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A Phenome-Wide Association Study of genes associated with COVID-19 severity reveals shared genetics with complex diseases in the Million Veteran Program

The study aims to determine the shared genetic architecture between COVID-19 severity with existing medical conditions using electronic health record (EHR) data. We conducted a Phenome-Wide Association Study (PheWAS) of genetic variants associated with critical illness (n = 35) or hospitalization (n = 42) due to severe COVID-19 using genome-wide association summary data from the Host Genetics Initiative. PheWAS analysis was performed using genotype-phenotype data from the Veterans Affairs Million Veteran Program (MVP). Phenotypes were defined by International Classification of Diseases (ICD) codes mapped to clinically relevant groups using published PheWAS methods. Among 658,582 Veterans, variants associated with severe COVID-19 were tested for association across 1,559 phenotypes. Variants at the ABO locus (rs495828, rs505922) associated with the largest number of phenotypes (n rs495828 = 53 and n rs505922 = 59); strongest association with venous embolism, odds ratio (OR rs495828 1.33 (p = 1.32 x 10 –199 ), and thrombosis OR rs505922 1.33, p = 2.2 x10 -265 . Among 67 respiratory conditions tested, 11 had significant associations including MUC5B locus (rs35705950) with increased risk of idiopathic fibrosing alveolitis OR 2.83, p = 4.12 × 10 –191 ; CRHR1 (rs61667602) associated with reduced risk of pulmonary fibrosis, OR 0.84, p = 2.26× 10 –12 . The TYK2 locus (rs11085727) associated with reduced risk for autoimmune conditions, e.g., psoriasis OR 0.88, p = 6.48 x10 -23 , lupus OR 0.84, p = 3.97 x 10 –06 . PheWAS stratified by ancestry demonstrated differences in genotype-phenotype associations. LMNA (rs581342) associated with neutropenia OR 1.29 p = 4.1 x 10 –13 among Veterans of African and Hispanic ancestry but not European. Overall, we observed a shared genetic architecture between COVID-19 severity and conditions related to underlying risk factors for severe and poor COVID-19 outcomes. Differing associations between genotype-phenotype across ancestries may inform heterogenous outcomes observed with COVID-19. Divergent associations between risk for severe COVID-19 with autoimmune inflammatory conditions both respiratory and non-respiratory highlights the shared pathways and fine balance of immune host response and autoimmunity and caution required when considering treatment targets.

59 BASIC BIOLOGICAL SCIENCES↗

Mechanistic modelling of SARS-CoV-2 and other infectious diseases and the effects of therapeutics

Modern viral kinetic modeling and its application to therapeutics is a field that attracted the attention of the medical, pharmaceutical and modeling communities during the early days of the AIDS epidemic. Its successes lead to applications of modeling methods not only to HIV but a plethora of other viruses, such as hepatitis C virus (HCV), hepatitis B virus (HBV) and cytomegalovirus (CMV), which along with HIV cause chronic diseases, and viruses such as influenza, respiratory syncytial virus (RSV), West Nile virus (WNV), Zika virus, and SAR-CoV-2, which generally cause acute infections. Here we first review the historical development of mathematical models to understand HIV and HCV infections and the effects of treatment by fitting the models to clinical data. Furthermore, we then focus on recent efforts and contributions of applying these models towards understanding SARS-CoV-2 infection and highlight outstanding questions where modeling can provide crucial insights and help to optimize non-pharmaceutical and pharmaceutical interventions of the COVID-19 pandemic. The review is written from our personal perspective emphasizing the power of simple target cell limited models that provided important insights and then their evolution into more complex models that captured more of the virology and immunology. To quote Albert Einstein “Everything should be made as simple as possible, but not simpler”, and this idea underlies the modeling we describe below.

60 APPLIED LIFE SCIENCES↗

ChAdOx1 interacts with CAR and PF4 with implications for thrombosis with thrombocytopenia syndrome

Vaccines derived from chimpanzee adenovirus Y25 (ChAdOx1), human adenovirus type 26 (HAdV-D26), and human adenovirus type 5 (HAdV-C5) are critical in combatting the severe acute respiratory coronavirus 2 (SARS-CoV-2) pandemic. As part of the largest vaccination campaign in history, ultrarare side effects not seen in phase 3 trials, including thrombosis with thrombocytopenia syndrome (TTS), a rare condition resembling heparin-induced thrombocytopenia (HIT), have been observed. This study demonstrates that all three adenoviruses deployed as vaccination vectors versus SARS-CoV-2 bind to platelet factor 4 (PF4), a protein implicated in the pathogenesis of HIT. We have determined the structure of the ChAdOx1 viral vector and used it in state-of-the-art computational simulations to demonstrate an electrostatic interaction mechanism with PF4, which was confirmed experimentally by surface plasmon resonance. These data confirm that PF4 is capable of forming stable complexes with clinically relevant adenoviruses, an important step in unraveling the mechanisms underlying TTS.

60 APPLIED LIFE SCIENCES↗

Glycosylation of SARS-CoV-2: structural and functional insights

The COVID-19 pandemic is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Similar to other coronaviruses, its particles are composed of four structural proteins: spike (S), envelope (E), membrane (M), and nucleocapsid (N) proteins. S, E, and M proteins are glycosylated, and the N protein is phosphorylated. The S protein is involved in the interaction with the host receptor human angiotensin-converting enzyme 2 (hACE2), which is also heavily glycosylated. Recent studies have revealed several other potential host receptors or factors that can increase or modulate the SARS-CoV-2 infection. Interestingly, most of these molecules bear carbohydrate residues. While glycans acquired by the viruses through the hijacking of the host machinery help the viruses in their infectivity, they also play roles in immune evasion or modulation. Here, glycans play complex roles in viral pathobiology, both on their own and in association with carrier biomolecules, such as proteins or glycosaminoglycans (GAGs). Understanding these roles in detail can help in developing suitable strategies for prevention and therapy of COVID-19. In this review, we sought to emphasize the interplay of SARS-CoV-2 glycosylated proteins and their host receptors in viral attachment, entry, replication, and infection. Moreover, the implications for future therapeutic interventions targeting these glycosylated biomolecules are also discussed in detail.

59 BASIC BIOLOGICAL SCIENCES↗

Wildfire Smoke Adjustment Factors for Low-Cost and Professional PM 2.5 Monitors with Optical Sensors

Air quality monitors using low-cost optical PM 2.5 sensors can track the dispersion of wildfire smoke; but quantitative hazard assessment requires a smoke-specific adjustment factor (AF). This study determined AFs for three professional-grade devices and four monitors with low-cost sensors based on measurements inside a well-ventilated lab impacted by the 2018 Camp Fire in California (USA). Using the Thermo TEOM-FDMS as reference, AFs of professional monitors were 0.85 for Grimm mini wide-range aerosol spectrometer, 0.25 for TSI DustTrak, and 0.53 for Thermo pDR1500; AFs for low-cost monitors were 0.59 for AirVisual Pro, 0.48 for PurpleAir Indoor, 0.46 for Air Quality Egg, and 0.60 for eLichens Indoor Air Quality Pro Station. We also compared public data from 53 PurpleAir PA-II monitors to 12 nearby regulatory monitoring stations impacted by Camp Fire smoke and devices near stations impacted by the Carr and Mendocino Complex Fires in California and the Pole Creek Fire in Utah. Camp Fire AFs varied by day and location, with median (interquartile) of 0.48 (0.44–0.53). Adjusted PA-II 4-h average data were generally within ±20% of PM 2.5 reported by the monitoring stations. Adjustment improved the accuracy of Air Quality Index (AQI) hazard level reporting, e.g., from 14% to 84% correct in Sacramento during the Camp Fire.

47 OTHER INSTRUMENTATION↗

Modeling PAH Mixture Interactions in a Human In Vitro Organotypic Respiratory Model

One of the most significant challenges in human health risk assessment is to evaluate hazards from exposure to environmental chemical mixtures. Polycyclic aromatic hydrocarbons (PAHs) are a class of ubiquitous contaminants typically found as mixtures in gaseous and particulate phases in ambient air pollution associated with petrochemicals from Superfund sites and the burning of fossil fuels. However, little is understood about how PAHs in mixtures contribute to toxicity in lung cells. To investigate mixture interactions and component additivity from environmentally relevant PAHs, two synthetic mixtures were created from PAHs identified in passive air samplers at a legacy creosote site impacted by wildfires. The primary human bronchial epithelial cells differentiated at the air–liquid interface were treated with PAH mixtures at environmentally relevant proportions and evaluated for the differential expression of transcriptional biomarkers related to xenobiotic metabolism, oxidative stress response, barrier integrity, and DNA damage response. Component additivity was evaluated across all endpoints using two independent action (IA) models with and without the scaling of components by toxic equivalence factors. Both IA models exhibited trends that were unlike the observed mixture response and generally underestimated the toxicity across dose suggesting the potential for non-additive interactions of components. Overall, this study provides an example of the usefulness of mixture toxicity assessment with the currently available methods while demonstrating the need for more complex yet interpretable mixture response evaluation methods for environmental samples.

3D in vitro models↗

Iterative computational design and crystallographic screening identifies potent inhibitors targeting the Nsp3 macrodomain of SARS-CoV-2

The nonstructural protein 3 (NSP3) of the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) contains a conserved macrodomain enzyme (Mac1) that is critical for pathogenesis and lethality. While small-molecule inhibitors of Mac1 have great therapeutic potential, at the outset of the COVID-19 pandemic, there were no well-validated inhibitors for this protein nor, indeed, the macrodomain enzyme family, making this target a pharmacological orphan. Here, we report the structure-based discovery and development of several different chemical scaffolds exhibiting low- to sub-micromolar affinity for Mac1 through iterations of computer-aided design, structural characterization by ultra-high-resolution protein crystallography, and binding evaluation. Potent scaffolds were designed with in silico fragment linkage and by ultra-large library docking of over 450 million molecules. Both techniques leverage the computational exploration of tangible chemical space and are applicable to other pharmacological orphans. Overall, 160 ligands in 119 different scaffolds were discovered, and 153 Mac1-ligand complex crystal structures were determined, typically to 1 Å resolution or better. Our analyses discovered selective and cell-permeable molecules, unexpected ligand-mediated conformational changes within the active site, and key inhibitor motifs that will template future drug development against Mac1.

60 APPLIED LIFE SCIENCES↗

Identification of a pathway for electron uptake in Shewanella oneidensis

Extracellular electron transfer (EET) could enable electron uptake into microbial metabolism for the synthesis of complex, energy dense organic molecules from CO 2 and renewable electricity. Theoretically EET could do this with an efficiency comparable to H 2 -oxidation but without the need for a volatile intermediate and the problems it causes for scale up. However, significant gaps remain in understanding the mechanism and genetics of electron uptake. For example, studies of electron uptake in electroactive microbes have shown a role for the Mtr EET complex in the electroactive microbe Shewanella oneidensis MR-1, though there is substantial variation in the magnitude of effect deletion of these genes has depending on the terminal electron acceptor used. This speaks to the potential for previously uncharacterized and/or differentially utilized genes involved in electron uptake. To address this, we screened gene disruption mutants for 3667 genes, representing ≈99% of all nonessential genes, from the S. oneidensis whole genome knockout collection using a redox dye oxidation assay. Confirmation of electron uptake using electrochemical testing allowed us to identify five genes from S. oneidensis that are indispensable for electron uptake from a cathode. Knockout of each gene eliminates extracellular electron uptake, yet in four of the five cases produces no significant defect in electron donation to an anode. This result highlights both distinct electron uptake components and an electronic connection between aerobic and anaerobic electron transport chains that allow electrons from the reversible EET machinery to be coupled to different respiratory processes in S. oneidensis. Homologs to these genes across many different genera suggesting that electron uptake by EET coupled to respiration could be widespread. These gene discoveries provide a foundation for: studying this phenotype in exotic metal-oxidizing microbes, genetic optimization of electron uptake in S. oneidensis; and genetically engineering electron uptake into a highly tractable host like E. coli to complement recent advances in synthetic CO2 fixation.

59 BASIC BIOLOGICAL SCIENCES↗

Leveraging Structured Biological Knowledge for Counterfactual Inference: A Case Study of Viral Pathogenesis

Counterfactual inference is a useful tool for comparing outcomes of interventions on complex systems. It requires us to represent the system in form of a structural causal model, complete with a causal diagram, probabilistic assumptions on exogenous variables, and functional assignments. Specifying such models can be extremely difficult in practice. The process requires substantial domain expertise, and does not scale easily to large systems, multiple systems, or novel system modifications. At the same time, many application domains, such as molecular biology, are rich in structured causal knowledge that is qualitative in nature. This manuscript proposes a general approach for querying a causal knowledge graph with a causal question and converting the qualitative result into a quantitative structural causal model that can learn from data to answer the question. Here, we demonstrate the feasibility, accuracy and versatility of this approach using two case studies in systems biology. The first demonstrates the appropriateness of the underlying assumptions and the accuracy of the results. The second demonstrates the versatility of the approach by querying a knowledge base for the molecular determinants of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-induced cytokine storm and performing counterfactual inference to predict the causal effect of medical countermeasures for severely ill COVID-19 patients.

60 APPLIED LIFE SCIENCES↗

Structural basis of the American mink ACE2 binding by Y453F trimeric spike glycoproteins of SARS‐CoV‐2

Abstract Severe Acute Respiratory Syndrome Coronavirus 2 (SARS‐CoV‐2) enters the host cell by binding to angiotensin‐converting enzyme 2 (ACE2). While evolutionarily conserved, ACE2 receptors differ across various species and differential interactions with Spike (S) glycoproteins of SARS‐CoV‐2 viruses impact species specificity. Reverse zoonoses led to SARS‐CoV‐2 outbreaks on multiple American mink (Mustela vison) farms during the pandemic and gave rise to mink‐associated S substitutions known for transmissibility between mink and zoonotic transmission to humans. In this study, we used bio‐layer interferometry (BLI) to discern the differences in binding affinity between multiple human and mink‐derived S glycoproteins of SARS‐CoV‐2 and their respective ACE2 receptors. Further, we conducted a structural analysis of a mink variant S glycoprotein and American mink ACE2 (mvACE2) using cryo‐electron microscopy (cryo‐EM), revealing four distinct conformations. We discovered a novel intermediary conformation where the mvACE2 receptor is bound to the receptor‐binding domain (RBD) of the S glycoprotein in a “down” position, approximately 34° lower than previously reported “up” RBD. Finally, we compared residue interactions in the S‐ACE2 complex interface of S glycoprotein conformations with varying RBD orientations. These findings provide valuable insights into the molecular mechanisms of SARS‐CoV‐2 entry.

Virology↗

An antibody-free platform for multiplexed, sensitive quantification of protein biomarkers in complex biomatrices

Sensitive, multiplexed protein quantification remains challenging despite recent advancements in LC-MS assays for targeted protein biomarker quantification. High-sensitivity protein biomarker measurements usually require immuno-affinity enrichment of target protein; a process which is highly dependent on capture reagent and limited in capability to measure multiple analytes. Herein, we report a novel antibody-free platform, which measures multiple biomarkers from complex matrices employing a strategically optimized solid-phase extraction cleanup and orthogonal multidimensional LC-MS. Eight human protein biomarkers with different specifications were spiked into canine plasma as a model investigation system. The developed strategy achieved the desired sensitivity, robustness, and throughput via the following steps: (1) post digestion mixed-mode cation exchange-reverse phase SPE enrichment cleaned up the sample initially; (2) rapid, high-pH peptide fractionation further eliminated background components efficiently while selectively enriched signature peptides (SP) to provide sufficient sensitivity for multiple targets; and (3) trapping-micro-LC-MS analysis delivered high sensitivity comparable to a nano-LC-MS method but with much better robustness and throughput for the final analysis. Compared with a conventional LC-MS assay with direct protein digestion and limited clean-up, analysis with this antibody-free platform improved the LLOQ by 1–2 orders of magnitude for the eight protein biomarkers, reaching as low as 5 ng/mL in plasma, with feasible robustness and throughput. In conclusion, this platform was applied for the quantification of biomarkers of respiratory conditions in patients with various lung diseases, demonstrating real-world applicability.

59 BASIC BIOLOGICAL SCIENCES↗

Unraveling the Hsp70-ROS-autophagy axis in pentachlorophenol-challenged lung and liver epithelial cells

Pentachlorophenol (PCP) was extensively utilized as an organochlorine pesticide and wood preservative in the United States from the 1930s until the Environmental Protection Agency (EPA) imposed restrictions due to concerns about its toxicity and potential carcinogenic properties. Although it is no longer widely used, PCP remains a concern due to its environmental persistence and potential for long-term health effects. Significant occupational and environmental exposures have likely occurred, with the health and economic costs of PCP exposure potentially being substantial given its known toxicity. Notably, PCP exhibits rapid absorption through both the skin and respiratory system and has been shown to cause hepatotoxicity, developmental toxicity, immunotoxicity, irritation, and carcinogenicity in laboratory animal studies. PCP exposure induces oxidative stress, a key mechanism underlying its inflammatory and toxic effects, which can activate cellular stress responses including upregulation of heat shock protein 70 (Hsp70). Previous studies in lung and liver epithelial cells have shown that Hsp70 and oxidative stress play pivotal roles in triggering autophagy. This study establishes the critical role of the Hsp70-reactive oxygen species (ROS)-autophagy axis in regulating cellular responses to PCP exposure in human alveolar (A549) and liver carcinoma (HepG2) epithelial cells. Our research elucidated the molecular mechanisms underlying PCP's cellular effects, demonstrating that its exposure resulted in increased expression of autophagy-related proteins (Beclin-1, LC3B, ATG12, and ATG16), subunits of NADPH oxidase (NCF-1, NCF-2, NOX2, and Rac), and antioxidant proteins (SOD and GPx) in both lung and liver cell types. Notably, PCP augmented the interaction between Hsp70 and the autophagy regulator Beclin-1. Pretreatment with the ROS inhibitor N-acetylcysteine or Hsp70 knockdown markedly reversed PCP-induced responses. Our in-silico protein–protein docking analysis and molecular dynamics simulation studies revealed enhanced interactions and/or stable confirmations maintained throughout the simulations for TLR4-Hsp70 and Hsp70-Beclin-1 complexes in the presence of PCP. These findings provide a strong foundation for future studies, employing in vivo experimental models and human populations to identify promising targets for PCP-induced toxicity and cellular injury. As a result, these findings may have far-reaching implications for public health and environmental policy, ultimately leading to the identification of biomarkers and the development of more effective interventions for environmentally induced toxicity and diseases.

97 MATHEMATICS AND COMPUTING↗

Site specific N- and O-glycosylation mapping of the spike proteins of SARS-CoV-2 variants of concern

Abstract The glycosylation on the spike (S) protein of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes COVID-19, modulates the viral infection by altering conformational dynamics, receptor interaction and host immune responses. Several variants of concern (VOCs) of SARS-CoV-2 have evolved during the pandemic, and crucial mutations on the S protein of the virus have led to increased transmissibility and immune escape. In this study, we compare the site-specific glycosylation and overall glycomic profiles of the wild type Wuhan-Hu-1 strain (WT) S protein and five VOCs of SARS-CoV-2: Alpha, Beta, Gamma, Delta and Omicron. Interestingly, both N- and O-glycosylation sites on the S protein are highly conserved among the spike mutant variants, particularly at the sites on the receptor-binding domain (RBD). The conservation of glycosylation sites is noteworthy, as over 2 million SARS-CoV-2 S protein sequences have been reported with various amino acid mutations. Our detailed profiling of the glycosylation at each of the individual sites of the S protein across the variants revealed intriguing possible association of glycosylation pattern on the variants and their previously reported infectivity. While the sites are conserved, we observed changes in the N- and O-glycosylation profile across the variants. The newly emerged variants, which showed higher resistance to neutralizing antibodies and vaccines, displayed a decrease in the overall abundance of complex-type glycans with both fucosylation and sialylation and an increase in the oligomannose-type glycans across the sites. Among the variants, the glycosylation sites with significant changes in glycan profile were observed at both the N -terminal domain and RBD of S protein, with Omicron showing the highest deviation. The increase in oligomannose-type happens sequentially from Alpha through Delta. Interestingly, Omicron does not contain more oligomannose-type glycans compared to Delta but does contain more compared to the WT and other VOCs. O-glycosylation at the RBD showed lower occupancy in the VOCs in comparison to the WT. Our study on the sites and pattern of glycosylation on the SARS-CoV-2 S proteins across the VOCs may help to understand how the virus evolved to trick the host immune system. Our study also highlights how the SARS-CoV-2 virus has conserved both N - and O - glycosylation sites on the S protein of the most successful variants even after undergoing extensive mutations, suggesting a correlation between infectivity/ transmissibility and glycosylation.

60 APPLIED LIFE SCIENCES↗

Cleavage at the nsp5–nsp6 site of SARS-CoV-2 main protease intermediate precursor is faster from a monomer than a dimer form

Our previous studies of severe acute respiratory syndrome coronavirus 2 main protease (MPro) precursor monomer indicate that the initial N-terminal nonstructural protein (nsp)4/nsp5 cleavage occurs intramolecularly, with a small fraction of the active site loop equilibrium being in the active state. To understand the influence of dimer formation of MPro upon N-terminal cleavage on the subsequent C-terminal nsp5/nsp6 intermolecular cleavage kinetics, the stepwise processing of a monomeric, inactive precursor containing the native terminal cleavage sites of MPro (MBP- (−6) MPro C145A(+3) -GB1-6H, 86.2 kDa) by mature WT MPro (MPro WT ) was investigated. Differential scanning fluorimetry and analytical ultracentrifugation measurements of various MPro constructs suggest that the C145A mutation decreases the dimer dissociation constant (K dimer ) by ∼26-fold, relative to WT C145 and H41A. The monomeric precursor’s nsp4–nsp5 site appears to saturate MProWT’s active sites and cleave faster, followed by a slower first-order cleavage at the C-terminal site. No detectable product resulting from the C-terminal cleavage is observed until most of the N-terminal cleavage is complete. The initial intermediate product (termed MPro C145A-IP ) is a homodimer with an estimated K dimer of <0.05 μM. In contrast, the first-order kinetics observed for the cleavage of the monomeric form of the intermediate product is at least 300 times faster than that of the dimer form. Room-temperature X-ray structure of the MPro C145A-IP –ensitrelvir complex is like that of the MPro WT –ensitrelvir complex and reveals a dynamic C-terminal region including MPro residues 302 to 306. These results are interpreted from the point of view of a mechanism in which nsp5–nsp6 cleavage may occur from a monomeric intermediate, and dimer formation restricts this cleavage.

60 APPLIED LIFE SCIENCES↗

Quantifying Impacts of Renewable Electricity Deployment on Air Quality and Human Health in Southeast Asia Based on Aims III Scenarios

Exposure to outdoor air pollution is the largest environmental risk factor for death and disease worldwide, associated with millions of cases of excess deaths (mortality) each year. Although there are many pollutants in the air that affect our health, the most important class of pollutants is fine particulate matter, PM 2.5 , which are airborne particles of diameter ≤2.5 micrometers (µm). These particles are small enough to deposit deep in the respiratory system where they can then enter the bloodstream, traveling and causing damage to other bodily systems. Exposure to outdoor (ambient) PM 2.5 has been found to be the most important environmental risk factor for mortality in Southeast Asia, associated with 130,000 - 320,000 excess deaths in Association of Southeast Asian Nations (ASEAN) member countries in 2019. Southeast Asia, especially its mega-cities, but also other areas, has some of the worst air quality in the world. Almost all human activity emits air pollutants. Fine particulate matter is both directly emitted and formed in the atmosphere through chemical reactions, the latter of which requires modeling to predict. Power generation is one of the major sources of air pollutants that lead to elevated concentrations of fine particulate matter, including in Southeast Asia. Fossil fuel combustion for power generation, especially coal but also diesel, is the main source of air pollutant emissions from power generation. While natural gas burns cleaner than coal or diesel, in the quantities combusted for power generation in Southeast Asia, it is also a significant emitter. This study augments the ASEAN Interconnection Masterplan Study III (AIMS III) by quantifying changes to air quality and human health that result from its renewable integration and transmission interconnection scenarios. Performing this analysis requires translation of the changes in projected generation from different power sector fuel sources in the AIMS III scenarios to changes in air pollutant emissions, developing what's known as an emissions inventory for each scenario and year evaluated. We then use for the first time a new global, reduced-complexity air quality model to transform the changes in emissions to changes in air pollutant concentration of the deadliest air pollutant for human health, fine particulate matter (or PM 2.5 ). The air quality model, Global InMAP, then utilizes the location of human population in ASEAN countries to calculate exposure to PM 2.5 concentration changes and translates that to estimates of excess mortality attributable to the AIMS III scenarios.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗