scholarly journals Highlighting the compound risk of COVID-19 and environmental pollutants using geospatial technology

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.

Author(s):  
Harold I Zeliger

Air pollution impacts 90% of the world's population and is the number one cause of premature deaths worldwide, etiamted at 8-10 million pre year. Breathing polluted air is associated with the accelerated onset of numerous illnesses, including respiratory diseases, cardiovascular diseases, several cancers and Alzheimer's disease. Fice major pollutants are typically monitored in cities around the world for air quality. These include ozone, particulate matter, dulfur dioxide, nitrogen dioxide and carbon monoxide. The Air Quality Toxicity Index (AQTI), that is first reported here, provides a quantitative indicator with which to monitor air quality, make air quality comparisons of different locations and compare air quality of the same locations as a function of time.


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>


2004 ◽  
Vol 63 (4) ◽  
pp. 579-585 ◽  
Author(s):  
Frank J. Kelly

Air is one of our most important natural resources; however, it is also in the front line for receiving environmental pollution. Air quality decreased markedly following the industrial revolution, but it was not until the great London Smog in 1952 that air quality made it onto the political agenda. The introduction of the Clean Air Act in 1956 led to dramatic decreases in black smoke and SO2 concentrations over the next two decades, as domestic and industrial coal-burning activities ceased. However, as these improvements progressed, a new threat to public health was being released into the air in ever-increasing quantities. Rapid motorisation of society from the 1960s onwards has led to the increased release of atmospheric pollutants such as tiny particles (particulate matter of &10 μm in aerodynamic diameter) and oxides of N, and the generation of the secondary pollutant O3. These primary and secondary traffic-related pollutants have all proved to be major risks factors to public health. Recently, oxidative stress has been identified as a unifying feature underlying the toxic actions of these pollutants. Fortunately, the surface of the lung is covered with a thin layer of fluid containing a range of antioxidants that appear to provide the first line of defence against oxidant pollutants. As diet is the only source of antioxidant micronutrients, a plausible link now exists between the sensitivity to air pollution and the quality of the food eaten. However, many questions remain unanswered in relation to inter-individual sensitivity to ambient air pollution, and extent to which this sensitivity is modified by airway antioxidant defences.


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.


2020 ◽  
Vol 19 (3) ◽  
pp. 288-300
Author(s):  
Ahmet Cosgun ◽  

Individuals have to work in collective living spaces which might be indoor or outdoor areas. In indoor works, people spend approximately 90% of their time in a closed space. There are many parameters affecting indoor air quality. Among these, for indoor and outdoor, important parameters can be listed as carbon monoxide (CO), carbon dioxide (CO2), sulfur dioxide (SO₂), particles, nitrogen oxides (NOx), various microorganisms, harmful allergens, and powders. Some health problems might emerge in people who stay in indoor environments for a long time. For instance, newborns and infants are more likely to stay indoors. It is the primary reason for occurring many acute and chronic diseases at an early age, as babies and children are more sensitive to environmental pollutants. Recently published studies, which report that appendicitis failures might be fatal and air pollution can increase the rate of these failures, are remarkable. On the other hand, there are many negative effects of polluted indoor air on human health such as attention deficit and excessive daytime sleepiness. Moreover, the negative effects of this kind of indoor air quality on human learning and perception can not be neglected. The researchers focusing on indoor air quality are conducting studies showing that air pollution has an effect on physical activity and neurological interaction in humans. Even though air pollutants in outdoor air content were evaluated with fuzzy logic method in many studies, there are quite few studies using the fuzzy approach for indoor air quality. In this study, through the standard formula developed by the United States Environmental Protection Agency (EPA), calculations were made using fuzzy logic in MATLAB utilizing air quality index. In the study, indoor air quality measurement parameters were evaluated with the “Mamdani” method used in fuzzy logic. In the study, the model suitable for the logic structure created with the fuzzy tool in MATLAB was analyzed with the help of Mamdani method, and the suitability of evaluating the indoor air quality with artificial intelligence was investigated. A set of suggestions has been made evaluating and criticizing the results


2018 ◽  
Vol 3 (2) ◽  
pp. 69
Author(s):  
Rasool Entezar Mahdi ◽  
Mousa Ghelichi Ghojogh ◽  
Hojjat Kargar ◽  
Saeed Minaee Mehr

Introduction: Air pollution induced by human activities is one of major challenges faced by Iran, as well as the world . The AirQ model was used to evaluate the cardiovascular and respiratory diseases attributable to the exposure to suspended particles of less than 10 µm in Urmia city of West Azerbaijan Province, Iran, in 2015. Materials and Methods: This descriptive-analytic study was conducted in Urmia in 2015. The hourly data of the PM10 (particle matter up to 10 µm) pollutant were extracted as the raw material from the Environmental Health Center. The health effects of suspended particles of less than 10 µm were estimated by statistical analysis using the World Health Organization’s AirQ model.Results:  According to the results concentration of PM10 was higher in the cold seasons compared with the warm seasons. The annual average of PM10 concentration was 3.9 times higher than that prescribed as per the standards of clean air in Iran. In addition, the cumulative numbers of cardiovascular and respiratory diseases in the city of Urmia in the median estimate were 287 and 744 cases, respectively. Conclusion: As a consequently, air pollution in the Urmia city has contributed significantly to the rate of hospitalizations and deaths of people in 2015. Therefore, authorities should make appropriate, sustainable, and applicable strategies based on comprehensive research to control the Urmia air pollution crisis.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Alexandre Caseiro ◽  
Erika von Schneidemesser

AbstractExposure to poor air quality is considered a major influence on the occurrence of cardiovascular and respiratory diseases. Air pollution has also been linked to the severity of the effects of epidemics such as COVID-19 caused by the SARS-CoV-2 virus. Epidemiological studies require datasets of the long-term exposure to air pollution. We present the APExpose_DE dataset, a long-term (2010–2019) dataset providing ambient air pollution metrics at yearly time resolution for NO2, NO, O3, PM10 and PM2.5 at the NUTS-3 spatial resolution level for Germany (corresponding to the Landkreis or Kreisfreie Stadt in Germany, 402 in total).


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.


Atmosphere ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 512 ◽  
Author(s):  
Molina ◽  
Velasco ◽  
Retama ◽  
Zavala

More than half of the world’s population now lives in cities as a result of unprecedented urbanization during the second half of the 20th century. The urban population is projected to increase to 68% by 2050, with most of the increase occurring in Asia and Africa. Population growth and increased energy consumption in urban areas lead to high levels of atmospheric pollutants that harm human health, cause regional haze, damage crops, contribute to climate change, and ultimately threaten the society’s sustainability. This article reviews the air quality and compares the policies implemented in the Mexico City Metropolitan Area (MCMA) and Singapore and offers insights into the complexity of managing air pollution to protect public health and the environment. While the differences in the governance, economics, and culture of the two cities greatly influence the decision-making process, both have made much progress in reducing concentrations of harmful pollutants by implementing comprehensive integrated air quality management programs. The experience and the lessons learned from the MCMA and Singapore can be valuable for other urban centers, especially in the fast-growing Asia-Pacific region confronting similar air pollution problems.


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