R Lardy

M.-M Mialon

N Wagner

Y Gaudron

B Meunier

K Helle Sloth

D Ledoux

M Silberberg

A De Boyer Des Roches

Q Ruin

M Bouchon

C Cirié

V Antoine

J Koko

I Veissier

Claudia Kasper

Understanding anomalies in animal behaviour: data on cow activity in relation to health and welfare

Keywords:

We collected data on the behaviour of dairy cows in barns, clinical signs of diseases as well as events that may stress or agitate the cows. A Real-Time Locating System gives the position of individual cows every second. The position of the cow is determined by triangulation based on radio waves emitted by a tag fixed on each cow neck collar and captured by antennas in the barn. The cow's activity is inferred from its position: 'eating' if the cow is positioned at the feeding table, 'resting' if the cow is in a resting area (typically cubicles), else 'in alleys'. We aggregated this information to get the time spent in each activity per hour. We also calculated the activity level of the cow for each hour of the day by attributing a weight to the time spent in each activity. For each cow and day, we collected information on health events or other events that may affect behaviour. There were 11 types of events. Six events were linked to health: lameness; mastitis; LPS (i.e. administration of lipopolysaccharide (LPS) in the mammary gland, an experimental treatment to induce udder inflammation); subacute ruminal acidosis; other diseases (such as colic, diarrhoea, ketosis, milk fever or other infectious diseases); and accidents (such as retained placenta or vaginal laceration). Two events were linked to reproduction: oestrus and calving. Three events were stress events: animal mixing, disturbance (i.e. mild intervention on animals such as late feeding, alarm test) and marginal management changes (ration changes, fill bed). In addition, a Boolean sums up whether this hour was considered as normal or not. Data contain four datasets. It consists of univariate time series. Each time series corresponds to the hourly activity level of a cow. Datasets 1 and 2 are from the INRAE Herbipôle experimental farm and include data from experiments; datasets 3 and 4 are from commercial farms. They contain data on respectively 28, 28, 30 and 300 cows monitored for 6 months, 2 months, 40 days and one year. The data can be used to study the links between health, reproduction events and stress on the one hand and cow behaviour on the other hand. More specifically, it can be used to build and test tools for an earlier detection of health and disturbances, with a view to inform caretakers so that corrective actions can be rapidly put in place.

Specification table

Subject

Behaviour and Health Management

Specific subject area

Cow behaviour through hourly cow activity data and associated event labels (e.g. oestrus, diseases, lameness, . . .)

Type of data Table

How data were acquired

We collected data from the CowView system (GEA Farm Technology, Bönen, Germany), which is a Real-Time Locating System (RTLS) that gives the position of each cow in a barn every second. The cow's activity is inferred from its position: 'eating' if the cow is positioned at the feeding table, 'resting' if the cow is in a resting area (typically cubicles), else 'in alleys'. We also calculated the level of activity of the cow for each hour of the day. For each cow and day, we collected information on health events or other events that may affect behaviour. Event data were collected from logbooks or from sanitary information system (SICPA sanitaire, https://doi.org/10.15454/ A1UV8Q). The caretakers logged any event as soon as it was observed (oestrus Even though data on activity can be obtained by different sensors, the results obtained are likely to be valid on datasets of animal activity obtained by other means (other sensors or observation) [START_REF] Buller | Animal Welfare Management in a Digital World[END_REF].

Data description

Data are composed of four datasets and one table (Table 1). The datasets are structured as follows: cow working id (3 or 5 digits); No cow belongs to several datasets; therefore, there are 386 unique cows. date; hour (integer). The time spent in each activity is aggregated at hourly scale because lower scales contain too much variability; the hourly scale allows to study variations during the day and results in datasets which can be processed easily by softwares such as R. The agreement between INRAE and GEA Farm Technologies was thus established on the basis of activity data collected per hour; the time(s) spent 'walking' during one hour (the cow is positioned 'in alleys'); the time(s) spent 'resting' during one hour (the cow is in a resting area (typically cubicles)); the time(s) spent 'eating' during one hour (the cow is positioned at the feeding table ); the activity level (unitless), which is the weighted sum of the time spent in each activity (with the following weights: À0.23 for resting, +0.16 for in alleys, and +0.42 for eating, [START_REF] Wagner | Detection of changes in the circadian rhythm of cattle in relation to disease, stress, and reproductive events[END_REF]). Due to the weights, the hourly activity level can range from À828 (i.e. À0.23 Â 3 600) to 1512 (i.e. 0.42 Â 3 600). To attribute a weight to each activity, a Factorial Analysis of Correspondence was run with observations being the hours of the day and variables being the time spent in each activity [START_REF] Veissier | Short communication: Early modification of the circadian organization of cow activity in relation to disease or estrus[END_REF]. The weights attributed to each activity to calculate the activity level are those obtained on the first component which expressed at most the variability between hours of the day and is thus likely to reveal the circadian cycle. This analysis was performed on each dataset. Although the datasets were obtained in farms managed under varying conditions (e.g. conventional vs. automatic milking, mixed diet vs. roughage and concentrate distributed separately), the weights obtained showed good closeness (mean absolute variation of coefficient was 6.7% ±. 11.0%). We thus calculated averaged weights across the four datasets, that we think generic enough to be applied on any farm even outside of the present datasets; Finally, for each of the 11 types of events, a Boolean is provided, for the question ''is there this type of event on this hour ?" (i.e. 1 means this type of event was reported for this hour; 0 means that this type of event was not reported for this hour). Note that in fact daily events are reported here at hourly scale.

There are 11 types of events:

-oestrus [ATOL_0005321]; -calving [ATOL_0000877]; -lameness [AHOL_0003029] includes all types of lameness and issues on claw or leg; -mastitis [AHOL_0003088] includes all types of mastitis; -Event LPS is specific to experimentation as it is for administered lipopolysaccharide (LPS) in the mammary gland on one day to induce inflammation [AHOL_0003064]. Table 1 provides the additional information on whether the cow received a nonsteroidian anti-inflammatory drug or a physiological serum; -Event acidosis [AHOL_0003154] stands for subacute ruminal acidosis. When the measure was not available, the dataset contains 'NA'; -Event labelled 'other_disease', which contains all other diseases such as colic, diarrhoea, ketosis, milk fever or other infectious diseases; -Event accidents contain all types of accidents such as retained placenta or vaginal laceration; -Event disturbance is mild intervention on animal (e.g. late feeding, alarm test, animal tied for injection, claw trimming, drying of the cow) and other issues on the day but that did not concern management changes; -Event mixing is for when cows were mixed or moved to another park; -Event labelled 'management_changes' contains marginal management such as ration changes or bed filling. This event is reported in the dataset, but is not considered to influence the animal behaviour;

Table 2 gives a summary of the number of events per type and per dataset.

A final Boolean sums up the information on whether this hour is considered as normal (i.e. if all the Booleans (without considering the management changes one) are equal to 0, then this hour can be considered as normal, otherwise (at least one event) then the Boolean is set to 1).

Dataset 1 -This dataset contains data for 28 cows monitored for 6 months (5 124 cow  day, i.e. the number of times where data are present for a specific cow on a specific day). Due to some missing data, the dataset contains only 107 665 cow  hour observations (i.e. the number of times where data are present for a specific cow on a specific hour, 12.4% of missing data).

Dataset 2-This dataset contains data for 28 cows monitored during 2 months (60 days) (1 680 cow  day). Due to some missing data, the dataset contains only 40 246 cow * hour observations (0.2% of missing data).

Table 1

This table is linked to the dataset 1. For each cow, it indicates whether the dairy cow received a non-steroidian anti-inflammatory drug (Ketofen Ò 10%, 3 mg/kg; CEVA Santé Animale, Libourne, France) (NSAID), or a physiological serum (0.9% NaCl, 3 mL/100 kg, BIOLUZ, St Jean de Luz, France) (CONTROL). Cow 6664 is present in the dataset 1, but it did not receive lipopolysaccharide (LPS) as it was lame at the time of the LPS challenge, which is then noted as 'NONE' in the Dataset 3 -This dataset contains data for 30 cows monitored for 40 or 41 days, resulting in 1 220 cow  day. Due to some missing data, the dataset contains only 26 224 cow * hour observations (10.4% of missing data).

Dataset 4 -This dataset contains data for 109 800 cow  day with 300 cows for year. Due to some missing data, the dataset contains only 2 177 207 cow  hour observations (17.3% of missing data).

Table 1 is linked to dataset 1. For each cow, it indicates whether the cow received a non-steroidian anti-inflammatory drug (Ketofen Ò 10%, 3 mg/kg; CEVA Santé Animale, Libourne, France) (NSAID), or a physiological serum (0.9% NaCl, 3 mL/100 kg, BIOLUZ, St Jean de Luz, France) (CONTROL). Cow 6664 is present in dataset 1, but it did not receive lipopolysaccharide (LPS) because it was lame at the time of the LPS challenge, it is then noted as 'NONE' in the column 'Treatment' of the table.

Experimental design, material and methods

All the data were obtained on dairy cows. Raw data from sensors were processed by the CowView system (GEA Farm Technology, Bönen, Germany): position changes were kept only if the position change was higher than 15 cm or if the cow kept this position for more than 60 s). Then using the building map, we extracted raw information on cow positions (i.e. in alleys, in cubicles or in feeding table) at hourly scale. Incomplete hours were not kept.

Event data were collected from logbooks or from the sanitary information system (SICPA sanitaire, https://doi.org/10.15454/ A1UV8Q). The caretakers logged any event as soon as it was observed (oestrus, calving, lameness, clinical mastitis, clinical signs of other diseases, accident-related health problems, disturbances such as handling for vaccination, change of pen, mixing of animals) in a logbook (or the information system), together with the treatment applied to the animal.

Dataset 1 comes from INRAE Herbipôle experimental farm. The cows were milked at fixed times twice a day. The food was delivered in the morning then pushed back close to the feeding gates three times in the afternoon. The cows were administered 25 lg ultra-pure LPS from Escherichia Coli O111 (tlrl-3pelps, InVivogen, United States) in the mammary gland on one day to induce inflammation. The acute inflammation lasted 2 days. In addition, the challenged cows received an intramuscular injection of either saline solution (0.9% NaCl, 3 mL/100 kg, BIOLUZ, St Jean de Luz, France) (LPS group) or Ketoprofen (Ketofen Ò 10%, 3 mg/kg; CEVA Santé Animale, Libourne, France) (LPS + NSAID group) on average 30 min (minimum-maximum: 26-31 min) after been challenged. Volumes of saline solution injected in LPS group were equivalent to the volumes of Ketoprofen injected. Cow body temperature was monitored to check that they reacted to LPS. This dataset contains events of oestrus, calving, lameness, mastitis, LPS, other diseases, disturbance and mixing, but no occurrences of accidents or marginal management changes. Acidosis was not measured.

Dataset 2 comes from INRAE Herbipôle experimental farm. The cows were milked at fixed times twice a day, and fed twice a day. Half of the cows received a high-starch diet for 1 month to induce subacute ruminal acidosis. Ruminal pH was monitored using a sensor (eCow bolus, Exeter, UK). According to the method proposed by [START_REF] Villot | Relative reticulorumen pH indicators for subacute ruminal acidosis detection in dairy cows[END_REF], we normalised the ruminal pH values of each cow to take into account inter-individual variability, sensor drift and sensor noise. Then, we considered that a cow was under subacute ruminal acidosis (SARA) when the normalised ruminal pH (NpH) decreased by at least 0.3 for more than 50 min/d and the daily standard deviation in NpH was above 0.2 or the daily NpH range was above 0.8. This dataset contains events of oestrus, lameness, mastitis, acidosis, other diseases, disturbance and marginal management changes, but no occurrences of calving, accidents or mixing. LPS was never administered on these cows.

Dataset 3 comes from three commercial farms. On two farms, the cows were milked at fixed times twice or three times a day, and food was delivered twice a day or only once in the morning then pushed back after each milking. The third farm was equipped with an automatic milking system, so the cows had no fixed milking times. Food was delivered in the morning and regularly pushed back by a robot. Contrary to datasets 1, 2 and 4 where oestrus was detected by caretaker observation, in dataset 3, progesterone was assayed in the milk daily, and oestrus was detected when progesterone concentration dropped dramatically for at least three consecutive days (e.g. from 20 down to 5 ng/mL; Ovucheck Ò Milk test, Biovet Ò , Saint-Hyacinthe QC, Canada). This dataset contains only events of oestrus and no other types of events (LPS was not administered and acidosis was not measured).

Dataset 4 comes from a commercial farm with 300 cows monitored for 12 months. The farm was equipped with an automatic milking system. The food was delivered in the morning and regularly pushed back by a robot. This dataset contains events of oestrus, calving, lameness, mastitis, other disease, accidents, disturbance and marginal management changes, but no occurrences of or mixing. LPS was not administered, and acidosis was not measured.

  table.

	Cow id	Treatment
	6601	CONTROL
	6610	NSAID a
	6612	NSAID a
	6613	NSAID a
	6621	NSAID a
	6629	NSAID a
	6633	CONTROL
	6634	NSAID a
	6637	CONTROL
	6638	CONTROL
	6643	CONTROL
	6646	NSAID a
	6656	CONTROL
	6664	NONE
	6674	CONTROL
	6675	CONTROL
	6683	CONTROL
	6686	NSAID a
	6689	NSAID a
	6690	CONTROL
	6693	NSAID a
	6695	NSAID a
	6699	CONTROL
	6701	NSAID a
	6714	CONTROL
	6721	CONTROL
	6750	CONTROL
	7600	NSAID a

a Non-steroidian anti-inflammatory drug.

Table 2

 2 Number of events per type and per dataset of hourly dairy cow activities.

	Type of Event	dataset 1	dataset 2	dataset 3	dataset 4
	Oestrus	41	7	26	257
	Calving	8	0	0	171
	Lameness	4	16	0	114
	Mastitis	9	3	0	32
	Lipopolysaccharide (LPS)	27	0	0	0
	Acidosis	0	271	0	0
	other_disease	10	8	0	66
	Accidents	0	0	0	15
	Disturbance	173	671	0	12 223
	Mixing	72	0	0	0
	Management changes	0	168	0	2 581

Acknowledgments

We thank the staff from the Herbipôle experimental unit and the farmers for allowing us to use the data from their logbooks.

Financial support statement

This collaborative work was made possible by funding from the French government research agency ''Agence Nationale de la Recherche through the Investissements d'Avenir" programme (16-IDEX-0001 CAP 20-25, 2017). Nicolas Wagner PhD grant was provided by INRAE (Phase division) and Université Clermont Auvergne (SPI doctorate school). The experiment on LPS injections (in dataset 1) was funded by the INRAE GISA programme (Long-Health Project, coord. Pierre Germon) and CEVA Santé Animale. The experiment on subacute acidosis (in dataset 2) was part of the #311825 EU-PLF project (Animal and farmcentric approach to precision livestock farming in Europe) co-financed by the European Commission. Quentin Ruin work was supported by the #730924 SmartCow project also co-financed by the European Commission.

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Ethics approval

Datasets 1 and 2 were obtained in experimental conditions. The conditions for using the animals aligned with the framework of the EU Directive 2010/63 for the protection of animals used for scientific purposes. The INRAE 'Herbipôle' experimental facility (https://doi.org/10.15454/1.5572318050509348E12, UE 1414, Marcenat, France) received approval from the French Ministry of Agriculture to carry out experiments on live animals (EEA accreditation #C15-114-01). All scientists and technicians involved in the experiments received initial training for experiments on live animals and are regularly retrained to maintain and refresh their capacities, in line with French regulations governing experiments on animals. The protocol used in dataset 1 was submitted to and approved by the regional ethics committee (approval: APA-FIS2015043014541577). The protocol used in dataset 2 did not require such an approval.

Datasets 3 and 4 were obtained with no additional interventions on animals because measurements, diet, housing, handling of the animals or any other environment or management factors were part of the on-farm routine.

Declaration of interest

Karen Helle Sloth was employed by GEA Farm Technology that commercialises the CowView system that was used to detect the position of cows. All the authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


Malek Zaibi
email: malek.zaibi@univ-poitiers.fr-jamel.belhadj@esstt.rnu.tn

Toufik Madani Layadi
email: layaditm@gmail.com

Gérard Champenois
email: gerard.champenois@univ-poitiers.fr

Xavier Roboam
email: xavier.roboam@laplace.univ-tlse.fr-bruno.sareni@laplace.univ-tlse.fr

Bruno Sareni

Jamel Belhadj

A Hybrid Spline Metamodel for Photovoltaic/Wind/Battery Energy Systems

Keywords: Hybrid power systems, Metamodeling, Battery management systems, Hydraulic systems

This paper proposes a metamodel design for a Photovoltaic/Wind/Battery Energy System. The modeling of a hybrid PV/wind generator coupled with two kinds of storage i.e. electric (battery) and hydraulic (tanks) devices is investigated. A metamodel is carried out by hybrid spline interpolation to solve the relationships between several design variables i.e. the design parameters of different subsystems and their associate response variables i.e. system indicators performance. The developed model has been successfully validated under real test conditions.

I. INTRODUCTION

For complex systems like renewable energy sources, the design assigns highly computation-intensive process for analyses and simulations. Multiple techniques in engineering design and other disciplines have been developed to reduce the computational burden of evaluating numerous designs. Researchers have employed several metamodeling techniques in design and optimization, among which a simpler approximate model named "metamodel" can replace the original system process [START_REF] Wang | Review of metamodeling techniques in support of engineering design optimization[END_REF]. For example, the latter makes use of polynominal functions to solve the relationships between several design variables and one or more response variables. Many authors have suggested various types of metamodels among others: classical polynominal function models [START_REF] Chlelaa | A new methodology for the design of low energy buildings[END_REF], stochastic models such as the Kriging interpolation model [START_REF] Coelho | Multi-objective reliability-based optimization with stochastic metamodels[END_REF], [START_REF] Wang | Development of metamodeling based optimization system for high nonlinear engineering problems[END_REF], [START_REF] Song | Multidisciplinary optimization of a butterfly valve[END_REF] and artificial neural network models [START_REF] Betiku | Modeling and optimization of bioethanol production from breadfruit starch hydrolyzate vis-à-vis response surface methodology and artificial neural network[END_REF], [START_REF] Fang | Design and Modeling for Computer Experiments[END_REF]. The aim of the present paper is to introduce another metamodel named as hybrid spline model. Due to the complexity of system (approximation model, design variable and problem formulation) the hybrid spline model will be developed. Hence, we use the metamodel to solve the optimization problem. This paper contains three major parts. First, the hybrid Photovoltaic (PV)/Wind Turbines (WT) sources with battery bank powering electrical and hydraulic loads is presented. Second, the metamodel-based global system process is carried out. The metamodel process is based on three steps: Design space sampling of the real-model, parameter extraction of the metamodel and metamodel validation. Finally, the metamodel is used for assessing the hybrid system performance.

II. SYSTEM DESCRIPTION

The present system includes hybrid Photovoltaic (PV)/Wind turbines (WT) sources with battery bank powering electrical loads and hydraulic network loads. The latter is composed of water pumping and Reverse Osmosis (RO) desalination unit to produce permeate water. Fig. 1 presents the global system architecture. The PV/WT/Battery system consists of photovoltaic panels, wind turbines, battery bank and converters (DC/DC and AC/DC). The brackish water pumping and desalination process are composed of two motor-pumps, RO membrane, two water tanks and two (DC/AC) inverters. The different subsystems are coupled to DC Bus. The meteorological profiles: wind speed ( ), solar irradiation ( ) and ambient temperature ( ) of a typical region (North Tunisia) have been recorded for one year.

A. Hybrid Energy Models 1) PV generator model:

The PV generator power is determined from a model as defined in [START_REF] Hofierka | Assessment of photovoltaic potential in urban areas using open-source solar radiation tools[END_REF]- [START_REF] Liu | Photovoltaic dc building module based bipv system: Concept and design considerations[END_REF]:

= ⋅ ⋅ [1 -⋅ ( - )] ⋅ ⋅ (1)
where is PV efficiency, the power tracking equipment efficiency, which is equal to 0.9 with a perfect maximum point tracker, the temperature coefficient, ranging from 0.004 to 0.006 per ∘ C for silicon cells, normal operating PV cell temperature ( ∘ C), the PV panels area (m 2 ) and the PV cell temperature ( ∘ C) which can be expressed by [START_REF] Lasnier | Photovoltaic Engineering Handbook[END_REF]:

= 30 + 0.0175 ⋅ ( -300) + 1.14 ⋅ ( -25) (2)
where denotes the ambient temperature ( ∘ C).

978-1-4799-7947-9/15/$31.00 c ⃝ 2015 IEEE 2) Wind turbine model: The wind turbine power is expressed as follows [START_REF] Shepherd | Energy Studies[END_REF]:

= 1 2 ⋅ ⋅ ⋅ ⋅ 3 (3)
where is the wind turbine power coefficient, the air mass density and the wind turbine swept area.

3) Battery storage model: In this study, we propose an ideal model for the battery. During the charging and discharging process, the state of charge ( ) vs time ( ) can be described by [START_REF] Abbes | Life cycle cost, embodied energy and loss of power supply probability for the optimal design of hybrid power systems[END_REF]:

( ) = { ( -Δ )+ ℎ ⋅ / ⋅ Δ ( -Δ )+ 1 ⋅ / ⋅ Δ } ( 4
)
where Δ is the time step (here, three minutes), represents the battery power, ℎ and are respectively the battery efficiencies during charging and discharging phases.

denotes the nominal DC bus voltage. represents the nominal capacity of the battery bank in Ampere hour (Ah). At any time step Δ , the must comply with the following constraints:

≤ ( ) ≤ (5)
where and are the minimum and maximum allowable storage capacities, respectively.

4) Electrical load profile: Typical power consumption (

) data were acquired for a residential home. During 365 days with three minutes acquisition period, this profile describes the weekdays and weekend days consumption (see Fig. 2).

B. Hydraulic network models

The hydraulic network is shown in Fig. 1. It includes four principal subsystems: the motor-pump 1 which draws water from well, a water storage tank 1, the high pressure motorpump 2 associated with a reverse osmosis desalination device and a water tank storage 2. this final storage is placed at the output of the desalination process to store fresh water.

1) Model of the motor-pump 1:

The GRUNDFOS R ⃝ motorpump ("CRN" type) was selected for pumping water from well to the tank water storage 1. The electric power 1 required for motor-pump 1 at head H and flow rate 1 can be calculated as [START_REF]The Centrifugal Pump[END_REF]:

1 = ⋅ ⋅ ⋅ 1 ⋅ (6)
where is the density of water (kg/m 3 ), g the gravity constant (m/s 2 ), the motor efficiency and the pump efficiency. 2) Model of the water storage tank 1: Water tank 1 is used to store brackish water. It is characterized by its water level 1 and its section 1 . The level 1 can be calculated as follows:

1 ( ) = 1 ( -Δ ) + ( 1 ( ) -2 ( )) 1 ⋅ Δ (7)
This tank is fitted with four sensors measuring four different water levels: two minimum sublevels, i.e. high and low ( 1 and 1

) and two maximum sublevels, i.e high and low ( 1 and 1

). The high and low levels are separated by a hysteresis band. This hysteresis avoids the switch On/Off of the motor-pump during operation.

3) Model of the motor-pump 2 with reverse osmosis membrane:

The GRUNDFOS R ⃝ motor-pump ("CRN" type) [START_REF]The Centrifugal Pump[END_REF] was selected for water pumping from the tank water storage 1 to the tank water storage 2 via a reverse osmosis (RO) desalination system (ROMEMBRA R ⃝ TORAY RO membrane, "TM" type [START_REF] Toray | Operation, Maintenance and Handling Manual for membrane elements[END_REF]). In this study, the RO membrane model is characterized by the nominal fresh (permeate) water production in day (m 3 /d).

Three design configuration between the motor-pumps and RO membrane are used to develop a model (from a fitting approach). Fig. 3 presents three RO membrane characteristics 2 ( 2 ) and the Fig. 4 shows three motor-pump characteristics 2 ( 2 ) with their efficiencies.

The expression of the flow rate 2 is a function of the electric power 2 and the nominal fresh water : For the RO process, the flow rate 2 is separated between the permeate flow 2 and the concentrate flow 2 .

{ 2 = ⋅ 2 2 = 2 -2 (10)
where is the conversion rate of the RO membrane (i.e. =20%).

4) Modeling of the fresh water storage tank 2:

Water storage tank 2 is the tank of the permeate (fresh) water. It is characterized by the level 2 and section 2 . The level 2 can be calculated as follows:

2 ( ) = 2 ( -Δ ) + ( 2 ( ) - ( )) 2 ⋅ Δ (11)
where is the water flow demand required by the consumers. Fig. 5 represents the daily water flow demand.

As previously, this tank is fitted with four level sensors: two useful levels, i.e. high and low ( 2 and 2 ) and two maximum levels, i.e. high and low ( 2and 2

). The high and low levels are also determined by a hysteresis band.

C. System indicators performance

To assess the performance of this complex system, three indicators are used as follows:

1) The Loss of electric Power Supply Probability ( ),

(%) = ∑ Δ =1 Δ (Δ ) ⋅ Δ ∑ Δ =1 (Δ ) ⋅ Δ (12)
with

Δ = { - , ≤ 0, ℎ (13)
where is the renewable source power and is the electrical load power.

2) The Loss of hydraulic Power Supply Probability ( ),

(%) = ∑ Δ =1 (Δ ) ⋅ Δ ⋅ (14)
where

= { , 2 = 0 0, ℎ (15)
3) The exchange energy by the battery (

ℎ ) ℎ ( ℎ) = ∫ 0 | | ⋅ (16)
To obtain the performance of the three system indicators, a dynamic simulator is developed using MATLAB R ⃝ environment [START_REF] Abbes | Life cycle cost, embodied energy and loss of power supply probability for the optimal design of hybrid power systems[END_REF]. The different models of the studied system are integrated in the dynamic simulator. The latter during one year with sample time of three minutes allows us to simulate the system evolution.

III. METAMODEL-BASED PROCESS

The proposed metamodel process is summarized in Fig. 6. The first step resides in the sampling of the design space with the dynamic simulator. Then the building of the metamodel is performed to deduce the predicted responses. finally the validation step of the metamodel is presented.

A. Design Space Sampling

The relationships between the design variables and the system indicators performance characterized from the dynamic simulator. Given a set of design sites = [ 1 . . . ] with ∈ ℜ (n: numbers of design variables) and responses = [ 1 . . . ] with ∈ ℜ (p: numbers of responses). For the design site , the design variables is,

= [ , , , , 2 , 2 , 1 , ] (17)
The responses versus the system indicators performance are,

= [ , , ℎ ] (18)
The space filling design, the sample points around the border and only put few points in the interior of the design space:

= ⎛ ⎜ ⎜ ⎜ ⎜ ⎜ ⎜ ⎜ ⎜ ⎜ ⎜ ⎜ ⎜ ⎜ ⎜ ⎝ : 1 = { 1 , 1 + 1 2 , 1 } : 2 = { 2 , 2 + 2 2 , 2 } : 3 = { 3 , 3 + 3 2 , 3 } : 4 = { 4 , 4 + 4 2 , 4 } 2 : 5 = { 5 , 5 + 5 2 , 5 } 2 : 6 = { 6 , 6 + 6 2 , 6 } 1 : 7 = { 7 , 7 + 7 2 , 7 } : 8 = { 8 , 8 + 8 2 , 8 } ⎞ ⎟ ⎟ ⎟ ⎟ ⎟ ⎟ ⎟ ⎟ ⎟ ⎟ ⎟ ⎟ ⎟ ⎟ ⎠ (19)

B. Parameter extraction of the Metamodel

The design space data were used for the model fitting to explore the best polynomial function. Those data were employed using MATLAB R ⃝ Model-Based Calibration Toolbox. In this toolbox, two main global linear models are developed such as polynomial or hybrid splines. After testing these models, the hybrid splines models are used to predict the system indicators performance. The hybrid spline model is a piecewise polynomial function, where different sections of polynomial are fitted smoothly together. The locations of the breaks are called knots. The required number of knots (up to a maximum of 50) and their positions are chosen. In this case all the pieces of curves between the knots are formed from polynomial of the same order (the order up to 3).

C. Metamodel validation

The predicted responses obtained from the hybrid spline model were compared with simulator dynamic responses for testing and validating the metamodel. Different points are used to validate the metamodel. There are two measures of the accurate model, defined as below:

• The Root Mean Square Error (

) is: • The square value, coefficient of determination, ( 2) is:

= ⎷ ∑ =1 ( -ˆ ) 2 (20)
2 = 1 - ∑ =1 ( -ˆ ) 2 ∑ =1 ( -) 2 (21)
where is the number of validation points; ˆ is the predicted value for the observed value ; is the mean of the observed values at the validation points.

IV. RESULTS AND DISCUSSION

Following the proposed process, the constraints of the design variables are defined as

⎧          ⎨          ⎩ 30 m 2 ≤ ≤ 90 m 2 60 m 2 ≤ ≤ 220 m 2 400 Ah ≤ ≤ 600 Ah 30 % ≤ ≤ 100 % 0.3 m ≤ 2 ≤ 1.9 m 2 m 2 ≤ 2 ≤ 20 m 2 600 W ≤ 1 ≤ 1600 W 7 m 3 /d ≤ ≤ 30 m 3 /d (22)
For each design variable, three values (minimal, mean and maximal) are used to obtain the following design space ,

= ⎛ ⎜ ⎜ ⎜ ⎜ ⎜ ⎜ ⎜ ⎜ ⎜ ⎝ = {30, 60, 90} [m 2 ] = {60, 140, 220} [m 2 ] = {400, 500, 600} [Ah] = {30, 65, 100} [%] 2 = {0.3, 1.1, 1.9} [m] 2 = {2, 11, 20} [m 2 ] 1 = {600, 1100, 1600} [W] = {7, 18, 30} [m 3 /d] ⎞ ⎟ ⎟ ⎟ ⎟ ⎟ ⎟ ⎟ ⎟ ⎟ ⎠ (23)
Therefore, 6561 (3 8 ) design configurations are simulated by the dynamic simulator. Then, the system indicators performance (i.e. responses) are deduced for these design sites. The

   ⎨    ⎩ ˜ = 1 ( , , , , 2 , 2 , 1 , , ) ˜ = 2 ( , , , , 2 , 2 , 1 , , ) ˜ ℎ = 3 ( , , , , 2 , 2 , 1 , , ) = ( , ) (24)
where 1 , 2 and 3 are the second-order polynomial functions;

is the B-spline function: degree 1, is the number of knots ( = 1) and the knot position is the mean of . This metamodel design along with the predicted responses is shown in Fig. 7 and an illustration example for 100 design configurations is presented in Fig. 8.

Table I and Fig. 7 show that the hybrid spline metamodels performed quite well leading to a coefficient of determination close to 1 and small values of the measure. It can be noted that first and second system performance indicators (i.e. and ) are better interpolated than the third performance criterion (i.e. ).

In Table . II, the comparative CPU Time between the dynamic simulator and the hybrid spline model is presented. This results shows the most advantage of the hybrid spline metamodel when using a high number of system simulations such as the optimization process.

V. CONCLUSION

This work provides an application of the metamodel design for a Photovoltaic/Wind/Battery energy system. The develop-Fig. 8. An illustration of predicted responses (100 design configurations) ment in metamodelling is categorized according to the complexity of system: approximation model, design variable and problem formulation. Future developments will aim to use the metamodel instead of the dynamic simulator in an optimization process requiring a high number of system simulations. Such approach will benefit of the significant reduction of the CPU time and allow finding optimal configurations of the hybrid system with regard to the performance criteria.

Fig. 1 .

 1 Fig. 1. Global system architecture

Fig. 2 .

 2 Fig. 2. Weekly power consumption profile

2 = 4 . 2 ⋅ 2 . 2 ( 8 ) 2 =Fig. 3 .Fig. 4 .

 42228234 Fig. 3. Different RO membrane characteristics

Fig. 5 .

 5 Fig. 5. Daily water flow profile

Fig. 6 .

 6 Fig. 6. Metamodel design process

  ℎ

TABLE I .

 I RESULTS OF METAMODELS MEASURES

				ℎ
	2	0.978	0.949	0.994
		0.336	3.958	52.495

Fig. 7. Predicted responses based on hybrid spline model

TABLE II .

 II CPU TIME OF DYNAMIC SIMULATOR AND HYBRID SPLINE

		METAMODEL
	Technique	CPU Time for 6561 design configurations
	Dynamic simulator	34769 s
	Hybrid spline metamodel	19 s
	expressions of the predicted system indicators performance are,
	⎧

ACKNOWLEDGMENT

The authors would like to thank the CMCU UTIQUE Program for financial support. This work was supported by the Tunisian Ministry of High Education and Research under Grant LSE-ENIT-LR 11ES15.


Marianella Quispe-Sihuas

Jean-Baptiste Charlier

Roland Lastennet

Olivier Cabaret

Benoit Dewandel

Alain Denis

Characterization of hydrogeological processes of karst-influenced multi-layered aquifers of basin edge using statistical and geochemical approaches (northern Aquitaine basin, France)

This study aims to characterize the regional hydrodynamic and hydrochemical variability of multi-layer carbonate aquifers of basin edge by considering their karst feature. The study area is the northern edge Aquitaine Basin in Southwest France, which is characterized by two main Upper Cretaceous and Jurassic reservoirs. A dataset of water levels and physico-chemical analyses in 65 springs/shallow wells and 94 boreholes was collected from French public database. A statistical approach was conducted in order to differentiate aquifer compartments in relation with their hydrogeological context. First results show a contrasted physico-chemical signature between Jurassic and Upper Cretaceous aquifers, which is explained by the lithological properties, the aquifer depth and the residence time. Nevertheless, some locations present temperature and hydrochemical anomalies. Likely hypothesis are the karst influence due to localized recharge from fast river losses, as well as the karstification degree in unconfined and confined compartments.

Introduction

The edge zone of sedimentary basins is the site of interactions involving the recharge of multi-layer aquifers, affecting the quality of the water resource. At the regional scale, the karst feature of the reservoirs is rarely taken into account in hydrogeological processes. However, karst aquifers are characterized by complex recharge, exchanges and mixing between reservoirs, and interaction with surface water. Previous studies on Norther AB were conducted to understand the geological and hydrogeological functioning of different aquifers [START_REF] Cabaret | Gestion des eaux souterraines en Région Aquitaine -Connaissances des karsts aquitains -Étude des karsts libres et sous couverture du département de la Dordogne -Convention Régionale Eaux Souterraines 2015-2020 -Module 3.1[END_REF][START_REF] Husson | Origine, caractérisation et distribution prédictive du Karst sur la bordure Nord-Aquitaine -OKaNA[END_REF][START_REF] Lorette | Fonctionnement et vulnérabilité d'un système karstique multicouche à partir d'une approche multi-traceurs et d'un suivi haute-résolution : application aux Sources du Toulon à Périgueux[END_REF][START_REF] Platel | Perspectives de gestion des nappes du Secondaire en Agenais-Périgord. Synthèse géologique et hydrogéologique, modélisation hydrodynamique[END_REF][START_REF] Stempel | Etude des ressources en eau de la région de Périgueux (Dordogne)[END_REF]. Nevertheless, a major question remains about the karstic feature of the carbonate aquifers. This study aims to characterize the regional hydrodynamic and hydrochemical variability of multi-layer carbonate aquifers located in the basin edge by consider-ing their karst feature. The study site is the Northern Aquitaine Basin (AB) in Southwest France, characterized by two main Cretaceous and Jurassic reservoirs. First, we present a spatial analysis of the hydrodynamic variability of the two main reservoirs. Then, we investigate the geothermal gradient over the study zone. Finally, we explore the spatial hydrochemical variability of the compartments in link with geological and hydrogeological characteristics. This study focuses on the relationships between the secondary aquifers, Upper Cretaceous and Jurassic, and the role of the edge zone in the water quality. Thus, our objective with this method is to identify representative hydrogeological parameters of the main aquifers, and to identify the processes that best explain their variability.

Study area

The Aquitaine Basin (AB) is a regional multi-layer aquifer system located in Southwest France ( Fig. 1). In the Northern AB, sedimentary terrains from Trias to Upper Cretaceous overly a Hercynian granite and schist basement. Because of the variety of sedimentary deposits, the alternation of aquifers and aquitards create a complex multilayer aquifer system composed of six majors reservoirs: Jurassic, Upper Creta-ceous, Eocene, Oligocene, Miocene and Plio-Quaternary, which can themselves be subdivided [START_REF] Platel | Perspectives de gestion des nappes du Secondaire en Agenais-Périgord. Synthèse géologique et hydrogéologique, modélisation hydrodynamique[END_REF].

The Jurassic and Upper Cretaceous (at the East of the Northern AB) outcrops show evidence of two vast marine transgressions during Mesozoic. These predominantly carbonate formations are karstified, both outcrop and undercover. [START_REF] Platel | Stratigraphie, sédimentologie et évolution géodynamique de la plate-forme carbonatée du Crétacé supérieur du nord du bassin d'Aquitaine[END_REF]. The Upper Cretaceous multi-layer system is mainly composed of fractured limestone and contains four aquifers (from the deeper to the shallower): Cenomanian, Turonian, Coniacian-Santonian and Campanian. The Cenomanian aquifer (50 m thick) is located only in the North of the Northern AB. The Turonian (30-60 m) is a fractured and karstified aquifer, which contains predominantly limestone. The Coniacian-Santonian aquifer geometry follow the one of Turonian, and is the thickest cretaceous aquifer (30-275 m). It results a complex system with lateral and vertical variations of facies, which develops a secondary porosity in granular limestone (fissures and karstic conduits) and in sandstone layers with interstitial porosity, separated by chalky and marls formations. In the Jurassic unit, it is possible to identify five reservoirs, in some places separated by marly or marl-limestone layers. The Lias aquifer (35-100 m thick) made up of sandstone and dolomitic limestone. The limestone and dolomite of the Bajocian aquifer (30-70 m thick). The limestone of the Bathonian -Callovian -Oxfordian aquifer (100-650 m thick), which represent the principal Jurassic aquifer in the region. The limestone of the Kimmeridgian aquifer (50-210 m thick). These three aquifers can be considered as a monotonous and homogeneous series formed of limestone with partial secondary dolomitization, highly karstified. However, some marly levels might be present and can delimit local aquitards. Finally, the dolomitic limestone of the Tithonian aquifer, which is located above the marly levels, representing a local aquifer.

Materials and methods

Groundwater and hydrological dataset was compiled from several public databases. It comprises (1) hydrochemical data (major elements) and water levels from "ADES," n.d.) and (2) geological and technical information from springs and wells ("La Banque du sous-sol (BSS) | InfoTerre," n.d.)

Regarding water levels, 54 boreholes were selected: i) 29 in Upper Cretaceous aquifers (Turonian and/or Coniacian Santonian and/or Cenomanian), ii) and 25 in Jurassic aquifers (Bajocian and/or Bathonian Callovo Oxfordian and/or Kimmeridgian). Therefore, piezometric maps were established using standard krigging interpolation method for both aquifers during the dry and wet seasons of 2017.

Regarding hydrochemical data, 65 springs and shallow wells (maximum 7 m depth), and 94 boreholes (up to 1.2 km in depth, 330 m in average) were selected. To ensure that each borehole capture only one reservoir, the boreholes screened both in the Jurassic and Upper Cretaceous aquifers were not selected. Additionally, a minimum of 5 samples per site over the 2000-2019 period was required to integrate the analysis. An ionic balance was carried out to validate the samples, of which a value greater than 5% was not accepted. Physico-chemical parameters (temperature, pH, and electrical conductivity at 25°C), chemical analyses of major elements and nitrogen parameters were selected. In this study, the median value of the hydrochemical dataset is considered more representative than the mean, since it does not take into account the extreme or aberrant data that can bias the analysis.

To identify patterns in our large dataset, multivariate analyses were conducted using a Principal Component Analysis (PCA) on primary variable descriptors of all hydrochemical and physico-chemical data. Linear regression were also used to assess the correlation between variables. The geothermal gradient was calculated from 81 sites (boreholes) with a screen at least at 25 m deep and with flow logs and/or water strikes information. The screened interval must be less than 100 m. For the determination of the gradient, a simple linear regression was used. Additionally, PCA method was used to identify the main hydrochemical components

Results and discussion

Hydrogeological characteristics

The general pattern of the piezometric map ( Fig. 1) in Upper Cretaceous and Jurassic is similar in both the dry and wet seasons. In the Upper Cretaceous aqui-fers, the seasonal variations are up to 12 m in the unconfined area (outcrops) to a few centimetres in the confined area. The groundwater flow direction is globally from Northeast to Southwest. These maps highlight recharge zones on the Turonian and Coniacian Santonian outcrops but do not show evidence of groundwater recharge by river losses. Nevertheless, rivers such as Dordogne, Lizonne, Dronne and Isle appear to drain the cretaceous aquifer.

In the Jurassic aquifers, the average seasonal water level fluctuation is about 3.1 m, and can locally reaches 15 m. Two main flow direction are observed, the first is East-West in the area of Périgueux, and the second is NE-SW between Sarlat-la-Canéda and Cahors in the Causses du Quercy area. This dividing line seems accentuated by the piezometric depression in the Southeast of Sarlat-la-Canéda, which is probably due to the large amount of water abstracted by pumping in this area. Previous Jurassic piezometric surface [START_REF] Bichot | Gestion des eaux souterraines en Aquitaine, année 1. Evaluation des ressources. Extension du modèle Nord-Aquitain : synthèse des données et concepts[END_REF] from the 95-96 years, shows the same piezometric depression but 10 meters less deeper and with a main East-West flow direction. Which shows the vulnerability of the Jurassic confined aquifers in Villeneuve-sur-Lot.

From the piezometric point of view, it has been shown that stable levels and cyclic seasonal variations, mainly due to aquifer recharge [START_REF] Platel | Perspectives de gestion des nappes du Secondaire en Agenais-Périgord. Synthèse géologique et hydrogéologique, modélisation hydrodynamique[END_REF], characterize the Upper Cretaceous and Jurassic aquifers. Nevertheless, a diminution of the Jurassic groundwater table from the years 95-96 has been shown, especially at the confined areas.

Geothermal gradient

Groundwater temperatures from the 81 selected boreholes vary from 13.5 to 40°C, of which a global regional geothermal gradient of 2.060 °C/100 m (r 2 =0.59) was computed (Fig. 2). This model significantly differs from the theoretical geothermal gradient (3°C/100 m). This difference is due to cold-water anomalies at important depths, which can be explained by mixing processes with colder super-ficial waters transported by karstic features. The calculation of the geothermal gradient accounting for the two main Upper Cretaceous and Jurassic reservoirs does not improve so much the model in both cases (r² of 0.65 and 0.61, respectively). A slightly more efficient model is observed for the Upper Cretaceous aquifers. This could be link to a weaker degree of karstification and an important geological compartmentation of these aquifers, contrarily to the Jurassic aquifers that are strongly karstified.

Hydrochemical variability

The results of PCA on hydrochemical data are shown in the Fig. 3. The two first axes explain 76 % of the total variance, where two majors poles are differentiated.

Regarding variables, Mg 2+ is well correlated with water temperature (Tw) and is negatively correlated with Ca 2+ , HCO 3 -, and NO 3 -. These two groups of variables outline the first axis on Factor 1 of water transit time, increasing from NO 3 -(surface pollution) towards Mg 2+ , which are indicators of fast infiltration and high mineralization (and of dolomite dissolution), respectively. A third group shows that Na + , Cl -, K + and SO 4 2-are well correlated and have a nearly independent pattern compared to tracers determining Factor 1. Na + and SO 4 2-enrichment in Jurassic waters can be explained by vertical leakage from the Lias aquifer because of its evaporitic component (presence of anhydrite). However, an evaporitic and dolomitic signature can be also seen on the confined Upper Cretaceous waters, even if dolomite and anhydrite are not present in its lithology. Following the natural course of Na + and K + is difficult because of possible addition from anthropogenic activities .

Regarding observations, a first group is formed mainly by boreholes deeper than 200 meters with a few exceptions. This group represents boreholes with elevated values of temperature, and ions such as Mg 2+ (7-26 mg/L), Na + (5-72 mg/L), SO 4

2-(5-64 mg/L), Cl -(9-24 mg/L), that might indicate a higher mineralization (LeGal LaSalle et al., 1996). The mineralization is observed in the deep confined area of Upper Cretaceous and Jurassic aquifers, towards Villeneuve-sur-Lot, which may suggest an enrichment because of the residence time and a vertical drainage up to the upper Cretaceous layers. On the other hand, a second group is formed by springs, shallow wells and boreholes of shallow depth (<200 m). This group is dominated by high values of calcium (60-140 mg/L) and bicarbonates (220-420 mg/L), which characterize the water-rock interaction in an open carbonate system [START_REF] Edmunds | Baseline geochemical condi-tions in the Chalk aquifer, Berkshire, U.K.: a basis for groundwater quality management[END_REF][START_REF] Hanshaw | Major geochemical processes in the evolution of carbonate-Aquifer systems[END_REF]. Moreover, higher concentration of nitrates is found in this group (mean value of 12mg/L and a maximum of 44 mg/L), due to its sensitivity to agricultural practices. However, some deep boreholes are within this group indicating a mixing zone in which the karstic features may play a major role.

The spatial variability of the main major ions (Ca 2+ and Mg 2+ ) is presented in Fig. 4. High concentrations of Ca 2+ (around 120 mg/L) are seen in both Upper Cretaceous and Jurassic outcrops, explained by the immediate dissolution of the calcite in an open carbonate system. Rainwater infiltrating the soil overlying the carbonate outcrops quickly becomes saturated with respect to calcite. However, there is a Ca 2+ decrease from East to West and Southwest, which is consistent with the progressive confinement of Upper Cretaceous and Jurassic formations. A simi-lar phenomenon is shown at the chalk aquifer [START_REF] Edmunds | Baseline geochemical condi-tions in the Chalk aquifer, Berkshire, U.K.: a basis for groundwater quality management[END_REF], where it is likely the a Mg and Ca exchange takes place during progressive recrystallization of microcrystalline calcite or by incongruent dissolution of the carbonate.

On the contrary, there is an Mg 2+ increase from East to West and Southwest, in both Upper cretaceous and Jurassic aquifers. This pattern is likely explained by the dolomite facies that are only present in Jurassic layers. Additionally, little impurities of magnesium and high residence time in the Cretaceous reservoirs can be the source of the increased concentrations.

Conclusions and perspectives

The aim of this study was to characterize the hydrogeological processes of a karst-influenced multi-layered aquifers of basin edge. From a regional analysis in the Aquitaine Basin (AB) of hydrogeological and hydrochemical data, we showed the role of the edge zone into the recharge of multi-layered aquifers. The Upper Cretaceous and Jurassic aquifers are widely heterogenous. The hydrogeochemistry varies according the lithology facies, the residence time, the depth, and very likely because of the karstic feature. Our results show evidences of mixing zones between the two main Cretaceous and Jurassic reservoirs. This is probably due to the karstic and fractured natures of the carbonate formations that allow a fast infiltration through vertical drainage of water from the surface towards the deep parts of the aquifers. Thus, the groundwater that constitutes the global resource of the AB show a certain vulnerability due to the karstification of the main geological formations. Physical and chemical characteristics of the groundwater data show important variations according to increasing depth, to the progressive confinement from NE-SW and to the geological variations of facies.

  Fig. 1 : (a) Study area in the edge North Aquitaine Basin (southwest France) showing the piezometric map for both Upper Cretaceous and Jurassic aquifers (dry season 2017) and the (b) hydrogeological cross sections.

Fig. 2 :Fig. 3 :Fig. 4 :

 234 Fig. 2: Regional geothermal gradient models for models. Only the confidence intervals for the model 3 is presented.


Jonathan Pearce

Dave Jones

Jerry Blackford

Stanley Beaubien

Edwin Foekema

Vassiliki Gemeni

Karen Kirk

Julie Lions

Richard Metcalfe

Christophe Moni

Karon Smith

Michael Stevens

Julie West

Fotini Ziogou

A guide for assessing the potential impacts on ecosystems of leakage from CO 2 storage sites

Keywords: Leakage, ecosystem impacts, CO2 storage, risk assessment

Evidence to date indicates that leakage is of low probability if site selection, characterisation and storage project design are undertaken correctly. In Europe, the Storage Directive (EC, 2009) provides a legislative framework, implemented by Member States, which requires appropriate project design to ensure the storage of CO 2 is permanent and safe. However, it is incumbent on storage site operators to demonstrate an understanding of the potential impacts on surface ecosystems should a leak occur. The RISCS (Research into Impacts and Safety in CO 2 Storage) project has produced a Guide to potential impacts of leakage from CO 2 storage (the 'Guide'). RISCS assessed the potential effects of CO 2 leakage from geological storage on both onshore and offshore near-surface ecosystems and on potable ground water. This assessment was achieved through laboratory and field experiments, through observations at sites of natural CO 2 seepage and through numerical simulations. The Guide summarises some of the key findings of the project. The Guide provides information on the best approaches to evaluate potential impacts of hypothetical leakage from CO 2 storage sites and to provide guidance on appraising these impacts. This information will be relevant to regulators and operators in particular, but also to other stakeholders who are concerned with CO 2 storage, such as national and local governments, and members of the public.

Introduction

The Guide considers the potential impacts of leakage. This information could be used when assessing the potential risks during detailed project design, enabling specific aspects of the site characterisation to be planned. Once site selection and characterisation has been undertaken, the information provided by the Guide could be further used to develop environmental monitoring plans. Corrective measures plans (mitigation and remediation) and site closure plans might also benefit from consideration of the Guide. Regulators and other stakeholders might also use the Guide to assess the appropriateness of those plans. The Guide does not make specific recommendations for a formal Environmental Impact Assessment, although the information should be relevant for this type of assessment.

The assessment of environmental impacts will be a key feature of the design and permitting process for CO 2 storage projects, and will focus mainly on the potential impacts arising during the construction of infrastructure and during the routine operation of the storage site. Potential impacts arising from the leakage of CO 2 following injection may be considered as part of the assessments, as a regulatory requirement. The Guide specifically addresses potential impacts following leakage of CO 2 from geological storage; although similar impacts could also arise from leakage from pipelines, these have not, in general, been considered explicitly.

The RISCS project has specifically undertaken research into the potential impacts of leakage in a European regulatory context, in both terrestrial and marine environments of most relevance to Europe. However, some of the results obtained should be of wider relevance for similar environments elsewhere and under other regulations. The Guide and supporting research focussed on the impacts of leakage rather than the processes leading to leakage within the reservoir or caprock.

The RISCS project conducted a broad range of research to understand the possible impacts that might occur in the event of CO 2 leakage from geological storage systems. Issues relating to CO 2 injectivity, storage capacity and containment integrity were outside the project's scope. Similarly, the potential impacts of water or other formation fluids being displaced from the storage complex by injected CO 2 , even though the CO 2 does not itself leak from the storage complex, were also not considered, although it is noted that these impacts could potentially be significant. A significant amount of information is already known about the potential impacts of brine displacement from studies of aquifer salination.

Leakage Scenarios

Hypothetical leakage scenarios enable developers of a CO 2 storage project to:

1. Illustrate to stakeholders, including regulators, that the consequences of unexpected CO 2 leakage are understood; and thereby 2. Enable stakeholders to understand where impacts are insignificant and in what circumstances mitigation would be required.

Develop mitigation plans 4. Develop efficient monitoring strategies

These scenarios are needed because regulations require the possible impacts of leakage to be discussed while at the same time demonstrating that leakage has not been detected; the scenarios make no a priori assumptions about leakage probability.

Each leakage scenario defined here consisted of general descriptions of a reference environment, including its climatic conditions and/or water depth and salinity (in the case of marine scenarios) and kinds of ecosystems that occur. The 'receptors', which are those components of a reference environment that could be impacted by any CO 2 that were to leak, include biota and ground water aquifers that might be exploited for drinking water. The CO 2 leakage characteristics are defined in terms of the leakage pattern and consequential emission pattern (and quantity) at the surface of the solid earth, whether the CO 2 is a free phase or dissolved in water and the kind of dispersion of CO 2 after leaving the surface of the solid earth (in the case of aquatic environments).

The following scenarios were defined for leakage pathways in terrestrial environments:

• Normal Evolution Scenario (no leakage). This is expected to be the most likely scenario for the majority of storage sites where site characterisation and design have reduced the potential for leakage.

•

Direct release to the atmosphere, via a well (high flux for a relatively short time period -e.g. days); Diffuse release of CO 2 -charged water through the sediment and subsequently to the water column over a wide area.

Reference Environments

The Guide aims to build confidence among stakeholders such that, if the suitability of a particular European CO 2 storage site was to be assessed in the future, the potential impacts of any CO 2 leakage, if it occurs, can be evaluated and understood adequately. A related aim is to provide guidance on how these potential impacts can be evaluated. Given the expected large range in environmental characteristics between individual sites both on-and off-shore, it is impractical to investigate all possible kinds of sites in a generic study of the kind undertaken in RISCS. Consequently, the approach taken was to research potential impacts within a few different kinds of environments (henceforth termed 'generic environments') that collectively contain all the important features and processes that might cause leaking CO 2 , if present, to impact on sensitive domains above an actual storage site. It is likely that an actual CO 2 storage site will not be exactly like any of the generic environments. However, it is expected that the important features and processes that influence potential impacts within the actual storage site will occur within one or more of the generic environments. Consequently, by providing evidence to stakeholders that potential impacts within all the generic environments can be assessed adequately, the Guide will contribute to confidence among the stakeholders that potential impacts at the actual storage site can be assessed sufficiently. Similarly, based on experience gained by investigating and assessing potential impacts for the generic environments, techniques can be demonstrated that are appropriate for investigating and assessing potential impacts in any actual CO 2 storage site.

A small number of reference environments, including both marine and terrestrial examples have been defined (Table 1). The environments together explore a representative range of receptor classes within the two main broad categories, to give an indication of the range of features, events and processes that need to be considered when investigating potential impacts of CO 2 leakage.

Reference environments

Notes

Terrestrial Maritime temperate

Representative of a northern central European, cool climate (e.g. UK and the Netherlands). The region is highly developed and has some of the world's highest population densities. Potential environmental risks from CO2 leakage apply mainly to the root systems of agricultural crops, to soil microfauna or larger soil dwelling animals and to exploitable ground water supplies.

Continental

Climate associated with northern (but not Arctic) European continental land mass countries. The distribution of this environment corresponds broadly to the distribution of 'boreal forest' and extends as far north as the tree line. The environment is characterised by some of the lowest population densities in Europe. It also covers most of Sweden, Finland, and much of Norway.

Mediterranean

Representative of warmer, more arid, southern European climates. The tree, bush and dwarf shrub dominated habitat types (forest, scrub and heath lands) occupy more than half of the region's landscape. Dense forests occur mostly in plantations or in natural forests under humid conditions by wetlands or in valleys.

Generic urban

Specifically designed to explore potential impacts on humans should a storage system be located close to a large urban centre. At high concentrations, the principle risk is asphyxiation, particularly where CO 2 concentrations might increase in confined environments such as cellars. Detailed studies of the physiognomic effects of CO 2 are beyond the scope of this Guide and have not been considered in the RISCS project.

Marine

Cool, temperate, deep

Continental shelf remote from shoreline influences where the water depth is greater than 60 m, and typically over one hundred metres. Tides significantly influence mixing and currents but not water depth. The environment is not Arctic (no sea ice), but bottom water is cool (around 5°C). The moderately nutrient rich water is seasonally stratified, surface temperatures varying from around 4°C to around 15°C annually. Such an environment may be in the northern North Sea, or to the west of Norway south of the Arctic Circle.

Cool, temperate, shallow

Land is relatively close and the water depth is a few tens of metres. A comparatively large tidal range could cause significant changes in water depth and strong mixing. Some seasonal stratification may occur but normally the water column is fully mixed. The temperature varies from around 4°C to around 15°C annually. Nutrient rich (eutrophic) water may be impacted by riverine water. An example could be in the southern North Sea.

Warm shallow

Land is relatively close and water is a few tens of metres deep. The tidal range is small. Variable seasonal runoff from adjacent land masses may be significant. The temperature is a minimum of 5°C at the seabed and varies annually from 6°C to 25°C, with a mean of 10-12°C, at the sea surface. Such a site could be in the Adriatic Sea.

Low salinity (saline, but

Land is relatively close and water is a few tens of metres deep. The tidal range is small. Water salinity is much lower than that of open ocean water (which is present in the other lower than mean ocean salinity) marine environments), but varies depending upon the proximity of the coast and open ocean. Biodiversity is much less than in the open-ocean. Such an environment would be in the Baltic Sea.

Terrestrial Impacts

Baseline studies

Baseline studies need to cover the range of ecosystem and aquifer types within the project area and account for natural variability on different timescales (e.g. daily, seasonal, year on year). Results from the RISCS project suggest that the following should be included in baseline studies:

1. Soil gas concentrations and fluxes. The impacts of potential CO 2 leakages on ecosystems can only be evaluated if the baseline CO 2 soil gas concentrations and fluxes are available for any site. CO 2 soil gas concentrations above 10% may impact on terrestrial ecosystems. Thus CO 2 soil gas concentrations above this concentration that were detected during the site characterisation phase would require further investigation to establish the cause.

2. Plant surveys. Differences in sensitivity in different species have been observed at all the RISCS project sites with grasses generally being more resilient than other plant types. Plant stress is detected where CO 2 concentrations are above 10% at 30 cm depth in the soil, although this concentration is within measured levels in natural soils in some areas. Plant stress is manifested by discolouration of leaves (loss of chlorophyll). If exposure is stopped plants are likely to recover, but if exposure continues, plants are likely to die in less than four weeks. Additionally, poorly draining soils with high moisture content reduce CO 2 dispersal into the atmosphere. Thus baseline surveys should establish the land and agricultural use of a site, including the flora and soil type prior to any CO 2 injection. This would include any possible changes in crops in agricultural areas.

3. Soil microbiology surveys. Increased CO 2 concentrations have a complex impact on microbial populations which is difficult to interpret. Nevertheless, at sites where there has been prolonged exposure to high CO 2 concentrations, the microbial community has adapted to this environment with acidiphilic, anaerobic populations predominating. The RISCS project has not determined the significance of these changes with regard to soil fertility. Baseline studies could include an analysis of the microbial community present in the soil at a variety of depths so that any changes could be monitored in the event of leakage. Such analysis would be performed in areas of particular sensitivity, such as protected sites and would be undertaken once to establish baseline conditions, due to the expense of the surveys and the variable nature of microbial populations.

4. Ground waters. A good understanding of an aquifer will require knowledge of the geology (lithology of the aquifer) and hydrogeology (flow and hydrodynamics) but also the 'baseline' conditions of mineralogy and water chemistry prior to CO 2 injection. This will help identify the potential impacts on the potable ground water resource. Baseline monitoring of aquifers will be required in all reference environments where ground waters are used, or could be used in the future, for fresh water supply. Some of this monitoring may be undertaken already if the aquifer is used to supply drinking water.

a. Baseline monitoring of a drinking water aquifer prior to deep injection is strongly recommended, with a wide range of parameters being measured in different areas and over different seasons to ensure a complete characterisation of the chemistry and spatial and temporal variability of the aquifer. This could include all carbonate system parameters, major and trace elements, dissolved gases and redox level. For example, work at the Florina site has shown seasonal variability of ground water chemistry as a result of recharge rates in rainy versus dry periods of the year.

b. Mineralogical analyses of the aquifer are also desirable to aid in geochemical modelling and computer simulations of potential impacts, especially analyses of carbonate mineralogy for buffering capacity and of oxides for redox buffering and potential trace metal contents. The importance of site mineralogy was clearly shown at Latera and San Vittorino, where volcanic rock mineralogy at the former versus a carbonate mineralogy at the latter greatly influenced the level of impact and the specific changes in the water chemistry caused by the naturally-elevated CO 2 . At San Vittorino, the greater buffering capacity of the carbonate lithologies reduced the potential changes in ground water chemistry caused by the CO 2 .

c. Specialised geochemical analyses can greatly aid interpretation of water rock interactions, as demonstrated at Montmiral. In shallow ground waters at Montmiral, water-rock interactions were assessed to determine that the observed reactions were caused by water in contact with a biogenic CO 2 soil reservoir. Lack of interaction with gaseous CO 2 of a deep origin was also confirmed by the absence of a 18 O shift towards more negative values as observed for example in the neighbouring Massif Centrale. Accurate interpretation of the data from these baseline ecosystem studies will need to take into account other information including weather (such as temperature, precipitation and wind) and any other factors which might also impact on the health of the ecosystem.

Repeat baseline studies may need to be undertaken over a period of several years depending on regulatory demands and the seasonal variability at the site itself. Monitoring may be needed, for example, for between two and five years to sufficiently capture the expected range in natural variability. Indeed, it may be prudent to undertake baseline surveys over long periods to determine changes resulting from other factors such as land-use changes and climatic variations. For some parameters, like soil gas concentrations and fluxes, continuous monitoring stations can be deployed to better define long-term (e.g. seasonal) variability at key locations. These can be used to extend baselines into the injection phase of a storage project, provided that no leakage occurs, and could help to identify underlying longer term trends.

Seasonal effects on plants and near-surface ecosystems, such as changes due to temperature, precipitation, and/or day length will impact plant growth and activity. Thus there is limited benefit to monitoring of terrestrial ecosystems in the winter when growth is very limited because any impacts are unlikely to be detected, although near surface gas monitoring is often best in late autumn or winter when biological CO 2 production is at its lowest.

Plant response to increased CO 2 soil gas concentrations is very rapid. The threshold for observing responses appears to be at about 10% soil gas concentration at shallow depth (30 cm). Between 15-20% CO 2 at this depth, results indicate that broad-leafed plants become stressed within 7-14 days of exposure during the growing season and then die after a few weeks of continued exposure. However, plants with root systems that are well developed before exposure might be more resilient to subsequent increased CO 2 concentrations. For example, autumn-sown crops which were then exposed to CO 2 leakage in the following spring were less susceptible.

Although CO 2 leakages have the potential to cause large decreases in yields from crops with short growing periods, such decreases are likely to have little economic impact because leakages are most likely to take place over small areas. Indeed, impacts may not be detected until harvest. This must be viewed in the context of other environmental stressors (e.g. weather extremes, disease and pests) which are likely to have greater overall impacts on crop yield. For well-established pasture, the impacts of CO 2 leakage on yields for animal feed might also be minimal, though need to be evaluated carefully to establish whether there is a significant long-term (over several years) economic loss.

Recommendations for terrestrial sites made in the Guide

Ecosystem baseline surveys should be carried out at proposed storage sites to ascertain any changes resulting from leakage. These will also assist in Environmental Impact Assessments. It would also be beneficial if reference sites were similarly assessed and monitored so that any ecosystem changes attributed to CO 2 leakage can then be compared to changes at the control site. The significance of impacts from a credible leakage scenario on near surface ecosystems is expected to be very low, relative to other types of environmental damage such as climate change and extreme weather events. However, the significance of any leakage will depend on when it occurs (i.e. leakage during the growing season is likely to be more damaging than in winter) and its duration before detection and potential remediation. Additionally, marginal terrestrial environments, such as those with very short growing seasons, may be more sensitive to CO 2 leakage although this was not studied in the RISCS project. Consequently, it is important to take into account the context of leakage when assessing impacts on terrestrial ecosystems for a particular storage project. Storage projects should, as a minimum, undertake regular CO 2 soil gas evaluations at a variety of scales (metre to kilometre scale) and depths. It is not recommended to undertake ecosystem monitoring in the winter because ecosystems are much less active at this time. Initially, two to three surveys might be undertaken per year to define baselines although this will depend on land use. The RISCS project has shown that short term exposure to elevated CO 2 has no long term effects for many crops. Affected crops should either be allowed to grow until harvesting or should be replanted. The decision on the approach will depend on economic considerations and the timing of leakage. However, recovery in pasture and after long-term exposure to elevated CO 2 concentrations is unclear and it is recommended that further research is undertaken to clarify these uncertainties. Further research should be undertaken to understand the effects of ecosystem changes on soil fertility arising from elevated CO 2 soil gas concentrations. Research into the potential use of bio-indicators as quick monitoring techniques should also be carried out.

Marine Impacts

Baselines

The natural variation in pH can be significant over relatively small spatial and temporal scales, and in some cases diurnal signals can approach the magnitude of seasonal variability. Over an annual cycle the acidity in seawater will vary by 0.2-1.0 pH units (typically 0.3-0.4 pH units in shelf seas. Frontal systems and biological features such as blooms also give rise to significant spatial discontinuities. This variability is greatest in well-lit surface waters, where most of the primary production (photosynthesis) occurs. Primary production associated with benthic systems occurs only in shallow regions (<20 m) of relatively turbid waters like the North Sea but may occur at depths of up to 100 m in relatively clear waters (as found in some parts of the Mediterranean). At the benthic surface, where leakage signals are most likely to be apparent, the main biological process is respiration which can create locally significant increases in CO 2 .

If leaked CO 2 appears at the sea floor in gaseous form it will be buoyant and form a rising bubble plume. Concurrently, as CO 2 is highly soluble in seawater, it will dissolve rapidly. The RISCS project has not explicitly researched bubble plume dynamics, but relying on published information we can be confident that bubble plumes will generally dissolve within 10 m of the seafloor. Seawater with a high concentration of dissolved CO 2 has a higher density and will tend to sink relative to 'normal' seawater. This effect is likely to create a plume of higher CO 2 concentration near the sea bed over several tens to hundreds of metres from the source. As a result, most environmental impact is predicted to occur at the sea floor, to benthic communities and especially sessile, immobile biota.

Whilst the epicentre of a leak is likely to induce a pH significantly lower than found naturally, this might be confined to a small volume and be difficult to detect. The surrounding area affected by the leak will likely show deviations similar to that expected due to natural variability.

Impacts

The scale of biological effects that can be expected as a consequence of leaking CO 2 depends on the local biological situation, such as the presence of sensitive species/life stages and food availability. In addition, physical circumstances can play a role. In the warm shallow marine reference environment (such as the Mediterranean), there is some indication that temperatures make a difference to the impact from elevated CO 2 exposure on some marine organisms such as crabs. However this was not observed in the cool temperate shallow marine environment (such as the North Sea). However, it should be recognised that temperature changes can also have an indirect effect on habitat and species, by altering the balance between components of the food chain.

Populations that are already living under less favourable conditions (such as food and nutrient shortage, lower oxygen levels, sub-optimal salinity or temperature) are likely to be more vulnerable to the impact of elevated CO 2 concentrations than populations experiencing optimal environmental conditions. This will also be the case for populations that are exposed to anthropogenic pollutants, especially since some dissolved heavy metals become more toxic at lower pH values due to their increased bioavailability.

Apart from the sensitivity of the ecosystem during the leak, the vulnerability of an environment is also determined by the capacity to recover after the leak has been stopped. Simulations suggest that once the CO 2 flux is ended recovery to normal CO 2 levels can be expected, typically within days in the pelagic system, although less is known about the benthic system. This implies that an area that has been negatively impacted by a CO 2 leak is available for re-colonisation soon after the leak has been stopped. Therefore if the area that is potentially affected by a CO 2 leak is relatively small, in most situations unaffected populations of the affected species will be present in the neighbourhood. The majority of the sessile marine species have a high reproductive potential, often with planktonic larval stages that are widely distributed by water currents. It may therefore be expected that recovery of an affected community can occur rather quickly, at least with respect to species diversity. Evidently, it will take longer for longer living species to recover to the original age structure of the population. However, impacts on habitat-creating organisms, like deep sea coral reefs, might affect the whole community that depends on the reef structure as a habitat. Hence, recovery strongly depends on the degree of connection with other populations. The more isolated populations are, the longer it will take them to recover after the CO 2 leakage has been stopped.

CO 2 dispersion in seawaer

Dispersion of CO 2 plumes in seawater is a complex process. Initially highly buoyant gaseous CO 2 dissolves rapidly, forming potentially dense plumes of water containing higher concentrations of CO 2 that will tend to sink in the water column. Whilst local currents will determine the mean direction of a leakage plume, especially in cool temperate shallow and deep marine reference environments like the North Sea, tidal mixing is the main method of plume dispersion. Generally, tidal movement forces water masses in an elliptical pattern, accelerating dispersion. As shown below the resulting plume revolves around the leakage centre, with implications for both impacts and monitoring.

Model based studies indicate that dispersion can be relatively rapid so that only the neighbourhood of a leak event is likely to be strongly impacted (Figure 16), although this area could be metres or kilometres across, depending on the leakage rate. However, tides and currents will combine to make plume behaviour complex such that the CO 2 concentration and pH is prone to oscillate at any given point in space (Figure 17 and Figure 16). Deeper regions of shelf seas and most oceans stratify seasonally, i.e. when summer heating creates a warm less dense surface layer which does not mix with deeper waters. In such a case, any leaked CO 2 would be effectively trapped below the thermocline, with increased impacts on the benthic system.

Clearly any leakage event will be unique, and it is important to stress that the dispersion from any leak would depend on the flux rate, time of year, depth, tidal strength as well as local topography, the phase nature of the flux and its distribution on the sea floor. We have taken the approach of analysing a selected number of evidence based scenarios that cover the spectrum of leak possibilities, to define the scale of potential impact and broadly assess the areas and volume affected.

We elected to develop a small number of exemplar scenarios based on the leakage scenarios identified in the RISCS project, set into a typical cool temperate marine reference environment. The scenarios investigated included, amongst others, a continuous release of 4T d -1 , a temporary leakage of 9000T representing leakage from surface infrastructure and a continuous leakage of 1500 T d -1 . For convenience, we have adapted a regional model of the SW English Channel for our purposes, rather than attempt to mimic a specific site that has been identified for storage. Our domain provides conditions that are typical of the NW European shelf in terms of tidal strength and hydrodynamic properties, so that the results can be considered qualitatively transferrable to other regions on the shelf. Bespoke simulations for specific storage sites will require detailed information on local conditions and the explicit design of an appropriate model domain. Such information is available, but would require some dedicated effort.

Previous work suggests that the environmental conditions will have a strong bearing on the evolution of a leak, therefore each scenario has been tested in a range of tidally driven mixing regimes. Damping input flow velocity at the model boundary has been used to produce a weak, medium and strong flow regime with mean current velocities of 0.10 m/s, 0.14 m/s and 0.17 m/s, respectively. These are typical of offshore North Sea conditions.

Intensive water mixing in the area where the CO 2 is released will result in a wider area that is exposed to seawater with typically lower CO 2 concentrations than areas with less mixing or more stratification. This was illustrated during the seasonal sampling campaigns conducted at the natural CO 2 leaking site at Panarea, Italy. In deeper waters during summer, stratification of warm and cold water layers can occur, trapping the CO 2 enriched water near the bottom resulting in higher CO 2 concentrations than in non-stratified conditions. Other forms of stratification, such as those caused by salinity in fjords, which dominate much of the Norwegian coast, may also result in increased retention of CO 2 in the deeper waters. As the biological impact is rapidly reduced with increasing dilution, locations with intensive water mixing and little chance for stratification can thus be considered less sensitive to the impact of CO 2 leakage.

Site selection

In site selection, the effect of an unforeseen CO 2 leak must be minimised as much as possible. This can be realised by selecting sites with the following characteristics, in addition to the primary requirement to have a geological store that will permanently retain the injected CO 2 :

Regions of unusually low mixing of the water column might be avoided where possible, both from the point of view of dispersing leakage and aiding recovery by colonisation.

Regions with unusually heavy reliance on calcification as the basis of the ecosystem (e.g. cold water corals) or other unique and sensitive ecosystems should be avoided. The ecosystem should not be overly affected by other natural (e.g. low salinity, oxygen depletion, food shortage, etc.), or anthropogenic (pollutants) stressors. Once a site or region is identified for storage and the likely subterranean footprint of the reservoir complex known it is recommended that:

The sites chosen for storage are subject to rigorous baseline surveys, drawing on existing data, models and if necessary new observations. This should include the analysis of the normal co-variance of CO 2 , oxygen and temperature to aid monitoring interpretation. Bespoke simulations of leakage dispersal are made to identify optimal siting of monitoring equipment. An analysis of impact potential, based on the above, is developed. Assessment of impacts arising from potential leakage should also consider the cumulative and combined effects of a CO 2 leak as an addition to the stress induced by other marine activities.

Recommendations

Evidence to date indicates that leakage is of low probability if site selection, characterisation and storage project design are undertaken correctly. In Europe, the Storage Directive (EC, 2009) provides a legislative framework, implemented by Member States, which requires appropriate project design to ensure the storage of CO 2 is permanent and safe. The work undertaken in the RISCS project, including comparisons with other published results, allows us to draw the following high-level conclusions:

• Impacts from CO 2 leakage are expected to be small compared to impacts caused by other stressors. These additional stressors include, but are not limited to, changes in land use, extreme weather events, periods of abnormal weather and activities such as bottom trawler fishing; and the impacts that CCS seeks to mitigate such as climate change and ocean acidification.

• It is recommended that storage operators and relevant Competent Authorities demonstrate that an appropriate level of understanding has been developed of the potential impacts that might arise if a leak did occur from the specific site being considered for CO 2 storage.

• Evaluation of risks of leakage and potential impacts should be undertaken at each site, since each will have specific characteristics which will influence the nature and scale of the environmental response. The context of what specific impacts mean for a particular storage site (e.g. selection of crops) is fundamental and should be explained where relevant.

• The research undertaken in RISCS and reviewed research published elsewhere indicates that there are no reasons why a storage project could not be sited within any of the large-scale environmental types that have been studied here.

• Potential impacts will be further reduced by careful site selection and appropriate monitoring and mitigation plans.

• All monitoring programmes should use ecosystem evaluation techniques. Monitoring technologies and assessment methodologies have been developed and tested that allow the impacts of CO 2 in terrestrial and marine environments to be assessed.

• Indicator species that occur within specific onshore sites have been identified that can be monitored in conjunction with other environmental factors to assess the scale of an impact and the efficacy of any remediation.

Furthermore, it is concluded that:

• Carefully selected reference sites, both onshore and offshore, could be a powerful tool for providing ongoing baseline data against which storage sites can be compared. They would allow changes related to factors other than CO 2 leakage to be assessed. Sites managed via joint industry initiatives may be a suitable approach to enable a smaller number of reference sites to be developed for use by several storage projects.

• Evidence indicates that areas that might be affected by leakage will be localised. Individual seeps can be up to a few tens of metres across, and groups of these seeps might occur along fault zones. However, the total area of these seeps would still be a very small proportion of the area that might be used for CO 2 storage. This applies to onshore and offshore sites and includes potential impacts on ground waters. This implies that monitoring techniques able to detect leaks at these small scales over large areas should be deployed if leakage is suspected.

• Monitoring a number of parameters in addition to those directly indicative of CO 2 levels will help to separate natural variations in CO 2 content from leakage, such as measuring nitrogen, oxygen and isotopic contents of soil gas or recording temperature and dissolved oxygen in marine systems.

• Baseline surveys will be required and are a fundamental part of demonstrating site performance. Ecosystem baseline surveys should be carried out at proposed storage sites to ascertain changes resulting from any leakage. These will also assist in Environmental Impact Assessments. It would also be beneficial if reference sites were similarly assessed and monitored so that any ecosystem changes attributed to CO2 leakage can be compared to results from the non-injection site.

Specific recommendations for operators and regulators to consider are:

• Site-specific monitoring will aid confidence building and demonstrate that the duty of care for safe, permanent storage has been met appropriately.

• Baseline surveys should be designed to account for a full range of natural variation, which may occur over more than one year. Changes at the storage site due to other external factors should also be taken into account, for example through the use of reference sites. Communication of these baseline results to the local stakeholders (such as residents and NGO's) is advisable to create dialogue and increase knowledge of the natural system and its variability.

• Investigations for storage sites should include an assessment to determine whether the Conservation Objectives of Natura 2000 sites and any other protected areas are significantly affected by the project

Table 1

 1 Reference environments defined in the Guide.

• Leaks may have a cumulative, additional impact on ecosystems already stressed by other factors, such as low salinity marine environments, existing contaminated areas or marginal systems that are already restricted in their development.

• The timing and duration of the exposure will influence the scale of the impact. Timing is important because the stage of development of plants and animals affects their response, whilst the ecosystem in its entirety may be able to cope with enhanced CO 2 for a short duration.

• The scale of the likely impacts examined in the RISCS project means that they are considered manageable both by the ecosystem and by relevant stakeholders (operators and regulators).

• Offshore sites where mixing in the seawater column would allow dilution of CO 2 would be preferred because if a leak were to occur the natural mixing processes in the seawater could enhance dispersion and thereby minimise impacts. Similarly, onshore sites that avoid potential build up of CO 2 in confined areas would also be preferred, as under normal conditions light winds can quickly disperse any leaking CO 2 .

• Natural recovery in dynamic marine systems is expected to be relatively rapid i.e. mostly within one 'growing cycle' or season, due to the large pool of ecosystem resources and small scale of the impacted area, although this may not apply to all scales of leakage.

• In terrestrial systems, replanting of crops should be possible in affected areas once leakage has ceased, as no long term effects are expected based on experiments on crops. However the longer term recovery of pasture land has not been fully evaluated.

Acknowledgements

The Guide has greatly benefitted from the support, advice and review of a number of people within the RISCS project for which the authors are very grateful. In particular, Camilla Skriung of ZERO and Samuela Vercelli, of URS, have both been instrumental in ensuring the report meets with the requirements of the intended readership. Further advice and review was provided by the following, who the authors gratefully acknowledge: David Hilditch of the Cooperative Research Centre for Greenhouse Gas Technologies (CO2CRC), Lee Spangler of Montana State University, Tim Dixon of IEAGHG, Malcolm Wilson of University of Regina, Matt Baggaley and Tim Hill of E.ON New Build and Technology, Ines Koehler of Vattenfall, Alv-Arne Grimstad of Sintef, Thomas Thielemann of RWE, Tore Torp and Aina Janbu of Statoil.

The Guide has also been reviewed by a range of external stakeholders including representatives from relevant industries, environmental non-governmental organisations (NGOs) and some regulatory bodies, who the authors gratefully acknowledge.

The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 240837 and from industry partners ENEL I&I, Statoil, Vattenfall AB, E.ON and RWE.