input in the form of photos of street crowds will be processed using computer vision and deep learning to identify the type of object for later analysis of the calculation results according to the calendar and the level of restrictions on current community activities. The percentage of object detection accuracy using deep learning is 80% using a confidence threshold value of 0.3. © 2022 IEEE.

Promoting economic and environmental resilience in the post-COVID-19 era through the city and regional on-road fuel sustainability development

How to control the global temperature rise within 1.5 °C in the post-COVID-19 era has attracted attention. Road transport accounts for nearly a quarter of global CO2 emissions, and the related sulfur dioxide (SO2) emissions also trigger air pollution issues in population-intensive cities and areas. Many cities and states have announced a timetable for phasing out urban-based fossil fuel vehicles. By combining a Markov-chain model with a dynamic stochastic general equilibrium (DSGE) model, the impacts of on-road energy structural change led by phasing out fossil fuel vehicles in the road transportation sector are evaluated. The impact of automobile emissions (both CO2 and SO2) on the environment is evaluated, taking into consideration of variation between cities, regions, and countries. Two other major driving forces in addition to CO2 emissions reduction in promoting fossil fuel vehicles' transition toward net-zero carbon are identified and analyzed with multiple different indicators. Under the framework of the DSGE model, climate policy instruments' effects on economic development, energy consumption, and their link to economic and environmental resilience are evaluated under exogenous shocks as well.

Assessment of fuel price, exchange rate and unemployment rate impact on road passenger journeys in South Africa

In recent decades passenger transportation journeys experienced a decline and this decline may due to various causes such as cost of transportation, low economic growth, exchange rate volatility, unemployment and petrol price. [...]to the best knowledge of the author, no study was conducted to determine the relationship between the aforementioned variables. [...]the main objective of the current study is to analyse the impact of the exchange rate, petrol price and unemployment rate on road passenger journeys in the South African transportation sector. [...]to minimize either monetary budget or physical and mental burden, irrespective of having their cars, people prefer to use public transport (Guo & Wilson, 2011;Onderwater & Kishoon, 2017). South African road transport depend on the imported fuel and the price of the latter within the domestic market is determined by the exchange rate. [...]the exchange rate is another economic variable that impacts road transpo0rt demand (Havenga et al., 2014).

Multilevel Mixed-Effects Models to Identify Contributing Factors on Freight Vehicle Crash Severity

Freight vehicle crashes are more serious than regular vehicle crashes because they are likely to lead to major damage and injury once they occur;therefore, countermeasures are needed. The fatality rate from freight vehicle crashes is 1.5 times higher than that of all other accidents, and the death rate from expressway freight vehicle crashes continues to increase. In this study, the ten-freight-vehicle crash severity models (the ordered logit and probit model, the multinomial logit and probit model, mixed-effects logit and probit model, random-effects ordered logit and probit model, and multilevel mixed-effects ordered logit and probit model) are used to analyze the freight vehicle crash severity factors. The model was constructed using data collected from expressways over eight years, and 13 factors were derived to increase the severity of crashes and 7 factors to reduce the severity of crashes. As a result of comparing the 10 constructed models using AIC and BIC, the multilevel mixed-effects ordered probit model showed the best performance. It is expected that it can contribute to improving the safety of freight vehicles in the expressway section by utilizing factors related to the severity of crashes derived from this study.

Evaluation of Using Genetic Algorithm and ArcGIS for Determining the Optimal-Time Path in the Optimization of Vehicle Routing Applications

Transportation is regarded as one of the most important issues currently being researched;this issue needs the search for approaches or processes that might lessen many contemporary traffic concerns. Congestion, pollution, and accidents have escalated lately, negatively impacting urban environments, economic development, and citizens’ lifestyles. The rise of illnesses and epidemics throughout the world, such as COVID-19, has created an urgent need to find the best way to save people’s lives. The vehicle routing problem (VRP) is a well-known moniker for improving transportation systems and is regarded as one of the ancient and contemporary difficulties in route planning applications. One of the main tasks of VRP is serving many customers by determining the optimal route from an initial point to a destination on a real-time road map. The best route is not necessarily the shortest-distance route, but, in emergency cases, it is the route that takes the least fitness cost (time) and the fastest way to arrive. This paper aims to provide an adaptive genetic algorithm (GA) to determine the optimal time route, taking into account the factors that influence the vehicle arrival time and cause delays. In addition, the Network Analyst tool in ArcGIS is used to determine the optimal route using real-time map based on the user’s preferences and suggest the best one. Experimental results indicate that the performance of GA is mainly determined by an efficient representation, evaluation of fitness function, and other factors such as population size and selection method.

Requirements for the use of impact-based forecasts and warnings by road maintenance services in Germany

Impact-based forecasts and warnings (IBFs) are seen as important drivers for adequate anticipation and assessment of potential threats to public safety as they give a better understanding of the weather event's impacts. To prepare for impacts of weather events and prevent weather-related accidents, road maintenance services are actively using weather information in their daily work routine. This paper looks into the requirements that road maintenance services have for IBFs and how weather forecasts are used at the moment. The study is part of an interdisciplinary research project and follows a qualitative social science research approach. Findings show that the following factors are general user requirements: relevance of information, recognition of spatial and temporal requests, acceptability, comprehensibility, and technical demands. These are also applicable to IBFs with the extension to provide a benefit for road maintenance services in situations that rarely occur and where no embodied knowledge in the organization is existent.