Air Quality Measurements in Kitchener, Ontario, Canada Using Multisensor Mini Monitoring Stations

The Region of Waterloo is the third fastest growing region in Southern Ontario in Canada with a population of 619,000 as of 2019. However, only one air quality monitoring station, located in a city park in Kitchener, Ontario, is currently being used to assess the air quality of the region. In September 2020, a network of AQMesh Multisensor Mini Monitoring Stations (pods) were installed near elementary schools in Kitchener located near different types of emission source. Data analysis using a custom-made long-distance scaling software showed that the levels of nitrogen oxides (NO and NO2), ground level ozone (O3), and fine particulate matter (PM2.5) were traffic related. These pollutants were used to calculate the Air Quality Health Index-Plus (AQHI+) at each location, highlighting the inability of the provincial air quality monitoring station to detect hotspot areas in the city. The case study presented here quantified the impact of the 2021 summer wildfires on the local air quality at a high time resolution (15-min). The findings in this article show that these multisensor pods are a viable alternative to expensive research-grade equipment. The results highlight the need for networks of local scale air quality measurements, particularly in fast-growing cities in Canada.

DARCLOS: a cloud shadow detection algorithm for TROPOMI

Cloud shadows are observed by the TROPOMI satellite instrument as a result of its high spatial resolution as compared to its predecessor instruments. These shadows contaminate TROPOMI's air quality measurements, because shadows are generally not taken into account in the models that are used for aerosol and trace gas retrievals. If the shadows are to be removed from the data, or if shadows are to be studied, an automatic detection of the shadow pixels is needed. We present the Detection AlgoRithm for CLOud Shadows (DARCLOS) for TROPOMI, which is the first cloud shadow detection algorithm for a spaceborne spectrometer. DARCLOS raises potential cloud shadow flags (PCSFs), and actual cloud shadow flags (ACSFs). The PCSFs indicate the TROPOMI ground pixels that are potentially affected by cloud shadows based on a geometric consideration with safety margins. The ACSFs are a refinement of the PCSFs using spectral reflectance information of the PCSF pixels, and identify the TROPOMI ground pixels that are confidently affected by cloud shadows. We validate DARCLOS with true color images made by the VIIRS instrument on board of Suomi NPP orbiting in close constellation with TROPOMI on board of Sentinel 5-P. We conclude that the PCSF can be used to exclude cloud shadow contamination from TROPOMI data, while the ACSF can be used to select pixels for the scientific analysis of cloud shadow effects.

Comparability of family planning quality of care measurement tools in low-and-middle income country settings: a systematic review

Background In low-and-middle income countries (LMICs), accurate measures of the elements of quality care provided by a health worker through family planning services (also known as process quality) are required to ensure family’s contraceptives needs are being met. There are many tools used to assess family planning process quality of care (QoC) but no one standardized method. Those measuring QoC in LMICs should select an appropriate tool based the program context and financial/logistical parameters, but they require data on how well each tool measures routine clinical care. We aim to synthesize the literature on validity/comparability of family planning process QoC measurement tools through a quantitative systematic review with no meta-analysis. Methods We searched six literature databases for studies that compared quality measurements from different tools using quantitative statistics such as sensitivity/specificity, kappa statistic or absolute difference. We extracted the comparative measure along with other relevant study information, organized by quality indicator domain (e.g. counseling and privacy), and then classified the measure by low, medium, and high agreement. Results We screened 8172 articles and identified eight for analysis. Studies comparing quality measurements from simulated clients, direct observation, client exit interview, provider knowledge quizzes, and medical record review were included. These eight studies were heterogenous in their methods and the measurements compared. There was insufficient data to estimate overall summary measures of validity for the tools. Client exit interviews compared to direct observation or simulated client protocols had the most data and they were a poor proxy of the actual quality care received for many measurements. Conclusion To measure QoC consistently and accurately in LMICs, standardized tools and measures are needed along with an established method of combining them for a comprehensive picture of quality care. Data on how different tools proxy quality client care will inform these guidelines. Despite the small number of studies found during the review, we described important differences on how tools measure quality of care.

PSV-11 The effects of pelleting and extrusion on nutrient composition and protein quality measurements in a variety Canadian pulses

Alternative forms of protein are an important focus in nutrition. This study sought to compare the effects of pelleting and extrusion on nutrient composition and protein quality measurements of Canadian pulses. Pulses used for the study included: 2 pea variety (Amarillo and dunn), lentils, chickpeas, and faba bean. Ingredients were ground through a 10/64” or a 2/64” screen to create a coarse and fine ground product, respectively. Both coarse and fine ground ingredients were pelleted at 60–65, 70–75, and 80–85 C0. Fine ground ingredients were extruded at three different temperatures (110, 130, 150 C0) and two moisture levels (18 and 22%). Samples were collected for all runs at the beginning, middle, and end of each run for both pelleted and extruded samples. Samples were analyzed for proximate analysis, amino acids including lysinoalanine, total and damaged starch, and total dietary fibre (including insoluble and soluble). Data were analyzed using a mixed model via proc glimmix in SAS, where ingredient, process, grind, temperature, and extrusion moisture were treated as fixed effects with different interactions selected based on model investigated. Crude protein content of whole pulses was highest in faba bean and lowest in the Amarillo pea, with faba bean protein content significantly higher than all other pulses, and lentil protein content significantly higher than Amarillo peas (P < 0.05). All pelleting temperatures, nested within grind, significantly increased crude protein content of all pulses compared to whole pulses (P < 0.05). All extrusion moistures significantly increased crude protein content of all pulses compared to whole pulses (P < 0.05) and moisture/temperature interactions were significantly higher for all pulses compared to whole pulses (P < 0.05). Amino acid comparisons produced similar significant results. This suggests that pelleting and extrusion processing can have a positive impact on protein content of pulses and protein quality measurements in pulses.

Polymethyl Methacrylate Quality Modeling with Missing Data Using Subspace Based Model Identification

This paper addresses the problem of quality modeling in polymethyl methacrylate (PMMA) production. The key challenge is handling the large amounts of missing quality measurements in each batch due to the time and cost sensitive nature of the measurements. To this end, a missing data subspace algorithm that adapts nonlinear iterative partial least squares (NIPALS) algorithms from both partial least squares (PLS) and principal component analysis (PCA) is utilized to build a data driven dynamic model. The use of NIPALS algorithms allows for the correlation structure of the input–output data to minimize the impact of the large amounts of missing quality measurements. These techniques are utilized in a simulated case study to successfully model the PMMA process in particular, and demonstrate the efficacy of the algorithm to handle the quality prediction problem in general.

PENGARUH RENTANG WAKTU PENINGKATAN SALINITAS TERHADAP KELULUSHIDUPAN DAN PERTUMBUHAN LARVA IKAN BAUNG (H. nemurus)

This research is expected to be useful especially for fish farmers as additional information in raising baung fish. The method used was an experimental method using a Completely Randomized Design (CRD) with 4 treatments and 3 replications namely: P1 = 5 ‰ per 3 days 7 ‰ per 3 days, 9 ‰ per 3 days, P2 = 5 ‰ per 5 days 7 ‰ per 5 days 9 ‰ per 5 days, P3 = 5 ‰ per 7 days 7 ‰ per 7 days 9 ‰ per 7 days, P4 = 5 ‰ per 9 days 7 ‰ per 9 days 9 ‰ per 9 days. The baung fish used for the study was obtained from spawning at the Fish Seed Center (BBI) of the Faculty of Agriculture, Riau Islamic University with a weight of 0.14 gr of baung fish/tail and 1.6 cm in length/tail. The container used is a jar a size of 10 liters. From the results of the study obtained the best absolute weight growth and absolute length of the treatment (P4) with a weight of 4.35 gr and a length of 1.84 cm, followed by treatment (P2) with a weight of 3.96 gr and P3 a length of 1.82 cm, (P3 ) weighing 3, 75 gr and P2, 1.73 cm long, and the lowest in treatment (P1) with a weight of 2.64 grams and a length of 1.28 cm. The daily weight growth rate in the treatment group (P2) was 17.31%, (P2) 15.17%, (P4) 13.18%, and the lowest (P3) was 12.60%. The best survival rate for treatment (P4) was 72.00%, followed by treatment (P3) at 54.67%, and the lowest for treatment (P1) was 6, 67%. The results of water quality measurements in this study were temperature 28-300C, pH 6-7, dissolved oxygen 0.4 ppm, ammonia 0.05 ppm. Based on the observations of water quality during the study was within the range of tolerance for the growth and life of baung fish.

Evaluation of Seaport Service Quality in Tanzania: From the Dar es Salaam Seaport Perspective

Many countries rely heavily on seaports to promote their well-being and economy. Unreliability of seaport services can considerably impact cargo owners, seaport customers and shipping lines resulting to their dissatisfaction. This study aimed to evaluate service quality of Tanzanian seaports considering Dar es Salaam seaport as a study area. The study discovered the negative gap on the service quality after evaluating seaport user’s perceptions and expectations of delivered seaport services, meanwhile the service quality of Dar es Salaam seaport is poor. Opinions of seaport user’s concerning seaport service quality were computed based on the SERVQUAL model which developed by Parasuraman by considering the essential measurements of Tangibility, Empathy, Reliability, Assurance and Responsiveness. Senior administrators and managers employed in numerous shipping lines in Tanzania were interviewed to check the model validity, then 314 members of Tanzania shipping and logistics associations were engaged in a study survey. Partial Least Squares Structural Equation Modelling (PLS-SEM) was applied to validate the seaport service quality measurements and to observe their association with satisfaction of seaport customers using Amos Graphics software version 26. It found that seaport service quality is a five-measure construct; responsiveness was significantly influence customer satisfaction while empathy and assurance could insignificantly influence customer satisfaction. Reliability was found significantly to cause customer dissatisfaction and tangibility was insignificantly to cause customer dissatisfaction. Academically, this research donates to management practice as seaport administrators, managers and executives can utilize the seaport service quality measurements to evaluate their customer’s satisfaction and defending for seaport service quality investments as a relational marketing strategy.