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To promote extraction efficiency of bioactive polysaccharides from sclerotium of Polyporus umbellatus, ultrasonic-assisted extraction was applied to extract polysaccharides from P. umbellatus sclerotium. The effects of extraction time, ultrasonic power, extraction temperature and liquid-to-material ratio on the yield of polysaccharide were investigated by combining single factor experiments and response surface optimization, and the optimal extraction parameters were also determined. Meanwhile, antioxidant activities were evaluated by DPPH free radical scavenging ability and reducing power test. The results showed that the yield of polysaccharides from sclerotia of P. umbellatus was significantly correlated to the interaction between extraction temperature and ultrasonic power, extraction temperature and liquid-to-material ratio, ultrasonic power and liquid-to-material ratio, liquid-to-material ratio and extraction time. The optimum extraction parameters were extraction temperature 72.0 ℃, extraction power 300 W, extraction time 65 min and liquid-solid ratio 22 mL/g, and the maximum yield was 2.47%±0.03%. PUPF30, PUPF60 and PUPF80 were obtained from polysaccharide extracts by graded ethanol precipitation. Their polysaccharide contents were respectively 39.99%, 58.60% and 50.35%, and the protein contents were respectively 25.80%, 14.42% and 25.54%. Within the tested dose range, PUPF30, PUPF60 and PUPF80 showed the highest DPPH scavenging rate of 50.63%, 83.95%, 87.48%, respectively, and the highest reduction power of 0.828, 1.433, 1.525, respectively. The ultrasonic-assisted extraction optimized by response surface methodology was preferable for effective extraction and preparation of bioactive polysaccharides from sclerotia of P. umbellatu. This study would lay a foundation for the further development and utilization of polysaccharides from sclerotia of P. umbellatus.

Blueberry (Vaccinium corymbosum) is reputed as a rich source of health-promoting phytonutrients, which contributes to its burgeoning consumer demand and production. However, blueberries are much smaller and have lower yields than most domesticated berries, and the inherent regulatory mechanisms remain elusive. In this study, the cytological and physiological changes, as well as comparative transcriptomic analysis throughout flower and fruit development in the southern highbush blueberry cultivar ‘O’Neal’ were performed. ‘O’Neal’ hypanthium and fruit exhibited a distinctive cell proliferation pattern, and auxin accumulation was unusual throughout development, while abscisic acid (ABA) levels rapidly increased in association with anthocyanin accumulation, total phenolic reduction and fruit maturation. Transcriptomic data showed that many differentially expressed genes (DEGs) were specifically expressed at each flower bud and fruit developmental stage. Further weighted gene co-expression network analysis (WGCNA) revealed numerous DEGs that correlated with the cell numbers of outer mesocarp and columella, showed two distinctive expression patterns. Most of the DEGs involved in auxin biosynthesis, transportation and signal transduction were upregulated, and this upregulation was accompanied by cell expansion, and flower bud and fruit development. However, individual members of VcSAUR50 and VcIAA9 families might be insensitive to auxin, suggesting that these genes play a distinctive role in the growth and development of blueberry fruits. These results will support future research to better understand the flower and fruit development of southern highbush blueberry.

Abstract Global air pollution and climate change are major threats to planetary health. These threats are strongly linked through the short‐lived climate forcers (SLCFs); ozone (O3), aerosols, and methane (CH4). Understanding the impacts of ambitious SLCF mitigation in different source emission sectors on planetary health indicators can help prioritize international air pollution control strategies. A global Earth system model is applied to quantify the impacts of idealized 50% sustained reductions in year 2005 emissions in the eight largest global anthropogenic source sectors on the SLCFs and three indicators of planetary health: global mean surface air temperature change (∆GSAT), avoided PM2.5‐related premature mortalities and gross primary productivity (GPP). The model represents fully coupled atmospheric chemistry, aerosols, land ecosystems and climate, and includes dynamic CH4. Avoided global warming is modest, with largest impacts from 50% cuts in domestic (−0.085 K), agriculture (−0.034 K), and waste/landfill (−0.033 K). The 50% cuts in energy, domestic, and agriculture sector emissions offer the largest opportunities to mitigate global PM2.5‐related health risk at around 5%–7% each. Such small global impacts underline the challenges ahead in achieving the World Health Organization aspirational goal of a 2/3 reduction in the number of deaths from air pollution by 2030. Uncertainty due to natural climate variability in PM2.5 is an important underplayed dimension in global health risk assessment that can vastly exceed uncertainty due to the concentration‐response functions at the large regional scale. Globally, cuts to agriculture and domestic sector emissions are the most attractive targets to achieve climate and health co‐benefits through SLCF mitigation.

A decline of surface biogenic secondary organic aerosols through the mediation of reduced anthropogenic aerosols has been recognized as an air quality co-benefit of anthropogenic emission control over the southeastern US. However, the climate impacts of this anthropogenic–biogenic interaction remain poorly understood. Here, we identified a substantial decline of summertime aerosol loading aloft over the southeastern US in recent decades through the interaction, which leads to a stronger decline in column-integrated aerosol optical depth and a greater increase in radiative fluxes over the southeastern than northeastern US, different from trends of anthropogenic emissions and near-surface aerosol loading. The anthropogenic–biogenic interaction is shown to explain more than 60% of the coherent increasing trend of 5.3 Wm ^−2 decade ^−1 in clear-sky surface downward radiative fluxes. We show that current climate models fail to represent this interaction. The interaction is further projected to amplify the positive radiative forcing from emission control by 42.3% regionally over the southeastern US and globally by 5.4% in 2050 under RCP4.5 compared to 2005. This amplification effect implies greater challenges to achieving the Paris Agreement temperature targets with continuous emission control in future.

Bermudagrass [Cynodon dactylon (L.) Pers.], an important turfgrass used in public parks, home lawns, golf courses and sports fields, is widely distributed in China. In the present study, sequence-related amplified polymorphism (SRAP) markers were used to assess genetic diversity and population structure among 157 indigenous bermudagrass genotypes from 20 provinces in China. The application of 26 SRAP primer pairs produced 340 bands, of which 328 (96.58%) were polymorphic. The polymorphic information content (PIC) ranged from 0.36 to 0.49 with a mean of 0.44. Genetic distance coefficients among accessions ranged from 0.04 to 0.61, with an average of 0.32. The results of STRUCTURE analysis suggested that 157 bermudagrass accessions can be grouped into three subpopulations. Moreover, according to clustering based on the unweighted pair-group method of arithmetic averages (UPGMA), accessions were divided into three major clusters. The UPGMA dendrogram revealed that accessions from identical or adjacent areas were generally, but not entirely, clustered into the same cluster. Comparison of the UPGMA dendrogram and the Bayesian STRUCTURE analysis showed general agreement between the population subdivisions and the genetic relationships among accessions. Principal coordinate analysis (PCoA) with SRAP markers revealed a similar grouping of accessions to the UPGMA dendrogram and STRUCTUE analysis. Analysis of molecular variance (AMOVA) indicated that 18% of total molecular variance was attributed to diversity among subpopulations, while 82% of variance was associated with differences within subpopulations. Our study represents the most comprehensive investigation of the genetic diversity and population structure of bermudagrass in China to date, and provides valuable information for the germplasm collection, genetic improvement, and systematic utilization of bermudagrass.

Zoysiagrass (Zoysia Willd.) is an important warm season turfgrass that is grown in many parts of the world. Salt tolerance is an important trait in zoysiagrass breeding programs. In this study, a genetic linkage map was constructed using sequence-related amplified polymorphism markers and random amplified polymorphic DNA markers based on an F1 population comprising 120 progeny derived from a cross between Zoysia japonica Z105 (salt-tolerant accession) and Z061 (salt-sensitive accession). The linkage map covered 1211 cM with an average marker distance of 5.0 cM and contained 24 linkage groups with 242 marker loci (217 sequence-related amplified polymorphism markers and 25 random amplified polymorphic DNA markers). Quantitative trait loci affecting the salt tolerance of zoysiagrass were identified using the constructed genetic linkage map. Two significant quantitative trait loci (qLF-1 and qLF-2) for leaf firing percentage were detected; qLF-1 at 36.3 cM on linkage group LG4 with a logarithm of odds value of 3.27, which explained 13.1% of the total variation of leaf firing and qLF-2 at 42.3 cM on LG5 with a logarithm of odds value of 2.88, which explained 29.7% of the total variation of leaf firing. A significant quantitative trait locus (qSCW-1) for reduced percentage of dry shoot clipping weight was detected at 44.1 cM on LG5 with a logarithm of odds value of 4.0, which explained 65.6% of the total variation. This study provides important information for further functional analysis of salt-tolerance genes in zoysiagrass. Molecular markers linked with quantitative trait loci for salt tolerance will be useful in zoysiagrass breeding programs using marker-assisted selection.

The northern high latitudes (50-90°N, mostly including boreal forest and tundra ecosystem) has been undergoing rapid climate and ecological changes over recent decades, leading to significant variations in volatile organic compounds (VOCs) emissions from biogenic and biomass burning sources. HCHO, a widely used indicator of VOC emission, exhibits high climate sensitivity. However, the interannual variability of HCHO and its main drivers over the region remain unclear. In this study, we use the GEOS-Chem chemical transport model and satellite retrievals from Ozone Monitoring Instrument (OMI) and Ozone Mapping and Profiler Suite (OMPS) to examine HCHO vertical column density (VCD) interannual variations in summertime of 2005-2019. Our results show that wildfires heavily influence interannual variability of HCHO VCD over Siberia, Alaska, and North Canada, while biogenic emissions and background methane oxidation are the predominant drivers of HCHO interannual variability over East Europe. Solarinduced chlorophyll fluorescence (SIF) from Orbiting Carbon Observatory-2 (OCO-2) provides additional evaluation for HCHO interannual variability from biogenic emission, showing potential of constraining biogenic emission in northern high latitudes. [ABSTRACT FROM AUTHOR]

Biogenic secondary organic aerosols (SOA) contribute to a large fraction of fine aerosols globally, impacting air quality and climate. The formation of biogenic SOA depends on not only emissions of biogenic volatile organic compounds (BVOCs) but also anthropogenic pollutants including primary organic aerosol, sulfur dioxide (SO2), and nitrogen oxides (NOx). However, the anthropogenic impact on biogenic SOA production (AIBS) remains unclear. Here we use the decadal trend and variability of observed OA in the southeast US, combined with a global chemistry-climate model, to better constrain AIBS. We show that the reduction in SO2 emissions can only explain 40% of the decreasing decadal trend of OA in this region, constrained by the low summertime month-to-month variability of surface OA. We hypothesize that the rest of OA decreasing trend is largely due to reduction in NOx emissions. By implementing a scheme for monoterpene SOA with enhanced sensitivity to NOx, our model can reproduce the decadal trend and variability of OA in this region. Extending to centennial scale, our model shows that global SOA production increases by 36% despite BVOC reductions from preindustrial period to present day, largely amplified by AIBS. Our work suggests a strong coupling between anthropogenic and biogenic emissions in biogenic SOA production that is missing from current climate models. [ABSTRACT FROM AUTHOR]

Organic aerosol (OA), with a large biogenic fraction in summertime southeast US, adversely impacts on air quality and human health. Stringent air quality controls have recently reduced anthropogenic pollutants including sulfate, whose impact on OA remains unclear. Three filter measurement networks provide long-term constraints on the sensitivity of OA to changes in inorganic species, including sulfate and ammonia. The 2000-2013 summertime OA decreases by 1.7~1.9 %/year with little month-to-month variability, while sulfate declines rapidly with significant monthly difference in early 2000s. In contrast, modeled OA from a chemical-transport model (GEOS-Chem) decreases by 4.9 %/year with much larger month-to-month variability, largely due to the predominant role of acid-catalyzed reactive uptake of epoxydiols (IEPOX) onto sulfate. The overestimated modeled OA dependence on sulfate can be improved by implementing a coating effect and assuming constant aerosol acidity, suggesting the needs to revisit IEPOX reactive uptake in current models. Our work highlights the importance of secondary OA formation pathways that are weakly dependent on inorganic aerosol in a region that is heavily influenced by both biogenic and anthropogenic emissions. [ABSTRACT FROM AUTHOR]

Methane (CH4) is both a greenhouse gas and a precursor of tropospheric ozone, making it an important focus of chemistry-climate interactions. Methane has both anthropogenic and natural emission sources, and reaction with the atmosphere's principal oxidizing agent, the hydroxyl radical (OH), is the dominant tropospheric loss process of methane. The tight coupling between methane and OH abundances drives indirect linkages between methane and other short-lived air pollutants and prompts the use of interactive methane chemistry in global chemistry-climate modeling. In this study, an updated contemporary inventory of natural methane emissions and the soil sink is developed using an optimization procedure that applies published emissions data to the NASA GISS ModelE2-Yale Interactive terrestrial Biosphere (ModelE2-YIBs) global chemistry-climate model. Methane observations from the global surface air-sampling network of the Earth System Research Laboratory (ESRL) of the U.S. National Oceanic and Atmospheric Administration (NOAA) are used to guide refinement of the natural methane inventory. The optimization process indicates global annual wetland methane emissions of 140 Tg CH4 y-1. The updated inventory includes total global annual methane emissions from natural sources of 181 Tg CH4 y-1 and a global annual methane soil sink of 60 Tg CH4 y-1. An interactive-methane simulation is run using ModelE2-YIBs, applying dynamic methane emissions and the updated natural methane emissions inventory that results from the optimization process. The simulated methane chemical lifetime of 10.4 ± 0.1 years corresponds well to observed lifetimes. The simulated year 2005 global-mean surface methane concentration is 1.1 % higher than the observed value from the NOAA ESRL measurements. Comparison of the simulated atmospheric methane distribution with the NOAA ESRL surface observations at 50 measurement locations finds that the simulated annual methane mixing ratio is within 1 % (i.e., +1 % to -1 %) of the observed value at 76 % of locations. Considering the 50 stations, the mean relative difference between the simulated and observed annual methane mixing ratio is a model overestimate of only 0.5 %. Comparison of simulated annual column-averaged methane concentrations with SCIAMACHY satellite retrievals provides an independent post-optimization evaluation of modeled methane. The comparison finds a slight model underestimate in 95 % of grid cells, suggesting that the applied methane source in the model is slightly underestimated or the model's methane sink strength is slightly too strong outside of the surface layer. Overall, the strong agreement between simulated and observed methane lifetimes and concentrations indicates that the ModelE2-YIBs chemistry-climate model is able to capture the principal processes that control atmospheric methane. [ABSTRACT FROM AUTHOR]

We apply the NCAR CAM5-Chem global aerosol-climate model to quantify the net global radiative effects of black and organic carbon aerosols from global and Indian solid fuel cookstove emissions for the year 2010. Our updated assessment accounts for the direct radiative effects, changes to cloud albedo and lifetime (aerosol indirect effect, AIE), impacts on clouds via the vertical temperature profile (semi-direct effect, SDE), and changes in the surface albedo of snow and ice (surface albedo effect). In addition, we provide the first estimate of household solid fuel black carbon emission effects on ice clouds. Anthropogenic emissions are from the IIASA GAINS ECLIPSE V5a inventory. A global dataset of black carbon (BC) and organic aerosol (OA) measurements from surface sites and aerosol optical depth (AOD) from AERONET is used to evaluate the model skill. Compared with observations, the model successfully reproduces the spatial patterns of atmospheric BC and OA concentrations, and agrees with measurements to within a factor of 2. Globally, the simulated AOD agrees well with observations, with normalized mean bias close to zero. However, the model tends to underestimate AOD over India and China by ~ 19 % but overestimate it over Africa by ~ 25 %. Without BC serving as ice nuclei (IN), global and Indian solid fuel cookstove aerosol emissions have a net cooling impact on global climate of -141 ± 4 mW m-2 and -12 ± 4 mW m-2, respectively. The net radiative impacts are dominated by the AIE and SDE mechanisms, which originate from enhanced cloud condensation nuclei concentrations for the formation of liquid and mixed-phase clouds, and a suppression of convective transport of water vapor from the lower troposphere to the upper troposphere/lower stratosphere that in turn leads to reduced ice cloud formation. When BC is allowed to behave as a source of IN, the net global climate impacts of the global and Indian solid fuel cookstove emissions range from -260 to +135 mW m-2 and -33 to +24 mW m-2, with globally averaged values -51 ± 210 and 0.3 ± 29 mW m-2 respectively. The uncertainty range is calculated from sensitivity simulations that alter the maximum freezing efficiency of BC across a plausible range: 0.01, 0.05 and 0.1. BC-ice cloud interactions lead to substantial increases in high cloud (< 500 hPa) fractions. Thus, the net sign of the impacts of carbonaceous aerosols from solid fuel cookstoves on global climate (warming or cooling) remains ambiguous until improved constraints on BC interactions with mixed-phase and ice clouds are available. [ABSTRACT FROM AUTHOR]