Industrial Output Research Articles

A five-year Study Using Sentinel-5P Data Observing Seasonal Dynamics and Long-term Trends of Atmospheric Pollutants

Air pollution is an escalating concern for both environmental sustainability and public health, exacerbated by urbanization and industrial growth. In Saudi Arabia, pollutants primarily from industrial activities and vehicle emissions present significant health hazards. This study utilizes data from the Sentinel-5P satellite to analyze the variations in Carbon Monoxide (CO), Nitrogen Dioxide (NO₂), Sulfur Dioxide (SO₂), and Particulate Matter (PM2.5) over a five-year period, from January 2019 to December 2023. The data was processed using Google Earth Engine (GEE) to produce monthly and seasonal averages, while ArcGIS Pro was used to map trends and spatial distribution. The results reveal distinct seasonal fluctuations in pollution levels, with CO peaking between March-May and July-September but showing an overall decline. NO₂ and SO₂ exhibit seasonal highs with slight upward trends, likely linked to industrial output and traffic emissions. PM2.5, the most harmful pollutant to human health, consistently surpasses World Health Organization (WHO) limits, especially during high-emission periods. These findings underscore the urgency of adopting targeted measures to mitigate pollution during critical times and safeguard public health. The seasonal spikes, particularly in industrial and densely populated regions, highlight the need for improved policies and technologies to effectively monitor and manage air quality

Analysis of the spatiotemporal evolution of birth rates and influencing factors in the Yangtze River Basin.

The declining birth rate is one of the world's major challenges. There is much literature on birth rate research in China. However, there are few studies on spatial distribution and influencing factors of birth rate in the Yangtze River Basin. In this study, data from 11 regions of the Yangtze River Basin from 2006 to 2023 were used to analyze the spatial and temporal distribution characteristics of birth rates using GIS spatial visualization and four-quadrant diagram. At the same time, 13 factors affecting birth rates were combined to carry out research. The results show that: (1) In 2023, five regions reported birth rates above 7‰, with Tibet faring the best, while six regions had rates below 7‰, with Hunan being the least favorable. (2) The first type of birth rate area shows a process of slow increase-slight decrease-accelerated growth-rapid decrease; the second type of birth rate area shows a process of gradual decrease-moderate increase-rapid decrease-rapid increase-rapid decrease; the third type of birth rate area has increased rapidly since 2021. The three types of birth rate areas show the characteristics of the spatiotemporal pattern of continuous spread and development. (3) The aging rate, per capita GDP, proportion of primary industry output value, proportion of tertiary industry output value, female illiteracy rate, per capita disposable income, per capita consumption expenditure, urbanization rate, proportion of higher education, juvenile dependency ratio, and elderly dependency ratio have different degrees of influence on the birth rate.

Exploring the Relationship between CO2 Emission, Economic Growth, and Energy Consumption at Aggregate Level: A Panel Data Analysis

This article explores the relationship between CO2 emissions, economic growth, energy consumption, and, other control factors for the eight highest CO2-emitting countries (USA, Russia, Iran, China, Germany, India, Japan, and Canada) in 1995-2023. The m objective of the study is to determine how economic growth (GDP), energy consumption (EC), industrial production (IP), and other macroeconomic factors influence CO2 emissions. Using panel data analysis, this study applies various econometric techniques, including fixed and random effects models, Multicollinearity tests, heteroscedasticity tests, and cross-sectional dependence tests. Independent variables include GDP, Total energy use, Industrial output, Density of the population, and Trade while the dependent variable is CO2 emission. The results suggest that energy consumption positively correlates with CO2 emission, where, for each unit of energy consumption, CO2 emission increases by 0.0024 units. The outcomes also reveal a negative correlation of international trade with CO2 emissions implying that trade inhibits emissions. However, the relationship between GDP and, carbon emissions was formed to be statistically insignificant. Population density and industrial production have mixed effects on emissions, with industrial production showing a positive impact. The study emphasizes the importance of adopting cleaner energy sources, enhancing energy efficiency, and considering trade policies that might reduce emissions. The findings suggest that transitioning from coal and oil to cleaner energy sources, such as natural gas, could be an effective strategy for reducing carbon emissions without significantly hindering economic growth. The study provides valuable insights for policymakers in high-emission countries aiming to balance economic development with environmental sustainability.

Research on Industrial CO2 Emission Intensity and Its Driving Mechanism Under China’s Dual Carbon Target

As global climate change becomes increasingly severe, industrial CO2 emissions have received increasing attention, but the impact factors and driving mechanisms of industrial CO2 emission intensity remain unclear. Based on panel data from 2010 to 2021 in Shandong Province, a key economic region in eastern China, the industrial CO2 emission intensity under China’s dual carbon target was analyzed using multivariate ordination methods. The results showed that (1) total CO2 emissions from industry are increasing annually, with an average growth rate of 3.74%, and electricity, coal, and coke are the primary sources of CO2 emissions. (2) Total CO2 emissions originated primarily from the heavy manufacturing, energy production, and high energy intensity industry categories, and the CO2 emission intensity of different types of energy increased by 21.24% from 2010 to 2021. (3) CO2 emission intensity is significantly positively correlated with the proportion of high energy intensive industry, energy consumption intensity, and investment intensity and significantly negatively correlated with gross industrial output. In addition, the effects of different types of energy on industrial CO2 emission intensity varied, and coal, coke, electricity, and diesel oil were significantly positively correlated with CO2 emission intensity. Therefore, to reduce the CO2 emission intensity of the industrial sector in the future and to achieve China’s dual carbon target, it is necessary to adjust and optimize the industrial and energy structure, strengthen technological progress and innovation, improve energy utilization efficiency, improve and implement relevant policies for industrial carbon reduction, and then ensure the sustainable development of the economy, society, and environment.

Analyzing industrial policy portfolios

AbstractIndustrial policy has regained political attention due to the challenges associated with global market integration, technological changes, and the need for sustainable transformation. However, the lack of a consistent understanding of industrial policy hampers systematic comparisons. This paper develops a novel concept of industrial policy portfolios that captures different dimensions of industrial policy outputs across countries and over time. We illustrate this approach by comparing the policy dynamics in the United States and Germany over the last four decades and show that despite similar dynamics of policy growth, the countries display pronounced variation in the areas and instruments they prioritized.

Can Service be a Catalyst for Industrial Output? Insights from Indian Manufacturing Industries

Can Service be a Catalyst for Industrial Output? Insights from Indian Manufacturing Industries

Development of an input-output CGE model for collaborative management of water pollution reduction and carbon mitigation

Achieving the dual goals of improving water quality and reducing carbon emissions requires a systematic study of the combined effects of economic and environmental policies on industrial systems. A CGE-IWCR model is developed to examine the long-term evolution of industrial economic and environmental responses in the Yangtze River Economic Belt (YREB) under varying levels of carbon and water pollution taxes. The CGE-IWCE model offers several advantages: i) under the dual tax (carbon and water pollution tax) interventions, it can effectively forecast industrial CO2 and water pollution emissions driven by both macro and local factors from 2025 to 2060; ii) it quantitatively captures the interactions between various policy interventions, thereby providing guidance for comprehensive regional policy formulation. It is discovered that in the double-tax scenario, various combinations of carbon and water pollution taxes significantly impact direct carbon emissions and direct water pollution emissions, and from local consumption, imports, and exports in industrial sectors. Among them, the dual pressure of high carbon and water pollution taxes, which significantly raise production costs. In addition, increasing the carbon tax from 10 ¥/tonne to 50 ¥/tonne, the water pollution equivalent (WPE) reduction rate rises from 20.79% to 52.67% with the increase in the carbon tax from 2050 to 2060, when the water pollution tax is low. Between 2025 and 2060, the carbon tax plays a significant role in influencing the total industrial output change rate in YREB. from 2025 to 2060, the water pollution tax will play a more significant role in CO2 reduction in YREB’s industrial sector. The results will offer decision-making support for water pollution reduction and carbon mitigation in the YREB’s industrial sector, quantitatively identify the interactions between the dual taxes, and provide new insights for analyzing the impacts of pollution reduction and carbon mitigation policies.

External Sector Variables, Exchange Rate and Industrial Sector Output Performance in Nigeria

This study examines the relationship between external sector variables, exchange rate and industrial sector output performance in Nigeria from 1980-2023 using the Ordinary Least Square analysis, the co-integration test and error correction mechanism. The study revealed the existence of a positive relationship between foreign direct investment and foreign port investment while a negative links exists between exchange rate and industrial capacity utilization on the industrial sector output performance in Nigeria within the period under consideration, 1980-2023. The error correction coefficient ECM (-1) value is -0.804506 or 80 per cent and correctly signed (negative sign) and significant. This implies that external sector variables, exchange rate and industrial sector output performance in Nigeria adjust speedily to the changes in the explanatory variables. Therefore, the ECM is able to correct and tie any deviations from the long –run relationship between industrial sector output performance and the explanatory variables to its short-run period.

Economic and environmental implications of India's industry transition to net zero

In line with global mitigation ambition and the domestic target of achieving net zero emissions by 2070, India's industrial sector is expected to undergo a major transition. This transition is not trivial given the rapid growth of industrial output, dependence on fossil fuels, high emission intensity, and complicated emission abatement processes. In this paper, we provide a whole systems analysis of the manufacturing industries- iron & steel, aluminium, cement, chemical and petrochemical, textile, residual- for achieving net zero by 2070. The methodology combines the qualitative inputs from stakeholders with the energy-economy modelling using IMACLIM-IND and AIM/Enduse models. We develop four scenarios: Business-As-Usual (BAU), Development First (DFS), Carbon Neutral (CNT) and Synchronous (SYNCH). For each of these scenarios, we assess impacts of the structural transformation on sustainable development mainly through impacts on economy (gross value added and material imports), environment (material resource savings), and investment needs. The SYNCH scenario achieves 63 % emission reduction and requires an investment of 1.7 trillion USD by 2050 compared to BAU. The key policy insight is that new investments should go towards decarbonizing electricity, recycling infrastructure, and Carbon Capture and Storage. Clear standards and regulations for emission reporting by the production firms should be stipulated by the government.

Industrialization meets sustainability: Analysing the role of technological innovations, energy efficiency and urbanisation for major industrialized economies

Considering how crucial environmental quality is to development, production often takes precedence over the development process when certain macroeconomic policies are being implemented. This phenomenon has been the subject of several studies conducted in various regions and nations. In this context, the recent article explores the nonlinear effects of industrial output, renewable energy, technological innovations, energy efficiency, and urbanization on CO2 emissions in the top ten industrialized countries. It recommends contradictory policy approaches due to its reported conflicting outcomes, opening up new research directions. To this end, the study relies on advanced econometric tools such as panel QARDL (Quantile Autoregressive Distributed Lag) and the nonparametric quantile Granger causality (NPQGC) test to attain robust results. The findings suggest that industrial output and urbanization significantly deteriorate environmental quality by increasing CO2 emissions across various time horizons. However, renewable energy, technological innovations, and energy efficiency have a significant influence towards enhancing environmental quality. Notably, industrialization and urbanization become environmentally friendly when energy efficiency is integrated with these variables. Additionally, the NPQGC test supports the main results by confirming the Granger causality between the modelled series. Based on the outcomes, the study suggests that the integration of energy efficiency with industrialization and urbanization can significantly contribute to achieving a sustainable environment.

Analisis Pendapatan dan Kelayakan Usaha Salad Buah pada Mf Dessert

Income is all income received from other parties in the form of money or goods, as well as industrial output, which is valued based on the current amount of money from these assets. Turnover is one of the company's components and the main objective in preparing the income statement. This research aims to conduct an analysis of fruit salad income at Mf Dessert. Through this careful research and comprehensive literature review, it is hoped that we can provide deeper insight into the income that contributes to Fruit Salad at Mf Dessert and provide recommendations that can help Mf Dessert businesses optimize their business potential. The method used is descriptive qualitative. The results of this research show that the average revenue from Mf Dessert is IDR 3,900,000,- per 5 months with production costs incurred of IDR 3,484,873,- per 5 months. The production costs consist of fixed costs of IDR 4,000 per 5 months and variable costs of IDR 3,435,000 per 5 months. From the results of data analysis, it was found that the income earned by fruit salad at Mf Dessert was IDR 415,127 per 5 months. Based on feasibility research on Mf Dessert (R/C Ratio), a value (R/C Ratio) of 1.22 or 1.22 > 1 was obtained, meaning that for every cost incurred Rp. 1, it produces income of Rp. 1.22 so that the revenue is greater than the capital spent. So it can be concluded that the fruit salad at Mf Dessert can be said to be profitable and worth running.

Alexander Hamilton’s Report on Manufactures and Industrial Policy

Hamilton’s 1791 state paper on manufactures is a forward-looking argument for US industrialization supported by public policies designed to encourage it. Conventional wisdom circa 1790, along with static considerations of comparative advantage indicated that the United States should stick to farming, export its agricultural surpluses, and import European manufactures. Mercantilist trade policies of the major European empires, however, were barriers to US exports. Hamilton therefore contended that US manufacturing using the latest machine technologies would alleviate the effects of European trade restrictions by creating domestic demand for agricultural surpluses. His report specifies industries worthy of support, and policy measures to encourage their development. During the century that followed, US governments adopted nearly all of Hamilton’s recommendations. These measures contributed to an average annual rate of growth of industrial output of 5 percent during that century, helping the United States to become the world’s leading manufacturing nation.

ASSESSING THE IMPACT OF MACROECONOMIC VARIABLES ON MANUFACTURING SECTOR IN WEST AFRICA REGION

The West African manufacturing grew immediately after post-independence period, which was largely shaped by state-led and protectionist policies. The structural adjustment reforms of the state-owned enterprises and trade liberalization, along with foreign aid, restarted West African manufacturing in the 1990s. However, the increased competition from foreign products and pressures on its currencies, such as devaluations, made these gains to be short-lived. The study examined the macroeconomic variables and industrial output in West African region using cross session approach between 2008 and 2020. Contribution of industrial output to Gross Domestic Product (GDP), External Debt, Lending Rate and Inflationary Rate were used as variables. It was found that industrial output contribution to GDP estimate shows that there exist an inverse relationship between Industrial output and Lending Rate, Inflationary rate, while Industrial output and External Debt are positively related. It is recommended that a conducive macroeconomic policy should be operated to curb inflationary rate within the country so that raw materials for production would be cheap which will result to a continuous generation of output.

Electrification pathways for light-duty logistics vehicles based on perceived cost of ownership in Northern China

Urban decarbonization and environmental mitigation necessitate the electrification of light-duty logistics vehicles (LDLVs), including battery electric, plug-in hybrid, and hydrogen fuel cell variants. Although the market uptake of electric LDLVs is ecologically imperative, it is impeded by range anxiety and charging infrastructure limitations, particularly pronounced in Northern China’s cold climates. This paper employs a system dynamics model to assess the Perceived Cost of Ownership of electric LDLVs, integrating both direct expenses - initial investment and energy costs - and indirect factors like energy replenishment, vehicle substitution, and lifecycle carbon emissions. This analysis reveals that, notwithstanding higher upfront costs, electric LDLVs offer substantial economic and environmental advantages, with significant energy and maintenance savings projected by 2030 under various electrification scenarios. This paper predicts that policy incentives, electricity pricing, and technological progress will significantly influence the market dynamics and industry output of new energy vehicles in Northern China. Notably, the findings indicate that by 2030, electric LDLVs could achieve substantial cost savings and environmental benefits, with market penetration and industry output contingent on the interplay of policy support and technological advancements. The baseline scenario forecasts a 48.17% market share and CNY 60.015 billion in industry output, whereas the high-speed electrification scenario projects the most optimistic outcomes, with a 75.29% market share and CNY 306.087 billion in output.

Measuring Rurality and Analyzing the Drivers of Rurality in Megacities—A Case Study of Shanghai, China

The Rurality Index is an important reference for the formulation of rural development strategies and policies, but the evaluation of the rurality of megacities based on the township scale is relatively limited. Based on the perspective of spatial governance, this study constructed the evaluation index system of Shanghai’s rurality and carried out the evaluation of Shanghai’s rurality at the township scale from 2005 to 2020. The article adopts the MGWR model to analyze the driving effects of five key driving factors (the proportion of foreign population, per capita industrial output value, public finance revenue, social fixed asset investment, and rail transit coverage), and adopts the Geo-Detector model to analyze the interactive driving effects of two factors. The results indicate that the rurality index of megacities and townships as a whole shows a weakening trend, and the above factors have a predominantly negative impact on rurality, with differences in the intensity of the impact in different periods. There is an obvious interactive additive effect between the factors. When formulating policies for township development, government departments need to take into account the functional positioning of the region and comprehensively adopt targeted policies on population, industry, transportation, finance and investment to regulate and guide the transformation or sustainable development of the countryside.

Agricultural carbon emissions in China: measurement, spatiotemporal evolution, and influencing factors analysis

IntroductionThe agricultural sector is the second largest emitter of greenhouse gases, accounting for 23% of global anthropogenic carbon emissions. Analysis of the basic state of carbon emissions from China's agriculture is helpful to achieve carbon reduction targets.MethodsAgricultural carbon emissions were calculated using the emission factor method, based on data from the China Rural Statistical Yearbook and various provincial statistical yearbooks. To analyze spatial patterns, the standard deviation ellipse method and the center of gravity migration model were employed, uncovering the migration path of agricultural carbon emissions. Regional disparities and the driving factors of agricultural carbon emissions were further examined using the Theil index and the Logarithmic Mean Divisia Index (LMDI) model.ResultsThe analysis indicated that the emissions center has gradually shifted towards the central and western regions, reflecting changes in agricultural production activity areas. Intraregional differences are the primary contributors to the imbalance in agricultural carbon emissions, with pronounced disparities in grain production and consumption balance regions. Key influencing factors include agricultural production efficiency, adjustments in agricultural industrial structure, economic structure and output, and urbanization levels. The economic output effect and urbanization effect are identified as the main drivers of increased carbon emissions, while declining production efficiency has hindered emission reduction efforts.ConclusionThe findings provide valuable insights for regional management and policymaking in China's agricultural sector, highlighting the need to enhance production efficiency and optimize agricultural structure to reduce emissions.

Transforming Learning Orientations Through STEM Interdisciplinary Project-Based Learning

Science, technology, engineering, and math (STEM) education is challenged by industries to incorporate business, engineering, and communication experiences to prepare students for workplace success. In this study, we outline an approach—the STEM Oriented Alliance for Research (SOAR)—to enhance student experience by offering interdisciplinary project-based learning (IPBL) for undergraduate students majoring in electrical engineering, communications, and marketing. We examined how students’ disciplinary and cooperative orientations toward learning shifted in response to their experiences in a semester-long interdisciplinary project-based learning experience with authentic industry outputs. Using a multi-method approach, we explored how interdisciplinary projects influenced student experiences in terms of five collaboration abilities: positive interdependence, accountability, promotive interaction, group processing, and social skills. Further, we observed a shift from fixed- to more growth-oriented mindsets, and from a primarily disciplinary to interdisciplinary focus for their future professional work. The outcomes of the SOAR project make clear that providing structure for professional cooperation on interdisciplinary projects can have profound effects on how students learn to cooperate and position themselves as learners. For most SOAR participants, the experience was deeply formative and contributed to their readiness to cooperate and learn within the interdisciplinary and STEM-oriented workforce.

Influencing factors and predictions of carbon emissions for the chemical industry in China

As global warming increases the frequent occurrences of natural disasters, the reduction of carbon emissions has become an important issue around the world. The chemical industry is an important source of carbon emissions in China. The carbon emissions of the chemical industry are calculated from 2000 to 2019 by using the emission factor method. The logarithmic mean divisia index (LMDI) method is exploited to analyze the factors that influence carbon emissions, and the emissions variations are attributed to the contributions of carbon intensity, energy structure, energy intensity, industrial value-added rate, per capita industrial output value, and industrial scale. The results of decomposition show that per capita industrial output value is the main driving factor, and energy intensity is the main inhibiting factor of the chemical industry’s carbon emissions. In order to quantify the variation of carbon emissions, the extended stochastic impacts by regression on population, affluence, and technology (STIRPAT) model is constructed and examined. Using the STIRPAT model, the basic scenario and energy intensity control scenario are set, and the carbon emissions are predicted, which shows that under a strict energy intensity control scenario, carbon emissions may reach a peak around 2031. The factors influencing the decomposition and prediction of carbon emissions should be helpful in reducing the carbon emissions of the chemical industry in China.

Ecological Consequences of Changes in the Territorial and Branch Structure of Moscow Manufacturing Industry in 1990–2023

The peculiarities of the dynamics of the volume and structure of emissions from manufacturing enterprises in Moscow in 1990–2023 have been revealed. It is noted that the economic process of deindustrialization in the 1990s–2000s has been replaced in recent years by a small reverse process of reindustrialization, with an increase in the diversity of sectoral structure, and a change in the role and internal structure of machine building and chemical industry. The decrease of manufacturing industry output was noticed, while pollution from large enterprises producing products necessary for the city was preserved; at the same time, the rates of decrease in specific pollution for these enterprises have slowed down in recent years. It is concluded that during periods of crisis and recession there is a faster change in industrial structure compared to the change in pollution structure, and that during the recovery phase the pollution structure changes faster, largely due to the fact that industries are expanded initially without adequate expansion of treatment systems.

Do consumers gain or lose when managers become socially concerned?

The Friedman Doctrine states, “an entity's greatest responsibility lies in the satisfaction of the shareholders.” This leads us to consider managerial firms’ corporate social responsibility (CSR) activities delegated by profit-maximizing owners. Our research follows the Ferstman-Judd-Skilvas framework to examine if profit-maximizing owners could ask managers to be socially rather than privately concerned and its impacts on social welfare, contributing to the literature of CSR by presenting the following results. First, CSR delegation is a dominant strategy. Second, CSR delegation reduces the industry output level. We further show that consumers’ surplus and social welfare decrease in the number of managerial firms adopting CSR delegation. The above results imply that socially concerned managers with profit-maximizing owners are socially undesirable in a market with output delegation.