Air Pollution Modelling: Local-, Regional-, and Global-Scale Application
The air pollution problem inevitably accompanies our human activities. Severe air pollution situations have been reported, especially in emerging countries, and satisfying the air quality standards fully remains an underlying issue. Today, modeling research is one of the more valuable approaches to...
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| Year of Publication: | 2021 |
| Language: | English |
| Physical Description: | 1 electronic resource (174 p.) |
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| 035 | |a (EXLCZ)995400000000046000 | ||
| 041 | 0 | |a eng | |
| 100 | 1 | |a Itahashi, Syuichi |4 edt | |
| 245 | 1 | 0 | |a Air Pollution Modelling: Local-, Regional-, and Global-Scale Application |
| 246 | |a Air Pollution Modelling | ||
| 260 | |a Basel, Switzerland |b MDPI - Multidisciplinary Digital Publishing Institute |c 2021 | ||
| 300 | |a 1 electronic resource (174 p.) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 506 | |a Open access |f Unrestricted online access |2 star | ||
| 520 | |a The air pollution problem inevitably accompanies our human activities. Severe air pollution situations have been reported, especially in emerging countries, and satisfying the air quality standards fully remains an underlying issue. Today, modeling research is one of the more valuable approaches to understanding the behavior of air pollutants, and is useful for regulation-, policy- and decision-making. Such modeling applications range, with regard to horizontal grid resolution, from a few km (local) to hundreds of km (regional), to thousands of km (global). To foster our current scientific knowledge on modeling potentialities and limitations, scientific research related to multi-scale air pollution modeling is collected in this book. | ||
| 546 | |a English | ||
| 650 | 7 | |a Environmental science, engineering & technology |2 bicssc | |
| 653 | |a Urban pollution | ||
| 653 | |a Street canyon | ||
| 653 | |a Nitrate aerosol | ||
| 653 | |a CFD | ||
| 653 | |a Air quality | ||
| 653 | |a open burning | ||
| 653 | |a biomass burning | ||
| 653 | |a sugarcane crops | ||
| 653 | |a environmental assessment | ||
| 653 | |a air quality modeling | ||
| 653 | |a chemical reaction model | ||
| 653 | |a urban canyon | ||
| 653 | |a radiation | ||
| 653 | |a mesoscale models | ||
| 653 | |a reactive pollutants | ||
| 653 | |a Community Multiscale Air Quality (CMAQ) | ||
| 653 | |a East Asia | ||
| 653 | |a Tokyo | ||
| 653 | |a SO42- | ||
| 653 | |a stabilized Criegee intermediates (SCI) | ||
| 653 | |a wildfire plume rise | ||
| 653 | |a smoke modeling | ||
| 653 | |a large eddy simulation | ||
| 653 | |a emissions dispersion | ||
| 653 | |a WRF-SFIRE | ||
| 653 | |a RxCADRE | ||
| 653 | |a RePLaT-Chaos | ||
| 653 | |a large-scale atmospheric advection | ||
| 653 | |a chaotic advection | ||
| 653 | |a stretching rate | ||
| 653 | |a escape rate | ||
| 653 | |a education | ||
| 653 | |a CMAQ | ||
| 653 | |a PM10 | ||
| 653 | |a atmospheric reanalysis | ||
| 653 | |a PM2.5 | ||
| 653 | |a PM2.5 components | ||
| 653 | |a three-dimensional chemical transport model | ||
| 653 | |a model inter-comparison | ||
| 653 | |a urban scale | ||
| 653 | |a secondary particles | ||
| 653 | |a WRF-Chem | ||
| 653 | |a visibility | ||
| 653 | |a eastern China | ||
| 653 | |a neural network algorithm | ||
| 653 | |a IMPROVE | ||
| 776 | |z 3-0365-0644-6 | ||
| 776 | |z 3-0365-0645-4 | ||
| 700 | 1 | |a Itahashi, Syuichi |4 oth | |
| 906 | |a BOOK | ||
| ADM | |b 2023-12-15 05:44:20 Europe/Vienna |f system |c marc21 |a 2022-04-04 09:22:53 Europe/Vienna |g false | ||
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