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Direct air capture (DAC) systems that capture carbon dioxide (CO2) directly from the atmosphere are garnering considerable attention for their potential role as negative emission technologies in achieving net-zero CO2 emission goals. Common DAC technologies are based either on liquid–solvent (L-DAC) or solid–sorbent (S-DAC) to capture CO2. A comprehensive multi-factor comparative economic analysis of the deployment of L-DAC and S-DAC facilities across various United States (U.S.) cities is presented in this paper. The analysis considers the influence of various factors on the favorability of DAC deployment, including local climatic conditions such as temperature, humidity, and CO2 concentrations; the availability of energy sources to power the DAC system; and costs for the transport and storage of the captured CO2 along with the consideration of the regional market and policy drivers. The deployment analysis in over 70 continental U.S. cities shows that L-DAC and S-DAC complement each other spatially, as their performance and operational costs vary in different climates. L-DAC is more suited to the hot, humid Southeast, while S-DAC is preferrable in the colder, drier Rocky Mountain region. Strategic deployment based on regional conditions and economics is essential for promoting the commercial adoptability of DAC, which is a critical technology to meet the CO2 reduction targets. [ABSTRACT FROM AUTHOR]

Difference in terms of cost-of-living between rural and urban areas is a frequent theoretical analysis in Regional Economics. Lack of routine measures in rural areas does not usually allow to observe changes in rural costs. We adapt the Big Mac index, typically used to measure purchasing power parity between countries, as a potential quick and inexpensive indicator of short-term local price variations. With a national random sample of McDonald's stores repeated in time, we find prices grew slightly faster in rural areas than in urban areas. Spatial transmission of prices seems to be limited to very localized effects, meaning that rural price increases are not due to urban spillover effects. [ABSTRACT FROM AUTHOR]

A metropolitan area comprises a collection of cities and counties bound by strong socioeconomic ties. Despite the pivotal role that metropolitan areas play in regional economics, their delineation remains a challenging task for researchers and urban planners. Current threshold-based delineation methods select counties based on their connection strength with prespecified core counties. Such an approach often neglects potential interactions among outlying counties and fails to identify polycentric urban structures. The delineation of a metropolitan area is fundamentally a spatial optimization problem, whose objective is to identify a set of counties with high interconnectivity while also meeting specific constraints, such as area, contiguity, and shape. In this study, we present a novel spatial optimization model designed for metropolitan area delineation. This model aims to maximize intercounty connection strength in terms of both industry and daily life. This approach ensures a more accurate representation of the multicore structure that is commonly seen in developed metropolitan areas. Additionally, our model avoids the possibility of holes in metropolitan area delineation, leading to more coherent and logical metropolitan boundaries. We provide a mixed-integer programming formulation for the proposed model. Its efficacy is demonstrated by delineating the boundaries of the Nanjing and Lhasa metropolitan areas. This study also delves into discussions and policy implications pertinent to both of these metropolitan areas. [ABSTRACT FROM AUTHOR]

Assessing the urban rooftop photovoltaic (PV) economics is important for scaling up rooftop PVs for rapid decarbonization. In this study, socioeconomic, technological, and policy factors were integrated into a rooftop PV economic assessment. This comprehensive method was applied to 21 cities in the Guangdong province of China, in combination with local real parameters. The results show that, with higher urbanization levels, electricity tariffs, and PV self-consumption rates, cities in the Pearl River Delta area generally had better economic performance in terms of both economic scale and profitability. They accounted for 75% of the total rooftop PV potential in Guangdong Province and had an internal rate of return (IRR) as high as 14.6–19.2% for Commercial and Industrial buildings (C&I), and 9.9–15.9% for residential buildings (R). Socioeconomic, technological, and policy factors jointly affect the economic performance and create a promising future for Guangdong rooftop PVs. It is projected that the IRR of current worst performing cities will grow by 4.9–5.8, and 4.4–5.9 percentage points, and the payback period will be shortened by 5.8–6.7 and 3.4–4.1 years by 2030 for R and C&I buildings, respectively. Among the three factors, technological advancement had the most significant long-term effect, followed by socioeconomic development. Policy factors play an important role in alleviating short-term cash flow pressure. Integrating the three factors in the assessment provides us with a more comprehensive picture of how urban rooftop PV economics will evolve and a better idea of how to prioritize rooftop PV development. Suggestions for prioritizing the deployment of rooftop PV systems in Guangdong by 2030 were provided. • Socioeconomic, technological, and policy factors were integrated into the urban rooftop PV economics assessment. • An orderly deployment plan for urban rooftop PVs in the Guangdong province of China is proposed. • The technology factor had the most significant effect on rooftop PV economic trends through capital cost reduction. • Socio-economic development contributes to higher electricity demand and revenue. • Policy factors play an important role in the short term in alleviating the cash flow pressure through preferential loan rate. [ABSTRACT FROM AUTHOR]