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The Gross Primary Productivity (GPP) is an important component in regional and global carbon budgets. Southeastern China has experienced vegetation greening and climate change. Yet, it remains unclear how these changes have impacted GPP in this region. As one of six special national parks in China with complex topography, high biodiversity, and little destructive human activities to the ecosystems, the Wuyi Mountain region is selected to study these impacts. In this study, we use a hydroecological model (BEPS-TerrainLab V2.0) to simulate the spatial and temporal variations of GPP in the Wuyi Mountain region over 2001–2018. We quantitatively separate the effects of vegetation greening and climate change on the trend and interannual variation in GPP through sensitivity experiments. The results show a significant increasing trend in Leaf Area Index (LAI) in the region over 2001–2018 (0.06 m2 m−2 yr−1, p

Abstract Events of stratospheric intrusions to the surface (SITS) can lead to severe ozone (O3) pollution. Still, to what extent SITS events impact surface O3 on a national scale over years remains a long-lasting question, mainly due to difficulty of resolving three key SITS metrics: frequency, duration and intensity. Here, we identify 27,616 SITS events over China during 2015-2022 based on spatiotemporally dense surface measurements of O3 and carbon monoxide, two effective indicators of SITS. An overview of the three metrics is presented, illustrating large influences of SITS on surface O3 in China. We find that SITS events occur preferentially in high-elevation regions, while those in plain regions are more intense. SITS enhances surface O3 by 20 ppbv on average, contributing to 30-45% of O3 during SITS periods. Nationally, SITS-induced O3 peaks in spring and autumn, while over 70% of SITS events during the warm months exacerbate O3 pollution. Over 2015-2022, SITS-induced O3 shows a declining trend. Our observation-based results can have implications for O3 mitigation policies in short and long terms.

Urban tree classification enables informed decision-making processes in urban planning and management. This paper introduces a novel data reformation method, pseudo tree crown (PTC), which enhances the feature difference in the input layer and results in the improvement of the accuracy and efficiency of urban tree classification by utilizing artificial intelligence (AI) techniques. The study involved a comparative analysis of the performance of various machine learning (ML) classifiers. The results revealed a significant enhancement in classification accuracy, with an improvement exceeding 10% observed when high spatial resolution imagery captured by an unmanned aerial vehicle (UAV) was utilized. Furthermore, the study found an impressive average classification accuracy of 93% achieved by a classifier built on the PyTorch framework, with ResNet50 leveraged as its convolutional neural network layer. These findings underscore the potential of AI-driven approaches in advancing urban tree classification methodologies for enhanced urban planning and management practices.

The ozone (O3) variations in southeast China are largely different between mountainous forest areas located inland, and lowland urban areas located near the coast. Here, we selected these two kinds of areas to compare their similarities and differences in surface O3 variability from diurnal to seasonal scales. Our results show that in comparison with the lowland urban areas (coastal areas), the mountainous forest areas (inland areas) are characterized with less human activates, lower precursor emissions, wetter and colder meteorological conditions, and denser vegetation covers. This can lead to lower chemical O3 production and higher O3 deposition rates in the inland areas. The annual mean of 8-h O3 maximum concentrations (MDA8 O3) in the inland areas are ~15 μg·m−3 (i.e. ~15%) lower than that in the coastal areas. The day-to-day variation in surface O3 in the two types of the areas is rather similar, with a correlation coefficient of 0.75 between them, suggesting similar influences on large scales, such as weather patterns, regional O3 transport, and background O3. Over 2016–2020, O3 concentrations in all the areas shows a trend of “rising and then falling”, with a peak in 2017 and 2018. Daily MDA8 O3 correlates with solar radiation most in the coastal areas, while in the inland areas, it is correlated with relative humidity most. Diurnally, during the morning, O3 concentrations in the inland areas increase faster than in the coastal areas in most seasons, mainly due to a faster increase in temperature and decrease in humidity. While in the evening, O3 concentrations decrease faster in the inland areas than in the coastal areas, mostly attributable to a higher titration effect in the inland areas. Seasonally, both areas share a double-peak variation in O3 concentrations, with two peaks in spring and autumn and two valleys in summer and winter. We found that the valley in summer is related to the summer Asian monsoon that induces large-scale convections bringing local O3 upward but blocking inflow of O3 downward, while the one in winter is due to low O3 production. The coastal areas experienced more exceedance days (~30 days per year) than inland areas (~5-10 days per year), with O3 sources largely from the northeast. Overall, the similarities and differences in O3 concentrations between inland and coastal areas in southeastern China are rather unique, reflecting the collective impact of geographic-related meteorology, O3 precursor emissions, and vegetation on surface O3 concentrations.

Abstract Surface ozone increased unexpectedly over northern China during the COVID-19 lockdown (CLD) period (23 January–29 February 2020), which was characterized by vigorous emission reduction. The reasons for this ozone enhancement have been speculated from perspectives of chemical responses to the emissions and meteorology. As known, the processes of natural stratospheric ozone injecting to the troposphere are most active in winter and spring. Yet, little attention was paid to stratospheric influences on this ozone enhancement. Here we report a stratospheric intrusion (SI) that reached the surface over northern China on 15–17 February during the CLD. The coevolution of enhanced ozone and sharply declined carbon monoxide and relative humidity (RH) was indicative of the SI occurrence. We show that the SI was facilitated by a cutoff low system that led to abnormally high surface ozone in most part of northern China. We estimate that over the SI period, the injected stratospheric ozone constituted up to 40–45% of the surface ozone over northern China. If the stratospheric ozone inputs were scaled over the entire CLD period, these inputs would account for 4–8% of the surface ozone. In view of the unexpected ozone increase during the CLD, this SI event could explain up to 18% of the ozone increase in some cities, and average 5–10% over larger areas that were affected. Hence, the nonnegligible stratospheric influences urge extra consideration of natural ozone sources in disentangling the role of emission reduction and meteorological conditions during the CLD in China and elsewhere in the world.

Climate change has caused more frequent instances of extreme climatic events around the world, being an influential factor on the occurrence of wildfires in China on large scale. However, the impact of changes in extreme climate on the occurrence of wildfires in different climate zones remains unclear. In the present study, 26 extreme climate indices were selected to analyze the thereof relationship with wildfire occurrences from 2005 to 2018 in different regions of China. Wildfires in China primarily occur in the south, with a measurable presence in the north. On an annual scale, the wildfire occurrences in southwestern China show stronger correlations with mean temperature than extreme temperature indices, but show stronger correlations with extreme precipitation indices than the total precipitation. On the contrary, the wildfire occurrences in southeastern China show stronger correlations with the total precipitation than extreme precipitation indices, but show stronger correlations with extreme temperature indices than the mean temperature. In Northeast China, wildfires show a more significant correlation with mean temperature than with any extreme climate indices, indicating a minimal impact from extreme climatic conditions. The fire-climate relationships in the main fire season (January-April) are similar to those in the annual scale. The wildfire occurrences in the southwestern, south-central, and southeastern China, which are located in the same latitudes, were affected by extreme climate indices of different types and on different time scales. Furthermore, we recommend that consecutive dry days (CDD) and diurnal temperature range (DTR) should be considered first when studying the relationship between wildfire occurrence and extreme climate in southwestern and southeastern China respectively.

Surface ozone (O3) is influenced not only by anthropogenic emissions but also by meteorological factors, with wind direction being one of the most overlooked factors. Here, we combine the observational data of both O3 and wind flow to compare the variation in surface O3 with wind direction between coastal and inland regions of Fujian, a province in the southeast coast of China with complicated topography. We further conduct a numerical simulation using a global chemical transport model, GEOS-Chem, to interpret the observational results, explore the linkages between these O3 variations and wind flows, and identify the dominant processes for the occurrence of high O3 that varies with wind flows. The results from the observations over 2015–2021 suggest that, over coastal regions, surface O3 concentrations show a strong dependence on wind flow changes. On average, during the daytime, when southeasterly winds prevail, the mean of O3 concentrations reaches 83.5 μg/m3, which is 5.0 μg/m3 higher than its baseline values (the mean O3 concentrations), while the northwesterly winds tend to reduce surface O3 by 6.4 μg/m3. The positive O3 anomalies with southeasterly wind are higher in the autumn and summer than in the spring and winter. During the nighttime, the onshore northeasterly winds are associated with enhanced O3 levels, likely due to the airmass containing less NO2, alleviating the titration effects. Over inland regions, however, surface O3 variations are less sensitive to wind flow changes. The GEOS-Chem simulations show that the prevailing southeasterly and southwesterly winds lead to the positive anomaly of chemical reactions of O3 over coastal regions, suggesting enhanced photochemical production rates. Furthermore, southeasterly winds also aid in transporting more O3 from the outer regions into the coastal regions of Fujian, which jointly results in elevated surface O3 when southeasterly winds dominates. When affected by wind flows in different directions, the chemical reaction and transport in the inland regions do not exhibit significant differences regarding their impact on O3. This could be one of the reasons for the difference in O3 distribution between coastal and inland regions. This study could help to deepen our understanding of O3 pollution and aid in providing an effective warning of high-O3 episodes.

Abstract Objectives To compare overall agreement between magnetic resonance imaging (MRI)–ultrasound (US) fusion biopsy (FB) and MRI cognitive fusion biopsy (CB) of the prostate and determine which factors affect agreement for prostate cancer (PCa) who underwent both modalities in a prospective within‐patient protocol. Patients and Methods From August 2017 to January 2021, patients with at least one Prostate Imaging Reporting & Data System (PI‐RADS) 3 or higher lesion on multiparametric MRI underwent transrectal FB and CB in a prospective within‐patient protocol. CB was performed for each region of interest (ROI), followed by FB, followed by standard 12 core biopsy. Patients who were not on active surveillance were analysed. The primary endpoint was agreement for any PCa detection. McNemar's test and kappa statistic were used to analyse agreement. Chi‐square test, Fisher's exact test and Wilcoxon rank sum test were used to analyse disagreement across clinical and MRI spatial variables. A multivariable generalized mixed‐effect model was used to compare the interaction between select variables and fusion modality. Statistics were performed using SAS and R. Results Ninety patients and 98 lesions were included in the analysis. There was moderate agreement between FB and CB (k = 0.715). McNemar's test was insignificant (p = 0.285). Anterior location was the only variable associated with a significant variation in agreement, which was 70% for anterior lesions versus 89.7% for non‐anterior lesions (p = 0.035). Discordance did not vary significantly across other variables. In a mixed‐effect model, the interaction between anterior location and use of FB was insignificant (p = 0.411). Conclusion In a within‐patient protocol of patients not on active surveillance, FB and CB performed similarly for PCa detection and with moderate agreement. Anterior location was associated with significantly higher disagreement, whereas other patient and lesion characteristics were not. Additional studies are needed to determine optimal biopsy technique for sampling anterior ROI.

Shallow convective clouds (SCCs) frequently occur over mountainous terrain. However, previous studies have mostly focused on SCCs over flat surfaces. Here, the effects of mountainous terrains on the cloud size distributions (CSDs) and spatial distributions of SCCs are investigated using data obtained from the Landsat-8 satellite. We find that the CSDs are well-described by double power laws separated by scale breaks. The CSDs are controlled by two parameters, i.e., the scale breaks and the number of clouds with sizes between 0.2 and 1 times the scale breaks. We also find that the number of clouds generally increases with the elevation. In particular, the number of clouds larger than the scale breaks increases faster than that of the smaller clouds. The sizes of the larger clouds (the 90th and 95th percentiles) increase with the elevation, while the sizes of the smaller clouds are not sensitive to the elevation. It is suggested that the variations of cloud numbers and sizes with elevation should be used together with the CSDs to describe the cloud fields over mountainous terrains.

Antimicrobial resistance (AMR) is a threat to global public health. However, unsatisfactory approaches to directly measuring the AMR burden carried by individuals has hampered efforts to assess interventions aimed at reducing selection for AMR. Metagenomics can provide accurate detection and quantification of AMR genes within an individual person's faecal flora (their gut "resistome"). Using this approach, we aimed to test the hypothesis that differences in antimicrobial use across different hospitals in the United Kingdom will result in observable differences in the resistome of individual patients. Three National Health Service acute Hospital Trusts with markedly different antibiotic use and Clostridioides difficile infection rates collected faecal samples from anonymous patients which were discarded after C. difficile testing over a period of 9 to 15 months. Metagenomic DNA was extracted from these samples and sequenced using an Illumina NovaSeq 6000 platform. The resulting sequencing reads were analysed for taxonomic composition and for the presence of AMR genes. Among 683 faecal metagenomes we found huge variation between individuals in terms of taxonomic diversity (Shannon Index range 0.10-3.99) and carriage of AMR genes (Median 1.50 genes/cell/sample overall). We found no statistically significant differences in diversity (median Shannon index 2.16 (IQR 1.71-2.56), 2.15 (IQR 1.62-2.50) and 2.26 (IQR 1.55-2.51)) or carriage of AMR genes (median 1.37 genes/cell/sample (IQR 0.70-3.24), 1.70 (IQR 0.70-4.52) and 1.43 (IQR 0.55-3.71)) at the three trusts respectively. This was also the case across the sample collection period within the trusts. While we have not demonstrated differences over place or time using metagenomic sequencing of faecal discards, other sampling frameworks may be more suitable to determine whether organisational level differences in antibiotic use are associated with individual-level differences in burden of AMR carriage.

ABSTRACT: Disruptive innovation forces small-business managers to innovate by carrying out exploitation and exploration activities simultaneously. This ambidexterity is crucial to the survival of today’s businesses, especially small and medium-sized enterprises (SMEs). In the organizational structure of SMEs, the manager and owner play an essential role in determining the business orientation. This study examined the influence of SME managers’ social networks on the organization’s ambidexterity and its impact on the firm’s innovation performance. This study used two moderating variables in the form of two internal factors in respect to managers: how proactive they are and their commitment to innovation. The study population was drawn from SMEs in the creative manufacturing sector in Indonesia and Taiwan, with a total sample of 224 SMEs, including 101 from Indonesia and 123 from Taiwan. The analytical technique was the PLS-SEM, conducted by the Smart-PLS software version 3.3.6: Hamburg, Germany. The results supported the construction in both countries. The results of the multiple-group analysis show that the SMEs in Indonesia exhibited greater ambidexterity, commitment to innovation, and innovation performance than those in Taiwan.

Carbon monoxide (CO) is an important trace gas in the troposphere, while the El Niño-Southern Oscillation (ENSO) phenomenon is the most important tropical climate variability. ENSO is known to influence interannual variation in meteorological variables on the global scale but its influence on atmospheric CO over large areas in a long term is uncertain. Here we report a strong positive teleconnection between the El Niño–Southern Oscillation (ENSO) in winter (November to February) to tropospheric CO over the North Atlantic European region (NAE) in the following spring (March to May). This ENSO teleconnection is evident in trajectory-mapped airborne CO data (In-service Aircraft for a Global Observing System, IAGOS) over 2002–2019. CO concentrations in El Niño years are 5–20 ppbv higher than those in La Niña years over the NAE troposphere. The regional mean difference from the surface to 300 hPa is 9.4 ppbv (7.6% of the mean). The correlation coefficient (r) between the ENSO index and detrended CO concentrations in the NAE is 0.67 at 400 hPa and 0.63 near the surface, both statistically significant at the 95% level. Such a teleconnection is also observed in independent surface observations, with r ranging from 0.57 to 0.74, all at 95% significance level. From analysis of fire emissions and atmospheric conditions, combined with tagged CO simulations using a chemical transport model, GEOS-Chem, we conclude that this teleconnection results from the combined effects of ENSO on both biomass burning and atmospheric transport. We find that in El Niño years, CO emissions from biomass burning are significantly enhanced in Northern Hemispheric South America, Southeast Asia, and North America due to warmer air temperatures and lowered precipitation. In addition, ENSO enhances CO transport from these regions to the NAE by enhancing upward and northeastward motions in the fire regions, accelerating westerlies over 20°N–40°N, and prompting ascents over the Atlantic and descents over Europe, while reducing CO outflow at the eastern boundary of Europe. The combined effect of ENSO on both CO emissions and CO transport leads to interannual variability in tropospheric CO over the NAE.

Absorbing aerosols have significant influences on tropospheric photochemistry and regional climate change. Here, the direct radiative effects of absorbing aerosols at the major AERONET sites in East Asia and corresponding impacts on near-surface photochemical processes were quantified by employing a radiation transfer model. The average annual aerosol optical depth (AOD) of sites in China, Korea, and Japan was 1.15, 1.02 and 0.94, respectively, and the corresponding proportion of absorbing aerosol optical depth (AAOD) was 8.61%, 6.69%, and 6.49%, respectively. The influence of absorbing aerosol on ultraviolet (UV) radiation mainly focused on UV-A band (315–400 nm). Under the influence of such radiative effect, the annual mean near-surface J[NO2] (J[O1D]) of sites in China, Korea, and Japan decreased by 16.95% (22.42%), 9.61% (13.55%), and 9.63% (13.79%), respectively. In Beijing–Tianjin–Hebei (BTH) and Yangtze River Delta (YRD) region, the annual average AOD was 1.48 and 1.29, and the AAOD was 0.14 and 0.13, respectively. The UV radiative forcing caused by aerosols dominated by black carbon (BC-dominated aerosols) on the surface was −3.19 and −2.98 W m−2, respectively, accounting for about 40% of the total aerosol radiative forcing, indicating that the reduction efficiency of BC-dominated aerosols on solar radiation was higher than that of other types of aerosols. The annual mean J[NO2] (J[O1D]) decreased by 14.90% (20.53%) and 13.71% (18.20%) due to the BC-dominated aerosols. The daily maximum photolysis rate usually occurred near noon due to the diurnal variation of solar zenith angle and, thus, the daily average photolysis rate decreased by 2–3% higher than that average during 10:00–14:00.

Fire activity in China and its associations with climate are not well quantified at a local scale. Here, the authors present a detailed fire occurrence dataset for China and find a dipole fire pattern between southwestern and southeastern China that is modulated by the El Niño-Southern Oscillation (ENSO).

Carbon and water fluxes in ecosystems are tightly coupled by gas diffusion through stomata. However, carbon–water (C–W) relationships vary largely across time scales, vegetation types, and regions. Subtropical forests in China play an important role in the global carbon and water cycles, yet studies of C–W relationships in this region remain limited. Here, we investigated summer-time C–W relationships in this region at two subtropical sites: the evergreen broadleaved forest at Dinghushan (23.17° N, 112.53° E, 300 m) and the evergreen coniferous forest at Qianyanzhou (26.74° N, 115.06° W, 106 m), using the flux tower data from the FLUXNET2015. The C–W relationship was examined using two measures. The first was daily water use efficiency (WUE), which is the ratio of daily gross primary productivity (GPP) to evapotranspiration (ET). The second was the correlation coefficient (r) of hourly GPP and ET. Our analysis showed that the daily WUE in the two forests ranged over 4–14 mg CO2 per g H2O, higher in the coniferous forest than in the broadleaved forest. The mean values of r for hourly C–W coupling were similar at the two forests, being 0.5–0.6, which suggests asynchronous diurnal variations in GPP and ET. Both daily WUE and r were modulated by meteorological conditions. In general, high radiation, air temperature, and humidity can reduce WUE at both sites. For the broadleaved forest, the most influential factor on WUE was VPD, followed by radiation, while in the coniferous forest, VPD, air temperature, and radiation were almost equally important. For hourly C–W coupling, VPD plays a significant role. The drier the air is, the weaker the coupling in the two forests. The daily WUE and hourly C–W coupling reflect the C–W relationship from different perspectives. Both showed the strongest response to VPD but with different sensitivity.

The vertical distribution of tropospheric O3 from ozonesondes is compared with that from In-service Aircraft for a Global Observing System (IAGOS) measurements at 23 pairs of sites between about 30°S and 55°N, from 1995 to 2021. Profiles of tropospheric O3 from IAGOS aircraft are in generally good agreement with ozonesonde observations, for Electrochemical concentration cells (ECC), Brewer-Mast, and Carbon-Iodine sensors, with average biases of 7.03 ppb, 6.28 ppb, and -4.48 ppb, and correlation coefficients (R) of 0.72, 0.86, and 0.82, respectively. Agreement between the aircraft and Indian-sonde observations is poor, with an average bias of 24.07 ppb and R of 0.41. The O3 concentration observed by ECC sondes is on average higher by 5-10% than that observed by IAGOS aircraft, and the relative bias increases modestly with altitude. For other sonde types, there are some seasonal and altitude variations in the relative bias with respect to IAGOS measurements, but these appear to be caused by local differences. The distance between station and airport within 4° has little effect on the comparison results. For the ECC ozonesonde, the overall bias with respect to IAGOS measurements varies from 5.7 to 9.8 ppb, when the station pairs are grouped by station-airport distances of <1° (latitude and longitude), 1-2°, and 2-4°. Correlations for these groups are R = 0.8, 0.9 and 0.7. These comparison results provide important information for merging ozonesonde and IAGOS measurement datasets. They can also be used to evaluate the relative biases of the different sonde types in the troposphere, using the aircraft as a transfer standard. [ABSTRACT FROM AUTHOR]

Abstract When many cities need quantitative forecasts of air quality to adjust industrial production plans and urbanization development, how to build an efficient forecast model remain a challenge. Methodology for quantitative prediction of air quality can no longer rely on single‐site observations, and thus approaches that require fewer input data and are more efficient and more reliable need to be explored. This paper proposes the principles and steps of a new model using the empirical orthogonal function (EOF) and principal component regression (PCR), which is a hybrid EOF‐PCR approach that decomposes the panel data of PM2.5 and predictors into spatial structures (EOFs) and time expansion coefficients (ECs) by EOF analysis, establishes the PCR of the ECs of PM2.5, and simulates the PM2.5 concentrations in each city by projecting the fitted ECs through EOFs. The very heart of the new model is the PCR modeling and projection. The results are presented for PM2.5 concentrations over Jiangsu Province in eastern China. The results show that this EOF‐PCR model, which is based on EC1s with a cumulative variance contribution rate above 90%, has an average prediction accuracy of 65%. The model performs best in spring and autumn, better in summer and worst in winter. Most predictors have a maximum lag of a week, and they are quite different among seasons. Considering the influence of the spatial distributions of predictors, rather than covariates at a single site, this model can reflect regional influences and effectively improve the simulation effect.

Aim Gunshot wounds (GSW) to the penis represent a rare type of traumatic injury in the civilian United States population. Although small, single‐center studies have reported results of care for these types of injured patients, no national analyses have examined this group. Methods A cohort of patients with GSW to the penis was identified using the 2017 American College of Surgeons Trauma Quality Programs database, a comprehensive national database of 753 accredited trauma centers. Results Gunshot wounds to the penis occurred in 722 patients, which represents 1.7% of all GSW patients (n = 41,017). Gunshot wounds from altercations with law enforcement or accidental discharge of a firearm were rare; the vast majority (n = 655, 90.7%) occurred as a result of assault, intentional self‐harm, attempted suicide, or attempted homicide. Patients with a major concomitant non‐genitourinary injury comprised 119 (16.5%) patients of the cohort. Most patients (n = 499, 69.1%) underwent a genitourinary procedure during their trauma admission. Penile salvage was successful in most cases, with only 13 (1.8%) patients requiring completion penectomy. Most patients (87.8%) required admission with a median length of stay of 49.8 h. Most patients were treated at the initial trauma center without requiring transfer to another center, and complications during admission were rare. Conclusions This analysis, the first national examination of care of patients with GSW to the penis, reveals overall favorable outcomes. Admission and surgical intervention were required in most patients, but penectomy was rare and length of stay was generally short. These results will guide resource utilization and quality improvement efforts in this patient cohort.

An objective method, employing HYSPLIT back-trajectories and Moderate Resolution Imaging Spectroradiometer (MODIS) fire observations, is developed to estimate ozone enhancement in air transported from regions of active forest fires at 18 ozone sounding sites located across North America. The Differential Back Trajectory (DBT) method compares mean differences between ozone concentrations associated with fire-affected and fire-unaffected parcels. It is applied to more than 1100 ozonesonde profiles collected from these sites during the summer months June to August 2006, 2008, 2010 and 2011. Layers of high ozone associated with low humidity were first removed from the ozonesonde profiles to minimize the potential effects of stratospheric intrusions on the calculations. No significant influence on average ozone levels by North American fires was found for stations located at Arctic latitudes. The ozone enhancement for stations nearer large fires, such as Trinidad Head and Bratt's Lake, was up to 4.8% of the TTOC (Total Tropospheric Ozone Column). Fire ozone accounted for up to 8.3% of TTOC at downwind sites such as Yarmouth, Sable Island, Narragansett, and Walsingham. The results are consistent with other studies that have reported an increase in ozone production with the age of the smoke plume.

Abstract Background Extracellular vesicles (EVs) and exosomes are nano-sized, membrane-bound vesicles shed by most eukaryotic cells studied to date. EVs play key signaling roles in cellular development, cancer metastasis, immune modulation and tissue regeneration. Attempts to modify exosomes to increase their targeting efficiency to specific tissue types are still in their infancy. Here we describe an EV membrane anchoring platform termed “cloaking” to directly embed tissue-specific antibodies or homing peptides on EV membrane surfaces ex vivo for enhanced vesicle uptake in cells of interest. The cloaking system consists of three components: DMPE phospholipid membrane anchor, polyethylene glycol spacer and a conjugated streptavidin platform molecule, to which any biotinylated molecule can be coupled for EV decoration. Results We demonstrate the utility of membrane surface engineering and biodistribution tracking with this technology along with targeting EVs for enhanced uptake in cardiac fibroblasts, myoblasts and ischemic myocardium using combinations of fluorescent tags, tissue-targeting antibodies and homing peptide surface cloaks. We compare cloaking to a complementary approach, surface display, in which parental cells are engineered to secrete EVs with fusion surface targeting proteins. Conclusions EV targeting can be enhanced both by cloaking and by surface display; the former entails chemical modification of preformed EVs, while the latter requires genetic modification of the parent cells. Reduction to practice of the cloaking approach, using several different EV surface modifications to target distinct cells and tissues, supports the notion of cloaking as a platform technology.

From the earliest observations of ozone in the lower atmosphere in the 19th century, both measurement methods and the portion of the globe observed have evolved and changed. These methods have different uncertainties and biases, and the data records differ with respect to coverage (space and time), information content, and representativeness. In this study, various ozone measurement methods and ozone datasets are reviewed and selected for inclusion in the historical record of background ozone levels, based on relationship of the measurement technique to the modern UV absorption standard, absence of interfering pollutants, representativeness of the well-mixed boundary layer and expert judgement of their credibility. There are significant uncertainties with the 19th and early 20th-century measurements related to interference of other gases. Spectroscopic methods applied before 1960 have likely underestimated ozone by as much as 11% at the surface and by about 24% in the free troposphere, due to the use of differing ozone absorption coefficients. There is no unambiguous evidence in the measurement record back to 1896 that typical mid-latitude background surface ozone values were below about 20 nmol mol–1, but there is robust evidence for increases in the temperate and polar regions of the northern hemisphere of 30–70%, with large uncertainty, between the period of historic observations, 1896–1975, and the modern period (1990–2014). Independent historical observations from balloons and aircraft indicate similar changes in the free troposphere. Changes in the southern hemisphere are much less. Regional representativeness of the available observations remains a potential source of large errors, which are difficult to quantify. The great majority of validation and intercomparison studies of free tropospheric ozone measurement methods use ECC ozonesondes as reference. Compared to UV-absorption measurements they show a modest (~1–5% ±5%) high bias in the troposphere, but no evidence of a change with time. Umkehr, lidar, and FTIR methods all show modest low biases relative to ECCs, and so, using ECC sondes as a transfer standard, all appear to agree to within one standard deviation with the modern UV-absorption standard. Other sonde types show an increase of 5–20% in sensitivity to tropospheric ozone from 1970–1995. Biases and standard deviations of satellite retrieval comparisons are often 2–3 times larger than those of other free tropospheric measurements. The lack of information on temporal changes of bias for satellite measurements of tropospheric ozone is an area of concern for long-term trend studies.

Accuracy of global tropopause altitude products from reanalyses is important to applications of the products, including the derivation of tropospheric column ozone (TCO). Here, monthly biases in lapse-rate tropopause pressure (PLRT) in two reanalyses, NCEP/NCAR and MERRA-2, and associated implications for estimating TCO are examined, based on global radiosonde observations over 1980–2017 at 689 stations. Our analysis suggests that the global mean PLRT is underestimated by −2.3 hPa in NCEP/NCAR and by −0.9 hPa in MERRA-2, mainly attributable to large negative biases around the subtropics (~20°–50°) in both hemispheres, with generally positive biases at other latitudes. Overall, NCEP/NCAR outperforms MERRA-2 in the Northern Hemisphere but underperforms MERRA-2 in the Southern Hemisphere. PLRT biases in the two reanalyses vary more evidently with latitude than with longitude. From winter to summer, the peaks of negative PLRT biases around the subtropics shift poleward by ~10°. Approximately, 70% of the reanalysis PLRT biases are within −10–10 hPa. Consequently, a negative (positive) PLRT bias induces a positive (negative) TCO bias. In absolute magnitude, the mean ozonesonde TCO bias attributable to PLRT biases is ~0.2, ~0.8 and ~1.2 Dobson Units (DU) if a PLRT bias is within 0–5, 10–15, and 10–15 hPa. Using a global ozone climatology, we estimate that the global mean bias in TCO induced by the PLRT biases in both reanalyses is positive, being 0.64 DU (or 2.2%) for NCEP/NCAR and 0.28 DU (or 1.1%) for MERRA-2.

Diagnostic terrestrial biosphere models (TBMs) forced by remote sensing observations have been a principal tool to provide benchmarks on global gross primary productivity (GPP) and evapotranspiration (ET). However, these models often estimate GPP and ET at coarse daily or monthly step, hindering analysis of ecosystems dynamics at the diurnal (hourly) scales, and prescribe some essential parameters (i.e., the Ball-Berry slope (m) and the maximum carboxylation rate at 25 °C (Vcmax25)) as constant, inducing uncertainties in the estimates of GPP and ET. In this study, we present hourly estimation of global GPP and ET datasets at a 0.25° resolution from 2001 to 2020 simulated with a widely used diagnostic TBM – Biosphere-atmosphere Exchange Process Simulator (BEPS). We employed eddy covariance observations and machine learning approaches to derive and upscale the seasonally varied m and Vcmax25 for carbon and water fluxes. The estimated hourly GPP and ET are validated against flux observation, remote sensing, and machine learning-based estimates across multiple spatial and temporal scales. The correlation coefficients (R²) and slopes between hourly tower-measured and modeled fluxes are: R² = 0.83, regression slope = 0.92 for GPP and, R² = 0.72, regression slope = 1.04 for ET. At the global scale, we estimated a global mean GPP of 137.78 ± 3.22 Pg C yr-1 (mean ± 1 SD) with a positive trend of 0.53 Pg C yr-2 (p < 0.001), and ET of 89.03 ± 0.82 × 103 km³ yr-1 with a slight positive trend of 0.10 × 103 km³ yr-2 (p < 0.001) from 2001 to 2020. The spatial pattern of our estimates agrees well with other products, with R² = 0.77–0.85 and R² = 0.74–0.90 for GPP and ET, respectively. Overall, this new global hourly dataset serves as a `handshake’ among process-based models, remote sensing, and the eddy covariance flux network, providing a reliable long-term estimate of global GPP and ET with diurnal patterns and facilitating studies related to ecosystem functional properties, global carbon, and water cycles. The hourly and accumulated daily GPP and ET estimates are available at https://doi.org/10.5281/zenodo.8240492 (Leng et al., 2023). [ABSTRACT FROM AUTHOR]