Cycling Routes Research Articles

A GIS based spatiotemporal modelling approach for cycling risk mapping using crowd-sourced sensor data

ABSTRACT The major objective of this study is to apply integrated data-driven methods to estimate cyclist risk and discomfort in Berlin based on the OpenSenseMap dataset. The proposed approach makes use of crowd-sourced sensor data collected during cycling (speed, bike vibration, distance to other objects), spatial statistics and multi-criteria decision analysis to provide a continuous estimation of cycling discomfort and risk in the traffic network. We employed cycling traffic volume and route discomfort estimation techniques to determine the spatiotemporal patterns of cycling traffic volume and discomfort levels. Accordingly, a GIS-based multiple criteria analysis approach was applied to map areas with high cycling traffic volume based on the condition of the cycling lanes, environmental, road traffic, land use and sociodemographic characteristics. The results show that the central area of Berlin has a high cycling traffic volume as well as a high level of discomfort. In this context, we found a significant spatial correlation between the cycling traffic volume and discomfort with the land use characteristics such as commercial or residential areas, motor vehicle traffic volume and sociodemographic characteristics in Berlin. Furthermore, results revealed a correlation between intensive traffic volume and commercial zones, schools and university areas. As we identified high-risk cycling directions and their autocorrelation with relevant indicators, the obtained results from this study will support decision-makers and authorities in recognizing the high-risk cycling areas and optimizing the risk areas, which accordingly increase the cycling safety and wellbeing of citizens.

Impact of Climate Change on Transmission Patterns of Infectious Diseases and Public Health Responses

Global warming has expanded the transmission range of some pathogens and disease vectors (such as mosquitoes) that initially lived in tropical or subtropical regions, increasing their chances of disease transmission. This change increases the risk of the spread of some infectious diseases, such as dengue fever, malaria and cholera. These infectious diseases have caused a huge impact and harm to human health. Therefore, this article analyzes and summarizes some academic research articles to study infectious disease changes and spread ways, and why these infectious diseases are affected by climate change and the influence of public health measures, through this topic research also can clearly know how climate change will make the pathogen life cycle and transmission route, expand media activities, finally should strengthen monitoring and early warning system, promote international cooperation, improve public health facilities and environmental health targeted control strategies, strengthen public education and health propaganda.

An examination of public perspectives on cycle infrastructure projects: An Irish case study

Increasing levels of everyday cycling has many benefits for both individuals and for cities. Reduced traffic congestion, improved air quality and safer spaces for all vulnerable road users are among the significant benefits for urban developments. Despite this, public opposition to cycling infrastructure is common, particularly when it involves reprioritising road space for cycles instead of vehicles. The purpose of the research was to examine various stakeholders’ perspectives on proposed cycle infrastructure projects. This study utilised an innovative data collection approach through detailed content analysis of 322 public consultation submissions on a proposed active travel scheme in Limerick City, Ireland. By categorising submissions into support, opposition, and proposals, the study reveals the nuanced public perceptions that influence behavioural adaptation and acceptance of sustainable transport infrastructure. Supportive submissions, which outnumbered opposition-related submissions by approximately 2:1, emphasised the need for dedicated cycling infrastructure, enhanced cyclist safety, and potential improvements in environmental conditions. In contrast, opposition submissions focused on concerns over car parking removal, decreased accessibility for residents, and safety issues for vulnerable populations, particularly the elderly. Proposal submissions suggested design modifications, including enhanced safety features, provisions for convenient car parking, and alternative cycle routes. This paper highlights the value of structured public consultation data in uncovering behavioural determinants and barriers to cycling infrastructure adoption, offering policymakers essential insights into managing public opposition and fostering support. The methodology demonstrates how qualitative data from consultations can be effectively used to inform policy by capturing community-specific needs and enhancing the design of sustainable urban mobility systems. These findings underscore the need for innovative, inclusive data collection methods that reveal public sentiment, facilitating evidence-based transport policies that support climate-neutral mobility.

Involving Infrastructure as a Latent Variable in Active Transportation Mode Choice: The Case Study of Baghdad City

Infrastructural developments have been implemented with the objective of promoting active transportation as a sustainable transportation mode, including the construction of cycling and walking routes and the improvement of existing infrastructure. The impact of this factor on ridership has been a subject of research, and the incorporation of this variable into mode choice models has also been contemplated. Nevertheless, road users’ perception regarding the utilization of these infrastructures has yet to be investigated. Accordingly, this research aims to examine the role of infrastructure provision for walking and cycling as a Latent Variable (LV) in the transport mode choice of high school students in Baghdad City, where this subject has not been previously addressed. A self-designed questionnaire was employed to collect the requisite data. The Integrated Choice and Latent Variable (ICLV) models have been designed and the results demonstrate that the time and cost of trips have a significant impact on the choice of transportation mode. Furthermore, the provision of walking and cycling infrastructure has a notable effect on the choice of walking and cycling for transport. The sub-models indicate that the provision of cycling fences and pedestrian bridges are the most significant variables. Consequently, it is recommended that these results be considered in the provision and improvement of cycling and walking infrastructures to promote active transportation.

Safety and bicycle route choice – To what extent does accident risk and perceived safety influence bicycle route choice?

Safety is a major issue in bicycle traffic and understanding safety-related factors that influence bicycle route choice is crucial for improving safety and promoting sustainable transportation. However, there is a notable lack of research on the impact of accident risk and perceived safety on cyclists' route choice. This study addresses this gap by investigating whether accident-prone areas or perceived insecure locations affect actual route choice decisions. The contribution explores this relationship by leveraging an extensive dataset comprising approximately 4,000 trips from around 170 participants, alongside additional data on infrastructure, operations, exposure, accidents, and mobility diaries on critical incidents. The findings broadly confirm the results from other studies regarding the influence of route characteristics (e.g., existence of cycling infrastructure, traffic volumes of motorized traffic, or presence of signal-controlled intersections). Moreover, the study reveals that a high accident risk along a route does have a slight negative influence on route choice. Surprisingly, perceived safety does not significantly influence route choice of cyclists.

Set Covering Routing Problems: A review and classification scheme

Cyclic routing problems are a well-researched category of combinatorial problems in Operations Research (OR). They involve finding an optimal cycle (route), starting from an initial point (e.g., depot), visiting some nodes (e.g., customer or demand points), and returning to the starting point while adhering to constraints and optimizing a specific objective. These problems are categorized into two main types: (i) Hamiltonian routing problems: All customer nodes must be visited (must be on a cycle), such as the Traveling Salesman Problem (TSP), seeking the shortest possible cycle visiting each node once. (ii) Non-Hamiltonian routing problems: At least one customer node is not on a route. This work mainly focuses on classifying one of the main sub-problems of non-Hamiltonian routing problems, known as Set Covering Routing Problems (SCRPs), in which customers may be directly visited or covered by another node on the cycle or route. The SCRPs also incorporate Steiner nodes (transition points) to cover the customers who are not directly visited, integrating covering and routing decisions. SCRPs have wide-ranging applications in logistics, transportation planning, healthcare, telecommunication network design, and disaster response, making them vital for theoretical exploration and practical solutions. This work reviews the studies on SCRPs, presenting a classification scheme and a generic mathematical model for these problems, enabling a unified analysis and comparison. Finally, the study gaps, future research directions, and the limitations and implications for practical applications are discussed.

Comparative life cycle assessment and route optimization modeling of smart versus conventional municipal waste collection: Environmental impact analysis in an urban context

This study conducts a life cycle assessment comparing smart and conventional municipal waste collection systems over a 10-year period in a medium-sized urban area, employing the IMPACT 2002+ method and simulation modeling. The smart waste collection system demonstrated significant environmental advantages across key impact categories. Global Warming Potential was reduced by 45.7 % (19,209,995 kg CO₂ eq vs. 35,370,480 kg CO₂ eq) through optimized route planning and reduced fuel consumption. Human health impacts improved substantially, with the smart system showing a net positive effect (-9.7756731 DALY) compared to the conventional system's detrimental impact (23.574054 DALY). Ecosystem quality impacts decreased by 37.3 % (15,662,705 vs. 24,999,196 PDFm²yr), while resource depletion was 46 % lower in the smart system, despite increased mineral extraction for electronic components. The simulation revealed a 52 % reduction in vehicle distance traveled (38,535.36 vs. 80,282.00 km/month). While demonstrating clear environmental benefits, the study identifies challenges in electronic component lifecycle management and mineral resource recovery. Future research should prioritize developing recyclable components, integrating renewable energy sources, and optimizing end-of-life management strategies. These findings provide practical guidance for municipalities transitioning to smart waste collection systems, particularly in medium-sized urban areas. Real-world implementations in cities like Amsterdam and Barcelona have shown similar improvements, with route efficiency gains of 35–40 %, validating the potential of smart waste management technologies in urban sustainability initiatives.

Spatio-temporal analysis of bicyclists' PM2.5 exposure levels in a medium sized urban agglomeration.

Many cities have promoted decarbonized transportation modes to mitigate climate change, reduce air pollution and promote healthy behaviors. However, cyclists may be particularly exposed to higher concentrations of on-road air pollutants than other commuters due to their proximity to traffic, higher breathing rates, and prolonged commutes. In addition, there is scarce information analyzing the geographic exposure levels of cyclists in medium-sized urban agglomerations of Latin American cities. We aimed to assess cyclists' exposure to PM2.5 at the spatio-temporal level using low-cost sensors in the Mendoza Metropolitan Area, Argentina. We calculated PM2.5 inhalation doses (IDs) for different routes with distinctive characteristics, considering different age ranges and gender of cyclists. The dose was represented as temporally and spatially disaggregated exposure maps, one of the first to represent it in Latin America using this method. All link types analyzed exhibited significant differences in PM2.5 concentrations, although the most frequent concentrations were less than 5µgm-3, with secondary peaks of 6.5 and 9µgm-3. As expected, ID increases with age and is greater in males than in females. Our findings further reinforce the fact that route choice (busy vs. quiet) and time of day (peak vs. off-peak) appreciably affect the pollutant exposure of cyclists. All these results could be helpful in the selection of alternative cycling routes with lower PM2.5 at different hours of day but also enable us to investigate further implications of exposure to PM2.5 for the health of urban bicycle commuters.

Modelling the impact of road infrastructure on cycling moving speed

Cycling for transport is a sustainable alternative to using motorised vehicles for daily trips and is a key form of micromobility. Travel time is a critical factor influencing cycling route choice behaviour and uptake. Thus, it is important to understand the factors affecting cycling travel time and speed and their impact on cycling behaviour. In this study, an agent-based transport simulation model with heterogeneous cycling speeds was developed and used for Melbourne to study the impact of a hypothetical traffic signal optimisation intervention along six key cycling corridors. Linear regression and random forest models were used to identify factors affecting cycling speed, which informed the parameters of the agent-based model. Simulation outputs showed, on average, an increase of 4.1 % in the number of cyclists on the corridors, as existing cyclists chose to use these corridors, and an average reduction in cyclists’ moving travel time of 6.2 % for those using the intervention corridors (excluding time spent waiting at traffic signals). The findings provide insights into the effects of road attributes on cycling speed and behaviour, as well as the effectiveness of interventions aimed at reducing cycling delays. These insights are valuable for developing solutions to optimise urban infrastructure for micromobility, enhancing the efficiency and appeal of cycling as a viable transport option.

A Theoretical Perspective for Ammonia Synthesis: Nitric Oxide or Nitrate Electroreduction?

Ammonia is an important raw material for agricultural production, playing a key role in global food production. However, conventional ammonia synthesis resulted in extensive greenhouse gas emissions and huge energy consumption. Recently, researchers have proposed electrocatalytic reverse artificial nitrogen cycle (eRANC) routes to circumvent these issues, which can be driven by electrocatalysis and sustainable electricity. Here, a theoretical and computational perspective on the challenges and opportunities with the comparison with experimental results: electrochemical reduction of nitrate (eNO3RR) and nitrite (eNO2RR), electrochemical reduction of nitric oxide (eNORR) combined with oxidative nitrogen fixation are presented. By comparison, the N2→NO→NH3 route is proposed as the most promising in case the NO solubility can be solved well in reactor design. Its high efficiency of ammonia production is demonstrated. Instead, the eNO3RR can be another choice because it is non-toxic and the solid-liquid interface is usually efficient for electrochemical reactions, while its low selectivity at low overpotentials is an issue. These fundamentals highlight the potential and key factors of eRANC as an efficient and sustainable route for ammonia production.

Collecting population-representative bike-riding GPS data to understand bike-riding activity and patterns using smartphones and Bluetooth beacons

Bike-riding GPS data offers detailed insights and individual-level mobility information which are critical for understanding bike-riding travel behaviour, enhancing transportation safety and equity, and developing models to estimate bike route choice and volumes at high spatio-temporal resolution. Yet, large-scale bicycling-specific GPS data collection studies are infrequent, with many existing studies lacking robust spatial and/or temporal coverage, or have been influenced by sampling biases leading to these data lacking representativeness. Additionally, accurately detecting bike-riding trips from continuously collected raw GPS data without human intervention remains a challenge. This study presents a novel GPS data collection approach by leveraging the combination of a smartphone application with a Bluetooth beacon attached to a participant’s bike. Aided by minimal heuristic post-processing, our method limits data collection to trips taken by bike without the need for participant intervention, carefully optimising between survey participation, privacy challenges, participant workload, and robust bike-riding trip detection. Our method is applied to collect 19,782 bike trips from 673 adults spanning eight months and three seasons in Greater Melbourne, Australia. The collected dataset is shown to represent the underlying adult bike-riding population in terms of demographics (sex, occupation and employment type), temporal and spatial patterns. The average trip length (median = 4.8 km), duration (median = 20.9 min), and frequency of bicycling trips (median = 2.7 trips/week) were greater among men, middle-aged and older adults. The ‘Interested but Concerned’ riders (classified using Geller typology) rode more frequently, while the ‘Strong and Fearless’ and ‘Enthused and Confident’ groups rode greater distances and for longer. Participants rode on roads/streets without bike infrastructure for more than half of their trips by distance, while spending 24% and 17% on off-road paths and bike lanes respectively. This population-representative dataset will be key in the context of urban planning and policymaking.

Exploring the geographical equity-efficiency tradeoff in cycling infrastructure planning

Cycling is affordable, healthy, and sustainable, but access to destinations on low-stress safe cycling routes in most cities is both limited and unevenly distributed. Many cities are expanding cycling networks to improve safety, increase cycling mode share, and increase diversity in access to cycling, however resources remain limited which requires prioritization of infrastructure. When proposed infrastructure locations are optimized to provide the highest average access to opportunities using a utilitarian definition of accessibility, marginalized groups and locations may be further left behind. This occurs since the greatest gains to network connectivity, using a utility definition, come from expansions inside or directly adjacent to the densest network areas. We compare utilitarian and equity-driven planning strategies for cycling network expansion and explore tradeoffs in spatial coverage, equity, and efficiency, using Toronto, Canada as a case study. We find that optimizing accessibility in several small regions instead of city-wide leads to an infrastructure plan that is more spatially dispersed. Further, we show that an optimization model targeting low-access areas produces an infrastructure plan with more regions meeting a minimum threshold of accessibility but with lower average accessibility gains, indicating the presence of an equity-efficiency tradeoff. We also find that infrastructure projects that maximize a region's accessibility to jobs are often located outside that region, challenging political perceptions of "local" infrastructure and benefits. These results inform planning, advocacy, design, and policy, and shed light on spatial and socio-demographic equity tradeoffs in deciding where to add cycling infrastructure.

Cycle route uptake and scenario estimation (CRUSE): an approach for developing strategic cycle network planning tools

This paper describes an approach for developing strategic cycle network planning tools. Based on our experience developing and deploying the Cycle Route Uptake and Scenario Estimation (CRUSE) Tool for Ireland, we outline the underlying methods, including disaggregation of origin–destination data with the open source ‘odjitter’ software, incorporation of additional trip purposes, routing, scenario generation, and development of an intuitive user interface that is tested and used by practitioners. Commissioned by the national infrastructure agency Transport Infrastructure Ireland, CRUSE provides estimates of current and potential future cycling levels under ‘snapshot’ scenarios to inform investment decisions. The publicly available results at https://cruse.bike/ enable planners, engineers, and other stakeholders to make more evidence-based decisions. CRUSE goes beyond previous work by: modeling networks at high spatial resolution; simulating multiple trip purposes (social, shopping, personal utility, recreational, and cycle touring), supplementing official origin–destination datasets on travel for work and education; and providing estimates of ‘quietness’ (a proxy for cyclist comfort and route preference) at the route segment level. Three network types—‘Fastest’, ‘Balanced’, and ‘Quietest’—help plan both arterial and residential cycle networks. Workshops with stakeholders were used to inform the development of the tool. Feedback shows that the tool has a wide range of uses and is already being used in practice to inform urban, inter-urban, and rural cycle network designs. The approach is flexible and open source, allowing the underlying ideas and code to be adapted, supporting more evidence-based and effective cycling policies and interventions internationally.

Informed sampling and recommendation of cycling routes: leveraging crowd-sourced trajectories with weighted-latent Dirichlet allocation

Attractive cycling routes can effectively promote active mobility, thus reducing the twin pressures of the population boom and the greenhouse effect. However, the existing approaches for cycling route recommendation primarily concentrate on identifying the most efficient routes while ignoring the urban spatial context, which is essential to meet the user’s particular preferences. This article proposes a novel method for informed sampling and recommending cycling routes leveraging crowd-sourced trajectories with weighted-latent Dirichlet allocation (WLDA). Precisely, spatial context mapping, incorporating a weighting mechanism into LDA, latent topics mining, and cycling route recommendation based on informed sampling are introduced. We collected 1,016 cycling trajectories around Cologne, Germany, for experimental analysis. The experimental results show that the three latent topics within the trajectories, leisure, city, and green tours, are clearly presented in the line density analysis. The insightful recommendation for unfamiliar cyclists could also be actively sampled upon the WLDA model. These findings suggest that our approach could shift the route recommendation paradigm from GIS analysis to a semantic mining perspective, yielding highly interpretable results and offering novel research avenues for applying machine learning in route planning.

School bikeability – what is it, and why is it important? An overview of key indicators and measurement

ABSTRACT Despite the theoretical recognition of children’s specific needs regarding road safety, there remains a lack of literature focusing on children’s bikeability or bikeability to school. This is rather concerning as many developed countries have witnessed a decline in active travel to school over the past few decades, despite the existence of well-recognized positive benefits of cycling for children. Recognising the significance of school travel, this study addresses this gap. Through an overview of existing literature, it discusses the importance of school bikeability and sheds light on its specific differences from general accessibility and bikeability, and identifies a set of indicators for measuring it. These indicators, categorised into four domains – Cycling Infrastructure, Connectivity and urbanisation, Safety, and Surrounding environment, can be further utilised to assess school bikeability in any given area. The results of such an assessment can be effectively used to guide investments and policies aimed at establishing safe and secure cycling routes to and from schools.

How destination attributes affect mountain bikers’ behavioral intention: The mediating roles of enduring involvement and place attachment

This research investigated the effects of destination attributes, enduring involvement, place attachment, and satisfaction on mountain bikers’ behavioral intentions by incorporating the Mehrabian-Russell model. A survey approach was employed to test this model. Data was collected from 682 mountain bikers in the Taiwan Bike Association and Taiwan Cyclist Federation from March 2022 to July 2022. This was analyzed using structural equation modeling. Our results indicate that the destination attributes of tourism attraction and accessibility and amenities and complementary services affect enduring involvement both positively and negatively. While tourism attraction and accessibility positively affect place attachment and satisfaction, amenities and complementary services positively affect place attachment but not satisfaction. Moreover, enduring involvement, place attachment, and satisfaction positively affect behavioral intentions. Enduring involvement, place attachment, and satisfaction had mediating effects on the relationship between tourism attraction and accessibility and behavioral intentions. Enduring involvement also played a mediating role in the relationship between amenities and complementary services and behavioral intentions. We discuss both the theoretical and managerial implications of these findings. Management implicationsThe findings of the current study have the following management implications.•Excellent natural resources and accessibility are essential for positive assessments of cycling routes.•Tourism attraction and accessibility is a strong predictor of enduring involvement, place attachment, and satisfaction.•Professional trail building and ongoing maintenance can mitigate adverse environmental impacts and improve the mountain biking experience.•An oversupply of amenities and services can diminish mountain bikers' sense of accomplishment and the pleasure and relaxation of the activity.

Demographic characteristics of those who cycle commute and the effect access to on- and off-road cycle paths has on cycle commute uptake.

ObjectivesIncreasing cycle commute uptake could be an important approach to improving worker health and reducing carbon emissions, congestion and air pollution. In order to increase cycle commute uptake, we must understand the characteristics of those who already cycle to work and the aspects of physical infrastructure that could promote cycling. MethodsIn this work, we use administrative data pertaining to those in employment aged 16-74 years living and working in Glasgow and Edinburgh, Scotland on the night of the 2011 population census. We calculate distances to the nearest cycle path for each individual from cycle route data from around the time of the census that were made computer readable. We looked at the characteristics of those who cycled to work and how proximity to nearest cycle path differed between groups along with how distance from place of residence and place of work to nearest cycle path influenced cycle commute uptake. ResultsWe show how the propensity to cycle commute differs across population characteristics such as sex, age and the National Statistics Socio-economic classification and how the interaction of these factors affects propensity to cycle commute. We also show the ways in which living and working closer to on- and off-road cycle paths increases the likelihood of cycle commuting. DiscussionThe results of this study can be used to inform the most promising groups to aim cycling interventions at thereby improving health and environmental outcomes.

Built environment and childhood obesity.

Childhood obesity, an escalating global health challenge, is intricately linked to the built environment in which children live, learn, and play. This review and perspective examined the multifaceted relationship between the built environment and childhood obesity, offering insights into potential interventions for prevention. Factors such as urbanization, access to unhealthy food options, sedentary behaviors, and socioeconomic disparities are critical contributors to this complex epidemic. Built environment encompasses the human-modified spaces such as homes, schools, workplaces, and urban areas. These settings can influence children's physical activity levels, dietary habits, and overall health. The built environment can be modified to prevent childhood obesity by enhancing active transportation through the development of safe walking and cycling routes, creating accessible and inviting green spaces and play areas, and promoting healthy food environments by regulating fast-food outlet density. School design is another area for intervention, with a focus on integrating outdoor spaces and facilities that promote physical activity and healthy eating. Community engagement and education in reinforcing healthy behaviors is necessary, alongside the potential of technology and innovation in encouraging physical activity among children. Policy and legislative support are crucial for sustaining these efforts. In conclusion, addressing the built environment in the fight against childhood obesity requires the need for a comprehensive, multipronged approach that leverages the built environment as a tool for promoting healthier lifestyles among children, ultimately paving the way for a healthier, more active future generation.

City-wide cycling network extension and bicycle ridership in São Paulo: A causal analysis

Over the past 15 years, São Paulo, a megacity in Southeastern Brazil, has tackled its enduring mobility challenges by constructing over 500 km of bike routes and supporting various cycling initiatives, including recreational cycling programs, mobility strategies and bikeshare. Despite the generally positive impacts of these initiatives, the absence of robust causal evidence on their benefits can pose serious challenges for future investments in light of the existing social dynamic favoring the use of automobiles. Driven by the need to reduce motorized transport in Brazilian cities, we investigate the causal effects of bicycle routes on ridership between 2007 and 2017, focusing on travellers highly exposed to bike routes developed between 2008 and 2015. Using Difference-in-Differences models alongside Household Travel Surveys conducted before and after the interventions, we observed a modest but positive increase in cycling mode choice probability, ranging from 0.60 % to 1.37 %, among the highly exposed treatment groups. Our findings provide policymakers with valuable insights to support future cycling infrastructure planning and investment, demonstrating their potential net benefits even in car-dependent urban areas. By integrating these results into existing economic appraisal tools, policymakers can further assess additional benefits related to physical activity, health, and emissions reduction.

Urban air quality comparison on bike and driving routes: a case study for UK

Air quality in cities is very important in both tackling climate change and promoting healthy sustainable urban living. Understanding the air quality around cities has been a challenge faced by local authorities around the world. With the new net zero targets in place, government and charitable organisations across the UK have been trying hard to both monitor and control air pollutants to influence citizen behavior towards environmentally friendly living. This study looks at urban air quality in two UK cities with the idea of understanding air quality and its relation to the mode of transport, health and well-being. This case study compares the urban air quality as Particulate Matter (PM 10 and PM 2.5) and gaseous pollutants (NO 2) on the bike and motor driving routes in Cambridge and Colchester. The study designed experiments and data collection campaigns to understand the factors leading to air quality fluctuations in urban traffic routes. The resulting measurements show that NO 2 concentrations are higher in motor driving routes and in certain locations on the bike routes that are part of (or very close to) the motor route. The PM concentrations are generally higher near parks and open greenspaces but can be argued to be within the recommended limits. Finally, this paper proposes steps to improve the urban infrastructure to tackle emissions and spread awareness among the citizens.