Measured and modelled air quality trends in Italy over the period 2003–2010

Abstract. Air pollution harms human health and the environment. Several regulatory efforts and different actions have been taken in the last decades by authorities. Air quality trend analysis represents a valid tool in assessing the impact of these actions taken both at national and local levels. This paper presents for the first time the capability of the Italian national chemical transport model, AMS-MINNI, in capturing the observed concentration trends of three air pollutants, NO2, inhalable particles having diameter less than 10 micrometres (PM10) and O3, in Italy over the period 2003–2010. We firstly analyse the model performance finding it in line with the state of the art of regional models applications. The modelled trends result in a general significant downward trend for the three pollutants and, in comparison with observations, the values of the simulated slopes show the same magnitude for NO2 (in the range −3.0 ÷ −0.5 ug m−3 yr−1), while a smaller variability is detected for PM10 (−1.5 ÷ −0.5 ug m−3 yr−1) and O3-maximum daily 8-hour average concentration (−2.0 ÷ −0.5 ug m−3 yr−1). As a general result, we find a good agreement between modelled and observed trends; moreover, the model allowed to extend both the spatial coverage and the statistical significance of pollutants' concentrations trends with respect to observations, in particular for NO2. We also conduct a qualitative attempt to correlate the temporal concentration trends to meteorological and emission variability. Since no clear tendency in yearly meteorological anomalies (temperature, precipitation, geopotential height) was observed for the period investigated, we focus the discussion of concentrations trends on emissions variations. We point out that, due to the complex links between precursors emissions and air pollutants concentrations, emission reductions do not always result in a corresponding decrease in atmospheric concentrations, especially for those pollutants that are formed in the atmosphere such as O3 and the major fraction of PM10. These complex phenomena are still uncertain and their understanding is of the utmost importance in planning future policies for reducing air pollution and its impacts on health and ecosystems.

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Measured and modelled air quality trends in Italy over the period 2003–2010

Atmospheric Chemistry and Physics ◽

10.5194/acp-21-10825-2021 ◽

2021 ◽

Vol 21 (13) ◽

pp. 10825-10849

Author(s):

Ilaria D'Elia ◽

Gino Briganti ◽

Lina Vitali ◽

Antonio Piersanti ◽

Gaia Righini ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Transport Model ◽

Statistical Significance ◽

Average Concentration ◽

Air Pollutant ◽

Chemical Transport Model ◽

Spatial Coverage ◽

Significant Downward Trend ◽

The Impact

Abstract. Air pollution harms human health and the environment. Several regulatory efforts and different actions have been taken in the last decades by authorities. Air quality trend analysis represents a valid tool in assessing the impact of these actions taken both at national and local levels. This paper presents for the first time the capability of the Italian national chemical transport model, AMS-MINNI, in capturing the observed concentration trends of three air pollutants – NO2, inhalable particles having diameter less than 10 µm (PM10), and O3 – in Italy over the period 2003–2010. We firstly analyse the model performance finding it in line with the state of the art of regional air quality modelling. The modelled trends result in a general significant downward trend for the three pollutants and, in comparison with observations, the values of the simulated trends were of a similar magnitude for NO2 (in the range −3.0 to −0.5 µg m−3 yr−1), while a smaller range of trends was found than those observed for PM10 (−1.5 to −0.5 µg m−3 yr−1) and O3 maximum daily 8 h average concentration (−2.0 to −0.5 µg m−3 yr−1). As a general result, we find good agreement between modelled and observed trends; moreover, the model provides a greater spatial coverage and statistical significance of pollutant concentration trends with respect to observations, in particular for NO2. We also conduct a qualitative attempt to correlate the temporal concentration trends to meteorological and emission variability. Since no clear tendency in yearly meteorological anomalies (temperature, precipitation, geopotential height) was observed for the period investigated, we focus the discussion of concentration trends on emission variations. We point out that, due to the complex links between precursor emissions and air pollutant concentrations, emission reductions do not always result in a corresponding decrease in atmospheric concentrations, especially for those pollutants that are formed in the atmosphere such as O3 and the major fraction of PM10. These complex phenomena are still uncertain and their understanding is of the utmost importance in planning future policies for reducing air pollution and its impacts on health and ecosystems.

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Pre-monsoon air quality over Lumbini, a world heritage site along the Himalayan foothills

10.5194/acp-2016-430 ◽

2016 ◽

Cited By ~ 2

Author(s):

Dipesh Rupakheti ◽

Bhupesh Adhikary ◽

Puppala S. Praveen ◽

Maheswar Rupakheti ◽

Shichang Kang ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Forest Fires ◽

Air Pollutants ◽

Transport Model ◽

World Heritage ◽

World Heritage Site ◽

Pollution Level ◽

Pollution Transport ◽

Heritage Site

Abstract. Lumbini, in southern Nepal, is a UNESCO world heritage site of universal value as the birthplace of Buddha. Poor air quality in Lumbini and surrounding regions is a great concern for public health as well as for preservation, protection and promotion of Buddhist heritage and culture. We present here results from measurements of ambient concentrations of key air pollutants (PM, BC, CO, O3) in Lumbini, first of its kind for Lumbini, conducted during an intensive measurement period of three months (April–June 2013) in the pre-monsoon season. The measurements were carried out as a part of the international air pollution measurement campaign; SusKat-ABC (Sustainable Atmosphere for the Kathmandu Valley – Atmospheric Brown Clouds). The ranges of hourly average concentrations were: PM10: 10.5–604.0 µg m−3, PM2.5: 6.1–272.2 µg m−3; BC: 0.3–30.0 µg m−3; CO: 125.0–1430.0 ppbv; and O3: 1.0–118.1 ppbv. These levels are comparable to other very heavily polluted sites throughout South Asia. The 24-h average PM2.5 and PM10 concentrations exceeded the WHO guideline very frequently (94 % and 85 % of the sampled period, respectively), which implies significant health risks for the residents and visitors in the region. These air pollutants exhibited clear diurnal cycles with high values in the morning and evening. During the study period, the worst air pollution episodes were mainly due to agro-residue burning and regional forest fires combined with meteorological conditions conducive of pollution transport to Lumbini. Fossil fuel combustion also contributed significantly, accounting for more than half of the ambient BC concentration according to aerosol spectral light absorption coefficients obtained in Lumbini. WRF-STEM, a regional chemical transport model, was used to simulate the meteorology and the concentrations of pollutants. The model was able to reproduce the variation in the pollutant concentrations well; however, estimated values were 1.5 to 5 times lower than the observed concentrations for CO and PM10 respectively. Regionally tagged CO tracers showed the majority of CO came from the upwind region of Ganges valley. The model was also used to examine the chemical composition of the aerosol mixture, indicating that organic carbon was the main constituent of fine mode PM2.5, followed by mineral dust. Given the high pollution level, there is a clear and urgent need for setting up a network of long-term air quality monitoring stations in the greater Lumbini region.

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Extending methane profiles from aircraft into the stratosphere for satellite total column validation using the ECMWF C-IFS and TOMCAT/SLIMCAT 3-D model

Atmospheric Chemistry and Physics ◽

10.5194/acp-17-6663-2017 ◽

2017 ◽

Vol 17 (11) ◽

pp. 6663-6678 ◽

Cited By ~ 2

Author(s):

Shreeya Verma ◽

Julia Marshall ◽

Mark Parrington ◽

Anna Agustí-Panareda ◽

Sebastien Massart ◽

...

Keyword(s):

Greenhouse Gases ◽

Transport Model ◽

A Priori ◽

Atmospheric Composition ◽

Random Errors ◽

Chemical Transport Model ◽

Spatial Coverage ◽

Forecasting System ◽

The Impact ◽

Total Column

Abstract. Airborne observations of greenhouse gases are a very useful reference for validation of satellite-based column-averaged dry air mole fraction data. However, since the aircraft data are available only up to about 9–13 km altitude, these profiles do not fully represent the depth of the atmosphere observed by satellites and therefore need to be extended synthetically into the stratosphere. In the near future, observations of CO2 and CH4 made from passenger aircraft are expected to be available through the In-Service Aircraft for a Global Observing System (IAGOS) project. In this study, we analyse three different data sources that are available for the stratospheric extension of aircraft profiles by comparing the error introduced by each of them into the total column and provide recommendations regarding the best approach. First, we analyse CH4 fields from two different models of atmospheric composition – the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System for Composition (C-IFS) and the TOMCAT/SLIMCAT 3-D chemical transport model. Secondly, we consider scenarios that simulate the effect of using CH4 climatologies such as those based on balloons or satellite limb soundings. Thirdly, we assess the impact of using a priori profiles used in the satellite retrievals for the stratospheric part of the total column. We find that the models considered in this study have a better estimation of the stratospheric CH4 as compared to the climatology-based data and the satellite a priori profiles. Both the C-IFS and TOMCAT models have a bias of about −9 ppb at the locations where tropospheric vertical profiles will be measured by IAGOS. The C-IFS model, however, has a lower random error (6.5 ppb) than TOMCAT (12.8 ppb). These values are well within the minimum desired accuracy and precision of satellite total column XCH4 retrievals (10 and 34 ppb, respectively). In comparison, the a priori profile from the University of Leicester Greenhouse Gases Observing Satellite (GOSAT) Proxy XCH4 retrieval and climatology-based data introduce larger random errors in the total column, being limited in spatial coverage and temporal variability. Furthermore, we find that the bias in the models varies with latitude and season. Therefore, applying appropriate bias correction to the model fields before using them for profile extension is expected to further decrease the error contributed by the stratospheric part of the profile to the total column.

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Impacts of emission changes in China from 2010 to 2017 on domestic and intercontinental air quality and health effect

10.5194/acp-2021-385 ◽

2021 ◽

Author(s):

Yuqiang Zhang ◽

Drew Shindell ◽

Karl Seltzer ◽

Lu Shen ◽

Jean-Francois Lamarque ◽

...

Keyword(s):

Air Pollution ◽

Air Quality ◽

Air Pollutants ◽

Transport Model ◽

Surface Ozone ◽

Health Effect ◽

Premature Deaths ◽

Concentration Changes ◽

Emission Changes ◽

Related Mortality

Abstract. China has seen dramatic emission changes from 2010, especially after the implementation of Clean Air Action in 2013, with significant air quality and human health benefits observed. Air pollutants, such as PM2.5 and surface ozone, as well as their precursors, have long enough lifetime in the troposphere which can be easily transported downwind. So emission changes in China will not only change the regional air quality domestically, but also affect the air quality in downwind regions. In this study, we use a global chemistry transport model to simulate the influence on both domestic and foreign air quality from the emission change from 2010 to 2017 in China. By applying the health impact functions derived from epidemiology studies, we then quantify the changes in air pollution-related (including both PM2.5 and O3) mortality burdens at regional and global scales. The majority of air pollutants in China reach their peak values around 2012 and 2013. Compared with the year 2010, the population-weighted annual PM2.5 in China increases till 2011 (94.1 μg m−3), and then begins to decrease. In 2017, the population-weighted annual PM2.5 decreases by 17.6 %, compared with the values in 2010 (84.7 μg m−3). The estimated national PM2.5 concentration changes in China are comparable with previous studies using fine-resolution regional models, though our model tends to overestimate PM2.5 from 2013 to 2017 when evaluated with surface observation in China during the same periods. The emission changes in China increased the global PM2.5-related mortality burdens from 2010 to 2013, by 27,700 (95 %CI: 23,900–31, 400) deaths yr−1 in 2011, and 13, 300 (11,400–15,100) deaths yr−1 in 2013, among which at least 93 % occurred in China. The sharp emission decreases after 2013 bring significant benefits for reduced avoided premature mortality in 2017, reaching 108, 800 (92,800–124,800) deaths yr−1 globally, among which 92 % happening in China. Different trend as PM2.5, the annual maximum daily 8-hr ozone in China increased, and also the ozone-related premature deaths, ranging from 3,600 (2,700–4,300) deaths yr−1 in 2011 (75 % of global total increased premature deaths), and 8,500 (6,500–9,900) deaths yr−1 in 2017 (143 % of the global total). Downwind regions, such as South Korea, Japan, and U.S. generally see a decreased O3-related mortality burden after 2013 as a combination of increased export of ozone and decreased export of ozone precursors. In general, we conclude that the sharp emission reductions in China after 2013 bring benefits of improved air quality and reduced premature deaths associated with air pollution at global scale. The benefits are dominated by the PM2.5 decreases since the ozone is shown to actually increase with the emission decrease.

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Efficiency and Eco-Costs of Air Purifiers in Terms of Improving Microbiological Indoor Air Quality in Dwellings—A Case Study

Atmosphere ◽

10.3390/atmos10120742 ◽

2019 ◽

Vol 10 (12) ◽

pp. 742 ◽

Cited By ~ 3

Author(s):

Ewa Brągoszewska ◽

Magdalena Bogacka ◽

Krzysztof Pikoń

Keyword(s):

Air Pollution ◽

Air Quality ◽

Indoor Air Quality ◽

Indoor Air ◽

Pollution Prevention ◽

Average Concentration ◽

Environmental Cost ◽

Bacterial Aerosol ◽

The Impact ◽

Ecological Cost

Air pollution, a by-product of economic growth, generates an enormous environmental cost in Poland. The issue of healthy living spaces and indoor air quality (IAQ) is a global concern because people spend approximately 90% of their time indoors. An increasingly popular method to improve IAQ is to use air purifiers (APs). Indoor air is often polluted by bioaerosols (e.g., viruses, bacteria, fungi), which are a major concern for public health. This work presents research on culturable bacterial aerosol (CBA) samples collected from dwellings with or without active APs during the 2019 summer season. The CBA samples were collected using a six-stage Andersen cascade impactor (ACI). The CBA concentrations were expressed as Colony Forming Units (CFU) per cubic metre of air. The average concentration of CBA in dwellings when the AP was active was 450–570 CFU/m3, whereas the average concentration when the AP was not active was 920–1000 CFU/m3. IAQ, when the APs were active, was on average almost 50% better than in cases where there were no procedures to decrease the concentration of air pollutants. Moreover, the obtained results of the particle size distribution (PSD) of CBA indicate that the use of APs reduced the proportion of the respirable fraction (the particles < 3.3 µm) by about 16%. Life cycle assessment (LCA) was used to assess the ecological cost of air purification. Our conceptual approach addresses the impact of indoor air pollution on human health and estimates the ecological cost of APs and air pollution prevention policies.

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Impacts of Current and Projected Oil Palm Plantation Expansion on Air Quality Over Southeast Asia

10.5194/acp-2016-158 ◽

2016 ◽

Author(s):

Sam J. Silva ◽

Colette L. Heald ◽

Jeffrey A. Geddes ◽

Kemen G. Austin ◽

Prasad S. Kasibhatla ◽

...

Keyword(s):

Air Quality ◽

Southeast Asia ◽

Oil Palm ◽

Urban Areas ◽

Transport Model ◽

Chemical Transport Model ◽

Oil Palm Plantation ◽

Deposition Velocities ◽

Current Constellation ◽

The Impact

Abstract. Over recent decades oil palm plantations have rapidly expanded across Southeast Asia (SEA). According to the United Nations, oil palm production in SEA increased by a factor of 3 from 1995 to 2010. We investigate the impacts of current (2010) and future (2020) oil palm expansion in SEA on surface-atmosphere exchange and the resulting air quality in the region. For this purpose, we use satellite data, high-resolution land maps, and the chemical transport model GEOS-Chem. Relative to a no oil palm plantation scenario (~ 1990), overall simulated isoprene emissions in the region increase by 13 % due to oil palm plantations in 2010 and a further 11 % by 2020. In addition, the expansion of palm plantations leads to local increases in ozone deposition velocities of up to 20 %. The net result of these changes is that oil palm expansion in SEA increases surface O3 by up to 3.5 ppbv over dense urban regions, and could rise more than 4.5 ppbv above baseline levels by 2020. Biogenic secondary organic aerosol loadings also increase by up to 1 μg m−3 due to oil palm expansion, and could increase a further 2.5 μg m−3 by 2020. Our analysis indicates that while the impact of recent oil palm expansion on air quality in the region has been significant, the retrieval error and sensitivity of the current constellation of satellite measurements limit our ability to observe these impacts from space. Oil palm expansion is likely to continue to degrade air quality in the region in the coming decade and hinder efforts to achieve air quality regulations in major urban areas such as Kuala Lumpur and Singapore.

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Changes in dissolved iron deposition to the oceans driven by human activity: a 3-D global modelling study

Biogeosciences Discussions ◽

10.5194/bgd-12-3943-2015 ◽

2015 ◽

Vol 12 (5) ◽

pp. 3943-3990

Author(s):

S. Myriokefalitakis ◽

N. Daskalakis ◽

N. Mihalopoulos ◽

A. R. Baker ◽

A. Nenes ◽

...

Keyword(s):

Air Quality ◽

Transport Model ◽

Organic Ligand ◽

Photochemical Reactions ◽

Anthropogenic Emissions ◽

Spatial And Temporal Variability ◽

Deposition Flux ◽

Chemical Transport Model ◽

The Future ◽

The Impact

Abstract. The global atmospheric iron (Fe) cycle is parameterized in the global 3-D chemical transport model TM4-ECPL to simulate the proton- and the organic ligand-promoted mineral Fe dissolution as well as the aqueous-phase photochemical reactions between the oxidative states of Fe(III/II). Primary emissions of total (TFe) and dissolved (DFe) Fe associated with dust and combustion processes are also taken into account. TFe emissions are calculated to amount to ~35 Tg Fe yr−1. The model reasonably simulates the available Fe observations, supporting the reliability of the results of this study. Accounting for proton- and organic ligand-promoted Fe-dissolution in present-day TM4-ECPL simulations, the total Fe-dissolution is calculated to be ~0.163 Tg Fe yr−1 that accounts for up to ~50% of the calculated total DFe emissions. The atmospheric burden of DFe is calculated to be ~0.012 Tg Fe. DFe deposition presents strong spatial and temporal variability with an annual deposition flux ~0.489 Tg Fe yr−1 from which about 25% (~0.124 Tg Fe yr−1) are deposited over the ocean. The impact of air-quality on Fe deposition is studied by performing sensitivity simulations using preindustrial (year 1850), present (year 2008) and future (year 2100) emission scenarios. These simulations indicate that an increase (~2 times) in Fe-dissolution may have occurred in the past 150 years due to increasing anthropogenic emissions and thus atmospheric acidity. On the opposite, a decrease (~2 times) of Fe-dissolution is projected for near future, since atmospheric acidity is expected to be lower than present-day due to air-quality regulations of anthropogenic emissions. The organic ligand contribution to Fe dissolution shows inverse relationship to the atmospheric acidity thus its importance has decreased since the preindustrial period but is projected to increase in the future. The calculated changes also show that the atmospheric DFe supply to High-Nutrient-Low-Chlorophyll oceanic areas (HNLC) characterized by Fe scarcity, has increased (~50%) since the preindustrial period. However, the DFe deposition flux is expected to decrease (~30%) to almost preindustrial levels over the Northern Hemisphere HNLC oceanic regions in the future. Significant reductions of ~20% over the Southern Ocean and the remote tropical Pacific Ocean are also projected which can further limit the primary productivity over HNLC waters.

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Air Pollutants Reduce The Physical Activity Of Professional Soccer Players.

10.21203/rs.3.rs-558780/v1 ◽

2021 ◽

Author(s):

Michał Zacharko ◽

Robert Cichowicz ◽

Marcin Andrzejewski ◽

Paweł Chmura ◽

Edward Kowalczuk ◽

...

Keyword(s):

Physical Activity ◽

Air Pollution ◽

Air Quality ◽

Air Pollutants ◽

Well Being ◽

Soccer Players ◽

Professional Soccer ◽

Considerable Problem ◽

The Impact ◽

Sporting Performance

Abstract The aim of the study was to determine the impact of air quality – analyzed on the basis of the model of integrating three types of air pollutants (ozone – O3, particulate matter - PM, nitrogen dioxide – NO2) – on the physical activity of soccer players. Study material consisted of 8927 individual match observations of 461 players competing in the German Bundesliga during the 2017/2018 and 2018/2019 domestic seasons. The measured indices included players’ physical activities: total distance (TD) and high intensity effort (HIE). Statistical analysis showed that with increasing levels of air pollution, both TD (F = 13.900(3); p = 0.001) and HIE (F = 8.060(3); p = 0.001) decrease significantly. The worsening of just one parameter of air pollution results in a significant reduction in performance. This is important information as air pollution is currently a considerable problem for many countries. Improving air quality during training sessions and sports competitions will result in better well-being and sporting performance of athletes, and will also help protect athletes from negative health effects caused by air pollution.

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Temperature response measurements from eucalypts give insight into the impact of Australian isoprene emissions on air quality in 2050

Atmospheric Chemistry and Physics ◽

10.5194/acp-20-6193-2020 ◽

2020 ◽

Vol 20 (10) ◽

pp. 6193-6206

Author(s):

Kathryn M. Emmerson ◽

Malcolm Possell ◽

Michael J. Aspinwall ◽

Sebastian Pfautsch ◽

Mark G. Tjoelker

Keyword(s):

Air Quality ◽

Transport Model ◽

Temperature Response ◽

Emission Factors ◽

Eucalyptus Species ◽

Chemical Transport Model ◽

Mixing Ratios ◽

The Impact ◽

Temperature Responses ◽

Insight Into

Abstract. Predicting future air quality in Australian cities dominated by eucalypt emissions requires an understanding of their emission potentials in a warmer climate. Here we measure the temperature response in isoprene emissions from saplings of four different Eucalyptus species grown under current and future average summertime temperature conditions. The future conditions represent a 2050 climate under Representative Concentration Pathway 8.5, with average daytime temperatures of 294.5 K. Ramping the temperature from 293 to 328 K resulted in these eucalypts emitting isoprene at temperatures 4–9 K higher than the default maximum emission temperature in the Model of Emissions of Gases and Aerosols from Nature (MEGAN). New basal emission rate measurements were obtained at the standard conditions of 303 K leaf temperature and 1000 µmol m−2 s−1 photosynthetically active radiation and converted into landscape emission factors. We applied the eucalypt temperature responses and emission factors to Australian trees within MEGAN and ran the CSIRO Chemical Transport Model for three summertime campaigns in Australia. Compared to the default model, the new temperature responses resulted in less isoprene emission in the morning and more during hot afternoons, improving the statistical fit of modelled to observed ambient isoprene. Compared to current conditions, an additional 2 ppb of isoprene is predicted in 2050, causing hourly increases up to 21 ppb of ozone and 24-hourly increases of 0.4 µg m−3 of aerosol in Sydney. A 550 ppm CO2 atmosphere in 2050 mitigates these peak Sydney ozone mixing ratios by 4 ppb. Nevertheless, these forecasted increases in ozone are up to one-fifth of the hourly Australian air quality limit, suggesting that anthropogenic NOx should be further reduced to maintain healthy air quality in future.

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Application of Fuzzy Inference System in the Prediction of Air Quality Index

Journal of Computing Research and Innovation ◽

10.24191/jcrinn.v6i3.242 ◽

2021 ◽

Vol 6 (3) ◽

pp. 75-85

Author(s):

Nor Hayati Shafii ◽

Nur Aini Mohd Ramle ◽

Rohana Alias ◽

Diana Sirmayunie Md Nasir ◽

Nur Fatihah Fauzi

Keyword(s):

Air Pollution ◽

Air Quality ◽

Fuzzy Inference System ◽

Quality Index ◽

Fuzzy Inference ◽

Average Concentration ◽

Air Quality Index ◽

Inference System ◽

Proposed Model ◽

The Impact

Air pollution is the presence of substances in the atmosphere that are harmful to the health of humans and other living beings. It is caused by solid and liquid particles and certain gases that are suspended in the air. The air pollution index (API) or also known as air quality index (AQI) is an indicator for the air quality status at any area. It is commonly used to report the level of severity of air pollution to public and to identify the poor air quality zone. The AQI value is calculated based on average concentration of air pollutants such as Particulate Matter 10 (PM10), Ozone (O3), Carbon Dioxide (CO2), Sulfur Dioxide (SO2) and Nitrogen Dioxide (NO2). Predicting the value of AQI accurately is crucial to minimize the impact of air pollution on environment and human health. The work presented here proposes a model to predict the AQI value using fuzzy inference system (FIS). FIS is the most well-known application of fuzzy logic and has been successfully applied in many fields. This method is proposed as the perfect technique for dealing with environmental well known and tackling the choice made below uncertainty. There are five levels or indicators of AQI, namely good, moderate, unhealthy, very unhealthy, and hazardous. This measurement is based on classification made from the Department of Environment (DOE) under the Ministry of Science, Technology, and Innovation (MOSTI). The results obtained from the actual data are compared with the results from the proposed model. With the accuracy rate of 93%, it shows that the proposed model is meeting the highest standard of accuracy in forecasting the AQI value.

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