El Niño driven haze over the Southern Malaysian Peninsula and Borneo

Assessing local and transboundary fine particulate matter pollution and sectoral contributions in Southeast Asia during haze months of 2015-2019

While previous studies have investigated haze events over Southeast Asia (SEA), local and transboundary contributions of various emission sources to haze months over the entire SEA have yet to be assessed comprehensively and systematically. We utilized the Particle Source Apportionment Technique (PSAT) to quantify the spatial local, transboundary, and sectoral contributions to PM2.5 over SEA during the haze months of 2015-2019. Results show that local emission contributions accounted for 56.1 % ~ 94.2 % of PM2.5 in Indonesia, Philippines, Vietnam, and Thailand. Transboundary contributions (23.1 % ~ 57.6 %) from Indonesia notably influenced maritime SEA. Vietnam (15.6 % ~ 39.1 %) and super-regional (17.0 % ~ 34.3 %) contributions outside the SEA exerted remarkable impacts on mainland SEA. Among different sectors, fire emissions contributed the most to PM2.5 over maritime SEA (23.0 % ~ 68.6 %) during the studied haze months, whereas residential and other emissions were the main contributors to mainland SEA (27.2 % ~ 36.7 %). Regarding the source species, primary PM2.5 accounted for the majority of PM2.5. VOC and SO2 composed most of the secondary PM2.5 due to massive VOC emissions in the region and the priority reaction of NH3 with sulfuric acid (H2SO4) to form ammonium sulfate. Besides, the intensified haze months in Oct 2015 and Sep 2019 were characterized by more intensive fire emissions in the region and the climatic variability-induced meteorological effects that provided favorable condition for transboundary air pollution (56.9 % and 44.9 %, respectively, for maritime SEA, as well as 46.0 % and 37.7 %, respectively, for mainland SEA in the two studied haze months). The haze months can be attributed to the notable drought conditions amidst global climatic phenomena such as El Niño and positive Indian Ocean Dipole (IOD) in Oct 2015 and Sep 2019, respectively.

Global distribution, trends and types of active fire occurrences

Fire occurrence is synonymous to terrestrial ecosystems and an important component of the Earth system. Climate change, vegetation characteristics, and human activity regulate fire occurrence and spread, however, fires also interact with them in multiple ways. Due to the complicated mechanisms of interactions between fire and land use or cover, the spatial distribution, change trends and land use or cover types of fire occurrences exist wide discrepancies in different regions or countries around the world. Therefore, the quantitative and spatial relationship and differences between fire and land use or cover at the global scale remain poorly understood systematically. Here, we combine active fire and land cover products during 2001-2020 to explore the spatio-temporal features, trends, and types of active fires from global to continental scales. Globally, the annual changes of monthly active fire occurrences kept a dramatic increase in first two or three years but a circuitous decrease since then. Most areas prevailingly experienced active fires for once to five times, a small part of areas clustered in Africa, Southeast Asia, and South America experienced active fires for over five times in the last 20-years. In particular, above 60 % of active fires (re-)occurred in forest and 20-25 % in cropland, whereas grassland and construction land only accounted for about 5 % and less than 2 % respectively. Driven by active fires, the conversion of forest to cropland accounted for nearly 60 % and the transition of cropland to forest (about 10 %) followed and formed an interactive circle. Our findings improve the understanding of fire-land cover change interactions, particularly agricultural expansion and forest loss driven by active fires. Future efforts on agricultural expansion, urban safety, carbon sequestration and biodiversity conservation should take the results of this research into account.

Application of CHIRPS dataset in the selection of rain-based indices for drought assessments in Johor River Basin, Malaysia

This paper aims to select the most appropriate rain-based meteorological drought index for detecting drought characteristics and identifying tropical drought events in the Johor River Basin (JRB). Based on a multi-step approach, the study evaluated seven drought indices, including the Rainfall Anomaly Index (RAI), Standardized Precipitation Index (SPI), China-Z Index (CZI), Modified China-Z Index (MCZI), Percent of Normal (PN), Deciles Index (DI), and Z-Score Index (ZSI), based on the CHIRPS rainfall gridded-based datasets from 1981 to 2020. Results showed that CZI, MCZI, SPI, and ZSI outperformed the other indices based on their correlation and linearity (R2 = 0.96-0.99) along with their ranking based on the Compromise Programming Index (CPI). The historical drought evaluation revealed that MCZI, SPI, and ZSI performed similarly in detecting drought events, but SPI was more effective in detecting spatial coverage and the occurrence of 'very dry' and 'extremely dry' drought events. Based on SPI, the study found that the downstream area, north-easternmost area, and eastern boundary of the basin were more prone to higher frequency and longer duration droughts. Furthermore, the study found that prolonged droughts are characterized by episodic drought events, which occur with one to three months of 'relief period' before another drought event occurs. The study revealed that most drought events that coincide with El Niño, positive Indian Ocean Dipole (IOD), and negative Madden-Julian Oscillation (MJO) events, or a combination of these events, may worsen drought conditions. The application of CHIRPS datasets enables better spatiotemporal mapping and prediction of drought for JRB, and the output is pertinent for improving water management strategies and adaptation measures. Understanding spatiotemporal drought conditions is crucial to ensuring sustainable development and policies through better regulation of human activities. The framework of this research can be applied to other river basins in Malaysia and other parts of Southeast Asia.

Clustering of Environmental Parameters and the Risk of Acute Ischaemic Stroke

Acute ischaemic stroke (AIS) risk on days with similar environmental profiles remains unknown. We investigated the association between clusters of days with similar environmental parameters and AIS incidence in Singapore. We grouped calendar days from 2010 to 2015 with similar rainfall, temperature, wind speed, and Pollutant Standards Index (PSI) using k-means clustering. Three distinct clusters were formed 'Cluster 1' containing high wind speed, 'Cluster 2' having high rainfall, and 'Cluster 3' having high temperatures and PSI. We aggregated the number of AIS episodes over the same period with the clusters and analysed their association using a conditional Poisson regression in a time-stratified case-crossover design. Comparing the three clusters, Cluster 3 had the highest AIS occurrence (IRR 1.09; 95% confidence interval (CI) 1.05-1.13), with no significant difference between Clusters 1 and 2. Subgroup analyses in Cluster 3 showed that AIS risk was amplified in the elderly (≥65 years old), non-smokers, and those without a history of ischaemic heart disease/atrial fibrillation/vascular heart disease/peripheral vascular disease. In conclusion, we found that AIS incidence may be higher on days with higher temperatures and PSI. These findings have important public health implications for AIS prevention and health services delivery during at-risk days, such as during the seasonal transboundary haze.

Recovery of Carbon and Vegetation Diversity 23 Years after Fire in a Tropical Dryland Forest of Indonesia

Understanding the recovery rate of forest carbon stocks and biodiversity after disturbance, including fire, is vital for developing effective climate-change-mitigation policies and actions. In this study, live and dead carbon stocks aboveground, belowground, and in the soil to a 30 cm depth, as well as tree and shrub species diversity, were measured in a tropical lowland dry forest, 23 years after a fire in 1998, for comparison with adjacent unburned reference forests. The results showed that 23 years since the fire was insufficient, in this case, to recover live forest carbon and plant species diversity, to the level of the reference forests. The total carbon stock, in the recovering 23-year-old forest, was 199 Mg C ha−1 or about 90% of the unburned forest (220 Mg C ha−1), mainly due to the contribution of coarse woody debris and an increase in the 5–10 cm soil horizon’s organic carbon, in the burned forest. The carbon held in the live biomass of the recovering forest (79 Mg C ha−1) was just over half the 146 Mg C ha−1 of the reference forest. Based on a biomass mean annual increment of 6.24 ± 1.59 Mg ha−1 yr−1, about 46 ± 17 years would be required for the aboveground live biomass to recover to equivalence with the reference forest. In total, 176 plant species were recorded in the 23-year post-fire forest, compared with 216 in the unburned reference forest. The pioneer species Macaranga gigantea dominated in the 23-year post-fire forest, which was yet to regain the similar stand structural and compositional elements as those found in the adjacent unburned reference forest.

Hybridization of hierarchical clustering with persistent homology in assessing haze episodes between air quality monitoring stations

Haze has been a major issue afflicting Southeast Asian countries, including Malaysia, for the past few decades. Hierarchical agglomerative cluster analysis (HACA) is commonly used to evaluate the spatial behavior between areas in which pollutants interact. Typically, using HACA, the Euclidean distance acts as the dissimilarity measure and air quality monitoring stations are grouped according to this measure, thus revealing the most polluted areas. In this study, a framework for the hybridization of the HACA technique is proposed by considering the topological similarity (Wasserstein distance) between stations to evaluate the spatial patterns of the affected areas by haze episodes. For this, a tool in the topological data analysis (TDA), namely, persistent homology, is used to extract essential topological features hidden in the dataset. The performance of the proposed method is compared with that of traditional HACA and evaluated based on its ability to categorize areas according to the exceedance level of the particulate matter (PM₁₀). Results show that additional topological features have yielded better accuracy compared to without the case that does not consider topological features. The cluster validity indices are computed to verify the results, and the proposed method outperforms the traditional method, suggesting a practical alternative approach for assessing the similarity in air pollution behaviors based on topological characterizations.

Impacts of and adaptation to climate change on the oil palm in Malaysia: a systematic review

The interaction and the interplay of climate change with oil palm production in the Southeast Asia region are of serious concern. This particularly applies in Malaysia due to its rank as the second largest palm oil producer in the world. The anthropogenic activities and the agroecological practices in oil palm plantation, including excessive use of fertilisers, bush fire due to land clearing, and cultivation on peatland, have exacerbated the effects of climate change featuring extreme events, drought, flooding, heatwave, as well as infestation of pest and diseases. These adverse impacts on oil palm production highlight the significance of deploying effective adaptation strategies. The study aims to examine the impact of climate change on oil palm production and identify the farmers' adaptation strategies to the impacts of climate change in Malaysia. This study was conducted a comprehensive review of the articles published from 2000 to 2021 in the contexts of climate change and oil palm production in Malaysia. The review shows that climate change has a range of impacts on the oil palm production in Malaysia. As a result, several adaptation options were identified, such as breeding of hybrid varieties that are tolerant and resistant to heat; sustainable management of soil; pit and tranches to enhance water management in plantation areas; minimal use of fertilisers, herbicides, and pesticides; zero burning; and minimum tillage. The reviewed studies recommended the following to mitigate the adverse impacts of climate change: sustainable national policy on climate change, conservation of the existing carbon stock, effective management of tropical rainforest biodiversity, afforestation for carbon sequestration, and reduction in greenhouse gas (GHG) emission.

Energy Consumption and Spatial Assessment of Renewable Energy Penetration and Building Energy Efficiency in Malaysia: A Review

The development of sustainable energy systems is very important to addressing the economic, environmental, and social pressures of the energy sector. Globally, buildings consume up to 40% of the world’s total energy. By 2030, it is expected to increase to 50%. Therefore, the world is facing a great challenge to overcome these problems related to global energy production. Malaysia is one of the top consumers of primary energy in Asia. In 2018, primary energy consumption for Malaysia was 3.79 quadrillion btu at an average annual rate of 4.58%. In this paper, we have carried out a detailed literature review on several previous studies of energy consumption in the world, especially in Malaysia, and how geographical information system (GIS) methods have been used for the spatial assessment of energy efficiency. Indeed, strategies of energy efficiency are essential in energy policy that could be created using various approaches used for energy savings in buildings. The findings of this review reveal that, for estimating energy consumption, exploring renewable energy sources, and investigating solar radiation, several geographic information system techniques such as multiple criteria decision analysis (MCDA), machine learning (ML), and deep learning (DL) are mainly utilized. The result indicates that the fuzzy DS method can more reliably determine the optimal PV farm locations. The 3D models are also regarded as an effective tool for estimating solar radiation, since this method generates a 3D model exportable to software tools. In addition, GIS and 3D can contribute to several purposes, such as sunlight access to buildings in urban areas, city growth prediction models and analysis of the habitability of public places.

Coastal meteorology on the dispersion of air particles at the Bachok GAW Station

Meteorology over coastal region is a driving factor to the concentration of air particles and reactive gases. This study aims to conduct a research to determine the level of year-round air particles and the interaction of the meteorological driving factors with the particle number and mass in 2018, which is moderately influenced by Southeast Asian haze. We obtained the measurement data for particle number count (PNC), mass, reactive gases, and meteorological factors from a Global Atmospheric Watch (GAW) station located at Bachok Marine Research Center, Bachok, Kelantan, Malaysia. For various timeseries and correlation analyses, a 60-second resolution of the data has been averaged hourly and daily and visualized further. Our results showed the slight difference in particle behavior that is either measured by unit mass or number count at the study area. Diurnal variations showed that particles were generally high during morning and night periods. Spike was observed in August for PM_2.5/PNC_2.5 and PM₁₀/PNC₁₀ and in November for PM_Coarse/PNC_Coarse. From a polar plot, the particles came from two distinct sources (e.g., seaside and roadside) at the local scale. Regional wind vector shows two distinct wind-blown directions from northeast and southwest. The air mases were transported from northeast (e.g., Philippines, mainland China, and Taiwan) or southwest (e.g., Sumatra) region. Correlation analysis shows that relative humidity, wind direction, and pressure influence the increase in particles, whereas negative correlation with temperature is observed, and wind speed may have a potential role on the decline of particle concentration. The particles at the study area was highly influenced by the changes in regional wind direction and speed.

Carbon balance of tropical peat forests at different fire history and implications for carbon emissions

Accurate assessment of tropical peat forest carbon stocks and impact of fires on carbon pools is required to determine the magnitude of emissions to the atmosphere and to support emissions reduction policies. We assessed total aboveground carbon (AGC) in biomass pools including trees, shrubs, deadwood, litter and char, and peat carbon to develop empirical estimates of peat swamp forest carbon stocks in response to fire and disturbance. In contrast to the common assumption that peat fires combust all AGC, we observed that about half of undisturbed forest AGC, equivalent to about 70 Mg C ha^-1, remains after one or two recent fires - mainly in dead trees, woody debris and pyrogenic carbon. Both recently burnt and repeatedly burnt peat forests store similar amounts of carbon in the top 10 cm of peat when compared with undisturbed forests (70 Mg C ha^-1), mainly due to increased peat bulk density after fires that compensates for their lower peat C%. The proportion of fuel mass consumed in fire, or combustion factor (CF), is required to make accurate estimates of peat fire emissions for both AGC and peat carbon. This study estimated a CF for AGC (CF_AGC) of 0.56, comparable to the default value of the Intergovernmental Panel on Climate Change (IPCC). This study estimated a varying CF for peat (CF_PEAT) that ranged from 0.4 to 0.68 as depth of burn increased. This revised CF_PEAT is one third to one half of the IPCC default value of 1.0. The current assumption of complete combustion of peat (CF = 1.0) is widely acknowledged in the literature as oversimplification and is not supported by our field observations or data. This study provides novel empirical data to improve estimates of peat forests carbon stocks and emissions from tropical peat fires.