A critical review on global CO2 emission: where do industries stand?

Global CO2 emissions from different industries have been increasing at an alarming rate. This growth is outpacing the efforts, nations are putting in place to reduce their carbon footprints. In this topical review, we critically analyze the level of CO2 emissions on a global scale and across various industries and activities within them and the dominant anthropogenic forcing instability. The global CO2 emission from various economic sectors such as industries, transportation and variety of waste sources were traced globally and regionally. To contextualize our review, the sector wise CO2 emission trends data for a period more than a decade is reviewed which highlighted the main sources of emissions. The data shows the overall reduction of carbon footprints and its progress across various sectors is very limited. The governing factors for this continued global pattern can be ascribed to two main factors: high consumer demands, and poor efforts towards shifting low and zero carbon services across all sectors. Some efforts have been witnessed to shift towards clean fuels and renewables, particularly in Europe and North America. However, rapid growth in industrialization limits the shifting of fossil-based energy systems towards less harmful systems. In Asia, particularly in eastern, southern, and south-eastern regions, the carbon footprints were found to increased owing to a huge demand for materials production, travelling and energy services. Therefore, it is of utmost importance to identify, understand and tackle the most persistent and climate-harmful factors across all industries and drive such policies to substitute the fossil fuels with renewables.

Predicting visceral adipose tissue in older adults: A pilot clinical study.

BACKGROUND & AIMS: Visceral adipose tissue (VAT) is a recognized risk factor for cardiometabolic disease, and dual energy X-ray absorptiometry (DXA) has been recently validated for the quantification of VAT. This study aims to explore VAT prediction by utilizing bioimpedance analysis (BIA), anthropometric measures and biochemical markers. METHODS: Data from BIA, anthropometric measures, biochemical markers and DXA scans were collected in 1064 older adults participants (761 F, 303 M) with a mean age of 82 ± 6 years old. DXA-VAT was quantified at the android region (DXA-VAT - volume cm3) using the enCore software. Multifactorial linear regression analysis was used to establish the proposed predicting equations and define the values more associated with VAT. RESULTS: In our multivariate model, the main VAT predictable markers were in both genders, weight (kg), Triglycerides (mmol/L) and height (m). These models (stratified for gender) included the BIA outcomes as regressor factors. The VAT calculation equation formula was VAT = 148.89 + (weight (kg)∗33.81) + (Trg (mmol/L)∗1.41) + (height (m)∗-8.99) for females and VAT = 1481.22 + (weight (kg)∗43.94) + (Trg (mmol/L)∗-21.27) + (height (m)∗3.57) for males. In both equations, the r2 was 0.76. The Network analysis showed a strong link network between weight and resistance (Rz). CONCLUSIONS: The independent and combined use of anthropometric measures and biochemical markers could accurately predict VAT in the older adults' population. Because of the strong link between Rz and weight, BIA might be included in future equations predicting VAT but different data pools and populations are needed.