scholarly journals An Analysis of Remote Sensing Data to Evaluate the Problem of Atmospheric Aerosol Pollution in Africa

2021 ◽  
Author(s):  
Gerard Rushingabigwi ◽  
Celestin Twizere ◽  
Philibert Nsengiyumva ◽  
Jean De Dieu Ntawangaheza ◽  
Liguo Sun
Keyword(s):  
Air Pollutants ◽  
Geographical Information Systems ◽  
Region Of Interest ◽  
Software Tool ◽  
Mitigation Strategies ◽  
Fine Particulates ◽  
Robotic Networks ◽  
Atmospheric Air ◽  
Spatio Temporal ◽  
Moderate Resolution Imaging Spectroradiometer

The particulate matter (PM) directly endangers the human health. Remotely sensed tiny atmospheric particles, aerosols, are presented in this research as atmospheric air pollutants. Globally overviewed for the first instances, and then a focus put on Africa and Asia, the selected aerosols are fine particulates (PM2.5), black carbon (BC), and Sulfate (SO4). According to the existing literature, the motivation to research on air pollutants came from the fact that the polluted air globally kills many people, by attacking cardiovascular system. The online accessible remote sensing’s data has been mostly collected from the second version of modern era retrospective analysis for research and applications (MERRA-2), a model selected for its update as well as the fact that its data are directly assimilated from the most renown remote sensors: Moderate resolution Imaging Spectroradiometer (MODIS) and the advanced very high-resolution radiometer (AVHRR). MERRA-2 also compiles data from different aerosol robotic networks (AERONETs). With a vast region of interest, and considering the big temporal resolution, reduced spatio-temporal resolutions facilitated the focused research. Goddard interactive online visualization and analysis infrastructure (GIOVANNI) bridged our research objectives with the data; Geographical Information Systems (Arc GIS) is a main software tool. Map-based as well as time series results for PM2.5 and other atmospheric air pollutants are presented; health dangers associated with the dust from erstwhile research highlighted. Finding that the annually-averaged mass concentration of the dust’s PM2.5 is significantly greater than the mean recommended concentration, 25 μg/m3, in all the seasons of the center of the research region of interest (Africa), this research recommends further research on dust aerosols mitigation strategies, during the seasons of heaviest air pollutants in particular.

scholarly journals Comparison of spatio-temporal transmission characteristics of COVID-19 and its mitigation strategies in China and the US

2020 ◽  
Vol 30 (12) ◽  
pp. 1963-1984
Author(s):  
Zhiming Feng ◽  
Chiwei Xiao ◽  
Peng Li ◽  
Zhen You ◽  
Xu Yin ◽  
...  
Keyword(s):  
Mitigation Strategies ◽  
Transmission Characteristics ◽  
The Us ◽  
Spatio Temporal

Vertical profiling of atmospheric air pollutants in rural India: A case study on particulate matter (PM10/PM2.5/PM1), carbon dioxide, and formaldehyde

Measurement ◽  
2021 ◽  
Vol 185 ◽  
pp. 110061
Author(s):  
Sneha Gautam ◽  
Cyril Sammuel ◽  
Aniket Bhardwaj ◽  
Zahra Shams Esfandabadi ◽  
M. Santosh ◽  
...  
Keyword(s):  
Carbon Dioxide ◽  
Particulate Matter ◽  
Air Pollutants ◽  
Rural India ◽  
Atmospheric Air ◽  
Vertical Profiling

How low-cost air pollution sensors could make homes smarter?

2021 ◽  
Author(s):  
Hamid Omidvarborna ◽  
Prashant Kumar
Keyword(s):  
Air Pollution ◽  
Indoor Air ◽  
Air Pollutants ◽  
Indoor Air Pollution ◽  
Prediction Models ◽  
Disease Risk ◽  
Low Cost ◽  
Mortality And Morbidity ◽  
Spatio Temporal ◽  
Indoor Air Pollutants

<p>The majority of people spend most of their time indoors, where they are exposed to indoor air pollutants. Indoor air pollution is ranked among the top ten largest global burden of a disease risk factor as well as the top five environmental public health risks, which could result in mortality and morbidity worldwide. The spent time in indoor environments has been recently elevated due to coronavirus disease 2019 (COVID-19) outbreak when the public are advised to stay in their place for longer hours per day to protect lives. This opens an opportunity to low-cost air pollution sensors in the real-time Spatio-temporal mapping of IAQ and monitors their concentration/exposure levels indoors. However, the optimum selection of low-cost sensors (LCSs) for certain indoor application is challenging due to diversity in the air pollution sensing device technologies. Making affordable sensing units composed of individual sensors capable of measuring indoor environmental parameters and pollutant concentration for indoor applications requires a diverse scientific and engineering knowledge, which is not yet established. The study aims to gather all these methodologies and technologies in one place, where it allows transforming typical homes into smart homes by specifically focusing on IAQ. This approach addresses the following questions: 1) which and what sensors are suitable for indoor networked application by considering their specifications and limitation, 2) where to deploy sensors to better capture Spatio-temporal mapping of indoor air pollutants, while the operation is optimum, 3) how to treat the collected data from the sensor network and make them ready for the subsequent analysis and 4) how to feed data to prediction models, and which models are best suited for indoors.</p>

scholarly journals A Spatio-Temporal Investigation of the Growth Rate of COVID-19 Incidents in Ohio, USA, Early in the Pandemic

2021 ◽  
Vol 121 (2) ◽  
pp. 33-47
Author(s):  
Alessandro M. Selvitella ◽  
Liam Carolan ◽  
Justin Smethers ◽  
Christopher Hernandez ◽  
Kathleen L. Foster
Keyword(s):  
Growth Rate ◽  
Transmission Rate ◽  
Time Lag ◽  
Early Period ◽  
Mitigation Strategies ◽  
Initial Growth ◽  
School Closures ◽  
Policy Makers ◽  
Susceptible Population ◽  
Spatio Temporal

Understanding the initial growth rate of an epidemic is important for epidemiologists and policy makers as it can impact their mitigation strategies such as school closures, quarantines, or social distancing. Because the transmission rate depends on the contact rate of the susceptible population with infected individuals, similar growth rates might be experienced in nearby geographical areas. This research determined the growth rate of cases and deaths associated with COVID-19 in the early period of the 2020 pandemic in Ohio, United States. The evolution of cases and deaths was modeled through a Besag-York-Molliè model with linear- and power-type deterministic time dependence. The analysis showed that the growth rate of the time component of the model was subexponential in both cases and deaths once the time-lag across counties of the appearance of the first COVID-19 case was considered. Moreover, deaths in the northeast counties in Ohio were strongly related to the deaths in nearby counties.

scholarly journals Mobile monitoring of urban air quality at high spatial resolution by low-cost sensors: Impacts of COVID-19 pandemic lockdown

2020 ◽  
Author(s):  
Shibao Wang ◽  
Yun Ma ◽  
Zhongrui Wang ◽  
Lei Wang ◽  
Xuguang Chi ◽  
...  
Keyword(s):  
Air Quality ◽  
Air Pollutants ◽  
Low Cost ◽  
Air Pollutant ◽  
Mitigation Strategies ◽  
Traffic Emissions ◽  
Urban Air ◽  
Industrial Emissions ◽  
Gis Technology ◽  
Mobile Monitoring

Abstract. The development of low-cost sensors and novel calibration algorithms provides new hints to complement conventional ground-based observation sites to evaluate the spatial and temporal distribution of pollutants on hyper-local scales (tens of meters). Here we use sensors deployed on a taxi fleet to explore the air quality in the road network of Nanjing over the course of a year (Oct. 2019–Sep. 2020). Based on GIS technology, we develop a grid analysis method to obtain 50 m resolution maps of major air pollutants (CO, NO2, and O3). Through hotspots identification analysis, we find three main sources of air pollutants including traffic, industrial emissions, and cooking fumes. We find that CO and NO2 concentrations show a pattern: highways > arterial roads > secondary roads > branch roads > residential streets, reflecting traffic volume. While the O3 concentrations in these five road types are in opposite order due to the titration effect of NOx. Combined the mobile measurements and the stationary station data, we diagnose that the contribution of traffic-related emissions to CO and NO2 are 42.6 % and 26.3 %, respectively. Compared to the pre-COVID period, the concentrations of CO and NO2 during COVID-lockdown period decreased for 44.9 % and 47.1 %, respectively, and the contribution of traffic-related emissions to them both decreased by more than 50 %. With the end of the COVID-lockdown period, traffic emissions and air pollutant concentrations rebounded substantially, indicating that traffic emissions have a crucial impact on the variation of air pollutants levels in urban regions. This research demonstrates the sense power of mobile monitoring for urban air pollution, which provides detailed information for source attribution, accurate traceability, and potential mitigation strategies at urban micro-scale.

scholarly journals THE IMPROVEMENT OF APPROACHES TO THE ASSESSMENT OF EFFECTS OF THE ANTHROPOGENIC AIR POLLUTION ON THE POPULATION IN ORDER TO MANAGEMENT THE RISK FOR HEALTH

2019 ◽  
Vol 98 (1) ◽  
pp. 82-86 ◽  
Author(s):  
Aleksandr O. Karelin ◽  
A. Yu. Lomtev ◽  
M. V. Volkodaeva ◽  
G. B. Yeremin
Keyword(s):  
Risk Assessment ◽  
Air Pollution ◽  
Evidence Based Medicine ◽  
Air Pollutants ◽  
Health Assessment ◽  
Developed Countries ◽  
Epidemiological Methods ◽  
Evidence Based ◽  
Atmospheric Air ◽  
Based Medicine

The air pollution has got a great risk to the health of the population. In the risk assessment, objective and subjective uncertainties have appeared. The aim of the study to analyze the uncertainties arising in the assessment of health adverse effects of air pollution and possible ways to decrease them. Methods of the scientific hypothetical deductive cognition, general logical methods, and approaches of researches: analysis, synthesis, abstracting, generalization, induction. In this paper, we analyzed the uncertainties arising in the risk assessment for the health of population caused by air pollution and proposed measures to improve the approaches to assessment and management of the risk. The analysis revealed the main causes of the uncertainties. In the field of the atmospheric air monitoring, they are lack of modern equipment and officially approved methods for measurement, the absence of criteria and recommendation for choosing of controlled air pollutants. For the health assessment, it is advisable to use epidemiological methods and methodology of risk analysis taking into account the uncertainties of each approach. Usage of the geographic information systems let increase the informativity of data and efficiency of analysis. Accurate quantification of the risk for the health of population caused by air pollution is a difficult to challenge. It is necessary to take into account the experience of developed countries in the development of domestic criteria for the selection of substances for the control of atmospheric air quality. It is advisable to combine the analysis of data on the actual concentrations of pollutants obtained at stationary and mobile observation posts, and integrated calculations of air pollution. It is necessary to use basic concepts of evidence-based medicine to identify the real impact of air pollutants on public health and reduce uncertainties. Conclusion. In the assessment of risk for health caused by air pollution a lot of objective and subjective uncertainties appear. Based on the principles of evidence-based medicine, they should be comprehensively analyzed and minimized using modern methodological approaches, taking into account their capabilities and limitations.

Influence of emission inventory resolution on the modeled spatio-temporal distribution of air pollutants in Buenos Aires, Argentina, using WRF-Chem

2021 ◽  
pp. 118839
Author(s):  
Ana I. López-Noreña ◽  
Lucas Berná ◽  
Maria Florencia Tames ◽  
Emmanuel N. Millán ◽  
S. Enrique Puliafito ◽  
...  
Keyword(s):  
Air Pollutants ◽  
Emission Inventory ◽  
Buenos Aires ◽  
Temporal Distribution ◽  
Spatio Temporal
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