Low cost air quality sensors "PurpleAir" calibration and inter-calibration dataset in the context of Beirut, Lebanon.

The PurpleAir PA-II-SD is a low-cost particulate matter (PM2.5 and PM10) sensor that is currently available on the market. It is one of many such low-cost and commercially available particulate matter sensors which are being adopted by individuals and researchers worldwide. With growing use of these sensors, there is an interest in better understanding the performance and characteristics of these devices. Data was collected from twelve of these low-cost PurpleAir PA-II-SD sensors and two high fidelity Met One E-BAM PLUS instruments installed at a single location, on the campus of the American University of Beirut, in Beirut, Lebanon over a period of time from June 28, 2020 to September 30, 2020. The data was collected with the aim of assessing inter-sensor variability for the PurpleAir sensors and the sensor accuracy of the PurpleAir when compared to a high fidelity Met One E-BAM PLUS instrument.

Updated national emission inventory and comparison with the Emissions Database for Global Atmospheric Research (EDGAR): case of Lebanon.

Physically based computational modeling is an effective tool for estimating and predicting the spatial distribution of pollutant concentrations in complex environments. A detailed and up-to-date emission inventory is one of the most important components of atmospheric modeling and a prerequisite for achieving high model performance. Lebanon lacks an accurate inventory of anthropogenic emission fluxes. In the absence of a clear emission standard and standardized activity datasets in Lebanon, this work serves to fill this gap by presenting the first national effort to develop a national emission inventory by exhaustively quantifying detailed multisector, multi-species pollutant emissions in Lebanon for atmospheric pollutants that are internationally monitored and regulated as relevant to air quality. Following the classification of the Emissions Database for Global Atmospheric Research (EDGAR), we present the methodology followed for each subsector based on its characteristics and types of fuels consumed. The estimated emissions encompass gaseous species (CO, NOx, SO2), and particulate matter (PM2.5 and PM10). We compare totals per sector obtained from the newly developed national inventory with the international EDGAR inventory and previously published emission inventories for the country for base year 2010 presenting current discrepancies and analyzing their causes. The observed discrepancies highlight the fact that emission inventories, especially for data-scarce settings, are highly sensitive to the activity data and their underlying assumptions, and to the methodology used to estimate the emissions.

Longitudinal study on the effect of surgical weight loss on beat-to-beat blood pressure variability in patients undergoing bariatric surgery: a study protocol.

INTRODUCTION: Alterations in linear and non-linear parameters of beat-to-beat blood pressure variability (BPV) have been shown to predict disease prognosis and distinguish between risk categories in various pathological conditions, independently of average blood pressure levels. Obesity places subjects at elevated risk of vascular diseases, including hypertension, resulting in serious cardiac, respiratory and cerebral events. However, little is known about the status of vascular dynamics in obese and morbidly obese adults. METHODS AND ANALYSIS: In this present quasi-experimental longitudinal study, changes in beat-to-beat BPV, using continuous, non-invasive blood pressure monitoring, in obese subjects undergoing bariatric surgery are characterised. The capacity of linear and non-linear measures of BPV to detect differences between hypertensive, prehypertensive and normotensive obese subjects prebariatric and postbariatric surgery are tested. Additionally, potential correlations between beat-to-beat BPV and age, body mass index, gender and comorbidities will be investigated. In parallel, the impact of the unsteady fluctuations of beat-to-beat blood pressure on the dynamic stresses imparted by blood flow on blood vessel walls will be explored. We expect to find altered BPV profiles in hypertensive and prehypertensive subjects as compared with normotensive subjects. We also expect to see differential normalisation in BPV profiles between hypertensive, prehypertensive and normotensive subjects over time. ETHICS AND DISSEMINATION: The study has been approved by the Institutional Review Board at the American University of Beirut (IRB ID: BIO-2018-0040). Study results will be made available to the public through publications in peer-reviewed journals and conference papers and/or presentations.

Bayesian identification of oil spill source parameters from image contours.

Oil spills at sea pose a serious threat to coastal environments. Identifying oil pollution sources could help to investigate unreported spills, and satellite imagery can be an effective tool for this purpose. We present a Bayesian approach to estimate the source parameters of a spill from contours of oil slicks detected by remotely sensed images. Five parameters of interest are estimated: the 2D coordinates of the source of release, the time and duration of the spill, and the quantity of oil released. Two synthetic experiments of a spill released from a fixed point source are investigated, where a contour is fully observed in the first case, while two contours are partially observed at two different times in the second. In both experiments, the proposed method is able to provide good estimates of the parameters along with a level of confidence reflected by the uncertainties within.

Transdisciplinary interventions for environmental sustainability.

This paper presents a case study of a transdisciplinary research based on an ex-post assessment of the environmental and socio-behavioral contexts of solid waste management in Lebanese peri-urban communities. Lessons learned are compiled into the Transdisciplinary Interventions for Environmental Sustainability conceptual framework. The approach starts with building a team of researchers and non-academic partners, continues with co-creating solution-oriented knowledge, and ends by integrating and applying the produced knowledge. The co-created knowledge includes the environmental and socio-behavioral ex-post assessment's results. The former reveals low air pollution levels, evidence of waste-related water contamination, and higher self-reported frequencies of ill-health symptoms and diseases closer to the landfill. The latter indicates that the community's perception about waste production differs from the real accounting of generated waste. Nine lessons are identified: (1) inherent common interest between the researchers and the community, (2) flexible interdisciplinary research team, (3) representative citizen committee, (4) contextually-informed outreach coordinator, (5) iterative research process accounting for the shifting socio-political context, (6) common expectations of the research process, (7) boundary objects leading to spin-off activities in the same setting, (8) effective communication strategy, and (9) ex-post assessment of subsequent societal and scientific impacts. The non-phased framework links all nine pointers in a logical order to ease scalability. The study answers a global need for a unified, clear, broadly adopted framework for transdisciplinarity and a deeper understanding of factors ensuring full-circle knowledge co-creation in waste-related contexts in the global South. The study offers managerial and research implications and suggests avenues for further research.

PM10 Plume dispersion data of the Zouk power plant in Lebanon.

Ambient air pollution is a major risk to the human health and to the environment. The data presented quantifies the (PM10) contribution of the Zouk Mikael power plant to the ambient air pollution in Lebanon for the year 2014. The data is the outcome of a computer simulation using The Air Pollution Model (TAPM), taking into account the emission source data, the spatio-temporal meteorological conditions, the terrain height, and the land cover characteristics. The data set presents the annual, seasonal and monthly averages of the spatial distribution of the ground-level particulate (PM10) concentrations in the ambient air. The data set also includes spatial distribution of the maximum concentrations, which revealed two zones of elevated concentrations. Monthly averages and maximum concentrations in these two zones are also reported. Analysis of the data can provide information on the health risk the residents in the affected areas are subjected to. The data can also provide insight on the impact of the meteorological conditions (temperature and velocity) and the topography on pollutant dispersion in regions bounded by the sea and by a mountain range.