Use of Fourier Series in X-ray Diffraction (XRD) Analysis and Fourier-Transform Infrared Spectroscopy (FTIR) for Estimation of Crystallinity in Cellulose from Different Sources.

Cellulose crystallinity can be described according to the crystal size and the crystallinity index (CI). In this research, using Fourier-transform infrared spectroscopy (FTIR) and X-ray diffraction (XRD) methods, we studied the crystallinity of three different types of cellulose: banana rachis (BR), commercial cellulose (CS), and bacterial cellulose (BC). For each type of cellulose, we analyzed three different crystallization grades. These variations were obtained using three milling conditions: 6.5 h, 10 min, and unmilled (films). We developed a code in MATLAB software to perform deconvolution of the XRD data to estimate CI and full width at half-maximum (FWHM). For deconvolution, crystalline peaks were represented with Voigt functions, and a Fourier series fitted to the amorphous profile was used as the amorphous contribution, which allowed the contribution of the amorphous profile to be more effectively modeled. Comparisons based on the FTIR spectra and XRD results showed there were no compositional differences between the amorphous samples. However, changes associated with crystallinity were observed when the milling time was 10 min. The obtained CI (%) values show agreement with values reported in the literature and confirm the effectiveness of the method used in this work in predicting the crystallization aspects of cellulose samples.

Impact of the COVID-19 Lockdown on Air Quality and Resulting Public Health Benefits in the Mexico City Metropolitan Area.

Meteorology and long-term trends in air pollutant concentrations may obscure the results from short-term policies implemented to improve air quality. This study presents changes in CO, NO2, O3, SO2, PM10, and PM2.5 based on their anomalies during the COVID-19 partial (Phase 2) and total (Phase 3) lockdowns in Mexico City (MCMA). To minimise the impact of the air pollutant long-term trends, pollutant anomalies were calculated using as baseline truncated Fourier series, fitted with data from 2016 to 2019, and then compared with those from the lockdown. Additionally, days with stagnant conditions and heavy rain were excluded to reduce the impact of extreme weather changes. Satellite observations for NO2 and CO were used to contrast the ground-based derived results. During the lockdown Phase 2, only NO2 exhibited significant decreases (p < 0.05) of between 10 and 23% due to reductions in motor vehicle emissions. By contrast, O3 increased (p < 0.05) between 16 and 40% at the same sites where NO2 decreased. During Phase 3, significant decreases (p < 0.05) were observed for NO2 (43%), PM10 (20%), and PM2.5 (32%) in response to the total lockdown. Although O3 concentrations were lower in Phase 3 than during Phase 2, those did not decrease (p < 0.05) from the baseline at any site despite the total lockdown. SO2 decreased only during Phase 3 in a near-road environment. Satellite observations confirmed that NO2 decreased and CO stabilised during the total lockdown. Air pollutant changes during the lockdown could be overestimated between 2 and 10-fold without accounting for the influences of meteorology and long-term trends in pollutant concentrations. Air quality improved significantly during the lockdown driven by reduced NO2 and PM2.5 emissions despite increases in O3, resulting in health benefits for the MCMA population. A health assessment conducted suggested that around 588 deaths related to air pollution exposure were averted during the lockdown. Our results show that to reduce O3 within the MCMA, policies must focus on reducing VOCs emissions from non-mobile sources. The measures implemented during the COVID-19 lockdowns provide valuable information to reduce air pollution through a range of abatement strategies for emissions other than from motor vehicles.

Fitting of experimental data using a fractional Kalman-like observer.

In this paper, a fractional order Kalman filter (FOKF) is presented, this is based on a system expressed by fractional differential equations according to the Riemann-Liouville definition. In order to get the best fitting of the FOKF, the cuckoo search optimization algorithm (CS) was used. The purpose of using the CS algorithm is to optimize the order of the observer, the fractional Riccati equation and the FOKF tuning parameters. The Grünwald-Letnikov approximation was used to compute the numerical solution of the FOKF. To show the effectiveness of the proposed FOKF, four examples are presented, the brain activity, the cutaneous potential recordings of a pregnant woman, the earthquake acceleration, and the Chua's circuit response.

Utilização da análise de FOURIER no estudo de variáveis micrometeorológicas de uma floresta de transição do norte de Mato Grosso / Use of FOURIER analysis for studying micrometeorological variables of a northern Mato Grosso transition forest

Este trabalho foi realizado utilizando dados coletados em uma Floresta de Transição, em uma área pertencente à Fazenda Maracaí no Noroeste de Sinop, MT, com dados micrometeorológicos obtidos com o sistema de correlação de vórtices turbulentos (Eddy Covarience) instalado numa torre de 40 metros. Teve como objetivo principal estudar as potencialidades da análise de Fourier aplicada a dados de fluxo de Calor Latente (LE), Calor Sensível (H) e Temperatura (T). Para os cálculos foram feitas médias de 3 em 3 horas para cada mês, ao longo do período de 1999 a 2005, para as variáveis estudadas. Os períodos dominantes encontrados foram de 24; 12; 4 e 3,4 horas. Os dois primeiros são atribuíveis ao movimento de rotação da Terra, ou seja, à periodicidade dia/noite. Quanto aos dois períodos menores, há indícios que estão relacionados com a dinâmica de abertura dos estômatos. Assim sendo, os resultados deste trabalho indicam que os fatores que influenciam predominantemente as variáveis microclimatológicas durante o dia (freqüências entre 10-5 a 10-4 Hz) são a radiação solar e a dinâmica de abertura dos estômatos, um resultado que destaca as potencialidades da aplicação do método de Fourier no estudo da dinâmica de microclimas em ecossistemas.

In this work, we employed data collected in a transition forest, on the Maracaí farm, northwest of Sinop, MT, Brazil. The data was obtained by the eddy covariance method, using equipment installed on a 42m high tower. Its main purpose was to study the potentialities of Fourier analysis applied to data of latent (H) and sensible (Le) heat flux and the air temperature (T). We investigated the main frequencies presented by the data, and obtained mean values for the variables corresponding to every 3 hours, between 1999 and 2005. The main periods obtained with the Fourier method were 24; 12; 4 and 3.4 hours. The first two are attributed to the solar radiation and to the Earth rotation. The last two periods, as indicated by the data, are related to stomata dynamics. In this way, the results indicate that the main factors that predominantly influence the microclimatological variables during the day (frequencies between 10-5 a 10-4 Hz), were the solar radiation and the stomata dynamics. These results reinforce the importance of employing the Fourier method in studying microclimatic dynamics of ecosystems.

Utilização da análise de FOURIER no estudo de variáveis micrometeorológicas de uma floresta de transição do norte de Mato Grosso

In this work, we employed data collected in a transition forest, on the Maracaí farm, northwest of Sinop, MT, Brazil. The data was obtained by the eddy covariance method, using equipment installed on a 42m high tower. Its main purpose was to study the potentialities of Fourier analysis applied to data of latent (H) and sensible (Le) heat flux and the air temperature (T). We investigated the main frequencies presented by the data, and obtained mean values for the variables corresponding to every 3 hours, between 1999 and 2005. The main periods obtained with the Fourier method were 24; 12; 4 and 3.4 hours. The first two are attributed to the solar radiation and to the Earth rotation. The last two periods, as indicated by the data, are related to stomata dynamics. In this way, the results indicate that the main factors that predominantly influence the microclimatological variables during the day (frequencies between 10-5 a 10-4 Hz), were the solar radiation and the stomata dynamics. These results reinforce the importance of employing the Fourier method in studying microclimatic dynamics of ecosystems.

Este trabalho foi realizado utilizando dados coletados em uma Floresta de Transição, em uma área pertencente à Fazenda Maracaí no Noroeste de Sinop, MT, com dados micrometeorológicos obtidos com o sistema de correlação de vórtices turbulentos (Eddy Covarience) instalado numa torre de 40 metros. Teve como objetivo principal estudar as potencialidades da análise de Fourier aplicada a dados de fluxo de Calor Latente (LE), Calor Sensível (H) e Temperatura (T). Para os cálculos foram feitas médias de 3 em 3 horas para cada mês, ao longo do período de 1999 a 2005, para as variáveis estudadas. Os períodos dominantes encontrados foram de 24; 12; 4 e 3,4 horas. Os dois primeiros são atribuíveis ao movimento de rotação da Terra, ou seja, à periodicidade dia/noite. Quanto aos dois períodos menores, há indícios que estão relacionados com a dinâmica de abertura dos estômatos. Assim sendo, os resultados deste trabalho indicam que os fatores que influenciam predominantemente as variáveis microclimatológicas durante o dia (freqüências entre 10-5 a 10-4 Hz) são a radiação solar e a dinâmica de abertura dos estômatos, um resultado que destaca as potencialidades da aplicação do método de Fourier no estudo da dinâmica de microclimas em ecossistemas.