Analysis Of Environmental Effects Research Articles

Analyzing sustainability in bread production: a life cycle assessment approach to energy, exergy and environmental footprint.

Bread production is a pivotal component of global nutrition. However, its extensive production imposes significant strain on resources and energy, resulting in substantial environmental consequences. This study focuses on a multidimensional assessment of the environmental sustainability of the bread life cycle as a case study in Iran. By integrating four life cycle assessment (LCA) methods, this research demonstrates a comprehensive analysis of environmental effects, energy consumption, and exergy demand in bread production. It also identifies the hotspot stages and inputs within the bread production chain. Eventually, it proposes strategies for mitigating the environmental impacts in line with sustainable development goals. Data collection involved questionnaires by face-to-face interviews. The LCA evaluation was conducted using SimaPro software. Sustainability analysis was assessed using four different methods: CML, ReCiPe, cumulative energy demand (CED), and cumulative exergy demand (CExD) method, from cradle to bakery gate. The CML method results indicate that the highest environmental impacts are associated with marine aquatic ecotoxicity (157.04 to 193.36 kg 1,4-DB eq), fossil fuel depletion (11.05 to 12.73 MJ), eutrophication (4.20 × 10-3 to 4.70 × 10-3 kg PO4-3eq), acidification (8.09 × 10-3 to 9.16 × 10-3 kg SO2 eq), and global warming (0.61 to 0.69 kg CO2 eq). The ReCiPe method highlights wheat production stages and gas consumption as the most significant contributors to damage in terms of human health, ecosystems, and resource consumption indicators. The CED method reveals that fossil energy accounts for over 97% of the energy consumed during the bread life cycle. Energy consumption per kilogram of bread ranges from 12.07 to 13.93 MJ. The CExD method for producing 1 kg of traditional bread falls between 32.25 and 35.88 MJ. More than 60% of this value is attributed to renewable resources of water used in irrigation during the wheat farming stage, while over 35% is linked to non-renewable fossil resources, primarily due to the consumption of natural gas in bakery operations. To assess the potential decrease in environmental emissions, a sensitivity analysis was performed, considering the effects of substituting natural gas with biogas and grid electricity with photovoltaic electricity in the bakery. Then, three improved scenarios were developed, each demonstrating effective reductions in environmental impacts, with the most remarkable decreases observed in marine aquatic ecotoxicity (55%) and fossil fuel depletion (44%). Overall, the findings demonstrate that Sangak bread production exhibits a more environmentally friendly profile than other types of bread. These results can guide decision-makers in the bread production industry towards implementing sustainable practices that prioritize resource efficiency and environmental conservation. Also, stakeholders can develop strategies to reduce the environmental impacts and work towards a more sustainable future.

Analysis of environmental impact reduction effect of applying high-speed flash mixer in sewage sludge dewatering process

Analysis of environmental impact reduction effect of applying high-speed flash mixer in sewage sludge dewatering process

Factor analysis of environmental effects in circular closed‐loop supply chain network design and modelling under uncertainty in the manufacturing industry

AbstractSustainable development and competitive advantage are impacted by strategic choices that maximize resource value and reduce waste. Numerous instances of thriving OEM remanufacturing can be observed, predominantly in the business‐to‐business domain. The significance of Closed‐Loop Supply Chain (CLSC) in generating value and managing the recovery process is widely acknowledged within the supply chain industry. Manufacturing companies now have to come up with green supply chain and process design strategies in response to recent changes in environmental regulations. This study designates the specific features of circular closed‐loop supply‐chain design considering end‐of‐life products. Uncertainty in various aspects, such as acquisition, processing, and market stages, is impeding the progress of circular economies and also sustainable development in closed‐loop supply chains (CLSCs). This has led to increased complexity in remanufacturing processes and decreased efficiency. To address this issue, the study proposes a comprehensive, integrative approach for establishing a sustainable CLSC network that adapts to fluctuating demand through a questionnaire analysis. Moreover, the study introduces a multi‐objective optimization model for a dual‐channel supply chain network, aiming to enhance the flow. This model considers both economic and environmental objectives to achieve a sustainable and efficient supply chain system. To determine the ideal circular closed‐loop supply chain (CLSC) network design, the research proposes linear programming model with mixed integer, where recovery can take place in one of three ways: through material recovery, component recovery, or product recovery. Numerous findings from a thorough analysis by data backup that inform CLSC managers of ways to improve product returns in terms of quantity and quality. To address the uncertainty problem, the research also developed the fuzzy credibility constraint technique with a Simulated Annealing algorithm. Using cutting‐edge methods, it is explored and compared how sensitivity analysis results, the impact of altering the problem parameters, and the performance of the suggested model respectively.

Performance enhancement of engineered cementitious composite through tailoring recycled iron sand

Engineered cementitious composite (ECC) possesses predominant tensile properties while a relatively low modulus of elasticity (MOE) due to the low sand-to-binder ratio and fine quartz sand (QS, QS-ECC). Further, the excessive consumption of QS in concrete industry has imposed a serious challenge to natural resource preservation. Iron sand (IS), a by-product of the iron industry with high particle modulus, could be a potential alternative in developing ECC (IS-ECC). This research focused on recycling IS as fine aggregate to develop a sustainable ECC with high mechanical performance, especially high MOE. The influences of water-to-binder ratio, sand-to-binder ratio, and IS particle size were systematically investigated. The results indicated that all the IS-ECC demonstrated robust tensile performance with the tensile strength and strain capacity over 5 MPa and 5%, respectively. Compared with the QS-ECC, a comparable or even superior compressive strength was achieved by all the IS-ECC. Impressively, the MOE of IS-ECC with 20–40 and 40–80 mesh of IS particles exhibited 68% and 60% higher than that of QS-ECC, respectively. SEM observations well reflected the macroscopic tensile performances. The cost and environmental effect analysis revealed the sustainability of IS-ECC. This research provides the groundwork for promoting the utilization of IS in developing high performance ECC material.

Environmental Risk Assessment of a Hydrocracker Unit in Abadan Oil Refinery Using the EFMEA Analysis

Background: The aim of risk assessment is to use a rational method to analyze risks and to identify the possible hazards and outcomes for people, equipment, materials, and the environment. Methods: The criteria and indices for assessing the environmental, health, and safety risks of the hydrocracker unit were determined by a Delphi questionnaire in this study. Then, an Environmental Failure Mode and Effects Analysis was applied to evaluate, score, and rank the risks based on their probability of occurrence, severity, probability of detection, extent of pollution, and potential of recycling. Results: According to the results of the Delphi process, 19 out of the 22 items were identified as the main criteria in the environmental, health, and safety risk evaluation of the hydrocracker unit at the Abadan Oil Refinery. However, the results indicated that 67% of the risks associated with the life cycle operation were low while 33% of them were high in terms of intensity. In contrast, 75% of the risks associated with control room operators were low and 25% were high in terms of intensity. On the other hand, 64, 7, and 29% of the risks associated with the activities of site employees were low, moderate, and high in terms of intensity, respectively, while the corresponding figures were 14, 29, and 57% in the case of risks associated with repairs. Conclusion: Based on the results of techniques of environmental failure modes and effects analysis (EFMEA) and Delphi, appropriate methods can be used to identify and reduce risks in similar industries.

Analysis of the Interrelationships between Lightweight Design and Design for Sustainability

Lightweight design is gaining in importance for design for sustainability due to its capability to reduce weight, conserve materials, and enhance energy efficiency. However, environmental sustainability encompasses a broader spectrum, including, for instance, a responsible resource management as well as material recyclability. Despite their shared objective of optimizing resource consumption, can lightweight design indeed be substantiated as sustainable, and if so, how?Therefore, this contribution emphasizes a systematic approach for the analysis of environmental effects caused by property changes resulting from the implementation of lightweight design strategies (system, form, material and manufacturing lightweight design) in products. Thereby, life cycle issues of the lightweight design strategies are evaluated on the basis of a holistic life cycle perspective. Finally, the interrelationships between lightweight design strategies and sustainability strategies (eco-efficiency, eco-effectiveness, and sufficiency) are discussed. In future, the presented approach supports both positive synergies as well as negative conflicts of lightweight design and design for sustainability to be efficiently and strategically evaluated throughout the design process, so that holistically optimized lightweight and sustainable products can thus be created.

Intrinsic mechanisms and spatial effects of multidimensional urbanization and carbon emissions.

Existing studies on urbanization and carbon emissions are mostly based on a single pathway and lack the support of a theoretical framework. This study innovatively integrates Grossman's perspective of environmental effects analysis to develop a new framework to interpret the mechanism of multidimensional urbanization (MU) and carbon emissions (CEs). We first explored the spatial effects of MUs and CEs in the Yangtze River Delta urban agglomeration (YRDUA) and then introduced the "population-land-economic" urbanization variables into the S-STIRPAT model to determine the impact mechanisms of each factor on CEs under different urbanization dimensions. The results show that the spatiotemporal development patterns of MUs and CEs overlap to some extent. The Shanghai-Nanjing line is a high-value area of urbanization with different dimensions, as some edge cities are in low-value areas. However, there are local differences in the different dimensions of urbanization, e.g., population urbanization in the southern area is in a high-value area. CEs show a core-edge structure of "high in the center and low in the north and south". All factors, except for population urbanization, affect CEs locally, and their spillover effects are all positive, except for energy intensity, which has a negative influence on CEs in neighboring regions. Land urbanization has the largest positive impact on CEs, with a total effect coefficient of 0.409; economic urbanization has a coefficient of 0.195, and population urbanization has a coefficient of only 0.070. The findings can help to maximize urbanization growth while minimizing harmful environmental externalities.

Analysis of environmental biological effects and OBT accumulation potential of microalgae in freshwater systems exposed to tritium pollution

The ecological risk of tritiated wastewater into the environment has attracted much attention. Assessing the ecological risk of tritium-containing pollution is crucial by studying low-activity tritium exposure's environmental and biological effects on freshwater micro-environment and the enrichment potential of organically bound tritium (OBT) in microalgae and aquatic plants. The impact of tritium-contaminated wastewater on the microenvironment of freshwater systems was analyzed using microcosm experiments to simulate tritium pollution in freshwater systems. Low activity tritium pollution (105 Bq/L) induced differences in microbial abundance, with Proteobacteria, Bacteroidota, and Desulfobacterota occupying important ecological niches in the water system. Low activity tritium (105–107 Bq/L) did not affect the growth of microalgae and aquatic plants, but OBT was significantly enriched in microalgae and two aquatic plants (Pistia stratiotes, Spirodela polyrrhiza), with the enrichment coefficients of 2.08–3.39 and 1.71–2.13, respectively. At the transcriptional level, low-activity tritium (105 Bq/L) has the risk of interfering with gene expression in aquatic plants. Four dominant cyanobacterial strains (Leptolyngbya sp., Synechococcus elongatus, Nostoc sp., and Anabaena sp.) were isolated and demonstrated good environmental adaptability to tritium pollution. Environmental factors can modify the tritium accumulation potential in cyanobacteria and microalgae, theoretically enhancing food chain transfer.

Urban public lighting classification method and analysis of energy and environmental effects based on SDGSAT-1 glimmer imager data

Urban lighting system is an important part of urban space service functions. With the continuous advancement of sustainable development goals, governments of various countries are gradually paying attention to the energy, social, economic and environmental benefits of urban lighting systems, and promote the use of LED lighting to replace HPS lamp lighting to save urban energy consumption. In this study, we used the glimmer imager data of SDGSAT-1 launched in 2021, combined with the streetlight dataset of the District of Columbia, to establish a classification model for distinguishing LED lights from HPS lamps, with an overall recognition accuracy of 80.3% and the kappa coefficient is 0.603. Based on this model, we identify light types in the central cities of China’s three urban agglomerations: Beijing, Shanghai, Guangzhou, and Shenzhen, and describe their lighting composition and spatial distribution patterns. Additionally, we make a preliminary estimate of the money and electricity consumption saved by lighting renovations, and analyzed the impact of urban lighting changes on public perception. This study combines SDGSAT-1 data to propose a training model in urban lighting classification and applies it to a wide range of urban, the results of which help to provide data to support the implementation of SDG7.

Short-term exposure sequences and anxiety symptoms: a time series clustering of smartphone-based mobility trajectories

BackgroundShort-term environmental exposures, including green space, air pollution, and noise, have been suggested to affect health. However, the evidence is limited to aggregated exposure estimates which do not allow the capture of daily spatiotemporal exposure sequences. We aimed to (1) determine individuals’ sequential exposure patterns along their daily mobility paths and (2) examine whether and to what extent these exposure patterns were associated with anxiety symptoms.MethodsWe cross-sectionally tracked 141 participants aged 18–65 using their global positioning system (GPS) enabled smartphones for up to 7 days in the Netherlands. We estimated their location-dependent exposures for green space, fine particulate matter, and noise along their moving trajectories at 10-min intervals. The resulting time-resolved exposure sequences were then partitioned using multivariate time series clustering with dynamic time warping as the similarity measure. Respondents’ anxiety symptoms were assessed with the Generalized Anxiety Disorders-7 questionnaire. We fitted linear regressions to assess the associations between sequential exposure patterns and anxiety symptoms.ResultsWe found four distinctive daily sequential exposure patterns across the participants. Exposure patterns differed in terms of exposure levels and daily variations. Regression results revealed that participants with a “moderately health-threatening” exposure pattern were significantly associated with fewer anxiety symptoms than participants with a “strongly health-threatening” exposure pattern.ConclusionsOur findings support that environmental exposures’ daily sequence and short-term magnitudes may be associated with mental health. We urge more time-resolved mobility-based assessments in future analyses of environmental health effects in daily life.

Analysis of environmental effects and estimation of genetic parameters for carcass traits in Hanwoo steers produced through embryo transfer

This study estimated the environmental effects and genetic parameters for carcass traits of 2,309 Hanwoo steers produced through Embryo Transfer (ET) to confirm the performance improvement achieved. The data used for analysis collected information on offspring produced by ET from 2012 to 2020. SAS 9.4 GLM package was used to analyze the environmental effects affecting carcass traits, and genetic parameters were estimated using the REMLF90 program for heritability, genetic correlation, and phenotypic correlation. The collected Carcass Weight (CWT), Eye Muscle Area (EMA), Back-Fat Thickness (BFT), and Marbling Score (MS) were 505.2±58.19kg, 105.57±13.41cm2, 12.76±4.27mm, and 7.25±1.61 points, respectively. It was found that the environmental effect of growth area and slaughter month had a significant effect (p<0.01) on carcass traits. Heritability was 0.51, 0.64, 0.36, and 0.59 in CWT, EMA, BFT, and MS, respectively, and high heritability was observed in all traits except BFT. Due to the characteristics of ET, it is considered that the effect of genetic improvement was more pronounced because there were many offspring with the same parents or the same father or mother. Therefore, it is judged that more efficient improvement effect and performance can be confirmed if an optimal environmental model is set based on the results of this study and used as basic data for breeding. If these results continue to accumulate, it is thought that it will be able to contribute to the increase in farm household income through the improvement effect.

VICTORIA project: The LOFAR HBA Virgo Cluster Survey

Context. The Virgo cluster is the nearest (d = 16.5 Mpc) massive (M ≥ 1014 M⊙) galaxy cluster and is therefore a prime target for studying astrophysical processes in dense large-scale environments. In the radio band, we can probe the nonthermal components of the interstellar medium, the intracluster medium (ICM), and of active galactic nuclei (AGN). This allows an investigation of the impact of the environment on the evolution of galaxies and the contribution of AGN to ICM heating. With the ViCTORIA (VIrgo Cluster multi-Telescope Observations in Radio of Interacting galaxies and AGN) project, we are carrying out multiple wide-field surveys of the Virgo cluster at different frequencies. Aims. We aim to investigate the impact of the environment on the evolution of galaxies and the contribution of AGN to ICM heating – from the inner cluster regions out to beyond the virial radius. Methods. We performed a survey of the cluster at 120–168 MHz using the LOw-Frequency ARray (LOFAR). We imaged a 132 deg2 region of the cluster, reaching an order-of-magnitude greater sensitivity than existing wide-field radio surveys of this field at three times higher spatial resolution compared to other low-frequency observations. We developed a tailored data processing strategy to subtract the bright central radio galaxy M 87 from the data. This allowed us to correct for systematic effects due to ionospheric variation as a function of time and direction. Results. In the final mosaic, which has a resolution of 9″ × 5″, we reach a median noise level of 140 μJy beam−1 inside the virial radius and 280 μJy beam−1 for the full area. We detect 112 Virgo member galaxies and 114 background galaxies. In at least 18 cases, the radio morphology of the cluster member galaxies shows clear signs of ram-pressure stripping. This includes three previously unreported candidates. In addition, we reveal previously undiscovered tails of 150 kpc in length from a previous epoch of AGN activity for NGC 4472 (M 49). While no cluster-scale diffuse radio sources are discovered, we find the presence of an extended radio signature of the W′ group. This feature is coincident with an X-ray filament detected with SRG/eROSITA in the outskirts of the cluster. We speculate that this emission is synchrotron radiation, which could be related to shocks or turbulence from accretion processes. Conclusions. The data published in this paper serve as a valuable resource for future studies. In the follow-up work of the ViCTORIA project, we will use these data for an analysis of environmental effects on the radio properties of star-forming galaxies in Virgo.

Economic and Environmental Effect Analysis of Rhodium Recycling System

Economic and Environmental Effect Analysis of Rhodium Recycling System

Sustainability in anaesthesia and intensive care - an obligation to turn danger into opportunity.

Sustainability in anaesthesia and intensive care - an obligation to turn danger into opportunity.

A successive time-to-event model of phyllochron dynamics for hypothesis testing: application to the analysis of genetic and environmental effects in maize

BackgroundThe time between the appearance of successive leaves, or phyllochron, characterizes the vegetative development of annual plants. Hypothesis testing models, which allow the comparison of phyllochrons between genetic groups and/or environmental conditions, are usually based on regression of thermal time on the number of leaves; most of the time a constant leaf appearance rate is assumed. However regression models ignore auto-correlation of the leaf number process and may lead to biased testing procedures. Moreover, the hypothesis of constant leaf appearance rate may be too restrictive.MethodsWe propose a stochastic process model in which emergence of new leaves is considered to result from successive time-to-events. This model provides a flexible and more accurate modeling as well as unbiased testing procedures. It was applied to an original maize dataset collected in the field over three years on plants originating from two divergent selection experiments for flowering time in two maize inbred lines.Results and conclusionWe showed that the main differences in phyllochron were not observed between selection populations but rather between ancestral lines, years of experimentation and leaf ranks. Our results highlight a strong departure from the assumption of a constant leaf appearance rate over a season which could be related to climate variations, even if the impact of individual climate variables could not be clearly determined.

Analysis of Mechanical and Environmental Effects of Utilizing Waste Glass for the Creation of Sustainable Ultra-High Performance Concrete

Analysis of Mechanical and Environmental Effects of Utilizing Waste Glass for the Creation of Sustainable Ultra-High Performance Concrete

Sustainability Assessment Techniques and Potential Sustainability Accreditation Tools for Energy-Product Systems Modelling

The modelling of complex technological systems serves as the foundation for enhancing process performance, including sustainability features (triple-bottom line). The European Green Deal, proposed in 2019, aims to cut greenhouse gas emissions by 2050 and foster a resource-independent economy. Such a change must be carefully planned. Comprehensive sustainability protocols and guidelines are necessary to describe the standardized methodological procedure, the environmental certification procedures that allow market comparability and identification of the best solutions, the databases, the calculation tools and software, and the benchmark and target with which to make comparison. Policies and regulatory or incentive instruments promote the broad adoption of these approaches and ensure that policies reduce environmental, economic, and social impacts. This paper consists in an overview of sustainability assessment tools’ role in energy policy and short- and long-term modeling of more eco-friendly energy-product systems. Additionally, the paper explores these methods’ pros and cons in planning, analyzing, and optimizing energy/product systems, also according to the circular economy paradigm. All of these strategies aim to help the decision-maker make more consistent judgments by taking into consideration essential objective, such as end user or stakeholder demands, and minimizing subjective elements. An extensive listing of Sustainability accreditation and communication tools is provided. Sustainability assessment is an evaluation and optimization method that promotes sustainable development in all political planning and decision-making. It examines the social, economic, and environmental effects, finds conflicting goals, and recommends early optimization. Potentially, sustainability assessment should be integrated into the political planning process and depend on domain-specific research and assessments that currently exist or are planned, such as in combination with decision-making. Sustainability assessment is not designed to be an extra analytical tool. A sector-specific environmental or economic study from a strategic environmental analysis or regulatory effect analysis may be crucial to a sustainability assessment.

Environmental and enviro-economic effect analysis of hydrogen-methanol-gasoline addition into an SI engine

This paper provides a novel approach to the environmental and enviro-economic assessment of an SI engine at various loads (25Nm, 50Nm, 75 Nm, 100 Nm, and full load) using different fuel blends such as methanol-gasoline (20% methanol + 80% gasoline in volumetric), and hydrogen-methanol-gasoline (methanol-gasoline blend + 5% hydrogen). Environmental and enviro-economic analysis methods are applied based on emitted carbon amount in the atmosphere and carbon price. The average brake-specific fuel consumption value was observed to substantially increase the rate by 12.82% with the methanol and a reduction of 4.34% with the hydrogen addition. Moreover, the maximum engine torque increased by 4.15% with hydrogen at full engine load. The average values of the annual CO2 environmental effect were calculated at 29.02 tCO2/y, 29.06 tCO2/y, and 28.51 tCO2/y for gasoline, methanol, and hydrogen fuel blends, respectively. The environmental impact of CO2 values slightly increased by 0.11% with adding methanol to gasoline. However, a reduction was observed at 1.89% with the hydrogen addition. The average value of NO decreased by 2.25% with methanol, whereas it dramatically increased by 5.80% with hydrogen. The average values of the annual CO2 enviro-economic effect were obtained at 1863.98 $/y, 1866.02 $/y, and 1830.67 $/y for gasoline, methanol, and hydrogen fuel blends, respectively. The best engine parameters and the environmental effect values were obtained at 77.80 Nm, 286.93 g/kWh, and 28.99 tCO2/y according to over-fuel consumption and over-pollution amount. For the enviro-economic over-pollution cost, the best results have occurred at 83.03 Nm, 278.90 g/kWh, and 1960.20 $/y. The obtained results will present a new perspective for evaluating the use of alternative fuels in internal combustion engines. Thus, further investigations are required to assess alternative fuels’ longer-term environmental and enviro-economic impacts.

An Analysis of Environmental Effect on VIIRS Nighttime Light Monthly Composite Data at Multiple Scales in China

Nighttime light (NTL) can provide valuable information about human activities. The temporal NTL variation has been previously explored, but the effect of environmental factors has not been fully considered. Here, this article focused on the environmental effect on NTL time series in China, using the visible infrared imaging radiometer suite (VIIRS) monthly products, Earth Observations Group (EOG) product, and Black Marble product, from January 2014 to December 2020. It was found that the NTL variations were statistically correlated with aerosols, vegetation, and surface albedo. NTL variations were negatively correlated with aerosol and vegetation, but positively correlated with surface albedo. Aerosol optical depth was important to explain the NTL variation among environmental factors. In 79% of urban areas in China, the adjusted <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i> -squared of NTL and the three factors surpassed that of NTL and the two factors (vegetation and surface albedo) based on EOG product. In 60% of urban areas in China, the adjusted <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i> -squared of NTL and the three factors surpassed that of NTL and the two factors (vegetation and surface albedo), based on Black Marble product. Both EOG monthly product and Black Marble monthly product were affected by aerosols, surface albedo, and vegetation at multiple scales. However, Black Marble product was less affected by aerosols than EOG product. This article suggests that environmental effect is crucial in the NTL variation. Understanding NTL temporal variation can improve the accuracy of time series VIIRS imagery for socioeconomic applications.

Bayesian analysis of genetic and environmental effects on litter traits in a red fox (Vulpes vulpes) herd under long-term selection.

The economic efficiency of fur animal farms is considerably influenced by reproductive performance. The objectives of this study are to determine the effects of individual and maternal inbreeding, birth year, and dam and sire age on litter size at birth (LSB) and at weaning (LSW) and on preweaning mortality (PWM) in a red fox herd under long-term selection, and to determine the heritability of these traits. In total, 37,973 pedigreed individuals were used to calculate the inbreeding coefficients, based on records of 14,527 litters of 3856 dams born from the year 1958 to 2015. Two data sets (all data and data for the Polish variety) were analyzed. The highest heritability was estimated for PWM (0.292, 0.306) and the lowest for LSW (0.114, 0.115). In contrast to paternal and maternal inbreeding, litter inbreeding was found to exert a significant influence. The absence of significant effects of most varieties may suggest relatively large genetic similarity in the world red fox population. This corresponds with the similarity of the results obtained for the total herd and for the Polish variety. Favorable genetic trends were observed for the studied traits, indicating that the selection applied had been a relatively effective approach to improving these traits.