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A practical illustration of spatial smoothing methods for disconnected regions with INLA: spatial survey on overweight and obesity in Malaysia

Mohamad MS, Abdul Maulud KN, Faes C

Int J Health Geogr, 2023 Jun 21;22(1):14.
PMID: 37344913 DOI: 10.1186/s12942-023-00336-5

BACKGROUND: National prevalence could mask subnational heterogeneity in disease occurrence, and disease mapping is an important tool to illustrate the spatial pattern of disease. However, there is limited information on techniques for the specification of conditional autoregressive models in disease mapping involving disconnected regions. This study explores available techniques for producing district-level prevalence estimates for disconnected regions, using as an example childhood overweight in Malaysia, which consists of the Peninsular and Borneo regions separated by the South China Sea. We used data from Malaysia National Health and Morbidity Survey conducted in 2015. We adopted Bayesian hierarchical modelling using the integrated nested Laplace approximation (INLA) program in R-software to model the spatial distribution of overweight among 6301 children aged 5-17 years across 144 districts located in two disconnected regions. We illustrate different types of spatial models for prevalence mapping across disconnected regions, taking into account the survey design and adjusting for district-level demographic and socioeconomic covariates.
RESULTS: The spatial model with split random effects and a common intercept has the lowest Deviance and Watanabe Information Criteria. There was evidence of a spatial pattern in the prevalence of childhood overweight across districts. An increasing trend in smoothed prevalence of overweight was observed when moving from the east to the west of the Peninsular and Borneo regions. The proportion of Bumiputera ethnicity in the district had a significant negative association with childhood overweight: the higher the proportion of Bumiputera ethnicity in the district, the lower the prevalence of childhood overweight.
CONCLUSION: This study illustrates different available techniques for mapping prevalence across districts in disconnected regions using survey data. These techniques can be utilized to produce reliable subnational estimates for any areas that comprise of disconnected regions. Through the example, we learned that the best-fit model was the one that considered the separate variations of the individual regions. We discovered that the occurrence of childhood overweight in Malaysia followed a spatial pattern with an east-west gradient trend, and we identified districts with high prevalence of overweight. This information could help policy makers in making informed decisions for targeted public health interventions in high-risk areas.
Prediction of municipal solid waste generation using nonlinear autoregressive network

Younes MK, Nopiah ZM, Basri NE, Basri H, Abushammala MF, Maulud KN

Environ Monit Assess, 2015 Dec;187(12):753.
PMID: 26573690 DOI: 10.1007/s10661-015-4977-5

Most of the developing countries have solid waste management problems. Solid waste strategic planning requires accurate prediction of the quality and quantity of the generated waste. In developing countries, such as Malaysia, the solid waste generation rate is increasing rapidly, due to population growth and new consumption trends that characterize society. This paper proposes an artificial neural network (ANN) approach using feedforward nonlinear autoregressive network with exogenous inputs (NARX) to predict annual solid waste generation in relation to demographic and economic variables like population number, gross domestic product, electricity demand per capita and employment and unemployment numbers. In addition, variable selection procedures are also developed to select a significant explanatory variable. The model evaluation was performed using coefficient of determination (R(2)) and mean square error (MSE). The optimum model that produced the lowest testing MSE (2.46) and the highest R(2) (0.97) had three inputs (gross domestic product, population and employment), eight neurons and one lag in the hidden layer, and used Fletcher-Powell's conjugate gradient as the training algorithm.
Textural characteristics and sedimentary environment of sediment at eroded and deposited regions in the severely eroded coastline of Batu Pahat, Malaysia

Wan Mohtar WHM, Nawang SAB, Abdul Maulud KN, Benson YA, Azhary WAHWM

Sci Total Environ, 2017 Nov 15;598:525-537.
PMID: 28454026 DOI: 10.1016/j.scitotenv.2017.04.093

This study investigates the textural characteristics of sediments collected at eroded and deposited areas of highly severed eroded coastline of Batu Pahat, Malaysia. Samples were taken from systematically selected 23 locations along the 67km stretch of coastline and are extended to the fluvial sediments of the main river of Batu Pahat. Grain size distribution analysis was conducted to identify its textural characteristics and associated sedimentary transport behaviours. Sediments obtained along the coastline were fine-grained material with averaged mean size of 7.25 ϕ, poorly sorted, positively skewed and has wide distributions. Samples from eroded and deposition regions displayed no distinctive characteristics and exhibited similar profiles. The high energy condition transported the sediments as suspension, mostly as pelagic and the sediments were deposited as shallow marine and agitated deposits. The fluvial sediments of up to 3km into the river have particularly similar profile of textural characteristics with the neighbouring marine sediments from the river mouth. Profiles were similar with marine sediments about 3km opposite the main current and can go up to 10km along the current of Malacca Straits.
Spatial and temporal risk quotient based river assessment for water resources management

Wan Mohtar WHM, Abdul Maulud KN, Muhammad NS, Sharil S, Yaseen ZM

Environ Pollut, 2019 May;248:133-144.
PMID: 30784832 DOI: 10.1016/j.envpol.2019.02.011

Malaysia depends heavily on rivers as a source for water supply, irrigation, and sustaining the livelihood of local communities. The evolution of land use in urban areas due to rapid development and the continuous problem of illegal discharge have had a serious adverse impact on the health of the country's waterways. Klang River requires extensive rehabilitation and remediation before its water could be utilised for a variety of purposes. A reliable and rigorous remediation work plan is needed to identify the sources and locations of streams that are constantly polluted. This study attempts to investigate the feasibility of utilising a temporal and spatial risk quotient (RQ) based analysis to make an accurate assessment of the current condition of the tributaries in the Klang River catchment area. The study relies on existing data sets on Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Suspended Solids (TSS), and Ammonia (NH3) to evaluate the water quality at thirty strategic locations. Analysis of ammonia pollution is not only based on the limit established for river health but was expanded to include the feasibility of using the water for water intake, recreational activities, and sustaining fish population. The temporal health of Klang River was evaluated using the Risk Matrix Approach (RMA) based on the frequency of RQ > 1 and associated colour-coded hazard impacts. By using the developed RMA, the hazard level for each parameter at each location was assessed and individually mapped using Geographic Information System (GIS). The developed risk hazard mapping has high potential as one of the essential tools in making decisions for a cost-effective river restoration and rehabilitation.
Fulltext Relationships of Local Food and Physical Activity Environments With Overweight in 5- to 17-Year-Old Malaysian Children

Mohamad MS, Mahadir Naidu B, Virtanen SM, Lehtinen-Jacks S, Abdul Maulud KN

Asia Pac J Public Health, 2023 Jan;35(1):34-41.
PMID: 36321506 DOI: 10.1177/10105395221135407

Evidence on the associations between built environment and overweight in children outside developed countries is scarce. We examined associations between access to local food and physical activity environments and overweight in 5- to 17-year-old Malaysians in two states with differing overweight levels. Information on children was measured in the National Health and Morbidity Survey 2015 and combined with Geographic Information System-derived data on local food and physical activity environments. Access to the built environment was measured by presence and distance from child's residence. Complete data were available for 880 children. Access to local food outlets and parks was higher and associated with higher occurrence of overweight in children living in the state with higher overweight prevalence. When adjusted for sociodemographic factors, higher presence of and shorter distance to convenience stores and parks were associated with overweight. Both built environment and children's sociodemographic backgrounds should be considered when planning interventions to curb the overweight epidemic in Malaysia.
GIS-Based Assessments of Neighborhood Food Environments and Chronic Conditions: An Overview of Methodologies

Ganasegeran K, Abdul Manaf MR, Safian N, Waller LA, Abdul Maulud KN, Mustapha FI

Annu Rev Public Health, 2023 Dec 07.
PMID: 38061019 DOI: 10.1146/annurev-publhealth-101322-031206

The industrial revolution and urbanization fundamentally restructured populations' living circumstances, often with poor impacts on health. As an example, unhealthy food establishments may concentrate in some neighborhoods and, mediated by social and commercial drivers, increase local health risks. To understand the connections between neighborhood food environments and public health, researchers often use geographic information systems (GIS) and spatial statistics to analyze place-based evidence, but such tools require careful application and interpretation. In this article, we summarize the factors shaping neighborhood health in relation to local food environments and outline the use of GIS methodologies to assess associations between the two. We provide an overview of available data sources, analytical approaches, and their strengths and weaknesses. We postulate next steps in GIS integration with forecasting, prediction, and simulation measures to frame implications for local health policies. Expected final online publication date for the Annual Review of Public Health, Volume 45 is April 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
Fulltext Hydrological and climate impacts on river characteristics of pahang river basin, Malaysia

Kamarudin MKA, Toriman ME, Abd Wahab N, Abu Samah MA, Abdul Maulud KN, Mohamad Hamzah F, et al.

Heliyon, 2023 Nov;9(11):e21573.
PMID: 38058642 DOI: 10.1016/j.heliyon.2023.e21573

The climate, geomorphological changes, and hydrological elements that have occurred have all influenced future flood episodes by increasing the likelihood and intensity of extreme weather occurrences like extreme precipitation events. River bank erosion is a natural geomorphic process that occurs in all channels. As modifications of sizes and channel shapes are made to transport the discharge, sediment abounds from the stream catchment, and floods are triggered dramatically. The aim of this study is to analyze the flood-sensitive regions along the Pahang River Basin and determine how climate and river changes would have an impact on flooding based on hydrometeorological data and information on river characteristics. The study is divided into three stages, namely the upstream, middle stream, and downstream of the Pahang River. The main primary hydrometeorological data and river characteristics, such as Sinuosity Index, Dominant Slope Range and Entrenchment Ratio collected as important inputs in the statistical analysis process. The statistical analyses, namely HACA, PCA, and Linear Regression applied in river classification. The result showed that the middle stream and downstream areas demonstrated the worst flooding affected by anthropogenic and hydrological factors. Rainfall distribution is one of the factors that contributed to the flood disaster. There are strong correlations between the Sinuosity Index (SI) and water level, which indicates that changes occurred at both planform and stream classification. The best management practices towards sustainability are based on the application of the outcomes that have been obtained after the analysis of Pahang River planform changes, Pahang River geometry, and the local rainfall pattern in the Pahang River Basin.
Fulltext How Socio-economic Inequalities Cluster People with Diabetes in Malaysia: Geographic Evaluation of Area Disparities Using a Non-parameterized Unsupervised Learning Method

Ganasegeran K, Abdul Manaf MR, Safian N, Waller LA, Mustapha FI, Abdul Maulud KN, et al.

J Epidemiol Glob Health, 2024 Mar;14(1):169-183.
PMID: 38315406 DOI: 10.1007/s44197-023-00185-2

Accurate assessments of epidemiological associations between health outcomes and routinely observed proximal and distal determinants of health are fundamental for the execution of effective public health interventions and policies. Methods to couple big public health data with modern statistical techniques offer greater granularity for describing and understanding data quality, disease distributions, and potential predictive connections between population-level indicators with areal-based health outcomes. This study applied clustering techniques to explore patterns of diabetes burden correlated with local socio-economic inequalities in Malaysia, with a goal of better understanding the factors influencing the collation of these clusters. Through multi-modal secondary data sources, district-wise diabetes crude rates from 271,553 individuals with diabetes sampled from 914 primary care clinics throughout Malaysia were computed. Unsupervised machine learning methods using hierarchical clustering to a set of 144 administrative districts was applied. Differences in characteristics of the areas were evaluated using multivariate non-parametric test statistics. Five statistically significant clusters were identified, each reflecting different levels of diabetes burden at the local level, each with contrasting patterns observed under the influence of population-level characteristics. The hierarchical clustering analysis that grouped local diabetes areas with varying socio-economic, demographic, and geographic characteristics offer opportunities to local public health to implement targeted interventions in an attempt to control the local diabetes burden.
Statistical and spatial analysis for soil heavy metals over the Murray-Darling river basin in Australia

Tao H, Al-Hilali AA, Ahmed AM, Mussa ZH, Falah MW, Abed SA, et al.

Chemosphere, 2023 Mar;317:137914.
PMID: 36682637 DOI: 10.1016/j.chemosphere.2023.137914

Heavy metals (HMs) are a vital elements for investigating the pollutant level of sediments and water bodies. The Murray-Darling river basin area located in Australia is experiencing severe damage to increased crop productivity, loss of soil fertility, and pollution levels within the vicinity of the river system. This basin is the most effective primary production area in Australia where agricultural productivity is increased the gross domastic product in the entire mainland. In this study, HMs contaminations are examined for eight study sites selected for the Murray-Darling river basin where the inverse Distance Weighting interpolation method is used to identify the distribution of HMs. To pursue this, four different pollution indices namely the Geo-accumulation index (Igeo), Contamination factor (CF), Pollution load index (PLI), single-factor pollution index (SPLI), and the heavy metal pollution index (HPI) are computed. Following this, the Pearson correlation matrix is used to identify the relationships among the two HM parameters. The results indicate that the conductivity and N (%) are relatively high in respect to using Igeo and PLI indexes for study sites 4, 6, and 7 with 2.93, 3.20, and 1.38, respectively. The average HPI is 216.9071 that also indicates higher level pollution in the Murray-Darling river basin and the highest HPI value is noted in sample site 1 (353.5817). The study also shows that the levels of Co, P, Conductivity, Al, and Mn are mostly affected by HMs and that these indices indicate the maximum HM pollution level in the Murray-Darling river basin. Finally, the results show that the high HM contamination level appears to influence human health and local environmental conditions.
Fulltext Spatial clustering of colorectal cancer in Malaysia

Syed Soffian SS, Mohammed Nawi A, Hod R, Abdul Maulud KN, Mohd Azmi AT, Hasim Hashim MH, et al.

Geospat Health, 2023 May 25;18(1).
PMID: 37246545 DOI: 10.4081/gh.2023.1158

INTRODUCTION: The rise in colorectal cancer (CRC) incidence becomes a global concern. As geographical variations in the CRC incidence suggests the role of area-level determinants, the current study was designed to identify the spatial distribution pattern of CRC at the neighbourhood level in Malaysia.
METHOD: Newly diagnosed CRC cases between 2010 and 2016 in Malaysia were identified from the National Cancer Registry. Residential addresses were geocoded. Clustering analysis was subsequently performed to examine the spatial dependence between CRC cases. Differences in socio-demographic characteristics of individuals between the clusters were also compared. Identified clusters were categorized into urban and semi-rural areas based on the population background.
RESULT: Most of the 18 405 individuals included in the study were male (56%), aged between 60 and 69 years (30.3%) and only presented for care at stages 3 or 4 of the disease (71.3%). The states shown to have CRC clusters were Kedah, Penang, Perak, Selangor, Kuala Lumpur, Melaka, Johor, Kelantan, and Sarawak. The spatial autocorrelation detected a significant clustering pattern (Moran's Index 0.244, p< 0.01, Z score >2.58). CRC clusters in Penang, Selangor, Kuala Lumpur, Melaka, Johor, and Sarawak were in urbanized areas, while those in Kedah, Perak and Kelantan were in semi-rural areas.
CONCLUSION: The presence of several clusters in urbanized and semi-rural areas implied the role of ecological determinants at the neighbourhood level in Malaysia. Such findings could be used to guide the policymakers in resource allocation and cancer control.
Fulltext The impact of climate change on coastal erosion in Southeast Asia and the compelling need to establish robust adaptation strategies

Dong WS, Ismailluddin A, Yun LS, Ariffin EH, Saengsupavanich C, Abdul Maulud KN, et al.

Heliyon, 2024 Feb 29;10(4):e25609.
PMID: 38375273 DOI: 10.1016/j.heliyon.2024.e25609

Climate change alters the climate condition and ocean environment, leading to accelerated coastal erosion and a shift in the coastline shape. From previous studies, Southeast Asia's coastal region is suffering from severe coastal erosion. It is most sensitive and vulnerable to climate change, has broad and densely populated coastlines, and is under ecological pressure. Efforts to systematically review these studies are still insufficient despite many studies on the climate change linked to coastal erosion, the correlation between coastal erosion and coastal communities, and the adaptative measures to address these issues and their effectiveness in Southeast Asia. Therefore, by analyzing the existing literature, the purpose of this review was to bridge the knowledge gap and identify the link between climate change and coastal erosion in Southeast Asia in terms of sea-level rise, storm surge, and monsoon patterns. The RepOrting standards for Systematic Evidence Syntheses (ROSES) guided the study protocol, including articles from the Scopus and Dimension databases. There were five main themes considered: 1) climate change impact, 2) contributing factors to coastal erosion, 3) coastal erosion impact on coastal communities, 4) adaptation measure and 5) effectiveness of adaptation measure using thematical analysis. Subsequently, nine sub-themes were produced from the themes. Generally, in Southeast Asia, coastal erosion was reflected by the rising sea level. Throughout reviewing past literature, an interesting result was explored. Storm surges also had the potential to affect coastal erosion due to alterations of the atmospheric system and seasonal monsoon as the result of climate change. Meanwhile, an assessment of current erosion control strategies in relation to the relative hydrodynamic trend was required to avoid the failure of defence structures and the resulting danger to coastal communities. Systematically reviewing the existing literature was critical, hence it could significantly contribute to the body of knowledge. It provides valuable information for interested parties, such as authorities, the public, researchers, and environmentalists, while comprehending existing adaptation practices. This kind of review could strategize adaptation and natural resource management in line with coastal communities' needs, abilities, and capabilities in response to environmental and other change forms.
Fulltext Factors associated with community volunteering among adults over the age of 50 in Malaysia

Sutan R, Alavi K, Sallahuddin SN, Abdul Manaf MR, Jaafar MH, Shahar S, et al.

PLoS One, 2024;19(5):e0302220.
PMID: 38753828 DOI: 10.1371/journal.pone.0302220

BACKGROUND: Community volunteering is defined as voluntary participation in activities and services to benefit the local community. It has potential benefits to promote social, physical, and mental well-being, and it enhances productive, healthy, and active aging. The tendency to volunteer varies across individuals and communities. There is limited knowledge of contributing factors influencing volunteering among Malaysian adults over the age of 50.
AIMS: The present study aims to assess the association of demographic, cultural, and social factors with volunteering among Malaysian adults over the age of 50.
METHODS: A cross-sectional study was conducted in 2020 involving 3,034 Malaysians aged 50 years and above across Malaysia, selected using a multi-stratified random sampling technique based on National Census 2020 data. A validated survey questionnaire to determine the demographic factor (age, sex, education level, employment status, health status, physical disability, and location of residence), cultural factor (ethnicity and religion), and social factor (social support, marital status, living arrangement, mode of transportation) that influence voluntary participation was distributed and collected. The association between these factors and volunteer participation was analysed using logistic regression models to identify significant predictors of voluntary participation among Malaysian adults over the age of 50.
RESULTS: A regression model indicates that living in rural areas (OR 2.03, 95% CI 1.63-2.53), having higher education level (Tertiary level: OR 2.77, 95% CI 1.86-4.13), being employed (OR 1.31, 95% CI 1.10-1.56), differences in ethnicity background (Chinese: OR 0.58, 95% CI 0.39-0.86) and ease of transportation (Driving private transport: OR 1.26, 95% CI 1.19-1.32; Public transport: OR 1.07, 95% CI 1.00-1.154) were significantly associated with volunteering with R2 Nagelkerke of 0.147.
CONCLUSION: Recognising various factors towards community volunteering should be addressed by policymakers and volunteer organisations to increase volunteer participation from potential adults over the age of 50 in promoting healthy and active ageing.
Fulltext A Geospatial Drug Abuse Risk Assessment and Monitoring Dashboard Tailored for School Students: Development Study With Requirement Analysis and Acceptance Evaluation

Al-Aboosi AM, Sheikh Abdullah SNH, Ismail R, Abdul Maulud KN, Nahar L, Zainol Ariffin KA, et al.

JMIR Hum Factors, 2024 Jul 30;11:e48139.
PMID: 39078685 DOI: 10.2196/48139

BACKGROUND: The enormous consequences of drugs include suicides, traffic accidents, and violence, affecting the individual, family, society, and country. Therefore, it is necessary to constantly identify and monitor the drug abuse rate among school-going youth. A geospatial dashboard is vital for the monitoring of drug abuse and related crime incidence in a decision support system.
OBJECTIVE: This paper mainly focuses on developing MyAsriGeo, a geospatial drug abuse risk assessment and monitoring dashboard tailored for school students. It introduces innovative functionality, seamlessly orchestrating the assessment of drug abuse usage patterns and risks using multivariate student data.
METHODS: A geospatial drug abuse dashboard for monitoring and analysis was designed and developed in this study based on agile methodology and prototyping. Using focus group and interviews, we first examined and gathered the requirements, feedback, and user approval of the MyAsriGeo dashboard. Experts and stakeholders such as the National Anti-Drugs Agency, police, the Federal Department of Town and Country Planning, school instructors, students, and researchers were among those who responded. A total of 20 specialists were involved in the requirement analysis and acceptance evaluation of the pilot and final version of the dashboard. The evaluation sought to identify various user acceptance aspects, such as ease of use and usefulness, for both the pilot and final versions, and 2 additional factors based on the Post-Study System Usability Questionnaire and Task-Technology Fit models were enlisted to assess the interface quality and dashboard sufficiency for the final version.
RESULTS: The MyAsriGeo geospatial dashboard was designed to meet the needs of all user types, as identified through a requirement gathering process. It includes several key functions, such as a geospatial map that shows the locations of high-risk areas for drug abuse, data on drug abuse among students, tools for assessing the risk of drug abuse in different areas, demographic information, and a self-problem test. It also includes the Alcohol, Smoking, and Substance Involvement Screening Test and its risk assessment to help users understand and interpret the results of student risk. The initial prototype and final version of the dashboard were evaluated by 20 experts, which revealed a significant improvement in the ease of use (P=.047) and usefulness (P=.02) factors and showed a high acceptance mean scores for ease of use (4.2), usefulness (4.46), interface quality (4.29), and sufficiency (4.13).
CONCLUSIONS: The MyAsriGeo geospatial dashboard is useful for monitoring and analyzing drug abuse among school-going youth in Malaysia. It was developed based on the needs of various stakeholders and includes a range of functions. The dashboard was evaluated by a group of experts. Overall, the MyAsriGeo geospatial dashboard is a valuable resource for helping stakeholders understand and respond to the issue of drug abuse among youth.
Spatial-temporal variations in surface ozone over Ushuaia and the Antarctic region: observations from in situ measurements, satellite data, and global models

Nadzir MSM, Ashfold MJ, Khan MF, Robinson AD, Bolas C, Latif MT, et al.

Environ Sci Pollut Res Int, 2018 Jan;25(3):2194-2210.
PMID: 29116536 DOI: 10.1007/s11356-017-0521-1

The Antarctic continent is known to be an unpopulated region due to its extreme weather and climate conditions. However, the air quality over this continent can be affected by long-lived anthropogenic pollutants from the mainland. The Argentinian region of Ushuaia is often the main source area of accumulated hazardous gases over the Antarctic Peninsula. The main objective of this study is to report the first in situ observations yet known of surface ozone (O3) over Ushuaia, the Drake Passage, and Coastal Antarctic Peninsula (CAP) on board the RV Australis during the Malaysian Antarctic Scientific Expedition Cruise 2016 (MASEC'16). Hourly O3 data was measured continuously for 23 days using an EcoTech O3 analyzer. To understand more about the distribution of surface O3 over the Antarctic, we present the spatial and temporal of surface O3 of long-term data (2009-2015) obtained online from the World Meteorology Organization of World Data Centre for greenhouse gases (WMO WDCGG). Furthermore, surface O3 satellite data from the free online NOAA-Atmospheric Infrared Sounder (AIRS) database and online data assimilation from the European Centre for Medium-Range Weather Forecasts (ECMWF)-Monitoring Atmospheric Composition and Climate (MACC) were used. The data from both online products are compared to document the data sets and to give an indication of its quality towards in situ data. Finally, we used past carbon monoxide (CO) data as a proxy of surface O3 formation over Ushuaia and the Antarctic region. Our key findings were that the surface O3 mixing ratio during MASEC'16 increased from a minimum of 5 ppb to ~ 10-13 ppb approaching the Drake Passage and the Coastal Antarctic Peninsula (CAP) region. The anthropogenic and biogenic O3 precursors from Ushuaia and the marine region influenced the mixing ratio of surface O3 over the Drake Passage and CAP region. The past data from WDCGG showed that the annual O3 cycle has a maximum during the winter of 30 to 35 ppb between June and August and a minimum during the summer (January to February) of 10 to 20 ppb. The surface O3 mixing ratio during the summer was controlled by photochemical processes in the presence of sunlight, leading to the depletion process. During the winter, the photochemical production of surface O3 was more dominant. The NOAA-AIRS and ECMWF-MACC analysis agreed well with the MASEC'16 data but twice were higher during the expedition period. Finally, the CO past data showed the surface O3 mixing ratio was influenced by the CO mixing ratio over both the Ushuaia and Antarctic regions. Peak surface O3 and CO hourly mixing ratios reached up to ~ 38 ppb (O3) and ~ 500 ppb (CO) over Ushuaia. High CO over Ushuaia led to the depletion process of surface O3 over the region. Monthly CO mixing ratio over Antarctic (South Pole) were low, leading to the production of surface O3 over the Antarctic region.

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