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

<p>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<sub>2</sub>. 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<sub>2</sub> anthropogenic emissions used in WRF-Chem are updated using the independent satellite SO<sub>2</sub> 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<sub>2</sub> in situ measurements for 2015-2016, were used for validation and model evaluation. </p><p>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<sub>2</sub> 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<sub>2</sub> sources in the ME and significantly underestimate SO<sub>2</sub> emissions in the Arabian Gulf. CAMS reanalysis tends to overestimate PM<sub>2.5</sub> and underestimate PM<sub>10</sub> concentrations. In the coastal areas, MERRA2 underestimates sulfate and tends to overestimate sea salt concentrations. 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 PM<sub>2.5</sub>. The contribution of sea salt into PM can rich up to 5%. The contribution of organic matter into PM prevails over black carbon. SO<sub>2</sub> surface concentrations in major ME cities frequently exceed European air-quality limits.</p>

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.

scholarly journals Indoor Air Quality, Information, and Socioeconomic Status: Evidence from Delhi

2021 ◽  
Vol 111 ◽  
pp. 420-424
Author(s):  
Michael Greenstone ◽  
Kenneth Lee ◽  
Harshil Sahai
Keyword(s):  
Air Pollution ◽  
Socioeconomic Status ◽  
Air Quality ◽  
Indoor Air Quality ◽  
Indoor Air ◽  
Indoor Air Pollution ◽  
World Health ◽  
Quality Information ◽  
Air Purifier ◽  
Health Organization

In Delhi, one of the world's most polluted cities, there is relatively little information on indoor air pollution and how it varies by socioeconomic status (SES). Using indoor air quality monitors (IAQMs), we find that winter levels of household air pollution exceed World Health Organization standards by more than 20 times in both high-and low-SES households. We then evaluate a field experiment that randomly assigned monthlong IAQM user trials across medium-and high-SES households but suffered from significant survey non-response. Among respondents, IAQMs did not affect take-up of subsidized air purifier rentals or other defensive behavior.

scholarly journals Assessing the Immediate Effect of Covid-19 Lockdown on Air Quality: A Case Study of Delhi, India

2020 ◽  
Vol 13 (3-4) ◽  
pp. 27-33
Author(s):  
Ankit Sikarwar ◽  
Ritu Rani
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Spatial Interpolation ◽  
World Health ◽  
Guideline Values ◽  
Distance Weighting ◽  
Health Organization ◽  
The City ◽  
Inverse Distance

Abstract In India, a nationwide lockdown due to COVID-19 has been implemented on 25 March 2020. The lockdown restrictions on more than 1.3 billion people have brought exceptional changes in the air quality all over the country. This study aims to analyze the levels of three major pollutants: particulate matter sized 2.5 μm (PM2.5) and 10 μm (PM10), and nitrogen dioxide (NO2) before and during the lockdown in Delhi, one of the world’s most polluted cities. The data for PM2.5, PM10, and NO2 concentrations are derived from 38 ground stations dispersed within the city. The spatial interpolation maps of pollutants for two times are generated using Inverse Distance Weighting (IDW) model. The results indicate decreasing levels of PM2.5, PM10, and NO2 concentrations in the city by 93%, 83%, and 70% from 25 February 2020 to 21 April 2020 respectively. It is found that one month before the lockdown the levels of air pollution in Delhi were critical and much higher than the guideline values set by the World Health Organization. The levels of air pollution became historically low after the lockdown. Considering the critically degraded air quality for decades and higher morbidity and mortality rate due to unhealthy air in Delhi, the improvement in air quality due to lockdown may result as a boon for the better health of the city’s population.

scholarly journals Opinion: Insights into updating Ambient Air Quality Directive (2008/50EC)

2021 ◽  
Author(s):  
Joel Kuula ◽  
Hilkka Timonen ◽  
Jarkko V. Niemi ◽  
Hanna Manninen ◽  
Topi Rönkkö ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Management Strategies ◽  
Ambient Air ◽  
World Health ◽  
Ambient Air Quality ◽  
Adverse Health Effects ◽  
Quality Guidelines ◽  
Health Organization ◽  
Air Quality Guidelines

Abstract. As the evidence for the adverse health effects of air pollution continues to increase, World Health Organization (WHO) recently published its latest edition of the Global Air Quality Guidelines. Although not legally binding, the guidelines aim to provide a framework in which policymakers can combat air pollution by formulating evidence-based air quality management strategies. In the light of this, European Union has stated its intent to revise the current Ambient Air Quality Directive (2008/50/EC) to resemble closer to that of the newly published WHO guidelines. This article provides an informed opinion on selected features of the air quality directive that we believe would benefit from a reassessment. The selected features include discussion about 1) air quality sensors as a part of hierarchical observation network, 2) number of minimum sampling points and their siting criteria, and 3) new target air pollution parameters for future consideration.

scholarly journals Assessing the immediate effect of COVID-19 lockdown on air quality: A case study of Delhi, India

2020 ◽  
Author(s):  
Ankit Sikarwar ◽  
Ritu Rani
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Spatial Interpolation ◽  
World Health ◽  
Guideline Values ◽  
Distance Weighting ◽  
Health Organization ◽  
The City ◽  
Inverse Distance

Abstract In India, the nationwide lockdown due to COVID-19 has been implemented on 25 March 2020. The lockdown restrictions on more than 1.3 billion people have brought exceptional changes in the air quality all over the country. This study aims to analyze the levels of three major pollutants (PM2.5, PM10, and NO2) before and during the lockdown in Delhi, one of the world’s most polluted cities. The data for PM2.5, PM10, and NO2 concentrations are derived from 38 ground stations dispersed within the city. The spatial interpolation maps of pollutants for two times are generated using Inverse Distance Weighting (IDW) model. The results indicate the lowering of PM2.5, PM10, and NO2 concentrations in the city by 93%, 83%, and 70% from 25 February 2020 to 21 April 2020 respectively. It is found that before one month of the lockdown the levels of air pollution in Delhi were critically high and far beyond the guideline values set by the World Health Organization. The levels of air pollution are historically low after the lockdown. Considering the critically degraded air quality for decades and higher morbidity and mortality rate due to unhealthy air in Delhi, the improvement in air quality due to lockdown may result as a boon for the better health of the city’s population.

scholarly journals Global Air Quality: An Inter-Disciplinary Approach to Exposure Assessment for Burden of Disease Analyses

Atmosphere ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 48
Author(s):  
Gavin Shaddick ◽  
James M. Salter ◽  
Vincent-Henri Peuch ◽  
Guilia Ruggeri ◽  
Matthew L. Thomas ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Atmospheric Composition ◽  
World Health ◽  
Sources Of Information ◽  
Integration Model ◽  
Country Level ◽  
The World ◽  
Development Goals ◽  
Health Organization

Global assessments of air quality and health require comprehensive estimates of the exposures to air pollution that are experienced by populations in every country. However, there are many countries in which measurements from ground-based monitoring are sparse or non-existent, with quality-control and representativeness providing additional challenges. While ground-based monitoring provides a far from complete picture of global air quality, there are other sources of information that provide comprehensive coverage across the globe. The World Health Organization developed the Data Integration Model for Air Quality (DIMAQ) to combine information from ground measurements with that from other sources, such as atmospheric chemical transport models and estimates from remote sensing satellites in order to produce the information that is required for health burden assessment and the calculation of air pollution-related Sustainable Development Goals indicators. Here, we show an example of the use of DIMAQ with the Copernicus Atmosphere Monitoring Service Re-Analysis (CAMSRA) of atmospheric composition, which represents the best practices in meteorology and climate monitoring that were developed under the World Meteorological Organization’s Global Atmosphere Watch programme. Estimates of PM2.5 from CAMSRA are integrated within the DIMAQ framework in order to produce high-resolution estimates of air pollution exposure that can be aggregated in a coherent fashion to produce country-level assessments of exposures.

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 Impacts of the COVID-19 Pandemic on Ambient Air Quality in China: Atox Quasi-difference-in-difference Approach

2021 ◽  
Author(s):  
Tuo ZHANG ◽  
Maogang Tang
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Human Activities ◽  
Ambient Air ◽  
World Health ◽  
Static And Dynamic Analysis ◽  
Premature Deaths ◽  
Novel Coronavirus ◽  
Health Organization ◽  
Pollution Emissions

Abstract The novel coronavirus pandemic (COVID-19) outbreak has provided a distinct opportunity to explore the mechanisms by which human activities affect air quality and pollution emissions. We conduct a quasi-difference-in-differences (DID) analysis of the impacts of lockdown measures on air pollution during the first wave of COVID-19 pandemic in China. Our study covers 367 cities from the beginning of the lockdown on January 23, 2020 until April 22, two weeks after the lockdown in epicenter was lifted. Static and dynamic analysis of the average treatment effects of treated effects is conducted for the air quality index (AQI) and six criteria pollutants. The results indicate that, first, on average, the AQI decreased by about 7%. However, it was still over the threshold of the World Health Organization (WHO). Second, we detect heterogeneous changes in the level of different pollutants, which suggests heterogeneous impacts of the lockdown on human activities: carbon monoxide (CO) had the biggest drop of about 30% and nitrogen dioxide (NO2) had the second-biggest drop of 20%. In contrast, ozone (O3) increased by 3.74% due to the improvement of visibility. We project that it would reduce the premature deaths related to air pollution by 150 thousand nationwide during the research period, which is much larger than the death due to COVID-19 infections. Third, air pollution rebounded immediately after the number of infections dropped, which indicates a swift recovery of human activities. This study provides insights for the implementation of environmental policies in China and other developing countries.JEL codes: Q51, Q52, Q53

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 Green Home: New Application for Monitoring Indoor Air Quality Using Arduino Platform

2020 ◽  
Author(s):  
Ameera Ali Al-Fazari ◽  
Mahra Said Ahmed Al-Risi ◽  
Rasha AbdulWahhab
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Real Time ◽  
Web Application ◽  
Positive Impact ◽  
Pollution Monitoring ◽  
World Health ◽  
Potential Health ◽  
Air Pollution Monitoring ◽  
Health Organization

Air pollution is one of the most serious problems facing the atmosphere on the planet. Air pollution is defined as a collection of harmful chemicals and an organic material from factories are emitted in the atmosphere layer and causes many different diseases such as cough, eye irritation and even death. According to the World Health Organization (WHO), the number of deaths per year due to pollution from gases is about 3.5 million. The main objective of this research is to develop a real time air pollution monitoring web application able to detect indoor toxic gases titled Aircom. The proposed application has a special feature in which IoT technology is embedded in one of its units. The main purpose of using such technology is to help individual to check and get real time information about air’s parameters such as Methane, Ethanol, Toluene, CO2, CO, Alcohol, Acetone, LPG, NH4, Benzene and Hexane along with the temperature, humidity and dust. Aircome will be implemented as an integrated pollution monitoring application which consist of MQ-2, MQ-3, MQ-135, MQ-9, GP2Y1010AU0F, GPS,DHT11, ESP8266 Wi-Fi, Arduino Uno board and web server.  All the collected data form the suggested sensors are transmitting using Wifi technology to IoT module and in an online database.  Moreover, the collected data later can be viewed using web browser which is installed in any of electronic media. The retrieved data will be displayed in the form of tables and graphs. An alert will be send by Aircom instantly in case the level of air‘s parameters reach above normal level. Generally speaking, Aircom will be developed by using different languages such as C++, Arduino, Java, Java script, PHP, html and MySQL.  For further verification of our proposal, we employed a quantitative study to check if what we proposed will have positive impact among different samples in the society. The outcome of the survey indicates that using such application helps to protect individuals from the bad air quality and decreases the potential health problems.

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