Improvement of Raman lidar algorithm for quantifying aerosol extinction

Aerosols are particles of different composition and origin and influence the formation of clouds which are important in atmospheric radiative balance. At the present there is high uncertainty on the effect of aerosols on climate and this is mainly due to the fact that aerosol presence in the atmosphere can be highly variable in space and time. Monitoring of the aerosols in the atmosphere is necessary to better understanding many of these uncertainties. A lidar (an instrument that uses light to detect the extent of atmospheric aerosol loading) can be particularly useful to monitor aerosols in the atmosphere since it is capable to record the scattered intensity as a function of altitude from molecules and aerosols. One lidar method (the Raman lidar) makes use of the different wavelength changes that occur when light interacts with the varying chemistry and structure of atmospheric aerosols. One quantity that is indicative of aerosol presence is the aerosol extinction which quantifies the amount of attenuation (removal of photons), due to scattering, that light undergoes when propagating in the atmosphere. It can be directly measured with a Raman lidar using the wavelength dependence of the received signal. In order to calculate aerosol extinction from Raman scattering data it is necessary to evaluate the rate of change (derivative) of a Raman signal with respect to altitude. Since derivatives are defined for continuous functions, they cannot be performed directly on the experimental data which are not continuous. The most popular technique to find the functional behavior of experimental data is the least-square fit. This procedure allows finding a polynomial function which better approximate the experimental data. The typical approach in the lidar community is to make an a priori assumption about the functional behavior of the data in order to calculate the derivative. It has been shown in previous work that the use of the chi-square technique to determine the most likely functional behavior of the data prior to actually calculating the derivative eliminates the need for making a priori assumptions. We note that the a priori choice of a model itself can lead to larger uncertainties as compared to the method that is validated here. In this manuscript, the chi-square technique that determines the most likely functional behavior is validated through numerical simulation and by application to a large body of Raman lidar measurements. In general, we show that the chi-square approach to evaluate aerosol extinction yields lower extinction uncertainty than the traditional technique. We also use the technique to study the feasibility of developing a general characterization of the extinction uncertainty that could permit the uncertainty in Raman lidar aerosol extinction measurements to be estimated accurately without the use of the chi-square technique

Defend as You Can, React Quickly: The Effects of the COVID-19 Shock on a Large Fishery of the Mediterranean Sea

This paper presents an analysis of the effect of SARS-CoV-2 coronavirus pandemic and related restrictive measures on the activity of the Italian fleet of trawlers, which represents one of the most important fisheries in the Mediterranean Sea. We integrated multiple sources of information including: (1) Fleet activity data from Vessel Monitoring System, the most important satellite-based tracking device; (2) vessel-specific landing data disaggregated by species; (3) market and economic drivers affecting the effort variation during the lockdown and in the related fishing strategies; (4) monthly landings of demersal species in the main Italian harbors. These data sources are combined to: (1) Assess the absolute and relative changes of trawling effort in the geographical sub- areas surrounding the Italian coasts; (2) integrate and compare these changes with the market and economic drivers in order to explain the observed changes in fishing effort and strategy; (3) analyze the changes of the fishing effort on the Landing-per-unit- effort (LPUE) in order to further understand the strategy adopted by fishers during this crisis and to infer the potential consequence for the different stocks. The results provide an overview of the effects of the “COVID-19 shock,” in terms of fishing activity and socio-economic drivers, demonstrating that the consequences of the pandemic have been very varied. Although the COVID-19 shock has caused a marked overall reduction in activity in the first semester of 2020, in some cases the strategies adopted by fishermen and the commercial network linked to their activity have significantly reduced the impact of the emergency and taken back catch and effort to levels similar to those of previous years. These results could provide insights for management measures based on temporal stops of fishing activities. In particular, if no limits to the fishing effort after the restart of fishing activities are adopted, the benefits of fishing pressure reduction on fishery resources could be nullified. On the other hands, when fishing activities restart, and in the absence of catch control, effort tends to increase on coastal bottoms characterized by greater abundance of resources and longer effective fishing time

Liquid Water Cloud Measurements Using the Raman Lidar Technique: Current Understanding and Future Research Needs

This paper describes recent work in the Raman lidar liquid water cloud measurement technique. The range-resolved spectral measurements at the National Aeronautics and Space Administration Goddard Space Flight Center indicate that the Raman backscattering spectra measured in and below low clouds agree well with theoretical spectra for vapor and liquid water. The calibration coefficients of the liquid water measurement for the Raman lidar at the Atmospheric Radiation Measurement Program Southern Great Plains site of the U.S. Department of Energy were determined by comparison with the liquid water path (LWP) obtained with Atmospheric Emitted Radiance Interferometer (AERI) and the liquid water content (LWC) obtained with the millimeter wavelength cloud radar and water vapor radiometer (MMCR-WVR) together. These comparisons were used to estimate the Raman liquid water cross-sectional value. The results indicate a bias consistent with an effective liquid water Raman cross-sectional value that is 28%-46% lower than published, which may be explained by the fact that the difference in the detectors' sensitivity has not been accounted for. The LWP of a thin altostratus cloud showed good qualitative agreement between lidar retrievals and AERI. However, the overall ensemble of comparisons of LWP showed considerable scatter, possibly because of the different fields of view of the instruments, the 350-m distance between the instruments, and the horizontal inhomogeneity of the clouds. The LWC profiles for a thick stratus cloud showed agreement between lidar retrievals andMMCR-WVR between the cloud base and 150m above that where the optical depth was less than 3. Areas requiring further research in this technique are discussed

Simulating the Effects of Alternative Management Measures of Trawl Fisheries in the Central Mediterranean Sea: Application of a Multi-Species Bio-economic Modeling Approach

In the last decades, the Mediterranean Sea experienced an increasing trend of fish stocks in overfishing status. Therefore, management actions to achieve a more sustainable exploitation of fishery resources are required and compelling. In this study, a spatially explicit multi-species bio-economic modeling approach, namely, SMART, was applied to the case study of central Mediterranean Sea to assess the potential effects of different trawl fisheries management scenarios on the demersal resources. The approach combines multiple modeling components, integrating the best available sets of spatial data about catches and stocks, fishing footprint from vessel monitoring systems (VMS) and economic parameters in order to describe the relationships between fishing effort pattern and impacts on resources and socio-economic consequences. Moreover, SMART takes into account the bi-directional connectivity between spawning and nurseries areas of target species, embedding the outcomes of a larvae transport Lagrangian model and of an empirical model of fish migration. Finally, population dynamics and trophic relationships are considered using a MICE (Models of Intermediate Complexity) approach. SMART simulates the fishing effort reallocation resulting from the introduction of different management scenarios. Specifically, SMART was applied to evaluate the potential benefits of different management approaches of the trawl fisheries targeting demersal stocks (deepwater rose shrimp Parapenaeus longirostris, the giant red shrimp Aristaeomorpha foliacea, the European hake Merluccius merluccius, and the red mullet Mullus barbatus) in the Strait of Sicily. The simulated management scenarios included a reduction of both fishing capacity and effort, two different sets of temporal fishing closures, and two sets of spatial fishing closures, defined involving fishers. Results showed that both temporal and spatial closures are expected to determine a significant improvement in the exploitation pattern for all the species, ultimately leading to the substantial recovery of spawning stock biomass for the stocks. Overall, one of the management scenarios suggested by fishers scored better and confirms the usefulness of participatory approaches, suggesting the need for more public consultation when dealing with resource management at sea

An Investigation of Raman Lidar Aerosol Measurements and their Application to the study of the Aerosol Indirect Effect

The problem of the increasing global atmospheric temperature has motivated a large interest in studying the mechanisms that can influence the radiative balance of the planet. Aerosols are responsible for several radiative effects in the atmosphere: an increase of aerosol loading in the atmosphere increases the reflectivity of the atmosphere and has an estimated cooling effect and is called the aerosol direct effect. Another process involving aerosols is the effect that an increase in their concentration in the atmosphere has on the formation of clouds and is called the aerosol indirect effect. In the latest IPCC report, the aerosol indirect effect was estimated to be responsible for a radiative forcing ranging between -0.3 W/m2 to -1.8 W/m2, which can be as large as, but opposite in sign to, the radiative forcing due to greenhouse gases. The main goal of this dissertation is to study the Raman lidar measurements of quantities relevant for the investigation of the aerosol indirect effect and ultimately to apply these measurements to a quantification of the aerosol indirect effect. In particular we explore measurements of the aerosol extinction from both the NASA Goddard Space Flight Center Scanning Raman Lidar (SRL) and the US Department of Energy (DOE) ARM Climate Research Facility Raman Lidar (CARL). An algorithm based on the chi-squared technique to calculate the aerosol extinction, which was introduced first by Whiteman (1999), is here validated using both simulated and experimental data. It has been found as part of this validation that the aerosol extinction uncertainty retrieved with this technique is on average smaller that the uncertainty calculated with the technique traditionally used. This algorithm was then used to assess the performance of the CARL aerosol extinction retrieval for low altitudes. Additionally, since CARL has been upgraded with a channel for measuring Raman liquid water scattering, measurements of cloud liquid water content, droplet radius and droplet number density using this new capability have been studied. Some discrepancies are found between the CARL and AERI measurements of liquid water path and droplet effective radius and they need to be studied in more detail when a larger dataset is available. To study the correlation between aerosol presence and cloud microphysics the calculations of IE, introduced by Feingold as a parameterization of the aerosol indirect effect, has been performed here for the first time using exclusively Raman lidar data. The work shown here is an indication that the combined measurements of aerosol extinction, cloud liquid water content, droplet radius and droplet number density with a Raman lidar represents an interesting new technique for the study of the aerosol indirect effect

Huperzine a restores cortico-hippocampal functional connectivity after bilateral ampa lesion of the nucleus basalis of meynert

Huperzine A (Hup-A), an alkaloid isolated from Huperzia serrata (Thunb.) Trevis. (Lycopodiaceae), acts as a selective inhibitor of acetylcholinesterase and shows memory-enhancing properties. Although Hup-A has shown promising expectation for Alzheimer's disease (AD) patients, controlled clinical trials supporting its use are limited. The aim of this work was to study in vivo, in an animal model of AD, the pharmacological activity of systemic administration of Hup-A on cortex- and hippocampus-dependent memory. With this purpose, a set of experiments was planned to evaluate attention, learning, working and spatial memory with respect to cortical and hippocampal electroencephalogram (EEG) theta rhythm during the object recognition test and Morris water maze in animals with lesion of the nucleus basalis of Meynert (NBM). In NBM-lesioned animals, compared with control, an increased theta power in the cortex and a reduced theta rhythm oscillation in the hippocampus were found. These EEG changes were correlated with worse performance in learning and memory tasks. In rats with damaged NBM, Hup-A (0.5 mg/kg i.p.) was able to restore EEG architecture, producing cortical desynchronization and reduction in theta power, while in the hippocampus the drug increased theta oscillation and reduced the impairment in attention/working memory as well as spatial navigation performance in the behavioral tasks. Taken together, the present data suggest that Hup-A is able to restore cholinergic cortico-hippocampal functional connectivity. In conclusion, the present results are in agreement with other experimental evidence that promote the clinical use of this natural drug

The On-Line Integrated Mesoscale Chemistry Model BOLCHEM

This work presents the on-line coupled meteorology–chemistry transport model BOLCHEM, based on the hydrostatic meteorological BOLAM model, the gas chemistry module SAPRC90, and the aerosol dynamic module AERO3. It includes parameterizations to describe natural source emissions, dry and wet removal processes, as well as the transport and dispersion of air pollutants. The equations for different processes are solved on the same grid during the same integration step, by means of a time-split scheme. This paper describes the model and its performance at horizontal resolution of 0.2∘× 0.2∘ over Europe and 0.1∘× 0.1∘ in a nested configuration over Italy, for one year run (December 2009–November 2010). The model has been evaluated against the AIRBASE data of the European Environmental Agency. The basic statistics for higher resolution simulations of O3, NO2 and particulate matter concentrations (PM2.5 and PM10) have been compared with those from Copernicus Atmosphere Monitoring Service (CAMS) ensemble median. In summer, for O3 we found a correlation coefficient R of 0.72 and mean bias of 2.15 over European domain and a correlation coefficient R of 0.67 and mean bias of 2.36 over Italian domain. PM10 and PM2.5 are better reproduced in the winter, the latter with a correlation coefficient R of 0.66 and the mean bias MB of 0.35 over Italian domain