Abstract Genetic drift in infectious disease transmission results from randomness of transmission and host recovery or death. The strength of genetic drift for SARS-CoV-2 transmission is expected to be high due to high levels of superspreading, and this is expected to substantially impact disease epidemiology and evolution. However, we don’t yet have an understanding of how genetic drift changes over time or across locations. Furthermore, noise that results from data collection can potentially confound estimates of genetic drift. To address this challenge, we develop and validate a method to jointly infer genetic drift and measurement noise from time-series lineage frequency data. Our method is highly scalable to increasingly large genomic datasets, which overcomes a limitation in commonly used phylogenetic methods. We apply this method to over 490,000 SARS-CoV-2 genomic sequences from England collected between March 2020 and December 2021 by the COVID-19 Genomics UK (COG-UK) consortium and separately infer the strength of genetic drift for pre-B.1.177, B.1.177, Alpha, and Delta. We find that even after correcting for measurement noise, the strength of genetic drift is consistently, throughout time, higher than that expected from the observed number of COVID-19 positive individuals in England by 1 to 3 orders of magnitude, which cannot be explained by literature values of superspreading. Our estimates of genetic drift will be informative for parameterizing evolutionary models and studying potential mechanisms for increased drift. Author Summary The transmission of pathogens like SARS-CoV-2 is strongly affected by chance effects in the contact process between infected and susceptible individuals, collectively referred to as random genetic drift. We have an incomplete understanding of how genetic drift changes across time and locations. To address this gap, we developed a computational method that infers the strength of genetic drift from time series genomic data that corrects for non-biological noise and is computationally scalable to the large numbers of sequences available for SARS-CoV-2, overcoming a major challenge of existing methods. Using this method, we quantified the strength of genetic drift for SARS-CoV-2 transmission in England throughout time and across locations. These estimates constrain potential mechanisms and help parameterize models of SARS-CoV-2 evolution. More generally, the computational scalability of our method will become more important as increasingly large genomic datasets become more common.
Abstract. Despite the growing interest in understanding haze formation in Chinese megacities, air pollution has been largely overlooked for the Harbin-Changchun (HC) metropolitan area located in the severe cold climate region in Northeast China. In this study, we unfolded significant variations of fine particulate matter (PM2.5) in HC’s central city (Harbin) during two sequential heating seasons of 2018–2019 and 2019–2020, and explored major drivers for the observed variations. The two campaigns showed comparable organic carbon (OC) levels but quite different OC sources. The biomass burning (BB) to OC contribution decreased substantially for 2019–2020, which was attributed primarily to the transition of local policies on agricultural fires, i.e., from the “legitimate burning” policy released in 2018 to the “strict prohibition” policy in 2019. Meanwhile, the contribution of secondary OC (OCsec) increased significantly, associated with the much more frequent occurrences of high relative humidity (RH) conditions during the 2019–2020 measurement period. Similar to OCsec, the major secondary inorganic ions, i.e., sulfate, nitrate and ammonium (SNA), also exhibited RH-dependent increases. Given the considerable aerosol water contents predicted for the high-RH conditions, heterogeneous reactions were likely at play in secondary aerosol formation even in the frigid atmosphere in Harbin (e.g., with daily average temperatures down to below −20 °C). In brief, compared to 2018–2019, the 2019–2020 measurement period was characterized by a policy-driven decrease of biomass burning OC, a RH-related increase of OCsec and a RH-related increase of SNA, with the former two factors generally offsetting each other. In addition, we found that open burning activities were actually not eliminated by the “strict prohibition” policy released in 2019, based on a synthesis of air quality data and fire count results. Although not evident throughout the 2019–2020 measurement period, agricultural fires broke out within a short period before crop planting in spring of 2020, and resulted in off-the-chart air pollution for Harbin, with 1- and 24-hour PM2.5 concentrations peaking at ~2350 and 900 μg/m3, respectively. This study indicates that sustainable use of crop residues remains a difficult challenge for the massive agricultural sector in Northeast China.
Demographic noise, the change in the composition of a population due to random birth and death events, is an important driving force in evolution because it reduces the efficacy of natural selection. Demographic noise is typically thought to be set by the population size and the environment, but recent experiments with microbial range expansions have revealed substantial strain-level differences in demographic noise under the same growth conditions. Many genetic and phenotypic differences exist between strains; to what extent do single mutations change the strength of demographic noise? To investigate this question, we developed a high-throughput method for measuring demographic noise in colonies without the need for genetic manipulation. By applying this method to 191 randomly-selected single gene deletion strains from the E. coli Keio collection, we find that a typical single gene deletion mutation decreases demographic noise by 8% (maximal decrease: 81%). We find that the strength of demographic noise is an emergent trait at the population level that can be predicted by colony-level traits but not cell-level traits. The observed differences in demographic noise from single gene deletions can increase the establishment probability of beneficial mutations by almost an order of magnitude (compared to in the wild type). Our results show that single mutations can substantially alter adaptation through their effects on demographic noise and suggest that demographic noise can be an evolvable trait of a population.
NOx storage and reduction with CH4 by a plasma process was proposed for NOx removal at ambient temperature. The efficiency of this new process for NOx removal could achieve 95% at ambient temperature. NOx removal via cyclic operation has also been investigated, maintaining efficieniency above 90%.
The seasonal characteristics of fine particulate matter (PM2.5) were investigated from October 2020 to April 2021 (spreading fall, winter and spring) in Harbin, a city located in northeast China. The mass concentrations of PM2.5 in winter were significantly higher than those in fall and spring. Moreover, our results indicated that various aerosol species had obvious seasonality. The proportions of secondary components were higher in winter than other two seasons. In contrast, the ratios of nitrate to sulfate (NO3-/SO42-) showed lower levels in winter, which was because both the ratios of nitrogen dioxide to sulfur dioxide (NO2/SO2) and the ratios of nitrogen oxidation ratio to sulfur oxidation ratio (NOR/SOR) exhibited lower values in winter than in fall and spring. With PM2.5 increased, the NO3-/SO42- ratios showed increasing trends in all three seasons, which was mainly attributed to the increase of NOR/SOR ratios in fall and spring, and the increase of both NO2/SO2 and NOR/SOR ratios in winter. This result highlighted that nitrate was more important than sulfate as a driver for the growth of PM2.5 during the period of heavy air pollution. Additionally, the sources of organic aerosol (OA) in different seasons were also distinctly different. Overall, the sum of biomass burning OA (BBOA) and secondary OA (SOA) contributed >70% of OA in three seasons. The fractional contributions of BBOA to total OA, notably, exhibited higher levels in fall and spring, because of intensive open agricultural fires. The SOA fractions in OA were larger in winter, likely due to higher relative humidity which facilitated the secondary formation. A large increase in the proportions of BBOA was observed during polluted days in fall and spring compared to clean days. In comparison, during heavily-polluted periods, secondary formation made a dominant contribution to organic matter in winter.
Abstract. Brown carbon (BrC) represents an important target for the “win-win” strategy of mitigating climate change and improving air quality. However, estimating co-benefits of BrC control remains difficult for China, partially because current measurement results are insufficient to represent the highly variable emission sources and meteorological conditions across different regions. In this study, we investigated, for the first time, the diurnal variations of BrC during two distinct seasons in a largely unexplored megacity in Northeast China. The winter campaign conducted in January of 2021 was characterized by low temperatures rarely seen in other Chinese megacities (down to about −20 °C). The mass absorption efficiencies of BrC at 365 nm (MAE365) were found to be ~10 % higher at night. The variations of MAE365 could not be explained by the influence of residential biomass burning emissions or secondary aerosol formation, but were strongly associated with the changes of a diagnostic ratio for the relative importance of coal combustion and vehicle emissions (RS/N). Given that most coal combustion activities were uninterruptible, the higher nighttime MAE365 in winter were attributed primarily to increased emissions from heavy-duty diesel trucks. The spring campaign conducted in April of 2021 was characterized by frequent occurrences of agricultural fires, as supported by the intensive fire hotspots detected around Harbin and the more-than-doubled levoglucosan to organic carbon ratios (LG/OC) compared to winter campaign. In spring, MAE365 depended little on RS/N but exhibited a strong positive correlation with LG/OC, suggesting open burning emissions as the dominant influencing factor for BrC’s light absorption capacity. MAE365 were ~70 % higher at night for the spring campaign, pointing to the prevalence of nighttime agricultural fires, which were presumably in response to local bans on open burning. It is noteworthy that the agricultural fire emissions resulted in distinct peak at ~365 nm for the light absorption spectra of BrC, and a candidate for the compounds at play was inferred to be C7H7NO4. Due to the presence of the ~365 nm peak, the absorption Ångström exponents could not be properly determined for the agricultural fire-impacted samples. In addition, the ~365 nm peak became much less significant during the day, likely due to photo-bleaching of the relevant chromophores.
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