Analysis of the variability of airborne particulate matter with prevailing meteorological conditions across a semi-urban environment using a network of low-cost air quality sensors.

The concentrations of fine and coarse fractions of airborne particulate matter (PM) and meteorological variables (wind speed, wind direction, temperature and relative humidity) were measured at six selected locations in Ile Ife, a prominent university town in Nigeria using a network of low-cost air quality (AQ) sensor units. The objective of the deployment was to collate baseline air quality data and assess the impact of prevailing meteorological conditions on PM concentrations in selected residential communities downwind of an iron smelting facility. The raw data obtained from OPC-N2 of the AQ sensor units was corrected using the RH correction factor developed based k-Kohler theory. This PM (corrected) fast time resolution data (20 s) from the AQ sensor units were used to create daily averages. The overall mean mass concentrations for PM2.5 and PM10 were 213.3, 44.1, 23.8, 27.7, 20.2 and 41.5 μg/m3 and; 439.9, 107.1, 55.0, 72.4, 45.5 and 112.0 μg/m3 for Fasina (Iron-Steel Smelting Factory, ISSF), Modomo, Eleweran, Fire Service, O.A.U. staff quarters and Obafemi Awolowo University Teaching and Research Farm (OAUTRF), respectively. PM concentration and wind speed showed a negative exponential distribution curve with the lowest exponential fit coefficient of determination (R2) values of 0.08 for PM2.5 and 0.03 for PM10 during nighttime periods at Eleweran and Fire service sites, respectively. The relationship between PM concentration and temperature gave a decay curve indicating that higher PM concentrations were observed at lower temperatures. The exponential distribution curve for the relationship between PM concentration and relative humidity (RH) showed that PM concentrations do not vary for RH 80 % for both day and nighttime. The performances of the MLR model were slightly poor and as such not too reliable for predicting the concentration but useful for improving predictive model accuracy when other variables contributing to the variability of PM is considered. The study concluded that the anthropogenic and industrial activities at the smelting factory contribute significantly to the elevated PM mass concentration measured at the study locations

Random number datasets generated from statistical analysis of randomly sampled GSM recharge cards

In this article, a random number of datasets was generated from random samples of used GSM (Global Systems for Mobile Communications) recharge cards. Statistical analyses were performed to refine the raw data to random number datasets arranged in table. A detailed description of the method and relevant tests of randomness were also discussed

Exploration of UK Lotto results classified into two periods

United Kingdom Lotto results are obtained from urn containing some numbers of which six winning numbers and one bonus are drawn at each draw event. There is always a need from prospective players for analysis that can aid them in increasing their chances of winning. In this paper, historical data of the United Kingdom Lotto results were grouped into two periods (19/11/1994–7/10/2015 and 10/10/2015–10/5/2017). The classification was as a result of increase of the lotto numbers from 49 to 59. Exploratory statistical and mathematical tools were used to obtain new patterns of winning numbers. The data can provide insights on the random nature and distribution of the winning numbers and help prospective players in increasing their chances of winning the lotto

Datasets on the statistical properties of the first 3000 squared positive integers

The data in this article are as a result of a quest to uncover alter-native research routes of deepening researchers’understanding ofintegers apart from the traditional number theory approach.Hence, the article contains the statistical properties of the digitssum of thefirst 3000 squared positive integers. The data describesthe various statistical tools applied to reveal different statisticaland random nature of the digits sum of thefirst 3000 squaredpositive integers. Digits sum here implies the sum of all the digitsthat make up the individual intege

Datasets on the statistical properties of the first 3000 squared positive integers

The data in this article are as a result of a quest to uncover alternative research routes of deepening researchersâ understanding of integers apart from the traditional number theory approach. Hence, the article contains the statistical properties of the digits sum of the first 3000 squared positive integers. The data describes the various statistical tools applied to reveal different statistical and random nature of the digits sum of the first 3000 squared positive integers. Digits sum here implies the sum of all the digits that make up the individual integer. Keywords: Positive integer, Digits sum, Harrell-Davis quantiles, Boxplots, Bootstrap, M-estimators, Confidence intervals, Curve estimation, Model fi

Datasets on the statistical and algebraic properties of primitive Pythagorean triples

The data in this article was obtained from the algebraic and statistical analysis of the first 331 primitive Pythagorean triples. The ordered sample is a subset of the larger Pythagorean triples. A primitive Pythagorean triple consists of three integers a, b and c such that; a2+b2=c2. A primitive Pythagorean triple is one which the greatest common divisor (gcd), that is; gcd(a,b,c)=1 or a, b and c are coprime, and pairwise coprime. The dataset describe the various algebraic and statistical manipulations of the integers a, b and c that constitute the primitive Pythagorean triples. The correlation between the integers at each analysis was included. The data analysis of the non-normal nature of the integers was also included in this article. The data is open to criticism, adaptation and detailed extended analysis

Analysis of dataset on editorial board composition of Dove Medical Press by continent

This article presents the frequency of distribution of editorial members of Dove Medical press, across the world based on their official stated affiliations. Uneven distributions across the six continents were observed and this was confirmed by the Chi-square test of goodness of fit. Further research can focus on data on the gender composition, distribution of the affiliations of the first or corresponding authors of the respective journals, citation and editorial board composition based on the abstraction and indexation of the journals. Keywords: Dove Medical Press, Bibliometrics, Data analysis, Random, Smart campus, Ranking analytics, Statistic

Contamination and Source Identification of the Elemental Contents of Soil Samples from Municipal and Medical Waste Dumpsites in Ile-Ife, Nigeria

Contamination in soil samples collected from municipal and medical waste sites was assessed by employing four indices: contamination factor (Cf ), degree of contamination (Cdeg), pollution load index (PLI), and index of geoaccumulation (Igeo).  The sources of soil contaminants were identified by using Positive Matrix Factorization (PMF). Iron had the highest average concentrations of 46.47 ± 14.03 and 39.42 ± 2.54 µg/g in the municipal and medical waste dumpsites. Cf values were above 6 for both dumpsites, classifying the dumpsite soil as very high contamination with respect to Cr, Fe, Ni, Cu, Zn, As, Cd, and Pb. The overall Cdeg and PLI values are 176.9 and 170.4 and > 5 for both dumpsite implying very high degrees of contamination and progressive deterioration, respectively. The average Igeo values for Zn, Cd, and Pb of the two dumpsites were >3, indicating that the soil samples at both study areas were classified as highly to moderately polluted. The three identified sources resolved by PMF and their respective percentage contributions were crustal (32 %), scrap metals wastes (40 %), and electronic wastes (28 %)

Spatiotemporal distribution of pollutants and impact of local meteorology on source influence on pollutants' level in a traffic air-shed in Lagos megacity, Nigeria.

Pollution from vehicular emissions is a major cause of poor air quality observed in many urban and semi-urban towns and cities. As such, this study was conducted to assess air quality and the spatiotemporal distribution of vehicular and traffic-related pollutants in several air sheds of Lagos megacity, the economic nerve centre of Nigeria. A setup of low-cost air quality sensors comprising five (5) units was deployed between November 2018 and February 2019 within traffic corridors in the heart of the city. Diurnal variation of pollutants indicated that carbon dioxide (CO2) peaked during the early hours of the day, total oxide (Ox = NO2+O3) peaked at mid-day while carbon monoxide (CO) had two distinct peaks which correspond to morning and evening rush hours. Nitrogen dioxide (NO2) concentration peaked during evening hours. Average concentrations are NO2 (97.1 ± 9.7) ppb, Ox (78.6 ± 27.2) ppb, CO2 (450.1 ± 31.2) ppm, and CO (2285.63 ± 743.7) ppb. Average concentrations of pollutants were above thresholds set by the World Health Organization (WHO) except for NO2 which was within the range permissible limits. The implication of this is that the atmosphere is polluted due to elevated concentrations of airborne pollutants, an indication which is of both health and environmental concern. The air quality index (AQI) indicates that the quality of ambient air varies from good to very unhealthy for Ox, and unhealthy to very unhealthy for CO, while AQI for PM2.5 and PM10 showed hazardous at all the sampling locations except at UNILAG where it is unhealthy for the sensitive group. For all of the sampling sites, conditional bivariate probability function (CBPF) plots show a significant agreement with the location of known pollution sources