scholarly journals Assessment of natural and anthropogenic aerosol air pollution in the Middle East using MERRA-2, CAMS data assimilation products,and high-resolution WRF-Chem model simulations

2020 ◽  
Author(s):  
Alexander Ukhov ◽  
Suleiman Mostamandi ◽  
Arlindo da Silva ◽  
Johannes Flemming ◽  
Yasser Alshehri ◽  
...  
Keyword(s):  
Air Pollution ◽  
Data Assimilation ◽  
Oil Recovery ◽  
Dust Emission ◽  
World Health ◽  
So2 Emissions ◽  
Urban Centers ◽  
Anthropogenic Aerosol ◽  
Health Organization ◽  
Monitoring Service

Abstract. Modern-Era Retrospective analysis for Research and Applications v.2 (MERRA-2), Copernicus Atmosphere Monitoring Service Operational Analysis (CAMS-OA) data assimilation products, and a regional Weather Research and Forecasting model (10 km resolution) coupled with Chemistry (WRF-Chem) were used to evaluate natural and anthropogenic aerosol air pollution in the ME during 2015–2016. Satellite and ground-based AOD observations, as well as in-situ Particulate Matter (PM) measurements for 2016, were used for validation. WRF-Chem code was modified to correct the calculation of dust gravitational settling and aerosol optical properties. The dust emission in WRF-Chem is calibrated to fit Aerosol Optical Depth (AOD) and aerosol volume size distributions obtained from Aerosol Robotic Network (AERONET) observations. MERRA-2 was used to construct WRF-Chem initial and boundary conditions both for meteorology and chemical/aerosol species. SO2 emissions in WRF-Chem are based on the novel NASA SO2 emission dataset that reveals unaccounted sources over the ME. Although aerosol fields in WRF-Chem and assimilation products are quite consistent, WRF-Chem, due to its higher spatial resolution and better SO2 emissions, is preferable for analysis of regional air-quality over the ME. The WRF-Chem's PM background concentrations exceed the World Health Organization (WHO) guidelines over the entire ME. The major contributor to PM (~ 75–95 %) is mineral dust. In the ME urban centers and near oil recovery fields, non-dust aerosols (primarily sulfate) contribute up to 26 % into PM2.5. The contribution of sea salt into PM can rich up to 5 %. The contribution of organic matter into PM prevails over black carbon.

scholarly journals Assessment of natural and anthropogenic aerosol air pollution in the Middle East using MERRA-2, CAMS data assimilation products, and high-resolution WRF-Chem model simulations

2020 ◽  
Vol 20 (15) ◽  
pp. 9281-9310 ◽  
Author(s):  
Alexander Ukhov ◽  
Suleiman Mostamandi ◽  
Arlindo da Silva ◽  
Johannes Flemming ◽  
Yasser Alshehri ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
High Resolution ◽  
Middle East ◽  
Atmospheric Correction ◽  
World Health ◽  
So2 Emissions ◽  
Anthropogenic Aerosol ◽  
So2 Emission ◽  
Air Quality Forecast

Abstract. Modern-Era Retrospective analysis for Research and Applications v.2 (MERRA-2), Copernicus Atmosphere Monitoring Service Operational Analysis (CAMS-OA), and a high-resolution regional Weather Research and Forecasting model coupled with chemistry (WRF-Chem) were used to evaluate natural and anthropogenic particulate matter (PM) air pollution in the Middle East (ME) during 2015–2016. Two Moderate Resolution Imaging Spectrometer (MODIS) retrievals – combined product Deep Blue and Deep Target (MODIS-DB&amp;DT) and Multi-Angle Implementation of Atmospheric Correction (MAIAC) – and Aerosol Robotic Network (AERONET) aerosol optical depth (AOD) observations as well as in situ PM measurements for 2016 were used for validation of the WRF-Chem output and both assimilation products. MERRA-2 and CAMS-OA assimilate AOD observations. WRF-Chem is a free-running model, but dust emission in WRF-Chem is tuned to fit AOD and aerosol volume size distributions obtained from AERONET. MERRA-2 was used to construct WRF-Chem initial and boundary conditions both for meteorology and chemical and aerosol species. SO2 emissions in WRF-Chem are based on the novel OMI-HTAP SO2 emission dataset. The correlation with the AERONET AOD is highest for MERRA-2 (0.72–0.91), MAIAC (0.63–0.96), and CAMS-OA (0.65–0.87), followed by MODIS-DB&amp;DT (0.56–0.84) and WRF-Chem (0.43–0.85). However, CAMS-OA has a relatively high positive mean bias with respect to AERONET AOD. The spatial distributions of seasonally averaged AODs from WRF-Chem, assimilation products, and MAIAC are well correlated with MODIS-DB&amp;DT AOD product. MAIAC has the highest correlation (R=0.8), followed by MERRA-2 (R=0.66), CAMS-OA (R=0.65), and WRF-Chem (R=0.61). WRF-Chem, MERRA-2, and MAIAC underestimate and CAMS-OA overestimates MODIS-DB&amp;DT AOD. The simulated and observed PM concentrations might differ by a factor of 2 because it is more challenging for the model and the assimilation products to reproduce PM concentration measured within the city. Although aerosol fields in WRF-Chem and assimilation products are entirely consistent, WRF-Chem is preferable for analysis of regional air quality over the ME due to its higher spatial resolution and better SO2 emissions. The WRF-Chem’s PM background concentrations exceed the World Health Organization (WHO) guidelines over the entire ME. Mineral dust is the major contributor to PM (≈75 %–95 %) compared to other aerosol types. Near and downwind from the SO2 emission sources, nondust aerosols (primarily sulfate) contribute up to 30 % to PM2.5. The contribution of sea salt to PM in coastal regions can reach 5 %. The contributions of organic matter, black carbon and organic carbon to PM over the Middle East are insignificant. In the major cities over the Arabian Peninsula, the 90th percentile of PM10 and PM2.5 (particles with diameters less than 10 and 2.5 µm, respectively) daily mean surface concentrations exceed the corresponding Kingdom of Saudi Arabia air quality limits. The contribution of the nondust component to PM2.5 is <25 %, which limits the emission control effect on air quality. The mitigation of the dust effect on air quality requires the development of environment-based approaches like growing tree belts around the cities and enhancing in-city vegetation cover. The WRF-Chem configuration presented in this study could be a prototype of a future air quality forecast system that warns the population against air pollution hazards.

scholarly journals Assessment of Air Pollution in the Middle East Using Reanalyses Products and High-resolution WRF-Chem Simulations

2020 ◽  
Author(s):  
Alexander Ukhov ◽  
Suleiman Mostamandi ◽  
Johannes Flemming ◽  
Arlindo DaSilva ◽  
Nick Krotkov ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Middle East ◽  
Oil Recovery ◽  
Regional Climate ◽  
Arabian Gulf ◽  
Sea Salt ◽  
World Health ◽  
Ozone Monitoring Instrument ◽  
Health Organization

&lt;p&gt;The Middle East is notorious for high air pollution that affects both air-quality and regional climate. The Middle East generates about 30% of world dust annually and emits about 10% of anthropogenic SO&lt;sub&gt;2&lt;/sub&gt;. In this study we use Modern-Era Retrospective analysis for Research and Applications v.2 (MERRA-2), Copernicus Atmosphere Monitoring Service Operational Analysis (CAMS-OA) data assimilation products, and a regional Weather Research and Forecasting model (10 km resolution) coupled with Chemistry (WRF-Chem) to evaluate natural and anthropogenic air pollution in the ME. The SO&lt;sub&gt;2&lt;/sub&gt; anthropogenic emissions used in WRF-Chem are updated using the independent satellite SO&lt;sub&gt;2&lt;/sub&gt; emission dataset obtained from the Ozone Monitoring Instrument (OMI) observations onboard NASA EOS Aura satellite. Satellite and ground-based aerosol optical depth (AOD) observations, as well as Particulate Matter (PM) and SO&lt;sub&gt;2&lt;/sub&gt; in situ measurements for 2015-2016, were used for validation and model evaluation.&amp;#160;&lt;/p&gt;&lt;p&gt;Although aerosol fields in regional WRF-Chem and global assimilation products are quite consistent, WRF-Chem, due to its higher spatial resolution and novel OMI SO&lt;sub&gt;2&lt;/sub&gt; emissions, is preferable for analysis of regional air-quality over the ME. We found that conventional emission inventories (EDGAR-4.2, MACCity, and HTAP-2.2) have uncertainties in the location and magnitude of SO&lt;sub&gt;2&lt;/sub&gt; sources in the ME and significantly underestimate SO&lt;sub&gt;2&lt;/sub&gt; emissions in the Arabian Gulf. CAMS reanalysis tends to overestimate PM&lt;sub&gt;2.5&lt;/sub&gt; and underestimate PM&lt;sub&gt;10&lt;/sub&gt; concentrations. In the coastal areas, MERRA2 underestimates sulfate and tends to overestimate sea salt concentrations. The WRF-Chem&amp;#8217;s PM background concentrations exceed the World Health Organization (WHO) guidelines over the entire ME. The major contributor to PM (~75&amp;#8211;95%) is mineral dust. In the ME urban centers and near oil recovery fields, non-dust aerosols (primarily sulfate) contribute up to 26% into PM&lt;sub&gt;2.5&lt;/sub&gt;. The contribution of sea salt into PM can rich up to 5%. The contribution of organic matter into PM prevails over black carbon. SO&lt;sub&gt;2&lt;/sub&gt; surface concentrations in major ME cities frequently exceed European air-quality limits.&lt;/p&gt;

Decision Tree-Based Analytics for Reducing Air Pollution

2018 ◽  
Vol 17 (02) ◽  
pp. 1850015 ◽  
Author(s):  
Ajanta Das ◽  
Anindita Desarkar
Keyword(s):  
Air Pollution ◽  
Decision Tree ◽  
World Health ◽  
Pollution Level ◽  
Rule Base ◽  
Premature Deaths ◽  
Id3 Algorithm ◽  
Rule Sets ◽  
Term Basis ◽  
Health Organization

Air pollution indicates contaminated air which arises due to the effect of physical, biological or chemical alteration to the air in the atmosphere applicable both for indoors and outdoors. This situation arises when poisonous gases, dust or smoke enter into the atmosphere and make the surroundings vulnerable for any living beings as well as difficult for them to survive. Large numbers of premature deaths happen across the globe if exposed to these pollutants on a long-term basis as major portion of the cities have the pollution level above the threshold determined by World Health Organization (WHO). So appropriate measures need to be taken on a priority basis to reduce air pollution as well as save our planet. This paper proposes a novel air pollution reduction approach which collects source pollution data. After extraction of source data, it uses various databases (DBs) and then different decisions or classes are created. The decision tree was created with the help of Iterative Dichotomiser 3 (ID3) algorithm to implement the rule base appropriately depending on the air pollution level and a bunch of rule sets were derived from the decision tree further.

scholarly journals Noise and Air Pollution Related to Health in Urban Environments

Proceedings ◽  
2018 ◽  
Vol 2 (20) ◽  
pp. 1311 ◽  
Author(s):  
David Montes-González ◽  
Rosendo Vílchez-Gómez ◽  
Juan Miguel Barrigón-Morillas ◽  
Pedro Atanasio-Moraga ◽  
Guillermo Rey-Gozalo ◽  
...  
Keyword(s):  
Air Pollution ◽  
Road Traffic ◽  
Urban Environments ◽  
World Health ◽  
Sound Levels ◽  
European Environmental Agency ◽  
Environmental Health Risk ◽  
Health Organization ◽  
Relationship Of ◽  
The Relationship

Environmental noise is a pollutant considered by the World Health Organization (WHO) as a threat to public health due to its harmful effects on human health. In this regard, the European Environmental Agency (EEA) indicates that road traffic is the sound source that generates the greatest number of people exposed in Europe to sound levels above what is recommended by the European Noise Directive. In a similar way, the EEA also reports that air pollution is the most important environmental health risk in Europe, where road traffic is one of the main sources of emission of polluting gases. The relationship between both pollutants, leads to think about the development of common strategies. This paper presents a review on recent researches about the relationship of these two types of pollution in urban environments with different types of diseases.

scholarly journals Air Pollution and COVID-19: The Role of Particulate Matter in the Spread and Increase of COVID-19’s Morbidity and Mortality

2020 ◽  
Vol 17 (12) ◽  
pp. 4487 ◽  
Author(s):  
Silvia Comunian ◽  
Dario Dongo ◽  
Chiara Milani ◽  
Paola Palestini
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Close Contact ◽  
Atmospheric Particulate Matter ◽  
World Health ◽  
Angiotensin Converting Enzyme 2 ◽  
Positive Correlation ◽  
Pulmonary Cells ◽  
Health Organization

Sars-Cov-2 virus (COVID-19) is a member of the coronavirus family and is responsible for the pandemic recently declared by the World Health Organization. A positive correlation has been observed between the spread of the virus and air pollution, one of the greatest challenges of our millennium. COVID-19 could have an air transmission and atmospheric particulate matter (PM) could create a suitable environment for transporting the virus at greater distances than those considered for close contact. Moreover, PM induces inflammation in lung cells and exposure to PM could increase the susceptibility and severity of the COVID-19 patient symptoms. The new coronavirus has been shown to trigger an inflammatory storm that would be sustained in the case of pre-exposure to polluting agents. In this review, we highlight the potential role of PM in the spread of COVID-19, focusing on Italian cities whose PM daily concentrations were found to be higher than the annual average allowed during the months preceding the epidemic. Furthermore, we analyze the positive correlation between the virus spread, PM, and angiotensin-converting enzyme 2 (ACE2), a receptor involved in the entry of the virus into pulmonary cells and inflammation.

scholarly journals The Development of Air Pollution in Mexico City

SAGE Open ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 215824402093107
Author(s):  
Natalia Soto-Coloballes
Keyword(s):  
Air Pollution ◽  
Mexico City ◽  
Dust Storms ◽  
World Health ◽  
Dust Particles ◽  
Automotive Emissions ◽  
Industrialized Nations ◽  
Suspended Dust ◽  
The 1960S ◽  
Health Organization

The present essay documents changes to both objects of inquiry and the meaning of the epistemological concept of air pollution and it explains the processes that produced them. Smog as a result of production processes and the use of the automobile was not a concern for researchers and government managers in Mexico City, who were used to the dust storms resulting from the desiccation of the great Texcoco Lake during much of the 20th century, until the most industrialized nations of the West and the World Health Organization (WHO), alongside other international bodies such as the Organization for European Economic Cooperation (OEEC), reframed what was understood as air pollution, between the end of the 1960s and the beginning of the 1970s. Concerns about dust storms were displaced by concerns about factory and automotive emissions that contained new dangers—invisible hazards, just then being estimated, which altered what was understood or considered air pollution and gave rise to the quantification of particulate matter (which was then known as suspended dust particles) and new practices such as atmospheric monitoring. This essay concludes that what is understood as air pollution is situated; its meaning is not finite but simply evolves with time and with the rise of new global risks and concerns.

AIR POLLUTION AND ADVERSE BIRTH OUTCOMES: AN INTERNATIONAL ANALYSIS OF WORLD HEALTH ORGANIZATION GLOBAL SURVEY ON MATERNAL AND PERINATAL HEALTH

2011 ◽  
Vol 2011 (1) ◽  
Author(s):  
Nancy L. Fleischer ◽  
Marie S. O’Neill ◽  
Felipe Vadillo-Ortega ◽  
Aaron van Donkelaar ◽  
Randall V. Martin ◽  
...  
Keyword(s):  
Air Pollution ◽  
World Health Organization ◽  
Birth Outcomes ◽  
Perinatal Health ◽  
World Health ◽  
Adverse Birth Outcomes ◽  
Global Survey ◽  
Health Organization

scholarly journals The Homeless-Poor and the COVID-19 Stay-at-Home Policy of Government: Rethinking the Plight of Homelessness in Nigeria

SAGE Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 215824402110450
Author(s):  
Cletus O. Obasi ◽  
Christopher M. Anierobi
Keyword(s):  
Homeless People ◽  
World Health ◽  
Urban Centers ◽  
Healthcare Facilities ◽  
The World ◽  
Negative Perceptions ◽  
Policy Measures ◽  
The Government ◽  
Health Organization ◽  
At Home

The Government Stay-at-Home policy regarding the COVID-19 pandemic has seemingly aggravated the plight of the homeless, especially in Nigeria that has about 108 million homeless people who require special attention. Observations show that most of them situate randomly across urban centers in Nigeria and have no access to pronounced shelter, healthcare facilities, hygiene materials, and defined source of income. In response to the global COVID-19 pandemic currently ravaging many countries, most governments adopted the Stay-at-Home policy among some other policy measures that were recommended by the World Health Organization toward containing the spread of the virus. Given the COVID-19 Stay-at-Home policy of Nigerian Government, this study looked into the plight of the homeless-poor with a view to evolve an inclusive pro-poor housing strategy for the country. Findings show that the homeless poor have negative perceptions of the Stay-at-Home policy, which they see as being rather inimical to their survival. The study highlights lack of space and shelter as major reasons for their aversion to social distancing. Their reasons have serious implications for compliance to the COVID-19 Stay-at-Home policy as well as the spread curve of the virus. The study therefore recommends a review of the COVID-19 Regulation toward incorporating “Pro-Poor Housing Provisions” measures strictly for the homeless poor in the country. Strong collaboration between government and established institutions, such as Government-Church/Mosque strategy, is also recommended.

scholarly journals Risk Assessment for the Population of Kyiv, Ukraine as a Result of Atmospheric Air Pollution

2020 ◽  
Vol 10 (25) ◽  
pp. 200303 ◽  
Author(s):  
Oleksandr Popov ◽  
Andrii Iatsyshyn ◽  
Valeriia Kovach ◽  
Volodymyr Artemchuk ◽  
Iryna Kameneva ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Air Pollution ◽  
Air Quality ◽  
World Health ◽  
State Monitoring ◽  
Atmospheric Air ◽  
Map Design ◽  
Financial Interests ◽  
Health Organization ◽  
Human Health Effects

Background. According to the World Health Organization, 92% of the world's population lives in places where air quality levels exceed recommended limits. Recently, Ukraine had the most deaths per every 100,000 people (out of 120 countries) attributed to atmospheric air pollution. High levels of atmospheric air pollution have been observed not only in typically industrial regions, but in Ukraine's capital, Kyiv, as well. Objectives. The aim of the present study was to establish the state of air pollution in Kyiv and perform a risk assessment of associated human health effects. Methods. Using official statistics and state monitoring data, the study aimed to identify and analyze risks to the health of Kyiv's population associated with air pollution. The following methods were used: systematic, functional and comparative analysis, risk theory, mathematical modeling, probability theory and mathematical statistics, as well as geographic information system technologies for digital map design and objective-oriented methodology for software design systems. Results. The risk values across different areas of the city varied significantly, indicating that atmospheric air quality remains unstable. Areas with the highest and lowest risk values were identified. Conclusions. The environmental state of atmospheric air in Kyiv requires greater attention and additional research to identify the causes of air pollution, along with implementation of measures to improve air quality. Competing Interests. The authors declare no competing financial interests.

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