Analysis of Southeast Asian pollution episode during June 2013 using satellite remote sensing datasets

Contribution of agricultural land conversion to global GHG emissions: A meta-analysis

Greenhouse gases (GHG) have extensive environmental effects by trapping heat and causing climate change and air pollution. Land plays a key role in the global cycles of GHG (i.e., carbon dioxide (CO₂), methane (CH₄), and nitrogen oxide (N₂O)), and land use change (LUC) can lead to the release of such gases into the atmosphere or the removal of them from the atmosphere. One of the most common forms of LUC is agricultural land conversion (ALC) where agricultural lands are converted for other uses. This study aimed to review 51 original papers from 1990 to 2020 that investigate the contribution of ALC to GHG emissions from a spatiotemporal perspective using a meta-analysis method. The results of spatiotemporal effects on GHG emissions showed that the effects were significant. The emissions were affected by different continent regions representing the spatial effects. The most significant spatial effect was relevant to African and Asian countries. In addition, the quadratic relationship between ALC and GHG emissions had the highest significant coefficients, showing an upward concave curve. Therefore, increasing ALC to more than 8 % of available land led to increasing GHG emissions during the economic development process. The implications of the current study are important for policymakers from two perspectives. First, to achieve sustainable economic development, policymaking should prevent the conversion of more than 90 % of agricultural land to other uses based on the turning point of the second model. Second, policies to control global GHG emissions should take into account spatial effects (e.g., continental Africa and Asia), which show the highest contribution to GHG emissions.

Investigation of the Exposure of Schoolchildren to Ultrafine Particles (PM0.1) during the COVID-19 Pandemic in a Medium-Sized City in Indonesia

The health risk of schoolchildren who were exposed to airborne fine and ultrafine particles (PM0.1) during the COVID-19 pandemic in the Jambi City (a medium-sized city in Sumatra Island), Indonesia was examined. A questionnaire survey was used to collect information on schoolchildren from selected schools and involved information on personal profiles; living conditions; daily activities and health status. Size-segregated ambient particulate matter (PM) in school environments was collected over a period of 24 h on weekdays and the weekend. The personal exposure of PM of eight selected schoolchildren from five schools was evaluated for a 12-h period during the daytime using a personal air sampler for PM0.1 particles. The schoolchildren spent their time mostly indoors (~88%), while the remaining ~12% was spent in traveling and outdoor activities. The average exposure level was 1.5~7.6 times higher than the outdoor level and it was particularly high for the PM0.1 fraction (4.8~7.6 times). Cooking was shown to be a key parameter that explains such a large increase in the exposure level. The PM0.1 had the largest total respiratory deposition doses (RDDs), particularly during light exercise. The high level of PM0.1 exposure by indoor sources potentially associated with health risks was shown to be important.

Assessment and Prediction of Sea Level Trend in the South Pacific Region

Sea level rise is an important and topical issue in the South Pacific region and needs an urgent assessment of trends for informed decision making. This paper presents mean sea level trend assessment using harmonic analysis and a hybrid deep learning (DL) model based on the Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) technique, Convolutional Neural Network (CNN), Gated Recurrent Unit (GRU) and Neighbourhood Component Analysis (NCA) to build a highly accurate sea level forecasting model for three small islands (Fiji, Marshall Island and Papua New Guinea (PNG)) in the South Pacific. For a 20-year period, the estimated mean sea level rise per year from the harmonic computation is obtained: 112 mm for PNG, 98 mm for Marshall Island and 52 mm for Fiji. The DL procedure uses climate and environment-based remote sensing satellite (MODIS, GLDAS-2.0, MODIS TERRA, MERRA-2) predictor variables with tide gauge base mean sea level (MSL) data for model training and development for forecasting. The developed CEEMDAN-CNN-GRU as the objective model is benchmarked by comparison to the hybrid model without data decomposition, CNN-GRU and standalone models, Decision Trees (DT) and Support Vector Regression (SVR). All model performances are evaluated using reliable statistical metrics. The CEEMDAN-CNN-GRU shows superior accuracy when compared with other standalone and hybrid models. It shows an accuracy of >96% for correlation coefficient and an error of <1% for all study sites.

Impact of biomass burnings in Southeast Asia on air quality and pollutant transport during the end of the 2019 dry season

At the end of the dry season, March and April in Southeast Asia (SEA), agricultural refuse burnings occur over the region, mainly in the countries of Myanmar, Thailand, Laos, Cambodia and Vietnam, in preparation for the wet rice plantation. In this study, the impact of biomass burnings at the height of the burning period in March 2019 in mainland SEA on air quality and pollutant transport is modelled using the Weather Research Forecast WRF-Chem air quality model with emission input from the National Center for Atmospheric Research (NCAR) Fire Emission Inventory from NCAR (FINN). FINN is derived from satellite remote sensing data and species emission factors. A simulation of the dispersion of pollutants from biomass burnings from 13 to 19 March 2019, when the burnings was most intense, was performed. Validation of the model prediction using observed meteorological and pollutant data such as AOD measurements on ground from AERONET (Aerosol Robotic Network) and data from MODIS and CALIPSO satellites is carried out at various sites in the region. The results show that impact on air quality was most pronounced in Thailand and Laos but the effect of biomass burnings in mainland SEA at the end of the dry season is widespread in terms of pollutant dispersion and population exposure over the whole region and beyond. It is also shown that the transport of pollutants from biomass burnings in SEA to southern China, Taiwan and beyond is facilitated by the Truong Son mountain range, when under westerly wind, acting as a launching pad to uplift the pollutant plumes to higher altitude which then can be dispersed widely and transported farther from the biomass burning sources in Thailand and Laos.

Global warming, environmental security and its geo-economic dimensions case study: Caspian Sea level changes on the balance of transit channels

BACKGROUND

Global warming and climate change are considered as important environmental problems. Environmental security is more pronounced with regard to the Caspian Sea. Due to the geopolitical and geo-economic dimensions on the one hand, and its unique characteristics on the other, this large lake is considerably fragile against environmental challenges. In fact, the innate isolation of the Caspian Sea makes its conditions with regard to global warming unique. Using a descriptive-analytical method and library and valid article references, this study seeks to answer the question: "what are the effects of global warming on environmental security and what challenges does it pose to the Caspian Sea from the geo-economic point of view?"

METHODS

And Also maps and charts related to the research topic were collected and plotted in the GIS. In the next step, using a descriptive-analytical method based on geopolitical perspectives, especially environmental geopolitical studies and internet searches, we analyze the spatial effects of this universal phenomenon in the context of environmental geopolitical systems.

RESULTS

The findings indicate that global warming will pose a large spectrum of challenges and problems to the Caspian Sea from the destruction of its ecosystems to the complete transformation of its nature. This research has studied global warming and its effects on the sea level changes of the Caspian Sea and particularly the level of water in the transit channels of the Caspian Sea from the geo-economic point of view.

CONCLUSION

The results show that fluctuations in the water level of the Caspian Sea, in addition to environmental challenges, narrow the balance of its transit channels and threaten the geo-economics and environmental security of the Caspian Sea.

Isotope constraints of the strong influence of biomass burning to climate-forcing Black Carbon aerosols over Southeast Asia

Black Carbon (BC) deteriorates air quality and contributes to climate warming, yet its regionally- and seasonally-varying emission sources are poorly constrained. Here we employ natural abundance radiocarbon (¹⁴C) measurements of BC intercepted at a northern Malaysia regional receptor site, Bachok, to quantify the relative biomass vs. fossil source contributions of atmospheric BC, in a first year-round study for SE Asia (December 2015-December 2016). The annual average ¹⁴C signature suggests as large contributions from biomass burning as from fossil fuel combustion. This is similar to findings from analogous measurements at S Asian receptors sites (~50% biomass burning), while E Asia sites are dominated by fossil emission (~20% biomass burning). The ¹⁴C-based source fingerprinting of BC in the dry spring season in SE Asia signals an even more elevated biomass burning contribution (~70% or even higher), presumably from forest, shrub and agricultural fires. This is consistent with this period showing also elevated ratio of organic carbon to BC (up from ~5 to 30) and estimates of BC emissions from satellite fire data. Hence, the present study emphasizes the importance of mitigating dry season vegetation fires in SE Asia.

A high-resolution emission inventory of air pollutants from primary crop residue burning over Northern India based on VIIRS thermal anomalies

Emissions from the crop residue burning adversely affect the regional and global air quality including public health. In this study, a district-wise comprehensive emission inventory of key pollutants (PM_2.5, PM₁₀, CO, CO₂, SO₂, NOx, N₂O, NH₃, CH₄, NMVOC, EC, OC, PAH) emitted during primary crop residue burning was developed using activity data for the major agrarian states of north India for the agricultural year 2017-18. The emissions were scaled to the spatial resolution of 1 km grid to study the spatial distribution of crop residue burning activities using VIIRS Thermal anomalies datasets. An estimated 20.3 Mt and 9.6 Mt of crop residue were burned in Punjab and Haryana, resulting in an emission of 137.2 Gg and 56.9 Gg of PM_2.5 and 163.7 Gg and 72.1 of PM₁₀ Gg for respective states. The emissions of EC, OC, and PAHs were 8.6 Gg, 45.7 Gg, and 0.08 Gg in Punjab, whereas in Haryana emissions were 3.7 Gg, 17.7 Gg, and 0.03 Gg, respectively. The results show that rice and wheat crops were major contributor to residue burnt at the field (>90%) leading to the high load of atmospheric emissions in the IGP region. Further, CO₂ equivalent greenhouse gas emissions were 34.8 Tg and 17.3 Tg for Punjab and Haryana, respectively. Around 30000 and 8500 active fires were detected by VIIRS over the agricultural area of Punjab and Haryana during the studied year. The GIS-based bottom-up approach using gridded emission inventory shows pollutant distribution dominates over the south-western part of Punjab and north-western region of Haryana. The proximity of these regions to Delhi and transboundary movement of emissions towards Indo-Gangetic plains causes high air pollution episodes. The high-resolution inventory of various pollutants will be useful for regional air quality models to better predict and manage the hotspot of air pollution.

The burden of acute conjunctivitis attributable to ambient particulate matter pollution in Singapore and its exacerbation during South-East Asian haze episodes

INTRODUCTION

Urban air quality in South-East Asia is influenced by local and transboundary sources of air pollutants. Research studies have well characterized the short-term effects of air pollution on cardiovascular and respiratory health but less so on ocular health. We investigated the relationship between air pollution and acute conjunctivitis in Singapore, a tropical city-state located in South-East Asia.

METHODS

Assuming a negative-binomial distribution, we examined the short-term associations between all-cause acute conjunctivitis reports from 2009 to 2018 and contemporaneous ambient air pollutant concentrations using a time-series analysis. In separate pollutant models for PM_2.5 and PM₁₀, we fitted fractional polynomials to investigate the linearity between air pollutant exposures and conjunctivitis, adjusting for long-term trend, seasonality, climate variability, public holidays, immediate and lagged exposure effects, and autocorrelation.

RESULTS

There were 261,959 acute conjunctivitis reports over the study period. Every 10 μg/m³ increase in PM_2.5 was associated with a 3.8% (Incidence Rate Ratio (IRR): 1.038, 95% Confidence Interval (CI): 1.029-1.046, p < 0.001) cumulative increase in risk of conjunctivitis over the present and subsequent week. Every 10 μg/m³ increase in PM₁₀ was associated with a 2.9% (Incidence Rate Ratio (IRR): 1.029, 95% Confidence Interval (CI): 1.022-1.036, p < 0.001) cumulative increase in risk of conjunctivitis over the present and subsequent week. Acute conjunctivitis reports exhibited an inverse dependence on ambient air temperature and relative humidity variability. Approximately 3% of all acute conjunctivitis reports were attributable to PM_2.5. Particulate matter attributed acute conjunctivitis was disproportionately higher during transboundary haze episodes.

CONCLUSION

Our study strengthens the evidence linking particulate matter exposure to an increased risk of conjunctival disease, with a disproportionately higher disease burden during South-East Asia transboundary haze episodes. Our findings underscore the importance of reducing the health impact of indigenous and transboundary sources of ambient particulate matter pollution.

COVID-19's impact on the atmospheric environment in the Southeast Asia region

Since its first appearance in Wuhan, China at the end of 2019, the new coronavirus (COVID-19) has evolved a global pandemic within three months, with more than 4.3 million confirmed cases worldwide until mid-May 2020. As many countries around the world, Malaysia and other southeast Asian (SEA) countries have also enforced lockdown at different degrees to contain the spread of the disease, which has brought some positive effects on natural environment. Therefore, evaluating the reduction in anthropogenic emissions due to COVID-19 and the related governmental measures to restrict its expansion is crucial to assess its impacts on air pollution and economic growth. In this study, we used aerosol optical depth (AOD) observations from Himawari-8 satellite, along with tropospheric NO2 column density from Aura-OMI over SEA, and ground-based pollution measurements at several stations across Malaysia, in order to quantify the changes in aerosol and air pollutants associated with the general shutdown of anthropogenic and industrial activities due to COVID-19. The lockdown has led to a notable decrease in AOD over SEA and in the pollution outflow over the oceanic regions, while a significant decrease (27% - 30%) in tropospheric NO2 was observed over areas not affected by seasonal biomass burning. Especially in Malaysia, PM10, PM2.5, NO2, SO2, and CO concentrations have been decreased by 26-31%, 23-32%, 63-64%, 9-20%, and 25-31%, respectively, in the urban areas during the lockdown phase, compared to the same periods in 2018 and 2019. Notable reductions are also seen at industrial, suburban and rural sites across the country. Quantifying the reductions in major and health harmful air pollutants is crucial for health-related research and for air-quality and climate-change studies.

Time-Stratified Case Crossover Study of the Association of Outdoor Ambient Air Pollution With the Risk of Acute Myocardial Infarction in the Context of Seasonal Exposure to the Southeast Asian Haze Problem

Background

Prior studies have demonstrated the association of air pollution with cardiovascular deaths. Singapore experiences seasonal transboundary haze. We investigated the association between air pollution and acute myocardial infarction (AMI) incidence in Singapore.

Methods and Results

We performed a time‐stratified case‐crossover study on all AMI cases in the Singapore Myocardial Infarction Registry (2010–2015). Exposure on days where AMI occurred (case days) were compared with the exposure on days where AMI did not occur (control days). Control days were chosen on the same day of the week earlier and later in the same month and year. We fitted conditional Poisson regression models to daily AMI incidence to include confounders such as ambient temperature, rainfall, wind‐speed, and Pollutant Standards Index. We assessed relationships between AMI incidence and Pollutant Standards Index in the entire cohort and subgroups of individual‐level characteristics. There were 53 948 cases. Each 30‐unit increase in Pollutant Standards Index was association with AMI incidence (incidence risk ratio [IRR] 1.04, 95% CI 1.03–1.06). In the subgroup of ST‐segment–elevation myocardial infarction the IRR was 1.00, 95% CI 0.98 to 1.03, while for non–ST‐segment–elevation myocardial infarction, the IRR was 1.08, 95% CI 1.05 to 1.10. Subgroup analyses showed generally significant. Moderate/unhealthy Pollutant Standards Index showed association with AMI occurrence with IRR 1.08, 95% CI 1.05 to 1.11 and IRR 1.09, 95% CI 1.01 to 1.18, respectively. Excess risk remained elevated through the day of exposure and for >2 years after.

Conclusions

We found an effect of short‐term air pollution on AMI incidence, especially non–ST‐segment–elevation myocardial infarction and inpatient AMI. These findings have public health implications for primary prevention and emergency health services during haze.

Size-fractionated carbonaceous aerosols down to PM0.1 in southern Thailand: Local and long-range transport effects

In this study, size-fractionated particulate matters (PM) down to ultrafine (PM_0.1) particles were collected using a cascade air sampler with a PM_0.1 stage, in Hat Yai city, Songkhla province, southern Thailand during the year 2018. The particle-bound carbonaceous aerosols (CA) as elemental carbon (EC) and organic carbon (OC) were quantified with the thermal/optical reflectance method following the IMPROVE_TOR protocol. The concentrations of different temperature carbon fractions (OC1-OC4, EC1-EC3 and PyO) in the size-fractionated PM were evaluated to discern OC and EC correlations as well as those between char-EC and soot-EC. The results showed that biomass burning, motor vehicle, and secondary organic aerosols (SOC) all contributed to the size-fractionated PM. The OC/EC ratios ranged from 2.90 to 4.30 over the year, with the ratios of PM_2.5-10 being the highest, except during the open biomass burning period. The concentration of CA was found to increase during the pre-monsoon season and had its peak value in the PM_0.5-1.0 fraction. The long-range transport of PMs from Indonesia, southwest of Thailand toward southern Thailand became more obvious during the pre-monsoon season. Transported plumes from biomass burning in Indonesia may increase the concentration of OC and EC both in the fine (PM_0.5-1.0 and PM_1.0-2.5) and coarse (PM_2.5-10 and PM_>10) fractions. The OC fraction in PM_0.1 was also shown to be significantly affected by the transported plumes during the pre-monsoon season. Good OC and EC correlations (R² = 0.824-0.915) in the fine particle fractions indicated that they had common sources such as fossil fuel combustion. However, the lower and moderate correlations (R² = 0.093-0.678) among the coarser particles suggesting that they have a more complex pattern of emission sources during the dry and monsoon seasons. This indicates the importance of focusing emission control strategies on different PM particle sizes in southern Thailand.

Air-Pollution Control in an Emergent Market: Does It Work? Evidence from Romania

Economic development in a national and international context must be based on a sustainability strategy established on the systemic interaction between the economic, sociocultural, and ecological environments. Today, the world is confronted by many challenges related to climate change and natural-resource flows, including waste streams resulting from economic activity. The need for national and European environmental standards and the work of an environment monitoring authority to reduce air pollution are highlighted by economic and industrial activities. Thus, our research focused on determining if emissions of sulfur dioxide (SO₂), nitrogen (NO₂), and particulate matter 10 (PM₁₀) are influenced by planned and unplanned inspections made by competent authorities from Romania. We built a regression model that estimates the influence of economic measures imposed by the authorities on reducing industrial air pollution. Preliminary results showed that the number of inspections negatively influences air pollution, indicating that national and local authorities in Romania are striving to maintain air quality and are conducting more inspections when air pollution is high.

Impact of Air Pollution and Seasonal Haze on Neurological Conditions: A Review

Introduction: Air pollution is a global problem and seasonal haze from forest clearing and peat land burning in Indonesia is an annual phenomenon in Southeast Asia. As neurological disorders comprise 6.3% of the burden of disease globally, we reviewed evidence of the association between common neurological conditions and air pollution exposure, and summarised existing data on the impact of the haze phenomenon in Southeast Asia. Materials and Methods: A PubMed search for relevant studies on air pollution, Alzheimer’s disease (AD), dementia, epilepsy, haze, headache, migraine, stroke, Parkinson’s disease (PD) and neuromuscular conditions was performed. There were 52 articles which were relevant and were reviewed. Results: There were associations between short-term air pollution exposure with AD, epilepsy, ischaemic stroke and migraine. Long-term air pollution exposure was associated with AD, amyotrophic lateral sclerosis, dementia and ischaemic stroke. Evidence on the link between air pollution and PD was inconsistent. Currently, there is no specific data on the effects haze has on neurological conditions in Southeast Asia. Conclusion: Air pollution is associated with increased risk of certain common neurological disorders. More specific studies are needed to investigate the impact of seasonal haze on neurological conditions in Southeast Asia. Key words: Alzheimer’s disease, Epilepsy, Migraine, Parkinson’s disease, Stroke

The Uncharacteristic Occurrence of the June 2013 Biomass-Burning Haze Event in Southeast Asia: Effects of the Madden-Julian Oscillation and Tropical Cyclone Activity

One of the worst haze events to ever hit Peninsular Malaysia occurred in June 2013 due to smoke from Riau, Central Sumatra. While biomass-burning in the region is common, the early occurrence of a haze episode of this magnitude was uncharacteristic of the seasonality of extreme fire events, which usually occur between August and October in the Maritime Continent (MC). This study aims to investigate the phenomenology of the June 2013 haze event and its underlying meteorological forcing agents. The aerosol and meteorological environment during the event is examined using the Moderate Resolution Imaging Spectroradiometer (MODIS) active fire hotspot detections and aerosol optical thickness retrievals, satellite-based precipitation retrievals, and meteorological indices. These datasets are then supported by a WRF-Chem simulation to provide a comprehensive picture of the event’s meteorology and aerosol transport phenomenology. While extreme fire events are more characteristic of El Nino years, the MODIS fire count over the MC in June for the years 2001–2015 was highest in 2013 when neutral El Nino/Southern Oscillation (ENSO) conditions prevailed. Although, the mean daily precipitation for June 2013 was below average for June 2003–2015. An early active tropical cyclone (TC) season occurred in 2013, and results show that the combined induced subsidence and flow enhancement due to TC Bebinca and the dry phases of a strong Madden–Julian Oscillation (MJO) event contributed to the event intensification. Results also show that Bebinca induced a decrease in surface relative humidity of at least 10% over Riau, where fire hotspots were concentrated.

The Relationship Between Air Pollution and All-Cause Mortality in Singapore

Ambient air pollution is a risk factor for both acute and chronic diseases and poses serious health threats to the world population. We aim to study the relationship between air pollution and all-cause mortality in the context of a city-state exposed to the Southeast Asian haze problem. The primary exposure was ambient air pollution, as measured by the Pollutants Standards Index (PSI). The outcome of interest was all-cause mortality from 2010–2015. A time-stratified case-crossover design was performed. A conditional Poisson regression model, including environmental variables such as PSI, temperature, wind speed, and rainfall, was fitted to the daily count of deaths to estimate the incidence rate ratio (IRR) of mortality per unit increase in PSI, accounting for overdispersion and autocorrelation. To account for intermediate exposure effects (maximum lag of 10 days), a distributed lag non-linear model was used. There were 105,504 deaths during the study period. Increment in PSI was significantly associated with an increased risk of mortality. The adjusted IRR of mortality per the 10-unit increase in PSI was 1.01 (95%CI = 1.00–1.01). The lag effect was stronger when PSI was in the unhealthy range compared to the good and moderate ranges. At lag = 7 days, PSI appeared to have an adverse effect on mortality, although the effect was not significant. These findings provide evidence on the general health hazard of exposure to air pollution and can potentially guide public health policies in the region.

Spatiotemporal analysis of ground and satellite-based aerosol for air quality assessment in the Southeast Asia region

Satellite observations for regional air quality assessment rely on comprehensive spatial coverage, and daily monitoring with reliable, cloud-free data quality. We investigated spatiotemporal variation and data quality of two global satellite Aerosol Optical Depth (AOD) products derived from MODIS and VIIRS imagery. AOD is considered an essential atmospheric parameter strongly related to ground Particulate Matter (PM) in Southeast Asia (SEA). We analyze seasonal variation, urban/rural area influence, and biomass burning effects on atmospheric pollution. Validation indicated a strong relationship between AERONET ground AOD and both MODIS AOD (R² = 0.81) and VIIRS AOD (R² = 0.68). The monthly variation of satellite AOD and AERONET AOD reflects two seasonal trends of air quality separately for mainland countries including Myanmar, Laos, Cambodia, Thailand, Vietnam, and Taiwan, Hong Kong, and for maritime countries consisting of Indonesia, Philippines, Malaysia, Brunei, Singapore, and Timor Leste. The mainland SEA has a pattern of monthly AOD variation in which AODs peak in March/April, decreasing during wet season from May-September, and increasing to the second peak in October. However, in maritime SEA, AOD concentration peaks in October. The three countries with the highest annual satellite AODs are Singapore, Hong Kong, and Vietnam. High urban population proportions in Singapore (40.7%) and Hong Kong (21.6%) were associated with high AOD concentrations as expected. AOD values in SEA urban areas were a factor of 1.4 higher than in rural areas, with respective averages of 0.477 and 0.336. The AOD values varied proportionately to the frequency of biomass burning in which both active fires and AOD peak in March/April and September/October. Peak AOD in September/October in some countries could be related to pollutant transport of Indonesia forest fires. This study analyzed satellite aerosol product quality in relation to AERONET in SEA countries and highlighted framework of air quality assessment over a large, complicated region.

Modeling and efficient quantified risk assessment of haze causation system in China related to vehicle emissions with uncertainty consideration

Urban haze has become a severe pollution problem in China. Vehicle emission may be a key factor leading to haze pollution in China's megacities due to the rapid growth of vehicles and corresponding energy consumption. Until now, the haze formation mechanisms in China remain highly uncertain, which have not yet been understood quantitatively. In this work, an efficient modified haze causation system related to vehicle emissions is developed for reliable quantified risk assessment of urban haze in China's megacities. And fuzzy mathematical theory combining with fault tree approach is investigated and employed as the analysis tool/strategy. To provide objective basis for the reliability and practicability of the quantitative assessment results, an efficient data extraction strategy and relevant mathematical models are proposed and developed for the probability determination of basic risk events. Besides, the probability uncertainty of basic risk events during the data extraction is taken into account, where the occurrence probability of basic events is described as triangular fuzzy number, the quantitative analysis results will be more reliable and more tally with the actual situation. After the haze causation system related to vehicle emissions is established along with the identification of all critical risk factors related to vehicle emissions, Beijing and Tianjin are taken as illustrated case studies for the quantified risk assessment of haze causation system related to vehicle emissions in China. All the analysis results demonstrated that this work may provide a useful and effective tool/strategy for efficient quantified risk assessment and risk management of haze causation system relate to vehicle emission in China.

The Relationship Between Ambient Air Pollution and Acute Ischemic Stroke: A Time-Stratified Case-Crossover Study in a City-State With Seasonal Exposure to the Southeast Asian Haze Problem

STUDY OBJECTIVE

Studies are divided on the short-term association of air pollution with stroke. Singapore is exposed to seasonal transboundary haze. We aim to investigate the association between air pollution and stroke incidence in Singapore.

METHODS

We performed a time-stratified case-crossover analysis on all ischemic stroke cases reported to the Singapore Stroke Registry from 2010 to 2015. Exposure on days was compared with control days on which exposure did not occur. Control days were chosen on the same day of the week earlier and later in the same month in the same year. We fitted a conditional Poisson regression model to daily stroke incidence that included Pollutant Standards Index and environmental confounders. The index was categorized according to established classification (0 to 50=good, 51 to 100=moderate, and ≥101=unhealthy). We assessed the relationship between stroke incidence and Pollutant Standards Index in the entire cohort and in predetermined subgroups of individual-level characteristics.

RESULTS

There were 29,384 ischemic stroke cases. Moderate and unhealthy Pollutant Standards Index levels showed association with stroke occurrence, with incidence risk ratio 1.10 (95% confidence interval 1.06 to 1.13) and 1.14 (95% confidence interval 1.03 to 1.25), respectively. Subgroup analyses showed generally significant association, except in Indians and nonhypertensive patients. The association was significant in subgroups aged 65 years or older, women, Chinese, nonsmokers and those with history of diabetes, hypertension, and hyperlipidemia. Stratified by age and smoking, the risk diminished in smokers of all ages. Risk remained elevated for 5 days after exposure.

CONCLUSION

We found a short-term elevated risk of ischemic stroke after exposure to air pollution. These findings have public health implications for stroke prevention and emergency health services delivery.

Analysis of air pollution over Hanoi, Vietnam using multi-satellite and MERRA reanalysis datasets

Air pollution is one of the major environmental concerns in Vietnam. In this study, we assess the current status of air pollution over Hanoi, Vietnam using multiple different satellite datasets and weather information, and assess the potential to capture rice residue burning emissions with satellite data in a cloud-covered region. We used a timeseries of Ozone Monitoring Instrument (OMI) Ultraviolet Aerosol Index (UVAI) satellite data to characterize absorbing aerosols related to biomass burning. We also tested a timeseries of 3-hourly MERRA-2 reanalysis Black Carbon (BC) concentration data for 5 years from 2012–2016 and explored pollution trends over time. We then used MODIS active fires, and synoptic wind patterns to attribute variability in Hanoi pollution to different sources. Because Hanoi is within the Red River Delta where rice residue burning is prominent, we explored trends to see if the residue burning signal is evident in the UVAI or BC data. Further, as the region experiences monsoon-influenced rainfall patterns, we adjusted the BC data based on daily rainfall amounts. Results indicated forest biomass burning from Northwest Vietnam and Laos impacts Hanoi air quality during the peak UVAI months of March and April. Whereas, during local rice residue burning months of June and October, no increase in UVAI is observed, with slight BC increase in October only. During the peak BC months of December and January, wind patterns indicated pollutant transport from southern China megacity areas. Results also indicated severe pollution episodes during December 2013 and January 2014. We observed significantly higher BC concentrations during nighttime than daytime with peaks generally between 2130 and 0030 local time. Our results highlight the need for better air pollution monitoring systems to capture episodic pollution events and their surface-level impacts, such as rice residue burning in cloud-prone regions in general and Hanoi, Vietnam in particular.

Improved rice residue burning emissions estimates: Accounting for practice-specific emission factors in air pollution assessments of Vietnam

In Southeast Asia and Vietnam, rice residues are routinely burned after the harvest to prepare fields for the next season. Specific to Vietnam, the two prevalent burning practices include: a). piling the residues after hand harvesting; b). burning the residues without piling, after machine harvesting. In this study, we synthesized field and laboratory studies from the literature on rice residue burning emission factors for PM2.5. We found significant differences in the resulting burning-practice specific emission factors, with 16.9 g kg-2(±6.9) for pile burning and 8.8 g kg-2(±3.5) for non-pile burning. We calculated burning-practice specific emissions based on rice area data, region-specific fuel-loading factors, combined emission factors, and estimates of burning from the literature. Our results for year 2015 estimate 180 Gg of PM2.5 result from the pile burning method and 130 Gg result from non-pile burning method, with the most-likely current emission scenario of 150 Gg PM2.5 emissions for Vietnam. For comparison purposes, we calculated emissions using generalized agricultural emission factors employed in global biomass burning studies. These results estimate 80 Gg PM2.5, which is only 44% of the pile burning-based estimates, suggesting underestimation in previous studies. We compare our emissions to an existing all-combustion sources inventory, results show emissions account for 14-18% of Vietnam's total PM2.5 depending on burning practice. Within the highly-urbanized and cloud-covered Hanoi Capital region (HCR), we use rice area from Sentinel-1A to derive spatially-explicit emissions and indirectly estimate residue burning dates. Results from HYSPLIT back-trajectory analysis stratified by season show autumn has most emission trajectories originating in the North, while spring has most originating in the South, suggesting the latter may have bigger impact on air quality. From these results, we highlight locations where emission mitigation efforts could be focused and suggest measures for pollutant mitigation. Our study demonstrates the need to account for emissions variation due to different burning practices.

Satellites may underestimate rice residue and associated burning emissions in Vietnam

In this study, we estimate rice residue, associated burning emissions, and compare results with existing emissions inventories employing a bottom-up approach. We first estimated field-level post-harvest rice residues, including separate fuel-loading factors for rice straw and rice stubble. Results suggested fuel-loading factors of 0.27 kg m^-2 (±0.033), 0.61 kg m^-2 (±0.076), and 0.88 kg m^-2 (±0.083) for rice straw, stubble, and total post-harvest biomass, respectively. Using these factors, we quantified potential emissions from rice residue burning and compared our estimates with other studies. Our results suggest total rice residue burning emissions as 2.24 Gg PM_2.5, 36.54 Gg CO and 567.79 Gg CO₂ for Hanoi Province, which are significantly higher than earlier studies. We attribute our higher emission estimates to improved fuel-loading factors; moreover, we infer that some earlier studies relying on residue-to-product ratios could be underestimating rice residue emissions by more than a factor of 2.3 for Hanoi, Vietnam. Using the rice planted area data from the Vietnamese government, and combining our fuel-loading factors, we also estimated rice residue PM_2.5 emissions for the entirety of Vietnam and compared these estimates with an existing all-sources emissions inventory, and the Global Fire Emissions Database (GFED). Results suggest 75.98 Gg of PM_2.5 released from rice residue burning accounting for 12.8% of total emissions for Vietnam. The GFED database suggests 42.56 Gg PM_2.5 from biomass burning with 5.62 Gg attributed to agricultural waste burning indicating satellite-based methods may be significantly underestimating emissions. Our results not only provide improved residue and emission estimates, but also highlight the need for emissions mitigation from rice residue burning.

Study on spatial distribution of crop residue burning and PM2.5 change in China

With China as the study area, MODIS MOD14A1 and MCD12Q1 products were used to derive daily crop residue burning spots from 2014 to 2015. After vectorization of crop residue burning pixels and with the use of fishnet, burning density distribution maps were eventually completed. Meanwhile, the daily air quality data from 150 cities in 2014 and 285 cities in 2015 were used to obtain daily and monthly PM_2.5 distribution maps with the Kriging interpolation. The results indicate that crop residue burning occurs in a seasonal pattern, and its spatial distribution is closely related to farming activities. The annual PM_2.5 in China decreased 11.81% from 2014 to 2015, and the distribution of PM_2.5 in China's east and north is always higher than in China's west and south. Furthermore, the changes in PM_2.5 exhibit a hysteresis after crop residue burning in summer and autumn-winter. Regarding summer crop residue burning in China's middle-east, the r between crop residue burning spots and PM_2.5 is 0.6921 (P < 0.01) in 2014 and 0.5620 (P < 0.01) in 2015, while the correlation coefficient of autumn-winter crop residue burning in China's northeast is slightly lower with an r of 0.5670 (P < 0.01) in 2014 and 0.6213 (P < 0.01) in 2015. In autumn-winter, crop residue burning can induce evident PM_2.5 increase in China's northeast, and that is more obvious than summer crop residue burning in China's middle-east. Furthermore, when data of summer and autumn-winter crop residue burning from 2014 to 2015 are compared, we can see that the change in number of crop residue burning spots significant changes PM_2.5 in these regions. Both the summer and autumn-winter crop residue burning areas presented spatial consistency with high PM_2.5. By contrast, the results from many aspects indicated that the crop residue burning in spring did not cause a notable change of PM_2.5.

Comparison of global inventories of CO2 emissions from biomass burning during 2002-2011 derived from multiple satellite products

This study compared five widely used globally gridded biomass burning emissions inventories for the 2002-2011 period (Global Fire Emissions Database 3 (GFED3), Global Fire Emissions Database 4 (GFED4), Global Fire Assimilation System 1.0 (GFAS1.0), Fire INventory from NCAR 1.0 (FINN1.0) and Global Inventory for Chemistry-Climate studies-GFED4 (G-G)). Average annual CO2 emissions range from 6521.3 to 9661.5 Tg year(-1) for five inventories, with extensive amounts in Africa, South America and Southeast Asia. Coefficient of Variation for Southern America, Northern and Southern Africa are 30%, 39% and 48%. Globally, the majority of CO2 emissions are released from savanna burnings, followed by forest and cropland burnings. The largest differences among the five inventories are mainly attributable to the overestimation of CO2 emissions by FINN1.0 in Southeast Asia savanna and cropland burning, and underestimation in Southern Africa savanna and Amazon forest burning. The overestimation in Africa by G-G also contributes to the differences.