Day-to-day variations in paddy-residue burning and residential heating emissions control aerosol pollution peaks in rural north-west India

2021 ◽  
Author(s):  
Harshita Pawar ◽  
Baerbel Sinha
Keyword(s):  
Air Quality ◽  
Large Scale ◽  
Learning Algorithm ◽  
Low Cost ◽  
Winter Season ◽  
Ambient Air ◽  
Rural Site ◽  
North West ◽  
Daily Average ◽  
Residential Heating

<p>November onwards, the poor air quality over north-west India is blamed on the large-scale paddy residue burning in Punjab and Haryana. However, the emission strength of this source remains poorly constrained due to the lack of ground-based measurements within the rural source regions. In this study, we report the particulate matter (PM) levels at Nadampur, a rural site in the Sangrur district of Punjab that witnesses rampant paddy residue burning, using the Airveda low-cost PM sensors from October to December 2019. The raw PM measurements from the sensor were corrected using the Random Forest machine learning algorithm. The daily average PM<sub>10</sub> and PM<sub>2.5</sub> mass concentration at Nadampur correlated well  (r > 0.7) with the daily sum of VIIRS fire counts. Agricultural activities, including paddy residue burning and harvesting operations, contributed less than 40% to the overall PM loading, even in the peak burning period at Nadampur. We show that the increased residential heating emissions in the winter season have a profound and currently neglected impact on ambient air quality. A dip in the daily average temperature by 1 ºC increased the daily emission of PM<sub>10</sub> by 6.3 tonnes and that of PM<sub>2.5</sub> by 5.8 tonnes. Overall, paddy harvest, local and regional paddy residue burning, residential heating emissions, ventilation, and wet scavenging could explain 79% of the variations in PM<sub>10</sub> and 85% of the variations in PM<sub>2.5</sub>. Day to day variations in PM emissions from residential heating in response to the ambient temperature must be incorporated into emission inventories and models for accurate air quality forecasts.</p>

MOPGA/Make Air Quality Great Again: Filling in the air quality data gap in Africa using lower-cost RAMP monitors

2020 ◽  
Author(s):  
Ramachandran Subramanian ◽  
Matthias Beekmann ◽  
Carl Malings ◽  
Anais Feron ◽  
Paola Formenti ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Electrochemical Sensors ◽  
Low Cost ◽  
Fine Particulate Matter ◽  
Ambient Air ◽  
Ambient Air Pollution ◽  
Quality Data ◽  
Rural Site ◽  
Data Gap

<p>Ambient air pollution is a leading cause of premature mortality across the world, with an estimated 258,000 deaths in Africa (UNICEF/GBD 2017). These estimated impacts have large uncertainties as many major cities in Africa do not have any ground-based air quality monitoring. The lack of data is due in part to the high cost of traditional monitoring equipment and the lack of trained personnel. As part of the “Make Air Quality Great Again” project under the “Make Our Planet Great Again” framework (MOPGA), we propose filling this data gap with low-cost sensors carefully calibrated against reference monitors.</p><p>Fifteen real-time affordable multi-pollutant (RAMP) monitors have been deployed in Abidjan, Côte d'Ivoire; Accra, Ghana; Kigali, Rwanda; Nairobi, Kenya; Niamey, Niger; and Zamdela, South Africa (near Johannesburg). The RAMPs use Plantower optical nephelometers to measure fine particulate matter mass (PM<sub>2.5</sub>) and four Alphasense electrochemical sensors to detect pollutant gases including nitrogen dioxide (NO<sub>2</sub>) and ozone (O<sub>3</sub>).</p><p>Using a calibration developed in Créteil, France, the deployments thus far reveal morning and evening spikes in combustion-related air pollution. The median hourly NO<sub>2</sub> in Accra and Nairobi for September-October 2019 was about 11 ppb; a similar value was observed across November-December 2019 in Zamdela. However, a previous long-term deployment of the RAMPs in Rwanda showed that, for robust data quality, low-cost sensors must be collocated with traditional reference monitors to develop localized calibration models. Hence, we acquired regulatory-grade PM<sub>2.5</sub>, NO<sub>2</sub>, and O<sub>3</sub> monitors for Abidjan and Accra. We also collocated RAMPs with existing reference monitors in Zamdela, Kigali, Abidjan, and Lamto (a rural site in Côte d'Ivoire). In this talk, we will present results on spatio-temporal variability of collocation-based sensor calibrations across these different cities, source identification, and challenges and plans for future expansion.</p>

scholarly journals Ambient Air Quality Classification by Grey Wolf Optimizer Based Support Vector Machine

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Akash Saxena ◽  
Shalini Shekhawat
Keyword(s):  
Support Vector Machine ◽  
Air Quality ◽  
Industrial Development ◽  
Learning Algorithm ◽  
Ambient Air ◽  
Support Vector ◽  
Grey Wolf Optimizer ◽  
Mathematical Framework ◽  
Primary Concern

With the development of society along with an escalating population, the concerns regarding public health have cropped up. The quality of air becomes primary concern regarding constant increase in the number of vehicles and industrial development. With this concern, several indices have been proposed to indicate the pollutant concentrations. In this paper, we present a mathematical framework to formulate a Cumulative Index (CI) on the basis of an individual concentration of four major pollutants (SO2, NO2, PM2.5, and PM10). Further, a supervised learning algorithm based classifier is proposed. This classifier employs support vector machine (SVM) to classify air quality into two types, that is, good or harmful. The potential inputs for this classifier are the calculated values of CIs. The efficacy of the classifier is tested on the real data of three locations: Kolkata, Delhi, and Bhopal. It is observed that the classifier performs well to classify the quality of air.

scholarly journals Community Air Sensor Network (CAIRSENSE) project: Evaluation of low-cost sensor performance in a suburban environment in the southeastern United States

2016 ◽  
Author(s):  
Wan Jiao ◽  
Gayle Hagler ◽  
Ronald Williams ◽  
Robert Sharpe ◽  
Ryan Brown ◽  
...  
Keyword(s):  
Air Pollution ◽  
Carbon Monoxide ◽  
Air Quality ◽  
Sulfur Dioxide ◽  
Sensor Network ◽  
Correlation Coefficient ◽  
Low Cost ◽  
Ambient Air ◽  
Sensor Technology ◽  
Sensor Performance

Abstract. Advances in air pollution sensor technology have enabled the development of small and low cost systems to measure outdoor air pollution. The deployment of a large number of sensors across a small geographic area would have potential benefits to supplement traditional monitoring networks with additional geographic and temporal measurement resolution, if the data quality were sufficient. To understand the capability of emerging air sensor technology, the Community Air Sensor Network (CAIRSENSE) project deployed low cost, continuous and commercially-available air pollution sensors at a regulatory air monitoring site and as a local sensor network over a surrounding ~ 2 km area in Southeastern U.S. Co-location of sensors measuring oxides of nitrogen, ozone, carbon monoxide, sulfur dioxide, and particles revealed highly variable performance, both in terms of comparison to a reference monitor as well as whether multiple identical sensors reproduced the same signal. Multiple ozone, nitrogen dioxide, and carbon monoxide sensors revealed low to very high correlation with a reference monitor, with Pearson sample correlation coefficient (r) ranging from 0.39 to 0.97, −0.25 to 0.76, −0.40 to 0.82, respectively. The only sulfur dioxide sensor tested revealed no correlation (r  0.5), step-wise multiple linear regression was performed to determine if ambient temperature, relative humidity (RH), or age of the sensor in sampling days could be used in a correction algorithm to improve the agreement. Maximum improvement in agreement with a reference, incorporating all factors, was observed for an NO2 sensor (multiple correlation coefficient R2adj-orig = 0.57, R2adj-final = 0.81); however, other sensors showed no apparent improvement in agreement. A four-node sensor network was successfully able to capture ozone (2 nodes) and PM (4 nodes) data for an 8 month period of time and show expected diurnal concentration patterns, as well as potential ozone titration due to near-by traffic emissions. Overall, this study demonstrates a straightforward methodology for establishing low-cost air quality sensor performance in a real-world setting and demonstrates the feasibility of deploying a local sensor network to measure ambient air quality trends.

Trace gases and organic aerosol at a rural site in Vietnam during large scale biomass burning

2021 ◽  
Author(s):  
Simone M. Pieber ◽  
Dac-Loc Nguyen ◽  
Hendryk Czech ◽  
Stephan Henne ◽  
Nicolas Bukowiecki ◽  
...  
Keyword(s):  
Air Quality ◽  
Chemical Composition ◽  
Biomass Burning ◽  
Large Scale ◽  
Trace Gases ◽  
Organic Aerosol ◽  
Trace Gas ◽  
Rural Site ◽  
Air Masses ◽  
Mixing Ratios

<p>Open biomass burning (BB) is a globally widespread phenomenon. The fires release pollutants, which are harmful for human and ecosystem health and alter the Earth's radiative balance. Yet, the impact of various types of BB on the global radiative forcing remains poorly constrained concerning greenhouse gas emissions, BB organic aerosol (OA) chemical composition and related light absorbing properties. Fire emissions composition is influenced by multiple factors (e.g., fuel and thereby vegetation-type, fuel moisture, fire temperature, available oxygen). Due to regional variations in these parameters, studies in different world regions are needed. Here we investigate the influence of seasonally recurring BB on trace gas concentration and air quality at the regional Global Atmosphere Watch (GAW) station Pha Din (PDI) in rural Northwestern Vietnam. PDI is located in a sparsely populated area on the top of a hill (1466 m a.s.l.) and is well suited to study the large-scale fires on the Indochinese Peninsula, whose pollution plumes are frequently transported towards the site [1]. We present continuous trace gas observations of CO<sub>2</sub>, CH<sub>4</sub>, CO, and O<sub>3</sub> conducted at PDI since 2014 and interpret the data with atmospheric transport simulations. Annually recurrent large scale BB leads to hourly time-scale peaks CO mixing ratios at PDI of 1000 to 1500 ppb around every April since the start of data collection in 2014. We complement this analysis with carbonaceous PM<sub>2.5 </sub>chemical composition analyzed during an intensive campaign in March-April 2015. This includes measurements of elemental and organic carbon (EC/OC) and more than 50 organic markers, such as sugars, PAHs, fatty acids and nitro-aromatics [2]. For the intensive campaign, we linked CO, CO<sub>2</sub>, CH<sub>4</sub> and O<sub>3</sub> mixing ratios to a statistical classification of BB events, which is based on OA composition. We found increased CO and O<sub>3</sub> levels during medium and high BB influence during the intensive campaign. A backward trajectory analysis confirmed different source regions for the identified periods based on the OA cluster. Typically, cleaner air masses arrived from northeast, i.e., mainland China and Yellow sea during the intensive campaign. The more polluted periods were characterized by trajectories from southwest, with more continental recirculation of the medium cluster, and more westerly advection for the high cluster. These findings highlight that BB activities in Northern Southeast Asia significantly enhances the regional OA loading, chemical PM<sub>2.5 </sub>composition and the trace gases in northwestern Vietnam. The presented analysis adds valuable data on air quality in a region of scarce data availability.</p><p> </p><p><strong>REFERENCES</strong></p><p>[1] Bukowiecki, N. et al. Effect of Large-scale Biomass Burning on Aerosol Optical Properties at the GAW Regional Station Pha Din, Vietnam. AAQR. 19, 1172–1187 (2019).</p><p>[2] Nguyen, D. L, et al. Carbonaceous aerosol composition in air masses influenced by large-scale biomass burning: a case-study in Northwestern Vietnam. ACPD., https://doi.org/10.5194/acp-2020-1027, in review, 2020.</p>

scholarly journals Low-Cost Air Quality Sensors: One-Year Field Comparative Measurement of Different Gas Sensors and Particle Counters with Reference Monitors at Tušimice Observatory

Atmosphere ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 492 ◽  
Author(s):  
Petra Bauerová ◽  
Adriana Šindelářová ◽  
Štěpán Rychlík ◽  
Zbyněk Novák ◽  
Josef Keder
Keyword(s):  
Air Quality ◽  
Gas Sensors ◽  
Low Cost ◽  
Monitoring Network ◽  
Field Testing ◽  
Ambient Air ◽  
Monitoring Networks ◽  
Comparative Measurement ◽  
One Year ◽  
Pm2.5 And Pm10

With attention increasing regarding the level of air pollution in different metropolitan and industrial areas worldwide, interest in expanding the monitoring networks by low-cost air quality sensors is also increasing. Although the role of these small and affordable sensors is rather supplementary, determination of the measurement uncertainty is one of the main questions of their applicability because there is no certificate for quality assurance of these non-reference technologies. This paper presents the results of almost one-year field testing measurements, when the data from different low-cost sensors (for SO2, NO2, O3, and CO: Cairclip, Envea, FR; for PM1, PM2.5, and PM10: PMS7003, Plantower, CHN, and OPC-N2, Alphasense, UK) were compared with co-located reference monitors used within the Czech national ambient air quality monitoring network. The results showed that in addition to the given reduced measurement accuracy of the sensors, the data quality depends on the early detection of defective units and changes caused by the effect of meteorological conditions (effect of air temperature and humidity on gas sensors and effect of air humidity with condensation conditions on particle counters), or by the interference of different pollutants (especially in gas sensors). Comparative measurement is necessary prior to each sensor’s field applications.

Smoke incursions into urban areas: simulation of a Georgia prescribed burn

2009 ◽  
Vol 18 (3) ◽  
pp. 336 ◽  
Author(s):  
Yongqiang Liu ◽  
Scott Goodrick ◽  
Gary Achtemeier ◽  
William A. Jackson ◽  
John J. Qu ◽  
...  
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Ambient Air ◽  
Quality Standard ◽  
Prescribed Burn ◽  
Modeling Framework ◽  
North West ◽  
Transport Direction ◽  
Smoke Plumes ◽  
Ambient Air Quality Standard

This study investigates smoke incursion into urban areas by examining a prescribed burn in central Georgia, USA, on 28 February 2007. Simulations were conducted with a regional modeling framework to understand transport, dispersion, and structure of smoke plumes, the air quality effects, sensitivity to emissions, and the roles of burn management strategy in mitigating the effects. The results indicate that smoke plumes first went west, but turned north-west at noon owing to a shift in wind direction. The smoke then invaded metropolitan Atlanta during the evening rush hour. The plumes caused severe air quality problems in Atlanta. Some hourly ground PM2.5 (particulate matter not greater than 2.5 μm in diameter) concentrations at three metropolitan Atlanta locations were three to four times as high as the daily (24-h) US National Ambient Air Quality Standard. The simulated shift in the smoke transport direction and the resultant effects on air quality are supported by the satellite and ambient air measurements. Two sensitivity simulations indicate a nearly linear relation between the emission intensities and PM2.5 concentrations. Two other simulations indicate that the impacts on air quality for the residents of Atlanta during the evening commute could have been reduced if the starting time of the burn had been altered.

scholarly journals Low cost Passive Monitoring of Nitrogen dioxide and Sulphur dioxide in ambient air

2012 ◽  
Vol 27 ◽  
pp. 34-45 ◽  
Author(s):  
R. M. Byanju ◽  
M. B. Gewali ◽  
K. Manandhar
Keyword(s):  
Nitrogen Dioxide ◽  
Sulphur Dioxide ◽  
Coefficient Of Variation ◽  
Large Scale ◽  
Low Cost ◽  
Ambient Air ◽  
Distilled Water ◽  
Passive Monitoring ◽  
Standard Methods ◽  
Resource Limited

Standard nitrogen dioxide (NO2) and sulphur dioxide (SO2) monitoring techniques require expensive instrumentation which is not easily adapted for large scale monitoring by resource limited countries. This paper presents the use of locally available relatively cheaper polyethylene tubes to be developed as passive diffusive sampler and use for monitoring of ambient nitrogen dioxide and sulphur dioxide using Triethanolamine (TEA) as absorbent. After extraction with double distilled water, modified Griese-Saltzmann method and West-Gaeke method were used for analysis of nitrite and sulphate adduct formed due to reaction of NO2 and SO2 respectively with TEA using spectrophotometer. The results are successfully compared with other standard methods. The detection limits and precision of the method as expressed as Coefficient of variation are good enough for monitoring of NO2 and SO2 in ambient air.DOI: http://dx.doi.org/10.3126/jncs.v27i1.6439 J. Nepal Chem. Soc., Vol. 27, 2011 34-45Uploaded date: 16 July, 2012

Characterization of Ambient Air Quality in Selected Urban Areas in Uganda: A Low-Cost Approach

2021 ◽  
Author(s):  
Deo Okure ◽  
Engineer Bainomugisha ◽  
Nancy Lozano-Gracia ◽  
Maria Edisa Soppelsa
Keyword(s):  
Air Quality ◽  
Urban Areas ◽  
Low Cost ◽  
Ambient Air ◽  
Ambient Air Quality ◽  
Cost Approach
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