Global Air Quality and Pollution

By H. Akimoto. Science, 2003

1,093 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/1866198b9b4ec103f4ec36ff27019e3a5934716e

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In Mechanical Engineering

Citations in the corpus

Global source attribution of tropospheric ozone: Long-range transport from various source regions (2007, background): “[2] Tropospheric ozone (O3) is recognized as one of the key factors to control global-scale changes in climate [Gauss et al., 2003, 2006] and air quality [Akimoto, 2003].”
Deep Distributed Fusion Network for Air Quality Prediction (2018, background): “With the rapid development of urbanization, air pollution is becoming a severe environmental and societal issue for all developing countries around the world [1].”
The Economic Effects of COVID-19 Containment Measures (2020, methodology): “We follow the approach proposed by Jordà (2005) to assess the dynamic cumulative effect of containment measures on economic activity, a methodology used also by Auerbach and Gorodnichenko (2013), Ramey and Zubairy (2018), and Alesina et al.”
A preliminary assessment of the impact of COVID-19 on environment – A case study of China (2020, neutral): “NO and NO2 react with other chemicals and form acid rain, which harms the ecosystem (Akimoto, 2003).”
Polluted work: A self-control perspective on air pollution appraisals, organizational citizenship, and counterproductive work behavior (2017, neutral): “Throughout the world, air pollution is reaching hazardous levels with growing frequency (Akimoto, 2003; Dockery & Pope, 1994).”
Transcript expression profiles of Arabidopsis thaliana grown under controlled conditions and open-ai (2004, background): “Whatever the reasons for these changes, human intervention certainly being one, it is indisputable that increases in concentration of global atmospheric carbon dioxide and nitrous oxides, coupled with global warming, will lead to an increase in tropospheric ozone (Fowler et al., 1999; Akimoto, 2003;”
PM2.5 Prediction Based on Random Forest, XGBoost, and Deep Learning Using Multisource Remote Sensing Data (2019, neutral): “n_estimators 70 to 150 130 max_features [Auto, SQRT, Log2] SQRT min_samples_split [2,4,8] 2 bootstrap [True, False] False”
An Estimate of the Global Burden of Anthropogenic Ozone and Fine Particulate Matter on Premature Human Mortality Using Atmospheric Modeling (2010, background): “5 concentrations have increased most in industrialized areas, observations show that background concentrations have also increased in remote regions (Akimoto 2003; Schultz et al. 2006; Staehelin et al. 2001; Vingarzan 2004; Volz and Kley 1988). O3 and PM2.5 are associated with negative health impact”
The rise of low-cost sensing for managing air pollution in cities. (2015, background): “Consequently, the release of pollutants into the atmosphere continues to increase (Akimoto 2003), having adverse impacts on a local, regional and global scale, with significant associated health-effects (Lim et al.”