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This study investigates the rain-initiated mixing and variability in the concentration of selected trace gases in the atmosphere over the central Amazon rain forest. It builds on comprehensive data from the Amazon Tall Tower Observatory (ATTO), spanning from 2013 to 2020 and comprising the greenhouse gases (GHG) carbon dioxide (CO2) and methane (CH4), the reactive trace gases carbon monoxide (CO), ozone (O3), nitric oxide (NO), and nitrogen dioxide NO2 (NO2) as well as selected volatile organic compounds (VOC). Based on more than 1000 analyzed rainfall incidents, the study resolves the trace gas concentration patterns before, during, and after the rain events, along with its vertical concentration gradients across the forest canopy. The assessment of the rainfall events was conducted independently for daytime and nighttime periods, which allows us to elucidate the influence of solar radiation. The concentrations of CO2, CO, and CH4 clearly declined during rainfall, which can be attributed to the downdraft-related entrainment of pristine air from higher altitudes into the boundary layer, a reduction of the photosynthetic activity under increased cloud cover, as well as changes in the surface fluxes. Notably, CO showed a faster reduction than CO2, and the vertical gradient of CO2 and CO is steeper than for CH4. Conversely, the O3 concentration increased across all measurement heights in the course of the rain-related downdrafts. Following the O3 enhancement by up to a factor of two, NO and VOC concentrations decreased, whereas NO2 increased. The temporal and vertical variability of the trace gases is intricately linked to the diverse sink and source processes, surface fluxes, and free troposphere transport. Within the canopy, several interactions unfold among soil, atmosphere, and plants, shaping the overall dynamics. Also, the concentration of biogenic VOC (BVOC) clearly varied with rainfall, driven by factors such as light, temperature, physical transport, and soil processes. Our results disentangle the patterns in trace gas concentration in the course of the sudden and vigorous atmospheric mixing during rainfall events. By selectively uncovering processes that are not clearly detectable under undisturbed conditions, our results contribute to a better understanding of the trace gas life cycle and its interplay with meteorology, cloud dynamics, and rainfall in the Amazon and beyond. [ABSTRACT FROM AUTHOR]

Research focusing on energy, water vapor, and CO2 exchanges over the Caatinga Biome is recent. Consequently, there exist research gaps on this topic that limit our ability to understand and project interannual and long-term variations in the CO2 cycle of this environment. Thus, the objective of this study was to evaluate the behavior of the energy and CO2 balances of the Caatinga Biome under extreme rainfall conditions (extreme drought and intense rainfall) using simulations of the SITE model (Simple Tropical Ecosystem Model). Meteorological data from the years 2009 (heavy rainfall) and 2012 (extreme drought) obtained from an INMET automatic station were used. Relationships between monthly GPP and NEE values and rainfall were also analyzed. Although the SITE model had been previously calibrated for the region, adjustments to the calibration were necessary for our study due to the extreme climatic values of the selected years. The results highlight the impact of rainfall on energy and mass exchanges over the Caatinga, particularly evident in the partitioning of the energy balance and the CO2 balance. In 2009 (during heavy rainfall), the fraction of Rn converted into LE was nearly 6% higher compared to the values observed in 2012 (during extreme drought). Regarding CO2, it was found that the Caatinga behaved as a sink, even under extreme drought conditions (2012), with annual average values of −1.86 µmol m−2 s−1 (2009) and −0.81 µmol m−2 s−1 (2012). Relationships between monthly GPP and NEE values and rainfall were also investigated, revealing an asymptotic relationship between the components of CO2 balance and rainfall. It was evident that both the monthly values of GPP and NEE tend to stabilize when monthly rainfall volumes exceed 200 mm. [ABSTRACT FROM AUTHOR]

The relationship with bike infrastructure is missing in the current examination of user perception, which places a great deal of emphasis on visual aesthetic quality or surveys. Italy is experiencing the great development of cycling infrastructures, and the related plans, in line with sustainability objectives, have the task of examining users in various aspects. The purpose of this study is to examine users' criteria based on perceptions of the landscape in the presence of cycling infrastructures and to analyze the current infrastructures and understand their alignment with sustainable plans. One of the multiple-criteria decision analysis (MCDA) methods based on fuzzy comprehensive evaluation (FCE) was utilized, and it entails identifying the factors that constitute an index and assessing the priority of these factors in relation to other components. The findings demonstrate that the primary variables are distinct aspects of the landscape that are objective. We discovered that these components perform better for urban than metropolitan sectors in this study, as we divided the scenarios into metropolitan and general (urban, suburban, and coastal urban) scenarios. [ABSTRACT FROM AUTHOR]

The analysis of gross primary production (GPP) is crucial to better understand CO2 exchanges between terrestrial ecosystems and the atmosphere, while the quantification of water-use efficiency (WUE) allows for the estimation of the compensation between carbon gained and water lost by the ecosystem. Understanding these dynamics is essential to better comprehend the responses of environments to ongoing climatic changes. The objective of the present study was to analyze, through AMERIFLUX and LBA network measurements, the variability of GPP and WUE in four distinct tropical biomes in Brazil: Pantanal, Amazonia, Caatinga and Cerrado (savanna). Furthermore, data measured by eddy covariance systems were used to assess remotely sensed GPP products (MOD17). We found a distinct seasonality of meteorological variables and energy fluxes with different latent heat controls regarding available energy in each site. Remotely sensed GPP was satisfactorily related with observed data, despite weak correlations in interannual estimates and consistent overestimations and underestimations during certain months. WUE was strongly dependent on water availability, with values of 0.95 gC kg−1 H2O (5.79 gC kg−1 H2O) in the wetter (drier) sites. These values reveal new thresholds that had not been previously reported in the literature. Our findings have crucial implications for ecosystem management and the design of climate policies regarding the conservation of tropical biomes, since WUE is expected to change in the ongoing climate change scenario that indicates an increase in frequency and severity of dry periods. [ABSTRACT FROM AUTHOR]

Studying the dynamics of gross primary production (GPP) in seasonally dry tropical forests is of fundamental importance to understand the carbon dioxide (CO2) balance in this ecosystem, helping mitigate its potential impacts at the regional and global levels. Thus, the objective of this work was to evaluate the accuracy of GPP estimated via remote sensing in the Caatinga biome. A set of observed data retrieved from micrometeorological towers equipped with eddy covariance systems were used to validate remote sensing data. The set was measured in a preserved Caatinga fragment. Remotely sensed GPP data was retrieved from the MOD17A2 version 6.0 product of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the Terra satellite. The validation of MOD17A2 GPP estimates was carried out through the comparison with micrometeorological data measured in situ. In the Caatinga site the comparison between the two GPP data types showed a moderate correlation with Pearson's correlation coefficient (r) = 0.65 and coefficient of determination (R2) = 0.43 and the product performed better in representing GPP in the Caatinga during the dry season. Results showed that although the MOD17A2 product represents the annual behaviour of GPP, the algorithm could be improved in order to provide GPP information that is more similar to surface measured data over these land covers. [ABSTRACT FROM AUTHOR]

This research aims to provide a brief evaluation of remotely sensed estimates in representing gross primary production (GPP) over pasture in the Northeast Region of Brazil. We used GPP data measured in situ during a micrometeorological experiment performed in a pasture area located in the NEB region using the eddy covariance technique. Remotely sensed GPP was obtained through the MOD17A2H product of the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on board the Terra satellite. We concluded that the MOD17A2H product moderately represents surface-measured GPP in the studied site, highlighting the need for improvements in the quality of the remotely sensed GPP estimates over this type of ecosystem. [ABSTRACT FROM AUTHOR]

Forest ecosystems sequester large amounts of atmospheric CO2, and the contribution from seasonally dry tropical forests is not negligible. Thus, the objective of this study was to quantify and evaluate the seasonal and annual patterns of CO2 exchanges in the Caatinga biome, as well as to evaluate the ecosystem condition as carbon sink or source during years. In addition, we analyzed the climatic factors that control the seasonal variability of gross primary production (GPP), ecosystem respiration (Reco) and net ecosystem CO2 exchange (NEE). Results showed that the dynamics of the components of the CO2 fluxes varied depending on the magnitude and distribution of rainfall and, as a consequence, on the variability of the vegetation state. Annual cumulative NEE was significantly higher (p < 0.01) in 2014 (−169.0 g C m−2) when compared to 2015 (−145.0 g C m−2) and annual NEP/GPP ratio was 0.41 in 2014 and 0.43 in 2015. Global radiation, air and soil temperature were the main factors associated with the diurnal variability of carbon fluxes. Even during the dry season, the NEE was at equilibrium and the Caatinga acted as an atmospheric carbon sink during the years 2014 and 2015. [ABSTRACT FROM AUTHOR]

Given the increasing occurrence of landslides on the East Coast Northeast of Brazil (ECNEB), it is essential to understand its conditions and triggering factors because meteorological anomalies triggered by a landslide will threaten life and property in the region. In this sense, this research aimed to diagnose the meteorological conditions that triggered landslides in the ECNEB in May 2017, evaluate the terrain's intrinsic conditions using elevation, slope, and susceptibility parameters and determine critical precipitation thresholds for the city with the highest number of landslide risk areas in the region. A dynamic downscaling experiment was carried out using the Regional Climate Model (RegCM) to verify the ability of this model to represent rainfall over the ECNEB. The results from the intrinsic factors showed that the ECNEB is highly susceptible to landslides with various high-risk sectors for landslides to the population. The extreme rainfall event was associated with the convergence of humidity at low levels over the ocean, which contributed to landslides in the ECNEB, mainly in the State of Pernambuco, where 67 landslides were registered. The RegCM numerical simulation underestimated the high daily rainfall signal seen on the Tropical Rainfall Measuring Mission satellite. It is suggested that sensitivity tests can be performed using other physical parameters to find the best model configuration for the ECNEB. This work recommends that exploring the relationship between precipitation and landslides will provide objective criteria for assessing risk areas by contributing to the predictability of disasters in this region. [ABSTRACT FROM AUTHOR]

Although seasonally dry tropical forests are considered invaluable to a greater understanding of global carbon fluxes, they remain as one of the ecosystems with the fewest observations. In this context, ecological and ecosystem models can be used as alternative methods to answer questions related to the interactions between the biosphere and the atmosphere in dry forests. The objective of this study was to calibrate the simple tropical ecosystem model (SITE) and evaluate its performance in characterizing the annual and seasonal behavior of the energy and carbon fluxes in a preserved fragment of the Caatinga biome. The SITE model exhibited reasonable applicability to simulate variations in CO2 and energy fluxes (r > 0.7). Results showed that the calibrated set of vegetation parameters adequately simulated gross primary productivity (GPP) and net ecosystem CO2 exchange (NEE). The SITE model was also able to accurately retrieve the time at which daily GPP and NEE peaked. The model was able to simulate the partition of the available energy into sensible and latent heat fluxes and soil heat flux when the calibrated parameters were used. Therefore, changes in the dynamics of dry forests should be taken into consideration in the modeling of ecosystem carbon balances. [ABSTRACT FROM AUTHOR]