Estimation of NO2 emission strengths over Riyadh and Madrid from space from a combination of wind-assigned anomalies and machine learning technique

Nitrogen dioxide (NO2) air pollution provides valuable information for quantifying NOx emissions and exposures. This study presents a comprehensive method to estimate average tropospheric NO2 emission strengths derived from three-year (April 2018 - March 2021) TROPOMI observations by combining a wind-assigned anomaly approach and a Machine Learning (ML) method, the so-called Gradient Descent. This combined approach is firstly applied to the Saudi Arabian capital city Riyadh, as a test site, and yields a total emission rate of 1.04×1026 molec./s. The ML-trained anomalies fit very well with the wind-assigned anomalies with an R2 value of 1.0 and a slope of 0.99. Hotspots of NO2 emissions are apparent at several sites where the cement plant and power plants are located and over areas along the highways. Using the same approach, an emission rate of 1.80×1025 molec./s is estimated in the Madrid metropolitan area, Spain. Both the estimate and spatial pattern are comparable to the CAMS inventory. Weekly variations of NO2 emission are highly related to anthropogenic activities, such as the transport sector. The NO2 emissions were reduced by 24% at weekends in Riyadh, and high reductions are found near the city center and the areas along the highway. An average weekend reduction estimate of 30% in Madrid is found. The regions with dominant sources are located in the east of Madrid, where the residential areas and the Madrid-Barajas airport are located. Additionally, the NO2 emissions decreased by 21% in March-June 2020 compared to the same period in 2019 induced by the COVID-19 lockdowns in Riyadh. A much higher reduction (60%) is estimated for Madrid where a very strict lockdown policy was implemented. The high emission strengths during lockdown only persist in the residential areas and cover smaller areas during weekdays than at weekends. The spatial patterns of NO2 emission strengths during lockdown are similar to those observed at weekends in both cities. Though our analysis is limited to two cities as testing examples, the method has proved to provide reliable and consistent results. Therefore, it is expected to be suitable for other trace gases and other target regions. [ FROM AUTHOR] Copyright of Atmospheric Measurement Techniques Discussions is the property of Copernicus Gesellschaft mbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

To Adopt CCU Technology or Not? An Evolutionary Game between Local Governments and Coal-Fired Power Plants

Carbon dioxide capture and utilization (CCU) technology is a significant means by which China can achieve its ambitious carbon neutrality goal. It is necessary to explore the behavioral strategies of relevant companies in adopting CCU technology. In this paper, an evolutionary game model is established in order to analyze the interaction process and evolution direction of local governments and coal-fired power plants. We develop a replicator dynamic system and analyze the stability of the system under different conditions. Based on numerical simulation, we analyze the impact of key parameters on the strategies of stakeholders. The simulation results show that the unit prices of hydrogen and carbon dioxide derivatives have the most significant impact: when the unit price of hydrogen decreases to 15.9 RMB/kg or the unit price of carbon dioxide derivatives increases to 3.4 RMB/kg, the evolutionary stabilization strategy of the system changes and power plants shift to adopt CCU technology. The results of this paper suggest that local governments should provide relevant support policies and incentives for CCU technology deployment, as well as focusing on the synergistic development of CCU technology and renewable energy hydrogen production technology.

A SYSTEMS THINKING CONCEPTUAL MODEL FOR VALUE CREATION IN THE AFRICAN CEMENT MARKET

Sement is die wereld se belangrikste boumateriaal, en dit het Afrika, as 'n opkomende mark, afhanklik gemaak van die sementbedryf as 'n kritieke instrument om ekonomiese infrastruktuurgroei te bevorder. Vandag se uitdagende ekonomiese klimaat het sementprodusente ook toenemend afhanklik gemaak van spesialiste om hul bedrywighede op te gradeer, te moderniseer en in stand te hou. Die doel van hierdie navorsing is om te evalueer hoe ingenieursdiensorganisasies wat in Afrika werksaam is tans hul sake met hierdie sementprodusente bedryf. Die navorsing toon dat die literatuur oor stelselingenieurswese nie ten volle gebruik maak van waarde-ingenieurskonsepte nie. Die studie het hierdie gebrek aan samewerking identifiseer en 'n nuwe waarde-ingenieursisteemmodel voorgestel wat gebruik kan word om die gebruik van ingenieursdienste en -produkte in die Afrika-sementbedryf te bevorder en te versterk.Alternate :Cement is the worlds most important building material, and it has made Africa, as an emerging market, dependent on the cement industry as a critical tool to promote economic infrastructure growth. Todays challenging economic climate has also made cement producers increasingly dependent on specialists to upgrade, modernise, and maintain their operations. The objective of this research was to evaluate how engineering service organisations operating in Africa currently conduct their business with these cement producers. The research also showed that the literature on systems engineering does not make full use of value engineering concepts. The study identified this lack of collaboration, and proposed a new value engineering systems model that can be used to promote and strengthen the use of engineering services and products in the African cement industry.