scholarly journals Investigation of Low-Cost and Optical Particulate Matter Sensors for Ambient Monitoring

Atmosphere ◽  
2020 ◽  
Vol 11 (10) ◽  
pp. 1040
Author(s):  
Mariusz Rogulski ◽  
Artur Badyda
Keyword(s):  
Particulate Matter ◽  
Relative Humidity ◽  
Low Cost ◽  
Reference Station ◽  
Correction Function ◽  
Maximum Temperature ◽  
Large Set ◽  
Campaign Evaluation ◽  
The Impact

This article presents a long-term evaluation of low-cost particulate matter (PM) sensors in a field measurements campaign. Evaluation was performed in two phases. During the first five months of the campaign, two PM sensors were simultaneously compared with the results from the reference air quality monitoring station in various atmospheric conditions—from the days with freezing cold (minimum temperature below −10 °C) and high relative humidity (up to 95%) to the days with the maximum temperature above 30 °C and low relative humidity (at the level of 25%). Based on the PM10 measurements, the correlation coefficients for both devices in relation to the reference station were determined (r = 0.91 and r = 0.94, respectively), as well as the impact of temperature and relative humidity on measurements from the low-cost sensors in relation to the reference values. The correction function was formulated based on this large set of low-cost PM10 measurements and referential values. The effectiveness of the corrective function was verified during the second measurement campaign carried out in the city of Nowy Sącz (located in southern Poland) for the same five months in the following year. The absolute values of the long-term percentage errors obtained after adjustment were reduced to a maximum of about 20%, and the average percentage errors were usually around 10%.

scholarly journals Impact of Genetic Improvements of Rice on Its Water Use and Effects of Climate Variability in Egypt

Agriculture ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 865
Author(s):  
Mohamed Mehana ◽  
Mohamed Abdelrahman ◽  
Yasmin Emadeldin ◽  
Jai S. Rohila ◽  
Raghupathy Karthikeyan
Keyword(s):  
Relative Humidity ◽  
Climate Variability ◽  
Negative Impact ◽  
Rice Production ◽  
Maximum Temperature ◽  
Rice Cultivars ◽  
Rice Productivity ◽  
Unit Productivity ◽  
The Impact

Developing and disseminating resilient rice cultivars with increased productivity is a key solution to the problem of limited natural resources such as land and water. We investigated trends in rice cultivation areas and the overall production in Egypt between 2000 and 2018. This study identified rice cultivars that showed potential for high productivity when cultivated under limited irrigation. The results indicated that there were significant annual reductions in both the rice-cultivated area (−1.7% per year) and the production (−1.9% per year) during the study period. Among the commonly cultivated varieties, Sakha101 showed the highest land unit productivity, while Sakha102 showed the highest water unit productivity. The impact of deploying new cultivars was analyzed by substitution scenarios. The results showed that substituting cultivars Giza179 and Sakha107 has the potential to increase land productivity by 15.8% and 22.6%, respectively. This could result in 0.8 million m3 in water savings compared to 2018 water consumption. Long-term impacts of climate variability on the minimum and maximum temperature, relative humidity, and average precipitation during on- and off-season for rice productivity were also analyzed using an autoregressive distributed lag (ARDL) model. The results indicated that climate variability has an overall negative impact on rice productivity. Specifically, minimum temperature and on- and off-season precipitation had major long-term impacts, while higher relative humidity had a pronounced short-term impact on rice yields. The study revealed that short-duration cultivars with higher yields provided greater net savings in irrigation resources. These analyses are critical to guide the development of strategic management plans to mitigate short- and long-term climate effects on overall rice production and for developing and deploying improved rice varieties for sustainable rice production.

scholarly journals Developing Relative Humidity and Temperature Corrections for Low-Cost Sensors Using Machine Learning

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3338
Author(s):  
Ivan Vajs ◽  
Dejan Drajic ◽  
Nenad Gligoric ◽  
Ilija Radovanovic ◽  
Ivan Popovic
Keyword(s):  
Machine Learning ◽  
Air Quality ◽  
Relative Humidity ◽  
Low Cost ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Lower Accuracy ◽  
Wide Range ◽  
The Impact ◽  
Monitoring Stations

Existing government air quality monitoring networks consist of static measurement stations, which are highly reliable and accurately measure a wide range of air pollutants, but they are very large, expensive and require significant amounts of maintenance. As a promising solution, low-cost sensors are being introduced as complementary, air quality monitoring stations. These sensors are, however, not reliable due to the lower accuracy, short life cycle and corresponding calibration issues. Recent studies have shown that low-cost sensors are affected by relative humidity and temperature. In this paper, we explore methods to additionally improve the calibration algorithms with the aim to increase the measurement accuracy considering the impact of temperature and humidity on the readings, by using machine learning. A detailed comparative analysis of linear regression, artificial neural network and random forest algorithms are presented, analyzing their performance on the measurements of CO, NO2 and PM10 particles, with promising results and an achieved R2 of 0.93–0.97, 0.82–0.94 and 0.73–0.89 dependent on the observed period of the year, respectively, for each pollutant. A comprehensive analysis and recommendations on how low-cost sensors could be used as complementary monitoring stations to the reference ones, to increase spatial and temporal measurement resolution, is provided.

Long-term field evaluation of the Plantower PMS low-cost particulate matter sensors

2019 ◽  
Vol 245 ◽  
pp. 932-940 ◽  
Author(s):  
T. Sayahi ◽  
A. Butterfield ◽  
K.E. Kelly
Keyword(s):  
Particulate Matter ◽  
Low Cost ◽  
Field Evaluation ◽  
Term Field

The impact of botfly parasitism on the health of the gracile mouse opossum (Gracilinanus agilis)

Parasitology ◽  
2019 ◽  
Vol 146 (8) ◽  
pp. 1013-1021
Author(s):  
Priscilla Lóra Zangrandi ◽  
André Faria Mendonça ◽  
Ariovaldo Pereira Cruz-Neto ◽  
Rudy Boonstra ◽  
Emerson M. Vieira
Keyword(s):  
Relative Humidity ◽  
Body Condition ◽  
Animal Health ◽  
Haemoglobin Concentration ◽  
Blood Parameters ◽  
Small Population ◽  
Maximum Temperature ◽  
Food Supplementation ◽  
Local Extinctions ◽  
The Impact

AbstractFragmented habitats generally harbour small populations that are potentially more prone to local extinctions caused by biotic factors such as parasites. We evaluated the effects of botflies (Cuterebra apicalis) on naturally fragmented populations of the gracile mouse opossum (Gracilinanus agilis). We examined how sex, food supplementation experiment, season and daily climatic variables affected body condition and haemoglobin concentration in animals that were parasitized or not by botflies. Although parasitism did not affect body condition, haemoglobin concentrations were lower in parasitized animals. Among the non-parasitized individuals, haemoglobin concentration increased with the increase of maximum temperature and the decrease of relative humidity, a climatic pattern found at the peak of the dry season. However, among parasitized animals, the opposite relationship between haemoglobin concentration and relative humidity occurred, as a consequence of parasite-induced anaemia interacting with dehydration as an additional stressor. We conclude that it is critical to assess how climate affects animal health (through blood parameters) to understand the population consequences of parasitism on the survival of individuals and hence of small population viability.

scholarly journals Including the efficacy of land ice changes in deriving climate sensitivity from paleodata

2019 ◽  
Vol 10 (2) ◽  
pp. 333-345 ◽  
Author(s):  
Lennert B. Stap ◽  
Peter Köhler ◽  
Gerrit Lohmann
Keyword(s):  
Climate Sensitivity ◽  
Radiative Forcing ◽  
Climate Models ◽  
Co2 Concentration ◽  
Global Temperature ◽  
Maximum Temperature ◽  
Radiative Forcings ◽  
The Impact ◽  
The Last Glacial

Abstract. The equilibrium climate sensitivity (ECS) of climate models is calculated as the equilibrium global mean surface air warming resulting from a simulated doubling of the atmospheric CO2 concentration. In these simulations, long-term processes in the climate system, such as land ice changes, are not incorporated. Hence, climate sensitivity derived from paleodata has to be compensated for these processes, when comparing it to the ECS of climate models. Several recent studies found that the impact these long-term processes have on global temperature cannot be quantified directly through the global radiative forcing they induce. This renders the prevailing approach of deconvoluting paleotemperatures through a partitioning based on radiative forcings inaccurate. Here, we therefore implement an efficacy factor ε[LI] that relates the impact of land ice changes on global temperature to that of CO2 changes in our calculation of climate sensitivity from paleodata. We apply our refined approach to a proxy-inferred paleoclimate dataset, using ε[LI]=0.45-0.20+0.34 based on a multi-model assemblage of simulated relative influences of land ice changes on the Last Glacial Maximum temperature anomaly. The implemented ε[LI] is smaller than unity, meaning that per unit of radiative, forcing the impact on global temperature is less strong for land ice changes than for CO2 changes. Consequently, our obtained ECS estimate of 5.8±1.3 K, where the uncertainty reflects the implemented range in ε[LI], is ∼50 % higher than when differences in efficacy are not considered.

scholarly journals Author Correction: Long-term field comparison of multiple low-cost particulate matter sensors in an outdoor urban environment

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Florentin M. J. Bulot ◽  
Steven J. Johnston ◽  
Philip J. Basford ◽  
Natasha H. C. Easton ◽  
Mihaela Apetroaie-Cristea ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Urban Environment ◽  
Low Cost ◽  
Term Field

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

scholarly journals Long-Term Performance Assessment of Low-Cost Atmospheric Sensors in the Arctic Environment

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1919 ◽  
Author(s):  
Federico Carotenuto ◽  
Lorenzo Brilli ◽  
Beniamino Gioli ◽  
Giovanni Gualtieri ◽  
Carolina Vagnoli ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Relative Humidity ◽  
Air Temperature ◽  
Meteorological Parameters ◽  
Low Cost ◽  
Absolute Error ◽  
Atmospheric Composition ◽  
The Arctic ◽  
Svalbard Archipelago ◽  
Arctic Environment

The Arctic is an important natural laboratory that is extremely sensitive to climatic changes and its monitoring is, therefore, of great importance. Due to the environmental extremes it is often hard to deploy sensors and observations are limited to a few sparse observation points limiting the spatial and temporal coverage of the Arctic measurement. Given these constraints the possibility of deploying a rugged network of low-cost sensors remains an interesting and convenient option. The present work validates for the first time a low-cost sensor array (AIRQino) for monitoring basic meteorological parameters and atmospheric composition in the Arctic (air temperature, relative humidity, particulate matter, and CO2). AIRQino was deployed for one year in the Svalbard archipelago and its outputs compared with reference sensors. Results show good agreement with the reference meteorological parameters (air temperature (T) and relative humidity (RH)) with correlation coefficients above 0.8 and small absolute errors (≈1 °C for temperature and ≈6% for RH). Particulate matter (PM) low-cost sensors show a good linearity (r2 ≈ 0.8) and small absolute errors for both PM2.5 and PM10 (≈1 µg m−3 for PM2.5 and ≈3 µg m−3 for PM10), while overall accuracy is impacted both by the unknown composition of the local aerosol, and by high humidity conditions likely generating hygroscopic effects. CO2 exhibits a satisfying agreement with r2 around 0.70 and an absolute error of ≈23 mg m−3. Overall these results, coupled with an excellent data coverage and scarce need of maintenance make the AIRQino or similar devices integrations an interesting tool for future extended sensor networks also in the Arctic environment.

scholarly journals Kitchen Area Air Quality Measurements in Northern Ghana: Evaluating the Performance of a Low-Cost Particulate Sensor within a Household Energy Study

Atmosphere ◽  
2019 ◽  
Vol 10 (7) ◽  
pp. 400 ◽  
Author(s):  
Evan R. Coffey ◽  
David Pfotenhauer ◽  
Anondo Mukherjee ◽  
Desmond Agao ◽  
Ali Moro ◽  
...  
Keyword(s):  
Air Pollution ◽  
Particulate Matter ◽  
Relative Humidity ◽  
Low Cost ◽  
Absolute Humidity ◽  
Ground Truth ◽  
Household Air Pollution ◽  
Northern Ghana ◽  
Household Energy ◽  
Health And Human Rights

Household air pollution from the combustion of solid fuels is a leading global health and human rights concern, affecting billions every day. Instrumentation to assess potential solutions to this problem faces challenges—especially related to cost. A low-cost ($159) particulate matter tool called the Household Air Pollution Exposure (HAPEx) Nano was evaluated in the field as part of the Prices, Peers, and Perceptions cookstove study in northern Ghana. Measurements of temperature, relative humidity, absolute humidity, and carbon dioxide and carbon monoxide concentrations made at 1-min temporal resolution were integrated with 1-min particulate matter less than 2.5 microns in diameter (PM2.5) measurements from the HAPEx, within 62 kitchens, across urban and rural households and four seasons totaling 71 48-h deployments. Gravimetric filter sampling was undertaken to ground-truth and evaluate the low-cost measurements. HAPEx baseline drift and relative humidity corrections were investigated and evaluated using signals from paired HAPEx, finding significant improvements. Resulting particle coefficients and integrated gravimetric PM2.5 concentrations were modeled to explore drivers of variability; urban/rural, season, kitchen characteristics, and dust (a major PM2.5 mass constituent) were significant predictors. The high correlation (R2 = 0.79) between 48-h mean HAPEx readings and gravimetric PM2.5 mass (including other covariates) indicates that the HAPEx can be a useful tool in household energy studies.

scholarly journals 60 years of UK visibility measurements: impact of meteorology and atmospheric pollutants on visibility

2017 ◽  
Vol 17 (3) ◽  
pp. 2085-2101 ◽  
Author(s):  
Ajit Singh ◽  
William J. Bloss ◽  
Francis D. Pope
Keyword(s):  
Relative Humidity ◽  
Aerosol Particle ◽  
Urban Areas ◽  
Land Use Changes ◽  
Gas Absorption ◽  
Atmospheric Pollutants ◽  
Light Extinction ◽  
The Impact ◽  
Aerosol Hygroscopicity

Abstract. Reduced visibility is an indicator of poor air quality. Moreover, degradation in visibility can be hazardous to human safety; for example, low visibility can lead to road, rail, sea and air accidents. In this paper, we explore the combined influence of atmospheric aerosol particle and gas characteristics, and meteorology, on long-term visibility. We use visibility data from eight meteorological stations, situated in the UK, which have been running since the 1950s. The site locations include urban, rural and marine environments. Most stations show a long-term trend of increasing visibility, which is indicative of reductions in air pollution, especially in urban areas. Additionally, the visibility at all sites shows a very clear dependence on relative humidity, indicating the importance of aerosol hygroscopicity on the ability of aerosol particles to scatter radiation. The dependence of visibility on other meteorological parameters, such as wind speed and wind direction, is also investigated. Most stations show long-term increases in temperature which can be ascribed to climate change, land-use changes (e.g. urban heat island effects) or a combination of both; the observed effect is greatest in urban areas. The impact of this temperature change upon local relative humidity is discussed. To explain the long-term visibility trends and their dependence on meteorological conditions, the measured data were fitted to a newly developed light-extinction model to generate predictions of historic aerosol and gas scattering and absorbing properties. In general, an excellent fit was achieved between measured and modelled visibility for all eight sites. The model incorporates parameterizations of aerosol hygroscopicity, particle concentration, particle scattering, and particle and gas absorption. This new model should be applicable and is easily transferrable to other data sets worldwide. Hence, historical visibility data can be used to assess trends in aerosol particle properties. This approach may help constrain global model simulations which attempt to generate aerosol fields for time periods when observational data are scarce or non-existent. Both the measured visibility and the modelled aerosol properties reported in this paper highlight the success of the UK's Clean Air Act, which was passed in 1956, in cleaning the atmosphere of visibility-reducing pollutants.

scholarly journals A REVIEW ON MECHANICAL PROPERTIES OF NATURAL FIBRE REINFORCED CONCRETE FOR RIGID PAVEMENTS

2021 ◽  
pp. 266-270
Author(s):  
M.Venkata Naga Prasad ◽  
Dr.J.Sridhar
Keyword(s):  
Low Cost ◽  
Natural Fibers ◽  
Natural Fibre ◽  
Cement Matrix ◽  
Rigid Pavements ◽  
Steel Bars ◽  
Coconut Coir ◽  
The Impact ◽  
Coconut Fibers

This study focuses on fiber reinforcement, specifically the use of jute and coir as a fiber reinforcing material in concrete. Natural fibers have been used to provide substantial toughness and strength in a very fragile cement matrix composite. It is necessary to make effective changes in this regard. Uses a very alkaline cement matrix to achieve durability. It is preferable to have a chemical composition that is clear. Reinforce the cement and change the surface of the fibers composite. The usage of jute fiber in this article is discussed. Concrete and the impact it has on the characteristics of the concrete it produces, for example this is an attempt to review the work that has just been completed. In the discipline, as well as to establish a foundation for future study in that case. It is critical to create low-cost building and reinforcing techniques that are suited for developing countries. If agricultural by-products like coconut coir can be used to replace steel bars as reinforcement, building costs can be reduced. Down significantly the purpose of this study is to evaluate the characteristics of coconut fibers. Species produced in India and their uses in many fields of engineering, notably civil engineering enhancing the long-term durability of concrete and mortar using engineering as a building material with the addition of coconut fibers the overall objective is to look into the possibility of utilizing domestic resources. Wastes for construction on a tiny scale a review of several researchers’ experiences utilizing is presented in this publication. The performance of coconut coir as a reinforcing component is explored in depth.

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