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1. Country-level land carbon sink and its causing components by the middle of the twenty-first century

   https://doi.org/10.1186/s13717-021-00328-y  

   Jiang, Lifen; Liang, Junyi; Lu, Xingjie; Hou, Enqing; Hoffman, Forrest M.; Luo, Yiqi (September 2021, Ecological Processes)

   Abstract BackgroundCountries have long been making efforts by reducing greenhouse-gas emissions to mitigate climate change. In the agreements of the United Nations Framework Convention on Climate Change, involved countries have committed to reduction targets. However, carbon (C) sink and its involving processes by natural ecosystems remain difficult to quantify. MethodsUsing a transient traceability framework, we estimated country-level land C sink and its causing components by 2050 simulated by 12 Earth System Models involved in the Coupled Model Intercomparison Project Phase 5 (CMIP5) under RCP8.5. ResultsThe top 20 countries with highest C sink have the potential to sequester 62 Pg C in total, among which, Russia, Canada, USA, China, and Brazil sequester the most. This C sink consists of four components: production-driven change, turnover-driven change, change in instantaneous C storage potential, and interaction between production-driven change and turnover-driven change. The four components account for 49.5%, 28.1%, 14.5%, and 7.9% of the land C sink, respectively. ConclusionThe model-based estimates highlight that land C sink potentially offsets a substantial proportion of greenhouse-gas emissions, especially for countries where net primary production (NPP) likely increases substantially and inherent residence time elongates. 

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2. The Environmental Bias of Trade Policy*

   https://doi.org/10.1093/qje/qjaa042  

   Shapiro, Joseph S (December 2020, The Quarterly Journal of Economics)

   Abstract This article describes a new fact, then analyzes its causes and consequences: in most countries, import tariffs and nontariff barriers are substantially lower on dirty than on clean industries, where an industry’s “dirtiness” is defined as its carbon dioxide (CO2) emissions per dollar of output. This difference in trade policy creates a global implicit subsidy to CO2 emissions in internationally traded goods and contributes to climate change. This global implicit subsidy to CO2 emissions totals several hundred billion dollars annually. The greater protection of downstream industries, which are relatively clean, substantially accounts for this pattern. The downstream pattern can be explained by theories where industries lobby for low tariffs on their inputs but final consumers are poorly organized. A quantitative general equilibrium model suggests that if countries applied similar trade policies to clean and dirty goods, global CO2 emissions would decrease and global real income would change little. 

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3. Antimicrobial Resistance and Livestock Trade for Low and Middle Income Countries: Regional Analysis of Global Coordination Policies

   https://doi.org/10.3389/fsufs.2021.650315  

   Avraam, Charalampos; Lambrou, Anastasia S.; Jiang, Wei; Siddiqui, Sauleh (March 2021, Frontiers in Sustainable Food Systems)

   null (Ed.)

   Antimicrobial resistance is a threat to global health, aggravated by the use of antimicrobials in livestock production. Mitigating the growing economic costs related to antimicrobial use in livestock production requires strong global coordination, and to that end policy makers can leverage global and national food animal trade policies, such as bans and user fees. Evaluation of such policies requires representing the interactions between competing producers in the global meat market, which is usually out of the scope of statistical models. For that, we developed a game-theoretic food system model of global livestock production and trade between 18 countries and aggregate world regions. The model comprises the largest producing and consuming countries, the explicit interconnections between countries, and the use of antimicrobials in food animal production. Our model allows us to provide policy insights beyond standard literature and assess the trade-off between trade, cost of a policy, and antimicrobials-induced productivity. We studied three scenarios: global increased user fees on antimicrobials, a global ban of meat imports from Brazil, and a decrease in China's meat consumption. We found that a user fee that increases the price of antimicrobials by 50% globally leads to a 33% reduction in global antimicrobial use. However, participation of developing and emerging countries in the coordination scheme is jeopardized, since they become less competitive for meat sales compared to developed countries. When meat imports from Brazil are banned globally, importers of Brazil's meat would turn primarily to the U.S. to supplement their demand. Lastly, meeting China's medium-term lower meat consumption target would not affect global antimicrobial use, but could increase China's antimicrobial use by 11%. We highlighted the importance of trade for the outcome of a policy and concluded that global cooperation is required to align the incentives of all countries toward tackling antimicrobial resistance. 

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4. A Method for Estimating Driving Factors of Illicit Trade Using Node Embeddings and Clustering

   https://doi.org/10.1007/978-3-030-49076-8_22  

   González Ordiano, Jorge Ángel; Finn, Lisa; Winterlich, Anthony; Moloney, Gary; Simske, Steven (April 2020, Mexican Conference on Pattern Recognition)

   The trade on illegal goods and services, also known as illicit trade, is expected to drain 4.2 trillion dollars from the world economy and put 5.4 million jobs at risk by 2022. These estimates reflect the importance of combating illicit trade, as it poses a danger to individuals and undermines governments. To do so, however, we have to fi rst understand the factors that influence this type of trade. Therefore, we present in this article a method that uses node embeddings and clustering to compare a country based illicit supply network to other networks that represent other types of country relationships (e.g., free trade agreements, language). The results offer initial clues on the factors that might be driving the illicit trade between countries. 

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5. Unequal climate impacts on global values of natural capital

   https://doi.org/10.1038/s41586-023-06769-z  

   Bastien-Olvera, B A; Conte, M N; Dong, X; Briceno, T; Batker, D; Emmerling, J; Tavoni, M; Granella, F; Moore, F C (January 2024, Nature)

   Abstract Ecosystems generate a wide range of benefits for humans, including some market goods as well as other benefits that are not directly reflected in market activity¹. Climate change will alter the distribution of ecosystems around the world and change the flow of these benefits^2,3. However, the specific implications of ecosystem changes for human welfare remain unclear, as they depend on the nature of these changes, the value of the affected benefits and the extent to which communities rely on natural systems for their well-being⁴. Here we estimate country-level changes in economic production and the value of non-market ecosystem benefits resulting from climate-change-induced shifts in terrestrial vegetation cover, as projected by dynamic global vegetation models (DGVMs) driven by general circulation climate models. Our results show that the annual population-weighted mean global flow of non-market ecosystem benefits valued in the wealth accounts of the World Bank will be reduced by 9.2% in 2100 under the Shared Socioeconomic Pathway SSP2-6.0 with respect to the baseline no climate change scenario and that the global population-weighted average change in gross domestic product (GDP) by 2100 is −1.3% of the baseline GDP. Because lower-income countries are more reliant on natural capital, these GDP effects are regressive. Approximately 90% of these damages are borne by the poorest 50% of countries and regions, whereas the wealthiest 10% experience only 2% of these losses. 

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