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The emerging economies of Brazil, Russia, India, China and South Africa (BRICS) have significant influence on the global economic and environmental trajectories. They have carbon intensive economic systems, which contribute significantly to total global greenhouse gas (GHG) emissions, leading to climate change. However, BRICS have joined the race to net-zero emissions by 2050 in the quest for a climate neutral and sustainable global economy. The journey, however, is not without challenges and opportunities. The proliferation of the coronavirus disease 2019 (COVID-19) had mixed reactions from scientists regarding its implications on net-zero trajectories. While statistical data show a correlation between COVID-19 and a decrease in total emissions, it is envisaged that COVID-19 compromised the efforts to develop carbon neutral economies. Hence, there is still need for more scientific examination of COVID-19's impact on net-zero ambitions, especially in the emerging economies. This study focuses on India and South Africa's trajectories. Statistical analysis of secondary data from authentic interactive web-based dashboards for COVID-19 data repositories, namely Our World in Data and Climate Action Tracker was performed in conjunction with the document analysis approach following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) methodology. Some of the COVID-19 challenges as indicated by the results of the study include curtailing the technology transfer staircase in the energy sector, retaliatory emissions for recovery and resource diversion. The opportunities presented by COVID-19 in the quest for carbon neutrality include behavioural changes in investment, production and consumption patterns with a focus on low carbon options. Governments and stakeholders need to focus on addressing the barriers whilst riding on the opportunities presented by the pandemic to achieve net-zero emissions by 2050. [ABSTRACT FROM AUTHOR]

There is a strong coordinated effort by vaccination groups all over the world to put an end to the current crisis of COVID-19. Now sufficient data are available to analyse and compare some results to explore the aftereffects of vaccination. Some influence variables on transmissions of the disease were discussed e.g., mass vaccination, lockdown and seasonality. Most studies covered here are up to the beginning of July 2022, while some analyses focused on the earlier period of mass vaccination. Well established, simple statistical techniques to evaluate results were presented those used open data sources of authoritative bodies. Some comparisons between vaccinated vs. unvaccinated were also discussed based on data from UK Government Health Security Agency (UHSA). In terms of mass vaccination, adverse reactions after vaccination received attention, as health and safety issues of the general public are of prime importance. Apart from direct side effects, the secondary effect of mass vaccination needs attention too. After the initiation of the vaccination programme, almost all countries experienced a sudden surge in transmission and most countries had to impose strict lockdown measures. Many countries, with a low prevalence of disease, suddenly showed a steep jump and some countries even followed a synchronized pattern between the rate of transmissions and the variation of vaccine doses. Time series analyses and bar diagram presentations were able to capture those features. In that context, fast mutation of the virus and new variants after mass vaccination and possible mechanisms/consequences were also attended. To understand the effect of seasonality, similarities between COVID-19 and the seasonal Flu are discussed for Europe and US to gain useful insight. Using time series analyses and spatial plots of regional temperature composites we showed, like Flu, seasonality played a dominant role in transmissions of COVID-19 in the Europe. Regulations of vaccine dose and policy implication were explored too. From 22nd December 2021, global vaccine doses were reduced substantially, which followed a dramatic reduction in cases and thereafter deaths with around one month's lag between each. As strong dependency on seasonality is noticed in certain countries and observing that regulation of vaccine doses has roles in modulating the transmission with certain lags, globally as well as regionally, our results have policy implications for the management of COVID. Debating, questioning and criticism are always the foundation of great science and the major pillars of its progress. Following that objective, it is an effort to explore pragmatically, supported by scientific analyses, areas relating to the effectiveness of the COVID-19 vaccine and the exit strategy via the pathway of vaccination. • An effort to critically explore exit strategy of COVID via pathways of vaccine. • Understand seasonality, similarities between COVID and seasonal Flu are discussed. • Fast mutation of this virus and new variants after mass vaccination are discussed. • After initiation of vaccination programme, most countries experienced sudden surge. • Knowledge of seasonality and regulation of vaccine doses have important policy implication. [ABSTRACT FROM AUTHOR]

Soil erosion has become a common feature in certain national parks across the global biomes, and national parks in the Savanna biome of South Africa have not been spared. Given their prominence in hosting large land mammals that contribute significantly to the tourism sector, the vulnerability of the parks to soil erosion merits attention. This study examines soil erosion status in the Savanna biome national parks of South Africa to recommend management practices aligned with the degree of erosion susceptibility. The results show that erosion rates across the national parks range between 0 and 25 t/ha/yr, and only a few have soil loss rates above 25 t/ha/yr. The Kgalagadi National Park has the lowest erosion rates, with a water erosion severity index (ESI) of 0. The Kruger and Mokala National Parks have low erosion rates, with an ESI of 0.017 and 0.01, respectively. The Mapungubwe National Park has moderate rates of soil loss, with an ESI of 0.023, while Marakele has the highest rates of soil erosion, with an ESI of 0.39. Soil erosion by water action is generally a minor environmental threat for the Kgalagadi, Kruger and Mokala National Parks. However, for Mapungubwe, soil erosion has a moderate threat, while in Marakele, it imposes a very high threat level. The different rates of soil erosion are attributed to the heterogeneous biophysical conditions of the Savanna biome, as well as different historical land use patterns across the parks. Climate change could be exacerbating the susceptibility of national parks to soil erosion. Park-specific management strategies that consider historical land use patterns and biophysical conditions within a climate change context are recommended. • Soil erosion in Savanna South African national parks range between 0 and 25 t ha−1 yr−1. • Erosion severity is lowest in Kgalagadi National Park (ESI = 0). • Erosion severity is highest in Marakele National Park (ESI = 0.39). • The Kruger, Mokala and Mapungubwe have low to moderate erosion rates. • The heterogeneous biophysical conditions and historical land use influence erosion. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic poses a severe threat to public health, resulting in high levels of mortality and morbidity. In response, there has been a significant usage of hand sanitizers in homes, public places, and healthcare systems. In the global panic, the market has a variety of products, and there are serious concerns about the safety and the potential of hand sanitization as the blue bullet for COVID-19. Therefore, this article presents a critical review of types of hand sanitizers available on the market, their active ingredients coupled with their mode of action in the wake of antiviral efficacies. In addition, the adoption of a culture of hand sanitization by society could raise the demand for hand sanitizers for an extended period. The continuous use of hand sanitizers might pose some safety concerns. Consequently, the review articulates potential dangers associated with hand sanitizer used to equip suppliers and manufacturers with knowledge on the safety of different ingredients and formulations, hence safeguarding the final users. [ABSTRACT FROM AUTHOR]

Abstract: Knowledge of soil spatial variability is important in natural resource management, interpolation and soil sampling design, but requires a considerable amount of geo-referenced data. In this study, mid-infrared spectroscopy in combination with spatial analyses tools is being proposed to facilitate landscape evaluation and monitoring. Mid-infrared spectroscopy (MIRS) and geostatistics were integrated for evaluating soil spatial structures of three land settlement schemes in Zimbabwe (i.e. communal area, old resettlement and new resettlement; on loamy-sand, sandy-loam and clay soils, respectively). A nested non-aligned design with hierarchical grids of 750, 150 and 30m resulted in 432 sampling points across all three villages (730–1360ha). At each point, a composite topsoil sample was taken and analyzed by MIRS. Conventional laboratory analyses on 25–38% of the samples were used for the prediction of concentration values on the remaining samples through the application of MIRS–partial least squares regression models. These models were successful (R 2 ≥0.89) for sand, clay, pH, total C and N, exchangeable Ca, Mg and effective CEC; but not for silt, available P and exchangeable K and Al (R 2 ≤0.82). Minimum sample sizes required to accurately estimate the mean of each soil property in each village were calculated. With regard to locations, fewer samples were needed in the new resettlement area than in the other two areas (e.g. 66 versus 133–473 samples for estimating soil C at 10% error, respectively); regarding parameters, less samples were needed for estimating pH and sand (i.e. 3–52 versus 27–504 samples for the remaining properties, at same error margin). Spatial analyses of soil properties in each village were assessed by constructing standardized isotropic semivariograms, which were usually well described by spherical models. Spatial autocorrelation of most variables was displayed over ranges of 250–695m. Nugget-to-sill ratios showed that, in general, spatial dependence of soil properties was: new resettlement>old resettlement>communal area; which was potentially attributed to both intrinsic (e.g. texture) and extrinsic (e.g. management) factors. As a new approach, geostatistical analysis was performed using MIRS data directly, after principal component analyses, where the first three components explained 70% of the overall variability. Semivariograms based on these components showed that spatial dependence per village was similar to overall dependence identified from individual soil properties in each area. In fact, the first component (explaining 49% of variation) related well with all soil properties of reference samples (absolute correlation values of 0.55–0.96). This showed that MIRS data could be directly linked to geostatistics for a broad and quick evaluation of soil spatial variability. It is concluded that integrating MIRS with geostatistical analyses is a cost-effective promising approach, i.e. for soil fertility and carbon sequestration assessments, mapping and monitoring at landscape level. [Copyright &y& Elsevier]