Environmental Effects Research Articles

Job destruction or job creation?: Evidence from carbon emission trading policies

Based on the panel data of 285 cities in China from 2007 to 2019, this paper constructs a theoretical framework to analyze the employment effect of carbon emission trading policy, and quantitatively evaluates the effectiveness, decomposition effect and influence mechanism of carbon emission trading policy on employment based on PSM-DID method. The study shows that the carbon emissions trading policy has a positive impact on the level of urban employment while producing significant environmental governance effects, and that its positive impact on employment in the pilot cities stems from the negative effect of reducing employment destruction rather than from the positive effect of increasing the job-creating effect. Carbon emissions trading policy promotes employment in the pilot cities through structural transformation effects, specifically through the three paths of green technology innovation, energy structure optimization and industrial structure upgrading. At the same time, the impact of the policy on employment varies significantly across cities of different locations, sizes and resource endowments. The study proposes that the construction of the national carbon market should be accelerated, a market-oriented green technology innovation system should be constructed, the optimization of the energy structure and the upgrading of the industrial structure should be promoted, and training in employment skills should be strengthened. The theoretical analysis of this study provides a theoretical basis for the micro-mechanism of carbon emissions trading policy, and the empirical results provide practical reference for the change of employment structure and the high-quality development of employment.

Research on the restorative effects and perception of privacy driven activities in Chinese classical gardens-Case studies of three Suzhou gardens.

The need for privacy, recognized as a fundamental psychological requirement, has garnered increasing attention as researchers explore the restorative effects of privacy driven activities (PDA). This study employs quantitative experiments and analyses to assess the restorative benefits of PDA within three classical Chinese gardens, demonstrating their superiority over conventional leisure activities in promoting emotional recovery, reducing stress, and restoring attention. The experiment quantifies the restorative effects of PDA versus standard leisure activities using a classic restorative scale and physiological indicators reflecting emotional relief. Regression analyses then identify five key factors influencing the occurrence of PDA, derived from preferred locations and behavioral tendencies observed in the three gardens. Further analyses reveal significant differences in the impacts of these five environmental feature dimensions on the evaluation indicators of "preference for privacy-oriented activities" and "restorative effects". Among these dimensions, "spatial scale and accessibility" has the greatest impact on the "preference for privacy-oriented environments", while "spatial atmosphere" and "activity facilities" have the most significant impact on "restorative effects". The findings suggest that behavioral activities mediate the relationship between environmental factors and restorative effects, highlighting the potential of PDA as a mediating variable for a comprehensive investigation into the pathways and mechanisms influencing restorative environments in research and design.

Promoting Cultural Industry Management in the Context of a Green Ecological Environment

The green cultural industry is a key driving force for economic transformation and the upgrading of industrial structures. However, to achieve its development while protecting the environment, its influencing factors and the interactive relationship between the economy and the environment must be considered. This paper examines the environmental promotion effect of the green cultural industry by analyzing the interaction mechanism among these three elements, using the entropy method and coupling coordination model. The results show that the green cultural industry can develop cultural resources in line with national cultural characteristics, foster cultural innovation, promote economic growth, and reduce ecological resource consumption. At the same time, economic improvement enhances infrastructure, provides services to support the cultural industry, strengthens environmental protection, and improves ecological carrying capacity, offering greater resource support for cultural industry development.

Profitability and Cost Estimates for Producing Tropical Hibiscus in South Florida

Tropical hibiscus (Hibiscus rosa-sinensis) is a bushy evergreen shrub or small tree native to the temperate regions of Asia and an economically significant crop in Florida. According to the 2017 Census of Agriculture, the market value of the ornamental industry in Miami-Dade County was $697 million, and approximately 25% of the production was in hibiscus. Demand for the cultivation of plants with minimal pesticides is rising due to concerns about potential adverse environmental and health effects. Integrated pest management, or IPM, is an alternative to conventional pesticide application. A broad-based approach, it integrates both chemical and non-chemical practices for sustainable control of pests. To help growers and other stakeholders determine the best approach to changing demands for pesticide management, this publication estimates the costs and returns of producing tropical hibiscus on an established nursery in south Florida using both traditional and IPM methods.

A negative-carbon planning method for agricultural rural industrial park integrated energy system considering biomass energy and modern agricultural facilities

Biomass energy, recognized as a “zero-carbon” energy, has gradually become a crucial approach to promoting the low-carbon transformation of agricultural rural industrial parks (ARIP). Meanwhile, modern agricultural facilities (MAF) can play a significant role in adjusting agricultural load. Therefore, this paper proposes a negative-carbon planning method for the ARIP integrated energy system (IES). Firstly, carbon activities occurring during the operation of ARIP are sorted out and modeled based on the life cycle assessment (LCA) method, especially modeling the “zero-carbon” and “negative-carbon” benefits of biomass energy. At the same time, the models of both agricultural irrigation systems and straw bundling direct combustion heating are constructed in the ARIP planning. Then, a negative-carbon planning model for ARIP IES is established with the goal of minimizing the annualized total cost, where carbon emission reduction is integrated into the optimization objectives through carbon trading. On this basis, a two-stage distributionally robust optimization (DRO) planning model is constructed, where a box-like set and comprehensive norm constraints are used to model the seasonal differences of agricultural industry loads and the uncertainty of probability distribution in photovoltaic (PV) scenarios. Especially, a box set with adjustable uncertainty coefficients is introduced to simulate fluctuations of output in PV scenario. Finally, the CPLEX solver is used to solve the planning model. verify the effectiveness of the proposed planning method in enhancing the economic and environmental effects of ARIP. Results indicate that the proposed planning model can reduce the total cost by 49.584 × 104 $. Besides, the annual carbon emissions can be reduced from 37533.98 t CO2-eq to −15834.5 t CO2-eq. Especially, the carbon sequestration effect of biochar is the key link in achieving “negative carbon” in ARIP.

Expanding the Capability of a Legacy Combustion Flame Tube to Test High-Temperature Engine Materials in Relevant Environments

Abstract New materials and component designs are needed to advance gas turbine engine technology and provide the performance and efficiency needs for future applications. In order to advance these materials, testing in combustion environments is a critical step prior to engine testing. In this work, we detail the design and the fabrication of a materials test sector in a flame tube combustor facility. The facility simulates a combustion environment similar to that experienced by components in gas turbine engines. The flow regime is characterized by a combination of high-temperature, high-heat flux, and high-velocity that components experience in gas turbine engines. Exposure of components in this facility allows for the study of combined environmental effects and the impact on both coating and substrate durability. The test facility may operate across a wide range of pressures from 275 to 400 psig (1896–2758 kPa) and an air flowrate of 5 lb/s (2.27 kg/s). While combustion gas temperature is expected in excess of 3000 °F (1649 °C), 900 °F (482 °C) cooling air may be supplied to the backside of components or test articles. The flame tube combustor was previously used to evaluate fuel injectors and combustion products, and the new test configuration will also allow for materials exposure to complex, engine-like conditions. The interior of the test section was additively manufactured from GRCop-84 and cryogenically fit and brazed to a stainless-steel 304 housing. The use of a copper liner minimizes welds and, with active cooling, is expected to provide better durability over traditional hardware using stainless-steel or Inconel with a ceramic liner. The test section has two opposing 9.5 in × 3.125 in (241 mm × 80 mm) removable windows that can accommodate articles up to 3.5 in (89 mm) tall. This modular design allows for custom platforms to hold coupons, panels, or airfoil shapes to be tested with minimal re-engineering or fabrication. The bolted joint and sealing remains consistent, so any new testing only needs to work within the existing design footprint. This paper will provide an overview of the facility capabilities, design considerations, as well as thermal and structural analysis of the hardware. Future testing of ceramic matrix composite (CMC) airfoils and advanced environmental barrier coatings (EBCs) will also be discussed.

Environmental Effects of Natural Processes and Human Activities on the Water Environment in Watershed

The Special Issue focused on the water environment changes within watersheds due to its critical role in sustaining ecosystems, supporting biodiversity, and providing essential resources for human life [...]

Estimating best nanomaterial for energy harvesting through reinforcement learning DQN coupled with fuzzy PROMETHEE under road-based conditions

Energy harvesters based on nanomaterials are getting more and more popular, but on their way to commercial availability, some crucial issues still need to be solved. The objective of the study is to select an appropriate nanomaterial. Using features of the Reinforcement Deep Q-Network (DQN) in conjunction with Fuzzy PROMETHEE, the proposed model, we present in this work a hybrid fuzzy approach to selecting appropriate materials for a vehicle-environmental-hazardous substance (EHS) combination that operates in roadways and under traffic conditions. The DQN is able to accumulate useful experience of operating in a dynamic traffic environment, accordingly selecting materials that deliver the highest energy output but at the same time bring consideration to factors such as durability, cost, and environmental impact. Fuzzy PROMETHEE allows the participation of human experts during the decision-making process, going beyond the quantitative data typically learned by DQN through the inclusion of qualitative preferences. Instead, this hybrid method unites the strength of individual approaches, as a result providing highly resistant and adjustable material selection to real EHS. The result of the study pointed out materials that can give high energy efficiency with reference to years of service, price, and environmental effects. The proposed model provides 95% accuracy with a computational efficiency of 300 s, and the application of hypothesis and practical testing on the chosen materials showed the high efficiency of the selected materials to harvest energy under fluctuating traffic conditions and proved the concept of a hybrid approach in True Vehicle Environmental High-risk Substance scenarios.

Is Public Participation Weak Environmental Regulation? Experience from China’s Environmental Public Interest Litigation Pilots

Previous studies have generally concluded that public participation lacks substantive constraints and has weak environmental regulation effects. Using China’s environmental public interest litigation (EPIL), implemented in 2015, as a quasi-natural experiment to verify the environmental effects of public participation under judicial norms, the difference-in-differences (DID) estimates in this paper show that industrial wastewater and industrial sulfur dioxide (SO2) emissions in the treated cities declined by an average of 2.76 million tons and 2.51 kilotons per year, respectively, which ultimately improved the city’s environmental quality. The results of the mechanism also show that the EPIL was able to mobilize all three parties: the public, government and enterprises. In the context of the environment as an externality product, where the interests of all the parties are difficult to coordinate, the EPIL has the advantage of overcoming conflicts of interest. Our study provides a quantitative justification for the environmental impact assessment of public litigation and contributes empirical references to overcome the weak binding defect of public participatory environmental regulation.

The Influence of Work Motivation and Work Environment on the Performance of Employees of the UKM Cooperative Office of Kulon Progo District, Yogyakarta Special Region

Organizational achievement is influenced by the work environment where employees carry out activities also have an important role in improving their performance. The work environment refers to the material and psychological conditions of employees in the organization. This study aims to determine the effect of work motivation and work environment on employee performance at the Kulon Progo Regency Small and Medium Enterprises Cooperative Office. In this study, the data collection techniques used were questionnaires, observation, documentation and literature study. The analysis used is instrument test, classical assumptions, multiple regression, hypothesis testing, and R2 estimation. Sampling by distributing questionnaires directly to 37 samples. The results of data processing from motivation (X1) have a positive and significant effect on employee performance, namely tcount 2.573> ttable 2.032 with a significance of 0.015 <0.05 and the work environment (X2) has a positive and significant effect on employee performance, namely tcount 2.903> ttable 2.036 with a significance of 0.006 <0.05. Fcount value 7.803> Ftable 3.28, with a significance value of 0.002 <0.05. This means that motivation and work environment simultaneously affect employee performance. The results of the coefficient of determination test obtained an R-square value of 0.315 or 31.5%, which means that the influence of the independent variables on the dependent variable and the rest is influenced by other factors outside the research variables.

The Influence of Job Training, Motivation, and Work Environment on Employee Performance at PT. Telekomunikasi Indonesia, Tbk Kediri City

This investigation intends to determine and anatomize the effect of job training, motivation, and work environment on employee performance at PT Telekomunikasi Indonesia, Tbk Kediri City. A key element in a company's success is employee performance. Job training, motivation, and a positive work environment are necessary for effective employee performance. Data gathering techniques include distributing questionnaires and performing direct talks with 50 permanent employees of PT. Telekomunikasi Indonesia, Tbk Kediri City. Analyzing data found that job training, motivation, and work environment affect employee performance at PT. Telekomunikasi Indonesia, Tbk Kediri City. This study has a noteworthy impact on job training, motivation, and work environment on employee performance. This research contributes science to human resources. The results can be applied to PT. Telekomunikasi Indonesia, Tbk Kediri City, to optimize job training, motivate employees, and improve a good work environment, so that it can affect employee performance and achieve company success. In further research, it’s hoped that they will research broader and different research objects. Thus, the results attained will benefit numerous parties.

Pengaruh Lingkungan Kerja dan Disiplin Kerja terhadap Kinerja Pegawai pada Kantor Kecamatan Beji Kota Depok

Beji Sub-district Office is 1 of 11 sub-districts in the city of Depok which has the task of assisting the Mayor in coordinating the administration of general government affairs, government affairs in the field of community empowerment and urban villages as well as the delegation of part of government affairs in other fields. The purpose of this study was to determine the effect of work discipline and work environment on the performance of Beji District employees in Depok City. The research was conducted for 3 months (April - June 2024). Data collection methods are through interviews, questionnaires and observations distributed to 58 respondents. The analysis method is quantitative statistics. Data analysis includes instrument quality tests consisting of validity and reliability tests, classical assumption tests, t tests and F tests. The results of this study indicate that the Work Environment partially has a positive and significant effect on the Performance of Employees of the Beji District Office. Work Discipline partially has a positive and significant influence on the Performance of Employees of the Beji District Office. Work Environment and Work Discipline simultaneously have a positive and significant influence on the Performance of Employees of Beji Subdistrict Office. The implication of the results of this study is that providing a good work environment and work discipline will improve employee performance..

Machine Learning in Wear Prediction

Abstract As modern devices and systems continue to advance, device wear remains a key factor in limiting their performance and lifetime, as well as environmental and health effects. Traditional approaches often rely on wear prediction based on physical models, but due to device complexity and uncertainty, these methods often fail to provide accurate predictions and accurate wear identification. Machine learning, as a data-driven approach based on its ability to discover patterns and correlations in complex systems, has enormous potential for monitoring and predicting device wear. Here, we review recent advances in applying machine learning for predicting the wear of mechanical components. Machine learning for wear prediction shows significant potential in optimizing material selection, manufacturing processes, and equipment maintenance, ultimately enhancing productivity and resource efficiency. Successful implementation relies on careful data collection, standardized evaluation methods, and the selection of effective algorithms, with artificial neural networks (ANNs) frequently demonstrating notable success in predictive accuracy.

Does county urban shrinkage in China affect the concentration of lung-accessible particulate matter? An analysis from spatial effects and EKC perspectives.

The environmental effects of urban shrinkage have gradually attracted academic attention. Based on spatial effects and EKC perspectives, this study constructs an environmental impact assessment framework and examines the impact of urban shrinkage on the concentration of lung-accessible particulate matter at the county level in China from 2013 to 2020. The results show that, from a two-dimensional perspective in space and time, lung-accessible particulate matter concentrations show a decreasing trend in the time series and an obvious autocorrelation feature in space. Urban shrinkage can affect lung-accessible particulate matter concentrations through spatial effects. Through direct effects, urban shrinkage promotes the increase of lung-accessible particulate matter concentrations. Through spillover effects, urban shrinkage suppresses the growth of lung-accessible particulate matter concentrations. The effect of urban shrinkage on lung-accessible particulate matter concentration is nonlinear (EKC). This may be the result of the "siphon effect." Furthermore, in the extended STIRPAT model, it was found that population and economic and technological factors differentially affect lung-accessible particulate matter concentrations in shrinking cities. This study gives a new idea and insight into the changes in environmental pollution in shrinking cities.

How data factor flow affects corporate pollution reduction: The environmental effects of digital empowerment

This study the theoretical hypotheses by building a relatively exogenous data factor flow indicator and a corporate pollution emission intensity indicator system using China's data flow restriction policy and corporate pollution emission data. Data factor is emerging as an essential new factor of production in today's digital economy, and data cannot function valuablely without an efficient flow. This study constructs a theoretical model of the influence of data factor flow on the pollution emissions of downstream manufacturing enterprises based on the vertical correlation of inputs and outputs. Additionally, we employ additional contaminants as a robustness test and sulfur dioxide, a common representation of air pollution, as the baseline. The empirical analysis's findings indicate that: (1) Data factor flow significantly reduces pollution in manufacturing enterprises. (2) The main way that data factor flow helps organizations minimize pollution is by increasing their productivity and ability to innovate in technology. (3) Domestic data flow is more important than cross-border data flow in helping industrial companies reduce pollution. (4) In general, foreign-owned enterprises have a greater need for data factor flow to reduce pollution than do state-owned and private businesses.

High-temperature anaerobic calcination for stabilizing environmentally stressful elements in phosphoric acid production by-products

Phosphorus tailings (P) refer to the waste materials left over after the extraction of phosphorus from phosphate rock during mining and processing. phosphogypsum (PG) is typical by-products of phosphoric acid production (PPB), containing numerous environmentally hazardous elements (EHE) that pose significant risks to ecological safety. In this study, we examined the impact of high-temperature anaerobic calcination on the migration and immobilization of EHE in PPB. The results indicated that higher temperature ranges favorably controlled the leaching toxicity of PPB. In the calcination products of P and PG, the inhibition efficiency of Pb leaching toxicity reached 84.93% and 89.33%, respectively. Under higher temperature conditions (P at 700 °C, PG at 600 °C), the inhibition of Cr leaching toxicity reached 100%. The inhibitory effects of high-temperature environments on EHE in PPB were ranked as fluorine > phosphorus > heavy metals. The mechanisms of migration and transformation of EHE in PPB under high-temperature anaerobic calcination were elucidated in three aspects, ranked from strongest to weakest. Firstly, the encapsulation of EHE by a shell-like structure, attributed to the “melt-wrap” phenomenon. Secondly, the decomposition-gasification phenomenon induced by high-temperature conditions. Thirdly, the effect of high temperature on the transformation of the storage forms of EHE. This study fills a research gap in the field of thermal treatment of PPB, enhancing the understanding of the specific effects of thermal treatment on the transformation of EHE in PPB, and provides theoretical and data support for the high-temperature thermal treatment of solid wastes.

Nanoscale friction and wear of graphite surface in ambient and underwater conditions

The tribological properties of graphite are extremely sensitive to surrounding environment, which affects its longevity and friction reduction performance. This study aims to develop a comprehensive understanding of the effects of a liquid environment on interactions at the sliding interface, thereby influencing the nanoscale tribological properties of graphite surfaces. By combining atomic force microscopy experiments and molecular dynamics simulations, we conducted a comparative analysis of friction and wear behavior of graphite under two different environmental conditions: ambient (air) and underwater condition. Our investigations explored both the step edge and interior (step-free) graphite surfaces. The experimental results revealed a notable contrast in the frictional and wear behavior of graphite at nanoscale in these two environments. The interior surface exhibited a friction coefficient (COF) of approximately 0.003 and 0.006 against a diamond-coated surface in ambient and underwater conditions, respectively. Interestingly, the underwater environment not only increased friction but also significantly compromised the wear resistance of graphene layers near the graphite surface compared to the ambient environment, as evidenced in both step edge and interior step-free regions. The interior region sustained up to ∼7400 nN load in ambient condition but failed at ∼1500 nN under water. Similarly, the step edge failed at ∼375 and ∼187.5 nN in ambient and underwater conditions, respectively. Our simulations revealed that the increased friction in underwater condition is due to resistance of surrounding water molecules during tip sliding. The presence of water at tip-graphite contact interface generated substantial localized stress, leading to the initiation of wear and revealing the pronounced effect of water on the wear characteristics of graphite in underwater condition.

Environmental and Welfare Effects of Large-Scale Integration of Renewables in the Electricity Sector

AbstractThe 2022 energy crisis highlighted the dependence of the Europe electricity sector on imported natural gas and the need to accelerate the adoption of renewables to the power system. However, operating a reliable power system with high share of renewables might require curtailing some renewables and activating conventional generators not scheduled in the day-ahead markets to ensure system reliability. These actions can result in environmental impacts, higher system costs and welfare impacts for customers. We use a novel high-granularity data from the Spanish power system for the period 2019–2022 to estimate the effects of these actions and forecast future impact of implementing ambitious targets of the European Gas Reduction Plan. We show that reliance on conventional generators will sharply increase with the addition of renewables. However, higher electricity consumption reduces the negative welfare impacts of integrating renewables. Until renewables and storage technologies advance further, conventional generators are needed for reliable operation of the systems.

Removal of Per- and Polyfluoroalkyl Substances (PFAS) in fixed bed anion exchange reactors: Factors determining PFAS uptake capacity and models predicting PFAS breakthrough

Per- and polyfluoroalkyl substances (PFAS) are widespread contaminants with adverse environmental and public health effects. Anion exchange (IX) processes can effectively remove many PFAS from water. Objectives of this research were to (1) quantify the effects of PFAS structure and background water matrix constituents [dissolved organic matter (DOM) and major inorganic anions (bicarbonate, chloride, sulfate, and nitrate)] on PFAS uptake capacity of IX resins (KIX), and (2) develop models that predict PFAS breakthrough in packed bed IX columns from PFAS structure and background water matrix characteristics. Rapid small-scale column tests were conducted with two IX resins and 18 water matrices to determine breakthrough curves and KIX values for 23 PFAS. A quantitative structure-property relationship (QSPR) was developed that predicts KIX for different PFAS from a newly developed concept, the normalized chain length (NCL). NCL for each PFAS was calculated using a group contribution method, in which the contributions of PFAS structural fragments to NCL were normalized to that of -CF2-, which was assigned a value of 1.00. Relative to -CF2-, contributions of the structural fragments -O-, -CH2-, >CF-CF3, -CHF-, and -SO3H to NCL for the purposes of KIX prediction were 0.34, -1.87, 1.70, 0.00, and 3.65, respectively. DOM and nitrate adversely impacted PFAS removal, while chloride, sulfate, and bicarbonate, when added at concentrations of up to 3 meq/L above native background levels, had negligible effects on KIX. Based on the obtained water matrix effects, pseudo-single solute models were developed for the two tested IX resins, with which PFAS breakthrough curves for fixed bed IX columns can be predicted using only the NCL and the total organic carbon and nitrate concentrations of the influent water.

Economic and Environmental Effects of Farmers’ Green Production Behaviors: Evidence from Major Rice-Producing Areas in Jiangxi Province, China

This study examines the economic and environmental impacts of green production practices among farmers. It aims to contribute to sustainable agricultural development, mitigate agricultural non-point source (NPS) pollution, and align environmental protection with economic growth. This paper utilizes survey data from 1345 farm households in the main rice production areas of Jiangxi Province, China, using the example of reduced fertilizer application (RFA) among rice farmers. This study constructs a slack-based measure data envelopment analysis (DEA—SBM) model with undesirable outputs to measure environmental effects and applies an endogenous switching regression model (ESRM) to test the economic and environmental effects of farmers’ adoption of green production technologies. We found the following: (1) The RFA behavior of farmers has a significant positive impact on their net profit per hectare (NPH), helping farmers increase their income, with the increase ranging from 2.05% to 6.54%. (2) Farmers’ RFA behavior has a significant positive impact on agricultural green productivity (AGP), contributing to the improvement of the environment, ranging from 44.09% to 45.35%. (3) A heterogeneity analysis found inconsistencies in the income-enhancing and environmental-enhancing effects at different quantiles of NPH and AGP. Therefore, attention should be placed on improving the agricultural product quality supervision system under the market circulation mechanism, creating land scale conditions conducive to the promotion and application of fertilizer reduction technologies and promoting the implementation of externality internalization compensation systems.