<em>A method of scenario computing is developed for modeling systems with deep uncertainty</em>. The method consists three complementary parts: hybrid modelling, diverse computing, and interactive validation. Hybrid modelling is to dynamically develop models with merging historical knowledges and observed information. Diversity computation is to simulate multiple plausible scenarios about system future. Interactive validation helps scenario computing process being on the right way instead of deviating. Two cases are provided in this paper applying scenario computing, one is earthquake and the other is driving and transportation. The results show good performance of scenario computing method in modeling uncertainty systems.
Liu Y, Wang G, Wu Z, Fan Z, Chen Y. Scenario Computing for Analysis of Deep Uncertainty Systems. Xitong Fangzhen Xuebao / Journal of System SimulationXitong Fangzhen Xuebao / Journal of System SimulationXitong Fangzhen Xuebao / Journal of System Simulation. 2018;30:3608-3615.Abstract
Denitrification community in wetland plays an important role in nitrogen removal. The present study investigated the seasonal and spatial dynamics of denitrification rate and nirS-denitrifier communities and the potential influential factors in a large wetland system treating polluted river water. Wetland denitrification rate and the abundance, richness, diversity and composition of nirS-denitrifier community were found to vary with season and sampling site. Both wetland denitrification rate and denitrifier community were related to plant type. Wetland soils and sediments differed greatly in either denitrification rate or denitrifier community structure. Wetland generally had lower denitrification rate and denitrifier abundance in summer than in spring and winter. Denitrification rate showed no direct correlation to denitrifier abundance but was positively correlated to denitrifier diversity. Denitrification rate could be mediated by denitrifier community structure. Moreover, Spearman rank correlation analysis suggested that denitrification rate was significantly correlated to sediment/soil ammonia, nitrate, nitrite, total phosphorus and pH, while denitrifier abundance was significantly correlated to total phosphorus and temperature. Nitrite, total nitrogen, total organic carbon, and the ratio of total organic carbon to total nitrogen showed significant correlations with wetland denitrifier diversity, while ammonia, nitrate, total nitrogen and total phosphorus might have important roles in shaping wetland denitrifier community structure. In addition, for each wetland sediment or soil, 0.8-46.2% of the retrieved nirS sequences could be related to the sequences from cultivated denitrifiers. Dechloromonas-like denitrifiers were more abundant in wetland sediments than in wetland soils.
With the rapid economic development and urbanization of China, haze and photochemical smog events have been frequently observed during the last decade. To explore the temporal and spatial pollution characteristics in Ningbo, a medium-sized coastal city located in the Yangtze River Delta (YRD) in southeast China, 24-h PM2.5 (particulate matter with aerodynamic diameter < 2.5 mu m) samples were simultaneously collected at five sites (two urban residential sites, two urban coastal sites, and one suburban site) from winter 2012 to autumn 2013. The average PM2.5 concentration was 53.2 +/- 30.4 mu g m(-3). Furthermore, the concentration exhibited a seasonal variation: It was highest in winter and lowest in summer. The urban residential sites had the highest PM2.5 concentrations, followed by the urban coastal sites, and the suburban site had the lowest concentration. OM (Organic Matters) and secondary inorganic ions (sulfate, nitrate, and ammonium) were the dominant components of the PM2.5. As a coastal city with industrial zones, sources are more complex in Ningbo than in inland cities due to ship emissions and the interactions between land and sea, and the marine and atmospheric environments. Positive matrix factorization (PMF) was used to apportion the particle sources. Nine factors were resolved in this study: secondary nitrate, vehicle exhaust, secondary sulfate, coal combustion, industrial emission, ship emission, dust, biomass burning, and aged sea salt, with average contributions of 26%, 21%, 13%, 12%, 9%, 7%, 5%, 4%, and 3%, respectively. Secondary nitrate and vehicle exhaust were the major sources of PM2.5 pollution in Ningbo. Coal combustion contributed significantly in winter and autumn, whereas sea salt formed a considerable contribution in summer. This study suggests that decreasing the PM2.5 pollution in Ningbo requires not only strategies for reducing local primary sources but also joint inter-regional prevention and the control of air pollution in the YRD.
Seasonal pattern of transport pathways and potential sources of PM2.5 in Chengdu during 2012–2013 were investigated based on hourly PM2.5 data, backward trajectories, clustering analysis, potential source contribution function (PSCF), and concentration-weighted trajectory (CWT) method. The annual hourly mean PM2.5 concentration in Chengdu was 97.4 mg·m–3. 5, 5, 5 and 3 mean clusters were generated in four seasons, respectively. Short-distance air masses, which travelled within the Sichuan Basin with no specific source direction and relatively high PM2.5 loadings (>80 mg·m–3) appeared as important pathways in all seasons. These short pathways indicated that emissions from both local and surrounding regions of Chengdu contributed significantly to PM2.5 pollution. The cities in southern Chengdu were major potential sources with PSCF>0.6 and CWT>90 mg·m–3. The northeastern pathway prevailed throughout the year with higher frequency in autumn and winter and lower frequency in spring and summer. In spring, long-range transport from southern Xinjiang was a representative dust invasion path to Chengdu, and the CWT values along the path were 30-60 mg·m–3. Long-range transport was also observed in autumn from southeastern Xinjiang along a northwesterly pathway, and in winter from the Tibetan Plateau along a westerly pathway. In summer, the potential source regions of Chengdu were smaller than those in other seasons, and no long-range transport pathway was observed. Results of PSCF and CWT indicated that regions in Qinghai and Tibet contributed to PM2.5 pollution in Chengdu as well, and their CWT values increased to above 30 mg·m–3 in winter.
Significant progress has been made in perovskite solar cells by various effective film-forming methods. Solution-process methods for the perovskite film appropriate under ambient conditions are desired to be explored for the practical industrialization. Here, a secondary crystal growth strategy is developed for the fabrication of perovskite film in ambient atmosphere. By this method, the conversion from PbI2 to CH3NH3PbI3 on the planar substrate can be completed, overcoming the limitation of standard sequential deposition. After secondary growth, high-quality crystals are obtained and compact densely to form a pinhole-free film. Exceeding 17% of power conversion efficiency is achieved for planar CH3NH3PbI3 devices by controlling the reaction time of two stages carefully. This method can be easily controlled, reproduced and performed in the ambient, which meets the industrial requirements for highly efficient, low cost planar perovskite solar cells.
Organosulfates (OSs) with ambiguous formation mechanisms are a potential source of ``missing secondary organic aerosol (SOA)'' in current atmospheric models. In this study, we chemically characterized OSs and nitrooxy-OSs (NOSs) formed under the influence of biogenic emissions and anthropogenic pollutants (e.g., NOx, SO42-) in summer in Beijing. An ultrahigh-resolution mass spectrometer equipped with an electrospray ionization source was applied to examine the overall molecular composition of S-containing organics. The number and intensities of S-containing organics, the majority of which could be assigned as OSs and NOSs, increased significantly during pollution episodes, which indicated their importance for SOA accumulation. To further investigate the distribution and formation of OSs and NOSs, high-performance liquid chromatography coupled with mass spectrometry was employed to quantify 10 OSs and 3 NOS species. The total concentrations of quantified OSs and NOSs were 41.4 and 13.8 ng m(-3), respectively. Glycolic acid sulfate was the most abundant species among all the quantified species, followed by monoterpene NOSs (C10H16NO7S-). The total concentration of three isoprene OSs was 14.8 ng m(-3) and the isoprene OSs formed via the HO2 channel were higher than those formed via the NO/NO2 channel. The OS concentration coincided with the increase in acidic sulfate aerosols, aerosol acidity, and liquid water content (LWC), indicating the acid-catalyzed aqueousphase formation of OSs in the presence of acidic sulfate aerosols. When sulfate dominated the accumulation of secondary inorganic aerosols (SIAs; sulfate, nitrate, and ammonium; SO42-/SIA > 0.5), OS formation would obviously be promoted as the increasing of acidic sulfate aerosols, aerosol LWC, and acidity (pH < 2.8). Otherwise, acid-catalyzed OS formation would be limited by lower aerosol acidity when nitrate dominated the SIA accumulation. The nighttime enhancement of monoterpene NOSs suggested their formation via the nighttime NO3-initiated oxidation of monoterpene under high-NOx conditions. However, isoprene NOSs are presumed to form via acid-catalyzed chemistry or reactive uptake of oxidation products of isoprene. This study provides direct observational evidence and highlights the secondary formation of OSs and NOSs via the interaction between biogenic precursors and anthropogenic pollutants (NOx, SO2, and SO42-). The results imply that future reduction in anthropogenic emissions can help to reduce the biogenic SOA burden in Beijing or other areas impacted by both biogenic emissions and anthropogenic pollutants.
Coastal ecosystem structures and functions are changing under natural and anthropogenic influences. In this study, surface sediment samples were collected from disturbed zone (DZ), near estuary zone (NEZ), and far estuary zone (FEZ) of Hangzhou Bay, one of the most seriously polluted bays in China. The bacterial community structures and predicted functions varied significantly in different zones. Firmicutes were found most abundantly in DZ, highlighting the impacts of anthropogenic activities. Sediment total phosphorus was most influential on the bacterial community structures. Predicted by PICRUSt analysis, DZ significantly exceeded FEZ and NEZ in the subcategory of Xenobiotics Biodegradation and Metabolism; and DZ enriched all the nitrate reduction related genes, except nrfA gene. Seawater salinity and inorganic nitrogen, respectively as the representative natural and anthropogenic factor, performed exact-oppositely in nitrogen metabolism functions. The changes of bacterial community compositions and predicted functions provide a new insight into human-induced pollution impacts on coastal ecosystem.
The use of quantitative measures to select priority areas for conservation has been in practice since the early 1980s. However, the relative efficiency of different methods for identifying priority areas is still the subject of debate. Here, using the distribution data of 556 Rhododendron species in China with high spatial resolution, we evaluated the performance of the two commonly used methods, i.e. hotspot and complementarity and selected the efficient method to select priority areas for the conservation of Rhododendron in China. By overlaying the priority areas map with the locations of protected areas, we also identified the regions not covered by current protected areas (i.e. conservation gaps). We found that the complementarity method selected less number of grid cells to capture an equivalent number of species and hence had higher efficiency and representativeness than the commonly used hotspot method. Moreover, the complementarity method was better at capturing the range-restricted species than the hotspot method. Based on the complementarity method, we identified 61 grid cells of 50 × 50 km as priority areas for Rhododendron conservation in China. Among these priority areas, only about 50% grid cells were located in the hotspot areas (e.g. Hengduan Mountains), and 14% grid cells were outside the current protected area network. Our findings suggest that, despite its popularity and ease of implementation, the sites selected by hotspot algorithm may not necessarily be the best sites to allocate conservation efforts. Since the identification of priority areas in China has largely been based on the hotspot method, the current study has revived the need to reassess the priority areas for other taxonomic groups too. More importantly, our findings have emphasized the need to expand the conservation priorities from Hengduan Mountains to south and southeast China as well.
Abstract Electrically driven on-chip electron sources that do not need to be heated are long pursued, but their realization remains challenging. Here, it is shown that a nanogap formed by two electrodes on a silicon oxide substrate functions as an electron-emitting nanodiode after the silicon oxide in the nanogap is electrically switched to a high-resistance conducting state. A nanodiode based on graphene electrodes can be turned on by a voltage of ≈7 V in ≈100 ns and show an emission current of up to several microamperes, corresponding to an emission density of ≈106 A cm−2 and emission efficiency as high as 16.6%. We attribute the electron emission to be generated from a metal–insulator–metal tunneling diode on the substrate surface formed by the rupture of conducting filaments in silicon oxide. An array of 100 nanodiodes exhibits a global emission density of 5 A cm−2 and stable emission with negligible current degradation over tens of hours under modest vacuum. The combined advantages of a low operating voltage, fast temporal response, high emission density and efficiency, convenient fabrication and integration, and stable emission in modest vacuum make silicon oxide electron-emitting nanodiodes a promising on-chip electron sources.
