Found 9884 publications. Showing page 213 of 396:
Low concentrations of persistent organic pollutants (POPs) in air at Cape Verde
Ambient air is a core medium for monitoring of persistent organic pollutants (POPs) under the Stockholm Convention
and is used in studies of global transports of POPs and their atmospheric sources and source regions. Still,
data based on active air sampling remain scarce in many regions. The primary objectives of this study were to
(i) monitor concentrations of selected POPs in air outside West Africa, and (ii) to evaluate potential atmospheric
processes and source regions affecting measured concentrations. For this purpose, an active high-volume air
sampler was installed on the Cape Verde Atmospheric Observatory at Cape Verde outside the coast of West
Africa. Sampling commenced in May 2012 and 43 samples (24 h sampling) were collected until June 2013. The samples were analyzed for selected polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), hexachlorobenzene (HCB) and chlordanes. The concentrations of these POPs at Cape Verde were generally low and comparable to remote sites in the Arctic for several compounds. Seasonal trends varied between compounds and concentrations exhibited strong temperature dependence for chlordanes. Our results indicate
net volatilization fromthe Atlantic Ocean north of Cape Verde as sources of these POPs. Air mass back trajectories
demonstrated that air masses measured at Cape Verdewere generally transported fromthe Atlantic Ocean or the North African continent. Overall, the low concentrations in air at Cape Verde were likely explained by absence of major emissions in areas from which the air masses originated combined with depletion during long-range atmospheric
transport due to enhanced degradation under tropical conditions (high temperatures and concentrations of hydroxyl radicals).
Elsevier
2018
2008
Low cost sensor systems for air quality assessment. Possibilities and challenges.
Air quality is enjoying popular interest in the last years, with numerous projects initiated by civil society or individuals that aim to assess the quality of air locally, aided by new, low-cost monitoring technologies that can be used by “everyone”. Such initiatives are very welcome, but in this highly technical and (in the western world) thoroughly regulated area, the professional community seems to struggle with communication with these initiatives, trying to reconcile the often highly technical aspects with the social ones. The technical issues include subjects such as monitoring techniques, air quality assessment methods, or quality control of measurements, and disciplines such as metrology, atmospheric science or informatics.
In this report, we would like to provide the reader with a practically oriented overview indicating the position of these new technologies in the ecosystem of air quality monitoring and measurement activities. Sensing techniques are rapidly evolving. This ‘ever’ improving capability implies among other, that there is currently no traceable method of evaluation of data quality. Despite the efforts of numerous groups, including within the European standardization system, a certification system will take some time to develop. This has important implications for example, when comparing measurements taken in time, by different devices (or different versions of the same sensor system device). Fitness for purpose – why are we measuring or monitoring and how do we intend to use the information we obtain – should always be the main criterion for the technological choice.
The report starts with an overview of elements of a monitoring system and proceed to describe the new technologies. Then, we give examples of how low-cost sensor technologies are being used by citizens. These examples are followed by reflections upon providing actionable information. Having learned from practical applications of sensor systems, we also discuss how the data from citizen activities can be used to develop new information, and provide some reflections on developing sensor systems monitoring on a larger scale.
We feel that the new technologies, while a disruptive change, provide many exciting opportunities, and we hope that this report will contribute to promote their use alongside with other assessment methods. We believe that increased understanding of technical issues we discuss will ultimately lead to better communication on air quality, and in its consequence, will enable further improvements in this domain.
ETC/ACM
2019
2015
Low-Cost Particulate Matter Sensors for Monitoring Residential Wood Burning
Conventional monitoring systems for air quality, such as reference stations, provide reliable pollution data in urban settings but only at relatively low spatial density. This study explores the potential of low-cost sensor systems (LCSs) deployed at homes of residents to enhance the monitoring of urban air pollution caused by residential wood burning. We established a network of 28 Airly (Airly-GSM-1, SP. Z o.o., Poland) LCSs in Kristiansand, Norway, over two winters (2021–2022). To assess performance, a gravimetric Kleinfiltergerät measured the fine particle mass concentration (PM2.5) in the garden of one participant’s house for 4 weeks. Results showed a sensor-to-reference correlation equal to 0.86 for raw PM2.5 measurements at daily resolution (bias/RMSE: 9.45/11.65 μg m–3). High-resolution air quality maps at a 100 m resolution were produced by combining the output of an air quality model (uEMEP) using data assimilation techniques with the network data that were corrected and calibrated by using a proposed five-step network data processing scheme. Leave-one-out cross-validation demonstrated that data assimilation reduced the model’s RMSE, MAE, and bias by 44–56, 38–48, and 41–52%, respectively.
2023
2013
2017
Poland continues to rely heavily on coal and fossil fuels for household heating, despite efforts to reduce Particulate Matter (PM) levels. The availability of reliable air quality data is essential for policymakers, environmentalists, and citizens to advocate for cleaner energy sources. However, Polish air quality monitoring is challenging due to the limited coverage of reference stations and outdated equipment. Here, we report the results of a study on the spatio-temporal variability of Particulate Matter in Legionowo, Poland, using residents’ network of low-cost sensors. Along with identifying the hotspots of household-emitted PM, (1) we propose a data quality assurance scheme for PM sensors, (2) suggest an approach for estimating the Relative Humidity-induced uncertainty in the sensors without co-location with reference instruments, and (3) develop an interpretable Machine Learning (ML) model, a Generalized Additive Model (RMSE = 6.16 μg m−3, and R2 = 0.88), for unveiling the underlying relations between PM2.5 levels and other environmental parameters. The results in Legionowo suggest that as air temperature and wind speed increase by 1 °C and 1 km h−1, PM2.5 would respectively decrease by 0.26 μg m−3 and 0.14 μg m−3 while PM2.5 increases by 0.03 μg m−3 as RH increases by 1%.
Elsevier
2023
The increase of the commercial availability of low-cost sensor technology to monitor atmospheric composition is contributing to the rapid adoption of such technology by both public authorities and self-organized initiatives (e.g. grass root movements, citizen science, etc.). Low-cost sensors (LCS) can provide real time measurements, in principle at lower cost than traditional monitoring reference stations, allowing higher spatial coverage than the current reference methods. However, data quality from LCS is lower than the one provided by reference methods. Also, the total cost of deploying a dense sensor network needs to consider the costs associated not only to the sensor platforms but also the costs associated for instance with deployment, maintenance and data transmission.
This report aims to give an overview of the current status of LCS technology in relation to commercialization, measuring capabilities and data quality, with especial emphasis on the challenges associated to the use of this novel technology, and the opportunities they open when correctly used.
NILU
2021
2011
Low-Processing Data Enrichment and Calibration for PM2.5 Low-Cost Sensors
Particulate matter (PM) in air has been proven to be hazardous to human health. Here we focused on analysis of PM data we obtained from the same campaign which was presented in our previous study. Multivariate linear and random forest models were used for the calibration and analysis. In our linear regression model the inputs were PM, temperature and humidity measured with low-cost sensors, and the target was the reference PM measurements obtained from SEPA in the same timeframe.
2023
2022
2016