Aerosol acidity plays an important role in atmospheric chemistry. China emits large amounts of SO2, NOx, and NH3 into the atmosphere, but aerosol acidity is poorly characterized. In this study, simultaneous 1-h measurements of particulate and gaseous compositions along with the ISORROPIA-II thermodynamic equilibrium model were used to study aerosol acidity during severe haze episodes in northern China. The summed concentration of sulfate, nitrate and ammonium was 135 ± 51 μg/m3 with a maximum of 250 μg/m3, and the gas-phase NH3 mixing ratio was 22 ± 9 ppb. Fine particles were moderately acidic, with a pH range of 3.0−4.9 and an average of 4.2, which was higher than those in the United States and Europe.Excess NH3 and high aerosol water content are responsible for the relatively lower aerosol acidity. These results suggests that the new pathways for sulfate production in China proposed by recent studies should be revisited.
The Qulong porphyry copper and molybdenum deposit is located at the southwest margin of the Lhasa Terrane and in the eastern region of the Gangdese magmatic belt. It represents China's largest porphyry copper system, with similar to 2200 million tonnes of ore comprising 0.5 % Cu and 0.03 % Mo. The mineralization is associated with Miocene granodiorite, monzogranite and quartz-diorite units, which intruded into Jurassic volcanic units in a post-collisional (Indian-Asian) tectonic setting. Field observations and core logging demonstrate the alteration and mineralization at Qulong are akin to typical porphyry copper systems in subduction settings, which comprise similar magmatic-hydrothermal, potassic, propylitic and phyllic alteration assemblages. Molybdenite Re-Os geochronology confirms the relative timeframe defined by field observations and core logging and indicates that the bulk copper and molybdenum at Qulong were deposited within 350,000 years: between 16.10 +/- 0.06 [0.08] (without and with decay constant uncertainty) and 15.88 +/- 0.06 [0.08] Ma. This duration for mineralization is in direct contrast to a long-lived intrusive episode associated with mineralization based on previous zircon U-Pb data. Our fluid inclusion study indicates that the ore-forming fluid was oxidized and contained Na, K, Ca, Fe, Cu, Mo, Cl and S. The magmatic-hydrothermal transition occurred at similar to 425 A degrees C under lithostatic pressure, while potassic, propylitic and phyllic alteration occurred at hydrostatic pressure with temperature progressively decreasing from 425 to 280 A degrees C. The fluid inclusion data presented here suggests that there has been similar to 2.3 km of erosion at Qulong after its formation, and this erosion may be related to regional uplift of the Lhasa Terrane.
With the development of digital technologies, especially big data analytics, digital innovations are taking root in various industries, including energy sector. Particularly, urban energy system is also experiencing digital transition; such digital transition not only offers new business models commercially, but also brings new research problems scientifically. The new capabilities enabled by these digital technologies are reshaping the generation, transmission, consumption and storage sections in the urban energy system, sequentially the traditional way of how urban energy system is designed and operated should be reexamined. Starting from here, there have been many studies regarding how various digital technologies can be applied all along the urban energy system value chain; these studies range from individuals’ energy consumption pattern characterization by using customer behavior data in smart home, to complex data-driven planning of regional scale energy system. More specifically, numerous computational models have been proposed by the scientific community to mimic the dynamics of various components at various levels in the urban energy system. However, the potential benefits of applying these numerical models are somehow underestimated; we believe there are still several gaps from numerical modeling to computational intelligence which need to be bridged. In such a context, in this paper we strive to present a systematic review on the status of urban energy system related digital innovations as well as prospective outlook on the future application of such digital technologies. Through the study of this paper, we hope to identify several key points where digitalization should be prioritized in urban energy system, picture a roadmap towards future digital technology enabled intelligent urban energy system, and finally points out the research gaps that need to be fulfilled over there.
Estimating ground surface PM2.5 with fine spatiotemporal resolution is a critical technique for exposure assessments in epidemiological studies of its health risks. Previous studies have utilized monitoring, satellite remote sensing or air quality modeling data to evaluate the spatiotemporal variations of PM2.5 concentrations, but such studies rarely combined these data simultaneously. Through assembling techniques, including linear mixed effect regressions with a spatial-varying coefficient, a maximum likelihood estimator and the spatiotemporal Kriging together, we develop a three-stage model to fuse PM2.5 monitoring data, satellite-derived aerosol optical depth (AOD) and community multi-scale air quality (CMAQ) simulations together and apply it to estimate daily PM2.5 at a spatial resolution of 0.1 degrees over China. Performance of the three-stage model is evaluated using a cross-validation (CV) method step by step. CV results show that the finally fused estimator of PM2.5 is in good agreement with the observational data (RMSE = 23.0 g/m(3) and R-2 = 0.72) and outperforms either AOD-derived PM2.5 (R-2 = 0.62) or CMAQ simulations (R-2 = 0.51). According to step-specific CVs, in data fusion, AOD-derived PM2.5 plays a key role to reduce mean bias, whereas CMAQ provides spatiotemporally complete predictions, which avoids sampling bias caused by non-random incompleteness in satellite-derived AOD. Our fused products are more capable than either CMAQ simulations or AOD-based estimates in characterizing the polluting procedure during haze episodes and thus can support both chronic and acute exposure assessments of ambient PM2.5. Based on the products, averaged concentration of annual exposure to PM2.5 was 55.7 g/m(3), while averaged count of polluted days (PM2.5 > 75 g/m(3)) was 81 across China during 2014. Fused estimates will be publicly available for future health-related studies.
Atmospheric new particle formation and growth play important roles in climate change and air quality. Aiming at better understanding the particle growth mechanisms, the measurements on chemical composition of new particles are imperative. However, the instruments directly detecting chemical composition of nanoparticles (<30 nm) are very rare due to the tiny particle masses involved and low transmission efficiency. Alternatively, the hygroscopicity and volatility of nanoparticles were measured to infer chemical composition of the particle. Here, we summarized the progresses in studying the new particle growth processes on a basis of particle hygroscopicity and volatility measurements. Compared to clean environments, such as in boreal forest, the water soluble components contribute a larger fraction of newly formed particles (below 50 nm) in the polluted environments, such as in the sulfur-rich atmosphere of North China Plain. The extreme low volatility components in new particles were observed in both clean and polluted environments and contributed to 1/4 of particle growth in a rural site of Melpitz, Germany. In the future, the instruments capable of precisely detecting the hygroscopicity and volatility of particles below 10 nm are needed. Except for differential mobility analyzer, other novel methods without limitation of charging and transmission efficiency should be considered. The hygroscopicity and volatility of atmospheric relevant compounds should be investigated in the laboratory in order to provide supportive information to explain the hygroscopicity and volatility of new particle in the ambient air.