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Dengue fever, a mosquito-borne viral disease, poses a significant public health challenge whose transmission dynamics are highly sensitive to climatic conditions. However, the effects of extreme weather events like heatwaves remain poorly understood. This study investigated the influence of climatic factors and heatwaves on dengue incidence in two key Brazilian hotspots: the subtropical megacity of São Paulo (Sao Paulo State) and the tropical coastal city of Natal (Rio Grande do Norte State). We analyzed weekly confirmed dengue cases and meteorological data (temperature, precipitation, heatwaves) from 2014 to 2023. Distributed lag non-linear models and negative binomial regression were used to assess the complex, delayed associations between meteorological variables and dengue infections. Over the study period, 149,468 dengue cases were reported in São Paulo and 80,999 in Natal. Transmission patterns differed significantly, with Natal exhibiting more regular epidemic cycles. Our models revealed that higher minimum temperatures were associated with increased dengue risk in both cities. Conversely, and perhaps counter-intuitively, higher maximum temperatures and total precipitation showed negative associations with dengue cases. The impact of heatwaves was strikingly different between the locations. In São Paulo, the occurrence of a heatwave was associated with a 70% reduction in dengue risk in subsequent weeks (Relative Risk [RR]: 0.30, 95% Confidence Interval [CI]: 0.18–0.49). In contrast, no statistically significant association between heatwaves and dengue was observed in Natal. Our findings demonstrate that the relationship between extreme heat and dengue transmission is not uniform and can be inhibitory, challenging the assumption that warming consistently favors vector proliferation. These location-specific insights are critical for developing more accurate, tailored public health early-warning systems and caution against one-size-fits-all climate adaptation strategies for vector-borne diseases.

In the second quarter of 2021, the companies at the Capuava Petrochemical Complex (CPC, Santo André, Brazil) carried out a 50-day scheduled shutdown for the maintenance and installation of new industrial equipment. This process resulted in severe uncontrolled emissions of particulate matter (PM) and volatile organic compounds (VOCs) in a densely populated residential area (~3400 inhabitants/km2). VOCs can be emitted directly into the atmosphere in urban areas by vehicle exhausts, fuel evaporation, solvent use, emissions of natural gas, and industrial processes. PM is emitted by vehicle exhausts, mainly those powered by diesel, industrial processes, and re-suspended soil dust, in addition to that produced in the atmosphere by photochemical reactions. Our statistical analyses compared the previous (2017–2020) and subsequent (2021–2022) periods from this episode (April–May 2021) from the official air quality monitoring network of the PM10, benzene, and toluene hourly data to improve the proportion of this period of uncontrolled emissions. Near-field simulations were also performed to evaluate the dispersion of pollutants of industrial origin, applying the Gaussian plume model AERMOD (steady-state plume model), estimating the concentrations of VOC and particulate matter (PM10) in which the population was exposed in the region surrounding the CPC. The results comparing the four previous years showed an increase in the mean concentrations by a factor of 2 for PM10, benzene, and toluene, reaching maximum values during the episode of 174 µg m−3 (PM10), 79.1 µg m−3 (benzene), and 58.7 µg m−3 (toluene). Meanwhile, these higher concentrations continued to be observed after the episode, but their variation cannot be fully explained yet. However, it is worth highlighting that this corresponds to the post-pandemic period and the 2022 data also correspond to the period from January to June, that is, they do not represent the annual variation. A linear correlation indicated that CPC could have been responsible for more than 60% of benzene measured at the Capuava Air Quality Station (AQS). However, the PM10 behavior was not fully explained by the model. AERMOD showed that the VOC plume had the potential to reach a large part of Mauá and Santo André municipalities, with the potential to affect the health of more than 1 million inhabitants.

The main features of low‐level jet (LLJ) in the metropolitan region of São Paulo (MRSP), Brazil, are assessed using rawinsondes carried out: (a) every 3‐hr during 10‐consecutive days in summer and winter field campaigns of the MCITY BRAZIL Project in 2013, (b) at 0900 and 2100 local time, from September 2009 to August 2013. These observations indicate that the LLJ is a typical feature of the MRSP, observed in 85% of the 20 days of the field‐campaigns and 77.6% of the 1,446 days of regular rawinsonde period. The fine temporal and spatial resolution soundings indicate that most of the LLJs occur during nighttime and early in the morning, with mean intensity of 8.5 ± 0.3 m s−1, height of 539 ± 26 m, and mostly (52.5%) from east and north. The coarse resolution soundings indicate the LLJ display a seasonal variation with maximum intensity in October (8.6 ± 0.3 m s−1) and a minimum in February (7.1 ± 0.2 m s−1), a maximum height in March (703 ± 151 m) and a minimum in June (577 ± 151 m). During MCITY campaigns about 76.4% of LLJ events show inertial oscillation and 35.3% of them are combined with sea breeze. Only 17.6% of LLJ events are associated with cold fronts and post‐frontal high pressure system. The urban heat island intensity, surface inversion layer strength, particulate matter 2.5 and carbon monoxide concentrations are negatively correlated with the LLJ intensity, suggesting the jet‐induced turbulent mixing may contribute to reduce them. Key Points The low‐level jet (LLJ) is a remarkable robust feature of metropolitan region of São Paulo climate, occurring in more than 77% of time They occur during nighttime, under less disturbed synoptic conditions and more often in association to sea‐breeze circulation Most of LLJ display inertial oscillation and are correlated with urban heat island, surface inversion layer, and air pollution

The main purpose of this work is to report the presence of spurious discontinuities in the pattern of diurnal variation of sea level pressure of the three reanalysis datasets from: the National Centers for Environmental Prediction (NCEP) and National Center for Atmospheric Science (R1), the NCEP and Department of Energy (R2), and the European Centre for Medium Range Weather Forecasting (ERA-40). Such discontinuities can be connected to the major changes in the global observing system that have occurred throughout reanalyses years. In the R1, the richest period in discontinuities is 1956–1958, coinciding with the start of modern radiosonde observation network. Rapid increase in the density of surface-based observations from 1967 also had an important impact on both R1 and ERA-40, with larger impact on R1. The reanalyses show discontinuities in the 1970s related to the assimilation of radiances measured by the Vertical Temperature Profile Radiometer and TIROS-N Operational Vertical Sounders onboard satellites. In the ERA-40, which additionally assimilated Special Sensor Microwave/Imager data, there are discontinuities in 1987–1989. The R1 also presents further discontinuities, in 1988–1993 likely connected to replacement/introduction of NOAA-series satellites with different biases, and to the volcanic eruption of Mount Pinatubo in June 1991, which is known to have severely affected measurements of infrared radiances for several years. The discontinuities in 1996–1998 might be partially connected to change in the type of radiosonde, from VIZ-B to VIZ-B2. The R2, which covers only satellite era (1979-on), shows discontinuities mainly in 1992, 1996–1997, and 2001. The discontinuities in 1992 and 2001 might have been caused by change in the satellite measurements and those in 1996–1997 by some changes in land-based observations network.

This study shows climate projections of air temperature and precipitation over South America (SA) from the Regional Climate Model version 3 (RegCM3) nested in ECHAM5 and HadCM3 global models. The projections consider the A1B scenario from Intergovernmental Panel on Climate Change (IPCC) and three time-slices: present (1960–1990), near- (2010–2040), and far-future (2070–2100) climates. In the future, RegCM3 projections indicate general warming throughout all SA and seasons, which is more pronounced in the far-future period. In this late period the RegCM3 projections indicate that the negative trend of precipitation over northern SA is also higher. In addition, a precipitation increase over southeastern SA is projected, mainly during summer and spring. The lifecycle of the South American monsoon (SAM) was also investigated in the present and future climates. In the near-future, the projections show a slight delay (one pentad) of the beginning of the rainy season, resulting in a small reduction of the SAM length. In the far-future, there is no agreement between projections related to the SAM features.

Abstract Air pollution is associated to poor urban mobility conditions, as in the megacity of São Paulo. Three scenarios of policies of driving restrictions were simulated using the WRF/Chem model, to assess the impacts on ozone pollution and the consequences for environmental justice: urban toll, sustainable transition, and vehicle free zone. Results show that the urban toll leads to a decrease of 20 µg.m-3 in maximum 8-hour ozone averages and the prevention of six hours of exceedances of the air quality standard. Sustainable transition was the most promising scenario, with a decrease of 50 µg.m-3 and avoiding 22 hours of exceedances. The vehicle free zone did not show any advantages. For the implementation of adequate public transport systems, massive investments are required, in order to achieve better air quality with the greatest environmental justice possible, aiming towards the protection of human health along with a more democratic access to the urban spaces. Resumo A poluição atmosférica pode ser agravada devido à precárias condições de mobilidade urbana, como ocorre em São Paulo. Visando avaliar os impactos na poluição por ozônio e as consequências para a justiça ambiental, 3 cenários de políticas de restrição veicular foram simulados com o modelo WRF/Chem: pedágio urbano, transição sustentável e centro sem veículos. Os resultados indicaram que o pedágio urbano levou a uma redução de 20 µg.m-3 nas médias das máximas de 8 horas, e evitou seis ultrapassagens do padrão de qualidade do ar. A transição sustentável teve máximas até 50 µg.m-3 mais baixas e evitou 22 ultrapassagens. O centro sem veículos não demonstrou vantagens. Para a implementação de um sistema de transporte público adequado, são necessários expressivos investimentos para se atingir melhorias na qualidade do ar com a maior justiça ambiental possível, buscando a proteção da saúde da população juntamente à democratização do acesso aos espaços urbanos. Resumen La contaminación atmosférica puede agravarse debido à la movilidad urbana ineficiente, como en São Paulo. Visando avaliar los impactos em la contaminación por ozono y las consecuencias para la justicia ambiental, se simularan 3 escenarios de restricción vehicular con en el modelo WRF/Chem: peaje urbano, transición sustentable y centro sin vehículos. Los resultados indicaron que el peaje urbano condujo a una reducción de 20 µg.m-3 en las concentraciones medias máximas de 8 horas, y evito 6 excedencias de las normas de calidad del aire. La transición sustentable tuvo un máximo de hasta 50 µg.m-3 más bajo e 22 excedencias evitadas. El centro sin vehículos no presento ventajas. Para la implementación de un transporte público adecuado, se necesitan inversiones significativas para lograr mejoras en la calidad del aire con la mayor justicia ambiental posible, buscando proteger la salud de la población junto con la democratización del acceso a los espacios urbanos.

Atmospheric CO.sub.2 concentrations in urban areas reflect a combination of fossil fuel emissions and biogenic fluxes, offering a potential approach to assess city climate policies. However, atmospheric models used to simulate urban CO.sub.2 plumes face significant uncertainties, particularly in complex urban environments with dense populations and vegetation. This study addresses these challenges by analyzing CO.sub.2 dynamics in the Metropolitan Area of São Paulo (MASP) using the Weather Research and Forecasting model with Chemistry (WRF-Chem). Simulations were evaluated against ground-based observations from the METROCLIMA network, the first greenhouse gas monitoring network in South America, and column concentrations (XCO.sub.2) from the OCO-2 satellite spanning February to August 2019. To improve biogenic fluxes, we optimized parameters in the Vegetation Photosynthesis and Respiration Model (VPRM) using eddy covariance flux measurements for key vegetation types, including the Atlantic Forest, Cerrado, and sugarcane. Results show that at the urban site (IAG), the model consistently underestimated CO.sub.2 concentrations, with a negative mean bias of -9 ppm throughout the simulation period, likely due to the complexity of vehicular emissions and urban dynamics. In contrast, at the vegetated site (PDJ), simulations showed a consistent positive mean bias of 5 ppm and closely matched observations. Seasonal analyses revealed higher CO.sub.2 concentrations in winter, driven by greater atmospheric stability and reduced vegetation uptake estimated by VPRM, while summer exhibited lower levels due to increased mixing and higher agricultural productivity. A comparison of biogenic and anthropogenic scenarios highlights the need for integrated emission modeling and improved representation of biogenic fluxes, anthropogenic emissions, and boundary conditions for high-resolution modeling in tropical regions.

Atmospheric CO2 concentrations in urban areas reflect a combination of fossil fuel emissions and biogenic fluxes, offering a potential approach to assess city climate policies. However, atmospheric models used to simulate urban CO2 plumes face significant uncertainties, particularly in complex urban environments with dense populations and vegetation. This study addresses these challenges by analyzing CO2 dynamics in the Metropolitan Area of São Paulo (MASP) using the Weather Research and Forecasting model with Chemistry (WRF-Chem). Simulations were evaluated against ground-based observations from the METROCLIMA network, the first greenhouse gas monitoring network in South America, and column concentrations (XCO2) from the OCO-2 satellite spanning February to August 2019. To improve biogenic fluxes, we optimized parameters in the Vegetation Photosynthesis and Respiration Model (VPRM) using eddy covariance flux measurements for key vegetation types, including the Atlantic Forest, Cerrado, and sugarcane. Results show that at the urban site (IAG), the model consistently underestimated CO2 concentrations, with a negative mean bias of −9 ppm throughout the simulation period, likely due to the complexity of vehicular emissions and urban dynamics. In contrast, at the vegetated site (PDJ), simulations showed a consistent positive mean bias of 5 ppm and closely matched observations. Seasonal analyses revealed higher CO2 concentrations in winter, driven by greater atmospheric stability and reduced vegetation uptake estimated by VPRM, while summer exhibited lower levels due to increased mixing and higher agricultural productivity. A comparison of biogenic and anthropogenic scenarios highlights the need for integrated emission modeling and improved representation of biogenic fluxes, anthropogenic emissions, and boundary conditions for high-resolution modeling in tropical regions.

The South American low level jet (SALLJ) of the Eastern Andes is investigated with Regional Climate Model version 3 (RegCM3) simulations during the 2002-2003 austral summer using two convective parameterizations (Grell and Emanuel). The simulated SALLJ is compared with the special observations of SALLJEX (SALLJ Experiment). Both the Grell and Emanuel schemes adequately simulate the low level flow over South America. However, there are some intensity differences. Due to the larger (smaller) convective activity, the Emanuel (Grell) scheme simulates more intense (weaker) low level wind than analysis in the tropics and subtropics. The objectives criteria of Sugahara (SJ) and Bonner (BJ) were used for LLJ identification. When applied to the observations, both criteria suggest a larger frequency of the SALLJ in Santa Cruz, followed by Mariscal, Trinidad and Asunción. In Mariscal and Asunción, the diurnal cycle indicates that SJ occurs mainly at 12 UTCs (morning), while the BJ criterion presents the SALLJ as more homogenously distributed. The concentration into two of the four-times-a-day observations does not allow conclusions about the diurnal cycle in Santa Cruz and Trinidad. The simulated wind profiles result in a lower than observed frequency of SALLJ using both the SJ and BJ criteria, with fewer events obtained with the BJ. Due to the stronger simulated winds, the Emanuel scheme produces an equal or greater relative frequency of SALLJ than the Grell scheme. However, the Grell scheme using the SJ criterion simulates the SALLJ diurnal cycle closer to the observed one. Although some discrepancies between observed and simulated mean vertical profiles of the horizontal wind are noted, there is large agreement between the composites of the vertical structure of the SALLJ, especially when the SJ criterion is used with the Grell scheme. On an intraseasonal scale, a larger southward displacement of SALLJ in February and December when compared with January has been noted. The Grell and Emanuel schemes simulated this observed oscillation in the low-level flow. However, the spatial pattern and intensity of rainfall and circulation anomalies simulated by the Grell scheme are closer to the analyses than those obtained with the Emanuel scheme.

Atmospheric CO2 concentrations in urban areas reflect a combination of fossil fuel emissions and biogenic fluxes, offering a potential approach to assess city climate policies. However, atmospheric models used to simulate urban CO2 plumes face significant uncertainties, particularly in complex urban environments with dense populations and vegetation. This study addresses these challenges by analyzing CO2 dynamics in the Metropolitan Area of São Paulo (MASP) using the Weather Research and Forecasting model with Chemistry (WRF-Chem). Simulations were evaluated against ground-based observations from the METROCLIMA network, the first greenhouse gas monitoring network in South America, and column concentrations (XCO2) from the OCO-2 satellite spanning February to August 2019. To improve biogenic fluxes, we optimized parameters in the Vegetation Photosynthesis and Respiration Model (VPRM) using eddy covariance flux measurements for key vegetation types, including the Atlantic Forest, Cerrado, and sugarcane. Results show that at the urban site (IAG), the model consistently underestimated CO2 concentrations, with a negative mean bias of −9 ppm throughout the simulation period, likely due to the complexity of vehicular emissions and urban dynamics. In contrast, at the vegetated site (PDJ), simulations showed a consistent positive mean bias of 5 ppm and closely matched observations. Seasonal analyses revealed higher CO2 concentrations in winter, driven by greater atmospheric stability and reduced vegetation uptake estimated by VPRM, while summer exhibited lower levels due to increased mixing and higher agricultural productivity. A comparison of biogenic and anthropogenic scenarios highlights the need for integrated emission modeling and improved representation of biogenic fluxes, anthropogenic emissions, and boundary conditions for high-resolution modeling in tropical regions.