Model predictive control strategy in waked wind farms for optimal fatigue loads

With the rapid growth of wind power penetration, wind farms (WFs) are required to implement frequency regulation that active power control to track a given power reference. Due to the wake interaction of the wind turbines (WTs), there is more than one solution to distributing power reference among the operating WTs, which can be exploited as an optimization problem for the second goal, such as fatigue load alleviation. In this paper, a closed-loop model predictive controller is developed that minimizes the wind farm tracking errors, the dynamical fatigue load, and and the load equalization. The controller is evaluated in a mediumfidelity model. A 64 WTs simulation case study is used to demonstrate the control performance for different penalty factor settings. The results indicated the WF can alleviate dynamical fatigue load and have no significant impact on power tracking. However, the uneven load distribution in the wind turbine system poses challenges for maintenance. By adding a trade-off between the load equalization and dynamical fatigue load, the load differences between WTs are significantly reduced, while the dynamical fatigue load slightly increases when selecting a proper penalty factor.Comment: Accepted by Electric Power Systems Researc

MAX-DOAS measurements of tropospheric NO2 and HCHO in Nanjing and a comparison to ozone monitoring instrument observations

In this paper, we present long-term observations of atmospheric nitrogen dioxide (NO2) and formaldehyde (HCHO) in Nanjing using a Multi-AXis Differential Optical Absorption Spectroscopy (MAX-DOAS) instrument. Ground-based MAX-DOAS measurements were performed from April 2013 to February 2017. The MAX-DOAS measurements of NO2 and HCHO vertical column densities (VCDs) are used to validate ozone monitoring instrument (OMI) satellite observations over Nanjing. The comparison shows that the OMI observations of NO2 correlate well with the MAX-DOAS data with Pearson correlation coefficient (R) of 0.91. However, OMI observations are on average a factor of 3 lower than the MAX-DOAS measurements. Replacing the a priori NO2 profiles by the MAX-DOAS profiles in the OMI NO2 VCD retrieval would increase the OMI NO2 VCDs by similar to 30% with correlation nearly unchanged. The comparison result of MAX-DOAS and OMI observations of HCHO VCD shows a good agreement with R of 0.75 and the slope of the regression line is 0.99. An age-weighted backward-propagation approach is applied to the MAX-DOAS measurements of NO2 and HCHO to reconstruct the spatial distribution of NO2 and HCHO over the Yangtze River Delta during summer and winter time. The reconstructed NO2 fields show a distinct agreement with OMI satellite observations. However, due to the short atmospheric lifetime of HCHO, the backward-propagated HCHO data do not show a strong spatial correlation with the OMI HCHO observations. The result shows that the MAX-DOAS measurements are sensitive to the air pollution transportation in the Yangtze River Delta, indicating the air quality in Nanjing is significantly influenced by regional transportation of air pollutants. The MAX-DOAS data are also used to evaluate the effectiveness of air pollution control measures implemented during the Youth Olympic Games 2014. The MAX-DOAS data show a significant reduction of ambient aerosol, NO2 and HCHO (30 %-50 %) during the Youth Olympic Games. Our results provide a better understanding of the transportation and sources of pollutants over the Yangtze River Delta as well as the effect of emission control measures during large international events, which are important for the future design of air pollution control policies

On the mode-segregated aerosol particle number concentration load : contributions of primary and secondary particles in Hyytiälä and Nanjing

Aerosol particle concentrations in the atmosphere are governed by their sources and sinks. Sources include directly-emitted (primary) and secondary aerosol particles formed from gas-phase precursor compounds. The relative importance of primary and secondary aerosol particles varies regionally and with time. In this work, we investigated primary and secondary contributions to mode-segregated particle number concentrations by using black carbon as a tracer for the primary aerosol number concentration. We studied separately nucleation, Aitken and accumulation mode concentrations at a rural boreal forest site (Hyytiala, Finland) and in a rather polluted megacity environment (Nanjing, China) using observational data from 2011 to 2014. In both places and in all the modes, the majority of particles were estimated to be of secondary origin. Even in Nanjing, only about half of the accumulation mode particles were estimated to be of primary origin. Secondary particles dominated particularly in the nucleation and Aitken modes.Peer reviewe

Observations of aerosol optical properties at a coastal site in Hong Kong, South China

Temporal variations in aerosol optical properties were investigated at a coastal station in Hong Kong based on the field observation from February 2012 to February 2015. At 550 nm, the average light-scattering (151 +/- 100Mm(-1) / and absorption coefficients (8.3 +/- 6.1Mm(-1) / were lower than most of other rural sites in eastern China, while the single-scattering albedo (SSA = 0.93 +/- 0.05) was relatively higher compared with other rural sites in the Pearl River Delta (PRD) region. Correlation analysis confirmed that the darkest aerosols were smaller in particle size and showed strong scattering wavelength dependencies, indicating possible sources from fresh emissions close to the measurement site. Particles with D-p of 200-800 nm were less in number, yet contributed the most to the light-scattering coefficients among submicron particles. In summer, both Delta BC / Delta CO and SO2 / BC peaked, indicating the impact of nearby combustion sources on this site. Multi-year backward Lagrangian particle dispersion modeling (LPDM) and potential source contribution (PSC) analysis revealed that these particles were mainly from the air masses that moved southward over Shenzhen and urban Hong Kong and the polluted marine air containing ship exhausts. These fresh emission sources led to low SSA during summer months. For winter and autumn months, contrarily, Delta BC / Delta CO and SO2 / BC were relatively low, showing that the site was more under influence of well-mixed air masses from long-range transport including from South China, East China coastal regions, and aged aerosol transported over the Pacific Ocean and Taiwan, causing stronger abilities of light extinction and larger variability of aerosol optical properties. Our results showed that ship emissions in the vicinity of Hong Kong could have visible impact on the light-scattering and absorption abilities as well as SSA at Hok Tsui.Peer reviewe

Estimating cloud condensation nuclei number concentrations using aerosol optical properties : role of particle number size distribution and parameterization

The concentration of cloud condensation nuclei (CCN) is an essential parameter affecting aerosol–cloud interactions within warm clouds. Long-term CCN number concentration (NCCN) data are scarce; there are a lot more data on aerosol optical properties (AOPs). It is therefore valuable to derive parameterizations for estimating NCCN from AOP measurements. Such parameterizations have already been made, and in the present work a new parameterization is presented. The relationships between NCCN, AOPs, and size distributions were investigated based on in situ measurement data from six stations in very different environments around the world. The relationships were used for deriving a parameterization that depends on the scattering Ångström exponent (SAE), backscatter fraction (BSF), and total scattering coefficient (σsp) of PM10 particles. The analysis first showed that the dependence of NCCN on supersaturation (SS) can be described by a logarithmic fit in the range SS 4. At SS >0.4 % the average bias ranged from ∼0.7 to ∼1.3 at most sites. For the marine-aerosol-dominated site Ascension Island the bias was higher, ∼1.4–1.9. In other words, at SS >0.4 % NCCN was estimated with an average uncertainty of approximately 30 % by using nephelometer data. The biases were mainly due to the biases in the parameterization related to the scattering Ångström exponent (SAE). The squared correlation coefficients between the AOP-derived and measured NCCN varied from ∼0.5 to ∼0.8. To study the physical explanation of the relationships between NCCN and AOPs, lognormal unimodal particle size distributions were generated and NCCN and AOPs were calculated. The simulation showed that the relationships of NCCN and AOPs are affected by the geometric mean diameter and width of the size distribution and the activation diameter. The relationships of NCCN and AOPs were similar to those of the observed ones.The concentration of cloud condensation nuclei (CCN) is an essential parameter affecting aerosol-cloud interactions within warm clouds. Long-term CCN number concentration (N-CCN) data are scarce; there are a lot more data on aerosol optical properties (AOPs). It is therefore valuable to derive parameterizations for estimating N-CCN from AOP measurements. Such parameterizations have already been made, and in the present work a new parameterization is presented. The relationships between N-CCN, AOPs, and size distributions were investigated based on in situ measurement data from six stations in very different environments around the world. The relationships were used for deriving a parameterization that depends on the scattering Angstrom exponent (SAE), backscatter fraction (BSF), and total scattering coefficient (sigma(sp)) of PM10 particles. The analysis first showed that the dependence of N-CCN on supersaturation (SS) can be described by a logarithmic fit in the range SS 4. At SS > 0 :4% the average bias ranged from similar to 0.7 to similar to 1.3 at most sites. For the marine-aerosol-dominated site Ascension Island the bias was higher, similar to 1.4-1.9. In other words, at SS > 0:4% N-CCN was estimated with an average uncertainty of approximately 30% by using nephelometer data. The biases were mainly due to the biases in the parameterization related to the scattering Angstrom exponent (SAE). The squared correlation coefficients between the AOP-derived and measured N-CCN varied from similar to 0.5 to similar to 0.8. To study the physical explanation of the relationships between N-CCN and AOPs, lognormal unimodal particle size distributions were generated and N-CCN and AOPs were calculated. The simulation showed that the relationships of N-CCN and AOPs are affected by the geometric mean diameter and width of the size distribution and the activation diameter. The relationships of N-CCN and AOPs were similar to those of the observed ones.Peer reviewe

Multiplexed Cre-dependent selection yields systemic AAVs for targeting distinct brain cell types

Recombinant adeno-associated viruses (rAAVs) are efficient gene delivery vectors via intravenous delivery; however, natural serotypes display a finite set of tropisms. To expand their utility, we evolved AAV capsids to efficiently transduce specific cell types in adult mouse brains. Building upon our Cre-recombination-based AAV targeted evolution (CREATE) platform, we developed Multiplexed-CREATE (M-CREATE) to identify variants of interest in a given selection landscape through multiple positive and negative selection criteria. M-CREATE incorporates next-generation sequencing, synthetic library generation and a dedicated analysis pipeline. We have identified capsid variants that can transduce the central nervous system broadly, exhibit bias toward vascular cells and astrocytes, target neurons with greater specificity or cross the blood–brain barrier across diverse murine strains. Collectively, the M-CREATE methodology accelerates the discovery of capsids for use in neuroscience and gene-therapy applications

Cluster Analysis of Submicron Particle Number Size Distributions at the SORPES Station in the Yangtze River Delta of East China

Submicron particles in polluted regions have received much attention because of their influences on human health and climate. A k-means clustering technique was performed on a data set of particle number size distributions (PNSD) that was obtained over more than 3 years in the Yangtze River Delta (YRD) region of East China. With simultaneous measurements of meteorological conditions, trace gases and aerosol compositions, seven clusters were categorized and interpreted. Cluster 1 and cluster 2, which accounted for 9.9% of the total PNSD data, were attributed to new particle formation (NPF) and vehicle exhaust emissions with different intensities; Cluster 3 and Cluster 4, which accounted for 10.5% of the total PNSD data, were related to the growth of nucleation mode particles; Cluster 5, which accounted for 37.9% of the total data, was attributed to the humid YRD background; and Cluster 6 and Cluster 7, which accounted for 41.6% of the total data set, were both pollution-related clusters with similar mass concentrations but completely different PNSD. Although the PM2.5 mass concentrations were somewhat similar, the particle number concentrations of the accumulation mode particles could vary by more than one order of magnitude from the urban background cluster to the pollution-related clusters. The cluster proximity diagram and conversion flow chart of clusters clearly show the influence of NPF and growth on haze, as well as the conversion between background and polluted conditions. This study highlights the importance of PNSD for understanding urban air quality and recommends the clustering technique for analyzing complex PNSD datasets. Plain Language Summary Submicron particles in polluted regions have significant influences on human health and climate. Based on long-term field measurements, we used the k-means clustering technique to characterize the number size distributions of submicron particles in the Yangtze River Delta (YRD) of China. Seven clusters were categorized and interpreted. New particle formation (NPF), fossil fuel combustion and biomass burning are the main sources of submicron particles in the YRD. The influences of NPF and growth on haze, as well as the conversion between background and polluted conditions, were found. Key Points New particle formation (NPF), fossil fuel combustion and biomass burning are the main sources of submicron particles in Nanjing The influences of NPF and growth on haze, and the conversion between background and pollution conditions were found The k-means cluster technique is an effective tool to categorize particle number size distribution data setPeer reviewe

PgtE Enzyme of Salmonella enterica Shares the Similar Biological Roles to Plasminogen Activator (Pla) in Interacting With DEC-205 (CD205), and Enhancing Host Dissemination and Infectivity by Yersinia pestis

Yersinia pestis, the cause of plague, is a newly evolved Gram-negative bacterium. Through the acquisition of the plasminogen activator (Pla), Y. pestis gained the means to rapidly disseminate throughout its mammalian hosts. It was suggested that Y. pestis utilizes Pla to interact with the DEC-205 (CD205) receptor on antigen-presenting cells (APCs) to initiate host dissemination and infection. However, the evolutionary origin of Pla has not been fully elucidated. The PgtE enzyme of Salmonella enterica, involved in host dissemination, shows sequence similarity with the Y. pestis Pla. In this study, we demonstrated that both Escherichia coli K-12 and Y. pestis bacteria expressing the PgtE-protein were able to interact with primary alveolar macrophages and DEC-205-transfected CHO cells. The interaction between PgtE-expressing bacteria and DEC-205-expressing transfectants could be inhibited by the application of an anti-DEC-205 antibody. Moreover, PgtE-expressing Y. pestis partially re-gained the ability to promote host dissemination and infection. In conclusion, the DEC-205-PgtE interaction plays a role in promoting the dissemination and infection of Y. pestis, suggesting that Pla and the PgtE of S. enterica might share a common evolutionary origin.Peer reviewe

The effect of COVID-19 restrictions on atmospheric new particle formation in Beijing

During the COVID-19 lockdown, the dramatic reduction of anthropogenic emissions provided a unique opportunity to investigate the effects of reduced anthropogenic activity and primary emissions on atmospheric chemical processes and the consequent formation of secondary pollutants. Here, we utilize comprehensive observations to examine the response of atmospheric new particle formation (NPF) to the changes in the atmospheric chemical cocktail. We find that the main clustering process was unaffected by the drastically reduced traffic emissions, and the formation rate of 1.5 nm particles remained unaltered. However, particle survival probability was enhanced due to an increased particle growth rate (GR) during the lockdown period, explaining the enhanced NPF activity in earlier studies. For GR at 1.5-3 nm, sulfuric acid (SA) was the main contributor at high temperatures, whilst there were unaccounted contributing vapors at low temperatures. For GR at 3-7 and 7-15 nm, oxygenated organic molecules (OOMs) played a major role. Surprisingly, OOM composition and volatility were insensitive to the large change of atmospheric NOx concentration; instead the associated high particle growth rates and high OOM concentration during the lockdown period were mostly caused by the enhanced atmospheric oxidative capacity. Overall, our findings suggest a limited role of traffic emissions in NPF.Peer reviewe