Asian Journal of Atmospheric Environment最新文献

{"title":"A study on distribution characteristics of volatile organic compounds in Paju industrial complex area, using proton transfer reaction-time of flight mass spectrometry","authors":"So-Young Kim","doi":"10.1007/s44273-023-00023-8","DOIUrl":"10.1007/s44273-023-00023-8","url":null,"abstract":"<div><p>Paju City is located in the northwest of Gyeonggi-do, and its chemical emissions in 2020 were 1,287,917 kg, the 4th highest in Gyeonggi-do. In particular, the Munsan High-Tech Industrial Complex in Paju has LCD manufacturing plants and partner companies distributed in groups, and the volatile organic compounds used by these companies are causing many problems, such as causing bad odors, to the local community. In this sense, real-time analyzing equipment (proton-transfer-reaction time-of-flight mass spectrometry) was mounted on a vehicle for this study to look into the air quality around VOCs-using companies inside the High-tech Industrial Complex in Munsan, Paju from October 19 to October 21, 2020.</p><p>According to measurement results, toluene was detected the most at 25.7 ppb, followed by carbon tetrachloride (17.6 ppb), ethylbenzene (17.2 ppb), and xylene (8.5 ppb), which demonstrates that there is a need to control these substances to resolve the issue with VOCs in the region. In particular, benzene designated as the air quality standard was detected at 1.0 ppb in some sites, which is below the threshold (1.5 ppb). However, it was detected at 2.1 to 4.4 ppb, exceeding the threshold in most sites. Thus, continuous monitoring is expected to keep VOCs under control in Paju Industrial Complex down the road, using real-time measuring equipment.</p></div>","PeriodicalId":45358,"journal":{"name":"Asian Journal of Atmospheric Environment","volume":"18 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s44273-023-00023-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139391606","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CO2 removal characteristics of a novel type of moss and its potential for urban green roof applications","authors":"Ye-Bin Seo,&nbsp;Trieu-Vuong Dinh,&nbsp;Seungjae Kim,&nbsp;Da-Hyun Baek,&nbsp;Kweon Jung,&nbsp;Jo-Chun Kim","doi":"10.1007/s44273-023-00022-9","DOIUrl":"10.1007/s44273-023-00022-9","url":null,"abstract":"<div><p>The feasibility of a novel type of moss (Parkortanso No. 1 synthesized from <i>Racomitrium japonicum</i>, Dozy and Molk) to capture CO₂ in urban areas was demonstrated. The effects of light intensity (500, 1000, and 1500 µmol/m².s), ambient temperature (10 °C, 25 °C, and 35 °C), age (1-year-old and 3 years old), and leaf color (bright and dark green) on the CO₂ removal caused by the moss concerned were investigated. It was determined that stronger light intensity resulted in higher CO₂ removal by the target moss. The moss showed the best CO₂ capture at 25 °C, while the CO₂-capturing capacities declined when the ambient temperatures were 10 °C and 35 °C. Three years old bright green moss was found to have higher CO₂-capturing capacity than 1 year old. Similarly, bright green moss exhibited the best CO₂ uptake out of the mosses concerned. The highest net CO₂ emission of the moss was − 1.94 ± 0.72 kgCO₂/m².year, which was comparable to other moss and plant species. Consequently, the bright green and old Parkortanso No. 1 moss are recommended for a green roof application in terms of CO₂ capture.</p><h3>Graphical Abstract</h3>\u0000<div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":45358,"journal":{"name":"Asian Journal of Atmospheric Environment","volume":"17 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s44273-023-00022-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138972737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Long-term changes of rice yield loss estimated with AOT40 and M7 metrics using comprehensive ozone and rice cultivation data over South Korea","authors":"Jimin Lee,&nbsp;Jin-seok Han,&nbsp;Jinsu Park,&nbsp;Joon-Yeong Ahn,&nbsp;Gangwoong Lee","doi":"10.1007/s44273-023-00021-w","DOIUrl":"10.1007/s44273-023-00021-w","url":null,"abstract":"<div><p>This study examines the change in rice yield due to ozone exposure in South Korea using extended air quality monitoring data from 2000 onwards. Notably, the maximum daily 8-h average O₃ (MDA8O3) showed a substantial annual increase of 1 part per billion by volume (ppbv) from 1990 to 2021. AOT40 (accumulated dose of ozone over a threshold of 40 ppb) levels exceeded set thresholds in the early 2010s, and the M7 (mean 7-h ozone mixing ratio) index exhibited a parallel pattern, with a more pronounced increase than the AOT40 during the same period. Spatial variations of AOT40 and M7 metrics have been assessed annually across South Korea since 2000. Both metrics displayed spatial disparities, with higher values in western regions and lower values in the east. In particular, Dangjin and Seosan counties in Chungnam province experienced the greatest rice yield loss due to extensive rice cultivation area and high ozone exposure metrics. The quantified yield loss due to AOT40 increased from 127,000 in 2000 to 230,000 tonnes in 2021 with an increasing rate of 6500 tonnes per year. M7 indicated a rise in yield loss of 3500 tonnes per year, with yield losses growing from 32,000 in 2000 to 92,000 tonnes in 2021. Despite M7’s lower loss, it demonstrated a higher percentage increase of 188% over two decades, which was double AOT40’s 81%. While the decline in rice production was mainly linked to shrinking cultivation areas, its productivity was improved. Taking both factors into account, there was an unexplained 3% decrease in production over the same period. This discrepancy was close to the 2.5% rice yield loss attributed to the AOT40 metrics, suggesting that the majority of the additional 3% decline in production, surpassing improvements in productivity, could be attributed to the impacts of ozone exposure. We estimated the annual economic loss due to rice yield loss up to around 0.6 billion US dollars, corresponding to an annual rice production loss of 230,000 tonnes using AOT40. It is important to note that this value is expected to steadily worsen as ozone levels increase. This underscores the urgency of taking swift measures to reduce ozone levels, aiming not only to mitigate future economic losses but also to prevent potential health implications.</p></div>","PeriodicalId":45358,"journal":{"name":"Asian Journal of Atmospheric Environment","volume":"17 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s44273-023-00021-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138626174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Update of the year 2019 modeling emission inventory in China","authors":"Seoyeon Kim,&nbsp;Jinseok Kim,&nbsp;Hyejung Hu,&nbsp;Meongdo Jang,&nbsp;Jae-Bum Lee,&nbsp;Sung Chul Hong,&nbsp;Okgil Kim,&nbsp;Jung-Hun Woo","doi":"10.1007/s44273-023-00012-x","DOIUrl":"10.1007/s44273-023-00012-x","url":null,"abstract":"<div><p>Using updated emission inventories can enhance the accuracy of air quality forecast models. Given China’s rapid economic growth and Korea’s geographical and meteorological position on the windward side of China, updating China’s emission inventory has become particularly crucial for Korea’s air quality modeling. This study aimed to develop an updated version of China’s Emission Inventory in Comprehensive Regional Emissions for Atmospheric Transport Experiments version 3 for the base year of 2019 (CREATEv3 (YR 2019)). To achieve this goal, we utilized the Chinese emission inventory of CREATEv3 for the base year of 2015 (CREATEv3 (YR 2015)) as a framework to incorporate the latest Chinese emission data from the Multi-resolution Emission Inventory Model for Climate and Air Pollution Research for the base year of 2019 (MEIC COVID-19 (YR 2019)) and update the inventory. The updated China’s annual emissions are now reflected in CREATEv3 (YR 2019), and the amounts are as follows: 132 Tg for CO, 21 Tg for NO_<i>x</i>, 8 Tg for SO₂, 7 Tg for PM_2.5, 9 Tg for NH₃, and 28 Tg for volatile organic compound (VOC). By comparing previous Chinese emission inventories with the updated inventory developed in this study, it was found that SO₂, NO_<i>x</i>, VOC, and NH₃ emissions were decreased. Therefore, using the updated inventory seemingly reduces the impact of China’s fine dust on Korea. By comparing emissions by pollutant and region in China using CREATEv3 (YR 2019), it was found that regions with high emissions of targeted pollutants strongly correlated with major industries operating in those areas. This study is expected to provide insights into China’s emission changes in 2019 and support air quality forecasting.</p></div>","PeriodicalId":45358,"journal":{"name":"Asian Journal of Atmospheric Environment","volume":"17 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s44273-023-00012-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138624816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Physicochemical characteristics and seasonal variations of PM2.5 in urban, industrial, and suburban areas in South Korea","authors":"Kyucheol Hwang,&nbsp;Jeongho Kim,&nbsp;Jae Young Lee,&nbsp;Jong-Sung Park,&nbsp;Sechan Park,&nbsp;Gahye Lee,&nbsp;Chang Hyeok Kim,&nbsp;Pilho Kim,&nbsp;Su Hyun Shin,&nbsp;Kwang Yul Lee,&nbsp;Joon-Young An,&nbsp;Jungmin Park,&nbsp;Jong Bum Kim","doi":"10.1007/s44273-023-00018-5","DOIUrl":"10.1007/s44273-023-00018-5","url":null,"abstract":"<div><p>Among countries that are a part of the Organization for Economic Co-operation and Development, South Korea is the most exposed to PM_2.5. Despite the country having implemented various strategies to limit PM_2.5 emissions, its concentrations are still high enough to pose serious environmental and health concerns. Herein, we monitored various physiochemical properties of PM_2.5 across different regions in South Korea from January 1 to December 31, 2021. Specifically, the study area consisted of the city center, industrial complexes, and suburban areas. Before analyzing dynamics of emissions specific to each site, the Clean Air Policy Support System data for the three areas were compared to elucidate their respective primary emission sources. The particle concentrations for the three areas were 21.8–26.44 µg/m³, with the highest concentrations being observed in March. All the three areas exhibited high ratios of NO₃⁻ across all seasons. The particle number concentrations in the three sites were 1.3–1.5 × 10⁷, and the peak points of the concentrations were different in every site: city center (40 nm), industrial complexes (60 nm), and suburban areas (80 nm). We also conducted potential source contribution function and conditional bivariate probability function analyses. These analyses were conducted to determine the inflow direction of the pollution sources for high PM_2.5 episodes. For the episodes that occurred in spring and winter, there were no differences in the PM_2.5 concentrations between the three sites. Overall, the insights gained from this study offer a framework for developing air-quality management policies in South Korea, specifically in the context of PM_2.5 emissions.</p></div>","PeriodicalId":45358,"journal":{"name":"Asian Journal of Atmospheric Environment","volume":"17 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s44273-023-00018-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138608776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combined effects of elevated air temperature and CO2 on growth, yield, and yield components of japonica rice (Oryza sativa L.)","authors":"Masahiro Yamaguchi,&nbsp;Nobuyuki Tazoe,&nbsp;Tomoki Nakayama,&nbsp;Tetsushi Yonekura,&nbsp;Takeshi Izuta,&nbsp;Yoshihisa Kohno","doi":"10.1007/s44273-023-00019-4","DOIUrl":"10.1007/s44273-023-00019-4","url":null,"abstract":"<div><p>In the region where heat stress has become evident, the elevation of air temperature could reduce yield of heat stress-susceptible crops, such as rice (<i>Oryza sativa</i> L.), which is a major food staple in Asia. In addition to air temperature, atmospheric CO₂ is projected to be elevated in the future. To project rice yield in the future, it is necessary to clarify the responses of rice to concurrent elevations of air temperature and atmospheric CO₂. In the present study, two japonica rice cultivars with different heat tolerance, Hinohikari (sensitive) and Nikomaru (tolerant), were grown in pots inside open-top chambers and exposed to elevated air temperature and/or CO₂. The degrees of increase in the air temperature and CO₂ concentration by the treatments were approximately 1 °C and 120 µmol mol⁻¹ (ppm). The study was conducted in Nagasaki, Japan, where heat stress on rice has become evident. Elevated air temperature significantly decreased both whole-plant growth and grain yield. Elevated CO₂ significantly increased the growth but significantly decreased the yield. The effects of elevated air temperature and elevated CO₂ on growth and yield did not significantly differ between two cultivars. In both cultivars, the main cause of yield reduction by both treatments was reduction in spikelet fertility, which is typical heat stress on rice. The elevated CO₂-induced reduction in spikelet fertility could be explained partially by high-temperature regime during flowering due to acceleration of heading and by increase in canopy temperature via stomatal closure in flag leaves. Because elevated air temperature and elevated CO₂ treatments additively reduced spikelet fertility in both cultivars, concurrent elevations of air temperature and CO₂ caused considerable reduction in grain yield.</p></div>","PeriodicalId":45358,"journal":{"name":"Asian Journal of Atmospheric Environment","volume":"17 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s44273-023-00019-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139200718","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction: Characteristics of STILT footprints driven by KIM model simulated meteorological fields: implication for developing near real-time footprints","authors":"Samuel Takele Kenea,&nbsp;Haeyoung Lee,&nbsp;Sangwon Joo,&nbsp;Miloslav Belorid,&nbsp;Shanlan Li,&nbsp;Lev D. Labzovskii,&nbsp;Sanghun Park","doi":"10.1007/s44273-023-00020-x","DOIUrl":"10.1007/s44273-023-00020-x","url":null,"abstract":"","PeriodicalId":45358,"journal":{"name":"Asian Journal of Atmospheric Environment","volume":"17 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s44273-023-00020-x.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142415172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Simultaneous Sampling of NO, NO2, HONO and HNO3 in the Atmosphere by a Filter-Pack Method","authors":"Takumi Oda,&nbsp;Yusuke Fujii,&nbsp;Norimichi Takenaka","doi":"10.5572/ajae.2022.006","DOIUrl":"10.5572/ajae.2022.006","url":null,"abstract":"<div><p>A simultaneous sampling method for gaseous nitric oxide (NO), nitrogen dioxide (NO₂), nitrous acid (HONO) and nitric acid (HNO₃) was developed by a filter-pack sampling method to measure these concentrations at low cost in areas where monitoring stations are not available or at multiple locations. HONO and HNO₃ gases were collected with a conventional filter-pack method. NO₂ was collected with a guaiacol-impregnated filter at a flow rate of 0.3 dm³ min⁻¹. NO was collected using guaiacol by oxidizing it to NO₂ with potassium permanganate at a 0.3 dm³ min⁻¹ flow rate. The optimum concentration of KMnO₄ in the immersion solution for the impregnated filter was 0.16 mol dm⁻³ (in 0.51 mol dm⁻³ H₂SO₄). The concentrations of NO and NO₂ measured by the filter-pack method were in good agreement with those measured by the chemiluminescence method. It was calculated that 60 ppb NO could be oxidized to NO₂ with the KMnO₄-impregnated filter for 183 hours at a 0.3 dm³ min⁻¹ flow rate. This is enough time for sampling in a real environment. This method was applied to measure NO, NO₂, HONO and HNO₃ in the atmosphere at three points around Osaka, Japan.</p></div>","PeriodicalId":45358,"journal":{"name":"Asian Journal of Atmospheric Environment","volume":"16 2","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.5572/ajae.2022.006.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70710516","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Changes in Inorganic Chemical Species in Fog Water over Delhi","authors":"Rahul Sheoran,&nbsp;Umesh Chandra Dumka,&nbsp;Hulivahana Nagaraju Sowmya,&nbsp;Deewan Singh Bisht,&nbsp;Atul Kumar Srivastava,&nbsp;Suresh Tiwari,&nbsp;Shiv Dev Attri,&nbsp;Philip Karl Hopke","doi":"10.5572/ajae.2021.092","DOIUrl":"10.5572/ajae.2021.092","url":null,"abstract":"<div><p>Heavy fogs occur during the winter period over the part of northern India and impact aviation, public transport, the economy, public life, etc. During winter, fog water (FW) and non-monsoonal rainwater (NMRW) samples were collected in Delhi, which is a highly polluted and populated megacity in northern India. The collected FW and NMRW samples were analyzed for their inorganic chemical constituents (F⁻, Cl⁻, SO₄²⁻, NO₃⁻, NH₄⁺, Na⁺, K⁺, Ca²⁺, and Mg²⁺). The volume-weighted mean (VWM) pH, conductivity, and total dissolved solids (TDS) of FW were 6.89, 206 μS cm⁻¹, and 107 mg L⁻¹, respectively, indicating the dominance of alkaline species. The total measured ionic constituents (TMIC) in FW and NMRW were 5,738 and 814 μeq L⁻¹, respectively, indicating highly concentrated FW in Delhi. The TMIC in FW were factors of 16 and 7 times more concentrated than MRW and NMRW samples, respectively. The concentrations of inorganic acidic species (SO₄²⁻ and NO₃⁻) in FW were much higher than in monsoon rainwater (MRW: 3 and 5 times) and NMRW (8 and 12 times), respectively. Also, the concentrations of SO₄²⁻ and NO₃ in NMRW were approximately double compared to MRW indicating higher acidic species concentrations during the winter season over Delhi region. Significant decadal growth in the mean concentrations of ionic species in FW (SO₄²⁻ - ~9 times; NH₄⁺ - double) were observed between 1985 and 2010. However, the nitrate decreased by ~28%. The higher SO₄²⁻ is likely from heavy-duty vehicles that burn sulfur-containing fuel. The anions in FW, MRW, and NMRW contributed 20, 42, and 43%. However, the cation contributions were 80, 58, and 57%, respectively. The anion contributions were lower in FW than MRW and NMRW indicating the weak formation of acidic species in fog water. The observed alkalinity suggests that it is unlikely for acid precipitation to be present in this region.</p></div>","PeriodicalId":45358,"journal":{"name":"Asian Journal of Atmospheric Environment","volume":"16 2","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.5572/ajae.2021.092.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70709220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association of Air Pollutant Index (API) on SARS-CoV-2 of Coronavirus Disease 2019 (COVID-19) in Malaysia","authors":"Samsuri Abdullah,&nbsp;Muhammad Azhari Imran,&nbsp;Amalina Abu Mansor,&nbsp;Ku Mohd Kalkausar Ku Yusof,&nbsp;Nazri Che Dom,&nbsp;Siti Khamisah Saijan,&nbsp;Siti Rohana Mohd Yatim,&nbsp;Ali Najah Ahmed,&nbsp;Marzuki Ismail","doi":"10.5572/ajae.2021.094","DOIUrl":"10.5572/ajae.2021.094","url":null,"abstract":"<div><p>Malaysia reported its first COVID-19 case on January 25, 2020, and the cases have continued to grow, necessitating the implementation of additional measures. Hence, determining the factors responsible for the significant increase in COVID-19 cases is the top priority issue for the government to take necessary action and ultimately restrain this virus before the vaccine availability. Researchers had predicted that air pollution had an indirect relationship with COVID-19 in terms of virus infections. As a result, this study focuses on the link between the Air Pollutant Index (API) and COVID-19 infections. The initial data set consists of daily confirmed COVID-19 cases in Malaysia and API readings obtained from the Ministry of Health (MOH) and the Department of the Environment (DOE). The results show that Klang (S22) recorded the highest mean of API which at 62.70 while the lowest is at Limbang (S37) (25.37). Next, due to the implementation of Movement Control Order (MCO) in Malaysia and reducing social movement, 27 stations recorded a good level of API compare to the stations that recorded moderate and unhealthy levels. There is positive relationship between API and COVID-19 at each of the region which are North 0.4% (R²=0.004), Central 2.1% (R²=0.021), South 0.04% (R²=0.0004), East 1.6% (R²=0.016), Sarawak 0.2% (R²=0.002), meanwhile Sabah recorded negative correlation at 4.3% (R²=0.043). To conclude, the API value did not have a strong relationship with the rising number of COVID-19 daily cases.</p></div>","PeriodicalId":45358,"journal":{"name":"Asian Journal of Atmospheric Environment","volume":"16 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.5572/ajae.2021.094.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70709368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}