Oil and natural gas rents and CO2 emissions nexus in MENA: spatial analysis.

Background: Oil rents (OR) and natural gas rents (NGR) have significant contributions to the income of the Middle East and North Africa (MENA) economies and may increase emissions. Moreover, spatial autocorrelation is expected in carbon dioxide (CO2) emissions due to the geographically closed economies in the MENA region. Thus, we examine the impact of OR and NGR on CO2 emissions caring spatial dimensions and analyze the environmental Kuznets curve (EKC). Methods: We apply the spatial Durbin model technique on the effects of OR, NGR, and economic growth on CO2 emissions in 17 MENA nations from 2000-2019, i.e., Algeria, Bahrain, Egypt, Iran, Iraq, Israel, Jordan, Kuwait, Libya, Morocco, Oman, Qatar, Saudi Arabia, Syria, Tunisia, the United Arab Emirates (UAE), and Yemen. Moreover, diagnostic tests are applied to reach the most appropriate spatial specification and to have the most robust results. Results: The results disclose that CO2 emissions have spillovers and emissions of any country can damage the environment of neighboring countries. The EKC is corroborated with a turning point of 38,698 constant 2015 US dollars. Israel and Qatar are in 2nd phase of the EKC, and 15 MENA economies are in 1st stage. Thus, the economic expansion of most economies has ecological concerns. The effect of natural gas rents is found statistically insignificant. Oil rents have minute negative effects on emissions of local economies with an elasticity coefficient of -0.2117. Nevertheless, these have a positive indirect effect with an elasticity coefficient of 0.5328. Thus, the net effect of oil rents is positive. One percent increase in oil rents could accelerate 0.3211% of emissions. Thus, we suggest the MENA countries reduce reliance on oil rents in their income to avoid the negative environmental effects of the oil sector.

FDI, exports, imports, and consumption-based CO2 emissions in the MENA region: spatial analysis.

MENA region is full of natural resources and has a huge mineral sector in their economies. CO2 emissions are increasing global warming and foreign trade and investments can play their roles in determining CO2 emissions in the resource-rich MENA countries. Moreover, spatial linkages are expected in the emissions and trade relationship, which could catch less attention in the environmental literature of the MENA region. Thus, the present research is motivated to capture the contributions of exports, imports, and Foreign Direct Investments (FDI) in consumption-based CO2 (CBC) emissions in twelve MENA economies from 1995 to 2020 by applying Spatial Autoregressive (SAR) Model. Our results exhibit the existence of the Environmental Kuznets Curve (EKC). Moreover, the impact of exports is found negative in direct and total estimates. Thus, exports of the MENA region are reducing CBC emissions in the MENA region and transferring emissions to their importing partners. Moreover, the spillovers of exports are found positive and exports of one MENA country are also responsible for the transfer of CBC emissions to other MENA neighboring countries, which corroborates the trade linkages of the MENA region. Imports have a positive effect on CBC emissions in direct and total effects. This result confirms the fact of energy-intensive imports of the MENA region, which have environmental consequences in the domestic economies and the whole MENA region. FDI increases CBC emissions in direct and total estimates. This result substantiates the pollution Haven hypothesis in the MENA region and is in line with the fact that FDI is mostly coming in the mineral, construction, and chemical sectors. The study suggests that MENA countries should promote exports to reduce CBC emissions and to reduce energy-intensive imports in the region to save the environment from CBC emissions. Moreover, FDI should be attracted to the clean production process and environmental standards should be raised to avoid the environmental problems of FDI in the MENA region.

Analysis of Agriculture and Food Supply Chain through Blockchain and IoT with Light Weight Cluster Head.

By 2050, the world's population will have increased by 34%, to more than 9 billion people, needing a 70% increase in food production. Prepare more dishes with fewer ingredients. Therefore, the critical goal of manufacturers is to increase production while being ecologically benign. Supply chain systems that do not enable direct farmer-to-consumer connection and rising input costs influence data collection, security, and sharing. Constraints on data security, manipulation, and single-point failure are unfulfilled due to a lack of centralized IoT agricultural infrastructure. To address these issues, the article proposes a blockchain-based IoT model. This study also shows one-of-a-kind energy savings. The decentralization of data storage improves the supply chain's transparency and quality through blockchain technology, thus farmers can engage more efficiently. Blockchain technology improves supply chain traceability and security. This article provides a transparent, decentralized blockchain tracking solution and proposes an intelligent model protocol for several Internet of Things (IoT) devices that monitor crop development and the agricultural environment. A new approach has resolved the bulk of the supply chain difficulties. Smart contracts were utilized to organize all transactions in decentralized supply networks. The use of blockchain technology improves transaction quality, and customers may verify the legitimacy of an item's authenticity and legality by using the system. A total of 100 IoT nodes were distributed randomly to each 500 m2 cluster farm. The Internet of Things nodes were used to assess soil moisture, temperature, and crop disease. Network stability period and network life of the proposed method show 90.4% accuracy. The food supply chain will be more efficient and trustworthy with an intelligent model. The immutability of ledger technology and smart contract support further increases supply chain security, privacy, transparency, and trust among all stakeholders in the multi-party system. By 2050, the world's population will need a 70% increase in food production. The food supply chain will be more efficient and trustworthy with an intelligent model. This article provides a transparent, decentralized, and intelligent model protocol for several Internet of Things (IoT) devices.