Site selection for nature-based solutions for stormwater management in urban areas: An approach combining GIS and multi-criteria analysis.

In recent years, particularly following the definition of the UN Sustainable Development Goals (SDGs) for 2030, Nature-Based Solutions (NBS) have gained considerable attention, capturing the interest of both the scientific community and policymakers committed to addressing urban environmental issues. However, the need for studies to guide decision-makers in identifying suitable locations for NBS implementation within urban stormwater management is evident. To address this gap, the present study employs a methodological approach grounded in multi-criteria analysis integrated with Geographic Information Systems (GIS) to identify areas with potential for NBS implementation. In this process, ten NBS were proposed and tested in the drainage area of a shallow tropical urban lake in Londrina, southern Brazil. Additionally, the study investigates areas hosting lower-income populations, a relevant aspect for public managers given the diverse economic subsidies required to implement NBS. Furthermore, the study incorporates a preliminary analysis that evaluates the potential ecosystem benefits to determine the most suitable NBS for a specific site. The result shows that all the ten analyzed NBS were deemed suitable for the study area. Rain barrels had the highest percentage coverage in the study area (37.1%), followed by tree pits (27.9%), and rain gardens (25.4%). Despite having the highest distribution in the basin area, rain barrels exhibited only moderate ecosystem benefits, prompting the prioritization of other NBS with more significant ecological advantages in the final integrated map. In summary, the methodology proposed showed to be a robust approach to selecting optimal solutions in densely populated urban areas.

Spatial analysis of socio-economic factors and their relationship with the cases of COVID-19 in Pernambuco, Brazil.

OBJECTIVES: To analyse the spatial distribution of rates of COVID-19 cases and its association with socio-economic conditions in the state of Pernambuco, Brazil. METHODS: Autocorrelation (Moran index) and spatial association (Geographically weighted regression) models were used to explain the interrelationships between municipalities and the possible effects of socio-economic factors on rates. RESULTS: Two isolated clusters were revealed in the inner part of the state in sparsely inhabited municipalities. The spatial model (Geographically Weighted Regression) was able to explain 50% of the variations in COVID-19 cases. The variables proportion of people with low income, percentage of rented homes, percentage of families in social programs, Gini index and running water had the greatest explanatory power for the increase in infection by COVID-19. CONCLUSIONS: Our results provide important information on socio-economic factors related to the spread of COVID-19 and can serve as a basis for decision-making in similar circumstances.

Deforestation drivers in the Brazilian Amazon: assessing new spatial predictors.

Researches on the deforestation of the Amazon have gained prominence in the last recent years, mainly with the change in the policy regarding the facing of this phenomenon by the Brazilian government. Therefore, an understanding about the causes that pressure the occurrence of deforestation remains relevant and has a leading role in the world. Therefore, the aim of this study is to perform the analysis of the spatial variability of the reasons for the deforestation in the Amazon Biome, in Brazil, (2010-2019). To achieve this goal, 14 variables were selected, the choice and adjustment of the regression model were determined and a diagnosis was carried out in order to verify the most appropriate model. To achieve this purpose, a geographic database was structured in a geographic information system environment. The main results revealed that the adjusted R2 of the Geographically Weighted Regression (GWR) was 0.96, that is, the GWR model explains 96% of the variations in deforestation. Therefore, it was observed a significant gain when using this model. In addition, it was also observed that the average variable of the number of oxen was, among those analyzed, the one that showed the highest correlation with deforestation. Thus, it was found that the livestock sector in southern Amazonia is the main economic agent that pressures large areas of deforestation, since stockfarming is practiced extensively. Finally, it was concluded that the municipalities with the largest areas of deforestation formed a cluster in the southern portion of the Amazon, in the arc of deforestation.

Impact of mining activities on areas of environmental protection in the southwest of the Amazon: A GIS- and remote sensing-based assessment.

The southwest Brazilian Amazon state of Rondônia has a relatively recent non-indigenous occupation, which subsequently develops a variety of human pressures and conflicts of interest presently identified in the region. Given such framework, it is worthwhile to note that there are 57 Conservation Units that must guarantee the biodiversity protection of Amazonia biome. However, due to the need for electricity and the international high demand for minerals, the highlighted scenario has dramatically changed in recent years. Official data from mining processes in the studied area demonstrated the existence of high interest for minerals, especially cassiterite and gold. Mining is indeed an essential activity for the nation mainly due to the generation of jobs and income. On the other hand, it produces several environmental and social impacts that vary accordingly to the peculiarities of the mining and with respect to the type of ore. Therefore, this research work investigated the concentration of mining projects in the state of Rondônia and complementarily evaluated the impact of such activities on areas of environmental protection. Landsat 8 OLI imageries were employed to map the diversity of land covers across the study area and also to evaluate the corresponding impact of mining activities. More than 500 processes have been identified within the Conservation Units. A significant part of the mining areas, covering about 26 km2, was observed inside one of the three types of evaluated areas (Integral Protection Sustainable Use Conservation Units and Damping Zone), clearly showing the development of the illegal activity, as defined in terms of the National System of Conservation Units. If deforestation is considered in this analysis, the area increases to about 6110 km2, representing more than 5.2% of the Conservation Units. In addition, we proposed the creation of the Mining Pressure Index (MPI), which allows classifying a Conservation Unit by the degree of pressure from mining activities. The proposed index revealed to be very efficient since it predicted high values over Conservation Units where it was expected a greater vulnerability. The index is a promising tool for public policy formulation and management of protected areas, as well as for enforcement action. The results provide a new horizon in terms of the perspective of importance and applicability of geotechnologies in the evaluation of environmental impacts, not restricted to mining activity.

Development of a spatialized atmospheric emission inventory for the main industrial sources in Brazil.

In this work, atmospheric pollutant emissions of NOx, SOx, CO, particulate matter (PM), total organic compounds (TOC), and CO2 from larger stationary sources of pollutants in Brazil were inventoried and spatialized over the whole Brazilian territory for the base year 2011. The developed inventory comprises a total of 16 refining units, 1730 thermoelectric power plants (TPPs), 96 cement industries, and 64 paper and cellulose industries. To obtain the dataset, some strategies were used, including mail contact, official datasets, personal requesting, web maps usage, and official industry websites. The emission factors were based on lower and upper limits proposed by the AP-42 standards of the US Environmental Protection Agency - USEPA, as well as, emission factors provided by air pollution control agencies, industries, and those identified in the scientific literature. The results show values of 857 ± 415 Gg/year for NOx, 1.51 ± 1.23 Tg/year for SOx, 21.2 ± 13.7 Tg/year for CO, 10.4 ± 10.1 Tg/year for PM, 1.14 ± 0.95 Tg/year for TOC, and 476 ± 142 Tg/year for CO2. In comparison with the official vehicular emission inventory provided by the Ministry of Environment for the year 2011, the total NOx emissions estimated in this work were slightly lower than vehicular emissions, while SOx was 300 times greater than vehicular emissions. For CO, the stationary emissions inventoried were around 17 times greater than vehicular emissions, while PM was approximately 360 times greater than those from vehicles. In terms of comparison with existing global databases, the estimates of this work showed a good level of agreement with the pollutants estimated by the Global Emissions EDGAR v4.3.1, except for PM and CO, which were higher in our estimates. The major contribution of the proposed inventory lies in its improved spatialized distribution, higher resolution, and greater distinctness about the high level of uncertainty associated with the emission inventories for the region.

Biodegradable CA/CPB electrospun nanofibers for efficient retention of airborne nanoparticles.

The increase of the industrialization process brought the growth of pollutant emissions into the atmosphere. At the same time, the demand for advances in aerosol filtration is evolving towards more sustainable technologies. Electrospinning is gaining notoriety, once it enables to produce polymeric nanofibers with different additives and also the obtaining of small pore sizes and fiber diameters; desirable features for air filtration materials. Therefore, this work aims to evaluate the filtration performance of cellulose acetate (CA) nanofibers and cationic surfactant cetylpyridinium bromide (CPB) produced by electrospinning technique for retention of aerosol nanoparticles. The pressure drop and collection efficiency measurements of sodium chloride (NaCl) aerosol particles (diameters from 7 to 300 nm) were performed using Scanning Mobility Particle Sizer (SMPS). The average diameter of the electrospun nanofibers used was 239 nm, ranging from 113 to 398 nm. Experimental results indicated that the nanofibers showed good permeability (10-11 m2) and high-efficiency filtration for aerosol nanoparticles (about 100 %), which can include black carbon (BC) and the new coronavirus. The pressure drop was 1.8 kPa at 1.6 cm s-1, which is similar to reported for some high-efficiency nanofiber filters. In addition, it also retains BC particles present in air, which was about 90 % for 375 nm and about 60 % for the 880 nm wavelength. Finally, this research provided information for future designs of indoor air filters and filter media for facial masks with renewable, non-toxic biodegradable, and potential antibacterial characteristics.