Decomposing high uncertainty in greenhouse gas mitigation pathways in emerging regions: An approach to evaluate risks toward carbon neutrality.

In the context of ambitious greenhouse gas (GHG) mitigation strategies in emerging regions, addressing the prevailing uncertainty and its key influential factors is crucial. While uncertainty analysis of GHG mitigation pathways has been extensively explored, the systematic identification and quantification of pivotal factors has been notably absent. This study introduces a novel methodology that combines Quasi-Monte Carlo simulation with Sobol variance decomposition, which identifies key influential factors and traces the flow of uncertainties. Applied in Anhui Province, a rapidly developing region in China, our findings indicate an uncertain GHG emission proportion of 6.2 % by 2030, escalating to 68.6 % by 2060, with a 95 % confidence interval. This uncertainty results in a cumulative projection error of 2.1 billion tons of CO2e from 2020 to 2070. The per capita GDP factor emerges as the predominant influence, alongside the increasing impact of renewable energy factor and UHV import electricity factor. In our uncertainty flow analysis, the energy transformation sector is identified as the principal contributor to total uncertainty, driven significantly by economic and energy-related factors. These results underscore the critical need for policymakers in emerging regions to incorporate uncertainty decomposition analysis into their strategic planning to mitigate risks in GHG reduction efforts.

PM2.5 air quality and health gains in the quest for carbon peaking: A case study of Fujian Province, China.

China faces a dual challenge of improving air quality and reducing greenhouse gas (GHG) emissions. Stringent clean air actions gradually narrow the end-of-pipe (EOP) pollution control potential. Meanwhile, pursuing carbon peaking will reduce air pollution and health risks. However, the impact on air quality and health gains in individual Chinese provinces has not been assessed with a specific focus on local policies. Here, typical shared socio-economic pathways (SSPs) and local policies (i.e., business as usual, BAU; end-of-pipe controls, EOP; co-control mitigation, CCM) are combined to set three scenarios (i.e., BAU-SSP3, EOP-SSP4, CCM-SSP1). Under these three scenarios, we couple the Low Emissions Analysis Platform (LEAP) model, an air quality model and health risk assessment methodology to evaluate the characteristics of carbon peaking in Fujian Province. PM2.5 air quality and impacts on public health are assessed, using the metric of the deaths attributable to PM2.5 pollution (DAPP). The results show that energy-related CO2 emissions will only peak before 2030 in the CCM-SSP1 scenario. In this context, air pollutant emission pathways reveal that mitigation is limited under the EOP-SSP4 scenario, necessitating further mitigation under the CCM-SSP1 scenario. The annual average PM2.5 level is projected to be 16.5 µg·m-3 in 2035 with a corresponding decrease in DAPP of 297 (95 % confidence intervals: 217-308) compared with that of 2020. Despite the significant improvements in PM2.5 air quality and health gains under the CCM-SSP1 scenario, reaching the 5 µg·m-3 target of the World Health Organization (WHO) remains difficult. Furthermore, population aging will require stronger PM2.5 mitigation to enhance health gains. This study provides a valuable reference for other developing regions to co-control air pollution and GHGs.

Drivers of the increasing water footprint in Africa: The food consumption perspective.

In Africa, water resources pervade multiple sustainable development goals (SDGs), which mainly focus on eliminating poverty (SDG 1) and hunger (SDG 2), promoting good health and well-being (SDG 3) and supporting clean water and sanitation (SDG 6). Africa's water scarcity problems have been worsened by population growth and climate change. Agriculture is the largest consumer of water in Africa, and a clear understanding of the water-food nexus is necessary to effectively alleviate water-related pressures on food security. Water footprint (WF) accounts and decompositions provide insights into water management planning for policy-makers. We investigated the WF of food consumption from 2000 to 2018 in 23 African countries and used the logarithmic mean Divisia index (LMDI) to decompose its driving forces into consumption structure, per capita food consumption, water intensity and population effect. The WF of food consumption increased from 609.8 km3 in 2000 to 1212.9 km3 in 2018, with an average annual growth rate of 3.7%. The population effect contributed most to this change (64.6%), followed by per capita food consumption (28.3%) and consumption structure (7.1%). Cereals (46.7%) and livestock (24.4%) were the major contributors to the increase in the total WF. Our findings highlight that controlling population growth and improving water efficiency are effective measures to relieve water-related pressures on food consumption. However, a healthy dietary structure must also be promoted because Africa's current dietary energy level is below the global average. Moreover, nine countries in the research area have an inadequate supply of dietary energy; this will inevitably drive the WF of food, as calories increase and diets change. This study is helpful for understanding the water-food nexus in Africa and provides strategies to conserve water and enhance food production.