Success Measures for Transforming Into Car-Free Cities

Author(s):  
Rahma M. Doheim ◽  
Alshimaa Aboelmakarem Farag ◽  
Samaa Badawi

Private cars contribute heavily to air pollution and significantly lower air quality in cities. The number of deaths because of pollution and car accidents is increasing on a global level; therefore, achieving sustainable mobility in urban areas is essential. Hence, the transformation into a car-free model is not a marginal issue but rather a crucial need that should be a global trend. The biggest challenge in this transforming process is to minimize the dependency on private cars. This chapter reviews thoroughly some global practices of inspiring models of transforming into car-free cities around the world. This review aims to identify the success measures for the transformation of a car-free city through investigating the challenges that affected the adoption of the transformation process. This would potentially guide governments and policymakers to select the approach that copes effectively with the cultural, social, geographical, and economic characteristics of their countries.

2017 ◽  
Vol 7 (15) ◽  
pp. 8-17 ◽  
Author(s):  
Modise Wiston

Background. Air pollution is an important issue in developed and industrialized countries. The most common sources of air pollution are anthropogenic activities such as construction dust, vehicular emissions and mining. For low- and middle-income countries, biomass burning and indoor heating are the leading sources of air pollution. As more of the world undergoes development and human populations increase, industrialization is also increasing, along with the potential for air pollution. Objectives. This article reviews the status of air pollution to raise awareness of air quality and human health in Botswana. Discussion. Since independence, Botswana has experienced one of the highest economic development growth rates in the world. These changes have occurred as a result of economic growth and resource utilization associated with increased industrialization. However, there is growing worldwide concern about the effect and impact of pollution due to industrial growth. Botswana is ranked amongst the most polluted countries with serious air pollution, despite a population of just over 2 million. Conclusions. Rapid development and increased urbanization have had a major environmental impact around the world. This increased growth has the potential to lead to air quality degradation. Significant health threats are posed by industrial and vehicular emissions, especially in urban and peri-urban areas where the population is most concentrated. It is important that the linkage between air pollution and health effects is fully examined across all scales of life, especially in developing countries. In addition, programs should be devised to educate the public about the pollution impacts on health. Competing Interests: The authors declare no financial competing interests.


Encyclopedia ◽  
2021 ◽  
Vol 1 (3) ◽  
pp. 519-526
Author(s):  
Gabriele Donzelli ◽  
Lorenzo Cioni ◽  
Mariagrazia Cancellieri ◽  
Agustin Llopis-Morales ◽  
María Morales-Suárez-Varela

Air pollution exposure is one of the greatest risks to health worldwide. It is estimated to be responsible for about 4.2 million deaths around the world every year owing to many serious diseases such as heart disease, stroke, acute and chronic respiratory diseases, and lung cancer. The WHO guideline limits are exceeded in several areas around the world, and it is estimated that about 90% of the world’s population is exposed to high air pollution levels, especially in low- and middle-income countries. The COVID-19 pandemic has forced governments to implement severe mobility restriction measures to limit the spread of the virus. This represented a unique opportunity to study the impact of mobility on urban air quality. Several studies which have investigated the relations between the quality of the air and such containment measures have shown the significant reduction of the main pollutants in the urban environment so to encourage the adoption of new approaches for the improvement of the quality of air in the cities. The aims of this entry are both a brief analysis and a discussion of the results presented in several papers to understand the relationships between COVID-19 containment measures and air quality in urban areas.


2017 ◽  
Vol 68 (4) ◽  
pp. 841-846
Author(s):  
Hai-Ying Liu ◽  
Daniel Dunea ◽  
Mihaela Oprea ◽  
Tom Savu ◽  
Stefania Iordache

This paper presents the approach used to develop the information chain required to reach the objectives of the EEA Grants� RokidAIR project in two Romanian cities i.e., Targoviste and Ploiesti. It describes the PM2.5 monitoring infrastructure and architecture to the web-based GIS platform, the early warning system and the decision support system, and finally, the linking of air pollution to health effects in children. In addition, it shows the analysis performance of the designed system to process the collected time series from various data sources using the benzene concentrations monitored in Ploiesti. Moreover, this paper suggests that biomarkers, mobile technologies, and Citizens� Observatories are potential perspectives to improve data coverage by the provision of near-real-time air quality maps, and provide personal exposure and health assessment results, enabling the citizens� engagement and behavioural change. This paper also addresses new fields in nature-based solutions to improve air quality, and studies on air pollution and its mental health effects in the urban areas of Romania.


Land ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 236
Author(s):  
Ha Na You ◽  
Myeong Ja Kwak ◽  
Sun Mi Je ◽  
Jong Kyu Lee ◽  
Yea Ji Lim ◽  
...  

Environmental pollution is an important issue in metropolitan areas, and roadside trees are directly affected by various sources of pollution to which they exhibit numerous responses. The aim of the present study was to identify morpho-physio-biochemical attributes of maidenhair tree (Ginkgo biloba L.) and American sycamore (Platanus occidentalis L.) growing under two different air quality conditions (roadside with high air pollution, RH and roadside with low air pollution, RL) and to assess the possibility of using their physiological and biochemical parameters as biomonitoring tools in urban areas. The results showed that the photosynthetic rate, photosynthetic nitrogen-use efficiencies, and photochromic contents were generally low in RH in both G. biloba and P. occidentalis. However, water-use efficiency and leaf temperature showed high values in RH trees. Among biochemical parameters, in G. biloba, the lipid peroxide content was higher in RH than in RL trees, but in P. occidentalis, this content was lower in RH than in RL trees. In both species, physiological activities were low in trees planted in areas with high levels of air pollution, whereas their biochemical and morphological variables showed different responses to air pollution. Thus, we concluded that it is possible to determine species-specific physiological variables affected by regional differences of air pollution in urban areas, and these findings may be helpful for monitoring air quality and environmental health using trees.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ram Kumar Singh ◽  
Martin Drews ◽  
Manuel De la Sen ◽  
Prashant Kumar Srivastava ◽  
Bambang H. Trisasongko ◽  
...  

AbstractThe new COVID-19 coronavirus disease has emerged as a global threat and not just to human health but also the global economy. Due to the pandemic, most countries affected have therefore imposed periods of full or partial lockdowns to restrict community transmission. This has had the welcome but unexpected side effect that existing levels of atmospheric pollutants, particularly in cities, have temporarily declined. As found by several authors, air quality can inherently exacerbate the risks linked to respiratory diseases, including COVID-19. In this study, we explore patterns of air pollution for ten of the most affected countries in the world, in the context of the 2020 development of the COVID-19 pandemic. We find that the concentrations of some of the principal atmospheric pollutants were temporarily reduced during the extensive lockdowns in the spring. Secondly, we show that the seasonality of the atmospheric pollutants is not significantly affected by these temporary changes, indicating that observed variations in COVID-19 conditions are likely to be linked to air quality. On this background, we confirm that air pollution may be a good predictor for the local and national severity of COVID-19 infections.


Atmosphere ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 431
Author(s):  
Ayako Yoshino ◽  
Akinori Takami ◽  
Keiichiro Hara ◽  
Chiharu Nishita-Hara ◽  
Masahiko Hayashi ◽  
...  

Transboundary air pollution (TAP) and local air pollution (LAP) influence the air quality of urban areas. Fukuoka, located on the west side of Japan and affected by TAP from the Asian continent, is a unique example for understanding the contribution of LAP and TAP. Gaseous species and particulate matter (PM) were measured for approximately three weeks in Fukuoka in the winter of 2018. We classified two distinctive periods, LAP and TAP, based on wind speed. The classification was supported by variations in the concentration of gaseous species and by backward trajectories. Most air pollutants, including NOx and PM, were high in the LAP period and low in the TAP period. However, ozone was the exception. Therefore, our findings suggest that reducing local emissions is necessary. Ozone was higher in the TAP period, and the variation in ozone concentration was relatively small, indicating that ozone was produced outside of the city and transported to Fukuoka. Thus, air pollutants must also be reduced at a regional scale, including in China.


2021 ◽  
Author(s):  
Daniel Westervelt ◽  
Celeste McFarlane ◽  
Faye McNeill ◽  
R (Subu) Subramanian ◽  
Mike Giordano ◽  
...  

<p>There is a severe lack of air pollution data around the world. This includes large portions of low- and middle-income countries (LMICs), as well as rural areas of wealthier nations as monitors tend to be located in large metropolises. Low cost sensors (LCS) for measuring air pollution and identifying sources offer a possible path forward to remedy the lack of data, though significant knowledge gaps and caveats remain regarding the accurate application and interpretation of such devices.</p><p>The Clean Air Monitoring and Solutions Network (CAMS-Net) establishes an international network of networks that unites scientists, decision-makers, city administrators, citizen groups, the private sector, and other local stakeholders in co-developing new methods and best practices for real-time air quality data collection, data sharing, and solutions for air quality improvements. CAMS-Net brings together at least 32 multidisciplinary member networks from North America, Europe, Africa, and India. The project establishes a mechanism for international collaboration, builds technical capacity, shares knowledge, and trains the next generation of air quality practitioners and advocates, including domestic and international graduate students and postdoctoral researchers. </p><p>Here we present some preliminary research accelerated through the CAMS-Net project. Specifically, we present LCS calibration methodology for several co-locations in LMICs (Accra, Ghana; Kampala, Uganda; Nairobi, Kenya; Addis Ababa, Ethiopia; and Kolkata, India), in which reference BAM-1020 PM2.5 monitors were placed side-by-side with LCS. We demonstrate that both simple multiple linear regression calibration methods for bias-correcting LCS and more complex machine learning methods can reduce bias in LCS to close to zero, while increasing correlation. For example, in Kampala, Raw PurpleAir PM2.5 data are strongly correlated with the BAM-1020 PM2.5 (r<sup>2</sup> = 0.88), but have a mean bias of approximately 12 μg m<sup>-3</sup>. Two calibration models, multiple linear regression and a random forest approach, decrease mean bias from 12 μg m<sup>-3 </sup>to -1.84 µg m<sup>-3</sup> or less and improve the the r<sup>2</sup> from 0.88 to 0.96. We find similar performance in several other regions of the world. Location-specific calibration of low-cost sensors is necessary in order to obtain useful data, since sensor performance is closely tied to environmental conditions such as relative humidity. This work is a first step towards developing a database of region-specific correction factors for low cost sensors, which are exploding in popularity globally and have the potential to close the air pollution data gap especially in resource-limited countries. </p><p> </p><p> </p>


2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
J Gajic ◽  
D Dimovski ◽  
B Vukajlovic ◽  
M Jevtic

Abstract Issue/problem Increasing attention is being paid to air pollution as one of the greatest threats to public and urban health. The WHO’s Urban Health Initiative points out the importance of collecting data and mapping the present state of air quality in urban areas. For citizens, such engagement is enabled by the appearance of personal air quality measurement devices that use crowd-sourcing to make measurement results publicly accessible in real time. Description of the problem As a way of contributing to air pollution monitoring in their town, three PhD Public health students conducted over 40 measurements between the start of June and end of August 2018 on various locations in the city of Novi Sad, Serbia. Measurements were performed using AirBeam personal air quality monitoring devices and their results presented as μg/m3 of Particulate Matter 2.5 (PM2.5) and automatically uploaded to the internet using the Air-casting app. Results Measurements conducted in public transportation vehicles returned the rather high average value of 40 μg/m3, where coffee shops and restaurants scored an even higher value of 48,67 μg/m3. The lowest average air pollution levels were registered near the Danube river bank (5.67) and in the parks (6), while the sites near crossroads or in the street showed average air pollution of 8.33 μg/m3. Residential areas where smoking is present during the day reported 2.5 times higher PM2.5 values than those without smokers (33.8 and 12.78 μg/m3). Lessons Bearing in mind that the air quality is considered as a serious health risk in urban areas, results of this pilot investigation suggest potential health risk for citizens living in urban areas. The negative effects of combustion and smoking on air quality are strongly highlighted, as well as the positive impact of green areas and parks near residential areas. Key messages Air pollution exposure as a serious health risk in urban areas. Crowdsourcing as a way of air quality monitoring has great potential for contributing to public health.


Author(s):  
Luisa T. Molina ◽  
Tong Zhu ◽  
Wei Wan ◽  
Bhola R. Gurjar

Megacities (metropolitan areas with populations over 10 million) and large urban centers present a major challenge for the global environment. Transportation, industrial activities, and energy demand have increased in megacities due to population growth and unsustainable urban development, leading to increasing levels of air pollution that subject the residents to the health risks associated with harmful pollutants, and impose heavy economic and social costs. Although much progress has been made in reducing air pollution in developed and some developing world megacities, there are many remaining challenges in achieving cleaner and breathable air for their residents. As centers of economic growth, scientific advancement, and technology innovation, however, these urban settings also offer unique opportunities to capitalize on the multiple benefits that can be achieved by optimizing energy use, reducing atmospheric pollution, minimizing greenhouse gas emissions, and bringing many social benefits. Realizing such benefits will, however, require strong and wide-ranging institutional cooperation, public awareness, and multi-stakeholder involvement. This is especially critical as the phenomenon of urbanization continues in virtually all countries of the world, and more megacities will be added to the world, with the majority of them located in developing countries. The air quality and emission mitigation strategies of eight megacities—Mexico City, Beijing, Shanghai, Shenzhen, Chengdu, Delhi, Kolkata, and Mumbai—are presented as examples of the environmental challenges experienced by large urban centers. While these megacities share common problems of air pollution due to the rapid growth in population and urbanization, each city has its own unique circumstances—geographical location, meteorology, sources of emissions, human and financial resources, and institutional capacity—to address them. Nevertheless, the need for an integrated multidisciplinary approach to air quality management is the same. Mexico City’s air pollution problem was considered among the worst in the world in the 1980s due to rapid population growth, uncontrolled urban development, and energy consumption. After three decades of implementing successive comprehensive air quality management programs that combined regulatory actions with technological change and were based on scientific, technical, social, and political considerations, Mexico City has made significant progress in improving its air quality; however, ozone and particulate matter are still at levels above the respective Mexican air quality standards. Beijing, Shanghai, Shenzhen, and Chengdu are microcosms of megacities in the People’s Republic of China, with rapid socioeconomic development, expanding urbanization, and swift industrialization since the era of reform and opening up began in the late 1970s, leading to severe air pollution. In 2013, the Chinese government issued the Action Plan for Air Pollution Prevention and Control. Through scientific research and regional coordinated air pollution control actions implemented by the Chinese government authority, the concentration of atmospheric pollutants in several major cities has decreased substantially. About 20% of total megacities’ populations in the world reside in Indian megacities; the population is projected to increase, with Delhi becoming the largest megacity by 2030. The increased demands of energy and transportation, as well as other sources such as biomass burning, have led to severe air pollution. The air quality trends for some pollutants have reduced as a result of emissions control measures implemented by the Indian government; however, the level of particulate matter is still higher than the national standards and is one of the leading causes of premature deaths. The examples of the eight cities illustrate that although most air pollution problems are caused by local or regional sources of emissions, air pollutants are transported from state to state and across international borders; therefore, international coordination and collaboration should be strongly encouraged. Based on the available technical-scientific information, the regulations, standards, and policies for the reduction of polluting emissions can be formulated and implemented, which combined with adequate surveillance, enforcement, and compliance, would lead to progressive air quality improvement that benefits the population and the environment. The experience and the lessons learned from the eight megacities can be valuable for other large urban centers confronting similar air pollution challenges.


Author(s):  
Mo ◽  
Zhang ◽  
Li ◽  
Qu

The problem of air pollution is a persistent issue for mankind and becoming increasingly serious in recent years, which has drawn worldwide attention. Establishing a scientific and effective air quality early-warning system is really significant and important. Regretfully, previous research didn’t thoroughly explore not only air pollutant prediction but also air quality evaluation, and relevant research work is still scarce, especially in China. Therefore, a novel air quality early-warning system composed of prediction and evaluation was developed in this study. Firstly, the advanced data preprocessing technology Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (ICEEMDAN) combined with the powerful swarm intelligence algorithm Whale Optimization Algorithm (WOA) and the efficient artificial neural network Extreme Learning Machine (ELM) formed the prediction model. Then the predictive results were further analyzed by the method of fuzzy comprehensive evaluation, which offered intuitive air quality information and corresponding measures. The proposed system was tested in the Jing-Jin-Ji region of China, a representative research area in the world, and the daily concentration data of six main air pollutants in Beijing, Tianjin, and Shijiazhuang for two years were used to validate the accuracy and efficiency. The results show that the prediction model is superior to other benchmark models in pollutant concentration prediction and the evaluation model is satisfactory in air quality level reporting compared with the actual status. Therefore, the proposed system is believed to play an important role in air pollution control and smart city construction all over the world in the future.


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