The North-eastern Ecuadorian Amazon as a case study
General overview and importance of the study area
Ecuador is the fifth oil producer in Latin America (OECD, 2016). Ecuador has a five decades history of crude oil production, concentrated in the North-eastern Ecuadorian Amazon (NEA). However, the NEA is one of the most important biodiversity hotspot in the world (Bass et al., 2010): The NEA includes flora and fauna species representing high biodiversity even within Amazon basin intra-comparisons (Bass et al., 2010; Myers et al., 2000). At least, 210 mammals, 131 amphibians, 558 birds and more than 3,000 vascular plants species have been reported only in Yasuní National Park (Bass et al., 2010; Finer et al., 2008). Biodiversity is also important for the development of medicines (Chaudhary et al., 2015; Neergheen-Bhujun et al., 2017). The NEA is also home of eight indigenous populations: Kichwa, Waorani, Siona, Secoya, Cofán, Shuar, Tagaeri and Taromenane, among which the last two remain in voluntary isolation from western civilization.
Historically, the NEA is an important environmental study case as it has drawn attention of many scientists for decades in the fields of socio-ecological systems (Mena, 2008; Messina and Walsh, 2005; Walsh et al., 2008b) and complexity theory (Walsh et al., 2008a). This is notably because it is a historical high rate frontier deforestation setting (Messina et al., 2006; Sierra, 2000; Walsh et al., 2008a), where immigration pressures have played an important role (Holland et al., 2014; C. Mena et al., 2006), partially because of conflicts in land use practices between inhabitants with extensive agricultural practices vs. populations who use smaller and subsistence agriculture (Holland et al., 2014; Mena et al., 2006; Messina et al., 2006; Pan et al., 2004). These pressures are the result of oil driven development, which has extensively influenced road opening and consequent land use changes (Baynard et al., 2013).
The study area (Figure 4A) was restricted to the provinces of Sucumbíos and Orellana in the NEA (~144-900 m a.s.l., Amazon lowlands), representing a 35,051 km2 area (Figure 4B). This study excluded rivers with high flow rates (i.e., Napo, Tiputini, Coca, Payamino, Putumayo, Cuyabeno and Aguarico) where the surface waters and their interactions with groundwater are highly dynamic, therefore difficult or impossible to evaluate using scarce data.
Figure 4. Location of the study area. (A) The North-eastern Ecuadorian Amazon (NEA) in Ecuador, bordering Colombia in the North and Peru in the South. (B) The study area within the two NEA provinces of Sucumbíos and Orellana including major rivers and using as background a land cover mosaic, courtesy of GeoEye, Digital Globe, (2018). Represented human settlements are abbreviated: DAY= Dayuma; NL = Nueva Loja (aka Lago Agrio); SH = Shushufindi; TP = Tarapoa; PAC = Pacayacu; POM = Pompeya; PUT = Putumayo; COCA = Puerto Francisco de Orellana; JS = Joya de Los Sachas; YUT = Yuturi; DI = Dícaro; SIN = Singue; TP = Tiputini.
The study area is characterized by a warm climate with an annual temperature range of 20°C to 30°C, and an average annual rainfall of 2,900 mm.yr-1 (Institute of Meteorology and Hydrology-INHAMI). The hydrology regime is irregular with 1,000 to 5,000 m3.s-1 daily discharges, and characterized by flash floods, due to high sensitivity to rain events (Laraque et al., 2007). The Intertropical Convergence Zone (ITCZ) is responsible for complex atmospheric processes in the NEA, which is influenced by interchangeable wind direction throughout the year, i.e., north to southward direction from October to April and south to northward from May to September (Palermo and Parra, 2014).
Lithology and hydrogeology
Lithology refers to soil characteristics and properties. In the NEA region soils are mainly composed of three types (MAGAP-SIGTIERRAS and Tracasa-nipsa, 2015; Sourdat and Custode, 1982):
(i) Amazonian basin low plains in recent sedimentary rocks: well drained acidic montmorillonite and kaolinite clays of volcanic origin found over 600 m.a.s.l. These soils are low ancient rounded mountains formed by dissection of sedimentary banks of similar thickness and agglomerates, with slopes lower than 40%. Low fertility soils.
(ii) Amazonian basin low hilled modelled by ancient weathered sedimentary rock: heterogeneous drained sandy-silt mixed soils up to four meters over clay substrate of alluvial origin. These are most recent soils located lower than 600 m.a.s.l., with slopes lower than 10%.
(iii) Far Andean detritus material derived low-mountains: developed plains over sandy volcanic material between 300-900 m.a.s.l. clayed textures from the Tertiary, usually covered by forest or indigenous crop lands with low fertility.
Hydrogeological settings and properties indicate geological formations date from 5 to 56 million years ago (from the Eocene epoch to the Quaternary period). The NEA encompasses seven geological formations, where three possess pervious characteristics (Burbano et al., 2015):
(i) High permeability in alluvial lower plains containing sands and fluvial sediments.
(ii) Medium permeability in lime, sands pyroclastic lahars conglomerate formations.
(iii) Low permeability in mudstones, lime silty tidalites formations.
Thickness range from 150 to 548 meters (in locations where measures are available). Further non-exhaustive information on age, drainage directions and media composition of geological formation are detailed in Annex and Figure C.4.
Nature conservation measures
Probably it is not possible to explain the conservation measures of natural heritage implemented in the NEA without explaining the colonization process propelled by oil reserves discovered underneath the Amazonian forest. Two agrarian reforms, in 1964 and 1973, encouraged the colonization of forested lands in the NEA, as colonists engaged in forest clearing ensured title to lands (Holland et al., 2014). As a reaction to environmental degradation, several natural heritage sites have been declared by central government, Autonomous Local Governments (GADs), or have been community based or private owned (Ambiente, 2018). These conservation zones intended to regulate the socio-economic activities within geographical boundaries, notably via the protection of several environmental assets in the form of protected areas (PA). In 1979, Cuyabeno Fauna Reserve and Yasuní National Park, the largest Amazonian reserves most biologically and culturally diverse, were created to protect natural heritage (Ambiente, 2018). In 1981, the Ecuadorian Institute for Agrarian Reform and Colonization (IERAC) implemented a conservationist law named the Forestry Law. This law set the grounds for the network of natural heritage sites in Ecuador. In 1985, the wetland reserve of Limoncocha, fostering a lagoon with highly endemic aquatic fauna and flora, was created (Ambiente, 2018). According to Messina et al. (2006), the protection level of nature heritage has been successful at avoiding further deforestation in these areas (Figure 5).
However, the reshape of boundaries to allow oil production fields within several PA resulted in the establishment of the Patrimony Forest buffer zones. These zones limited but at less extent, the extractive industries, notably oil production (Mena et al., 2006). Patrimony Forest is an administrative category of lands where extractive activities are restricted and where land is communized, i.e., land titles are collective, impossible to be sold and managed by a collective entity; land usufruct rights are individual, can be transmitted and inherited but not sold (Mena et al., 2006). In addition, the GAD, are administrative divisions of the territory. GADs have jurisdictions at the local (parish16) and regional (province17) levels. GADs are entities that have certain autonomy to decide over the land use planning, have created several Protected Forests supported by international efforts to establish Biosphere Reserves, a heritage status awarded by the United Nations Educational, Scientific and Cultural Organization (UNESCO). Last but not least, the national initiative of the Socio-Bosque Program18 (2008) should also be cited. This initiative’s objective is to provide some monetary value to communities or individuals entitled land owners. The monetary incentives are given per hectare that is conserved, restored or managed under sustainable land use practices. Private or communal forested lands are eligible under the condition of maintaining the forest for at least twenty years and being outside of the system of protected areas (PSB-MAE, 2013). Table 4 indicates the main conservation events which were prompted to be declared for nature protection from increasing socio-economic activities, having oil production as main driver.
Oil activities in the NEA
In Ecuador, crude oil was discovered in 1937, with the prospecting activities by the Royal Dutch Shell Company, yet in 1960 the American Texaco started prospecting in the NEA. Actual production started only in 1967 with the American company Texaco, locally named Texpet in Nueva Loja19. Later, the production started for the giant oilfields of Nueva Loja and Shushufindi, and then for the Auca field. Seven operators20 were awarded contracts for the production of the NEA crude oil. In 1972 the state owned “Corporación Ecuatoriana de Petróleos del Ecuador” (CEPE), now PetroEcuador, was created. The first Trans-Ecuadorian crude oil pipeline (SOTE) connected the Amazon with the port of Esmeraldas, thus initiating the crude oil production famous period named the “oil boom of 1972-1982” (Acosta, 2006; Larrea, 2006). The revenues from crude oil exports doubled the per capita income and Ecuador became dependent on this primary commodity (Larrea, 2006). To summarize the long Ecuadorian crude oil history, three management time periods have been proposed, spanning five decades of oil production (Juteau et al., 2014). The time period are labelled hereafter as T1 from 1972 to 1992, T2 from 1992 to 2000 and T3 from 2001 onwards (Table 4).
Besides the numerous economic benefits of crude oil exports, these activities resulted in accidental or intentional pollution discharges as explained in section 1.3. These extractive activities may damage the environment, as well as the exposed local communities, who have claimed not benefiting from these revenues (Buccina et al., 2013; San Sebastián and Hurtig, 2005; SENPLADES, 2013). This resulted in the infamous long-term (1993-2018) Texaco trial (Buccina et al., 2013) (Figure 6). Some attempts to quantify the pollution discharge have been a matter of disputes between local communities and oil operators. For instance, between 1972 and 1992, different numbers of discharged amounts have been reported. The Programme of Environmental and Social Remediation (PRAS) reported a total of 505.6 kt. of poured crude oil (MAE-PRAS, 2016). The Amazon Defense Front21 (ADF) reported 6.6 Mm3 gas flared and 155 Mt crude oil spilled (Amazon Defense Front, 2008). 54.7 kt. crude oil and 96.8 Mt of produced waters were indicated by others (Kimerling, 1990). During the Remedial Action Plan (RAP) in 1995, only 158 pits have been alleged to be merely covered with a barren soil coating. Until 2013, more than 2,000 oil pits were documented, but only for 1,420 oil pits were measured and reported to have highly variable volumes (MAE-PRAS, 2016). These discharges may potentially contaminate ground waters that are used by the local communities (Barraza et al., 2018; Wasserstrom, 2013).
A few years after departing of Texaco, the indigenous communities formed the “Union de Afectados de la Amazonia” (Amazon Defense Front or ADF, by its abbreviation in English), whose purpose was to legally pursue the international oil firm due to alleged environmental pollution and related diseases, i.e., skin irritations, nauseas and headaches, increased cancer incidence and increased mortality (San Sebastián et al., 2001; San Sebastián and Hurtig, 2005). The ADF engaged in a long legal prosecution that aimed to repair the damages caused in this pristine area, estimated at a cost of US$18 billion. During the process, Texaco Inc. and Chevron Corp. were merged. The case continued for twenty five years, until an international court in The Hague, ruled in favour of the Chevron-Texaco firm in September, 2018 (BBC News, 2018).
The case was always conflicting around issues of the respective responsibility of the state owned company Petro-Ecuador and the Chevron-Texaco company. In fact, several issues may arise from the different management practices, monitoring and implemented technology regarding the upstream production chain quality, according to either state or private operators. It is unclear how private operators’ improvements are made, whereas state operators are more easily accounted, at least regarding oil spill prevention. Self-reported data is used in these claims and comparison between companies is very limited (Frynas, 2012).
T3 extends in practical terms, to the present day. More than 70% of oil production, corresponding to the majority of oil blocks, was assigned to Petro-Amazonas in 2018. Figure 7 shows main oil operators in the region as designated in 2018.
The thesis focuses mainly on T3, being the most recent period succeeding the establishment of hydrocarbon regulations25; and documentation that indicate the retrieved data is of improved quality and therefore more reliable to use for risk assessments, according to the National Secretary of Planning and Development in 2013 (SENPLADES, 2013).
To evaluate the importance of three key hazardous sources, a three question online-survey was conducted, regarding the perceived overall impact weight on societal, economical, health, and environmental assets. The first question was: “what is the relative weight of oil spills, gas flaring and oil pits as potential contaminating sources in the total pollution impact?” The working sector background of the people interviewed was the second question, formulated as: “In which sector do you work?”
All weights were measured on a scale from 1 (lowest) to 5 (highest). The resulting survey had 25 out of 100 respondents, corresponding to different activity sector stakeholders. The represented sectors were academia/research, non-governmental organizations, public governmental institutions and oil operators. The responses tended to give a similar weight to the different sources, i.e. oil pits were perceived as slightly more important (3.75), followed closely by oil spills (3.6) and gas flaring (3.4). The perception was that hazard sources weight do not vary significantly among them (Appendix A1) and there is lack of consensus between actors (Appendix A2), meaning that further in-depth surveys and other methods should be employed. In the meanwhile, the three sources should be investigated, as this survey suggests they are equally potential hazards to the NEA26.
26 See Appendix A for details on methodology and detailed results of this survey.
Thesis rationale and research questions
At least, two-thirds of the data used in this thesis were compiled from online public data, from the National Board of Hydrocarbons, and from the ANR-MONOIL and MAE-PRAS research collaboration agreement. Two assets were selected as case studies for environmental vulnerability assessment: (1) natural heritage and biodiversity, and (2) groundwater resources. This choice was made based on the relevance of these attributes of concern, in general (Al-Adamat et al., 2003; Gardner et al., 2009; Sala et al., 2000; Shrestha et al., 2017) and for the studied area (Barraza et al., 2018; Mena et al., 2006; Province GAD Orellana, 2011; Province GAD Sucumbios, 2013; SENPLADES, 2013; Wernersson, 2004). But this was also was guided by practical criteria: time and budget constraints, availability, accessibility and perceived completeness and quality of data.
The Ph.D. thesis is framed within the trans-disciplinary ANR-MONOIL project, in partnership with Ecuadorian institutions (MAE-PRAS, 2016; MONOIL, 2017) and the National Secretariat of Education, Science and Technology of Ecuador (SENESCYT). This thesis aims to answer three main questions:
1. What are the spatial and temporal variations of hazardous emissions at the sources of pollution? For this purpose, (i) oil spills, (ii) gas flaring discharges and (iii) deposited total petroleum hydrocarbons in unlined oil pits were estimated.
2. How can we map current environmental vulnerability levels based on (i) groundwater and (ii) natural heritage, including biodiversity, to address their spatial variations?
3. How can we implement ERA using quantitative estimates of oil hazards and environmental vulnerability, coupled with overlay-index methods? This was illustrated with the evaluated risk of unlined pits to groundwater.
In addition, an underlying problem is addressed throughout the chapters: How suitable are institutional public data for risk assessments in developing countries?
For this purpose, hazards from oil infrastructure first had to be evaluated. Oil spills, unlined oil pits and flaring equipment have been considered. The hazards were assessed through the estimation of emissions at the pollutant source, in other words, at each oil infrastructure that is potentially capable of accidental or intentional release of pollutants. The frequencies and amounts of these emissions had not been previously estimated across the NEA. They needed to be addressed, before any subsequent hazard or exposure evaluation could be intended. The thesis has been divided in four chapters:
Chapter II, is entitled “Spatial inventory of selected atmospheric emissions from oil industry in Ecuadorian Amazon: insights from comparisons among satellite and institutional datasets”, is a submitted publication that encompasses flaring infrastructure hazards. It is perceived as a high hazard due to the constant release of gases and particulate aerosols into the atmosphere.
Chapter III, is dedicated to environmental vulnerability, specifically the perceived important asset of biodiversity and natural heritage. The challenge of scoring, rating and spatially indexing the vulnerability of this asset is apprehended and discussed. Its title is “Spatial vulnerability assessment of natural heritage and biodiversity using current land use cover and nature protection levels”.
Chapter IV is a publication in preparation that apprehends the last component of an ERA, the combination of indexed vulnerable assets and hazard from crude oil production to provide risk maps. There are many combinations that could be evaluated. Due to time limitation, the risk assessment was exemplified using only one environmental asset, but another important one: groundwater. It was scored, weighted and indexed spatially, and then combined with the unlined oil pit spatial distribution which logically appeared as the most likely to contaminate groundwater. The title of this final chapter is then “Risk assessment of unlined oil pits to groundwater in Ecuadorian Amazon: A modified GIS-DRASTIC approach”.
Table of contents :
1. Introduction générale (version abrégée en français)
1. General Introduction
1.1 Risk associated to oil and gas activities
1.1.1. The concept of risk
1.1.2. Risk Assessment
1.1.3. Environmental risk assessment for crude oil activities
1.2. The North-eastern Ecuadorian Amazon as a case study
1.2.1. General overview and importance of the study area
1.2.2. Biophysical characteristics
1.2.3. Lithology and hydrogeology
1.2.4. Nature conservation measures
1.2.5. Oil activities in the NEA
1.3. Thesis rationale and research questions
Chapter I – Spatial analysis of accidental oil spills using heterogeneous data: a case study from the north-eastern Ecuadorian Amazon
I.2. Materials and Methods
I.2.1. Study area
I.2.2. Data for crude oil spills
I.2.3. Accounting for heterogeneity in data quality: well- vs. poorly-documented oil blocks
I.2.4. Calculating the oil spill rates to be used for estimations on poorly-documented blocks
I.2.5. Oil spill mapping
I.2.6. Validity of the procedure to estimate oil spills on poorly-documented blocks
I.3.1. Oil spills: temporal and spatial patterns
I.3.2. Reliability of the procedure used to estimate missing data
I.4.1. Uncertainties and data quality
I.4.1.1. Data reporting
I.4.1.2. Spill estimates
I.4.2. Accuracy of oil spill estimations
I.4.3. Spatial distribution of spills and hazard potential
I.4.4. Potential economic, health, and environmental losses
Chapter II – Spatial inventory of selected atmospheric emissions from oil industry in Ecuadorian Amazon: insights from comparisons among satellite and institutional datasets
II.2. Materials and Methods
II.2.1. Study Area
II.2.2. Data for atmospheric emissions and comparisons
II.2.3. Emission processing and calculations
II.2.3.1. Gas flaring
II.2.3.2. Black carbon
II.2.4. Atmospheric emission mapping
II.2.5. Carbon dioxide and methane
II.2.5.1. Estimating variations based on percentile change in key parameters
II.3.1. Gas flaring and black carbon emissions according to publicly available data
II.3.2. Estimates of this study compared to other datasets
II.3.3. Mapping of airborne black carbon emissions at a regional scale
II.3.4. Greenhouse gas estimates
II.4.1. Data reporting
II.4.2. Emission estimates
II.4.2.1. Black carbon
II.4.2.2. Greenhouse gases
II.4.3. Comparison of emission sources
II.4.3.1. Single flare stacks from various countries
II.4.3.2. Institutional and satellite datasets
II.4.3.3. Across activity sectors
II.4.4. Potential economic, health, and environmental losses
Chapter III – Vulnerability assessment of natural heritage and biodiversity in the North-eastern Ecuadorian Amazon using land use cover and nature protection status.
III.2. Materials and Methods
III.2.1. Study area
III.2.2. Data compilation
III.2.3. Vulnerability assessment
III.2.3.1. Assessing ecological integrity vulnerability
III.2.3.2. Assessing biodiversity vulnerability
III.22.214.171.124. Calculating biodiversity value from land use types
III.126.96.36.199. Validity of the relationship between biodiversity and land use
III.2.4. Standardisation and combination of vulnerability values
III.3.1. Biodiversity vulnerability map obtained from land use
III.3.1.1. Species richness across land use categories in tropical regions
III.3.1.2. Relative vulnerability values across the landscape
III.3.2. Ecological integrity vulnerability map obtained from protection status
III.3.3. Relationships between vulnerabilities derived from the different metrics.
III.4.1. Relevance of protection status in vulnerability assessment
III.4.2. Biodiversity and land use
III.4.3. Implications for spatial planning and conservation policies
III.4.4. Caveats of the study and steps forward
Chapter IV – Risk assessment of unlined oil pits to groundwater quality in the Ecuadorian Amazon: A modified GIS-DRASTIC approach
IV.2. Materials and Methods
IV.2.1. Study area
IV.2.2. Compiling database for the modified DRASTIC index
IV.2.3. Intrinsic vulnerability: indexing and mapping
IV.2.3.1. Water-related parameters
IV.188.8.131.52. Hydrogeological settings and aquifer media
IV.2.3.2. Soil-related parameters
IV.2.4. Sensitivity analysis
IV.2.5. Hazard assessment: estimating volumetric properties of pits
IV.2.5.1. Estimation of TPH content in pits
IV.2.5.2. Propagation of hydrocarbons at a regional scale
IV.2.6. Contamination risk mapping: hazard overlaid with vulnerability
IV.3.1. Influence of single groundwater parameters to overall vulnerability
IV.3.2. Impact of parameter removal and assigned weights on vulnerability index variations
IV.3.3. Risk mapping: spreading contamination in groundwater vulnerability zones
IV.4.1. Components of risk: vulnerability and hazard
IV.4.1.1. Groundwater vulnerability
IV.4.1.2. Impact of hazard assessment in overall risk
IV.4.2. Land use planning implications
IV.4.3. Limitations and further adaptations
Chapter V – General discussion
V.1. The significance of the risk assessment approach
V.2. Spatial emission inventories
V.3. From the general concept of vulnerability to its ecological specificities
V.4. Groundwater vulnerability as a case study for risk assessment
V.5. Towards integrated ERA
V.5.1. Further assessment of environmental assets
V.5.2. Selection of alternative assets for vulnerability evaluation
V.5.3. Insights for land use planning implications: towards adaptive capacity management
V.6.1. Towards incorporating components for overall vulnerability: environmental resilience
V.6.2. Towards incorporating components for overall vulnerability: Societal assets
V.6.3. Transport models and validation
VI. – Conclusion
VI. – Conclusion en français