Two novel compounds inhibit Flavivirus infection in vitro and in vivo by targeting lipid metabolism.

Flavivirus infection capitalizes on cellular lipid metabolism to remodel the cellular intima, creating a specialized lipid environment conducive to viral replication, assembly, and release. The Japanese encephalitis virus (JEV), a member of the Flavivirus genus, is responsible for significant morbidity and mortality in both humans and animals. Currently, there are no effective antiviral drugs available to combat JEV infection. In this study, we embarked on a quest to identify anti-JEV compounds within a lipid compound library. Our research led to the discovery of two novel compounds, isobavachalcone (IBC) and corosolic acid (CA), which exhibit dose-dependent inhibition of JEV proliferation. Time-of-addition assays indicated that IBC and CA predominantly target the late stage of the viral replication cycle. Mechanistically, JEV nonstructural proteins 1 and 2A (NS1 and NS2A) impede 5'-adenosine monophosphate (AMP)-activated protein kinase (AMPK) activation by obstructing the liver kinase B1 (LKB1)-AMPK interaction, resulting in decreased p-AMPK expression and a consequent upsurge in lipid synthesis. In contrast, IBC and CA may stimulate AMPK by binding to its active allosteric site, thereby inhibiting lipid synthesis essential for JEV replication and ultimately curtailing viral infection. Most importantly, in vivo experiments demonstrated that IBC and CA protected mice from JEV-induced mortality, significantly reducing viral loads in the brain and mitigating histopathological alterations. Overall, IBC and CA demonstrate significant potential as effective anti-JEV agents by precisely targeting AMPK-associated signaling pathways. These findings open new therapeutic avenues for addressing infections caused by Flaviviruses. IMPORTANCE: This study is the inaugural utilization of a lipid compound library in antiviral drug screening. Two lipid compounds, isobavachalcone (IBC) and corosolic acid (CA), emerged from the screening, exhibiting substantial inhibitory effects on the Japanese encephalitis virus (JEV) proliferation in vitro. In vivo experiments underscored their efficacy, with IBC and CA reducing viral loads in the brain and mitigating JEV-induced histopathological changes, effectively shielding mice from fatal JEV infection. Intriguingly, IBC and CA may activate 5'-adenosine monophosphate (AMP)-activated protein kinase (AMPK) by binding to its active site, curtailing the synthesis of lipid substances, and thus suppressing JEV proliferation. This indicates AMPK as a potential antiviral target. Remarkably, IBC and CA demonstrated suppression of multiple viruses, including Flaviviruses (JEV and Zika virus), porcine herpesvirus (pseudorabies virus), and coronaviruses (porcine deltacoronavirus and porcine epidemic diarrhea virus), suggesting their potential as broad-spectrum antiviral agents. These findings shed new light on the potential applications of these compounds in antiviral research.

Critical Role of Simultaneous Reduction of Atmospheric Odd Oxygen for Winter Haze Mitigation.

The lockdown due to COVID-19 created a rare opportunity to examine the nonlinear responses of secondary aerosols, which are formed through atmospheric oxidation of gaseous precursors, to intensive precursor emission reductions. Based on unique observational data sets from six supersites in eastern China during 2019-2021, we found that the lockdown caused considerable decreases (32-61%) in different secondary aerosol components in the study region because of similar-degree precursor reductions. However, due to insufficient combustion-related volatile organic compound (VOC) reduction, odd oxygen (Ox = O3 + NO2) concentration, an indicator of the extent of photochemical processing, showed little change and did not promote more decreases in secondary aerosols. We also found that the Chinese provinces and international cities that experienced reduced Ox during the lockdown usually gained a greater simultaneous PM2.5 decrease than other provinces and cities with an increased Ox. Therefore, we argue that strict VOC control in winter, which has been largely ignored so far, is critical in future policies to mitigate winter haze more efficiently by reducing Ox simultaneously.

Directed percolation and numerical stability of simulations of digital memcomputing machines.

Digital memcomputing machines (DMMs) are a novel, non-Turing class of machines designed to solve combinatorial optimization problems. They can be physically realized with continuous-time, non-quantum dynamical systems with memory (time non-locality), whose ordinary differential equations (ODEs) can be numerically integrated on modern computers. Solutions of many hard problems have been reported by numerically integrating the ODEs of DMMs, showing substantial advantages over state-of-the-art solvers. To investigate the reasons behind the robustness and effectiveness of this method, we employ three explicit integration schemes (forward Euler, trapezoid, and Runge-Kutta fourth order) with a constant time step to solve 3-SAT instances with planted solutions. We show that (i) even if most of the trajectories in the phase space are destroyed by numerical noise, the solution can still be achieved; (ii) the forward Euler method, although having the largest numerical error, solves the instances in the least amount of function evaluations; and (iii) when increasing the integration time step, the system undergoes a "solvable-unsolvable transition" at a critical threshold, which needs to decay at most as a power law with the problem size, to control the numerical errors. To explain these results, we model the dynamical behavior of DMMs as directed percolation of the state trajectory in the phase space in the presence of noise. This viewpoint clarifies the reasons behind their numerical robustness and provides an analytical understanding of the solvable-unsolvable transition. These results land further support to the usefulness of DMMs in the solution of hard combinatorial optimization problems.

Topological Quantum Compiling with Reinforcement Learning.

Quantum compiling, a process that decomposes the quantum algorithm into a series of hardware-compatible commands or elementary gates, is of fundamental importance for quantum computing. We introduce an efficient algorithm based on deep reinforcement learning that compiles an arbitrary single-qubit gate into a sequence of elementary gates from a finite universal set. It generates near-optimal gate sequences with given accuracy and is generally applicable to various scenarios, independent of the hardware-feasible universal set and free from using ancillary qubits. For concreteness, we apply this algorithm to the case of topological compiling of Fibonacci anyons and obtain near-optimal braiding sequences for arbitrary single-qubit unitaries. Our algorithm may carry over to other challenging quantum discrete problems, thus opening up a new avenue for intriguing applications of deep learning in quantum physics.

Reconfigurable Cascaded Thermal Neuristors for Neuromorphic Computing.

While the complementary metal-oxide semiconductor (CMOS) technology is the mainstream for the hardware implementation of neural networks, an alternative route is explored based on a new class of spiking oscillators called "thermal neuristors", which operate and interact solely via thermal processes. Utilizing the insulator-to-metal transition (IMT) in vanadium dioxide, a wide variety of reconfigurable electrical dynamics mirroring biological neurons is demonstrated. Notably, inhibitory functionality is achieved just in a single oxide device, and cascaded information flow is realized exclusively through thermal interactions. To elucidate the underlying mechanisms of the neuristors, a detailed theoretical model is developed, which accurately reflects the experimental results. This study establishes the foundation for scalable and energy-efficient thermal neural networks, fostering progress in brain-inspired computing.

Collective dynamics and long-range order in thermal neuristor networks.

In the pursuit of scalable and energy-efficient neuromorphic devices, recent research has unveiled a novel category of spiking oscillators, termed "thermal neuristors." These devices function via thermal interactions among neighboring vanadium dioxide resistive memories, emulating biological neuronal behavior. Here, we show that the collective dynamical behavior of networks of these neurons showcases a rich phase structure, tunable by adjusting the thermal coupling and input voltage. Notably, we identify phases exhibiting long-range order that, however, does not arise from criticality, but rather from the time non-local response of the system. In addition, we show that these thermal neuristor arrays achieve high accuracy in image recognition and time series prediction through reservoir computing, without leveraging long-range order. Our findings highlight a crucial aspect of neuromorphic computing with possible implications on the functioning of the brain: criticality may not be necessary for the efficient performance of neuromorphic systems in certain computational tasks.

Self-averaging of digital memcomputing machines.

Digital memcomputing machines (DMMs) are a new class of computing machines that employ nonquantum dynamical systems with memory to solve combinatorial optimization problems. Here, we show that the time to solution (TTS) of DMMs follows an inverse Gaussian distribution, with the TTS self-averaging with increasing problem size, irrespective of the problem they solve. We provide both an analytical understanding of this phenomenon and numerical evidence by solving instances of the 3-SAT (satisfiability) problem. The self-averaging property of DMMs with problem size implies that they are increasingly insensitive to the detailed features of the instances they solve. This is in sharp contrast to traditional algorithms applied to the same problems, illustrating another advantage of this physics-based approach to computation.

Molecular detection and genetic characteristics of a novel porcine circovirus (porcine circovirus 4) and porcine reproductive and respiratory syndrome virus in Shaanxi and Henan Provinces of China.

Porcine circovirus 4 (PCV4) is a recently discovered circovirus that was first reported in 2019 in several pigs with severe clinical disease in Hunan province of China, and also identified in pigs infected with porcine reproductive and respiratory syndrome virus (PRRSV). To further investigate the epidemic profile and genetic characteristics of the two viruses, 150 clinical samples were collected from 9 swine farms in Shaanxi and Henan provinces of China, and a SYBR Green I-based duplex quantitative real-time polymerase chain reaction (qPCR) was developed for detecting PCV4 and PRRSV simultaneously. The results showed the limits of detection were 41.1 copies/µL and 81.5 copies/µL for PCV4 and PRRSV, respectively. The detection rates of PCV4 and PRRSV were 8.00% (12/150) and 12.00% (18/150) respectively, and a case of co-infection with PCV4 and PRRSV was found in the lung tissue of a suckling pig with respiratory symptom. Subsequently, the complete genomic sequences of five PCV4 strains were obtained, of which one PCV4 strain (SX-ZX) was from Shaanxi province, and these strains were 1770 nucleotides in length and had 97.7%-99.4% genomic identity with 59 PCV4 reference strains. The genome characteristic of the SX-ZX strain was evaluated from three aspects, a "stem-loop" structure, ORF1 and ORF2. As essential elements for the replication, the 17-bp iterative sequence was predicted as the stem structure, in which three non-tandem hexamers were found at downstream with H1/H2 (12-CGGCACACTTCGGCAC-27) as the minimal binding site. Three of the five PCV4 strains were clustered into PCV4b, which was composed of Suidae, fox, dairy cow, dog and raccoon dog. Phylogenetic analysis revealed that seven PRRSV strains from the present study were clustered into the PRRSV-2 genotype. Collectively, these data extend our understanding of the genome characteristic of PCV4 as well as the molecular epidemiology and the genetic profile of PCV4 and PRRSV.

Simultaneous detection and genetic characterization of porcine circovirus 2 and 4 in Henan province of China.

Porcine circovirus 4 (PCV4) was identified as a novel porcine circovirus in China in 2019. To investigate the prevalence and genetic characteristics of PCV2 and PCV4, 133 clinical samples (103 tissue samples and 30 serum samples) were collected from 30 different pig farms in Henan province of China, and a SYBR Green I-based duplex quantitative real-time polymerase chain reaction assay was established to detect PCV2 and PCV4 genomes simultaneously. The complete genome sequences of 20 PCV2 and 6 PCV4 strains from 19 and 6 clinical samples respectively were sequenced and analyzed. The results showed the detection limits of this assay were 80.2 copies/µL for PCV2 and 58.6 copies/µL for PCV4. The detection results of clinical samples revealed the PCV2 positive rate was 63.16% (84/133), the PCV4 positive rate was 33.33% (45/133), and the PCV2 and PCV4 co-infection positive rate was 21.05% (28/133). Among 20 PCV2 strains, 6 belonged to PCV2a, 6 belonged to PCV2b and 8 belonged to PCV2d. Co-infection with JZ1 (PCV2b) and JZ2 (PCV2d) strains was identified in one sample (JZ-1). Eleven putative recombination events were found through the recombination analysis, suggesting that the new PCV2 variant strains had circulated in Henan province, which contributes to our understanding of evolutionary characteristics of PCV2 in China. The possible genotypes of PCV4 strains were determined based on genomic sequences of 6 PCV4 strains in this study and 29 PCV4 reference strains available at GenBank. According to three different phylogenetic trees (ORF1, ORF2 and complete genome), all 35 PCV4 strains were clustered into two major genotypes (PCV4a and PCV4b), and 6 PCV4 strains in this study belonged to PCV4a. Additionally, the functional regions of PCV4 strains were predicted by comparison with other circoviruses, which are conducive to the further study of the biological functions of PCV4 genome.

Phylogenetic analysis of porcine circovirus 4 in Henan Province of China: A retrospective study from 2011 to 2021.

Porcine circovirus 4 (PCV4), a novel circovirus, was first discovered in April 2019 in Hunan Province of China. At present, PCV4 infection has been detected in China and South Korea. However, until 2019, there was little information about its circulating status and genetic characteristics. To further clarify the origin and prevalence of PCV4, a total of 152 clinical samples collected from 49 different swine farms of 15 cities in Henan Province of China from 2011 to 2021 were tested for the presence of PCV4 by qPCR, and the complete genome of PCV4 strains was amplified from the positive samples and sequenced. Among these samples, 45.39% (69/152) were positive for PCV4 and 86.67% (13/15) of the cities and 67.35% (33/49) of the swine farms were positive for PCV4. The genome sequences of 15 PCV4 strains were obtained, of which two PCV4 strains (HN-ZMD-201212 and HN-XX-201212) were achieved from archival samples in 2012, indicating that PCV4 has been circulating for at least 10 years in Henan Province of China. The phylogenetic analysis showed that 15 PCV4 strains in our study together with PCV4 strain HNU-AHG1-2019 were clustered into an identical but separate evolutionary branch, with genomic identity ranging from 98.2% to 98.8%. Our research further provides significant epidemiological information on PCV4 in China, which will help understand the origin and genetic characteristics of this new virus.

Genetic Characteristics and Pathogenicity of a Novel Porcine Epidemic Diarrhea Virus with a Naturally Occurring Truncated ORF3 Gene.

Porcine epidemic diarrhea virus (PEDV) is the major pathogen that causes diarrhea and high mortality in newborn piglets, with devastating impact on the pig industry. To further understand the molecular epidemiology and genetic diversity of PEDV field strains, in this study the complete genomes of four PEDV variants (HN2021, CH-HNYY-2018, CH-SXWS-2018, and CH-HNKF-2016) obtained from immunized pig farms in central China between 2016 to 2021 were characterized and analyzed. Phylogenetic analysis of the genome and S gene showed that the four strains identified in the present study had evolved into the subgroup G2a, but were distant from the vaccine strain CV777. Additionally, it was noteworthy that a new PEDV strain (named HN2021) belonging to the G2a PEDV subgroup was successfully isolated in vitro and it was further confirmed by RT-PCR that this isolate had a large natural deletion at 207-373 nt of the ORF3 gene, which has never been reported before. Particularly, in terms of pathogenicity evaluation, colostrum deprivation piglets challenged with PEDV HN2021 showed severe diarrhea and high mortality, confirming that PEDV HN2021 was a virulent strain. Hence, PEDV strain HN2021 of subgroup G2a presents a promising vaccine candidate for the control of recurring porcine epidemic diarrhea (PED) in China. This study lays the foundation for better understanding of the genetic evolution and molecular pathogenesis of PEDV.

Simultaneous detection and differentiation of porcine circovirus 3 and 4 using a SYBR Green І-based duplex quantitative PCR assay.

Porcine circovirus 4 (PCV4) was a novel circovirus identified from diseased pigs in 2019 in Hunan Province, China, and PCV3 and PCV4 co-infection has been reported. In order to detect and differentiate PCV3 and PCV4 simultaneously, the SYBR Green І-based duplex quantitative PCR (qPCR) assay was established in the present study. The two viruses could be easily distinguished by different Tm values: 86.5°C for PCV3 and 79°C for PCV4, while other porcine pathogens did not shown specific melting peaks. The detection limits of this duplex qPCR assay were 51.7 copies/µL for PCV3 and 67.7 copies/µL for PCV4, and both of the intra-assay and inter-assay of the CV analysis of this assay were less than 2.0 %. Sixty-four clinical samples from 22 different swine farms were screened by the duplex qPCR assay. The results showed that the positive detection rate of PCV3 was 37.5 % (24/64) and PCV4 was 34.38 % (22/64), and PCV3 and PCV4 co-infection rate was 17.19 % (11/64). The detection rate of the duplex qPCR assay was higher than that of the conventional PCR assay. The duplex qPCR was of high sensitivity and specificity, being able to provide technical support for clinical detection, differential diagnosis and control of PCV3 and PCV4.

Prevalence and genetic analysis of porcine circovirus type 2 (PCV2) and type 3 (PCV3) between 2018 and 2020 in central China.

Porcine circovirus type 2 (PCV2) is the causative agent of porcine circovirus-associated diseases (PCVAD), causing substantial economic losses to the swine industry worldwide. PCV3, as a recently discovered virus, is associated with porcine dermatitis, nephropathy syndrome, reproductive failure, congenital tremors, and other clinical symptoms. To further investigate the epidemic profile and genetic diversity of the two viruses, a total of 198 samples from swine at various growth stages suspected for PCVAD on 55 different pig farms between 2018 and 2020 were analyzed for presence of PCV2 and PCV3 by using a multiplex real-time PCR assay. Among the 198 samples, 113 (57.07%) and 72 (36.36%) were positive for PCV2 and PCV3 respectively, and 39 (19.7%) were positive for PCV2 and PCV3 co-infection. Subsequently, whole genome sequences of 34 PCV2 and 19 PCV3 strains were obtained from 30 and 19 clinical samples, respectively. Of these, 8 PCV2 strains belonged to PCV2a, 10 belonged to PCV2b and 16 belonged to PCV2d, indicating PCV2d was the predominant PCV2 genotype circulating in central China. Furthermore, co-infection of different PCV2 genotype strains was identified in three samples (JZ-4, KF-2 and JY-1), and a cross-recombination was found in the ORF2 region of the sequenced 13 PCV2d strains whose putative parental strains were LN6/1999 (MF278777) and MEX/41238/2014 (KT795287) strains. The phylogenetic analysis of PCV3 showed high nucleotide identity (>98%) among sequences obtained in this study and reference sequences. These data will aid our understanding of the molecular epidemiology and evolution of PCV2 and PCV3.

Source profiles of particulate organic matters emitted from cereal straw burnings.

Cereal straw is one of the most abundant biomass burned in China but its contribution to fine particulates is not adequately understood. In this study, three main kinds of cereal straws were collected from five grain producing areas in China. Fine particulate matters (PM2.5) from the cereal straws subjected to control burnings, both under smoldering and flaming status, were sampled by using a custom made dilution chamber and sampling system in the laboratory. Element carbon (EC) and organic carbon (OC) was analyzed. 141 compounds of organic matters were measured by gas chromatography-mass spectrum (GC-MS). Source profiles of particulate organic matters emitted from cereal straw burnings were obtained. The results indicated that organic matters contribute a large fraction in fine particulate matters. Levoglucosan had the highest contributions with averagely 4.5% in mass of fine particulates and can be considered as the tracer of biomass burnings. Methyloxylated phenols from lignin degradation also had high concentrations in PM2.5, and contained approximately equal amounts of guaiacyl and syringyl compounds. beta-Sitostrol also made up relatively a large fraction of PM2.5 compared with the other sterols (0.18%-0.63% of the total fine particle mass). Normal alkanes, PAHs, fatty acids, as well as normal alkanols had relatively lower concentrations compared with the compounds mentioned above. Carbon preference index (CPI) of normal alkanes and alkanoic acids showed characteristics of biogenic fuel burnings. Burning status significantly influenced the formations of EC and PAHs. The differences between the emission profiles of straw and wood combustions were displayed by the fingerprint compounds, which may be used to identify the contributions between wood and straw burnings in source apportionment researches.

Seasonal pollution characteristics of organic compounds in atmospheric fine particles in Beijing.

Beijing is a rapidly developing city with severe and unique air pollution problems. Organic matter is the most abundant fraction in fine particles in Beijing, occupying 30-50% of the total mass, indicating its key role in air pollution control. However, detailed chemical characterization of particulate organic matter in Beijing has never been reported. In this study, fine particles in the urban atmosphere in Beijing were investigated for its organic components by GC/MS technique. Over 100 individual organic compounds were identified and quantified in 25 PM2.5 samples from the summer, autumn and winter of 2002-2003. Alkanes, fatty acids, dicarboxylic acids, polycyclic aromatic hydrocarbons and some important tracer compounds (hopanes, levoglucosan and steroids) were the major constituents with the sum of their concentrations of 502, 1471 and 1403 ng m(-3) in summer, autumn and winter, respectively. Different organic compounds presented apparently different seasonal characteristics, reflecting their different dominant emission sources, such as coal combustion, biomass burning and cooking emission. The abundance and origin of these organic compounds are discussed to reveal seasonal air pollution characteristics of Beijing.

Chemical characterization of fine particles from on-road vehicles in the Wutong tunnel in Shenzhen, China.

Vehicle populations in China have been increasing sharply since 1990s. Vehicle emissions including various gaseous pollutants and particulate matter cause deterioration of air quality. However, measurements of particulate mater from on-road vehicles in China are scarcely reported, and thus the chemical compositions of particles emitted from vehicles in China are unknown. In this research, tunnel experiments were performed to measure PM2.5 in the Wutong tunnel, Shenzhen, China. Detailed PM2.5 chemical compositions, with organic compounds determined by GC/MS, in the tunnel were presented. Elemental carbon and organic matter composed 63% and 34% of the total PM2.5 mass in the Wutong tunnel, respectively. Alkanes, PAHs, hopanes, fatty acids, and dicarboxylic acids were the major identified organic compounds, and their source profiles in the PM2.5 in the Wutong tunnel were characterized. The comparisons of our measurements with those in the literature were also made to demonstrate the characteristics of the vehicle source profiles in the Wutong tunnel. The experimental results in this paper can improve understanding of particulate matter emitted from vehicles in China.

Quantitative relationship between visibility and mass concentration of PM2.5 in Beijing.

The pollution of particulate matter less than 2.5 microm (PM2.5) is a serious environmental problem in Beijing. The annual average concentration of PM2.5 in 2001 from seasonal monitor results was more than 6 times that of the U.S. national ambient air quality standards proposed by U.S. EPA. The major contributors to mass of PM2.5 were organics, crustal elements and sulfate. The chemical composition of PM2.5 varied largely with season, but was similar at different monitor stations in the same season. The fine particles (PM2.5) cause atmospheric visibility deterioration through light extinction. The mass concentrations of PM2.5 were anti-correlated to the visibility, the best fits between atmospheric visibility and the mass concentrations of PM2.5 were somehow different: power in spring, exponential in summer, logarithmic in autumn, power or exponential in winter. As in each season the meteorological parameters such as air temperature and relative humidity change from day to day, probably the reason of above correlations between PM2.5 and visibility obtained at different seasons come from the differences in chemical compositions of PM2.5.

Characterization of fine organic particulate matter from Chinese cooking.

PM2.5 samples were collected by a three-stage cascade impactor at two kinds of Chinese restaurants to characterize fine organic particulate matter from Chinese cooking sources. Major individual organic compounds have been quantified by GC/MS, including series of alkanes, n-alkanoic acids, n-alkanals, alkan-2-ones and PAHs. Alkanes and ketones make up a significant fraction of particle-phase organic compounds, ranging from C11 to C26, and C9 to C19, respectively. In addition, other organic compound classes have been identified, such as alkanols, esters, furans, lactones, amides, and nitriles. The mass concentrations of fine particles, alkanes, n-alkanoic acids and PAHs in air emitted from the Uigur style cooking are hundreds times higher than ambient PM2.5 in Beijing.

Chemical composition and quantitative relationship between meteorological condition and fine particles in Beijing.

The recent year's monitor results of Beijing indicated that the pollution level of fine particles PM2.5 showed an increasing trend. To understand pollution characteristics of PM2.5 and its relationship with the meteorological conditions in Beijing, a one-year monitoring of PM2.5 mass concentration and correspondent meteorological parameters was performed in Beijing in 2001. The PM2.5 levels in Beijing were very high, the annual average PM2.5 concentration in 2001 was 7 times of the National Ambient Air Quality Standards proposed by US EPA. The major chemical compositions were organics, sulfate, crustals and nitrate. It was found that the mass concentrations of PM2.5 were influenced by meteorological conditions. The correlation between the mass concentrations of PM2.5 and the relative humidity was found. And the correlation became closer at higher relative humidity. And the mass concentrations of PM2.5 were negtive-correlated to wind speeds, but the correlation between the mass concentration of PM2.5 and wind speed was not good at stronger wind.

[A DRIFTS study of SO2 oxidation on the surface of CaCO3 particles].

CaCO3 is an important component of mineral dust aerosols in the atmosphere, but its role in atmospheric heterogeneous chemistry is still unclear. In this paper, the oxidation of SO2 on CaCO3 particles was studied using diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS). Formation of sulfite and sulfate was identified on the surface, and the role of O3 on the oxidation process is determined by comparing the experiments in different conditions. DRIFTS is proved as a useful tool for studying heterogeneous reactions on CaCO3 particles. The results show that in the presence of O3, SO2 can be oxidized into sulfate on the surface of CaCO3 particles. A two-step mechanism that involves adsorption of SO2 followed by oxidation is presented.