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| submission-date = 2018-10-09
 
| submission-date = 2018-10-09
 
| type = Report
 
| type = Report
| url = https://mediawiki.envri.eu/images/0/05/D1.1._Roadmap_for_the_emergence_of_European_industry_providers_and_market_landscape_analysis.pdf
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| pdf =
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| zenodo =
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| url = http://www.envriplus.eu/wp-content/uploads/2018/10/D1.1-Emerging-technologies-emerging-markets-fostering-the-innovation-potential-of-research-infrastructures.pdf
 
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The aim of WP1-task 1.1, is to identify and analyse emerging environmental observations technologies (sensors and platforms) that could be useful to, and benefit from, Research infrastructures (RIs) to realize and achieve their market potential. The task also aims to explore technical challenges, market barriers and ongoing initiatives related to these technologies. The deliverable D1.1 is tailored to be a source of inspiration for Small and Medium Enterprises (SMEs), while investigating new business opportunities, as well as for the EU bodies, pointing them the specific areas requiring additional attention and financing.
 
The aim of WP1-task 1.1, is to identify and analyse emerging environmental observations technologies (sensors and platforms) that could be useful to, and benefit from, Research infrastructures (RIs) to realize and achieve their market potential. The task also aims to explore technical challenges, market barriers and ongoing initiatives related to these technologies. The deliverable D1.1 is tailored to be a source of inspiration for Small and Medium Enterprises (SMEs), while investigating new business opportunities, as well as for the EU bodies, pointing them the specific areas requiring additional attention and financing.
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Monitoring environmental parameters and climate change is a complex task which answers grand challenges. It is of crucial importance (Bell and Joseph 2018) for all countries and societies. Development of technologies for such monitoring is in huge demand and driven by numerous factors (fig.1). Among them are demand for the high quality of measurements and development of new types of measurements, reduction of measurements costs, necessity to control the pollution and avoiding the legislative responsibility for the contamination of the environment. Besides, there is a large societal demand based on the ongoing decrease of air, soil and water quality. Environmental monitoring is a complicated activity, because technical requirements for the innovative measurement platforms, systems and sensors can vary significantly across regions and domains. Such variations certainly create unwanted difficulties for the technology producers, especially small and medium enterprises (SMEs), due to their generally limited resources. European businesses are limited in their development in this field due to the inability to overcome the technological differences, to overview the possible paths for development of corresponding markets and to establish the contacts in-between research communities, technology producers and other supporting businesses. This deliverable of ENVRIplus<ref>https://www.envriplus.eu/</ref> project serves to overpass mentioned difficulties of environmental measurements in Europe. It is aimed to help SMEs, scientific communities and other interested partners to establish fruitful, beneficial collaborations and to understand the possible vectors of development of European environmental measurements and monitoring.  
 
Monitoring environmental parameters and climate change is a complex task which answers grand challenges. It is of crucial importance (Bell and Joseph 2018) for all countries and societies. Development of technologies for such monitoring is in huge demand and driven by numerous factors (fig.1). Among them are demand for the high quality of measurements and development of new types of measurements, reduction of measurements costs, necessity to control the pollution and avoiding the legislative responsibility for the contamination of the environment. Besides, there is a large societal demand based on the ongoing decrease of air, soil and water quality. Environmental monitoring is a complicated activity, because technical requirements for the innovative measurement platforms, systems and sensors can vary significantly across regions and domains. Such variations certainly create unwanted difficulties for the technology producers, especially small and medium enterprises (SMEs), due to their generally limited resources. European businesses are limited in their development in this field due to the inability to overcome the technological differences, to overview the possible paths for development of corresponding markets and to establish the contacts in-between research communities, technology producers and other supporting businesses. This deliverable of ENVRIplus<ref>https://www.envriplus.eu/</ref> project serves to overpass mentioned difficulties of environmental measurements in Europe. It is aimed to help SMEs, scientific communities and other interested partners to establish fruitful, beneficial collaborations and to understand the possible vectors of development of European environmental measurements and monitoring.  
  
<div class="figure" id="figure1">[[File:ENVRIplus D1.1-Fig. 1-Factors influencing the development of technology.png|center|frame|Figure 1: Factors influencing the development of technology]]</div>
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FIGURE 1 FACTORS INFLUENCING THE DEVELOPMENT OF TECHNOLOGY
  
 
==1.3 Approach of this work: methodology==
 
==1.3 Approach of this work: methodology==
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Atmospheric LIDAR is a class of instruments that uses laser light to study atmospheric properties from the ground up to the top of the atmosphere (Kavaya and Menzies 1985). Such instruments have been used to study, among other, atmospheric gases, aerosols, clouds, and temperature. The transmission unit consists of a laser source, followed by a series of mirrors, and a beam expander, which sends the collimated light beam vertically up to the open atmosphere. Part of the transmitted radiation is scattered by atmospheric components (i.e., gases, molecules, aerosols, clouds) backward to the LIDAR, where a telescope collects it. The backscattered light is driven to an optical analyser where the optical signal is first spectrally separated, amplified and transformed to an electrical signal. Finally, the signal is digitized and stored in a computer unit. While knowing the aerosol properties (forward problem) and predicting the LIDAR signal is a straightforward calculation, the inverse process is mathematically ill-posed (i.e., non-unique and incomplete solution space), showing a strong sensitivity on input uncertainties.  
 
Atmospheric LIDAR is a class of instruments that uses laser light to study atmospheric properties from the ground up to the top of the atmosphere (Kavaya and Menzies 1985). Such instruments have been used to study, among other, atmospheric gases, aerosols, clouds, and temperature. The transmission unit consists of a laser source, followed by a series of mirrors, and a beam expander, which sends the collimated light beam vertically up to the open atmosphere. Part of the transmitted radiation is scattered by atmospheric components (i.e., gases, molecules, aerosols, clouds) backward to the LIDAR, where a telescope collects it. The backscattered light is driven to an optical analyser where the optical signal is first spectrally separated, amplified and transformed to an electrical signal. Finally, the signal is digitized and stored in a computer unit. While knowing the aerosol properties (forward problem) and predicting the LIDAR signal is a straightforward calculation, the inverse process is mathematically ill-posed (i.e., non-unique and incomplete solution space), showing a strong sensitivity on input uncertainties.  
  
<div class="tablecaption" id="table28">TABLE 28 STRENGTHS AND LIMITATIONS OF LIDARS</div>
+
TABLE 28 STRENGTHS AND LIMITATIONS OF LIDARS  
{| class="wikitable"
 
! scope="row" | Strengths
 
! scope="row" | Limitations
 
|-
 
! scope="row" | Provide vertical distribution of aerosol
 
| Inversion is strongly sensitive on input uncertainties
 
|-
 
! scope="row" | Can provide the shape (degree of sphericity) of the particles
 
| Need integration with independent source of information
 
|-
 
! scope="row" | Multiple wavelength
 
| Works better during night (no sunlight interference)
 
|}
 
Producers are presented in table 29.
 
  
<div class="tablecaption" id="table"></div>
+
TABLE 29 COMPANIES PRODUCING LIDARS
{| class="wikitable"
 
! scope="row" | Producer name
 
! scope="row" | Website
 
|-
 
! scope="row" | Leosphere
 
| https://www.leosphere.com
 
|-
 
! scope="row" | Ala Systems
 
| https://www.alasystems.it
 
|}
 
  
 
====2.2.2.3 Aerosol chemical properties====
 
====2.2.2.3 Aerosol chemical properties====
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TOF-AMS is used to study the chemical and physical nature of aerosol particles online and is constructed as a combination of AMS vacuum system, particle focusing, sizing and evaporation/ionization components with a compact orthogonal acceleration reflection time-of-flight spectrometer (De Carlo et al. 2006). Aerosol particles in the size range of 0.04 to 1.0 micrometres are sampled into a high vacuum system where they are focused into a narrow beam. This beam is then directed via ionization quadrupole mass spectrometry. Particle aerodynamic diameter is determined from particle time of flight (velocity) measurements using a beam chopping technique.
 
TOF-AMS is used to study the chemical and physical nature of aerosol particles online and is constructed as a combination of AMS vacuum system, particle focusing, sizing and evaporation/ionization components with a compact orthogonal acceleration reflection time-of-flight spectrometer (De Carlo et al. 2006). Aerosol particles in the size range of 0.04 to 1.0 micrometres are sampled into a high vacuum system where they are focused into a narrow beam. This beam is then directed via ionization quadrupole mass spectrometry. Particle aerodynamic diameter is determined from particle time of flight (velocity) measurements using a beam chopping technique.
  
<div class="tablecaption" id="table30">TABLE 30 STRENGTHS AND LIMITATIONS OF TOF-AMS</div>
+
TABLE30STRENGTHSANDLIMITATIONSOFTOF-AMS  
{| class="wikitable"
+
 
! scope="row" | Strengths
+
TABLE 31 PRODUCERS OF DEVICES FOR TOF-AMS  
! scope="row" | Limitations
 
|-
 
! scope="row" | Online chemical and physical nature of aerosol particles
 
| Complexity
 
|-
 
! scope="row" | particle aerodynamic diameter and aerosol composition in a single measurement
 
| High cost
 
|-
 
! scope="row" | Quantitative particle analysis possible
 
|
 
|-
 
! scope="row" | direct sampling of aerosol
 
|
 
|-
 
! scope="row" | Fast measurements (1-10 sec) of particle size distributions and non-refractory chemical composition
 
|
 
|}
 
Producers of TOF-AMS are presented in table 31.
 
 
 
<div class="tablecaption" id="table31">TABLE 31 PRODUCERS OF DEVICES FOR TOF-AMS</div>
 
{| class="wikitable"
 
! scope="row" | Producer name
 
! scope="row" | Website
 
|-
 
! scope="row" | Aerodyne Research
 
| http://www.aerodyne.com/
 
|}
 
  
 
====2.2.2.4 Aerosol size distribution====
 
====2.2.2.4 Aerosol size distribution====
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A high intensity light source is used to illuminate the particle as it passes through the detection chamber. The particle passes through the light source (typically a laser or halogen light) and the redirected light is detected by a photodetector. The amplitude of the light scattered is measured and the particle is counted and tabulated into standardized counting bins, after assumption of the refractive index of the particles (Snider and Petters 2008)  
 
A high intensity light source is used to illuminate the particle as it passes through the detection chamber. The particle passes through the light source (typically a laser or halogen light) and the redirected light is detected by a photodetector. The amplitude of the light scattered is measured and the particle is counted and tabulated into standardized counting bins, after assumption of the refractive index of the particles (Snider and Petters 2008)  
  
<div class="tablecaption" id="table32">TABLE 32 STRENGTHS AND LIMITATIONS OF OPTICAL PARTICLE COUNTERS</div>
+
TABLE 32 STRENGTHS AND LIMITATIONS OF OPTICAL PARTICLE COUNTERS  
{| class="wikitable"
 
! scope="row" | Strengths
 
! scope="row" | Limitations
 
|-
 
! scope="row" | Can be miniaturize
 
| The binning of the particles depends on the assumed refractive index and on the shape of the particles
 
|-
 
! scope="row" | Fast response
 
| Unable to detect particles smaller than 50-100 nm
 
|}
 
Producers are presented in table 33.
 
  
<div class="tablecaption" id="table33">TABLE 33 COMPANIES PRODUCING OPTICAL PARTICLE COUNTERS</div>
+
TABLE 33 COMPANIES PRODUCING OPTICAL PARTICLE COUNTERS  
{| class="wikitable"
 
! scope="row" | Producer name
 
! scope="row" | Website
 
|-
 
! scope="row" | FAI Instruments
 
| https://www.fai-instruments.com
 
|-
 
! scope="row" | TSI
 
| https://www.tsi.com
 
|-
 
! scope="row" | GRIMM Aerosol Technik Ainring GmbH & Co.KG
 
| https://www.grimm-aerosol.com
 
|-
 
! scope="row" | Lighthouse Worldwide Solutions
 
| https://www.golighthouse.com/en
 
|}
 
  
 
=====2.2.2.4.2 Differential Mobility Particle Sizer (DMPS)=====
 
=====2.2.2.4.2 Differential Mobility Particle Sizer (DMPS)=====
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Differential mobility particle sizing is an alternative to the optical sizing technique for measurement of submicron aerosol size distributions (Wiedensohler et al. 2012). Differential mobility techniques are able to measure much smaller particles, down to 2.5nm and are not sensitive to differences in refractive index, but are not able to achieve the same temporal resolution as optical instruments, and are also sensitive to variations in particle shape. The Differential Mobility Particle Sizer (DMPS) couples a differential mobility analyser, which classifies charged particles according to their mobility in an electric field, and a condensation particle counter (CPC) to count particles of a specific mobility. Other instruments using variations on this technique include the SMPS and HTDMA.
 
Differential mobility particle sizing is an alternative to the optical sizing technique for measurement of submicron aerosol size distributions (Wiedensohler et al. 2012). Differential mobility techniques are able to measure much smaller particles, down to 2.5nm and are not sensitive to differences in refractive index, but are not able to achieve the same temporal resolution as optical instruments, and are also sensitive to variations in particle shape. The Differential Mobility Particle Sizer (DMPS) couples a differential mobility analyser, which classifies charged particles according to their mobility in an electric field, and a condensation particle counter (CPC) to count particles of a specific mobility. Other instruments using variations on this technique include the SMPS and HTDMA.
  
<div class="tablecaption" id="table34">TABLE 34 STRENGTHS AND LIMITATIONS OF DIFFERENTIAL MOBILITY PARTICLE SIZER </div>
+
TABLE 34 STRENGTHS AND LIMITATIONS OF DIFFERENTIAL MOBILITY PARTICLE SIZER  
{| class="wikitable"
 
! scope="row" | Strengths
 
! scope="row" | Limitations
 
|-
 
! scope="row" | Can measure particles down to 2.5 nm
 
| For non-spherical particles mobility diameter is a function of particle shape and orientation
 
|-
 
! scope="row" | Can operate with water as condensation fluid
 
| Need condensation fluid refill
 
|}
 
Producers are presented in table 35.
 
  
<div class="tablecaption" id="table35">TABLE 35 PRODUCERS OF DEVICES FOR DMPS</div>
+
TABLE 35 PRODUCERS OF DEVICES FOR DMPS  
{| class="wikitable"
 
! scope="row" | Producer name
 
! scope="row" | Website
 
|-
 
! scope="row" | TSI
 
| https://www.tsi.com
 
|-
 
! scope="row" | Particle Measuring Systems
 
| https://www.pmeasuring.com
 
|}
 
  
 
=====2.2.2.4.3 Aerodynamic Particle Sizer=====
 
=====2.2.2.4.3 Aerodynamic Particle Sizer=====
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The aerodynamic particle sizer uses the principle of inertia to size particles (Wang and John 1987). In this instrument the particle and sheath flow are constricted through a nozzle, accelerating the airflow. Particles within the airflow are also accelerated, but by different amounts depending on particle surface area and mass, thus particles exiting the jet have a velocity related to their aerodynamic diameter. Aerodynamic diameter is defined assuming spherical particles and unity density. The APS measures particle velocity by passing the particles through two laser beams separated by about 200 microns. A particle passing through both beams produces two pulses of scattered light, the time delay between the pulses being related to the velocity and hence aerodynamic diameter of the particle.  
 
The aerodynamic particle sizer uses the principle of inertia to size particles (Wang and John 1987). In this instrument the particle and sheath flow are constricted through a nozzle, accelerating the airflow. Particles within the airflow are also accelerated, but by different amounts depending on particle surface area and mass, thus particles exiting the jet have a velocity related to their aerodynamic diameter. Aerodynamic diameter is defined assuming spherical particles and unity density. The APS measures particle velocity by passing the particles through two laser beams separated by about 200 microns. A particle passing through both beams produces two pulses of scattered light, the time delay between the pulses being related to the velocity and hence aerodynamic diameter of the particle.  
  
<div class="tablecaption" id="table36">TABLE 36 STRENGTHS AND LIMITATIONS OF AERODYNAMIC PARTICLE SIZER</div>
+
TABLE 36 STRENGTHS AND LIMITATIONS OF AERODYNAMIC PARTICLE SIZER  
{| class="wikitable"
 
! scope="row" | Strengths
 
! scope="row" | Limitations
 
|-
 
! scope="row" | Can operate at very high rate (10 Hz)
 
| For non-spherical particles mobility diameter is a function of particle shape and orientation
 
|-
 
! scope="row" | Don’t need any refill or filter change
 
|
 
|}
 
Producers are presented in table 37.
 
  
<div class="tablecaption" id="table37">TABLE 37 COMPANIES PRODUCING AERODYNAMIC PARTICLE SIZER</div>
+
TABLE 37 COMPANIES PRODUCING AERODYNAMIC PARTICLE SIZER  
{| class="wikitable"
 
! scope="row" | Producer name
 
! scope="row" | Website
 
|-
 
! scope="row" | TSI
 
| https://www.tsi.com
 
|-
 
! scope="row" | Particle Measuring Systems
 
| https://www.pmeasuring.com
 
|}
 
  
 
===2.2.3 Emerging technologies for aerosol properties measurements===
 
===2.2.3 Emerging technologies for aerosol properties measurements===
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Budke at al 2008 described a novel device for ice nucleation measurements based on the following principles. Turbulent mixing of cold dry air with warm humid air is performed in the Fast Ice Nucleus Chamber. Resulting ice particles with the size over 4 μm formed during 10 s of experimental time are separated from the droplets based on their individual circular depolarization properties and counted by an optical detector. Biological fraction is measured by special fluorescence channel.
 
Budke at al 2008 described a novel device for ice nucleation measurements based on the following principles. Turbulent mixing of cold dry air with warm humid air is performed in the Fast Ice Nucleus Chamber. Resulting ice particles with the size over 4 μm formed during 10 s of experimental time are separated from the droplets based on their individual circular depolarization properties and counted by an optical detector. Biological fraction is measured by special fluorescence channel.
  
<div class="tablecaption" id="table38">TABLE 38 STRENGTHS AND LIMITATIONS OF ICE NUCLEATION DETECTION</div>
+
TABLE 38 STRENGTHS AND LIMITATIONS OF ICE NUCLEATION DETECTION  
{| class="wikitable"
+
 
! scope="row" | Strengths
+
====2.2.3.2 Measurements of particle morphology ====
! scope="row" | Limitations
+
 
|-
+
Aerosol Particle Spectrometer with Depolarization (APSD) measures light scattered at two angles from individual particles and the extent at which these particles rotate the incident plane of polarization when they pass through a focused laser beam. The amount of scattered light is used to determine the particle size using Mie theory, while the direction of scattered light is used to determine the deviation of particles shape from sphere.
! scope="row" | Active monitoring of RH and T in the ice activation region
 
| Complex depolarization
 
|-
 
! scope="row" | High sample flow
 
| Frost point measurements
 
|-
 
! scope="row" | Good counting statistics at low IN concentrations
 
|
 
|-
 
! scope="row" | Good possibility to vary the experimental conditions through changing the gases flow rates
 
|
 
|}
 
  
====2.2.3.2 Measurements of particle morphology ====
+
TABLE 39 STRENGTHS AND LIMITATIONS OF APSD  
 
 
Aerosol Particle Spectrometer with Depolarization (APSD) measures light scattered at two angles from individual particles and the extent at which these particles rotate the incident plane of polarization when they pass through a focused laser beam. The amount of scattered light is used to determine the particle size using Mie theory, while the direction of scattered light is used to determine the deviation of particles shape from sphere.
 
 
 
<div class="tablecaption" id="table39">TABLE 39 STRENGTHS AND LIMITATIONS OF APSD</div>
 
{| class="wikitable"
 
! scope="row" | Strengths
 
! scope="row" | Limitations
 
|-
 
! scope="row" | Can measure particles in cloud-free air and in the residuals of clouds, determining source of cloud nuclei
 
| Not found
 
|}
 
  
 
===2.2.4 Development of market of aerosols measurements===
 
===2.2.4 Development of market of aerosols measurements===
  
Aerosols impair visibility, affect ecosystem processes and can deposit onto surfaces, damaging materials. They also make an impact on climate change: most particles are reflective and lead to net cooling, while some, especially black carbon particles, absorb energy and promote global warming. Breathing particulate matter/ aerosols can cause coughing, difficulties in breathing, irregular heartbeat, nonfatal heart attacks, aggravated asthma, and decreased lung functioning and general irritation of airways. It can be a reason of premature death of people with heart or lung disease, as well as general decrease of life quality of exposed population. This is causing increased demand for the medical services and care, meaning additional healthcare expenses for the governments and local authorities.  
+
Aerosols impair visibility, affect ecosystem processes and can deposit onto surfaces, damaging materials. They also make an impact on climate change: most particles are reflective and lead to net cooling, while some, especially black carbon particles, absorb energy and promote global warming. Breathing particulate matter/ aerosols can cause coughing, difficulties in breathing, irregular heartbeat, nonfatal heart attacks, aggravated asthma, and decreased lung functioning and general irritation of airways. It can be a reason of premature death of people with heart or lung disease, as well as general decrease of life quality of exposed population.  
 +
This is causing increased demand for the medical services and care, meaning additional healthcare expenses for the governments and local authorities.  
  
 
Keeping in mind the above mentioned problems, local and state authorities would be the first in the list of parties, interested in monitoring and preventing air pollution with aerosols, both those, appearing due to the natural reasons, for example sandstorms, or forest fires and due the anthropogenic activity. State authorities would also be interested in development the legislation that would oblige large industrial and energy providers to monitor their fluxes of aerosols and analyse their composition. Thus, we believe that the main markets for the aerosol measurement devices will be:  
 
Keeping in mind the above mentioned problems, local and state authorities would be the first in the list of parties, interested in monitoring and preventing air pollution with aerosols, both those, appearing due to the natural reasons, for example sandstorms, or forest fires and due the anthropogenic activity. State authorities would also be interested in development the legislation that would oblige large industrial and energy providers to monitor their fluxes of aerosols and analyse their composition. Thus, we believe that the main markets for the aerosol measurement devices will be:  
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Increased concern of people about their health will increase the amount of private and state- funded research projects, dedicated to the investigations of aerosols, especially in the urban areas. Thus, we also expect universities and private companies to become strong consumers of sensors for aerosol measurement.
 
Increased concern of people about their health will increase the amount of private and state- funded research projects, dedicated to the investigations of aerosols, especially in the urban areas. Thus, we also expect universities and private companies to become strong consumers of sensors for aerosol measurement.
  
Measurement responses of modern devices for aerosol measurements depend largely on aerosol properties including particle shape, composition and density. These parameters may vary significantly depending on the type of aerosol, often remain unknown and bring significant uncertainties to the measurements. Thus, we think that more effort needs to be taken to improve measurement accuracies for realistic atmospheric samples. The measurement of organic species in atmospheric particles requires additional development. Atmospheric aerosols normally include dozens of organic compounds, and only a small fraction (∼10%) of these can be detected and identified by modern analytical methodologies. Total particulate organic carbon mass concentration measurements is another challenge due to the difficulties in determination of evaporative losses during sampling, adsorption of gas- phase organic compounds onto sampling substrates and the unknown relations between carbon mass and mass of the particulate organics. The development of improved methodologies for such measurements should be a high priority for the future. The new models of mass spectrometers capable of measuring the composition of individual particles have recently been developed. These instruments have to be improved to provide quantitative information on species mass concentrations, and more work is needed to perform routine interpretation of large datasets generated during field sampling.
+
Measurement responses of modern devices for aerosol measurements depend largely on aerosol properties including particle shape, composition and density. These parameters may vary significantly depending on the type of aerosol, often remain unknown and bring significant uncertainties to the measurements. Thus, we think that more effort needs to be taken to improve measurement accuracies for realistic atmospheric samples. The measurement of organic species in atmospheric particles requires additional development. Atmospheric aerosols normally include dozens of organic compounds, and only a small fraction (∼10%) of these can be detected and identified by modern analytical methodologies. Total particulate organic carbon mass concentration measurements is another challenge due to the difficulties in determination of evaporative losses during sampling, adsorption of gas- phase organic compounds onto sampling substrates and the unknown relations between carbon mass and mass of the particulate organics. The development of improved methodologies for such measurements should be a high priority for the future. The new models of mass spectrometers capable of measuring the composition of individual particles have recently been developed. These instruments have to be improved to provide quantitative information on species mass concentrations, and more work is needed to perform routine interpretation of large datasets generated during field sampling.  
  
 
=3 Measurements of land biosphere parameters=
 
=3 Measurements of land biosphere parameters=
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This technique is employed to measure exchanges between the surface (i.e.: ecosystem, including vegetation and soil) and the atmosphere.
 
This technique is employed to measure exchanges between the surface (i.e.: ecosystem, including vegetation and soil) and the atmosphere.
  
<div class="figure" id="figure2">[[File:ENVRIplus D1.1-Fig. 2-Eddy covariance technique on-site.png|center|frame|Figure 2: Eddy co-variance technique on-site]]</div>
+
FIGURE 2 EDDY-COVARIANCE TECHNIQUE ON-SITE
  
 
It can be used, for example, to measure how much a given surface is either a sink or a source for a greenhouse gas such as CO2 or any other species that can be sampled with a sufficiently fast time response. The technique is based on fast (10 Hz or more) measurements of both three dimensional wind velocity (atmospheric turbulence, usually done through an ultrasonic anemometer) and atmospheric concentration of the chemical species of interests (generally CO2, CH4 and N2O in addition to energy). These two measurements can be related together following a specific mathematical approach to yield a flux with a high temporal resolution and integrated at ecosystem scale (1 km2).  
 
It can be used, for example, to measure how much a given surface is either a sink or a source for a greenhouse gas such as CO2 or any other species that can be sampled with a sufficiently fast time response. The technique is based on fast (10 Hz or more) measurements of both three dimensional wind velocity (atmospheric turbulence, usually done through an ultrasonic anemometer) and atmospheric concentration of the chemical species of interests (generally CO2, CH4 and N2O in addition to energy). These two measurements can be related together following a specific mathematical approach to yield a flux with a high temporal resolution and integrated at ecosystem scale (1 km2).  
  
<div class="tablecaption" id="table40">TABLE 40 STRENGTHS AND LIMITATIONS OF EDDY COVARIANCE TECHNIQUE</div>
+
TABLE 40 STRENGTHS AND LIMITATIONS OF EDDY COVARIANCE TECHNIQUE  
{| class="wikitable"
+
 
! scope="row" | Strengths
+
TABLE 41 PRODUCERS OF DEVICES BASED ON EDDY COVARIANCE TECHNIQUE
! scope="row" | Limitations
+
 
|-
+
===3.2.2 Spectral imaging===
! scope="row" | Can measure how much a biospheric component (forest, grassland, …) is either a source or sink for greenhouse gas (CO<sub>2</sub>, CH<sub>4</sub>, N<sub>2</sub>O, H<sub>2</sub>O) or other species, or energy
 
| Requires specific conditions to work properly (horizontal homogeneity, absence of strong orography, specific atmospheric conditions)
 
|-
 
! scope="row" | Can measure net primary productivity (NPP), and infer gross primary productivity (GPP) and ecosystem respiration (ER)
 
| Requires fast response sensors and high flow sampling lines
 
|-
 
! scope="row" | It is not disturbing the ecosystem and integrates measurements over large areas, allowing a good link with satellite measurements
 
| It is complex to apply and relatively expensive
 
|}
 
Companies producing
 
  
<div class="tablecaption" id="table41">TABLE 41 PRODUCERS OF DEVICES BASED ON EDDY COVARIANCE TECHNIQUE</div>
+
Special cameras investigating wavelengths different from (or in addition to) the visible ones can give much more information about vegetation status. They are tools of great importance especially in precision agriculture since they allow investigating if there are specific areas where the plants are stressed due, for example, lack of water or the presence of pathogens. These tools work on the principle that plants are living breathing organisms therefore having different temperatures and spectral characteristics from the non-living background. This happens because they absorb light in specific wavelengths (the photosynthetic active radiation window, between 400 and 700 nanometres) and reflect it in various spectral regions (especially in the near infrared above 780 nanometres) according to biophysical properties of the vegetation. Stresses alters such plant responses and are therefore detectable with thermal (in the long-wave spectral domain) and multispectral (in the short-wave spectral domain) imaging, allowing a precise identification of critical situations where it is possible to intervene to improve agricultural practices.
{| class="wikitable"
+
 
! scope="row" | Producer name
+
TABLE 42 STRENGTHS AND LIMITATIONS OF SPECTRAL IMAGING
! scope="row" | Website
+
 
|-
+
TABLE 43 PRODUCERS OF DEVICES FOR SPECTRAL IMAGING
! scope="row" | LI-COR (gas analysers, full eddycovariance systems through link to other companies)
+
 
| https://www.licor.com/env/
+
====3.2.2.1 Proton-transfer-reactionmassspectrometry(PTR-MS)====
|-
 
! scope="row" | Campbell (ultrasonic anemometers,IRGAs)
 
| https://www.campbellsci.com/
 
|-
 
! scope="row" | Metek (ultrasonic anemometers)
 
| http://metek.de/
 
|-
 
! scope="row" | Gill (ultrasonic anemometers)
 
| http://gillinstruments.com/
 
|-
 
! scope="row" | PICARRO (gas analysers)
 
| https://www.picarro.com/
 
|-
 
! scope="row" | Los Gatos Research
 
| http://www.lgrinc.com/
 
|}
 
  
===3.2.2 Spectral imaging===
+
PTR-MS is a technique that uses hydronium ions to transfer protons to any ambient volatile organic compound. VOCs have a higher affinity to hydrogen ions (the protons) compared to water or air and are therefore proton transfer happens only on substances of interest. Charged VOCs are then passed through the mass-spectrometer phase of the technique which allows their identification and quantification on the basis of each VOC spectral peaks.
  
Special cameras investigating wavelengths different from (or in addition to) the visible ones can give much more information about vegetation status. They are tools of great importance especially in precision agriculture since they allow investigating if there are specific areas where the plants are stressed due, for example, lack of water or the presence of pathogens. These tools work on the principle that plants are living breathing organisms therefore having different temperatures and spectral characteristics from the non-living background. This happens because they absorb light in specific wavelengths (the photosynthetic active radiation window, between 400 and 700 nanometres) and reflect it in various spectral regions (especially in the near infrared above 780 nanometres) according to biophysical properties of the vegetation. Stresses alters such plant responses and are therefore detectable with thermal (in the long-wave spectral domain) and multispectral (in the short-wave spectral domain) imaging, allowing a precise identification of critical situations where it is possible to intervene to improve agricultural practices.
+
The technique has been recently enhanced by coupling the proton transfer reaction to a time of flight mass spectrometer (PTR-TOF-MS). This yields a higher resolving power and better duty cycle. All ions are detected at once without having to cycle on different mass-to-charge ratios for detection as it happens in the PTR-MS.
  
<div class="tablecaption" id="table42">TABLE 42 STRENGTHS AND LIMITATIONS OF SPECTRAL IMAGING</div>
+
TABLE 44 STRENGTHS AND LIMITATIONS OF PTR-MS
{| class="wikitable"
+
! scope="row" | Strengths
+
TABLE 45 PRODUCERS OF DEVICES FOR PTR-MS
! scope="row" | Limitations
 
|-
 
! scope="row" | Can detect plant stresses and improve agricultural activities
 
| Not easily generalizable, each situation requires a dedicated campaign and therefore a certain scientific and economic effort.
 
|-
 
! scope="row" | Better agricultural activities translate into greater yield and less environmental impacts
 
|
 
|}
 
  
<div class="tablecaption" id="table43">TABLE 43 PRODUCERS OF DEVICES FOR SPECTRAL IMAGING</div>
+
==3.3 Emerging Technologies: Fluorescence==
{| class="wikitable"
 
! scope="row" | Producer name
 
! scope="row" | Website
 
|-
 
! scope="row" | FLIR
 
| http://www.flir.it/home/
 
|-
 
! scope="row" | TETRACAM
 
| http://www.tetracam.com/
 
|-
 
! scope="row" | Ocean Optics
 
| https://oceanoptics.com/
 
|-
 
! scope="row" | HEADWALL Photonics
 
| http://www.headwallphotonics.com/
 
|-
 
! scope="row" | SPECIM
 
| http://www.specim.fi/
 
|-
 
! scope="row" | ITRES Research
 
| http://www.itres.com/
 
|-
 
|}
 
  
====3.2.2.1 Proton-transfer-reactionmassspectrometry(PTR-MS)====
+
===3.3.1 Fluorescence Measurement of Photosynthesis===
  
PTR-MS is a technique that uses hydronium ions to transfer protons to any ambient volatile organic compound. VOCs have a higher affinity to hydrogen ions (the protons) compared to water or air and are therefore proton transfer happens only on substances of interest. Charged VOCs are then passed through the mass-spectrometer phase of the technique which allows their identification and quantification on the basis of each VOC spectral peaks.
+
Photosynthesis is the key mechanism with which biosphere fixates (“absorbs”) CO2 from the atmosphere. Any change in gross photosynthesis will be reflected on the whole carbon cycle and, therefore, photosynthesis prediction is becoming a priority effort. Photosynthetic rates can also give information about plant growth and ecosystem productivity and therefore feedback mechanisms between vegetation, atmosphere and climate. Photosynthesis measurements are already commercially available for single leaves or very small canopies. It employs mainly two methods of measurements: either measuring on a small scale the CO2 exchange with the atmosphere (mainly produced by LICOR), either measuring the fluorescence emitted by the vegetation in specific wavelength due to the molecular mechanisms involved in the photosynthetic and energy dissipation processes (mainly produced by Walz). The latter method uses LED pulsating a certain frequencies followed by a spectral readout from the plant. This system is manageable at leaf scale, but its active principle (based on an excitation-response mechanism) is not applicable far from the plant canopy. Recently, though, a new ESA mission will launch a satellite, FLEX, in 2022 that will be able to use passive method for quantifying plant fluorescence (e.g SIF, Solar Induced Fluorescence). Plant photosynthesis will therefore enter a whole new scenario in which remote sensing will start playing an important role. The technology employed by such new observation satellite is actually being developed as aircraft payload by the Forschnungszentrum Jülich and the Specim Company, and will be commercially available for ground or aircraft-based biosphere measurements.  
  
The technique has been recently enhanced by coupling the proton transfer reaction to a time of flight mass spectrometer (PTR-TOF-MS). This yields a higher resolving power and better duty cycle. All ions are detected at once without having to cycle on different mass-to-charge ratios for detection as it happens in the PTR-MS.
+
TABLE 46 STRENGTHS AND LIMITATIONS OF FLUORESCENCE MEASUREMENT OF PHOTOSYNTHESIS
  
<div class="tablecaption" id="table44">TABLE 44 STRENGTHS AND LIMITATIONS OF PTR-MS</div>
+
TABLE 47 PRODUCERS OF DEVICES FOR FLUORESCENCE MEASUREMENT OF PHOTOSYNTHESIS
{| class="wikitable"
 
! scope="row" | Strengths
 
! scope="row" | Limitations
 
|-
 
! scope="row" | Real-time
 
| Cannot detect substances with proton affinity lower than H<sub>2</sub>O
 
|-
 
! scope="row" | No sample preparation required
 
|After 10 ppmv of VOCs the concentration response is not linear anymore. Samples can be diluted to overcome this limitation.
 
|-
 
! scope="row" | Can detect very low concentrations
 
|
 
|}
 
  
<div class="tablecaption" id="table45">TABLE 45 PRODUCERS OF DEVICES FOR PTR-MS</div>
+
===3.3.2 Fluorescence Measurements of Microorganisms
{| class="wikitable"
 
! scope="row" | Producer name
 
! scope="row" | Website
 
|-
 
! scope="row" | IONICON
 
| http://www.ionicon.com/information/technology/ptrms
 
|}
 
  
==3.3 Emerging Technologies: Fluorescence==
+
Land Biosphere measurements of microorganisms emitted from the plant canopy generally using a combination of meteorological measurements (such as radiation, wind speed and temperature, either as single-point measurement or profiles) and quantitative microbiological techniques (for more information see Despres et al., 2012 and Carotenuto et al., 2017).
  
===3.3.1 Fluorescence Measurement of Photosynthesis===
+
In the past years, though, a new technology is emerging that would be able to quantify microorganisms in real time. This is done through special aerosol samplers that not only determine physical characteristics of aerosols (such as size and asymmetry) but also response in fluorescence wavelengths related to organic molecules (such as NADH and the amino-acid tryptophan). Each aerosol particle is quickly illuminated (“flashed”) by exciting emitters and appropriate detectors collect the fluorescence response. The combination of such information allows discriminating between inorganic aerosols, bacteria, fungi, etc. measuring the organic fraction that can potentially rise up in the atmosphere and act as biological ice or cloud condensation nuclei.
  
Photosynthesis is the key mechanism with which biosphere fixates (“absorbs”) CO2 from the atmosphere. Any change in gross photosynthesis will be reflected on the whole carbon cycle and, therefore, photosynthesis prediction is becoming a priority effort. Photosynthetic rates can also give information about plant growth and ecosystem productivity and therefore feedback mechanisms between vegetation, atmosphere and climate. Photosynthesis measurements are already commercially available for single leaves or very small canopies. It employs mainly two methods of measurements: either measuring on a small scale the CO2 exchange with the atmosphere (mainly produced by LICOR), either measuring the fluorescence emitted by the vegetation in specific wavelength due to the molecular mechanisms involved in the photosynthetic and energy dissipation processes (mainly produced by Walz). The latter method uses LED pulsating a certain frequencies followed by a spectral readout from the plant. This system is manageable at leaf scale, but its active principle (based on an excitation-response mechanism) is not applicable far from the plant canopy. Recently, though, a new ESA mission will launch a satellite, FLEX, in 2022 that will be able to use passive method for quantifying plant fluorescence (e.g SIF, Solar Induced Fluorescence). Plant photosynthesis will therefore enter a whole new scenario in which remote sensing will start playing an important role. The technology employed by such new observation satellite is actually being developed as aircraft payload by the Forschnungszentrum Jülich and the Specim Company, and will be commercially available for ground or aircraft-based biosphere measurements.  
+
TABLE 48 STRENGTHS AND LIMITATIONS OF FLUORESCENCE MEASUREMENTS OF MICROORGANISMS
 +
 
 +
TABLE 49 STRENGTHS AND LIMITATIONS OF FLUORESCENCE MEASUREMENTS OF MICROORGANISMS
 +
 
 +
==3.4 Market overview==
  
<div class="tablecaption" id="table46">TABLE 46 STRENGTHS AND LIMITATIONS OF FLUORESCENCE MEASUREMENT OF PHOTOSYNTHESIS</div>
+
Agriculture is one of the sectors with largest environmental impact, which is expected to grow even further. The demand for the food is expected to grow 70% during next decades. Providing the food resources is the key to the international social stability, reducing the amounts of produced food is not the optimal solution. Thus the regulatory measures have to be taken to make agricultural sector produce larger amounts of food with less harm to the environment. There are a number of policies and strategies influencing the development of agricultural sector from the point of view of GHG emissions. First of all these are the globally binding agreements such as Kyoto protocol and Paris agreement, which led to the introduction of systems for Emissions quotes trading in the EU, but also such long term strategies as the EU low carbon roadmap, climate and energy policy. Policies and strategies help to undertake climate mitigation activities in the agricultural sector in the short term. For example, Nitrates Directive determines the amount of nitrogen that could be applied to the agricultural soils, while the National Emissions Ceiling Directive (Directive 2001/81/EC), establishes the limit values for ammonia, precursor to N2O. (Allen and Maréchal 2017) Agriculture GHG emissions: determining the potential contribution to the Effort Sharing Regulation. Report prepared for Transport and Environment. Institute for European Environmental Policy, London).
{| class="wikitable"
 
! scope="row" | Strengths
 
! scope="row" | Limitations
 
|-
 
! scope="row" | Passive sensor allowing to survey in real time photosynthesis of large vegetated surface
 
| Still in development and costly
 
|-
 
! scope="row" |
 
| Data retrieval non-straightforward
 
|}
 
  
<div class="tablecaption" id="table47">TABLE 47 PRODUCERS OF DEVICES FOR FLUORESCENCE MEASUREMENT OF PHOTOSYNTHESIS</div>
+
In 2016, European Commission presented the winter package of proposals for clean energy transition in Europe. This package includes a number of updates to the existing regulations, among them are revisions to the Renewable Energy Directive and setting of proposed Governance Regulation (COM 2016 759 final/2). Article 14 of this Regulation requires EU member states to prepare and report the European Commission their long-term emission strategies for the next 50 year period perspective to contribute to the reduction and removals of emissions in the EU. Such strategy shall include the plans for the reductions and removals of emissions in several individual sectors, including agriculture and forestry.
{| class="wikitable"
+
The main policy that directly influences the development of agricultural sector is the common agricultural policy (CAP) of European Union. It was established in 1962 and nowadays includes three core objectives: Viable food production, sustainable management of natural resources and climate action and, finally, balanced territorial development.
! scope="row" | Producer name
+
Agricultural production requires certain amounts of soil, water, sunlight and heat to develop. Availability of these factors have a great influence on the length of growing season, flowering and harvest dates for crops. Assuming that the climate change characterized by the general increase of temperature will continue, the northern countries will be able to enlarge their agricultural sector and cultivate more crops, while southern counties will suffer from extreme heat and will either shift the production to the colder seasons or reduce the total production. Main markets for the sensors are:
! scope="row" | Website
 
|-
 
! scope="row" | Walz (leaf photosynthesis)
 
| http://www.walz.com/
 
|-
 
! scope="row" | SPECIM (SIF passive sensors)
 
| http://www.specim.fi/
 
|}
 
  
===3.3.2 Fluorescence Measurements of Microorganisms===
+
Developing countries, with large population: China, India, Brazil developing countries of Africa. Huge population of these countries requires large amounts of food. For example, China is a world leader in production of pork, sheep, goat and duck meat, while India is the biggest producer of dairy products. Due to the steep economic growth and increasing demand for better life quality by large population, these countries can be considered as large markets for sensors for GHG measurements in the short and medium-period perspective.
  
Land Biosphere measurements of microorganisms emitted from the plant canopy generally using a combination of meteorological measurements (such as radiation, wind speed and temperature, either as single-point measurement or profiles) and quantitative microbiological techniques (for more information see Despres et al., 2012 and Carotenuto et al., 2017).
+
Developing countries with large agricultural potential and large producers of fertilizers: Russia, Ukraine, Belarus, Kazakhstan. These countries have the largest potential of agriculture development, due to the availability of large territories and good soil quality. For example, in 2017 Russia showed large increase in crops production and export. In addition, these countries are large producers and consumers of various fertilizers. Current demand for the sensors for GHG measurements in these countries is doubtful, because the environmental regulation are not very strict. However, they can become large markets for the GHG measurement sensors in the medium and long-term perspective.
  
In the past years, though, a new technology is emerging that would be able to quantify microorganisms in real time. This is done through special aerosol samplers that not only determine physical characteristics of aerosols (such as size and asymmetry) but also response in fluorescence wavelengths related to organic molecules (such as NADH and the amino-acid tryptophan). Each aerosol particle is quickly illuminated (“flashed”) by exciting emitters and appropriate detectors collect the fluorescence response. The combination of such information allows discriminating between inorganic aerosols, bacteria, fungi, etc. measuring the organic fraction that can potentially rise up in the atmosphere and act as biological ice or cloud condensation nuclei.
+
Northern countries with the potential to develop agriculture due to the global warming: Canada, Sweden, Finland, Russia. Due to the increase of average year temperatures, these countries have a great potential to grow the agriculture sector, since new territories will be available for the crop and animal production.
  
<div class="tablecaption" id="table48">TABLE 48 STRENGTHS AND LIMITATIONS OF FLUORESCENCE MEASUREMENTS OF MICROORGANISMS</div>
+
Developed countries, traditionally strong in agriculture, interested in further reduction of GHG emissions: USA, France, Germany, (EU) etc. These traditional players of agricultural market sector are interested in more efficient production of agricultural goods and precise monitoring of resulting emissions due to the very strict environmental regulations. These countries represent today’s largest market for the distribution of sensors for measurements of agriculture produced GHG.
{| class="wikitable"
 
! scope="row" | Strengths
 
! scope="row" | Limitations
 
|-
 
! scope="row" | Real time sensor
 
| High cost
 
|-
 
! scope="row" | Allow discrimination between different types of biological aerosols
 
| Potential interferences on the signals
 
|-
 
! scope="row" | Portable
 
|
 
|-
 
|}
 
  
<div class="tablecaption" id="table49">TABLE 49 STRENGTHS AND LIMITATIONS OF FLUORESCENCE MEASUREMENTS OF MICROORGANISMS</div>
+
=4 Measurement of Ocean parameters=
{| class="wikitable"
 
! scope="row" | Producer name
 
! scope="row" | Website
 
|-
 
! scope="row" | Droplet Measurement Technologies
 
| http://www.dropletmeasurement.com/
 
|-
 
! scope="row" | FLIR
 
| http://www.flir.it/home/
 
|}
 
  
==3.4 Market overview==
+
==4.1 Why measurements of ocean parameters are important==
  
Agriculture is one of the sectors with largest environmental impact, which is expected to grow even further. The demand for the food is expected to grow 70% during next decades. Providing the food resources is the key to the international social stability, reducing the amounts of produced food is not the optimal solution. Thus the regulatory measures have to be taken to make agricultural sector produce larger amounts of food with less harm to the environment. There are a number of policies and strategies influencing the development of agricultural sector from the point of view of GHG emissions. First of all these are the globally binding agreements such as Kyoto protocol and Paris agreement, which led to the introduction of systems for Emissions quotes trading in the EU, but also such long term strategies as the EU low carbon roadmap, climate and energy policy. Policies and strategies help to undertake climate mitigation activities in the agricultural sector in the short term. For example, Nitrates Directive determines the amount of nitrogen that could be applied to the agricultural soils, while the National Emissions Ceiling Directive (Directive 2001/81/EC), establishes the limit values for ammonia, precursor to N2O. (Allen and Maréchal 2017) Agriculture GHG emissions: determining the potential contribution to the Effort Sharing Regulation. Report prepared for Transport and Environment. Institute for European Environmental Policy, London).
+
Global Ocean is a sensitive system, closely interacting with all domains of planet Earth and, thus, serving as an indicator of global processes. Mankind interest has been focused on land and it took a long time before the importance of the ocean investigations for most of the natural sciences disciplines was acknowledged. Nowadays, there are plenty of paradigms based on certain observations. Thus Blue Planet paradigm is based on satellite observations (remote sensing), the “Hidden Planet” is based on seafloor research (deep sea observatory oriented - “Illuminating the Hidden Planet: The Future of Seafloor Observatory Science”<ref>http://www.nap.edu/catalog/9920</ref>), the Source to sink vision of the coastal processes either considers dilution of pollutants or hydrology and sediment transport, the eco-systemic approach of marine life deals with the tremendous marine biodiversity, the Energy buffer vision addresses the global circulation/vorticity and thermodynamic coupling with atmosphere, the Fluid interface to continental plate focuses on active boundaries or continental margin seeping processes and Blue Growth Economy aims at developing sustainable industries.
 +
The marine environment research infrastructure approach brings together several scientific questions from several disciplines with an objective of providing long-term in-situ data. The measurements of marine variables can last from hours to several decades while even longer processes are investigated by cryology (ice cores) or geology (sediment cores). Observations coming mainly from the sea surface and from underwater measurements are by far too scarce. The physical limitations drive the technological challenges: electromagnetic waves and photons hardly propagate through seawater. The imaging and signal transmission under water are generally based on acoustics principles.
  
In 2016, European Commission presented the winter package of proposals for clean energy transition in Europe. This package includes a number of updates to the existing regulations, among them are revisions to the Renewable Energy Directive and setting of proposed Governance Regulation (COM 2016 759 final/2). Article 14 of this Regulation requires EU member states to prepare and report the European Commission their long-term emission strategies for the next 50 year period perspective to contribute to the reduction and removals of emissions in the EU. Such strategy shall include the plans for the reductions and removals of emissions in several individual sectors, including agriculture and forestry.
+
The ocean science community bases the strategy of knowledge acquisition on the junction of modelling and in-situ collecting of “Essential Ocean Variables” (EOV). After the 2009 Ocean OBS<ref>https://www.oceanobs09.net/proceedings/summary/</ref>conference, the post-OceanOBS’09 task team prepared the report called “Integrated Framework for Sustained Ocean Observing” (Lindstrom et al 2009). The focus of this report was to:
The main policy that directly influences the development of agricultural sector is the common agricultural policy (CAP) of European Union. It was established in 1962 and nowadays includes three core objectives: Viable food production, sustainable management of natural resources and climate action and, finally, balanced territorial development.
 
Agricultural production requires certain amounts of soil, water, sunlight and heat to develop. Availability of these factors have a great influence on the length of growing season, flowering and harvest dates for crops. Assuming that the climate change characterized by the general increase of temperature will continue, the northern countries will be able to enlarge their agricultural sector and cultivate more crops, while southern counties will suffer from extreme heat and will either shift the production to the colder seasons or reduce the total production. Main markets for the sensors are:
 
  
Developing countries, with large population: China, India, Brazil developing countries of Africa. Huge population of these countries requires large amounts of food. For example, China is a world leader in production of pork, sheep, goat and duck meat, while India is the biggest producer of dairy products. Due to the steep economic growth and increasing demand for better life quality by large population, these countries can be considered as large markets for sensors for GHG measurements in the short and medium-period perspective.
+
* Use “Essential Ocean Variables” (EOVs) as the common focus
 
+
* Define a system based on requirements
Developing countries with large agricultural potential and large producers of fertilizers: Russia, Ukraine, Belarus, Kazakhstan. These countries have the largest potential of agriculture development, due to the availability of large territories and good soil quality. For example, in 2017 Russia showed large increase in crops production and export. In addition, these countries are large producers and consumers of various fertilizers. Current demand for the sensors for GHG measurements in these countries is doubtful, because the environmental regulation are not very strict. However, they can become large markets for the GHG measurement sensors in the medium and long-term perspective.
 
 
 
Northern countries with the potential to develop agriculture due to the global warming: Canada, Sweden, Finland, Russia. Due to the increase of average year temperatures, these countries have a great potential to grow the agriculture sector, since new territories will be available for the crop and animal production.
 
 
 
Developed countries, traditionally strong in agriculture, interested in further reduction of GHG emissions: USA, France, Germany, (EU) etc. These traditional players of agricultural market sector are interested in more efficient production of agricultural goods and precise monitoring of resulting emissions due to the very strict environmental regulations. These countries represent today’s largest market for the distribution of sensors for measurements of agriculture produced GHG.
 
 
 
=4 Measurement of Ocean parameters=
 
 
 
==4.1 Why measurements of ocean parameters are important==
 
 
 
Global Ocean is a sensitive system, closely interacting with all domains of planet Earth and, thus, serving as an indicator of global processes. Mankind interest has been focused on land and it took a long time before the importance of the ocean investigations for most of the natural sciences disciplines was acknowledged. Nowadays, there are plenty of paradigms based on certain observations. Thus Blue Planet paradigm is based on satellite observations (remote sensing), the “Hidden Planet” is based on seafloor research (deep sea observatory oriented - “Illuminating the Hidden Planet: The Future of Seafloor Observatory Science”<ref>http://www.nap.edu/catalog/9920</ref>), the Source to sink vision of the coastal processes either considers dilution of pollutants or hydrology and sediment transport, the eco-systemic approach of marine life deals with the tremendous marine biodiversity, the Energy buffer vision addresses the global circulation/vorticity and thermodynamic coupling with atmosphere, the Fluid interface to continental plate focuses on active boundaries or continental margin seeping processes and Blue Growth Economy aims at developing sustainable industries.
 
The marine environment research infrastructure approach brings together several scientific questions from several disciplines with an objective of providing long-term in-situ data. The measurements of marine variables can last from hours to several decades while even longer processes are investigated by cryology (ice cores) or geology (sediment cores). Observations coming mainly from the sea surface and from underwater measurements are by far too scarce. The physical limitations drive the technological challenges: electromagnetic waves and photons hardly propagate through seawater. The imaging and signal transmission under water are generally based on acoustics principles.
 
 
 
The ocean science community bases the strategy of knowledge acquisition on the junction of modelling and in-situ collecting of “Essential Ocean Variables” (EOV). After the 2009 Ocean OBS<ref>https://www.oceanobs09.net/proceedings/summary/</ref>conference, the post-OceanOBS’09 task team prepared the report called “Integrated Framework for Sustained Ocean Observing” (Lindstrom et al 2009). The focus of this report was to:
 
 
 
* Use “Essential Ocean Variables” (EOVs) as the common focus
 
* Define a system based on requirements
 
 
* Overview observations, data and information
 
* Overview observations, data and information
 
* Use “Technology Readiness Levels” (TRL) scale, based on assessment of feasibility, capacity, and impact, for each of the system components
 
* Use “Technology Readiness Levels” (TRL) scale, based on assessment of feasibility, capacity, and impact, for each of the system components
Line 1,170: Line 897:
 
The METS methane sensor was presented in 1999, as the first sensor for underwater methane monitoring and detection, using a gas-permeable membrane with tin-oxide (SnO2) semiconductor detection. It is described as being able to detect methane in the concentration range 50 nM–10 μM in its standard version, and up to 2 mM for some versions. It can perform at water depths down to 3500 m and temperatures of 2–40°C. The METS sensor has been widely used for the detection of methane-rich plume signals in the water column overlying cold seep environments or for long-term monitoring.  
 
The METS methane sensor was presented in 1999, as the first sensor for underwater methane monitoring and detection, using a gas-permeable membrane with tin-oxide (SnO2) semiconductor detection. It is described as being able to detect methane in the concentration range 50 nM–10 μM in its standard version, and up to 2 mM for some versions. It can perform at water depths down to 3500 m and temperatures of 2–40°C. The METS sensor has been widely used for the detection of methane-rich plume signals in the water column overlying cold seep environments or for long-term monitoring.  
  
====4.2.2.2 HydroC sensor====
+
====4.2.2.2 HydroC sensor===
  
 
HydroC (Konsberg) is the sensor, comparable to the METS sensor except that the detection principle is based on direct IR absorption spectroscopy in the 3.4-μm region. This detection method does not consume methane, what simplifies calibration and reduces measurement errors in flowing fluid. The system can measure concentrations of methane in the range 30 nM–500 μm with a resolution of 3–30 nM. The T90 of the detector is quoted to be 30 s. The HydroC/CH4 was deployed in 2007 during RV Sonne cruise 190 (27/02/07– 22/03/07) and was able to measure methane plumes (10–50 nM) over the New Zealand continental margin (Contros GmBH, personal communication).
 
HydroC (Konsberg) is the sensor, comparable to the METS sensor except that the detection principle is based on direct IR absorption spectroscopy in the 3.4-μm region. This detection method does not consume methane, what simplifies calibration and reduces measurement errors in flowing fluid. The system can measure concentrations of methane in the range 30 nM–500 μm with a resolution of 3–30 nM. The T90 of the detector is quoted to be 30 s. The HydroC/CH4 was deployed in 2007 during RV Sonne cruise 190 (27/02/07– 22/03/07) and was able to measure methane plumes (10–50 nM) over the New Zealand continental margin (Contros GmBH, personal communication).
Line 1,190: Line 917:
 
Optical sensors operate based on the principle of fluorescence quenching (Tengberg et al. 2006). Nowadays, the Aanderaa optodes 3835 & 4330 are the most used sensors implemented in ARGO floats, gliders and on moorings. Oxygen optodes are based on the oxygen luminescence quenching of a platinum porphyrin complex (fluorescent indicator) that is immobilized in a sensing foil. Optodes show a nonlinear decrease in luminescence decay time with increasing oxygen concentration. The signal can be linearized by means of the Stern–Volmer equation: [O2] = (τ0/τ – 1)/Ksv, where [O2] is oxygen concentration in μmol/L, τ is luminescence decay time, τ0 is the decay time in the absence of [O2], and Ksv is the Stern– Volmer constant (Demas et al. 1999). The advantages of the optical sensors are their excellent long-term stability and high precision. They also appear to be accurate provided they have sufficient time to come into equilibrium with the surrounding temperature and oxygen concentration and provided that their temperature response has been carefully calibrated (possibly by individual sensor factory-calibration plus in-situ calibration check/correction based on concomitant Winkler profile).
 
Optical sensors operate based on the principle of fluorescence quenching (Tengberg et al. 2006). Nowadays, the Aanderaa optodes 3835 & 4330 are the most used sensors implemented in ARGO floats, gliders and on moorings. Oxygen optodes are based on the oxygen luminescence quenching of a platinum porphyrin complex (fluorescent indicator) that is immobilized in a sensing foil. Optodes show a nonlinear decrease in luminescence decay time with increasing oxygen concentration. The signal can be linearized by means of the Stern–Volmer equation: [O2] = (τ0/τ – 1)/Ksv, where [O2] is oxygen concentration in μmol/L, τ is luminescence decay time, τ0 is the decay time in the absence of [O2], and Ksv is the Stern– Volmer constant (Demas et al. 1999). The advantages of the optical sensors are their excellent long-term stability and high precision. They also appear to be accurate provided they have sufficient time to come into equilibrium with the surrounding temperature and oxygen concentration and provided that their temperature response has been carefully calibrated (possibly by individual sensor factory-calibration plus in-situ calibration check/correction based on concomitant Winkler profile).
  
=====4.2.3.2.1 The Aanderaa optode sensors 3830-3835=====
+
=====4.2.3.2.1 TheAanderaaoptodesensors3830-3835=====
  
 
This sensors have a measuring range of 0-500 μM, a resolution of 1 μM and an accuracy of 5 μM as well as an operating depth of up to 6000 m. Due to their small size and power requirements, the first generation of optode sensors (3830/3835) have been also tested on profiling floats (Kortzinger et al. 2005). The first results obtained in 2004 demonstrated that high quality long-term oxygen measurements from ARGO floats are feasible.
 
This sensors have a measuring range of 0-500 μM, a resolution of 1 μM and an accuracy of 5 μM as well as an operating depth of up to 6000 m. Due to their small size and power requirements, the first generation of optode sensors (3830/3835) have been also tested on profiling floats (Kortzinger et al. 2005). The first results obtained in 2004 demonstrated that high quality long-term oxygen measurements from ARGO floats are feasible.
  
<div class="figure" id="figure3">[[File:ENVRIplus D1.1-Fig. 3-The Aanderaa optode sensor on a provor float.png|center|frame|Figure 3: The Aanderaa optode sensor on a provor float]]</div>
+
FIGURE 3 THE AANDERAA OPTODE SENSOR ON A PROVOR FLOAT
  
 
=====4.2.3.2.2 The SBE 63 sensor=====
 
=====4.2.3.2.2 The SBE 63 sensor=====
Line 1,222: Line 949:
 
* range of concentrations 0.1 nM - 2 mM, LOD 0.1 nM (open ocean), 0.1μM (profiling), 1-5 μM coastal/rivers and upwelling.
 
* range of concentrations 0.1 nM - 2 mM, LOD 0.1 nM (open ocean), 0.1μM (profiling), 1-5 μM coastal/rivers and upwelling.
  
===4.2.5 Salinity/density vs salinity/conductivity===
+
===4.2.5 Salinity/density vs salinity/conductivity==
  
 
Salinity is the parameter that characterizes global circulation and local exchanges of water masses. It must be known to understand the spatial significance of a measurement and in many cases to correct the raw data of sensors (sound speed, chemical concentration such as nitrate). Marine sciences in general focus and rely on the assessment of “absolute salinity”.  
 
Salinity is the parameter that characterizes global circulation and local exchanges of water masses. It must be known to understand the spatial significance of a measurement and in many cases to correct the raw data of sensors (sound speed, chemical concentration such as nitrate). Marine sciences in general focus and rely on the assessment of “absolute salinity”.  
Line 1,228: Line 955:
 
The measurements of seawater density does not face the same drawbacks as measurements of conductivity. Density may be measured through refractive index. Such measurement is based on the comparison of the deviation angle of the beam passing through two prisms of different index delimiting a seawater volume. The value of absolute salinity can be directly accessed through these measurements. A sensor called NOSS (nke Marine Electronics Optical Salinity Sensor) has been developed and validated (Le Menn et al. 2011) for the seawater density measurements. It is currently marketed by nke Marine Electronics.
 
The measurements of seawater density does not face the same drawbacks as measurements of conductivity. Density may be measured through refractive index. Such measurement is based on the comparison of the deviation angle of the beam passing through two prisms of different index delimiting a seawater volume. The value of absolute salinity can be directly accessed through these measurements. A sensor called NOSS (nke Marine Electronics Optical Salinity Sensor) has been developed and validated (Le Menn et al. 2011) for the seawater density measurements. It is currently marketed by nke Marine Electronics.
  
<div class="tablecaption" id="table50">TABLE 50 CORE SPECIFICATIONS FOR MEASURING CONDUCTIVITY</div>
+
TABLE 50 CORE SPECIFICATIONS FOR MEASURING CONDUCTIVITY  
{| class="wikitable"
 
|+ CONDUCTIVITY
 
|-
 
! scope="row" | Measurement range
 
| 0 - 7
 
| S/m
 
|-
 
! scope="row" | Accuracy
 
| 0,001
 
| S/m
 
|-
 
! scope="row" | Sensitivity
 
| 0,00005
 
| S/m
 
|}
 
  
 
===4.2.6 Turbidity/Optical Backscattering/Transmissometry===
 
===4.2.6 Turbidity/Optical Backscattering/Transmissometry===
Line 1,252: Line 964:
 
Optical backscatter technique can operate across a variety of wavelengths while the chosen combinations and measurement implementation determines the final measurement result. For example a single wavelength system measuring at 700 nm can quantify suspended particle concentrations within the sizes of 0,2 to 20 µm. Spikes in this signal can indicate larger particles, and the addition of other wavelengths can also expand particle quantification capability. The data obtained from optical backscattering measurements can also be calibrated to various quantities including POC concentration, using samples that are sufficiently specific. The ratio of chlorophyll-A to optical backscatter can also indicate variations in phytoplankton community. Conveniently, optical backscatter across two wavelengths and chlorophyll-a can be measured in a compact and power efficient triplet fluorescence instrument offered by Wetlabs.
 
Optical backscatter technique can operate across a variety of wavelengths while the chosen combinations and measurement implementation determines the final measurement result. For example a single wavelength system measuring at 700 nm can quantify suspended particle concentrations within the sizes of 0,2 to 20 µm. Spikes in this signal can indicate larger particles, and the addition of other wavelengths can also expand particle quantification capability. The data obtained from optical backscattering measurements can also be calibrated to various quantities including POC concentration, using samples that are sufficiently specific. The ratio of chlorophyll-A to optical backscatter can also indicate variations in phytoplankton community. Conveniently, optical backscatter across two wavelengths and chlorophyll-a can be measured in a compact and power efficient triplet fluorescence instrument offered by Wetlabs.
  
<div class="tablecaption" id="table51">TABLE 51 CORE SPECIFICATIONS FOR MEASURING TURBIDITY AND OPTICAL BACKSCATTER</div>
+
TABLE 51 CORE SPECIFICATIONS FOR MEASURING TURBIDITY AND OPTICAL BACKSCATTER
{| class="wikitable"
 
|+ TURBIDITY and OPTICAL BACKSCATTER (OBS)
 
|-
 
! scope="row" | Measurement Range
 
| 0 - 150
 
| NTU
 
|-
 
! scope="row" | Accuracy
 
| 0,1
 
| NTU
 
|-
 
! scope="row" | Sensitivity
 
| 0,02
 
| NTU
 
|}
 
  
 
===4.2.7 Currents===
 
===4.2.7 Currents===
Line 1,276: Line 973:
 
For the instrument to work properly, several parameters have to be defined before the measurement start. Usually the user defines a fixed pressure depending on the depth of the instrument, a fixed salinity value (assuming it is uniform for the column of water that is measured). Internal temperature sensor of the instrument helps to determine correct speed of sound in water. The instruments is also equipped with the tilt sensor and compass.
 
For the instrument to work properly, several parameters have to be defined before the measurement start. Usually the user defines a fixed pressure depending on the depth of the instrument, a fixed salinity value (assuming it is uniform for the column of water that is measured). Internal temperature sensor of the instrument helps to determine correct speed of sound in water. The instruments is also equipped with the tilt sensor and compass.
  
<div class="tablecaption" id="table51">TABLE 52 CORE SPECIFICATIONS FOR MEASURING CURRENTS</div>
+
TABLE 52 CORE SPECIFICATIONS FOR MEASURING CURRENTS
{| class="wikitable"
+
 
|+ CURRENTS
 
|-
 
! scope="row" | Velocity
 
| Accuracy
 
| 1% ±0,5 cm/s
 
| cm/s
 
|-
 
! scope="row" | Direction
 
| Accuracy
 
| ±2
 
| Degrees
 
|-
 
! scope="row" | Velocity
 
| Sensitivity
 
| 0,1
 
| cm/s
 
|-
 
! scope="row" | Direction
 
| Sensitivity
 
| 0,01
 
| Degrees
 
|-
 
|}
 
 
 
 
===4.2.8 Fluorescence/Chlorophyll-A===
 
===4.2.8 Fluorescence/Chlorophyll-A===
  
Line 1,308: Line 981:
 
Several companies sell in situ fluorometer systems that come with biofouling protection. There are also FRRF systems that can be fitted to observatories and autonomous systems. In the past five years there have been many long term deployments of fluorimeter systems that have provided useful and sensible data despite potential biofouling or other calibration issues. Like for the most other sensors, pre- and post- deployment in situ calibration measurements is the best way to correct the drift. Moreover, if the intent is to convert the fluorescence values to chlorophyll-A or other specific values, it is advised to collect size fractionated algal pigment samples for calibration purposes. Wet Labs ECO Triplet, or TriOS microFlu, nanoFlu, matrixFlu VIS; TurnerDesigns Cyclops and Chelsea AquaTracka III are examples of widely used systems.  
 
Several companies sell in situ fluorometer systems that come with biofouling protection. There are also FRRF systems that can be fitted to observatories and autonomous systems. In the past five years there have been many long term deployments of fluorimeter systems that have provided useful and sensible data despite potential biofouling or other calibration issues. Like for the most other sensors, pre- and post- deployment in situ calibration measurements is the best way to correct the drift. Moreover, if the intent is to convert the fluorescence values to chlorophyll-A or other specific values, it is advised to collect size fractionated algal pigment samples for calibration purposes. Wet Labs ECO Triplet, or TriOS microFlu, nanoFlu, matrixFlu VIS; TurnerDesigns Cyclops and Chelsea AquaTracka III are examples of widely used systems.  
  
<div class="figure" id="figure4">[[File:ENVRIplus D1.1-Fig. 4-TRIOS fluorometers equipped with Ifremer antifouling devices.png|center|frame|TRIOS fluorometers equipped with Ifremer antifouling devices]]</div>
+
FIGURE 4 TRIOS FLUOROMETERS EQUIPPED WITH IFREMER ANTIFOULING DEVICES
 
 
<div class="tablecaption" id="table53">TABLE 53 CORE SPECIFICATIONS FOR MEASURING FLUORESCENCE</div>
 
{| class="wikitable"
 
|+ FLUORESCENCE / Chlorophyll-Α
 
|-
 
! scope="row" | Measurement Range
 
| 0 - 125
 
| μg/l
 
|-
 
! scope="row" | Sensitivity
 
| 0,02
 
| μg/l
 
|}
 
  
 +
TABLE 53 CORE SPECIFICATIONS FOR MEASURING FLUORESCENCE
 +
 
===4.2.9 Underwater sound===
 
===4.2.9 Underwater sound===
  
Line 1,330: Line 992:
 
Devices called hydrophones are widely used to track the underwater sounds. Hydrophones convert sound in water into electrical signals that can be amplified, recorded, played back over loudspeakers, and used to measure the characteristics of the sound. Most hydrophones are made from a piezoelectric material. Under the pressure of a sound wave, the piezoelectric element flexes and produces electrical signals. Some hydrophones, called omnidirectional hydrophones, record sounds from all directions with equal sensitivity. Other hydrophones, called directional hydrophones, have a higher sensitivity to signals from a particular direction. Directional receivers are most often constructed using a number of omnidirectional hydrophones combined in an array. Directional hydrophones are typically used in systems constructed for locating and tracking objects. Hydrophones are specially designed for underwater use. They are normally encased in rubber or polyurethane to provide protection from seawater. They can be mounted in several different ways, such as attached to a boat, towed, or placed in a fixed position underwater.
 
Devices called hydrophones are widely used to track the underwater sounds. Hydrophones convert sound in water into electrical signals that can be amplified, recorded, played back over loudspeakers, and used to measure the characteristics of the sound. Most hydrophones are made from a piezoelectric material. Under the pressure of a sound wave, the piezoelectric element flexes and produces electrical signals. Some hydrophones, called omnidirectional hydrophones, record sounds from all directions with equal sensitivity. Other hydrophones, called directional hydrophones, have a higher sensitivity to signals from a particular direction. Directional receivers are most often constructed using a number of omnidirectional hydrophones combined in an array. Directional hydrophones are typically used in systems constructed for locating and tracking objects. Hydrophones are specially designed for underwater use. They are normally encased in rubber or polyurethane to provide protection from seawater. They can be mounted in several different ways, such as attached to a boat, towed, or placed in a fixed position underwater.
  
<div class="tablecaption" id="table54">TABLE 54 CORE SPECIFICATIONS FOR MEASURING PASSIVE ACOUSTICS (GEOLOGY SPECIFIC)</div>
+
TABLE 54 CORE SPECIFICATIONS FOR MEASURING PASSIVE ACOUSTICS (GEOLOGY SPECIFIC)
{| class="wikitable"
 
|+ PASSIVE ACOUSTICS (Geology specific)
 
|-
 
! scope="row" | Measurement Range
 
| 0,1 – 100
 
| Hz
 
|-
 
! scope="row" | Accuracy
 
| 1
 
| V/μPa
 
|-
 
! scope="row" | Sensitivity
 
| -190
 
| dB (re 1V/μPa)
 
|}
 
 
 
  
<div class="tablecaption" id="table55">TABLE 55 CORE SPECIFICATIONS FOR MEASURING PASSIVE ACOUSTICS (OCEAN CIRCULATION SPECIFIC)</div>
+
TABLE 55 CORE SPECIFICATIONS FOR MEASURING PASSIVE ACOUSTICS (OCEAN CIRCULATION
{| class="wikitable"
 
|+ PASSIVE ACOUSTICS (Ocean circulation specific)
 
|-
 
! scope="row" | Measurement Range
 
| 20 – 200.000
 
| Hz
 
|-
 
! scope="row" | Accuracy
 
| 1
 
| V/μPa
 
|-
 
! scope="row" | Sensitivity
 
| -190
 
| dB (re 1V/μPa)
 
|}
 
  
 
====4.2.10 Imagery of microorganisms and habitat====
 
====4.2.10 Imagery of microorganisms and habitat====
Line 1,372: Line 1,003:
  
 
The analysis of underwater imagery imposes a series of unique challenges, which need to be tackled by the IT community in collaboration with biologists and ocean scientists. Among the challenges are image enhancement, scene understanding, classification, detection, segmentation; detection and monitoring of marine life, form tracking, automatic video annotation and summarization, context-aware machine learning and image understanding, image compression.
 
The analysis of underwater imagery imposes a series of unique challenges, which need to be tackled by the IT community in collaboration with biologists and ocean scientists. Among the challenges are image enhancement, scene understanding, classification, detection, segmentation; detection and monitoring of marine life, form tracking, automatic video annotation and summarization, context-aware machine learning and image understanding, image compression.
 
+
 
<div class="tablecaption" id="table56">TABLE 56 CORE SPECIFICATIONS OF EMSO FOR RECORDING HD VIDEO AND STILL IMAGES</div>
+
TABLE 56 CORE SPECIFICATIONS OF EMSO FOR RECORDING HD VIDEO AND STILL IMAGES
{| class="wikitable"
+
 
|+ High Definition video and Still imaging Specifications
+
====4.2.10.1 The Imaging FlowCytoBot (IFCB) (McLane Research Laboratories)====
|-
 
! scope="row" | Resolution
 
| 4240×2824
 
| pixels
 
|-
 
! scope="row" | Minimum video capture speed
 
| 7
 
| Frames per second
 
|-
 
! scope="row" | Sensitivity
 
| Minimum 46%
 
| QE
 
|-
 
! scope="row" | Sensor type
 
| CCD + CMOS
 
|
 
|-
 
! scope="row" | Sensor size
 
| 1
 
| inches
 
|-
 
! scope="row" | Output protocol
 
| TCP/IP, USB3
 
|
 
|-
 
! scope="row" | Sensitivity to IR light
 
| 850 -900
 
| Nano metres
 
|}
 
 
 
====4.2.10.1 The Imaging FlowCytoBot (IFCB) (McLane Research Laboratories)====
 
  
 
IFCB is an in-situ automated submersible imaging flow cytometer that generates high resolution (1380x1034 pixels) images of suspended particles in-flow, in the size range <10 to 150 μm (such as diatoms and dinoflagellates). The instrument continuously samples at a rate of 15 ml seawater per hour, and, depending on the target population, can generate up to 30,000 high resolution images per hour. IFCB uses a combination of flow cytometry and video technology. Laser-induced fluorescence and light scattering from individual particles are measured and used to trigger targeted image acquisition. The optical and image data is then transmitted to the computer in real time, through an Ethernet link. Collected images are continuously monitored and processed externally by the specific automated image classification software. For each imaged particle, approximately 200 different parameters are extracted. Images can be automatically classified to the genus or even species level with demonstrated accuracy comparable to that of human experts (Olson and Sosik 2007).
 
IFCB is an in-situ automated submersible imaging flow cytometer that generates high resolution (1380x1034 pixels) images of suspended particles in-flow, in the size range <10 to 150 μm (such as diatoms and dinoflagellates). The instrument continuously samples at a rate of 15 ml seawater per hour, and, depending on the target population, can generate up to 30,000 high resolution images per hour. IFCB uses a combination of flow cytometry and video technology. Laser-induced fluorescence and light scattering from individual particles are measured and used to trigger targeted image acquisition. The optical and image data is then transmitted to the computer in real time, through an Ethernet link. Collected images are continuously monitored and processed externally by the specific automated image classification software. For each imaged particle, approximately 200 different parameters are extracted. Images can be automatically classified to the genus or even species level with demonstrated accuracy comparable to that of human experts (Olson and Sosik 2007).
Line 1,416: Line 1,016:
 
====4.2.10.3 The FastCAM prototype (IFREMER - LDCM)====
 
====4.2.10.3 The FastCAM prototype (IFREMER - LDCM)====
  
This system is based on a high resolution (2 Megapixels) and high speed camera allowing the acquisition of 340 frames per second. It digitizes 10 mL of sample with a 10 times magnification within only 15 min (which is not possible with the first generation of FlowCAM devices). Comparison of grayscale images with those obtained with the first generation of FlowCAM showed that this new system analyses samples much faster and provides high image quality. A LED, driven by a control box emits light pulses of 5 μs duration. Light is injected into a large core diameter (1 mm) optical fiber to homogenize the beam. Upon the exit from the optical fiber, light illuminates the flow cell. A 10X magnification microscope objective associated with a tube lens images the organisms that circulate in the flow cell. The frame grabbing is synchronized with the LED light emission. A pixel of the image corresponds to 0.5 μm. The images are saved on the PC in real time thanks to a fast hard drive. For the image acquisition, a specific software is developed in Visual Basic 12. A second software developed in C language is used for image processing. Thanks to the «Matrox MIL 10» library, nearly 50 parameters are computed based on each image. These parameters then are used to classify images by applying existing classification tools, like «Plankton Identifier» (Delphi and Tanagra environments) or «ZooImage» (R environment)
+
This system is based on a high resolution (2 Megapixels) and high speed camera allowing the acquisition of 340 frames per second. It digitizes 10 mL of sample with a 10 times magnification within only 15 min (which is not possible with the first generation of FlowCAM devices). Comparison of grayscale images with those obtained with the first generation of FlowCAM showed that this new system analyses samples much faster and provides high image quality. A LED, driven by a control box emits light pulses of 5 μs duration. Light is injected into a large core diameter (1 mm) optical fiber to homogenize the beam. Upon the exit from the optical fiber, light illuminates the flow cell. A 10X magnification microscope objective associated with a tube lens images the organisms that circulate in the flow cell. The frame grabbing is synchronized with the LED light emission. A pixel of the image corresponds to 0.5 μm. The images are saved on the PC in real time thanks to a fast hard drive. For the image acquisition, a specific software is developed in Visual Basic 12. A second software developed in C language is used for image processing. Thanks to the «Matrox MIL 10» library, nearly 50 parameters are computed based on each image. These parameters then are used to classify images by applying existing classification tools, like «Plankton Identifier» (Delphi and Tanagra environments) or «ZooImage» (R environment)
  
 
====4.2.10.4 Underwater Vision Profiler UVP5 (Hydroptic)====
 
====4.2.10.4 Underwater Vision Profiler UVP5 (Hydroptic)====
Line 1,442: Line 1,042:
 
Oceans environmental monitoring and seafloor exploitation needs in situ sensors and optical devices (cameras, lights) in various locations and on various carriers in order to initiate and to calibrate environmental models or to perform the supervision of underwater industrial processes. To be economically operational, these systems must be equipped with a biofouling protection of sensors and optical devices used in situ. Indeed, biofouling can modify the transducing interfaces of the sensors and cause unacceptable bias on the measurements performed by the in situ monitoring system in less than 15 days. In the same way biofouling can decrease the optical properties of windows and thus alter the lighting and the quality of the images recorded by the cameras.
 
Oceans environmental monitoring and seafloor exploitation needs in situ sensors and optical devices (cameras, lights) in various locations and on various carriers in order to initiate and to calibrate environmental models or to perform the supervision of underwater industrial processes. To be economically operational, these systems must be equipped with a biofouling protection of sensors and optical devices used in situ. Indeed, biofouling can modify the transducing interfaces of the sensors and cause unacceptable bias on the measurements performed by the in situ monitoring system in less than 15 days. In the same way biofouling can decrease the optical properties of windows and thus alter the lighting and the quality of the images recorded by the cameras.
  
<div class="figure" id="figure5">[[File:ENVRIplus D1.1-Fig. 5-Fouling on the sensors is the main constrains for in situ ocean autonomous measurements.png|center|frame|Figure 5: Fouling on the sensors is the main constraint for in situ ocean autonomous measurements]]</div>
+
FIGURE 5 FOULING ON THE SENSORS IS THE MAIN CONSTRAINT FOR IN SITU OCEAN AUTONOMOUS MEASUREMENTS
  
 
It is acknowledged that a coastal monitoring system must be able to run without maintenance for 3 months in order for the system to be economically acceptable. For deep-sea observatories, actual maintenance interval for the Canadian Venus system is 6 months. ESONET, the European network of excellence for deep-sea observatories defines maintenance interval recommendation from 12 up to 36 months.
 
It is acknowledged that a coastal monitoring system must be able to run without maintenance for 3 months in order for the system to be economically acceptable. For deep-sea observatories, actual maintenance interval for the Canadian Venus system is 6 months. ESONET, the European network of excellence for deep-sea observatories defines maintenance interval recommendation from 12 up to 36 months.
Line 1,451: Line 1,051:
 
Platform innovation is one of the drivers of increasing capabilities of marine systems. It is a structuring point for the constitution of several RIs (EUROARGO - profiling floats, GROOM - gliders, EMSO - sea floor + water column fixed point observatories, EuroFLEETS - oceanographic vessels). Each RI needs to mobilize the providers to cope with its own specifications and at the same time to benefit from inter RI cooperation. In this respect, manufacturers of sensors have to adapt to niche markets with high commercial/manufacturing cost ratio. That is why there is a market tendency for the instruments to include several sensors (multiprobe instruments since the 90s, EMSO Generic Instrumentation Module in 2017 EGIM).
 
Platform innovation is one of the drivers of increasing capabilities of marine systems. It is a structuring point for the constitution of several RIs (EUROARGO - profiling floats, GROOM - gliders, EMSO - sea floor + water column fixed point observatories, EuroFLEETS - oceanographic vessels). Each RI needs to mobilize the providers to cope with its own specifications and at the same time to benefit from inter RI cooperation. In this respect, manufacturers of sensors have to adapt to niche markets with high commercial/manufacturing cost ratio. That is why there is a market tendency for the instruments to include several sensors (multiprobe instruments since the 90s, EMSO Generic Instrumentation Module in 2017 EGIM).
  
<div class="figure" id="figure6">[[File:ENVRIplus D1.1-Fig. 6-Multiparameter system for sea measurements.png|center|frame|Multiparameter system for sea measurements]]</div>
+
FIGURE 6 MULTIPARAMETER SYSTEM FOR SEA MEASUREMENTS
  
 
AUVs and Gliders (marine drones) use the aircraft concept of “pay load” to offer an interface to any sensor of the client. Research Infrastructures need a careful metrology approach (WP2 ENVRIPLUS) and an easy plug and play sensor interface policy (see WP1 Task 4 in ENVRIPLUS) to deal with this industrial structuration.
 
AUVs and Gliders (marine drones) use the aircraft concept of “pay load” to offer an interface to any sensor of the client. Research Infrastructures need a careful metrology approach (WP2 ENVRIPLUS) and an easy plug and play sensor interface policy (see WP1 Task 4 in ENVRIPLUS) to deal with this industrial structuration.
Line 1,479: Line 1,079:
 
The energy constraint and the volume of data are limitations for long time monitoring. These limitations are addressed by implementing duty cycles, data compression and tentative in-situ data treatment. The Research Infrastructures such as JERICO, GROOM and EMSO are leading actors in implementing new generations of hydrophones and hydrophone interfaces to monitor both noise and marine mammal sounds.
 
The energy constraint and the volume of data are limitations for long time monitoring. These limitations are addressed by implementing duty cycles, data compression and tentative in-situ data treatment. The Research Infrastructures such as JERICO, GROOM and EMSO are leading actors in implementing new generations of hydrophones and hydrophone interfaces to monitor both noise and marine mammal sounds.
  
<div class="tablecaption" id="table57">TABLE 57 PROPOSED HYDROPHONE REQUIREMENTS FOR NOISE AND BIOACOUSTICS IN THE OPEN-OCEAN – FOR FIXO3/EMSO – ERIC DELORY – PLOCAN</div>
+
TABLE 57 PROPOSED HYDROPHONE REQUIREMENTS FOR NOISE AND BIOACOUSTICS IN THE OPEN-OCEAN – FOR FIXO3/EMSO – ERIC DELORY – PLOCAN
{| class="wikitable"
 
! scope="col" | Resolution
 
! scope="col" | Dynamic Range (DR)
 
! scope="col" | Directivity
 
! scope="col" | Accuracy
 
! scope="col" | Sampling frequency
 
! scope="col" | Special requirements
 
! scope="col" | Other1
 
! scope="col" | Other2
 
|-
 
| 16 to 24 bits, with different gains to fit DR
 
| <SS0; 50 to 180dB re 1μPa
 
| Omni-Directional
 
| +/-3dB
 
| 100kSps
 
|  Embedded noise and bioacoustics statistics
 
| Store on detection, Solidstate storage
 
| Low power for standalone systems<br />*ESONET Label
 
|}
 
  
 
====4.4.2.2 Active acoustics====
 
====4.4.2.2 Active acoustics====
Line 1,623: Line 1,204:
 
UAVs play an important role in gas sensing, especially in the remote areas or areas with limited accessibility. For example, drones are widely used to perform measurements of volcanic gases. Thus, McGonigle et al. (2008) carried out measurements of volcanic gases at la Fossa volcano crater in Italy. They used the UAV helicopter capable of 12 minutes flight time and equipped with the ultraviolet and infrared spectrometers for SO2 and CO2 measurements. Khan et al. 2012 developed a greenhouse gas analyser for the installation on the helicopter UAV, using a vertical cavity surface emitting laser (VCSEL) for these purposes. Watai et al. (2005) mounted NDIR sensing system on UAV to monitor atmospheric CO2. Authors designed economic and accurate gas sensor and performed several flight tests with the payload of 3.5 kg and operation time of no longer than 1 hour. While WSNs are usually equipped with MOX sensors as was discussed above, UAV mostly apply optical sensing devices. Malaver, Motta et al. (2015) performed analysis of applications of both MOX and optical devices to integrate both sensing technologies at both platforms and reduce the costs. The table presented in this study is shown below.
 
UAVs play an important role in gas sensing, especially in the remote areas or areas with limited accessibility. For example, drones are widely used to perform measurements of volcanic gases. Thus, McGonigle et al. (2008) carried out measurements of volcanic gases at la Fossa volcano crater in Italy. They used the UAV helicopter capable of 12 minutes flight time and equipped with the ultraviolet and infrared spectrometers for SO2 and CO2 measurements. Khan et al. 2012 developed a greenhouse gas analyser for the installation on the helicopter UAV, using a vertical cavity surface emitting laser (VCSEL) for these purposes. Watai et al. (2005) mounted NDIR sensing system on UAV to monitor atmospheric CO2. Authors designed economic and accurate gas sensor and performed several flight tests with the payload of 3.5 kg and operation time of no longer than 1 hour. While WSNs are usually equipped with MOX sensors as was discussed above, UAV mostly apply optical sensing devices. Malaver, Motta et al. (2015) performed analysis of applications of both MOX and optical devices to integrate both sensing technologies at both platforms and reduce the costs. The table presented in this study is shown below.
  
<div class="tablecaption" id="table58">TABLE 58 ADVANTAGES AND DISADVANTAGES OF MOX AND OPTICAL SENSORS FOR GHG MEASUREMENTS ACCORDING TO MALAVER, MOTTA ET AL. (2015)</div>
+
TABLE 58 ADVANTAGES AND DISADVANTAGES OF MOX AND OPTICAL SENSORS FOR GHG MEASUREMENTS ACCORDING TO MALAVER, MOTTA ET AL. (2015)
{| class="wikitable"
 
! rowspan="2" scope="col" | Category
 
! colspan="2" scope="col" | MOX sensors
 
! colspan="2" scope="col" | Optical Sensing Techniques
 
|-
 
| ''Advantages''
 
| ''Disadvantages''
 
| ''Advantages''
 
| ''Disadvantages''
 
|-
 
! scope="row" | Aerial missions
 
| Low energy consumption and light weight
 
| Slow sensor response hinder aerial applications
 
| Tested and proved
 
| Energy consumption and weight may limit flight endurance
 
|-
 
! scope="row" | Ground missions
 
| Tested and proved
 
| Cross reference to different gases and sensitive to humidity
 
| High sampling frequency, high specificity to target gas
 
| No data/sensor is too expensive to be left unattended
 
|-
 
! scope="row" | Continuous release mission
 
| Low energy consumption and light weight, covers wide range of gasses
 
| No data
 
|  High sampling frequency, high specificity to target gas
 
| Energy consumption and weight may limit flight endurance
 
|-
 
! scope="row" | Instantaneous release
 
| Low energy consumption and light weight, covers wide range of gasses
 
| Low sensor response time
 
| High sampling frequency, high specificity to target gas
 
| Energy consumption and weight may limit flight endurance
 
|-
 
! scope="row" | Computational resources
 
| Few output variables. Some variables remain over large range of gases
 
| No data
 
|  No data
 
|  The number of output variables to measure depends on the optical technique and target gas
 
|-
 
! scope="row" | Resolution
 
| Regular resistive sensors achieve ppm gases
 
| Few sensors achieve ppb resolution
 
| Several techniques achieve ppm and ppb resolution
 
|  No data
 
|-
 
! scope="row" | Cost position in market cost
 
| Low
 
| None
 
| Low for NDIR modules
 
| Medium too high for complex systems
 
|}
 
  
 
UAVs or drones are relatively new measurement platforms that have been used in most of the countries with strong climate research programs. Their great advantage is that they can be used in the conditions where presence of human is not desirable or not possible. These platforms are represented by the machines of diverse constructions and capabilities. Based on the ability to perform the measurements, UAV can be divided into following groups:
 
UAVs or drones are relatively new measurement platforms that have been used in most of the countries with strong climate research programs. Their great advantage is that they can be used in the conditions where presence of human is not desirable or not possible. These platforms are represented by the machines of diverse constructions and capabilities. Based on the ability to perform the measurements, UAV can be divided into following groups:
Line 1,687: Line 1,216:
 
Most of UAV systems find their application in the projects of the economically developed countries. However, these countries are not responsible for global pollution in the same extent as many developing countries, where people lack to take care of the environment due to the constant fight for their wellbeing. In these countries, the health of population is often under strike due to decreasing quality of water and air resources. Cost-effective drones can be used in these countries to sample and monitor water quality, composition of atmosphere and climate patterns.
 
Most of UAV systems find their application in the projects of the economically developed countries. However, these countries are not responsible for global pollution in the same extent as many developing countries, where people lack to take care of the environment due to the constant fight for their wellbeing. In these countries, the health of population is often under strike due to decreasing quality of water and air resources. Cost-effective drones can be used in these countries to sample and monitor water quality, composition of atmosphere and climate patterns.
  
<div class="tablecaption" id="table59">TABLE 59 STRENGTHS AND LIMITATIONS OF UAVS</div>
+
TABLE 59 STRENGTHS AND LIMITATIONS OF UAVS
{| class="wikitable"
+
 
! scope="row" | Strengths
+
==6.3 Systems for biosphere measurements==
! scope="row" | Limitations
+
 
|-
 
! scope="row" | Eco-friendly if battery powered
 
| Special person required for navigation
 
|-
 
! scope="row" | Silent, not disturbing nature
 
| Special person required for the interpretation of the results
 
|-
 
! scope="row" | Cheap versions available
 
| Agreed air path is required
 
|-
 
! scope="row" | Can fly in remote areas
 
| Unmanned technology is taken as a threat
 
|-
 
! scope="row" | Can collect results on routine basis for a long time
 
| Can be hacked
 
|}
 
 
 
==6.3 Systems for biosphere measurements==
 
 
 
 
Most of the drones employed in biosphere sciences are similar to the UAVs used in atmospheric applications. Generally rotary drones (e.g.: hexacopters, octocopters, etcetera) are used, since they have a high stability and are able to stay fixed at certain positions and altitudes in order to perform measurements. Payloads that are used in biosphere drone measurements are generally related to the assessment of vegetation status (i.e.: stresses and in homogeneities) or the amount of total biomass. For the first assessment a combination of thermal, RGB and hyperspectral cameras are used; while for the latter techniques such as Light Detection and Ranging (LIDAR) are used.’
 
Most of the drones employed in biosphere sciences are similar to the UAVs used in atmospheric applications. Generally rotary drones (e.g.: hexacopters, octocopters, etcetera) are used, since they have a high stability and are able to stay fixed at certain positions and altitudes in order to perform measurements. Payloads that are used in biosphere drone measurements are generally related to the assessment of vegetation status (i.e.: stresses and in homogeneities) or the amount of total biomass. For the first assessment a combination of thermal, RGB and hyperspectral cameras are used; while for the latter techniques such as Light Detection and Ranging (LIDAR) are used.’
  
Line 1,718: Line 1,228:
 
Underwater Unmanned Autonomous Vehicles (gliders and other UAVs) are commonly used by oceanographers for research and monitoring of the physical and biogeochemical characteristics of the first 1000m of the ocean. The recently created GOOS program called “OceanGliders” (current web domain is http://www.ego-network.org) is gathering the major part of the worldwide gliders fleet and focuses its activity on the sustainable measurements of five Essential Ocean Variables (EOVs): temperature, salinity, chlorophyll a, oxygen and Coloured Dissolved Organic Matter (CDOM). Unless only these parameters are part of the network, many other sensors have been developed, integrated, tested and operationally deployed on AUVs such as passive acoustics, ADCP (current sensor), turbulence, hydrocarbonic sensor, nutrients, pH etc. Currently these sensors are not integrated in the network mainly for harmonized data management reasons but also because the technology is sporadically used by the community. The increasing capacities of gliders (depth, endurance and payload) and the relatively low cost of the technology, make it a very interesting tool for marine and maritime industries. Ocean gliders naturally complement existing elements of the GOOS with their utility on the continental slopes, ability to complete repeat surveys and resolve mesoscale oceanographic features such as fronts.
 
Underwater Unmanned Autonomous Vehicles (gliders and other UAVs) are commonly used by oceanographers for research and monitoring of the physical and biogeochemical characteristics of the first 1000m of the ocean. The recently created GOOS program called “OceanGliders” (current web domain is http://www.ego-network.org) is gathering the major part of the worldwide gliders fleet and focuses its activity on the sustainable measurements of five Essential Ocean Variables (EOVs): temperature, salinity, chlorophyll a, oxygen and Coloured Dissolved Organic Matter (CDOM). Unless only these parameters are part of the network, many other sensors have been developed, integrated, tested and operationally deployed on AUVs such as passive acoustics, ADCP (current sensor), turbulence, hydrocarbonic sensor, nutrients, pH etc. Currently these sensors are not integrated in the network mainly for harmonized data management reasons but also because the technology is sporadically used by the community. The increasing capacities of gliders (depth, endurance and payload) and the relatively low cost of the technology, make it a very interesting tool for marine and maritime industries. Ocean gliders naturally complement existing elements of the GOOS with their utility on the continental slopes, ability to complete repeat surveys and resolve mesoscale oceanographic features such as fronts.
  
<div class="figure" id="figure7"><gallery>
+
FIGURE 7 DRONES FOR UNDERWATER MEASUREMENTS: (A) SEA EXPLORER, (B) SEAGLIDER
File:ENVRIplus D1.1-Fig. 7A-Drones for underwater measurements, (A) Sea explorer, (B) Seaglider.png|(A) Sea explorer
 
File:ENVRIplus D1.1-Fig. 7B-Drones for underwater measurements, (A) Sea explorer, (B) Seaglider.png|(B) Seaglider]]
 
</gallery>
 
 
 
Figure 7: Drones for underwater measurements</div>
 
  
 
The European Glider Network is composed of about 100 platforms that are deployed in the Atlantic, Mediterranean Sea and Baltic Sea. It is important to precise that some of the European gliders are also deployed in non-European region for specific research purposes. The European Glider Network will certainly keep growing as many “new” laboratories are currently purchasing platforms (Ireland and Sweden for example).
 
The European Glider Network is composed of about 100 platforms that are deployed in the Atlantic, Mediterranean Sea and Baltic Sea. It is important to precise that some of the European gliders are also deployed in non-European region for specific research purposes. The European Glider Network will certainly keep growing as many “new” laboratories are currently purchasing platforms (Ireland and Sweden for example).
Line 1,760: Line 1,265:
 
As known from the ENVRIplus community, technologies for the energy supply are represented by solar cells (63%), wind and hydroturbines (4% each) and other solutions (29%). Thus, solar panels is by far the most used technology, used to provide energy for isolated sites. Figure 8 shows the diagram of usage of various power supply solutions for isolated scientific stations within ENVRIplus network.  
 
As known from the ENVRIplus community, technologies for the energy supply are represented by solar cells (63%), wind and hydroturbines (4% each) and other solutions (29%). Thus, solar panels is by far the most used technology, used to provide energy for isolated sites. Figure 8 shows the diagram of usage of various power supply solutions for isolated scientific stations within ENVRIplus network.  
  
<div class="figure" id="figure8">[[File:ENVRIplus D1.1-Fig. 8-Power supply systems. ENVRIplus WP 3.1 'Energy report', 2017.png|center|frame|Figure 8: Power supply systems. ENVRIplus WP 3.1 "Energy report" (2017)]]</div>
+
FIGURE 8 POWER SUPPLY SYSTEMS. ENVRIPLUS WP 3.1 "ENERGY REPORT", 2017
  
 
===7.2.1 Solar panels===
 
===7.2.1 Solar panels===
Line 1,787: Line 1,292:
 
Lead acid batteries, VRLA (Valve Regulated Lead Acid), with gel or AGM are, by far, the most used ones through the ENVRI RI community. They are especially widely used for terrestrial measurements. Figure 9 shows the distribution (%) among battery technologies used for the measurements at 27 scientific stations within ENVRI network. As can be seen, 69% are taken by the lead batteries and 23% by lithium batteries, while alkaline and other technologies represent 4% each.  
 
Lead acid batteries, VRLA (Valve Regulated Lead Acid), with gel or AGM are, by far, the most used ones through the ENVRI RI community. They are especially widely used for terrestrial measurements. Figure 9 shows the distribution (%) among battery technologies used for the measurements at 27 scientific stations within ENVRI network. As can be seen, 69% are taken by the lead batteries and 23% by lithium batteries, while alkaline and other technologies represent 4% each.  
  
<div class="figure" id="figure9">[[File:ENVRIplus D1.1-Fig. 9-Power storage systems. ENVRIplus WP 3.1 'Energy report', 2017.png|center|frame|Figure 9: Power storage systems. ENVRIplus WP 3.1 "Energy report" (2017)]]</div>
+
FIGURE 9 POWER STORAGE SYSTEMS. ENVRI+ WP3.1 "ENERGY REPORT", 2017
  
 
The biggest challenges of the batteries are that they need to face and run under very low temperatures, down to -20°C, and sometimes down to -40° to 50°C and be as light as possible. The weight of batteries is especially important when one considers their installation on drones. Light weight of the batteries allows larger amount of scientific equipment to be installed and, thus, is more desirable. Lithium batteries are currently the ones with the highest energy-to-weight ratio. That is why they are widely used for the environmental measurements within oceanic domain, and for the installation on drones. In the table 60 we summarize the companies providing technologies for the power supply and specify the type/ model of technology.  
 
The biggest challenges of the batteries are that they need to face and run under very low temperatures, down to -20°C, and sometimes down to -40° to 50°C and be as light as possible. The weight of batteries is especially important when one considers their installation on drones. Light weight of the batteries allows larger amount of scientific equipment to be installed and, thus, is more desirable. Lithium batteries are currently the ones with the highest energy-to-weight ratio. That is why they are widely used for the environmental measurements within oceanic domain, and for the installation on drones. In the table 60 we summarize the companies providing technologies for the power supply and specify the type/ model of technology.  
  
<div class="tablecaption" id="table60">TABLE 60 COMPANIES PRODUCING TECHNOLOGICAL SOLUTIONS</div>
+
TABLE 60 COMPANIES PRODUCING TECHNOLOGICAL SOLUTIONS
{| class="wikitable"
 
! scope="col" | Technology
 
! scope="col" | Manufacturer
 
! scope="col" | Specification/model
 
! scope="col" | Comments
 
|-
 
! scope="row" | Solar panels
 
| Kyocera
 
| Any, Mono or poly crystalline from 10 to 100 W (typically)
 
| rowspan="4" | The market of solar panels is a new and very dynamic market, where new companies appear and disappear every day.
 
|-
 
!
 
| Victron
 
| Any, Mono or poly crystalline from 10 to 100 W (typically)
 
|-
 
! PhotoWatt (not exist anymore)
 
| Any, Mono or poly crystalline from 10 to 100 W (typically)
 
|-
 
! SolarWorld (not exist anymore)
 
| Any, Mono or poly crystalline from 10 to 100 W (typically)
 
|-
 
! scope="row" | Wind turbines
 
| Primus
 
| Primus AIR 30
 
|
 
|-
 
!
 
|
 
| Primus AIR 40
 
|
 
|-
 
!
 
| FORGEN
 
| Forgen Ventus 70
 
|
 
|-
 
!
 
|
 
| Forgen Antarctic
 
|
 
|-
 
!
 
| Wind-Kinetic
 
| Polar
 
|
 
|-
 
! scope="row" | Fuel Cell
 
| EFOY
 
| EFOY Pro 600
 
|
 
|-
 
! scope="row" | Batteries
 
| Sonnenschein
 
| Gel Dryfit, cycling, 30 to 100 Ah.
 
|
 
|-
 
!
 
| YUASA
 
| AGM cycling, 30 to 100 Ah.
 
|
 
|-
 
!
 
| Victron
 
| Gel or AGM cycling, 30 to 100 Ah.
 
|
 
|-
 
!
 
| Enersys
 
| Cyclon
 
|
 
|-
 
!
 
| Shaft
 
| Lithium Sulfuryl Chloride
 
| Non rechargeable. Mainly used for the measurements in the oceanic domain.
 
|-
 
!
 
| Victron
 
| Lithium FePO<sub>4</sub>
 
| Rechargeable battery.
 
|}
 
  
 
=8 Place of Research Infrastructures on the technological market=
 
=8 Place of Research Infrastructures on the technological market=
Line 1,880: Line 1,304:
 
The core of the scientific business dedicated to environmental measurements and climate change observations can be seen in interactions of producing companies with the consumers of their products. Such interactions are developed, facilitated, and actively promoted. However, these interactions are not always beneficial or successful due to the different views and capabilities of producers and consumers communities. Thus, producers do not always have the possibility to understand the needs of consumers due to the lack of communication or inability to dedicate the funds for the market research. This results in the production of low-functional, expensive devices and, consequently, decrease of companies revenues and incomes. At the same time, the end-users do not have the chance to explain the producers their needs and cannot afford purchasing expensive devices directly from them. Research infrastructures are the bodies that act as intermediates between producers of the technologies, their end-users and third parties, such as grant holders, providing benefits for all market players as shown below at figure 10.
 
The core of the scientific business dedicated to environmental measurements and climate change observations can be seen in interactions of producing companies with the consumers of their products. Such interactions are developed, facilitated, and actively promoted. However, these interactions are not always beneficial or successful due to the different views and capabilities of producers and consumers communities. Thus, producers do not always have the possibility to understand the needs of consumers due to the lack of communication or inability to dedicate the funds for the market research. This results in the production of low-functional, expensive devices and, consequently, decrease of companies revenues and incomes. At the same time, the end-users do not have the chance to explain the producers their needs and cannot afford purchasing expensive devices directly from them. Research infrastructures are the bodies that act as intermediates between producers of the technologies, their end-users and third parties, such as grant holders, providing benefits for all market players as shown below at figure 10.
  
<div class="figure" id="figure10">[[File:ENVRIplus D1.1-Fig. 10-Interactions of RIs with other participants in the market.png|center|frame|Interactions of RIs with other participants in the market]]</div>
+
FIGURE 10 INTERACTIONS OF RIS WITH OTHER PARTICIPANTS IN THE MARKET.
  
 
The arrows between the RI body and the companies represent:
 
The arrows between the RI body and the companies represent:
 
# Services that can be provided by RIs to the companies
 
# Services that can be provided by RIs to the companies
#* Representing large groups of the end-users, RIs are capable of purchasing products of high cost, which can be shared among the multiple end-users.
+
* Representing large groups of the end-users, RIs are capable of purchasing products of high cost, which can be shared among the multiple end-users.
#* As large entities, connecting numerous research institutes and governmental structures, RIs can collect the demands for the standardization and metrology and pass them to the companies for the future implementation.
+
* As large entities, connecting numerous research institutes and governmental structures, RIs can collect the demands for the standardization and metrology and pass them to the companies for the future implementation.
#* RIs can predict natural disasters affecting business and human well-being. This is a valuable capability for business management and crisis prevention.
+
* RIs can predict natural disasters affecting business and human well-being. This is a valuable capability for business management and crisis prevention.
#* Co-designing innovation. RIs can promote the development of new products and services as well as to adapt them to the market needs and rules.
+
* Co-designing innovation. RIs can promote the development of new products and services as well as to adapt them to the market needs and rules.
#* RIs can provide the facilities, necessary for testing of new technologies
+
* RIs can provide the facilities, necessary for testing of new technologies
#* RIs can perform data collection and management, to support companies and generate income.
+
* RIs can perform data collection and management, to support companies and generate income.
# Services that companies can provide to RIs
+
# Services that companies can provide to RIs
#* Companies can sell their innovative devices to RIs. In case the devices are of high cost, RIs will be able to purchase them in contrast to the single users/scientists.
+
* Companies can sell their innovative devices to RIs. In case the devices are of high cost, RIs will be able to purchase them in contrast to the single users/scientists.
#* Companies can provide new services to the RI, in larger extent than to the single users.
+
* Companies can provide new services to the RI, in larger extent than to the single users.
#* Data collection and transmission. While using the facilities of RIs, companies can collect data at low cost. This data can be shared with the members of RIs to make their work more efficient.
+
* Data collection and transmission. While using the facilities of RIs, companies can collect data at low cost. This data can be shared with the members of RIs to make their work more efficient.
# Services that RIs can provide to customers (end-users)
+
# Services that RIs can provide to customers (end-users)
#* RIs can assure that all the customers (end-users) have equal possibilities to access the facilities for the environmental measurements and climate change investigations, as well as to the data provided by each and every RI.
+
* RIs can assure that all the customers (end-users) have equal possibilities to access the facilities for the environmental measurements and climate change investigations, as well as to the data provided by each and every RI.
#* RIs provide transferable and reusable data and knowledge.
+
* RIs provide transferable and reusable data and knowledge.
# RIs become an attractive receiver of grants and funding
+
# RIs become an attractive receiver of grants and funding
#* Given the same amount of financial support, RIs can provide the access to the research facilities to larger amount of scientists or other interested communities.
+
* Given the same amount of financial support, RIs can provide the access to the research facilities to larger amount of scientists or other interested communities.
# Direct interactions between the end-users and producing companies
+
# Direct interactions between the end-users and producing companies
#* Direct interactions are possible, but are never as beneficial as interactions through the RIs due to the reasons mentioned in points1-4.
+
* Direct interactions are possible, but are never as beneficial as interactions through the RIs due to the reasons mentioned in points1-4.
 
+
 
==8.2 RIs as innovative business partners==
+
==8.2 RIs as innovative business partners==
 +
 
 +
From the types of interactions described above, it can be seen that RIs can catalyse the development of technologies by being their direct users and acting as innovation partners:
 +
 
 +
RIs as contributors to new products and services – RIs can work as competitive infrastructures for businesses. Start-up companies with limited possibilities of purchasing of high-tech devices can become more beneficial by using shared devices within RIs. Such access to the systems through the RIs will reduce the cost of system operation, ensure the full time-load of devices and, thus, increase the effectiveness of work.
  
From the types of interactions described above, it can be seen that RIs can catalyse the development of technologies by being their direct users and acting as innovation partners:
 
 
RIs as contributors to new products and services – RIs can work as competitive infrastructures for businesses. Start-up companies with limited possibilities of purchasing of high-tech devices can become more beneficial by using shared devices within RIs. Such access to the systems through the RIs will reduce the cost of system operation, ensure the full time-load of devices and, thus, increase the effectiveness of work.
 
  
 
RIs as users of innovative techniques – Upon their development and growth, RIs will demand new technological solutions with better measurement characteristics and thus promote research, development and manufacturing of new technological devices for environmental measurements and climate change investigations.
 
RIs as users of innovative techniques – Upon their development and growth, RIs will demand new technological solutions with better measurement characteristics and thus promote research, development and manufacturing of new technological devices for environmental measurements and climate change investigations.
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It is important to note, that companies, interested in the collaboration with RIs can be represented by Small and Medium sized companies (SMEs) as well as by large consortiums and conglomerates. Both SMEs and larger companies will have their own benefits from collaboration with RIs, however the interactions of the entities in such cases might differ. Table 61 compares the interactions of single researchers with SMEs and RIs with SMEs.
 
It is important to note, that companies, interested in the collaboration with RIs can be represented by Small and Medium sized companies (SMEs) as well as by large consortiums and conglomerates. Both SMEs and larger companies will have their own benefits from collaboration with RIs, however the interactions of the entities in such cases might differ. Table 61 compares the interactions of single researchers with SMEs and RIs with SMEs.
  
<div class="tablecaption" id="table61">TABLE 61 INTERACTION OF RESEARCHERS AND RIS WITH SMES</div>
+
TABLE 61 INTERACTION OF RESEARCHERS AND RIS WITH SMES
{| class="wikitable"
 
! scope="col" | Researcher to SMEs
 
! scope="col" | RIs to SMEs
 
|-
 
| Purchases at the small scale
 
| Purchases at the large scale
 
|-
 
| Precisely specifies the requirements for the instrument
 
| Provides specifications for the instrument
 
|-
 
| Vision of small scientific niche
 
| Vision of the worldwide market for research and applications
 
|-
 
| Share experience in their own scientific community
 
| Promotes exchange of experiences between communities
 
|}
 
Table 62 compares interactions of scientists with the large industrial agglomerates and such interactions of RIs.
 
  
<div class="tablecaption" id="table62">TABLE 62 INTERACTION OF RESEARCHERS AND RIS WITH LARGE COMPANIES</div>
+
TABLE 62 INTERACTION OF RESEARCHERS AND RIS WITH LARGE COMPANIES
{| class="wikitable"
 
! scope="col" | Researcher to large companies
 
! scope="col" | RIs to large companies
 
|-
 
| Provides knowledge in very specific field of expertise
 
| Provides all spectra of knowledge in the field
 
|-
 
| Interested to use the infrastructure of large company
 
| Provides infrastructure for business
 
|-
 
| Improves image of innovative industrial company
 
| Broadcast the image of innovative industrial company
 
|}
 
  
 
==8.3 Addressed technologies==
 
==8.3 Addressed technologies==
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On the way of development, technologies pass several stages. These stages are represented by the Technology Readiness Level (TRL) ranging from 1 to 9, where 1 refers to the least developed technology and 9 to the most developed one. Usually it is assumed, that technologies with the TRL from 1 to 5 are immature technologies, developed and worked on by individual scientists. Contrary, technologies with the TRL from 8 to 9 are mature technologies, ready to become commercial products. As can be noticed, technologies with the TRL 6-7 are in the intermediate state. In this stage they cannot be further developed with the capacities of scientists, as such development would require significant allocation of funds. At this intermediate stage, they are also unlikely to attract funds from the commercial sector, as the companies are not ready to invest in the technologies that will not bring the profit in the short-term perspective. TRL scale is illustrated in figure 11.
 
On the way of development, technologies pass several stages. These stages are represented by the Technology Readiness Level (TRL) ranging from 1 to 9, where 1 refers to the least developed technology and 9 to the most developed one. Usually it is assumed, that technologies with the TRL from 1 to 5 are immature technologies, developed and worked on by individual scientists. Contrary, technologies with the TRL from 8 to 9 are mature technologies, ready to become commercial products. As can be noticed, technologies with the TRL 6-7 are in the intermediate state. In this stage they cannot be further developed with the capacities of scientists, as such development would require significant allocation of funds. At this intermediate stage, they are also unlikely to attract funds from the commercial sector, as the companies are not ready to invest in the technologies that will not bring the profit in the short-term perspective. TRL scale is illustrated in figure 11.
  
<div class="figure" id="figure11">[[File:ENVRIplus D1.1-Fig. 11-Technology readiness level Axis (1-9) and stages of the technological product.png|center|frame|Technology readiness level Axis (1-9) and stages of the technological product]]</div>
+
FIGURE 11 TECHNOLOGY READINESS LEVEL AXIS (1-9) AND STAGED OF THE TECHNOLOGICAL PRODUCT.
  
 
RIs thus refer to the emerging technologies with the TRL from 6 to 7, to ensure that they will overpass the financial barrier and become the commercially successful technologies with the great potential of further development and improvement. Also RIs will target improvement of technologies, such as their miniaturization and bettering of precision, as these parameters can also be referred as innovation.
 
RIs thus refer to the emerging technologies with the TRL from 6 to 7, to ensure that they will overpass the financial barrier and become the commercially successful technologies with the great potential of further development and improvement. Also RIs will target improvement of technologies, such as their miniaturization and bettering of precision, as these parameters can also be referred as innovation.
Line 2,025: Line 1,420:
 
Application of sensors in various fields of human activity - it is a common mistake to think that existing and novel sensors can find their applications only in the scientific research. Common application areas also include private and public healthcare, education and increasing general information and awareness. Increase of number of spheres where the sensors will be applied is another well-seen trend.
 
Application of sensors in various fields of human activity - it is a common mistake to think that existing and novel sensors can find their applications only in the scientific research. Common application areas also include private and public healthcare, education and increasing general information and awareness. Increase of number of spheres where the sensors will be applied is another well-seen trend.
  
<div class="tablecaption" id="table63">TABLE 63 APPLICATIONS OF SENSORS FOR AIR AND WATER QUALITY MONITORING</div>
+
TABLE 63 APPLICATIONS OF SENSORS FOR AIR AND WATER QUALITY MONITORING
{| class="wikitable"
 
! scope="col" | Application
 
! scope="col" | Description
 
! scope="col" | Example
 
|-
 
! scope="row" | Research
 
| Scientific studies and experiments to track air or water pollution
 
| Network of sensors aimed to measure atmospheric and water quality/state in urban or natural areas
 
|-
 
! scope="row" | Personal exposure monitoring
 
| Monitoring air and water quality, that a single individual is exposed to in normal, everyday conditions
 
| Monitoring air and water quality in the private location of (for air) in the car
 
|-
 
! scope="row" | Control of health
 
| Monitoring pollution levels that might promote patient sickness
 
| A person having a clinical condition wears a sensor to identify the sudden change in ambient pollution of air or water, potentially affecting his/her health
 
|-
 
! scope="row" | Supplementing Existing Monitoring Data
 
| Sensors are placed within local monitoring area to fill the coverage
 
| Increasing the density of sensor network to improve the understanding of pollution gradient
 
|-
 
! scope="row" | Identification of source of pollution
 
| Identification of pollution source by deploying a network of sensors in the vicinity of suspected source
 
| A network of sensors can be installed near to the industrial facility to monitor the pollution gradient as a function of time
 
|-
 
! scope="row" | Education activities
 
| Using various sensors to educate students about the source of pollutions and means of its measurement
 
| Sensors are provided to students to understand the principles of measurements and importance of climate change tracking
 
|-
 
! scope="row" | General information and awareness
 
| Using sensors in public places to increase the awareness of people about pollution
 
| Install the sensors in the zones of public access to illustrate the current state of pollution of air and water
 
|}
 
  
 
As a result of this work, authors present the table, summarizing the technologies mentioned in the current document, in relation to the RIs, they are applied in and in relation to the domains, where they are used. The table can be found in a separate annex 1.
 
As a result of this work, authors present the table, summarizing the technologies mentioned in the current document, in relation to the RIs, they are applied in and in relation to the domains, where they are used. The table can be found in a separate annex 1.
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<!-- Document type -->
 
<!-- Document type -->
 
[[Category:Report]]
 
[[Category:Report]]
<!--Domains-->
+
<!-- Relevant domains -->
[[Category:All domains]]
+
[[Category:Atmosphere]]
 +
[[Category:Ecosystem]]
 +
[[Category:Marine]]
 +
[[Category:Solid Earth]]
 
<!-- Keywords -->
 
<!-- Keywords -->
 
[[Category:Innovation]]
 
[[Category:Innovation]]

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