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This book offers a comprehensive practitioner's guide to negotiating at the United Nations. Although much of the content can be applied broadly, the guide focuses onnavigating multilateral negotiations at the UN. The book is a tool to help new UN negotiators, explaining basic negotiation concepts and offering insight into the complexities of the UN system. Italsooffers a playbook for cooperation for negotiators at any level, exploring the dynamics of relationships and alliances, the art of chairing a negotiation, and the importance of balancing the power asymmetries present in any multilateral discussion.The book proposes improvements to the UN negotiation process and looks at the impact of information technologies on negotiation dynamics; it alsoshares stories from women UN delegates,illustrating what it means to be a female negotiator at the UN. This book is an exploration of the power of the individual in any negotiation, and of the responsibility all negotiators have in wielding that power to speak for a better world. This book will be of much interest to students of diplomacy, global governance, foreign policy, and International Relations, as well as practitioners and policymakers.

Abstract
China has made great progress in the electrification of passenger cars, and the sales of battery electric vehicles (BEVs) have exceeded 10%. We applied a life-cycle assessment (LCA) method to estimate the carbon dioxide (CO2) emissions of the past (2015), present (2020), and future (2030) BEVs, incorporating China's carbon peaking and neutrality policies, which would substantially reduce emissions from the electricity, operation efficiency, metallurgy, and battery manufacturing industries. BEVs can reduce cradle-to-grave (C2G) CO2 emissions by ∼40% compared with internal combustion engine vehicles (ICEVs) on the national-average level in 2020, far more significant than the benefit in 2015. Improved BEV operating efficiency was the largest factor driving emission reductions from 2015 to 2020. Looking forward to 2030, China's BEVs equipped with nickel–cobalt–manganese (NCM) batteries can achieve a further 43% of CO2 emissions reductions, among which 51 g km−1 of reduction is from the well-to-wheels (WTW) stage majorly owing to the further cleaner electricity mix, while other vehicle-cycle benefits are mainly from the advancement of battery (12 g km−1) and related metal materials (5 g km−1). We highlight the importance of better material efficiency and synchronized decarbonization through the automotive industrial chain in promoting climate mitigation from transport activities.

PurposeThe paper aims to study the relationship between corporate social responsibility, green supply chain management, and operational performance and the moderating effects of relational capital on these relationships.Design/methodology/approachThe authors conduct an empirical study with a structural equation modeling approach to investigate the relationship between corporate social responsibility—constructed by the quality and environmental responsibility, green supply chain management—including green supplier and customer management and operational performance—manifested by quality, cost, flexibility, and delivery performance using data from 308 manufacturers in China. Besides, the authors explore the moderating effect of supplier and customer relational capital on these relationships.FindingsThe findings indicate that a company's quality and environmental responsibility significantly impacts its green supply chain management practices, which further improve its operational performance in quality, cost, flexibility, and delivery. In addition, supplier and customer relational capital strengthens the influence of environmental responsibility on green supply chain management. While supplier relational capital reinforces the impact of green supplier management on flexibility and delivery performance, customer relational capital only strengthens the influence of green customer management on flexibility performance.Originality/valueThe study enriches the extant literature by developing a holistic framework integrating corporate social responsibility, green supply chain management, relational capital, and operational performance and unraveling their intricate relationships. The authors' findings help practitioners prioritize proactive steps in environmental conservation more than achieving operational performance.

On-road vehicle emissions are a major contributor to elevated air pollution levels in populous metropolitan areas. We developed a link-level emissions inventory of vehicular pollutants, called EMBEV-Link (Link-level Emission factor Model for the BEijing Vehicle fleet), based on multiple datasets extracted from the extensive road traffic monitoring network that covers the entire municipality of Beijing, China (16 400 km 2 ). We employed the EMBEV-Link model under various traffic scenarios to capture the significant variability in vehicle emissions, temporally and spatially, due to the real-world traffic dynamics and the traffic restrictions implemented by the local government. The results revealed high carbon monoxide (CO) and total hydrocarbon (THC) emissions in the urban area (i.e., within the Fifth Ring Road) and during rush hours, both associated with the passenger vehicle traffic. By contrast, considerable fractions of nitrogen oxides ( NO x ), fine particulate matter (PM 2.5 ) and black carbon (BC) emissions were present beyond the urban area, as heavy-duty trucks (HDTs) were not allowed to drive through the urban area during daytime. The EMBEV-Link model indicates that nonlocal HDTs could account for 29 % and 38 % of estimated total on-road emissions of NO x and PM 2.5 , which were ignored in previous conventional emission inventories. We further combined the EMBEV-Link emission inventory and a computationally efficient dispersion model, RapidAir ® , to simulate vehicular NO x concentrations at fine resolutions (10 m × 10 m in the entire municipality and 1 m × 1 m in the hotspots). The simulated results indicated a close agreement with ground observations and captured sharp concentration gradients from line sources to ambient areas. During the nighttime when the HDT traffic restrictions are lifted, HDTs could be responsible for approximately 10 µ g m −3 of NO x in the urban area. The uncertainties of conventional top-down allocation methods, which were widely used to enhance the spatial resolution of vehicle emissions, are also discussed by comparison with the EMBEV-Link emission inventory.

On-road vehicle emissions are a major contributor to elevated air pollution levels in populous metropolitan areas. We developed a link-level emissions inventory of vehicular pollutants, called EMBEV-Link (Link-level Emission factor Model for the BEijing Vehicle fleet), based on multiple datasets extracted from the extensive road traffic monitoring network that covers the entire municipality of Beijing, China (16 400 km2). We employed the EMBEV-Link model under various traffic scenarios to capture the significant variability in vehicle emissions, temporally and spatially, due to the real-world traffic dynamics and the traffic restrictions implemented by the local government. The results revealed high carbon monoxide (CO) and total hydrocarbon (THC) emissions in the urban area (i.e., within the Fifth Ring Road) and during rush hours, both associated with the passenger vehicle traffic. By contrast, considerable fractions of nitrogen oxides (NOx), fine particulate matter (PM2.5) and black carbon (BC) emissions were present beyond the urban area, as heavy-duty trucks (HDTs) were not allowed to drive through the urban area during daytime. The EMBEV-Link model indicates that nonlocal HDTs could account for 29 % and 38 % of estimated total on-road emissions of NOx and PM2.5, which were ignored in previous conventional emission inventories. We further combined the EMBEV-Link emission inventory and a computationally efficient dispersion model, RapidAir®, to simulate vehicular NOx concentrations at fine resolutions (10 m × 10 m in the entire municipality and 1 m × 1 m in the hotspots). The simulated results indicated a close agreement with ground observations and captured sharp concentration gradients from line sources to ambient areas. During the nighttime when the HDT traffic restrictions are lifted, HDTs could be responsible for approximately 10 µg m−3 of NOx in the urban area. The uncertainties of conventional top-down allocation methods, which were widely used to enhance the spatial resolution of vehicle emissions, are also discussed by comparison with the EMBEV-Link emission inventory.