As the world continues to be a globalized society, there have been variations in environmental quality, but studies including trade globalization into the environmental policy framework remain inconclusive. Therefore, employing the time series dataset of Uruguay over the period between 1980 and 2018, the main objective of this current study is to investigate the effect of trade globalization, natural resources rents, economic growth, and financial development on carbon emissions. By employing the bounds testing procedures in combination with the critical approximation p-values of Kripfganz and Schneider (2018), the Autoregressive Distributed Lag estimator, and spectral causality test to achieve the goal of this research. The outcomes of the bounds test confirm a long-run connection between carbon emissions and these determinants. Moreover, from the outcome of the Autoregressive Distributed Lag estimator, we observed that trade liberalization is found to exert CO2 emissions in the long and short run. The economic expansion in Uruguay imposes significant pressure on the quality of the environment in the long and short run. The abundance of natural resources significantly increases environmental deterioration in the long and short run. Furthermore, we uncover that financial development does not impact environmental deterioration in Uruguay. Finally, the outcome of the spectral causality test detected that trade globalization, economic growth, and natural resources forecast carbon emissions with the exclusion of financial development. Based on the outcome, this study suggests that policies should be tailored towards international trade must be reassessed, and the restrictions placed on the exportation of polluting-intensive commodities must be reinforced.
Pronounced subsidence leading to summer drought over southern Africa causes warmer than average surface air temperatures or even heatwave (HW) conditions. We investigated the occurrence of HWs during the summer drought over South Africa based on station data and the ECMWF ERA5 reanalyses. Temperature observations from the South African Weather Service were analyzed for seasonality and long-term trends (1981–2020) as background to the occurrence and variability of HWs. We focused on three severe El Niño Southern Oscillation (ENSO)-induced drought seasons, i.e., 1982/83, 1991/92, and 2015/16, to investigate HW characteristics. While 1997/98 was among the strongest El Niño seasons, the impacts were not as severe because it coincided with an intense Angola low, which allowed for rain-bearing cloud bands to form. Results showed that the hottest months were spread across the austral summer season from December to February. Regions experiencing high mean maximum temperatures and high HW frequencies exhibited a strong ENSO signal, with record HWs occurring during 2015/16. The establishment and persistence of a middle-level high-pressure system over Botswana/Namibia (Botswana High) appears to trigger the longest-lasting HWs during drought seasons. The Botswana high is usually coupled with a near-surface continental heat low and/or tropical warm air advection towards the affected region. It was also found that intense ENSO-induced drought events coincided with high HW frequency over South Africa, such as during 1982/83, 1991/92, and the recent 2015/16 events. The results of this study contribute to understanding drought and heat wave dynamics in a region experiencing rapid warming as a result of climate change.
Climate change has increased the frequency of extreme weather events such as heavy rainfall leading to floods in several regions. In Africa, rural communities are more vulnerable to flooding, particularly those that dwell in low altitude areas or near rivers and those regions affected by tropical storms. This study examined flood vulnerability in three rural villages in South Africa’s northern Limpopo Province and how communities are building resilience and coping with the hazard. These villages lie at the foot of the north-eastern escarpment, and are often exposed to frequent rainfall enhanced by orographic factors. Although extreme rainfall events are rare in the study area, we analyzed daily rainfall and showed how heavy rainfall of short duration can lead to flooding using case studies. Historical floods were also mapped using remote sensing via the topographical approach and two types of flooding were identified, i.e., those due to extreme rainfall and those due to poor drainage or blocked drainage channels. A field survey was also conducted using questionnaires administered to samples of affected households to identify flood vulnerability indicators and adaptation strategies. Key informant interviews were held with disaster management authorities to provide additional information on flood indicators. Subsequently, a flood vulnerability index was computed to measure the extent of flood vulnerability of the selected communities and it was found that all three villages have a ‘vulnerability to floods’ level, considered a medium level vulnerability. The study also details temporary and long-term adaptation strategies/actions employed by respondents and interventions by local authorities to mitigate the impacts of flooding. Adaptation strategies range from digging furrows to divert water and temporary relocations, to constructing a raised patio around the house. Key recommendations include the need for public awareness; implementation of a raft of improvements and a sustainable infrastructure maintenance regime; integration of modern mitigations with local indigenous knowledge; and development of programs to ensure resilience through incorporation of Integrated Development Planning.
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