Urban areas concentrate more than 50% of the world’s population and are highly impacted by human activities, mainly due to high population density, directly affecting the micro-climate. In this sense, green infrastructures (GIs) have been pointed out to be helpful in mitigating these effects in large urban areas, where most of the studies were conducted. Therefore, this study evaluates the impacts on meteorological variables in a medium-sized city through the Weather Research and Forecasting model by implementing urban classes of Local Climate Zones (LCZ). Five urban parks and an urban lake were identified and expanded in the inner model grid to analyze the effects of GIs on meteorological variables in the urban environment. Results show that the 10 m wind speed can present an improvement for all statistical indices due to the better vertical representation of urban structures in the central urban area by the LCZ urban classes. In addition, green areas contributed locally to reducing the urban heat island (UHI) effects, resulting in cooling rates around these infrastructures. Compared to the lake, the use of the urban LCZ classes has proven to be an effective way to improve the representation of meteorological variables by a mesoscale weather model. Regarding GIs, this practice performs environmental services capable of mitigating the effects of UHI, sustaining the importance of these systems in urban projects, even for medium-sized cities. Finally, these findings provide support for public decision-makers in creating Master Plans for medium-sized cities regarding the implementation of GIs.

Emission inventories are essential tools for air quality management. However, the state of Rio de Janeiro lacks a comprehensive inventory. Consequently, global models such as EDGAR (Emission Database for Global Atmospheric Research) become an attractive alternative. This study aims to analyze data on nitrogen oxides (NOx) and volatile organic compounds (VOCs) and compare them with existing data. To achieve this, a 3 × 3 km simulation grid centered on the state of Rio de Janeiro was constructed. Meteorological fields were generated using the Weather Research and Forecasting model, while emission data were obtained from EDGAR. The simulation period spanned 34 days in 2018. Emissions were analyzed for NOx and VOCs, and compared to mobile source inventory data from the State Environmental Institute of Rio de Janeiro. Sectoral contributions to NOx emissions revealed that industry, navigation, and energy were the dominant sources. For VOCs, the primary contributors were industry, residential sources, and transportation. The comparison with State Institute for the Environment of Rio de Janeiro (INEA-RJ) data indicated that the model underestimated NOx and VOC emissions by approximately 38 and 48%, respectively. Despite the underestimation, the model effectively captured the regional emission characteristics, highlighting its potential as a tool for emission analysis without a comprehensive local inventory.

Biomass burning has become an increasingly important driver of air quality degradation in Minas Gerais, southeastern Brazil, particularly during the dry season, when fire activity intensifies, and atmospheric dispersion is suppressed. This work addresses recent evidence on the role of regional biomass burning in shaping fine particulate matter (PM₂.₅) concentrations, with a particular focus on the extreme air pollution episodes observed during 2024. The analysis integrates long-term records of fire hotspots, ground-based air quality monitoring, and key meteorological variables to elucidate the coupled processes linking fire activity, atmospheric dynamics, and urban air quality.Minas Gerais encompasses the third largest metropolitan region in Brazil and hosts major local atmospheric emission sources, including intensive mining activities, steelmaking, and a dense urban–industrial infrastructure. Despite the persistent contribution of these structural sources to baseline air pollution levels, fire occurrence in the state exhibits pronounced seasonality, with approximately two-thirds of annual hotspots concentrated between August and October. The year 2024 stands out as one of the most critical periods of the last decade, characterized by prolonged drought, anomalously high temperatures, and persistently low relative humidity. These conditions not only favored the ignition and spread of fires but also created a meteorological environment highly unfavorable to pollutant dispersion.Time-series analyses indicate that peaks in PM₂.₅ concentrations closely coincided with periods of increased fire frequency and intensity, particularly in the Metropolitan Region of Belo Horizonte. Statistical analyses reveal a moderate-to-strong positive association between PM₂.₅ levels and fire hotspot counts, and a consistent negative association with relative humidity. Notably, even in a region with significant local emissions from mining, steel production, and vehicular traffic, biomass burning emerged in 2024 as the dominant driver of exceedances of the national PM₂.₅ air quality standards established by CONAMA Resolution No. 506/2024. These findings demonstrate that regional-scale transport and accumulation of biomass-burning emissions can outweigh the influence of traditional urban and industrial sources during extreme events.Several monitoring stations recorded historically high PM₂.₅ concentrations in 2024, leading to recurrent violations of national air quality thresholds. The compounded effects of extreme meteorological conditions and biomass burning led to short-lived but severe pollution episodes that substantially deteriorated air quality across the metropolitan area. Beyond local emission sources, regional fire activity therefore represents a critical and recurrent contributor to urban particulate pollution, with direct implications for public health and regulatory compliance.Overall, the results reinforce the need for integrated air quality management strategies that combine fire prevention and control, regional-scale monitoring, and meteorological forecasting. Such approaches are particularly relevant under a changing climate, in which the frequency and severity of droughts, heatwaves, and associated biomass-burning events are expected to increase, thereby amplifying their impacts on air quality even in heavily industrialized urban regions.