State-of-art in modelling particulate matter (PM) concentration: a scoping review of aims and methods
Air pollution is the one of the most significant environmental risks to health worldwide. An
accurate assessment of population exposure would require a continuous distribution of …
accurate assessment of population exposure would require a continuous distribution of …
The use of Google community mobility reports to model residential waste generation behaviors during and after the COVID-19 lockdown
This paper proposed an original analytical approach to quantify waste generation and
recycling behaviors in Regina, a Canadian capital city, using Google's Community Mobility …
recycling behaviors in Regina, a Canadian capital city, using Google's Community Mobility …
Contributions of meteorology to ozone variations: Application of deep learning and the Kolmogorov-Zurbenko filter
From hourly ozone observations obtained from three regions⸻ Houston, Dallas, and West
Texas⸻ we investigated the contributions of meteorology to changes in surface daily …
Texas⸻ we investigated the contributions of meteorology to changes in surface daily …
Deep learning mapping of surface MDA8 ozone: The impact of predictor variables on ozone levels over the contiguous United States
The limited number of ozone monitoring stations imposes uncertainty in various
applications, calling for accurate approaches to capturing ozone values in all regions …
applications, calling for accurate approaches to capturing ozone values in all regions …
A comprehensive approach combining positive matrix factorization modeling, meteorology, and machine learning for source apportionment of surface ozone …
Abstract Ozone concentrations in Houston, Texas, are among the highest in the United
States, posing significant risks to human health. This study aimed to evaluate the impact of …
States, posing significant risks to human health. This study aimed to evaluate the impact of …
Climate change, forest fires, and territorial dynamics in the Amazon rainforest: an integrated analysis for mitigation strategies
Recent times have witnessed wildfires causing harm to both ecological communities and
urban–rural regions, underscoring the necessity to comprehend wildfire triggers and assess …
urban–rural regions, underscoring the necessity to comprehend wildfire triggers and assess …
Design of a forest fire early alert system through a deep 3D-CNN structure and a WRF-CNN bias correction
A Casallas, C Jiménez-Saenz, V Torres… - Sensors, 2022 - mdpi.com
Throughout the years, wildfires have negatively impacted ecological systems and urban
areas. Hence, reinforcing territorial risk management strategies against wildfires is essential …
areas. Hence, reinforcing territorial risk management strategies against wildfires is essential …
Predicting PM2.5 Concentrations Across USA Using Machine Learning
PP Vignesh, JH Jiang, P Kishore - Earth and Space Science, 2023 - Wiley Online Library
Economic growth, air pollution, and forest fires in some states in the United States have
increased the concentration of particulate matter with a diameter less than or equal to 2.5 μm …
increased the concentration of particulate matter with a diameter less than or equal to 2.5 μm …
Air quality improvement following COVID-19 lockdown measures and projected benefits for environmental health
Many regions worldwide suffer from heavy air pollution caused by particulate matter (PM2.
5) and nitrogen dioxide (NO2), resulting in a huge annual disease burden and significant …
5) and nitrogen dioxide (NO2), resulting in a huge annual disease burden and significant …
A Coupled Deep Learning Model for Estimating Surface NO2 Levels From Remote Sensing Data: 15‐Year Study Over the Contiguous United States
This study proposes a novel two‐step deep learning (DL) model for estimating surface NO2
concentrations using satellite data over the contiguous United States (CONUS) from 2005 to …
concentrations using satellite data over the contiguous United States (CONUS) from 2005 to …