Mapping environmental noise of Guangzhou based on land use regression models.

Background: Environmental noise seriously affects people's health and life quality, but there is a scarcity of noise exposure data in metropolitan cities and at nighttime, especially in developing countries.

Objective: This study aimed to assess the environmental noise level by land use regression (LUR) models and create daytime and nighttime noise maps with high-resolution of Guangzhou municipality.

Methods: A total of 100 monitoring sites were randomly selected according to population density.

Evaluating background and local contributions and identifying traffic-related pollutant hotspots: insights from Google Air View mobile monitoring in Dublin, Ireland.

Mobile monitoring provides high-resolution observation on temporal and spatial scales compared to traditional fixed-site measurement. This study demonstrates the use of high spatio-temporal resolution of air pollution data collected by Google Air View vehicles to identify hotspots and assess compliance with WHO Air Quality Guidelines (AQGs) in Dublin City. The mobile monitoring was conducted during weekdays, typically from 7:00 to 19:00, between 6 May 2021 and 6 May 2022.

Development of a mobile application to represent food intake in inpatients: dietary data systematization.

Background: Nutritional risk situations related to decreased food intake in the hospital environment hinder nutritional care and increase malnutrition in hospitalized patients and are often associated with increased morbidity and mortality. The objective of this study is to develop and test the reliability and data similarity of a mobile application as a virtual instrument to assess the acceptability and quality of hospital diets for inpatients.

Methods: This intra- and interobserver development and reliability study investigated an in-hospital food intake monitoring application based on a validated instrument for patients with infectious diseases who were treated at the Evandro Chagas National Institute of Infectious Diseases (INI/FIOCRUZ).

Examining the status of improved air quality in world cities due to COVID-19 led temporary reduction in anthropogenic emissions.

Clean air is a fundamental necessity for human health and well-being. Anthropogenic emissions that are harmful to human health have been reduced substantially under COVID-19 lockdown. Satellite remote sensing for air pollution assessments can be highly effective in public health research because of the possibility of estimating air pollution levels over large scales.