Adoption of sustainable agricultural practices during the pandemic: the case of Ecuadorian family farming systems

PurposeThe objective of this study was to examine the impact of the pandemic on sustainable agricultural practices (SAP) adoption such as: organic fertilizers, minimal use of tillage, crop rotation, soil burning and crop association in the frame of family farming systems in Ecuador.Design/methodology/approachThe present research employed probit models' estimation with pooled data from 2018 to 2020. The study combined three sources of information with The Survey on Surface and Agricultural Continuous Production, as the main. This study also proposed the analysis of six regions: Coast, Coast Mountains, Northern Highlands, Central Highlands, Southern Highlands and the Amazon.FindingsThe authors see a lower adoption in the year 2020, where the pandemic was one of the causes. The only exception was the use of organic fertilizer. The adoption of these sustainable practices differed across the six regions. The findings also reveal that the employment generated by agricultural enterprises had a negative influence on the adoption of three sustainable practices, and that for the remaining practices the effect was positive.Research limitations/implicationsThe data set lacks information on the acceptance and the application of the practices promoted by agricultural technical assistance, which could provide insights into the effectiveness of the learning process. The limited observation period does not allow for investigating long-term effects on sustainable practices adoption.Originality/valueThis study helps to understand the implications of the COVID-19 pandemic in the adoption of SAP. Additionally, this research can help with the scalability of the practices starting from the regions that are most likely to adopt each of them.

Gender equity and spatial variability of covid 19 impacts on mobility behavior: A comparison of two household-travel surveys

The impact of COVID-19 has been enormous, and the situation has been unprecedented. Consequently, most countries around the world impose mobility restrictions on their citizens. Society changes impact the demand for transportation, reducing the number of trips and altering modes of transportation, as well as affecting the price of living. Inequalities between various groups of the Soussian community have been further aggravated by the current health crisis. This is particularly relevant since there is already a gap between genders, and women are the most affected. In this paper, we attempt to identify the hierarchy of the travel patterns of females in the various delegations of the Grand Sousse, analyzing mobility behavior of women. Based on results from two household/travel surveys conducted before and during COVID (in 2019 and 2020), a descriptive analysis was conducted according to four categories: general mobility characteristics, travel rate, mobility characteristics (modal split and reasons for travel) and the trinomial;distance, time, and cost. The results of our analysis are consistent with similar analysis done by other researchers, with significant differences between genders, indicating that women are at greater risk of mobilizing in the 'Grand Sousse'. A large percentage of individuals impacted by this epidemic is females. By applying a detailed spatial reading of mobility characteristics, it was possible to clarify these differences under a significant variation in the daily mobility characteristics of women in favor of the best-equipped delegations. © 2022 IEEE.

Observational data from uncrewed systems over Southern Great Plains

Uncrewed Systems (UxS), including uncrewed aerial systems (UAS) and tethered balloon/kite systems (TBS), are significantly expanding observational capabilities in atmospheric science. Rapid adaptation of these platforms and the advancement of miniaturized instruments have resulted in an expanding number of datasets captured under various environmental conditions by the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility. In 2021, observational data collected using ARM UxS platforms, including seven TigerShark UAS flights and 133 tethered balloon system (TBS) flights, were archived by the ARM Data Center (https://adc.arm.gov/discovery/#/, last access: 11 February 2022) and made publicly available at no cost for all registered users (10.5439/1846798) (Mei and Dexheimer, 2022). These data streams provide new perspectives on spatial variability of atmospheric and surface parameters, helping to address critical science questions in Earth system science research. This paper describes the DOE UAS/TBS datasets, including information on the acquisition, collection, and quality control processes, and highlights the potential scientific contributions using UAS and TBS platforms.

Exploratory spatial analysis for interval data: A new autocorrelation index with COVID-19 and rent price applications

This paper aims to identify the behavior of interval data associated to its respective geospatial information with in the framework of Symbolic Data Analysis. The main idea is to extend Moran’s autocorrelation index of Exploratory Spatial Analysis to interval data. Symbolic data analysis is a domain of research and application related to the areas of machine learning and statistics that provide tools to describe units (objects), enabling them to consider variability. Spatially correlated data are geospatial data with spatial autocorrelation, and the variability that comes from each region and neighborhood may be better expressed by intervals. Thus, this paper demonstrates the importance of considering the variability present in the interval variable and the variability present in geographical information. Experiments with synthetic interval data are performed to illustrate the usefulness of the proposed approach. We also, analyze two applications, dealing with COVID-19 and rent price interval data.

Impacts of air pollution on COVID-19 case fatality rate: a global analysis.

The coronavirus disease 2019 (COVID-19) pandemic is still rapidly spreading globally. To probe high-risk cities and the impacts of air pollution on public health, this study explores the relationship between the long-term average concentration of air pollution and the city-level case fatality rate (CFR) of COVID-19 globally. Then, geographically weighted regression (GWR) is applied to examine the spatial variability of the relationships. Six air pollution factors, including nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), PM2.5 (particles with diameter ≤2.5 µm), PM10 (particles with diameter ≤10 µm), and air quality index (AQI), are positively associated with the city-level COVID-19 CFR. Our results indicate that a 1-unit increase in NO2 (part per billion, PPB), SO2 (PPB), O3 (PPB), PM2.5 (microgram per cubic meter, µg/m3), PM10 (µg/m3), AQI (score), is related to a 1.450%, 1.005%, 0.992%, 0.860%, 0.568%, and 0.776% increase in the city-level COVID-19 CFR, respectively. Additionally, the effects of NO2, O3, PM2.5, AQI, and probability of living with poor AQI on COVID-19 spatially vary in view of the estimation of the GWR. In other words, the adverse impacts of air pollution on health are different among the cities. In summary, long-term exposure to air pollution is negatively related to the COVID-19 health outcome, and the relationship is spatially non-stationary. Our research sheds light on the impacts of slashing air pollution on public health in the COVID-19 pandemic to help governments formulate air pollution policies in light of the local situations.

Spatial Variability in COVID-19 Mortality.

COVID-19 emerged as a global pandemic in the spring of 2020. Since that time, the disease has resulted in approximately 150 million cases and 3 million deaths worldwide. However, there is significant spatial variation in the rate of mortality from COVID-19. Here, we briefly explore spatial variations in COVID-19 mortality by country groupings and propose possible explanations for the differences observed. Specifically, we find that there is a statistically significant difference in COVID-19 mortality between countries grouped into categories based on (1) developed, primarily western diets and healthcare systems; (2) "Scandinavian" countries with advanced healthcare systems and generally anti-inflammatory diets, and (3) developing countries. We do not infer causality but believe that the observed associations provide hypotheses for future research investigations. Moreover, our results add further evidence to support additional exploration of vitamin D exposure/status and COVID-19 mortality.