Centro de Investigación para el Territorio y el Hábitat Sostenible
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War Impact on Air Quality in Ukraine

2022 , Zalakeviciute, R. , Mejia, D. , Alvarez, H. , Bermeo, X. , Bonilla Bedoya, Santiago , Rybarczyk, Y. , Lamb, B.

In the light of the 21st century, after two devastating world wars, humanity still has not learned to solve their conflicts through peaceful negotiations and dialogue. Armed conflicts, both international and within a single state, still cause devastation, displacement, and death all over the world. Not to mention the consequences that war has on the environment. Due to a lack of published research about war impact on modern air quality, this work studies air pollution evolution during the first months of the Russian-Ukrainian conflict. Satellite images of NO2, CO, O3, SO2, and PM2.5 over Ukrainian territory and PM2.5 land monitoring data for Kyiv were analyzed. The results showed that NO2 and PM2.5 correlated the most with war activities. CO and O3 levels increased, while SO2 concentrations reduced four-fold as war intensified. Drastic increases in pollution (especially PM2.5) from bombing and structural fires, raise additional health concerns, which might have serious implications for the exposed local and regional populations. This study is an invaluable proof of the impact any armed conflict has on air quality, the population, and environment. © 2022 by the authors.

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Urban soil management in the strategies for adaptation to climate change of cities in the Tropical Andes

2022 , Bonilla Bedoya, Santiago , Ángel Herrera, M. , Vaca, A. , Salazar, L. , Zalakeviciute, R. , Mejía, D. , López-Ulloa, M.

The unique characteristics of a city amplify the impacts of climate change; therefore, urban planning in the 21st century is challenged to apply mitigation and adaptation strategies that ensure the collective well-being. Despite advances in monitoring urban environmental change, research on the application of adaptation-oriented criteria remains a challenge in urban planning in the Global South. This study proposes to include urban land management as a criterion and timely strategy for climate change adaptation in the cities of the Tropical Andes. Here, we estimate the distribution of the soil organic carbon stock (OCS) of the city of Quito (2,815 m.a.s.l.; population 2,011,388; 197.09 km2) in the following three methodological moments: i) field/laboratory: city-wide sampling design established to collect 300 soil samples (0–15 cm) and obtain data on organic carbon (OC) concentrations in addition to 30 samples for bulk density (BD); ii) predictors: geographic, spectral and anthropogenic dimensions established from 17 co-variables; and iii) spatial modeling: simple multiple regression (SMRM) and random forest (RFM) models of organic carbon concentrations and density as well as OCS stock estimation. We found that the spatial modeling techniques were complementary; however, SMRM showed a relatively higher fit both (OC: r2 = 20%, BD: r2 = 16%) when compared to RFM (OC: r2 = 8% and BD: r2 = 5%). Thus, soil carbon stock (0–0.15 m) was estimated with a spatial variation that fluctuated between 9.89 and 21.48 kg/m2; whereas, RFM showed fluctuations between 10.38 and 17.67 kg/m2. We found that spatial predictors (topography, relative humidity, precipitation, temperature) and anthropogenic predictors (population density, roads, vehicle traffic, land cover) positively influence the model, while spatial predictors have little influence and show multicollinearity with relative humidity. Our research suggests that urban land management in the 21st century provides key information for adaptation and mitigation strategies aimed at coping with global and local climate variations in the cities of the Tropical Andes. © 2022 Elsevier B.V.

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Urban soils as a spatial indicator of quality for urban socio-ecological systems

2021 , Bonilla Bedoya, Santiago , López-Ulloa M. , Mora-Garcés A. , Macedo-Pezzopane J.E. , Salazar L. , Herrera M.Á.

The development of criteria and indicators to quantify the transition to sustainability of the urban socio-ecological systems quality is determinant for planning policies and the 21st century urban agenda. This study models the spatial variation in the concentration and distribution of some macronutrients, micronutrients, and trace nutrients in the soil of a high-altitude city in the Andes. Meanwhile, machine learning methods were employed to study some interactions between the different dimensions that constitute an urban socio-ecosystem that caused these variations. We proposed a methodology that considered two phases: a) field work to collect data on 300 soil samples; laboratory analysis to measure the concentrations of 24 macronutrients, micronutrients, and trace nutrients; and the design of geophysical, spectral, and urban co-variables; b) statistical and geo-informatics analysis, where multivariate analysis grouped the elements into factors; and, machine learning integrated with co-variables was applied to derive the intensity of each factor across the city. Multivariate statistics described the variation in soil co-concentrations with a moderate percentage (42%). Four factors were determined that grouped some of the analyzed elements, as follows: F1 (Zn, S, Cu, Pb, Ni, and Cr), F2 (Ba, Ag, K, In, and Mg), F3 (B, V, Li, and Sr), and F4 (Si and Mn). The percentage R2 out-of-bag of the spatial model were: F1 = 20%, F2 = 8%, F3 = 14%, and F4 = 10%. Our outputs show that the enrichment and contamination by anthropogenic factors, such as the increase in population density, land use, road network, and traffic generated by fossil fuel vehicles, should be prioritized in urban planning decisions. © 2021

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Exploring Wardriving Potential in the Ecuadorian Amazon for Indirect Data Collection

2021 , Santos F. , Pesantes P. , Bonilla Bedoya, Santiago

Digital inclusion in the Ecuadorian amazon is known as a problem, which intensified with the pandemic. Since social distance is now the norm, we constructed a WiFi access point (WAP) scanner to map and analyze its data. We correlated it with ancillary geoinformation to observe its potential and limitations as a method for indirect data collection. Our result indicate that WAP correlate weakly but positively with nightlight, young population, accessibility to economical centres, and negatively with slope. Moreover, we differentiated vulnerability naming patters from Service Set Identifiers (SSDI) and differentiated the number of WAPs according to land cover for differentiate urban from rural areas. This output is now offering increasing applications to get updated rought estimates of internet activity and indirectly correlations to socio-economic conditions, technology practices, and opportunities for natural language processing. Therefore, we conclude that wardriving offer interesting opportunities for mapping social data but also concerns as an indirect data collection method. © Published under licence by IOP Publishing Ltd.

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Mapping 50 years of contribution to the development of soil quality biological indicators

2023 , Bonilla Bedoya, Santiago , Valencia K. , Herrera M.Á. , López-Ulloa M. , Donoso D.A. , Macedo Pezzopane J.E.

Biological indicators of soil quality express the capacity of a soil to maintain its ecosystem functions and services between socio-ecosystem inflection thresholds; therefore, they are determinants in management and land use decisions. However, their development until a few decades ago was limited for several reasons: reductionism and early development of other dimensions, such as physical and chemical indicators or their methodological complexity, thus affecting the importance given to biological factors and the integral evaluation of soil quality or health. Thus, this review presents a mapping of the scientific contributions of the last 50 years oriented to the theoretical and methodological development of biological indicators of soil quality, identifying their development and application in these decades. We conducted a bibliometric analysis that allowed us to present an overview of the field with respect to scientific production: temporality, geographical origin, institutional origin, journals that promote the development of the field, articles with greater influence by citation in the field of study, and the co-occurrences of these indicators in research. This analysis was complemented at the second stage by a systematic review of the literature with the greatest impact by citation. We found 2320 scientific papers distributed mainly in the United States (17.8%), China (12.2%), Brazil (8.3%), India (6.3%), and European Mediterranean countries, such as Spain, France, and Italy (14.2%). Our review showed 25 biological indicators with the highest occurrence; for example, microbial biomass (1 1 8), enzymatic activity (90), and organic matter (78); other indicators, such as earthworms, nematodes, or springtails, are also reported. All indicators showed relationships, to a greater or lesser extent, with soil biodiversity and its functions in the landscape. Important advances in soil indicators have developed gradually in the last few decades, with scientific efforts mainly concentrated in developed and emerging countries. In the last decade, the production curve continues with a growth trend., and research questions in the field revolve around the linkage of diversity and function from a molecular point of view. The scope goes beyond productivity, manifesting the real need to conserve and manage the ecosystem services of a limited and non-renewable natural resource. Pioneering research should begin to report on the scope of soil biological monitoring and its influence on policy, management, and land use. Finally, the promotion of research networks with developing countries can foster the development of regional and local soil monitoring policies in these regions. © 2023 The Author(s)

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Sentinel satellite data monitoring of air pollutants with interpolation methods in Guayaquil, Ecuador

2023 , Mejía C. D. , Alvarez H. , Zalakeviciute R. , Macancela D. , Sanchez C. , Bonilla Bedoya, Santiago

In Ecuador, there is a limitation on air quality monitoring due to the cost of monitoring networks. Although air quality monitoring stations are instruments for air measurement, they do not cover an entire city due to their scope. Satellite remote sensing is now an effective tool to study atmospheric pollutants and has been applied to continuously assess a region and overcome the limitations of fixed stations. Despite the application of satellite data for air quality monitoring, there are some limitations, such as measurement frequency, cloud cover and wide spatial resolution, which do not allow the assessment of air pollution in cities. Therefore, downscaling, applying interpolation methods, is essential for continuous air quality monitoring at smaller scales. For this research, Nitrogen Dioxide (NO2) data from the Sentinel-5 satellite percussor was used in the city of Guayaquil for January–December 2020, which is considered before, during and after the COVID-19 quarantine. This mid-size port city does not have a permanent monitoring network, which prevents us from knowing the air quality. Due to the limitation of pixel size, this study used satellite data to apply interpolation techniques and reduce pixels to assess air quality. Two categories of interpolation were selected: deterministic and stochastic. The empirical Bayesian kriging (EBK) interpolation obtained a R2 of 0.9546, which was superior to the other methods applied. Therefore, the EBK method had the best accuracy for tropospheric NO2 concentration. Finally, the method used in this research can help monitor air quality in cities lacking continuous monitoring networks, as the reduction of the pixel size gives us a better pattern of pollutants. © 2023 The Authors

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Distinguishing original and non-original stands at the zhanjiang mangrove national nature reserve (P.r. china): Remote sensing and gis for conservation and ecological research

2021 , Durango-Cordero J. , Satyanarayana B. , Chan J.C.-W. , Bogaert J. , Dahdouh-Guebas F.

The present research developed a novel methodological framework to differentiate natural mangrove stands (i.e., original), from stands which were planted and stands naturally established after interaction between planted and non-planted stands (e.g., through pollination, i.e., non-original). Ground-truth and remote sensing data were collected for Zhanjiang Mangrove National Nature Reserve (ZMNNR) in P.R. China. First, satellite images of Corona (1967) and GeoEye-1 (2009) were overlaid to identify original (1967) and non-original (2009) mangrove stands. Second, in both stands a total of 75 in situ plots (25 m2) were measured for ground-truthing of tree structural parameters including height, density, basal area and Complexity Index (CI). From temporal satellite data, we identify 236.12 ha of original mangrove and 567.88 ha of non-original mangrove in the reserve. Averaged measurements of the original mangrove stands, i.e., stem density (1164 nos. 0.1 ha−1), basal area (90.3 m2 0.1 ha−1) and CI (100.59), indicated that they were in a state of maturity and less disturbed compared to the non-original mangroves (density, 1241 nos. 0.1 ha−1; basal area, 4.92 m2 0.1 ha−1 and CI, 55.65). The Kruskal–Wallis test showed significant differentiation between the original and non-original mangrove tree structural parameters: Kandelia obovata’s density, X2 = 34.78, d.f. = 1, p = 0.001; basal area, X2 = 108.15, d.f. = 1, p = 0.001; Rizhopora stylosa’s density, X2 = 64.03, d.f. = 1, p = 0.001; basal area, X2 = 117.96, d.f. = 1, p = 0.001. The latter is also evident from the clustering plots generated from the Principal Component Analysis (PCA). Vegetation dynamics at the ZMNNR also enabled us to compare the species composition and distribution patterns with other Indo-West Pacific regions. Overall, the present study not only highlights the advantage of >50 years old satellite data but also provide a benchmark for future ecological research, conservation and management of the ZMNNR. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

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The effect of national protest in Ecuador on PM pollution

2021 , Zalakeviciute R. , Alexandrino K. , Mejia D. , Bastidas M.G. , Oleas N.H. , Gabela D. , Chau P.N. , Bonilla Bedoya, Santiago , Diaz V. , Rybarczyk Y.

Particulate matter (PM) accounts for millions of premature deaths in the human population every year. Due to social and economic inequality, growing human dissatisfaction manifests in waves of strikes and protests all over the world, causing paralysis of institutions, services and circulation of transport. In this study, we aim to investigate air quality in Ecuador during the national protest of 2019, by studying the evolution of PM2.5 (PM ≤ 2.5 µm) concentrations in Ecuador and its capital city Quito using ground based and satellite data. Apart from analyzing the PM2.5 evolution over time to trace the pollution changes, we employ machine learning techniques to estimate these changes relative to the business-as-usual pollution scenario. In addition, we present a chemical analysis of plant samples from an urban park housing the strike. Positive impact on regional air quality was detected for Ecuador, and an overall − 10.75 ± 17.74% reduction of particulate pollution in the capital during the protest. However, barricade burning PM peaks may contribute to a release of harmful heavy metals (tire manufacture components such as Co, Cr, Zn, Al, Fe, Pb, Mg, Ba and Cu), which might be of short- and long-term health concerns. © 2021, The Author(s).

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Risk assessment of unlined oil pits leaking into groundwater in the Ecuadorian Amazon: A modified GIS-DRASTIC approach

2022 , Durango-Cordero J. , Saqalli M. , Ferrant S. , Bonilla S. , Maurice L. , Arellano P. , Elger A.

This study evaluates the risk of groundwater contamination from unlined oil pits, in the Northern Ecuadorian Amazon (NEA). Applying spatial analysis, several maps were provided for its integration in land use planning, public health improvement and future site-specific investigations. Two main maps were produced: (1) a vulnerability indexed map using a modified DRASTIC model and (2) a hazard map based on the past (1995–1997) and present (2018) contamination using a weighted density equation. The hazard was derived from hydrocarbon contained in oil pits associated with a cost-distance analysis to obtain different maximum distance ranges (MDR), to model the surface of potentially impacted groundwater. The results indicate a total calculated hydrocarbons of 39 052 tons. A MDR from 500–10 000 km was retained to map aquifers at risk, the maximum surface potentially at risk covers 13% of the NEA, while 83% of the area represents low to medium-low vulnerability. This study led to several recommendations, such as the level of suitability of the available information, and what gaps should be filled to improve future research. A surface of 271–766.5 km in the 500-2000-m distance range should be prioritised for finer scale risk assessment. © 2021 Elsevier Ltd

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Socioecological system and potential deforestation in Western Amazon forest landscapes

2018 , Bonilla Bedoya, Santiago , Estrella-Bastidas A. , Molina J.R. , Herrera M.Á.

The ecosystem services provided by tropical forests are affected by deforestation. Territorial management strategies aim to prevent and mitigate forest loss. Therefore, modeling potential land use changes is important for forest management, monitoring, and evaluation. This study determined whether there are relationships between forest vulnerability to deforestation (potential deforestation distribution) and the forest management policies applied in the Ecuadorian Amazon. Proxy and underlying variables were used to construct a statistical model, based on the principle of maximum entropy that could predict potential land use changes. Entropy can be seen as a measure of uncertainty for a density function. Receiver operating characteristics (ROC) analysis and the Jackknife Test were used to validate the model. The importance of input variables in the model was determined through: Percent Contribution (PC) and Permutation Importance (PI). The results were compared with prevailing regional forest management strategies. The socioeconomic variables that provided the largest amount of information in the overall model (AUC = 0.81) and that showed most of the information not present in other variables were: “Protected areas-Intangible zone” (PC = 24%, PI = 12.4%), “timber harvesting programs” (PC = 21.7%, PI = 4.7%), “road network” (PC = 18.9%, PI = 7.7%), and “poverty rate” (PC = 3.7%, PI = 6.1%). Also, the biophysical variable “temperature” (PC = 7,9%, PI = 22.3%) provided information in the overall model. The results suggested the need for changes in forest management strategies. Forest policies and management plans should consider integrating and strengthening protected areas and intangible zones, as well as restricting timber harvesting in native forest and establishing forest areas under permanent management. Furthermore, the results also suggested that financial incentive programs to reduce deforestation have to be evaluated because their present distribution is inefficient. In this context, conservation incentive plans need to be revised so that they focus on areas at deforestation risk. © 2018 Elsevier B.V.

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