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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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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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Gradient boosting machine to assess the public protest impact on urban air quality

2021 , Zalakeviciute R. , Rybarczyk Y. , Alexandrino K. , Bonilla Bedoya, Santiago , Mejia D. , Bastidas M. , Diaz V.

Political and economic protests build-up due to the financial uncertainty and inequality spreading throughout the world. In 2019, Latin America took the main stage in a wave of protests. While the social side of protests is widely explored, the focus of this study is the evolution of gaseous urban air pollutants during and after one of these events. Changes in concentrations of NO2, CO, O3 and SO2 during and after the strike, were studied in Quito, Ecuador using two approaches: (i) inter-period observational analysis; and (ii) machine learning (ML) gradient boosting machine (GBM) developed business-as-usual (BAU) comparison to the observations. During the strike, both methods showed a large reduction in the concentrations of NO2 (31.5–32.36%) and CO (15.55–19.85%) and a slight reduction for O3 and SO2. The GBM approach showed an exclusive potential, especially for a lengthier period of predictions, to estimate strike impact on air quality even after the strike was over. This advocates for the use of machine learning techniques to estimate an extended effect of changes in human activities on urban gaseous pollution. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

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Modelling the relationship between urban expansion processes and urban forest characteristics: An application to the Metropolitan District of Quito

2020 , Bonilla Bedoya, Santiago , Mora A., Vaca A. , Estrella A. , Herrera M.Á.

The rapid process of global urbanisation engenders changes in urban socio-ecological systems and in the landscape structure. However, the future processes of urban expansion in Latin American cities has been little studied even though the wellbeing of its citizens will depend on territorial management and on planning the provision of ecosystemic benefits and services. This research, considering different socio-ecological dimensions, proposed to determine the causes of potential urban expansion, analysing the dimensions and possible predictors that would explain the expansion of a high Andean city and its influence on peri-urban forest landscapes. To develop a model that integrates the complexity of the system, we used the following five dimensions: biophysics, land cover and management, infrastructure and services, socio-economics, and landscape metrics, and we opted for a binomial analysis through a spatial logistic regression model developed from 33 predictors. Considering the odd radio of the model, we observe that the independent increase in predictors, including building blocks, drinking water, sewerage, waste collection, average land size, the Interspersion and Juxtaposition Index (IJI) and Largest Patch Index (LPI), and the constant behaviour of the others predictors, would increase the probability of a potential urbanisation of the territory. Similarly, the independent increase in predictors, including the presence of protected areas, the presence of protected forests, land cover, unemployment, and the Shannon Diversity Index(SHDI), reduce the probability of the urbanisation process. Our results suggest that the territorial vulnerability from a potential urbanisation process is strongly related to an increase in infrastructure, services, and the average size of properties variables. Moreover, the landscape with the greatest potential for urbanisation presents an adequate intercalation of the different patches that compose it. However, the presence of variables such as protected areas and protective forests, in addition to monitoring indicators such as landscape diversity and mitigation strategies, could be considered to focus the analysis on the current dynamics of urbanisation processes in Latin America. © 2019 Elsevier 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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Urban socio-ecological dynamics: applying the urban-rural gradient approach in a high Andean city

2020 , Bonilla Bedoya, Santiago , Estrella A. , Vaca Yánez A. , Herrera M.Á.

The urban-rural dichotomy and the simple cause-effect relationship do not allow establishing specific criteria for territorial management from a socio-ecological perspective. The gradient approach could be a powerful tool to understand urban socio-ecological dynamics. This research applied a methodological protocol to obtain urban-rural gradients while considering the specific characteristics of a mid-size Andean city. To achieve this goal, a mixed classification process was applied to a Landsat 8 image. Subsequently, a factor analysis (FA) grouped 25 urbanisation variables. Finally, we applied agglomerative hierarchical clustering. FA established four factors that explained (72%) of the urbanisation metrics’ variation. From this information, we obtained factor maps and a gradient map. The resulting map differentiated six gradients that contrast with the city’s territorial planning based on the urban-rural dichotomy. This study is a starting point to apply the gradient approach in land-use management and urban ecology planning for Andean cities. © 2019, © 2019 Landscape Research Group Ltd.

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Patterns of timber harvesting and its relationship with sustainable forest management in the western Amazon, Ecuador case

2017 , Bonilla Bedoya, Santiago , Estrella-Bastidas A. , Ordoñez M. , Sánchez A. , Herrera M.A.

The Amazon rainforest lies within the most diverse forest ecosystem in the world. However, a large part of the tropical rainforest is being degraded because of timber harvesting without any sustainability criteria and owing to a limited understanding of the effects of forest exploitation. The Ecuadorian Amazon (EA) is part of the Andes Amazon (AA), an area covered by five countries (Venezuela, Colombia, Ecuador, Peru and Bolivia). This research identified the patterns of legal timber harvesting in the EA and determined current trends with respect to mostly harvested forest species. Two harvesting programs aimed at small farmers prevail in the EA: first, naturally regenerated trees felling program, and simplified timber harvesting programs in native forests. Considering the surface and volume of logging, significant differences were detected between logging procedures and ecosystems in the region. Two hundred and thirty-two genera are registered for harvest and, 51.93% of the total harvesting volume comes from eight genera and ten species. This research shows that in fallows of fragmented forest ecosystems, small farmers are harvesting fast-growing pioneer species. Maintaining a sustainable production in timber harvesting depends, by and large, on the harvesting and felling programs established on small farms. © 2017 Taylor & Francis.

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Evaluating night-time light sources and correlation with socio-economic development using high-resolution multi-spectral Jilin-1 satellite imagery of Quito, Ecuador

2023 , Watson C.S. , Elliott J.R. , Córdova M. , Menoscal J. , Bonilla Bedoya, Santiago

Artificial light at night (ALAN) has positive and negative effects on social, economic, environmental, and ecological systems, and will increase with urban expansion. In this study, we used a multi-spectral 1.5 m resolution night-time acquisition from a Jilin-1 satellite over the city of Quito, Ecuador, to evaluate spatial lighting patterns in an expanding and topography complex-built environment. We demonstrated a requirement for robust georeferencing and orthorectification due to the complex topography, with errors on the order of 4–6 pixels (5.8–8.4 m CE95). We also quantified differences in observed brightness due to the image acquisition and local geometry. Street light type was distinguishable between high-pressure sodium (HPS) and light emitting diode (LED) sources (F1-score = 0.72–0.83) using a shark random forest decision tree approach. Additionally, street lights could be located within 10 m (F1-score = 0.71) with balanced omissions and commissions. Spatial trends revealed that the road network was the dominant source of illumination, accounting for 45% of illuminated pixels, whereas built-up areas accounted for 23%. Overall, 68% of all illuminated pixels were on or within 10 m of the road. Higher socio-economic development was associated with higher proportions of LED lighting, greater road network lighting and density of street lights, higher overall radiance for built-up areas and the road network, and greater coverage and illumination of designated green spaces. The broad impacts of ALAN mean that addressing the causes and consequences of lighting inequalities is a complex issue. Nonetheless, Jilin-1 night-time imagery offers a low-cost way to map and monitor light sources at high-resolution that will be beneficial to city-planners and progressing Sustainable Development Goals. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

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Central parks as air quality oases in the tropical Andean city of Quito

2024 , Zalakeviciute R. , Bonilla Bedoya, Santiago , Mejia Coronel D. , Bastidas M. , Buenano A. , Diaz-Marquez A.

Urban ecosystem is an intricate agglomeration of human, fauna and flora populations coexisting in natural and artificial environments. As a city develops and expands over time; it may become unbalanced, affecting the quality of ecosystem and urban services and leading to environmental and health problems. Fine particulate matter (particulate matter with aerodynamic diameter ≤2.5 μm - PM2.5) is the air pollutant posing the greatest risk to human health. Quito, the capital city of Ecuador, exhibits a high occurrence of exposure to unhealthy levels of PM2.5 due to a combination of natural and social variables. This study focused on three central parks of this high elevation city, investigating the spatial distribution of PM2.5 concentrations. The particle pollution was then modeled using Normalized Difference Vegetation Index (NDVI). Hazardous instantaneous levels of PM2.5 were consistently found on the edges of the parks along busy avenues, which are also the most frequented areas. This raises concerns about both short- and long-term exposures to toxic traffic pollution in recreational areas within urban dwellings in the global south. The NDVI model successfully predicted the spatial concentrations of PM2.5 in a smaller urban park, suggesting its potential application in other cities. However, further research is required to validate its effectiveness. © 2024 The Authors

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Mapping of the Successional Stage of a Secondary Forest Using Point Clouds Derived from UAV Photogrammetry

2023 , Cabral R.P. , da Silva G.F. , de Almeida A.Q. , Bonilla Bedoya, Santiago , Dias H.M. , De Mendonça A.R. , Rodrigues N.M.M. , Valente C.C.A. , Oliveira K. , Gonçalves F.G. , Sarcinelli T.S.

The definition of strategies for forest restoration projects depends on information of the successional stage of the area to be restored. Usually, classification of the successional stage is carried out in the field using forest inventory campaigns. However, these campaigns are costly, time-consuming, and limited in terms of spatial coverage. Currently, forest inventories are being improved using 3D data obtained from remote sensing. The objective of this work was to estimate several parameters of interest for the classification of the successional stages of secondary vegetation areas using 3D digital aerial photogrammetry (DAP) data obtained from unmanned aerial vehicles (UAVs). A cost analysis was also carried out considering the costs of equipment and data collection, processing, and analysis. The study was carried out in southeastern Brazil in areas covered by secondary Atlantic Forest. Regression models were fit to estimate total height (h), diameter at breast height (dbh), and basal area (ba) of trees in 40 field inventory plots (0.09 ha each). The models were fit using traditional metrics based on heights derived from DAP and a portable laser scanner (PLS). The prediction models based on DAP data yielded a performance similar to models fit with LiDAR, with values of R² ranging from 88.3% to 94.0% and RMSE between 11.1% and 28.5%. Successional stage maps produced by DAP were compatible with the successional classes estimated in the 40 field plots. The results show that UAV photogrammetry metrics can be used to estimate h, dbh, and ba of secondary vegetation with an accuracy similar to that obtained from LiDAR. In addition to presenting the lowest cost, the estimates derived from DAP allowed for the classification of successional stages in the analyzed secondary forest areas. © 2023 by the authors.