Sustainable development goals (SDGs) are outlined in the United Nations' 2030 agenda to combat climate change. It proposes various policy recommendations and instruments to aid in the transition to green growth and the mitigation process. This research examines how carbon taxes and technological advancements (mitigation techniques) affected OECD regions' demand, supply, and total emissions from 2000 to 2020. Cross-sectional dependencies necessitate error correction-based modelling approaches to examine the long-term relationship between the variables. The PMG-ARDL model estimates overall carbon emissions, whereas IPAT and STIRPAT determine emissions from demand and production. The findings provide more evidence of a long-run link between the variables. For example, in OECD countries, water and wastewater technology may offset production-based emissions by 18%, production and processing innovation by 12%, energy generation/transmission by 8%, and transportation-related emissions by 11%, while agriculture technologies are also helping curb emissions by 14%. In addition, environmental taxes reduce carbon emissions by 22% in the short term and 9% in the long run. However, energy consumption is the primary source of pollution across all economic sectors. In short, the findings show that policy objective attainment tends to be sub-regional (Asia-Oceania, America, Europe)—nonetheless, carbon levies and mitigation technology aid progress toward the SDGs of carbon reduction.

Canada is amongst the highest food waste-producing countries on a per capita basis. Landfilling is one of the main methods for food waste management which leads to an economical loss of $3 billion/year. To mitigate such losses, sustainable and cost-effective solutions for the management of food waste are being intensively researched. Food waste is readily biodegradable and can be used as a feedstock to produce high-value chemicals such as short-chain volatile fatty acids (SCFAs) via acidogenic fermentation process. Leach bed reactors (LBRs) are gaining a lot of attention as sustainable bioreactor platforms for SCFA production. However, before successful practical implementation, the two key challenges such as clogging at high volumetric loading (>25 gVS/Lreactor) and long fermentation time (14 days) need to be resolved.

A novel solid-state submerged fermenter (3SF) design was developed and investigated for SCFA production. The reactor is comprised of a completely perforated food waste holding chamber which is fully submerged in the inoculum, preventing clogging issues even at high organic loading of >50 gVS/Lreactor. The 3SF was successfully tested at higher inoculum/substrate (ISR) ratios of 4%,6%, 9%, and 16% and achieved 53 - 62% volatile solids reduction, hydrolysis yield between 573 g cumsCOD/gVSadded, and VFA yields of 530 g cumsCOD/gVSadded . Acetate and butyrate were (70 to 80%) dominant SCFAs. Further improvements in the physical design of the 3SF enhanced the reactor performance by 5-7%. Hence, the proposed novel solid-state fermentation reactor design can also be a potential food waste fermentation system for the biorefinery platform.

Developing high yield and drought tolerant crops will be helpful in achieving and sustaining food security. The high throughput plant phenotyping provides plant biomass, leaf characteristics, growth, yield, stress, and tolerance information and imaging of root system architecture is emerging as a frontier area for breeding for better root traits associated with nitrogen- and water- use efficiencies, biological carbon sequestration, The information provided by phenomics is also useful in selecting suitable genetic lines which can provide better yield, and many more desired characteristics. Plant phenotyping data is obtained by using noninvasive imaging technologies in both indoor (greenhouse and control environmental chambers) and from the field. The red, green, and blue (RGB) color imaging technology is the most widely used to collect phenotyping data. Other methods like multispectral-, hyperspectral-, X-ray- and thermal imaging are also used combined with different image processing and data analytics procedure. This review will provide more information about how phenomics will complement genomics and also provides a detailed outline about different conventional and emerging imaging techniques and how it is used in both indoor (tabletop imaging systems) and outdoor (drone based) environment, their advantages, and disadvantages. The review also provides information about many image processing and data analytics platforms.