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

scholarly journals A Time-Based Assessment of Particulate Matter (PM2.5) Levels at a Highly Trafficked Intersection: Case Study of Sango-Ota, Nigeria

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 532
Author(s):  
David Olukanni ◽  
David Enetomhe ◽  
Gideon Bamigboye ◽  
Daniel Bassey
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Health Risks ◽  
Air Pollutants ◽  
Air Contamination ◽  
Ogun State ◽  
Sight Distance ◽  
Volatile Organic ◽  
Road Corridors

Vehicle emissions have become one of the most prevailing air contamination sources, including nitrogen oxides, volatile organic compounds, carbon monoxide and particulate matter (PM). Among other air pollutants, PM limits visible sight distance and poses health risks upon inhalation into the human body. This study focused on assessing PM2.5 concentrations in air at different periods of the day at the highly trafficked grade-separated intersection of Sango-Ota, Ogun State, Nigeria. PM2.5 readings were taken at three at-grade points around the intersection’s roundabout between 10:00 a.m. and 5:00 p.m. for four (4) days using the BR-SMART-126 Portable 4-in-1 air quality monitor. The highest level of PM2.5 obtained on Day 1 (Monday) and Day 4 (Thursday) was about 45.1% and 38.6%, respectively, lower than that of Day 3 (Wednesday). The highest concentrations of PM2.5 were recorded between 11:00 and 13:00 and between 16:00 and 18:00 (up to 217 µg/m3) whereas the lowest levels were recorded between 14:00 and 15:00 (as low as 86 µg/m3). The concentration of PM2.5 at the Sango-Ota intersection is adjudged “very poor” with average hourly concentrations between 97 and 370 µg/m3. Outcomes obtained indicate the need for improved measures to control air quality along major road corridors and at intersections in Ogun State and Nigeria at large.

scholarly journals Vpliv omejitve gibanja med epidemijo Covid-19 na obremenjevanje ozračja v Sloveniji

2021 ◽  
Author(s):  
Marjan Senegačnik ◽  
Davorin Žnidarič ◽  
Drago Vuk
Keyword(s):  
Carbon Dioxide ◽  
Particulate Matter ◽  
Air Quality ◽  
Air Pollutants ◽  
Road Traffic ◽  
Virus Spread ◽  
Negative Effects ◽  
Positive Effects ◽  
Entire World ◽  
Source Of Pollution

In 2020 the entire world was severely affected by COVID -19 epidemics. Because of preventing of the SARS Cov 2 virus spread there was necessary to introduce considerable restrictions of movement of citizens. This resulted in various negative effects in the field of economy. However, as road traffic is an important source of pollution – particularly of emissions of air pollutants and greenhouse gases it could be expected that these mobility restrictions result in certain positive effects on the environment. The paper will try to estimate the air quality during the period of epidemics when mobility was severely restricted (second half of March and April 2020, second half of October, November and December 2020). The review will be limited to those kinds of pollutants which are particularly related to road traffic (nitrogen oxides, particulate matter, ozone) as well as to carbon dioxide as the most important greenhouse gas.

scholarly journals The Development and Application of Machine Learning in Atmospheric Environment Studies

2021 ◽  
Vol 13 (23) ◽  
pp. 4839
Author(s):  
Lianming Zheng ◽  
Rui Lin ◽  
Xuemei Wang ◽  
Weihua Chen
Keyword(s):  
Machine Learning ◽  
Particulate Matter ◽  
Nitrogen Deposition ◽  
Air Pollutants ◽  
Model Performance ◽  
Atmospheric Science ◽  
Atmospheric Environment ◽  
Significant Progress ◽  
Quantitative Statistics

Machine learning (ML) plays an important role in atmospheric environment prediction, having been widely applied in atmospheric science with significant progress in algorithms and hardware. In this paper, we present a brief overview of the development of ML models as well as their application to atmospheric environment studies. ML model performance is then compared based on the main air pollutants (i.e., PM2.5, O3, and NO2) and model type. Moreover, we identify the key driving variables for ML models in predicting particulate matter (PM) pollutants by quantitative statistics. Additionally, a case study for wet nitrogen deposition estimation is carried out based on ML models. Finally, the prospects of ML for atmospheric prediction are discussed.

scholarly journals Indoor environmental quality evaluation in a hot and arid climate: a case study of a higher education office building

2020 ◽  
Vol 167 ◽  
pp. 04004
Author(s):  
Yasmin Abdou ◽  
Young Ki Kim ◽  
Lindita Bande
Keyword(s):  
Higher Education ◽  
Carbon Dioxide ◽  
Particulate Matter ◽  
Environmental Quality ◽  
Well Being ◽  
Environmental Data ◽  
Office Building ◽  
Arid Climate ◽  
Indoor Environmental Quality

Indoor Environment Quality (IEQ) refers to the overall environmental quality within a building, especially as it relates to the health and comfort of the building’s occupants. It includes several factors such as lighting levels and indoor air quality (IAQ). As humans spend a significant amount of time indoors; particularly at the workplace for up to 12 hours a day, the IEQ of the office greatly affects one’s overall well-being, health with striking effects on productivity. As for IAQ, in severe cases, high levels of carbon dioxide (CO2), particulate matter (PM), and humidity may cause headache, allergy, and asthma. A higher education (HE) office building located in United Arab Emirates University (UAEU) campus has been taken as a case study. Situated in the UAE, this is characterized by an extremely hot-arid climate. The HE building has been monitored using a set of advanced sensor devices to record indoor environmental data such as the measurements of temperature, relative humidity, lux level, particulate matter 2.5/10(PM 2.5/ 10), carbon dioxide (CO2), and total volatile organic compounds (TVOCs). Results of this paper aim to use the onsite numerical assessment and future POE assessment to verify the building’s performance and discover where the operational gaps are. Better facility management strategies will be suggested to enhance the indoor environmental quality (IEQ) as well as more findings will be discussed in this paper.

scholarly journals The Problem of Carbon Dioxide Emissions from Closed Coal Mine Shafts – The Overview and the Case Study

2016 ◽  
Vol 61 (3) ◽  
pp. 587-600
Author(s):  
Paweł Wrona ◽  
Józef Sułkowski ◽  
Zenon Różański ◽  
Grzegorz Pach
Keyword(s):  
Carbon Dioxide ◽  
Carbon Dioxide Emissions ◽  
Carbon Dioxide Emission ◽  
Mining Area ◽  
Emission Point ◽  
Water Pumping ◽  
Gas Hazard ◽  
Flow Through ◽  
Reporting Procedures

Abstract Greenhouse gas emissions are a common problem noticed in every mining area just after mine closures. However, there could be a significant local gas hazard for people with continuous (but variable) emission of these gases into the atmosphere. In the Upper Silesia area, there are 24 shafts left for water pumping purposes and gases can flow through them hydraulically. One of them – Gliwice II shaft – was selected for inspection. Carbon dioxide emission with no methane was detected here. Changes in emission and concentration of carbon dioxide around the shaft was the aim of research carried out. It was stated that a selected shaft can create two kinds of gas problems. The first relates to CO2 emission into the atmosphere. Possible emission of that gas during one minute was estimated at 5,11 kg CO2/min. The second problem refers to the local hazard at the surface. The emission was detected within a radius of 8m from the emission point at the level 1m above the ground. These kinds of matters should be subject to regular gas monitoring and reporting procedures.

Exercise Performed Concomitantly with Particulate Matter Exposure Inhibits Lung Injury

2017 ◽  
Vol 39 (02) ◽  
pp. 133-140 ◽  
Author(s):  
Adriano Silva-Renno ◽  
Guilherme Baldivia ◽  
Manoel Oliveira-Junior ◽  
Maysa Brandao-Rangel ◽  
Elias El-Mafarjeh ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Systemic Inflammation ◽  
Air Pollutants ◽  
Lung Parenchyma ◽  
Treadmill Training ◽  
Tnf Alpha ◽  
Systemic Response ◽  
Pm 2.5 ◽  
Pm 10 ◽  
Particulate Matter Exposure

AbstractAir pollution is a growing problem worldwide, inducing and exacerbating several diseases. Among the several components of air pollutants, particulate matter (PM), especially thick (10–2.5 µm; PM 10) and thin (≤2.5 µm; PM 2.5), are breathable particles that easily can be deposited within the lungs, resulting in pulmonary and systemic inflammation. Although physical activity is strongly recommended, its effects when practiced in polluted environments are questionable. Therefore, the present study evaluated the pulmonary and systemic response of concomitant treadmill training with PM 2.5 and PM 10 exposure. Treadmill training inhibited PM 2.5- and PM 10-induced accumulation of total leukocytes (p<0.001), neutrophils (p<0.001), macrophages (p<0.001) and lymphocytes (p<0.001) in bronchoalveolar lavage (BAL), as well as the BAL levels of IL-1beta (p<0.001), CXCL1/KC (p<0.001) and TNF-alpha (p<0.001), whereas it increased IL-10 levels (p<0.05). Similar effects were observed on accumulation of polymorphonuclear (p<0.01) and mononuclear (p<0.01) cells in the lung parenchyma and in the peribronchial space. Treadmill training also inhibited PM 2.5- and PM 10-induced systemic inflammation, as observed in the number of total leukocytes (p<0.001) and in the plasma levels of IL-1beta (p<0.001), CXCL1/KC (p<0.001) and TNF-alpha (p<0.001), whereas it increased IL-10 levels (p<0.001). Treadmill training inhibits lung and systemic inflammation induced by particulate matter.

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