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Atmospheric humic-like substances (HULIS) affect the global radiation balance due to their strong light absorption at the ultraviolet wavelength. The potential sources and molecular compositions of water-soluble HULIS at a suburban site in the Yangtze River Delta from 2017 to 2018 were discussed, based on the results of the radiocarbon (14C) analysis and combining the Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) technique in this study. The 14C results showed that the averaged non-fossil-fuel source contributions to HULIS were 39 ± 8 % and 36 ± 6 % in summer and winter, respectively, indicating significant contributions from fossil fuel sources to HULIS. The Van Krevelen diagrams obtained from the FT-ICR-MS results showed that the proportions of tannin-like and carbohydrate-like groups were higher in summer, suggesting significant contribution of HULIS from biogenic secondary organic aerosols (SOAs). The higher proportions of condensed aromatic structures in winter suggested increasing anthropogenic emissions. Molecular composition analysis on the CHO, CHON, CHOS, and CHONS subgroups showed relatively higher intensities of high O-containing macromolecular oligomers in the CHO compounds in summer, further indicating stronger biogenic SOA formation in summer. High-intensity phenolic substances and flavonoids, which were related to biomass burning and polycyclic aromatic hydrocarbon (PAH) derivatives indicating fossil fuel combustion emissions, were found in winter CHO compounds. Besides, two high-intensity CHO compounds containing condensed aromatic ring structures (C9H6O7 and C10H5O8) identified in the summer and winter samples were similar to those from off-road engine samples, indicating that traffic emissions were one of the important fossil fuel sources of HULIS at the study site. The CHON compounds were mainly composed of nitro compounds or organonitrates with significantly higher intensities in winter, which were associated with biomass burning emissions, in addition to the enhanced formation of organonitrates due to high NOx in winter. However, the high-intensity CHON molecular formulas in summer were referring to N-heterocyclic aromatic compounds, which were produced from the atmospheric secondary processes involving reduced N species (e.g., ammonium). The S-containing compounds were mainly composed of organosulfates (OSs) derived from biogenic precursors, namely long-chain alkane and aromatic hydrocarbon, which illustrate the mixed sources of HULIS. Generally, different policies need to be considered for each season due to the different seasonal sources (i.e., biogenic emissions in summer and biomass burning in winter for non-fossil-fuel sources, traffic emissions and anthropogenic SOA formation in both seasons, and additional coal combustion in winter). Measures to control emissions from motor vehicles and industrial processes need to be considered in summer. Additional control measures on coal power plants and biomass burning should be applied in winter. These findings add to our understanding of the interaction between the sources and the molecular compositions of atmospheric HULIS.

Volatile organic compounds (VOCs) are key components of tropospheric chemistry. We investigated ambient VOCs in an industrial area in Nanjing, China, between July 2018 and May 2020. The sum of the suite of measured total VOC (TVOC) concentrations was 59.8 ± 28.6 ppbv (part per billion by volume) during the investigation period. About twice the TVOC concentrations were observed in the autumn (83 ± 20 ppbv) and winter (77.5 ± 16.8 ppbv) seasons compared to those in spring (39.6 ± 13.1 ppbv) and summer (38.8 ± 10.2 ppbv). In previous studies in Nanjing, oxygenated VOCs (OVOCs) and halocarbons were not measured, and the current TVOC concentration without halocarbons and OVOCs was similar to the previous investigation in the same study area. However, it was twofold higher than the one reported in the nonindustrial suburban area of Nanjing. Due to the industrial influence, the halocarbons VOC group (14.3 ± 7.3 ppbv, 24 %) was the second-largest contributor to the TVOCs after alkanes (21 ± 7 ppbv, 35 %), which is in contrast with the previous studies in Nanjing and also in almost all other regions in China. Relatively high proportions of halocarbons and aromatics were observed in autumn (25.7 % and 19.3 %, respectively) and winter (25.8 % and 17.6 %, respectively) compared to those in summer (20.4 % and 11.8 %, respectively) and spring (20.3 % and 13.6 %, respectively). According to the potential source contribution function (PSCF), short-distance transport from the surrounding industrial areas and cities was the main reason for the high VOC concentrations in the study area. According to positive matrix factorization (PMF) model results, vehicle-related emissions (33 %–48 %) contributed to the major portion of the ambient VOC concentrations. Aromatics, followed by alkenes, were the top contributors to the loss rate of OH radicals (LOH; 37 % and 32 %, respectively). According to the empirical kinetic modelling approach (EKMA) and relative incremental reactivity (RIR) analysis, the study area was in the VOC-sensitive regime for ozone (O3) formation during all measurement seasons. Therefore, alkenes and aromatics emissions from automobiles need to be decreased to reduce secondary air pollution formation in the study area.

Carbonaceous aerosols have great influence on the air quality, human health and climate change. Except for organic carbon (OC) and elemental carbon (EC), brown carbon (BrC) mainly originates from biomass burning as a group of OC, with strong absorption from the visible to near-ultraviolet wavelengths, and makes a considerable contribution to global warming. Large numbers of studies have reported long-term observation of OC and EC concentrations throughout the world, but studies of BrC based on long-term observations are rather limited. In this study, we established a two-wavelength method (658 and 405 nm) applied in the Sunset thermal–optical carbon analyzer. Based on a 1-year observation, we firstly investigated the characteristics, meteorological impact and transport process of OC and EC. Since BrC absorbs light at 405 nm more effectively than 658 nm, we defined the enhanced concentrations (dEC = EC405 nm − EC658 nm) and gave the possibility of providing an indicator of BrC. The receptor model and MODIS fire information were used to identify the presence of BrC aerosols. Our results showed that the carbonaceous aerosol concentrations were the highest in winter and lowest in summer. Traffic emission was an important source of carbonaceous aerosols in Nanjing. Receptor model results showed that strong local emissions were found for OC and EC; however, dEC was significantly affected by regional or long-range transport. The dEC/OC and OC/EC ratios showed similar diurnal patterns, and the dEC/OC increased when the OC/EC ratios increased, indicating strong secondary sources or biomass burning contributions to dEC. A total of two biomass burning events both in summer and winter were analyzed, and the results showed that the dEC concentrations were obviously higher on biomass burning days; however, no similar levels of the OC and EC concentrations were found both in biomass burning days and normal days in summer, suggesting that biomass burning emissions made a great contribution to dEC, and the sources of OC and EC were more complicated. Large number of open fire counts from the northwestern and southwestern areas of the study site were observed in winter and significantly contributed to OC, EC and dEC. In addition, the nearby Yangtze River Delta area was one of the main potential source areas of dEC, suggesting that anthropogenic emissions could also be important sources of dEC. The results proved that dEC can be an indicator of BrC on biomass burning days. Our modified two-wavelength instrument provided more information than the traditional single-wavelength thermal–optical carbon analyzer and gave a new idea about the measurement of BrC; the application of dEC data needs to be further investigated.

Abstract Mesenchymal stromal cells (MSCs) are multipotent cells that have great potential for regenerative medicine, tissue repair, and immunotherapy. Unfortunately, the outcomes of MSC-based research and therapies can be highly inconsistent and difficult to reproduce, largely due to the inherently significant heterogeneity in MSCs, which has not been well investigated. To quantify cell heterogeneity, a standard approach is to measure marker expression on the protein level via immunochemistry assays. Performing such measurements non-invasively and at scale has remained challenging as conventional methods such as flow cytometry and immunofluorescence microscopy typically require cell fixation and laborious sample preparation. Here, we developed an artificial intelligence (AI)-based method that converts transmitted light microscopy images of MSCs into quantitative measurements of protein expression levels. By training a U-Net+ conditional generative adversarial network (cGAN) model that accurately (mean $$r_s$$ r s = 0.77) predicts expression of 8 MSC-specific markers, we showed that expression of surface markers provides a heterogeneity characterization that is complementary to conventional cell-level morphological analyses. Using this label-free imaging method, we also observed a multi-marker temporal-spatial fluctuation of protein distributions in live MSCs. These demonstrations suggest that our AI-based microscopy can be utilized to perform quantitative, non-invasive, single-cell, and multi-marker characterizations of heterogeneous live MSC culture. Our method provides a foundational step toward the instant integrative assessment of MSC properties, which is critical for high-throughput screening and quality control in cellular therapies.

Roadside ditches serve an important role for draining storm water. Over time vegetation growth, natural sediment deposits, and other debris can change grade of ditches. Effectively monitoring and identifying these changes to prioritize ditch maintenance is important from both a pavement preservation perspective and prevention of localized flooding. This study evaluates the performance of two mobile LiDAR systems for mapping the cross-section of roadside ditches in the presence of vegetation. The geometric quality of data collected by two different wheel-based LiDAR systems were investigated. The mapped ditches were reported and visualized in 2D images as well as 3D point clouds. The cross-sections of man-made drainage ditches were extracted and the quality of mapped ditches was assessed against Real-Time Kinematic Global Navigation Satellite Systems (RTK-GNSS) survey. The overall point cloud accuracy was 4 cm for the medium-grade system, and 1 cm for the high-grade system. The mapping accuracy is 2 cm (medium-grade system) and 1 cm (high-grade system) for solid surface. For rough mowed areas and areas with significant vegetation, the vertical accuracy was found to be 7 cm and 11 cm, respectively, for both wheel-based systems.

Unmanned aerial vehicles (UAVs) have been widely used for 3D reconstruction/modelling in various applications such as precision agriculture, coastal monitoring, and emergency management. For such mapping applications, camera and LiDAR are the two most commonly used sensors. Mapping with imagery-based approaches is considered to be an economical and effective option and is often conducted using Structure from Motion (SfM) techniques where point clouds and orthophotos are generated. In addition to UAV photogrammetry, point clouds of the area of interest can also be directly derived from LiDAR sensors onboard UAVs equipped with global navigation satellite systems/inertial navigation systems (GNSS/INS). In this study, a custom-built UAV-based mobile mapping system is used to simultaneously collect imagery and LiDAR data. Derived LiDAR and image-based point clouds are investigated and compared in terms of their absolute and relative accuracy. Furthermore, stability of the system calibration parameters for the camera and LiDAR sensors are studied using temporal datasets. The results show that while LiDAR point clouds demonstrate a high absolute accuracy over time, image-based point clouds are not as accurate as LiDAR due to instability of the camera interior orientation parameters.

Particulate nitrate (NO3-) not only influences regional climates but also contributes to the acidification of terrestrial and aquatic ecosystems. In 2016 and 2017, four intensive online measurements of water-soluble ions in PM2.5 were conducted in Nanjing City in order to investigate the potential formation mechanisms of particulate nitrate. During the sampling periods, NO3- was the predominant species, accounting approximately for 35 % of the total water-soluble inorganic ions, followed by SO42- (33 %) and NH4+ (24 %). Significant enhancements of nitrate aerosols in terms of both absolute concentrations and relative abundances suggested that NO3- was a major contributing species to high-PM2.5 events (hourly PM2.5≥150 µg m−3). High NO3- concentrations mainly occurred under NH4+-rich conditions, implying that the formation of nitrate aerosols in Nanjing involved NH3. During the high-PM2.5 events, the nitrogen conversion ratios (Fn) were positively correlated with the aerosol liquid water content (ALWC; R>0.72 and p). Meanwhile, increasing NO3- concentrations regularly coincided with increasing ALWC and decreasing Ox (Ox=O3+NO2). These results suggested that the heterogeneous reaction was probably a major mechanism of nitrate formation during the high-PM2.5 events. Moreover, the average production rate of NO3- by heterogeneous processes was estimated to be 12.6 % h−1 (4.1 µg m−3 h−1), which was much higher than that (2.5 % h−1; 0.8 µg m−3 h−1) of gas-phase reactions. This can also explain the abrupt increases in nitrate concentrations during the high-PM2.5 events. Utilizing the ISORROPIA II model, we found that nitrate aerosol formation in Nanjing during the high-PM2.5 events was HNO3 limited. This indicated that control of NOx emissions will be able to efficiently reduce airborne particulate nitrate concentrations and improve the air quality in this industrial city.

Predicting tropospheric cloud formation and subsequent nutrient deposition relies on understanding the sources and processes affecting aerosol constituents of the atmosphere that are preserved in cloud water. However, this challenge is difficult to address quantitatively based on the sole use of bulk chemical properties. Nitrogenous aerosols, mainly ammonium (NH4+) and nitrate (NO3-), play a particularly important role in tropospheric cloud formation. While dry and wet (mainly rainfall) deposition of NH4+ and NO3- are regularly assessed, cloud water deposition is often underappreciated. Here we collected cloud water samples at the summit of Mt. Tai (1545 m above sea level) in eastern China during a long-lasting biomass burning (BB) event and simultaneously measured for the first time the isotopic compositions (mean ±1σ) of cloud water nitrogen species (δ15N-NH4+ = −6.53 ‰ ± 4.96 ‰, δ15N-NO3- = −2.35 ‰ ± 2.00 ‰, δ18O-NO3- = 57.80 ‰ ± 4.23 ‰), allowing insights into their sources and potential transformation mechanism within the clouds. Large contributions of BB to the cloud water NH4+ (32.9 % ± 4.6 %) and NO3- (28.2 % ± 2.7 %) inventories were confirmed through a Bayesian isotopic mixing model, coupled with our newly developed computational quantum chemistry module. Despite an overall reduction in total anthropogenic NOx emission due to effective emission control actions and stricter emission standards for vehicles, the observed cloud δ15N-NO3- values suggest that NOx emissions from transportation may have exceeded emissions from coal combustion. δ18O-NO3- values imply that the reaction of OH with NO2 is the dominant pathway of NO3- formation (57 % ± 11 %), yet the contribution of heterogeneous hydrolysis of dinitrogen pentoxide was almost as important (43 % ± 11 %). Although the limited sample set used here results in a relatively large uncertainty with regards to the origin of cloud-associated nitrogen deposition, the high concentrations of inorganic nitrogen imply that clouds represent an important source of nitrogen, especially for nitrogen-limited ecosystems in remote areas. Further simultaneous and long-term sampling of aerosol, rainfall, and cloud water is vital for understanding the anthropogenic influence on nitrogen deposition in the study region.

Water-soluble organic carbon (WSOC) is a significant fraction of organic carbon (OC) in atmospheric aerosols. WSOC is of great interest due to its significant effects on atmospheric chemistry, the Earth's climate and human health. The stable carbon isotope (δ13C) can be used to track the potential sources and investigate atmospheric processes of organic aerosols. However, the previous methods measuring the δ13C values of WSOC in ambient aerosols require a large amount of carbon content, are time-consuming and require labor-intensive preprocessing. In this study, a method of simultaneously measuring the mass concentration and the δ13C values of WSOC from aerosol samples is established by coupling the GasBench II preparation device with isotopic ratio mass spectrometry. The precision and accuracy of isotope determination is better than 0.17 ‰ and 0.5 ‰, respectively, for samples containing WSOC amounts larger than 5 µg. This method is then applied for the aerosol samples collected every 3 h during a severe wintertime haze period in Nanjing, eastern China. The WSOC values vary between 3 and 32 µg m−3, whereas δ13C−WSOC ranges from −26.24 ‰ to −23.35 ‰. Three different episodes (Episode 1, Episode 2 and Episode 3) are identified in the sampling period, showing a different tendency of δ13C−WSOC with the accumulation process of WSOC aerosols. The increases in both the WSOC mass concentrations and the δ13C−WSOC values in Episode 1 indicate that WSOC is subject to a substantial photochemical aging during the air mass transport. In Episode 2, the decline of the δ13C−WSOC is accompanied by the increase in the WSOC mass concentrations, which is associated with regional-transported biomass burning emissions. In Episode 3, heavier isotope (13C) is exclusively enriched in total carbon (TC) in comparison to WSOC aerosols. This suggests that the non-WSOC fraction in total carbon may contain 13C-enriched components such as dust carbonate, which is supported by the enhanced Ca2+ concentrations and air mass trajectory analysis. The present study provides a novel method to determine the stable carbon isotope composition of WSOC, and it offers a great potential to better understand the source emission, the atmospheric aging and the secondary production of water-soluble organic aerosols.

Microstructural evolution and dynamic recrystallization (DRX) behaviors of a Ni-Cr-Mo alloy were researched utilizing hot compressive experiments. The changed features of dislocation, subgrain and grain structure correlating to forming parameters were examined by transmission electron microscope (TEM) and electron backscatter diffraction (EBSD). Results illustrate that the consumption of dislocation and the coarsening of substructure/DRX grain are prominently enhanced with an increased forming temperature. However, the annihilation/interaction of dislocation and the expansion of subgrain/DRX grain boundary can be limited at a larger strain rate. Meanwhile, considering the discrepancy in DRX variation rates concerning the strain rate’s ranges, an improved DRX kinetic model was developed. Compared to the classical DRX kinetic model, the good consistency between the forecasted and tested results demonstrates that the established improved DRX kinetic model can precisely characterize the DRX features of the Ni-Cr-Mo alloy over a wide strain rate range. Additionally, the EBSD’s quantitative statistical results proved that the variation of DRX grain size can be supremely defined as the power formulation of the forming temperature and strain rate.

Arsenic (As) has long been recognized as a toxic element of mainly anthropogenic origins, having adverse effects on human health. However, there is insufficient understanding regarding As released into atmosphere from biomass burning (BB). To this end, daily airborne As concentrations in total particulate matter (TSP) were determined at Mount Hehuan (24.16° N, 121.29° E, 3001 m a.s.l.), Taiwan from September 2011 to September 2012. During the sampling period, As concentrations varied from 0.02 to 5.9 ng m−3, with a mean value of 0.5±1.0 ng m−3. Significantly seasonal variations of As were found over the subtropical free troposphere, and higher As concentrations were observed in the southern (S) and southeastern (SE) Asian BB seasons (from January to May). Principal component analysis (PCA) results showed that BB activities seemed to be a major source of As during the S and SE Asian BB periods, which were very distinct from the major source of coal-fired power plant during the periods between July and December. Based on backward trajectory analyses and WRF-Chem model simulations, we found that the high As concentrations during the BB periods were attributed to the biomass burning activities over S Asia where groundwater, soil and crops are severely contaminated by arsenic. A strong correlation (r = 0.73 p +, a chemical tracer of BB activities) in S Asian BB events also supported this hypothesis. During the S Asian BB events, the high As ∕ Pb ratios ( > 0.2) were also observed, indicating that burning crops contaminated by lead arsenate might be a crucial candidate for high As concentrations at Mount Hehuan. Nevertheless, the net influence of S Asian BB activities on airborne As concentrations has been estimated by comparing the differences of As concentrations on BB and non-BB days. On average, the difference in As concentrations was 1.0 ng m−3, which accounted for 63 % of the average As concentration on BB days. Moreover, a ratio of ΔAs∕ΔCO ( ∼ 0.00001) in the S Asian BB events was obtained. Using this value, arsenic emissions from S Asian BB activities were estimated to be 0.17 tons yr−1, resulting in high airborne As concentrations over the subtropical free troposphere and impacting As cycles on a regional scale in the S and SE Asian BB seasons.

Abstract Each year, a number of typhoons in the western North Pacific pass through the Luzon Strait into South China Sea (SCS). Although the storms remain above a warm open sea, the majority of them weaken due to atmospheric and oceanic environments unfavorable for typhoon intensification in SCS, which therefore serves as a natural buffer that shields the surrounding coasts from potentially more powerful storms. This study examines how this buffer has changed over inter-decadal and longer time scales. We show that the buffer weakens (i.e. greater potential for more powerful typhoons) in negative Pacific Decadal Oscillation (PDO) years, as well as with sea-level-rise and surface warming, caused primarily by the deepening of the ocean’s 26 °C isotherm Z 26 . A new Intensity Change Index is proposed to describe the typhoon intensity change as a function of Z 26 and other environmental variables. In SCS, the new index accounts for as high as 75% of the total variance of typhoon intensity change.

HBIM technology makes great contributions to 3D digital preservation and management of the existing traditional architectures, and VR technology has also been gradually emphasized by 3D users in recent years, especially 3D immersive situation makes users more likely to experience the real space field. Taking Han type traditional architecture with relatively complex geometrical structure as an example, this research carries out digital preservation through HBIM technology and tries to switch to VR platform to allow users to enter 3D immersive scene for management and display. It is shown in the research results that the application of integration of HBIM and VR technology to Han type traditional architecture needs to consider 3D digital model of the architecture, and the number of polygon shall be controlled below about 2 million, which can make the operation in VR environment more smooth; the integration of two technologies can achieve the purpose of 3D immersive digital management, which can provide the humanized application close to the real experience for the display of subsequent management of ancient relics and architectural aesthetics.

Ag3PO4/g-C3N4 heterojunctions, with different g-C3N4 dosages, were synthesized using an in situ deposition method, and the photocatalytic performance of g-C3N4/Ag3PO4 heterojunctions was studied under simulated sunlight conditions. The results revealed that Ag3PO4/g-C3N4 exhibited excellent photocatalytic degradation activity for rhodamine B (Rh B) and phenol under the same light conditions. When the dosage of g-C3N4 was 30%, the degradation rate of Rh B at 9 min and phenol at 30 min was found to be 99.4% and 97.3%, respectively. After five cycles of the degradation experiment for Rh B, g-C3N4/Ag3PO4 still demonstrated stable photodegradation characteristics. The significant improvement in the photocatalytic activity and stability of g-C3N4/Ag3PO4 was attributed to the rapid charge separation between g-C3N4 and Ag3PO4 during the Z-scheme charge transfer and recombination process.

Forest canopy density and height are used as variables in a number of environmental applications, including the estimation of biomass, forest extent and condition, and biodiversity. The airborne Light Detection and Ranging (LiDAR) is very useful to estimate forest canopy parameters according to the generated canopy height models (CHMs). The purpose of this work is to introduce an algorithm to delineate crown parameters, e.g. tree height and crown radii based on the generated rasterized CHMs. And accuracy assessment for the extraction of volumetric parameters of a single tree is also performed via manual measurement using corresponding aerial photo pairs. A LiDAR dataset of a golf course acquired by Leica ALS70-HP is used in this study. Two algorithms, i.e. a traditional one with the subtraction of a digital elevation model (DEM) from a digital surface model (DSM), and a pit-free approach are conducted to generate the CHMs firstly. Then two algorithms, a multilevel morphological active-contour (MMAC) and a variable window filter (VWF), are implemented and used in this study for individual tree delineation. Finally, experimental results of two automatic estimation methods for individual trees can be evaluated with manually measured stand-level parameters, i.e. tree height and crown diameter. The resulting CHM generated by a simple subtraction is full of empty pixels (called "pits") that will give vital impact on subsequent analysis for individual tree delineation. The experimental results indicated that if more individual trees can be extracted, tree crown shape will became more completely in the CHM data after the pit-free process.

The extraction of land cover information from remote sensing data is a complex process. Spectral information has been widely utilized in classifying remote sensing images. However, shadows limit the use of multispectral images because they result in loss of spectral radiometric information. In addition, true reflectance may be underestimated in shaded areas. In land cover classification, shaded areas are often left unclassified or simply assigned as a shadow class. Vegetation indices from remote sensing measurement are radiation-based measurements computed through spectral combination. They indicate vegetation properties and play an important role in remote sensing of forests. Airborne light detection and ranging (LiDAR) technology is an active remote sensing technique that produces a true orthophoto at a single wavelength. This study investigated three types of geometric lidar features where NDVI values fail to represent meaningful forest information. The three features include echo width, normalized eigenvalue, and standard deviation of the unit weight observation of the plane adjustment, and they can be derived from waveform data and discrete point clouds. Various feature combinations were carried out to evaluate the compensation of the three lidar features to vegetation detection in shaded areas. Echo width was found to outperform the other two features. Furthermore, surface characteristics estimated by echo width were similar to that by normalized eigenvalues. Compared to the combination of only NDVI and mean height difference, those including one of the three features had a positive effect on the detection of vegetation class.

Copper-metallized gallium nitride (GaN) high-electron-mobility transistors (HEMTs) using a Ti/Pt/Ti diffusion barrier layer are fabricated and characterized for Ka-band applications. With a thick copper metallization layer of 6.8 μm adopted, the device exhibited a high output power density of 8.2 W/mm and a power-added efficiency (PAE) of 26% at 38 GHz. Such superior performance is mainly attributed to the substantial reduction of the source and drain resistance of the device. In addition to improvement in the Radio Frequency (RF) performance, the successful integration of the thick copper metallization in the device technology further reduces the manufacturing cost, making it extremely promising for future fifth-generation mobile communication system applications at millimeter-wave frequencies.

Genetically attenuated microorganisms, including pathogenic and commensal bacteria, can be engineered to carry and deliver heterologous antigens to elicit host immunity against both the vector as well as the pathogen from which the donor gene is derived. These live attenuated bacterial vectors have been given much attention due to their capacity to induce a broad range of immune responses including localized mucosal, as well as systemic humoral and/or cell-mediated immunity. In addition, the unique tumor-homing characteristics of these bacterial vectors has also been exploited for alternative anti-tumor vaccines and therapies. In such approach, tumor-associated antigen, immunostimulatory molecules, anti-tumor drugs, or nucleotides (DNA or RNA) are delivered. Different potential vectors are appropriate for specific applications, depending on their pathogenic routes. In this review, we survey and summarize the main features of the different types of live bacterial vectors and discussed the clinical applications in the field of vaccinology. In addition, different approaches for using live attenuated bacterial vectors for anti-cancer therapy is discussed, and some promising pre-clinical and clinical studies in this field are outlined.

Traffic emissions are a significant source of airborne particulate matter (PM) in ambient environments. These emissions contain an abundance of toxic metals and thus pose adverse effects on human health. Size-fractionated aerosol samples were collected from May to September 2013 by using micro-orifice uniform deposited impactors (MOUDIs). Sample collection was conducted simultaneously at the inlet and outlet sites of Hsuehshan Tunnel in northern Taiwan, which is the second-longest freeway tunnel (12.9 km) in Asia. This endeavor aims to characterize the chemical constituents and size distributions, as well as fingerprinting ratios of particulate metals emitted by vehicle fleets. A total of 36 metals in size-resolved aerosols were determined through inductively coupled plasma mass spectrometry. Three major groups – namely, tailpipe emissions (Zn, Pb, and V in fine mode), wear debris (Cu, Cd, Fe, Ga, Mn, Mo, Sb, and Sn), and resuspended dust (Ca, Mg, K, and Rb) – of airborne PM metals were categorized on the basis of the results of enrichment factor, correlation matrix, and principal component analysis. Size distributions of wear-originated metals resembled the pattern of crustal elements, which were predominated by super-micron particulates (PM1–10). By contrast, tailpipe exhaust elements such as Zn, Pb, and V were distributed mainly in submicron particles. By employing Cu as a tracer of wear abrasion, several inter-metal ratios – including Fe / Cu (14), Ba / Cu (1.05), Sb / Cu (0.16), Sn / Cu (0.10), and Ga / Cu (0.03) – served as fingerprints for wear debris. However, the data set collected in this work is useful for further studies on traffic emission inventory and human health effects of traffic-related PM.

We are living in a world of over seven billion people, with annual greenhouse gas emissions of approximately 50 billion tons a year and rising steadily. If continued unabated, the world is on target to warm by about 2 °C in less than 40 years, pushing the climate to a regime unlike any that has been witnessed in the last million years. Nonetheless, we still have time to avert such a catastrophic scenario, or delay its occurrence by several decades to provide human societies and the ecosystem with the time to adjust. In order to mitigate the possibility of climate disruption, we need to recognize that fossil fuel based technologies have become outdated and transform the energy system to that of low-carbon, sustainable and secure energy systems. In addition, we have to mitigate emissions of the four short-lived climate pollutants to bring immediate relief from climate change and protect vulnerable societies. Stability of the climate system involves not only the centrality of scientific and technological advancements and investments, but also necessary shifts in social structure and behavior by individuals, communities and societies worldwide as well as market based instruments, sub-national collaborations and governance structure. Fortunately, living laboratories—such as the State of California and the University of California system, which has pledged to become carbon neutral by 2025—provide demonstrable solutions which hold promise in alleviating the climate warming in the next generation. These jurisdictions are tiny emitters in the global picture, but they offer the potential for leverage through demonstrating (Figure 1) new technologies as well as workable institutions that cut emissions. We outline 10 pragmatic solutions—a “kit of parts” rooted in California but scalable to the world—that taken together, can “bend the curve” of the upward trajectory of human-caused warming trends. Wholesale transformation of our current fossil fuel based energy systems towards sustainable energy is among the greatest of societal challenges—and opportunities—faced in the 21st century.

A new modal aerosol parameterization scheme, the statistical–numerical aerosol parameterization (SNAP), was developed for studying aerosol processes and aerosol–cloud interactions in regional or global models. SNAP applies statistical fitting on numerical results to generate accurate parameterization formulas without sacrificing details of the growth kernel. Processes considered in SNAP include fundamental aerosol processes as well as processes related to aerosol–cloud interactions. Comparison of SNAP with numerical solutions, analytical solutions, and binned aerosol model simulations showed that the new method performs well, with accuracy higher than that of the high-order numerical quadrature technique, and with much less computation time. The SNAP scheme has been implemented in regional air quality models, producing results very close to those using binned-size schemes or numerical quadrature schemes.