Data multi-scale decomposition strategies for air pollution forecasting: A comprehensive review

2020 ◽  
Vol 277 ◽  
pp. 124023
Author(s):  
Hui Liu ◽  
Shi Yin ◽  
Chao Chen ◽  
Zhu Duan
Keyword(s):  
Air Pollution ◽  
Comprehensive Review ◽  
Multi Scale ◽  
Decomposition Strategies ◽  
Air Pollution Forecasting

scholarly journals Development of Solid–Fluid Reaction Models—A Literature Review

2021 ◽  
Vol 5 (3) ◽  
pp. 36
Author(s):  
Leilei Dong ◽  
Italo Mazzarino ◽  
Alessio Alexiadis
Keyword(s):  
Process Design ◽  
Feasibility Studies ◽  
Time Frame ◽  
Physicochemical Process ◽  
Computational Time ◽  
Comprehensive Review ◽  
Multi Scale ◽  
Reaction Models ◽  
Feasible Solutions ◽  
Further Development

A comprehensive review is carried out on the models and correlations for solid/fluid reactions that result from a complex multi-scale physicochemical process. A simulation of this process with CFD requires various complicated submodels and significant computational time, which often makes it undesirable and impractical in many industrial activities requiring a quick solution within a limited time frame, such as new product/process design, feasibility studies, and the evaluation or optimization of the existing processes, etc. In these circumstances, the existing models and correlations developed in the last few decades are of significant relevance and become a useful simulation tool. However, despite the increasing research interests in this area in the last thirty years, there is no comprehensive review available. This paper is thus motivated to review the models developed so far, as well as provide the selection guidance for model and correlations for the specific application to help engineers and researchers choose the most appropriate model for feasible solutions. Therefore, this review is also of practical relevance to professionals who need to perform engineering design or simulation work. The areas needing further development in solid–fluid reaction modelling are also identified and discussed.

The impact of air pollution on skin and related disorders: A comprehensive review

2021 ◽  
Author(s):  
Ruhollah Abolhasani ◽  
Farnaz Araghi ◽  
Mohammadreza Tabary ◽  
Armin Aryannejad ◽  
Baharnaz Mashinchi ◽  
...  
Keyword(s):  
Air Pollution ◽  
Comprehensive Review ◽  
The Impact

scholarly journals Development of an ANN–based air pollution forecasting system with explicit knowledge through sensitivity analysis

2014 ◽  
Vol 5 (4) ◽  
pp. 696-708 ◽  
Author(s):  
Madhavi Anushka Elangasinghe ◽  
Naresh Singhal ◽  
Kim N. Dirks ◽  
Jennifer A. Salmond
Keyword(s):  
Air Pollution ◽  
Sensitivity Analysis ◽  
Explicit Knowledge ◽  
Forecasting System ◽  
Air Pollution Forecasting

scholarly journals Peramalan Pencemaran Udara Di Kota Surabaya Menggunakan Metode DSARIMA dengan Pendekatan Percentile Error Bootstrap (PEB)

2021 ◽  
Vol 8 (5) ◽  
pp. 987
Author(s):  
Novi Koesoemaningroem ◽  
Endroyono Endroyono ◽  
Supeno Mardi Susiki Nugroho
Keyword(s):  
Air Pollution ◽  
Actual Data ◽  
Forecast Data ◽  
Accuracy Result ◽  
The Difference ◽  
The Impact ◽  
Air Pollution Forecasting

<p>Peramalan pencemaran udara yang  akurat  diperlukan untuk mengurangi dampak pencemaran udara. Peramalan yang belum akurat akan berdampak kurang efektifnya tindakan yang dilakukan untuk mengantisipasi dampak pencemaran udara. Sehingga diperlukan sebuah pendekatan yang dapat mengetahui keakuratan plot data hasil peramalan. Penelitian ini dilakukan dengan tujuan melakukan peramalan pencemaran udara berdasarkan parameter PM<sub>10</sub>, NO<sub>2</sub>, CO, SO<sub>2</sub>, dan O<sub>3</sub>dengan metode DSARIMA. Data dalam penelitian ini sebanyak 8.760 data yang berasal dari Dinas Lingkungan Hidup Kota Surabaya. Berdasarkan hasil peramalan selama 168 jam kadar parameter PM<sub>10</sub>, NO<sub>2</sub>, SO<sub>2</sub> dan O<sub>3</sub> cenderung  menurun. Hasil peramalan selama 168 jam dengan menggunakan DSARIMA memberikan hasil peramalan yang nilainya mendekati data aktual terbukti dari polanya yang sesuai atau mirip dengan grafik plot data aktual dengan hasil ramalan. Dengan pendekatan PEB, selisih antara data aktual dan data ramalan kecil dan plot grafik PEB mengikuti plot grafik di data aktual, sehingga dapat dikatakan bahwa model sudah sesuai. Hasil akurasi terbaik yang dihasilkan adalah model DSARIMA dengan RMSE terkecil 0,59 didapatkan dari parameter CO yaitu ARIMA(0,1,[1,2,3])(0,1,1)<sup>24</sup>(0,1,1)<sup>168</sup>.</p><p> </p><p><em><strong>Abstract</strong></em></p><p class="Judul2"><em>Accurate air pollution forecasting is needed to reduce the impact of air pollution. Inaccurate forecasting will result in less effective actions taken to anticipate the impact of air pollution. So we need an approach that can determine the accuracy of the forecast data plot. This research was conducted with the aim of forecasting air pollution based on the PM<sub>10</sub>, NO<sub>2</sub>, CO, <sub>SO2</sub>, and O<sub>3</sub> parameters using the DSARIMA method. The data in this study were 8.760 data from the Surabaya City Environmental Service. Based on the results of forecasting for 168 hours, the levels of PM<sub>10</sub>, NO<sub>2, </sub>SO<sub>2</sub>, and O<sub>3</sub> parameters tend to decrease. Forecasting results for 168 hours using DSARIMA provide forecasting results whose values are close to the actual data as evidenced by the pattern that matches or is similar to the actual data plot graph with the forecast results. With the PEB approach, the difference between the actual data and the forecast data is small and the PEB graph plot follows the graph plot in the actual data, so it can be said that the model is appropriate. The best accuracy result is DSARIMA with the smallest RMSE 0,59 obtained from the CO parameter, namely </em>ARIMA(0,1,[1,2,3])(0,1,1)<sup>24</sup>(0,1,1)<sup>168</sup>.</p><p> </p><p> </p>

NESTED HIGH-RESOLUTION NOx AND PM SIMULATIONS OVER ZÜRICH

2021 ◽  
Author(s):  
Ivo Suter ◽  
Lukas Emmenegger ◽  
Dominik Brunner
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Boundary Conditions ◽  
Meteorological Conditions ◽  
Model Systems ◽  
Multi Scale ◽  
Wide Range ◽  
The Impact ◽  
The City ◽  
Concentration Levels

&lt;p&gt;Reducing air pollution, which is the world's largest single environmental health risk, demands better-informed air quality policies. Consequently, multi-scale air quality models are being developed with the goal to resolve cities. One of the major challenges in such model systems is to accurately represent all large- and regional-scale processes that may critically determine the background concentration levels over a given city. This is particularly true for longer-lived species such as aerosols, for which background levels often dominate the concentration levels, even within the city. Furthermore, the heterogeneous local emissions, and complex dispersion in the city have to be considered carefully.&lt;/p&gt;&lt;p&gt;In this study, the impact of processes across a wide range of scales on background concentrations over Switzerland and the city of Zurich was modelled by performing one year of nested European and Swiss national COSMO-ART simulations to obtain adequate boundary conditions for gas-phase chemical, aerosol and meteorological conditions for city-resolving simulations. The regional climate chemistry model COSMO-ART (Vogel et al. 2009) was used in a 1-way coupled mode. The outer, European, domain, which was driven by chemical boundary conditions from the global MOZART model, had a 6.6 km horizontal resolution and the inner, Swiss, domain one of 2.2 km. For the city scale, a catalogue of more than 1000 mesoscale flow patterns with 100 m resolution was created with the model GRAMM, based on a discrete set of atmospheric stabilities, wind speeds and directions, accounting for the influence of land-use and topography. Finally, the flow around buildings was solved with the CFD model GRAL forced at the boundaries by GRAMM. Subsequently, Lagrangian dispersion simulations for a set of air pollutants and emission sectors (traffic, industry, ...) based on extremely detailed building and emission data was performed in GRAL. The result of this nested procedure is a library of 3-dimensional air pollution maps representative of hourly situations in Zurich (Berchet et al. 2017). From these pre-computed situations, time-series and concentration maps can be obtained by selecting situations according to observed or modelled meteorological conditions.&lt;/p&gt;&lt;p&gt;The results were compared to measurements from air quality monitoring network stations. Modelled concentrations of NO&lt;sub&gt;x&lt;/sub&gt; and PM compared well to measurements across multiple locations, provided background conditions were considered carefully. The nested multi-scale modelling system COSMO-ART/GRAMM/GRAL can adequately reproduce local air quality and help understanding the relative contributions of local versus distant emissions, as well as fill the space between precise point measurements from monitoring sites. This information is useful for research, policy-making, and epidemiological studies particularly under the assumption that exceedingly high concentrations become more and more localised phenomenon in the future.&lt;/p&gt;

Sign in / Sign up

Export Citation Format

Share Document