Environmental Pollution Emissions Research Articles

Has the Anti-Corruption Campaign Decreased Environmental Pollution? Evidence from China

Whether anti-corruption efforts help reduce environmental pollution is a hot topic in academia. This paper analyzes the impact of anti-corruption on the emissions of environmental pollutants using panel data from 31 provinces (municipalities) in China from 2015 to 2022. By using the 2018 supervision system reform as an exogenous policy shock, a Difference-in-Differences (DID) model is employed to examine the impact of the anti-corruption campaign on environmental pollutant emissions. The results show that the effectiveness of anti-corruption measures has strengthened over time, especially after the 2018 system reform, although these reforms exhibit a lag effect before significantly reducing pollution levels. Furthermore, heterogeneity analysis indicates that due to the high-pollution, high-energy-consumption industrial structure, the pollution reduction effect of anti-corruption measures is more pronounced in resource-based provinces than in non-resource-based provinces. Our findings emphasize the importance of strengthening anti-corruption measures and establishing a sound legal framework to effectively curb corruption and enhance environmental protection.

Effects of SPAD value variations according to nitrogen application levels on rice yield and its components.

Nitrogen (N) is the most essential element for growth, development, and grain yield determination in crops. However, excessive nitrogen application can result in environmental pollution and greenhouse gas emissions that contribute to climate change. In this study, we used 158 rice genetic resources to evaluate the relationships between the soil and plant analysis development (SPAD) value and grain yield (GY) and its components. The SPAD value ranged between 30.5 and 55.8, with a mean of 41.7 ± 5.3, under normal nitrogen conditions (NN, 9 kg/10a), and between 27.5 and 52.3, with a mean of 38.6 ± 4.8, under low nitrogen conditions (LN, 4.5 kg/10a). Under NN conditions, the SPAD values were in the following order: japonica (43.5 ± 5.8), Tongil-type (41.7 ± 2.5), others (41.7 ± 5.2), and indica (38.3 ± 3.8). By contrast, under LN conditions, the SPAD values were in the following order: Tongil-type (40.4 ± 2.1), others (40.1 ± 4.5), japonica (39.6 ± 5.2), and indica (35.6 ± 3.9). The 158 genetic resources showed no correlation between SPAD and yield. Therefore, the low-decrease rate (LDR) and high-decrease rate (HDR) SPAD groups were selected to reanalyze the relationships between the surveyed traits. The SPAD values were positively correlated with 1000-grain weight (TGW) for both LDR and HDR groups (NN: 0.63, LN: 0.53), However, SPAD and GY were positively correlated only in the LDR group. For TGW, the coefficient of determination (R 2) was 20% and 13% under NN and LN conditions, respectively. For GY, R 2 values of 32% and 52% were observed under NN and LN conditions, respectively. Genetic resources with higher SPAD values in the LDR group exhibited the highest yield (NN: 1.19 kg/m2, LN: 1.04 kg/m2) under both NN and LN conditions. In conclusion, we selected 10 genetic resources that exhibited higher GY under both NN and LN conditions with minimal yield reductions. These genetic resources represent valuable breeding materials for nitrogen deficiency adaptation.

The mechanism and path of pollution reduction and carbon reduction affecting high quality economic development - taking the Yangtze River Delta urban agglomeration as an example

In the wake of the COVID19 pandemic, what is crucial for the continued promotion of ecological civilization construction and sustainable green development in China is to achieve the dynamic and balanced development between pollution reduction, carbon emission reduction, and economic growth. Therefore, the indexes of CO2 emissions, pollution reduction intensity, and high-quality economic development are quantified in this study by using the panel data related to 26 cities in the Yangtze River Delta urban agglomeration(YRDUA) from 2010 to 2020. Furthermore, kernel density analysis, GIS spatial analysis, and other methods are employed to demonstrate the spatial and temporal patterns of pollution reduction intensity, CO2 emission levels, and the characteristics of high-quality economic development in the YRDUA. In order to reveal the dynamic relationship between pollution reduction, carbon emission reduction, and high-quality economic development, a panel vector autoregressive model (PAVR) was established and the system generalized method of moments was used to estimate the model coefficients. Additionally, Granger causality tests, impulse response analysis, and variance decomposition were conducted. There is a fluctuating upward trend shown by the overall level of CO2 emissions in the YRDUA, with significant spatial nonuniformity exhibited in carbon emissions. Despite the self-promotion mechanism playing a more significant role in the high-quality economic development in the YRDUA and its three regions, the impact of pollutant and carbon emissions on high-quality economic development is quite limited. A significant promoting effect is exhibited in those high and moderately high-quality economic development regions, while nonlinear effects are observed in those high and moderately high-quality economic development regions. As for the interactive relationships, the three factors are correlated with each other to a more significant extent in those high and moderately high-quality economic development regions, which contributes to mutual influence and causal relationship. However, there is no effective interactive mechanism observed among the three factors in the whole area and low-quality economic development regions, with high-quality economic development playing a major role in environmental pollution and carbon emission reduction.

INTENSITY OF GREENHOUSE GAS FORMATION DUE TO LIVESTOCK FARMING ACTIVITIES – AS AN ENVIRONMENTAL FACTOR

According to numerous expert assessments by international organizations and specialists, animal husbandry makes a significant negative contribution to global climate change due to the emission of greenhouse gases (GHG), which are formed at different stages of livestock production as a result of various chemical and biological processes in the body of animals and in livestock waste. The domestic animal husbandry is developing mainly due to the intensification of production in the industry, but traditional farming methods as well as small-scale production in the individual sector also take place. Since the use of various technologies in animal husbandry has different effects on the level of environmental pollution and GHG emissions, the aim of the research was to study the differences in the intensity of GHG gas formation by one animal reared with individual features of animal rearing technologies and business activities. The intensity of gas formation and emission of CH4 and N2O in typical farms for pork production and milk production by one animal reared was determined, analyzed and substantiated. A significant variation in this indicator was found depending on the individual economic and technological features of the studied farms. The average weighted annual intensity of CH4 emission from animal manure in pig farms varied within the range of 0.95–25.71, in cattle farm – 2.74; CH4 from intestinal fermentation of dairy cows – 110.8–148.4; N2O (direct) in pig farms – 0.0–0.106, in cattle farm – 0.229; N2O (indirect) in pig farms – 0.071–0.097, in cattle farm – 0.174. The emission intensity is characterized separately in each age and sex group of animals in the herd structure of farms and the average weighted emission intensity in pork producing farms depending on the season. Based on the research results, it is proposed to use the generalized average annual indicator of greenhouse gas emissions per one average weighted animal reared (kg/head/year) as an indicator of the environmental load of livestock farms on the environment, which will allow planning production volumes with minimal environmental risks in the context of climate change.

Assistance Innovation In Organic Waste Management As A Hydroponic Media Substrate Building A Green Future

Organic waste management is becoming increasingly important in responding to current global environmental challenges. In this context, this community service aims to explore the potential for using organic waste as a substrate for hydroponic media in building a greener agricultural future in a sustainable system. The use of organic waste as a substrate for hydroponic media has great potential in supporting plant growth, because it contains available N, P2O5, K2O and C-organic nutrients which are sufficient for plant growth and development. Plants grown in organic waste-based substrates show comparable or even better growth compared to plants grown in conventional substrates. The use of organic waste in hydroponic farming also has a positive impact on the environment. More effective management of organic waste helps reduce environmental pollution and greenhouse gas emissions. This community service program has also succeeded in increasing public awareness and knowledge about organic waste management and hydroponic technology. Thus, the use of organic waste as a substrate for hydroponic media offers great potential in improving organic waste management, increasing agricultural productivity, and reducing negative impacts on the environment. This activity makes a real contribution to building a more sustainable agricultural future and contributes to global efforts in facing increasingly complex environmental challenges.

Pelatihan Pembuatan Pupuk Organik Cair dari Limbah Ternak Sapi

The training on the production of liquid organic fertilizer from cattle waste in Merembu Village, Labuapi Subdistrict, West Lombok Regency aimed to enhance the participants' knowledge and skills in managing livestock waste into economically valuable and environmentally friendly products. This training utilized Participatory Rapid Appraisal (PRA) and Participatory Learning and Action (PLA) methods, engaging participants actively at every stage of the learning process. Results from pre- and post-training questionnaires showed a significant increase in participants' knowledge and understanding, with an average score improvement of 55%. Observations and document studies indicated that participants successfully applied correct fermentation techniques and improved waste management methods. Additionally, some participants achieved halal certification, positively impacting their product operations and marketing. Case studies and literature demonstrate that processing cattle waste into liquid organic fertilizer can enhance soil fertility and crop yields, while reducing environmental pollution and greenhouse gas emissions. The training not only provided economic benefits by opening new business opportunities but also raised environmental awareness among participants, fostering a more caring and proactive community in maintaining environmental cleanliness and health.

Study on the key influencing factors of KOH-catalyzed coal pyrolysis for direct preparation of carbon nanotubes

The environmental pollution and greenhouse gas emission caused by the traditional utilization of coal such as combustion, coking and gasification are becoming increasingly apparent. Green and environmentally friendly coal utilization technology is an effective way to solve this problem. In this study, high-value carbon nanotubes (CNTs) were directly prepared from coal by catalytic pyrolysis with low KOH content. It was found that when the KOH additive amount was 50 wt%, the influence of three main factors on the preparation of CNTs was as follows: pyrolysis temperature＞residence time＞heating rate. Pyrolysis temperature of 900 °C, heating rate of 15 °C/min, and residence time of 60 min were the best combination of KOH-catalyzed coal pyrolysis to prepare CNTs, and the content of CNTs in the corresponding sample was 10.01 wt%. This study has a specific contributes to the high-value transformation and utilization of coal resources and the preparation of CNTs.

Life cycle assessment and comparison of energy supply system technical innovation: A case study

As the key sector of energy consumption in China, the industrial sector contributes the most to environmental pollution and CO2 emissions. With the goals of reaching the peak of CO2 emissions by 2030 and achieving carbon neutrality by 2060, optimizing the energy supply system of industrial enterprises is significant to achieve low-carbon development. In this study, the case of system upgrading concerning waste heat utilization in a manufacturing unit is applied. The total environmental impact of the energy supply system before and after transformation is quantified and compared based on life cycle assessment method, with “cradle to gate” as the system boundary and one year of system operation as the functional unit. It can be found that the environmental impact of the energy supply system is reduced from 4.54 to 4.14 through technical innovation. The key processes contributing to the environmental impact of the system are the refrigeration system, soft water system and boiler system. Electricity consumption of refrigeration system, NaCl of the soft water system and natural gas of the boiler system are identified as key substances. Sensitivity analysis reveals that the environmental benefits of reducing electricity consumption will be more effective than that of NaCl and natural gas. With the transformation of waste heat utilization and the increase of photovoltaic power generation, the environmental impact of the system is reduced obviously, which is significant for the low-carbon transformation of the manufacturing industry.

Optimization of engine performance, emission and combustion parameters by using mixed nonedible oil biodiesel with nano-additives using hybrid techniques

The current study is focused on three nonedible oils resource such as Ceiba pentandra, Mahua longifolia, and Azadirachta indica mixed together in a specific proportion for biodiesel production. The produced biodiesel serves as an alternative fuel source for operating a variable compression ratio diesel engine, addressing escalating environmental pollution and stringent emission standards. A nano-additive comprising CaO–TiO2 is incorporated into biodiesel blends to enhance engine performance and mitigate emissions. The matrix undergoes experimentation and validation using Box-Behnken Design, Deep Belief Network, and a hybrid DBN-based Arithmetic Optimization Algorithm to optimize engine parameters for achieving higher brake thermal efficiency, lower emission rates, and reduced brake-specific fuel consumption. All the experiments are conducted by varying the engine load, speed, quantity of nano-additives and biodiesel blend. The final empirical model is more significant for DBN with a regression coefficient greater than 0.99. The converged optimized input parametric ranges are load 60 %, biodiesel 25 %, nano-additive 20 wt% and engine speed 1400 rpm. When comparing diesel fuel with CaO–TiO2 biodiesel, the proposed method resulted in significant improvements, including a 41 % reduction in brake-specific fuel consumption, a 32 % decrease in CO emissions, a 25 % decrease in NOX emissions, and a 16.9 % increase in brake thermal efficiency.

Collaborative management of environmental pollution and carbon emissions drives local green growth: An analysis based on spatial effects

Collaborative management of environmental pollution and carbon emissions (CMPC) has been a major policy instrument to promote Sustainable Development Goals (SDG) in recent years. However, the relationship between the benefits and drawbacks of this environmental management practice for green growth in and around a local area remains to be clarified. Using 30 provinces in China during 2001–2019 as the object of analysis, we assessed the efficiency of local CMPC practices using the nonradial directional distance function (NDDF) model, predicted local green growth using the frontier green complexity index (GCI), and empirically examined the spatial effects, locational heterogeneity, and threshold characteristics of the relationship using the spatial Durbin model and the panel threshold model. Our study finds that although efficient CMPC does drive local green growth, the promotion effect is nonlinear with decreasing marginal effect. This effect is particularly obvious in economically developed regions with higher CMPCs, which will absorb resources from neighboring regions and create a "siphoning" effect. It was found that local financial support and foreign direct investment (FDI) can radiate green growth to neighboring regions; therefore, CMPC practice needs to pay more attention to the effect of joint governance, supplemented by financial and foreign investment policy tools, to better promote the green transformation of local economy.

탄소중립을 위한 순환자원 활용 시설재료의 성능분석

As the climate crisis and global environmental problems intensify, policies and technologies for reducing greenhouse gas in industry and life are being emphasized, and the development of eco-friendly synthetic materials with low environmental load while reinforcing the performance of natural materials with building or facility materials is becoming a useful strategy for industrialization of greenhouse gas reduction as well as technical aspects. This study was conducted to present basic data for using coffee ground, a circulating resource, as a material for synthetic wood. The possibility of using the leftover coffee grounds as an alternative facility to reduce the environmental load such as carbon emissions was confirmed by producing it as a synthetic deck material through a drying processing process. It was classified into Type I (50% coffee grounds), Type II (20% coffee grounds), and a control, and the quality suitability and performance with KS standards were verified when the content rates of coffee grounds and wood were different. Compared to KS standards (KSF 3230), the performance of synthetic wood deck materials that recycled coffee grounds satisfied the standards under all three types of experimental conditions, and in particular, it was found to be the best in Type I, which mixed coffee grounds ingredients and wood at a 50% ratio. Coffee grounds, which are circulating resources other than household waste, can be alternatives as sustainable materials with excellent performance that meets quality standards while minimizing environmental pollution or carbon emissions.

Stability Investigation of Fully Recycled Support System of Steel-Pipe-Anchored Sheet Pile in Soft Soil Excavation

As a temporary project, the supporting system of excavation often encounters issues such as the waste of support components, environmental pollution, and high carbon emissions. This article presents a foundation pit support technology that utilizes steel tube anchorage sheet piles, which can be assembled and fully recycled. The composition of the support system is also introduced. Furthermore, a large-scale model test of steel-pipe-anchored sheet piles was designed and implemented. The displacement of each component of system and stability during excavation were investigated using 3D finite element modeling and analysis. The study results indicate that the deformation and failure mode of the model foundation under the steel-pipe-anchored sheet pile support system are closely related to the distance between the pipe pile and the sheet pile. When the distance is 10 cm, both the pipe pile and the sheet pile tilt simultaneously. When the distance is approximately 30–50 cm, the sliding surface becomes exposed from the position of the pipe pile. At distances up to 100 cm, the sliding surface is exposed between the pipe pile and the sheet pile. The anchoring effect of pipe piles and tie rods can effectively reduce the horizontal displacement of the sheet pile itself. The horizontal displacement at the top of both the pipe pile and sheet pile remains consistent throughout the excavation period of this model foundation. During excavation, measured earth pressure on the sheet pile is less with theoretical active earth pressure. After excavation, the maximum horizontal displacement of the top of the pipe pile exhibits a hyperbolic relationship with excavation depth.

Experimental study of biological wastewater recovery using microbial fuel cell and application of reliability and machine learning to predict the system behavior

Today, the water crisis has necessitated wastewater recovery management more than ever. With the advancement of technology and the emergence of microbial fuel cells (MFCs), wastewater treatment has become an exceptional opportunity for electricity production. In the present work, an experimental study has been carried out for the possibility of treating the wastewater of Borujerd textile factories in a period of ten days using an MFC. In order to save time and costs for experimental studies, the reliability analysis has been used to predict the behavior of fuel cells made in simple mode and multi-anode shared cathode mode. In addition, in order to evaluate the performance of MFCs that are made at the experimental level, deep learning has been used to extract comprehensive relationships. Finally, the economic and environmental evaluation of the simple and multi-anode shared cathode MFC has been done. The research results show that the COD removal efficiency in the system constructed for textile wastewater is 73 %, while the constructed fuel cell maximum power density is 281.5 mW/m2 from wastewater recycling. Reliability analysis of the studied system shows that adding anode to the MFC increases its operational life so for a fuel cell with 6-anodes, the life of the fuel cell increases by approximately 74 days. But in the design of an MFC, it is necessary to pay attention to the cost and emission of environmental pollutants, because the increase of the anode increases the costs and emission of environmental pollutants so that the built fuel cell will function in the most optimal way possible.

Application of mushrooms as a pollutant remediator

From the Industrial Revolution, at the end of the 19th century and the beginning of the 20th century, there was a significant impact on the environment due to increased emission of environmental pollutants. This problem has seen considerable growth in recent years due to population growth, resulting in further ecosystem changes due to human action. Furthermore, demands for water, electricity, and food have led to increasingly large concentrations of waste being emitted. In this context, bioremediation is an up-and-coming biotechnological alternative to combat the growing emission of pollutants into the environment. From this perspective, basidiomycetes, popularly known as mushrooms, are an effective tool for remediating environmental pollutants. These fungi use different mechanisms in bioremediation processes, such as biodegradation, biosorption, bioaccumulation, and bioconversion. Currently, the remediation potential of mushrooms has been increasingly studied. Therefore, this bibliographic review aims to analyze the literature on the potential of mushrooms in pollutant remediation. At the end of this analysis, it is concluded that macrofungi are a very effective and promising tool for suppressing the emission of environmental pollutants.

Exploring the Mechanisms of Regional Environmental Collaborative Legislation in China: Policy Effectiveness, Practical Challenges, and Policy Suggestions

The legislation for regional environmental collaboration is of significant importance in enhancing the effectiveness of environmental protection. The existing literature focuses on the power struggle between central and local governments regarding environmental regulation within the realm of regional environmental governance, lacking an examination of the collaborative governance mechanisms and their effectiveness. Therefore, this study takes China’s regional environmental collaborative legislation as its research object. It employs a difference-in-differences model to test the effectiveness of regional environmental collaborative legislation concerning environmental governance and conducts a qualitative analysis to examine the current practical challenges facing regional environmental collaborative legislation. The quantitative analysis results indicate that regional environmental collaborative legislation can effectively suppress the emission of environmental pollutants. Specifically, the implementation of regional environmental collaborative legislation results in a 19.7% reduction in prefecture-level wastewater emissions and a 26.6% reduction in sulfur dioxide emissions. Qualitative analysis results show that regional environmental collaborative legislation currently faces challenges such as localism, difficulties in legislative authority allocation, and a lack of cooperation mechanisms. Therefore, this paper proposes to establish a collaboration platform, balance the interests of stakeholders, and improve the allocation mechanism of environmental regulatory powers in order to better optimize the regional environmental collaborative legislation and enhance the government’s environmental governance capacity.

Environmental Management Technologies, Environmental Policy Stringency, Energy Productivity and Pollution Emission: Fresh Evidence from Indonesia under STIRPAT Framework

The rapid pace of climate change and global warming has become an ever growing challenge all over the world. Global warming and carbon concentrations can be mitigated by adopting strict environmental policies and effective management of the environment. Therefore, the study aims to empirically investigate the effect of environmental policy stringency (EPS), energy productivity and environmental management technologies (EMT) on pollution emission in Indonesia- one of the most polluting countries of the world. To this end, the study collects data over the 1990 to 2020 period. The study uses Autoregressive Distributed Lag Model (ARDL) approach to carry out empirical estimation. The findings reveal that environmental management technologies, energy productivity and environmental policy stringency had negative impact on CO2 emission. However, economic growth (GDP) and urbanization had positive role in increasing CO2 emission in the long run and the short run. On the basis of the outcomes, the study recommends that Indonesia should adopt strict environmental policies and legislations to mitigate environmental deterioration. Indonesian government is recommended to promote the adoption of environmental management technologies by providing substantial incentives and investment opportunities for businesses.

How does digital transformation affect the emissions of environmental pollutants? From the perspective of nonlinear nexuses

How does digital transformation affect the emissions of environmental pollutants? From the perspective of nonlinear nexuses

Sustainable management of land use patterns and water allocation for coordinated multidimensional development

The sustainable and integrated management of resources is a crucial approach to achieving sustainable regional development in the face of limited land and increasingly scarce water resources. This paper proposes a multidimensional optimization model to jointly optimize land use patterns and water resource allocation under the conditions of maximizing economic benefits and minimizing social differences, ecological loads, environmental pollution, and carbon emissions. The optimization model is solved using the affiliation function method and then combined with random forest (RF) and cellular automata (CA) models to further obtain the optimal spatial layout of land use. This paper takes the Mid-Yangtze River City Cluster as an example and optimizes the land use pattern and water allocation in the region in 2020 and 2030. The results of the study show that the optimized water and land resource allocation scheme performs better than the status quo in all dimensions. The optimized economic benefits, social effects, ecological effects, environmental effects, and overall sustainability in 2020 are increased by 45.97%, 22.89%, 10.07%, 24.65%, and 42.73%, respectively. By 2030, overall sustainability reaches 0.69. The developed modeling framework helps to elucidate the internal linkages between land use and water allocation, and it provides decision-makers with diversified approaches to land and water resource management and adjustment for different cities in different periods, which promotes the sustainable development of urban agglomerations.

A novel heating strategy and its optimization of solar–air source heat pump heating system for rural buildings in northwest China

In the rural areas of Northwest China, the utilization of clean and renewable energy is deemed a crucial measure for reducing building energy consumption and environmental pollutant emissions. This paper focuses on constructing a simulation platform for a solar-assisted air source heat pump heating system. A rural residential building in Yongshou County, Shaanxi Province, serves as an illustrative example. A novel flexible temperature control method with a feedback controller in sub-area and period is proposed in this paper, alongside the selection of three distinct objective functions aimed at optimizing the heating system. The simulation results indicate an average temperature of 17.0 °C throughout the heating cycle, with a peak temperature of 18.7 °C. Moreover, the solar fraction is measured at 25.11%, underscoring the significance of collector area and heat storage tank volume as primary factors in system design. The results also demonstrate that across various optimization objectives, the life cycle cost optimization scheme yields greater economic benefits, while the target building unit heating cost optimization scheme boasts the shortest static payback period and lowest unit heating cost. Conversely, the solar fraction optimization scheme stands out for its superior environmental benefits. These findings offer valuable insights for the design of heating systems tailored to diverse objectives.

High-performance gas sensor utilizing g-C3N4/In2O3 composite for low concentration prediction to NO2

The demand for gas sensors is experiencing rapid growth, driven by the increasing need for air quality detection in the face of environmental pollution and industrial emissions. However, the widely used metal oxide semiconductor (MOS) gas sensors suffer from drawbacks such as low ability to predict gas concentration and poor selectivity. In this work, a sensor array was fabricated consisting of 10 various gas sensors and combined with an advanced deep learning algorithm to achieve precise predictions of nitrogen dioxide (NO2) at low concentrations. First, graphitic carbon nitride (g-C3N4) and In2O3 nanoparticles were composited with different mass ratios, resulting in the formation of distinct g-C3N4/In2O3 composites as sensing materials. Afterward, SEM, TEM, and XRD were employed to characterize the morphology, structure, and elemental composition of the samples. Furthermore, sensing properties including response, selectivity, and repeatability, are studied for 10 gas sensors based on g-C3N4/In2O3 composites. Finally, the convolutional neural network-efficient channel attention-gate recursive unit (CNN-AGRU) model was proposed to analyze the patterns of the signals collected from the sensor array when exposed to various NO2 concentrations from 1 to 9 ppm. The results demonstrated the integration of high-selectivity sensing materials to NO2 and an advanced deep learning algorithm CNN-AGRU enables to realize a high concentration prediction accuracy of about 97.04% and a low prediction error of 0.20527 ppm for NO2 gas.