Climate change and pollutant emissions impacts on air quality in 2050 over Portugal

Sá, E.; Martins, Helena; Ferreira, Joana; Marta‐Almeida, Martinho; Carvalho, Anabela; Freitas, S. R.; Borrego, Carlos

doi:10.1016/j.atmosenv.2016.01.040

Cited by 39 publications

(38 citation statements)

References 39 publications

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“…This rise is related to the rapid expansion of the global population, leading to an increased demand for fossil fuels in daily human activities and excessive use of fertilizers in agricultural production, and will cause global radiative forcing to reach 8.5 W m −2 by 2100 . From the perspective of the global environment, climate scenario RCP 8.5 is considered the most likely future climate scenario and is being studied extensively . This paper aims to how a higher emission of carbon dioxide will affect the habitat of L. invasa in the next 30 years, so this study used RCP 8.5 as a scenario for future climate.…”

Section: Methodsmentioning

confidence: 99%

Prediction of current and future potential distributions of theEucalyptuspestLeptocybe invasa(Hymenoptera: Eulophidae) in China using the CLIMEX model

Huang

Shi

et al. 2019

Pest Management Science

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BACKGROUND: The wasp Leptocybe invasaFisher & LaSalle (Hymenoptera: Eulophidae), a Eucalyptus (Myrtaceae) pest native to Australia, has caused economic and ecologic losses in China. It is a serious pest in southern provinces. Because climate is a limiting factor in insect distribution, we used the model CLIMEX to predict the effect of climate change on potential current and future distributions of L. invasa in China. Data were collected on the current locations of this wasp, along with the damage incurred to Eucalyptus. These data were used to create a forecast model to predict potential current and future distribution maps of L. invasa in China. RESULTS:The verification results showed that 99.5% of the distribution samples formulated by the model are highly reliable and accurate. The result predicted that the potential current distribution of L. invasa will concentrate south of the Yellow River basin. The future distribution maps predicted a small-scale potential expansion north-northwest of Guangxi and more areas within China will provide increasingly suitable habitats for colonization by L. invasa. CONCLUSION: These distribution predications will be useful in determining where preventive and control measures should be implemented against this pest wasp in Eucalyptus throughout China.

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Section: Methodsmentioning

confidence: 99%

Prediction of current and future potential distributions of theEucalyptuspestLeptocybe invasa(Hymenoptera: Eulophidae) in China using the CLIMEX model

Huang

Shi

et al. 2019

Pest Management Science

View full text Add to dashboard Cite

show abstract

“…Carvalho et al [33] found that throughout Portugal the maximum increase in PM10 concentrations are foreseen for the northern coastal region. Recently, Sá et al [34] have shown evidences regarding the increase in extreme values for O 3 and PM10 concentrations under future climate, in 2050. Considering only CC effects, NO 2 and PM10 annual average concentrations will increase in Portugal and in Porto urban area, while O 3 concentrations will increase in suburban areas and decrease in urban areas.…”

Section: Impacts Of CC On Air Qualitymentioning

confidence: 99%

“…In this case, PM10 annual average concentrations will increase over Portugal and reduce over Porto urban area, while O 3 concentrations will increase in the surrounding areas and decrease within urban areas, mainly due to the reduction of O 3 precursors. Sá et al [34] indicate that for Porto urban area PM10 and O 3 concentrations will record increases in occurrences, duration and intensity of extreme values, surpassing the annual legislated values, recording a higher number of daily exceedances. This air quality degradation pattern is likely related with the trends found for future climate, which implies warmer and dryer conditions, followed by an increase in background concentrations of O 3 and PM10.…”

Section: Impacts Of CC On Air Qualitymentioning

confidence: 99%

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Air quality, urban fluxes and cities resilience under climate change – A brief overview

Borrego¹,

Rafael²,

Rodrigues³

et al. 2018

Int. J. EI

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Cities are home of about 70% of the European population, and it is expected that by 2050 this number will be achieved around the world. As a result, cities are facing important challenges related to pressures induced by changes on urban metabolism and by climate change (CC) effects. Understanding the key factors determining the vulnerability of a city provides a framework to consider resilience. These issues become more and more relevant since changes in urban structure and metabolism together with CC will start affecting atmospheric emissions, urban air quality and consequently human health. Cobenefits of an urban air quality and CC approach need to be further addressed taking into consideration that CC creates both risks and opportunities. Therefore, an integrated assessment of the interaction between resilience factors and CC effects, and its influence on the urban microclimate and air quality, is required to better adapt to future climate. This knowledge is fundamental to support policy makers and stakeholders helping them to choose the best strategies to manage resources, to mitigate extreme weather events and to predict air pollution episodes. This article offers a systematic review on CC impacts in cities, providing some adaptation strategies and suggesting future research topics.

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“…Furthermore, in literature, the study of climate change impacts ranges from global scale down to the regional and urban scale [39,40] (e.g., in [40] the authors have performed a 10-year air quality projection under climate and city-level emission changes at urban scale applying a horizontal resolution of 4 km × 4 km). Nevertheless, the full understanding of the impact on air quality at a local scale is a challenge and the effects are still unknown.…”

Section: Introductionmentioning

confidence: 99%

Adaptation to Climate Change at Local Scale: A CFD Study in Porto Urban Area

Rodrigues¹,

Rafael²,

Sorte³

et al. 2018

Computational Fluid Dynamics - Basic Instruments and Applications in Science

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Green infrastructures play an essential role in urban planning, namely with their potential to reduce the impact from air pollution episodes together with extreme weather events. This chapter focuses on the assessment of green infrastructures' benefits on current and future microclimate and air quality patterns in Porto's urban area (Portugal). The effects of green infrastructures on flow dynamics are evaluated for the baseline scenarios by means of numerical and physical simulations, using the computational fluid dynamics (CFD) model VADIS and the wind tunnel of the University of Aveiro. The baseline morphological (BM) scenario focuses on the current morphological characteristics of Porto's urban area, while a baseline green (BG) scenario comprises the replacement of built-up areas by green areas and parks. In addition, the benefits of green infrastructures on air quality are assessed for the baseline and under future climate scenarios. The air quality simulations focus on particulate matter, one of the most critical air pollutants with severe impacts on human health. For the BM scenario, the simulated concentrations are compared with hourly averaged PM10 concentrations measured during a weekday at the air quality station located within the study domain.

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Climate change and pollutant emissions impacts on air quality in 2050 over Portugal

Cited by 39 publications

References 39 publications

Prediction of current and future potential distributions of theEucalyptuspestLeptocybe invasa(Hymenoptera: Eulophidae) in China using the CLIMEX model

Prediction of current and future potential distributions of theEucalyptuspestLeptocybe invasa(Hymenoptera: Eulophidae) in China using the CLIMEX model

Air quality, urban fluxes and cities resilience under climate change – A brief overview

Adaptation to Climate Change at Local Scale: A CFD Study in Porto Urban Area

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