Identifying resource-conscious and low-carbon agricultural development pathways through land use modelling.

Increasing agricultural production with current resources and technology may lead to increased GHG emissions. Additionally, large population countries like India face substantial challenges in terms of food demand, agro-ecological heterogeneity, carbon footprint and depleting natural resources, thus increasing the decision complexities for policymakers and planners. We aim to examine the potential of producing more food from available agricultural land with low-carbon (reduced GHG emissions) and resource-conscious (optimal resource use) options. The current study develops multiple calorie production and emission-centric land use using a land use optimization model wherein the calorie production and emission objective, resource and emissions constraints, and food production targets interact across multiple spatial levels. The capabilities of the developed model are demonstrated with a case study in India targeting ten crops (grown over two seasons) covering three food groups (cereals, legumes, and oilseeds). Three hypothetical scenarios for each objective of maximizing calories production (Calories-nation, Calories-group, Calories-crop) and minimizing GHG emissions (Emissions-nation, Emissions-group, Emissions-crop) are developed concerning targets of national crop production (Calories-nation, Emissions-nation), state food groups production (Calories-group, Emissions-group), and state crop production(Calories-crop, Emissions-crop), with different spatial levels of constraints. A maximum growth of 11% in calorie production is observed in Calories-nation while mitigating 2.5% emissions. Besides, the highest emission reduction of around 30% is observed in Emissions-group but with no change in calorie production. Emission scenarios can spare up to 14.8% land and 18.2% water, while calorie production-maximization scenarios can spare a maximum of 4.7% land and 6.5% water. The optimization-based methodology identifies the regions of altered land use by proposing appropriate crop substitution strategies, such as increasing oilseeds in Rajasthan and soybean in east Maharashtra. Many states show conservative production growth and emission reduction with state-level crop production targets (Calories-crop), suggesting crop redistribution within the state alone will not be sufficient unless improved technologies are introduced. The maximum growth and mitigation potential estimated in this study may be affected by climate shocks; therefore, introducing the improved technologies needs to be coupled with a crop redistribution mechanism to design climate-resilient and futuristic land use systems. The proposed land use model can be modified to incorporate climate change effects through consideration of scenarios of changed crop yields or through direct/indirect coupling with dynamic crop simulation models.

Assessing greenhouse gas emissions from the printing and dyeing wastewater treatment and reuse system: Potential pathways towards carbon neutrality.

The urgency of achieving carbon neutrality needs a reduction in greenhouse gas (GHG) emissions from the textile industry. Printing and dyeing wastewater (PDWW) plays a crucial role in the textile industry. The incomplete assessment of GHG emissions from PDWW impedes the attainment of carbon neutrality. Here, we firstly introduced a more standardized and systematic life-cycle GHG emission accounting method for printing and dyeing wastewater treatment and reuse system (PDWTRS) and proposed possible low-carbon pathways to achieve carbon neutrality. Utilizing case-specific operational data over 12 months, the study revealed that the PDWTRS generated 3.49 kg CO2eq/m3 or 1.58 kg CO2eq/kg CODrem in 2022. This exceeded the GHG intensity of municipal wastewater treatment (ranged from 0.58 to 1.14 kg CO2eq/m3). The primary contributor to GHG emissions was energy consumption (33 %), with the energy mix (sensitivity = 0.38) and consumption (sensitivity = 0.33) exerting the most significant impact on GHG emission intensity respectively. Employing prospective life cycle assessment (LCA), our study explored the potential of the anaerobic membrane bioreactor (AnMBR) to reduce emissions by 0.54 kg CO2eq/m3 and the solar-driven photocatalytic membrane reactor (PMR) to decrease by 0.20 kg CO2eq/m3 by 2050. Our projections suggested that the PDWTRS could achieve net-zero emissions before 2040 through an adoption of progressive transition to low-carbon management, with a GHG emission intensity of -0.10 kg CO2eq/m3 by 2050. Importantly, the study underscored the escalating significance of developing sustainable technologies for reclaimed water production amid water scarcity and climate change. The study may serve as a reminder of the critical role of PDWW treatment in carbon reduction within the textile industry and provides a roadmap for potential pathways towards carbon neutrality for PDWTRS.

The heterogeneous driving forces behind carbon emissions change in 30 selective emerging economies.

Emerging economies are predicted to be future emission hotspots due to expected levels of urbanization and industrialization, and their CO2 emissions are receiving more scrutiny. However, the driving forces underlying dynamic change in emissions are poorly understood, despite their crucial role in developing targeted mitigating pathways. We firstly compile energy-related emissions of 30 selective emerging economies from 2010 to 2018. Then, three growth patterns of emissions in these economies have been identified through emission data, which imply different low-carbon pathways. Most emerging economies saw an increase of varying degrees in emissions, driven by economic growth and partly offset by better energy efficiency and improvements in energy mixes. Furthermore, the industrial structure was another factor that slowed emissions, especially in Latin America and the Caribbean. Our research contributes to the heterogeneous exploration of CO2 emissions produced by energy among sectors and the creation of low-carbon development pathways in emerging economies.

A systematic review of transportation carbon emissions based on CiteSpace.

Transportation sector has become a major contributor to the escalation of carbon emissions and subsequent climate change. In this study, a bibliometric analysis was conducted using CiteSpace on published papers (1991-2022). Then a theoretical framework was proposed through traditional content analysis from three aspects: measurement, mechanism analysis, and low-carbon pathways analysis. The clustering results show that the research topics have involved mainly factor analysis, evaluation, system analysis, control measurement and pollutants. A further summary of the content of the relevant literature shows that there are five main accounting methods for measuring transportation carbon emissions (TCEs), which can be applied to different scenarios. Studies involving the spatio-temporal distribution of TCEs is limited and mainly focus on macroperspectives. The mechanism of TCEs involves three main aspects: system assessment, efficiency measurement, and driver analysis, which serve to identify the internal patterns of TCEs. Finally, the outlook regarding TCEs is presented.

LEAP-Based Greenhouse Gases Emissions Peak and Low Carbon Pathways in China's Tourist Industry.

China has grown into the world's largest tourist source market and its huge tourism activities and resulting greenhouse gas (GHG) emissions are particularly becoming a concern in the context of global climate warming. To depict the trajectory of carbon emissions, a long-range energy alternatives planning system (LEAP)-Tourist model, consisting of two scenarios and four sub-scenarios, was established for observing and predicting tourism greenhouse gas peaks in China from 2017 to 2040. The results indicate that GHG emissions will peak at 1048.01 million-ton CO2 equivalent (Mt CO2e) in 2033 under the integrated (INT) scenario. Compared with the business as usual (BAU) scenario, INT will save energy by 24.21% in 2040 and reduce energy intensity from 0.4979 tons of CO2 equivalent/104 yuan (TCO2e/104 yuan) to 0.3761 Tce/104 yuan. Although the INT scenario has achieved promising effects of energy saving and carbon reduction, the peak year 2033 in the tourist industry is still later than China's expected peak year of 2030. This is due to the growth potential and moderate carbon control measures in the tourist industry. Thus, in order to keep the tourist industry in synchronization with China's peak goals, more stringent measures are needed, e.g., the promotion of clean fuel shuttle buses, the encouragement of low carbon tours, the cancelation of disposable toiletries and the recycling of garbage resources. The results of this simulation study will help set GHG emission peak targets in the tourist industry and formulate a low carbon roadmap to guide carbon reduction actions in the field of GHG emissions with greater certainty.