Environmental Assessment Model Research Articles

Different Sensitivity of Flower-Visiting Diptera to a Neonicotinoid Insecticide: Expanding the Base for a Multiple-Species Risk Assessment Approach.

Insects play an essential role as pollinators of wild flowers and crops. At the same time, pollinators in agricultural environments are commonly exposed to pesticides, compromising their survival and the provision of pollination services. Although pollinators include a wide range of species from several insect orders, information on pesticide sensitivity is mostly restricted to bees. In addition, the disparity of methodological procedures used for different insect groups hinders the comparison of toxicity data between bees and other pollinators. Dipterans are a highly diverse insect order that includes some important pollinators. Therefore, in this study, we assessed the sensitivity of two hoverflies (Sphaerophoria rueppellii, Eristalinus aeneus) and one tachinid fly (Exorista larvarum) to a neonicotinoid insecticide (Confidor®, imidacloprid) following a comparative approach. We adapted the standardized methodology of acute contact exposure in honey bees to build dose-response curves and calculate median lethal doses (LD50) for the three species. The methodology consisted in applying 1 µL of the test solution on the thorax of each insect. Sphaerophoria rueppelli was the most sensitive species (LD50 = 10.23 ng/insect), and E. aeneus (LD50 = 18,176 ng/insect) the least. We then compared our results with those available in the literature for other pollinator species using species sensitivity distribution (SSD). Based on the SSD curve, the 95th percentile of pollinator species would be protected by a safety factor of 100 times the Apis mellifera endpoint. Overall, dipterans were less sensitive to imidacloprid than most bee species. As opposed to most bee species, oviposition and fecundity of many dipteran species can be reliably assessed in the laboratory. We measured the number of eggs laid following exposure to different insecticide doses and assessed the potential trade-off between oviposition and survival through the sublethal sensitivity index (SSI). Exposure to imidacloprid had a significant effect on fecundity, and SSI values indicated that oviposition is a sensitive endpoint for the three dipteran species tested. Future studies should integrate this information related to population dynamics in simulation models for environmental risk assessment.

Does the new energy vehicles subsidy policy decrease the carbon emissions of the urban transport industry? Evidence from Chinese cities in Yangtze River Delta

New energy vehicles (NEV) have become an important driving force for carbon reduction in the transportation industry. This paper adopts the extended environmental pressure assessment (STIRPAT) model and the time-varying difference in differences (DID) model to evaluate the effectiveness of the NEV subsidy policy to achieve sustainable governance. The results show that the NEV subsidy policy can significantly decrease the carbon emission of the transport industry. The mechanism analysis results indicate that the NEV subsidy policy can decrease carbon emissions by promoting a green transformation of the consumer car purchasing structure. Further analysis found that a “fraudulent subsidy” can significantly weaken the policy effect of subsidies. The results of heterogeneity analysis indicate that the subsidy policies introduced by different levels of government have different effects. The subsidy policy of the central government has a more significant effect, and repeated subsidies from central and local governments will weaken the policy's effectiveness. These findings provide valuable insights for policymakers in developing countries to optimize subsidies for new energy vehicles in reducing carbon emissions in the transportation industry.

A high-quality chromosome-level genome assembly of the Chinese medaka Oryzias sinensis

Oryzias sinensis, also known as Chinese medaka or Chinese ricefish, is a commonly used animal model for aquatic environmental assessment in the wild as well as gene function validation or toxicology research in the lab. Here, a high-quality chromosome-level genome assembly of O. sinensis was generated using single-tube long fragment read (stLFR) reads, Nanopore long-reads, and Hi-C sequencing data. The genome is 796.58 Mb, and a total of 712.17 Mb of the assembled sequences were anchored to 23 pseudo-chromosomes. A final set of 22,461 genes were annotated, with 98.67% being functionally annotated. The Benchmarking Universal Single-Copy Orthologs (BUSCO) benchmark of genome assembly and gene annotation reached 95.1% (93.3% single-copy) and 94.6% (91.7% single-copy), respectively. Furthermore, we also use ATAC-seq to uncover chromosome transposase-accessibility as well as related genome area function enrichment for Oryzias sinensis. This study offers a new improved foundation for future genomics research in Chinese medaka.

Environmental risk assessment and management of nuclear power plants based on big data analysis

In traditional research, monitoring data and samples are limited, and it is difficult to achieve ideal results in real-time monitoring and rapid response to environmental risks. By leveraging extensive environmental data gathered from nuclear power plants, the research employed machine learning methodologies for accurate feature selection and extraction of environmental parameters. An efficient environmental risk assessment model was successfully established by using a random forest algorithm. The 95% confidence interval for the area under the curve value spanned from 0.6894 to 0.9292. This provided a more dynamic and effective means for assessing and managing the environmental risks of nuclear power plants.

Unveiling the Spatial-Temporal Characteristics and Driving Factors of Greenhouse Gases and Atmospheric Pollutants Emissions of Energy Consumption in Shandong Province, China

As the largest energy-consuming province in China, Shandong faces the dual task of greenhouse gas (GHG) reduction and atmospheric pollution control. Based on the latest activity data and updated emission factors, this study establishes a high-resolution emission inventory (5 km × 5 km) for GHGs and main atmospheric pollutants from the energy consumption sectors of Shandong Province from 2010 to 2021, quantifies the relationship between social economic factors and GHGs and atmospheric pollutants emissions using the expanded stochastic environmental impact assessment (STIRPAT) model, and forecasts the future emission trend with the help of the scenario analysis method. Results indicate that the electricity and transportation sectors are the main contributors to all pollutants. Spatially, the high value of pollutants is mainly concentrated in the urban agglomerations of central and eastern Shandong. Up to 72% of GHGs and 50% of air pollution emissions are attributed to the top 10% of emission grids. Emission peaks occur mainly in summer and winter due to straw burning, increased utilization of temperature-controlled facilities, and expansion of plant capacity. Population, energy consumption, the proportion of secondary industry, and energy consumption intensity are the most significant influencing factors for pollutant emissions. Scenario analysis results indicate Shandong province can reach its carbon peak in 2027 without sacrificing population growth or economic progress.

The use of integrative tools and multiple models for aquatic environmental quality assessment: a case study of the Mirim Lagoon, Southern Brazil.

This study performed toxicity assays with microalgae, microcrustaceans, and fish as well as evaluated biochemical and behavioral biomarkers in fish and microcrustaceans to assess the quality of the surface water of Mirim Lagoon, which belongs to one of the largest hydrographic basins in the world, located in southern Brazil. Three distinct sampling periods were chosen (January, March, and June 2022) based on the rice plantation dynamics which is the main activity surrounding the lagoon. In January, the plantation is irrigated; in March, the water is drained into the Mirim Lagoon, and July is the off-season. Concerning toxicity tests, there was significant inhibition in microalgae growth when exposed to water collected in March, but no mortality was observed for Ceriodaphia dubia, Daphnia magna, and Danio rerio. Regarding biomarkers, behavioral variables contributed more to the higher values of the Integrated Biomarker Response (IBR) index for both D. magna and D. rerio, in March. The Redundancy Analysis (RDA) indicated a correlation between the biomarkers for both organisms and abiotic parameters, mainly nutrients (total phosphorus and total nitrogen), thermotolerant coliforms, total solids, and turbidity. Spatially, there was no difference during monitoring, but the most significant ecotoxicological effects were observed in March. Multivariate analysis and the IBR index proved to be useful tools for monitoring of water bodies such as Mirim Lagoon.

Computational Nanotoxicology Models for Environmental Risk Assessment of Engineered Nanomaterials.

Although engineered nanomaterials (ENMs) have tremendous potential to generate technological benefits in numerous sectors, uncertainty on the risks of ENMs for human health and the environment may impede the advancement of novel materials. Traditionally, the risks of ENMs can be evaluated by experimental methods such as environmental field monitoring and animal-based toxicity testing. However, it is time-consuming, expensive, and impractical to evaluate the risk of the increasingly large number of ENMs with the experimental methods. On the contrary, with the advancement of artificial intelligence and machine learning, in silico methods have recently received more attention in the risk assessment of ENMs. This review discusses the key progress of computational nanotoxicology models for assessing the risks of ENMs, including material flow analysis models, multimedia environmental models, physiologically based toxicokinetics models, quantitative nanostructure-activity relationships, and meta-analysis. Several challenges are identified and a perspective is provided regarding how the challenges can be addressed.

Environmental resource assessment model design based on fuzzy control algorithm and GIS technology

Environmental resource assessment model design based on fuzzy control algorithm and GIS technology

Environmental surveillance in Jinan city of East China (2014–2022) reveals improved air quality but remained health risks attributable to PM2.5-bound metal contaminants

PM2.5-bound metal contaminants are associated with multiple chronic diseases in human. At global level, the contamination status has not been well controlled yet. Here we report findings from a long-term air pollution surveillance in Jinan city of Shandong, China. During 2014–2022, the dynamics and trends of PM2.5-bound heavy metal contaminants were monitored in an industrial area and a downtown area. The surveillance targets included: antimony (Sb), aluminum (Al), arsenic (As), beryllium (Be), cadmium (Cd), chromium (Cr), mercury (Hg), lead (Pb), manganese (Mn), nickel (Ni), selenium (Se). The human exposure and health risks were calculated and we found that the health risks of most contaminants showed peak values in autumn and winter. But Al, Mn, Hg and Be were found to result in highest health risk in spring or summer in the downtown area. In the industrial area we identified 100% alarming health index >1 (ranged from 1.12 to 3.35) in autumn and winter. In winter the total non-carcinogenic HI was all above 1 (peak value 2.21). Mn and As together posed >85% non-carcinogenic risk. As and Cd were ranked as major drivers of carcinogenic risks (5.84 × 10−6 and 2.78 × 10−6). Pd and Cd both showed non-negligible environmental levels but risk assessment model for their air-exposure associated non-carcinogenic risks are not yet available. This study updates air pollution data and status for air pollution status in China. This study provides valuable 9 year long-term reference to experimental and field studies in the related fields.

ENVIRONMENTAL FLOW ASSESSMENT MODEL ON SUSTAINABILITY PLANNING STRATEGIES, KENYIR LAKE BASIN, MALAYSIA

The study presents the Environmental Flow Assessment (EFA) model on sustainability planning strategies to reduce damage in the main area of Kenyir Lake Basin. The XPSWMM model have been used to simulate the EFA in this study. Based on simulation in the Terengganu River, which has a most effective discharge of 42.78 m3/s with depth on 3.94 m and a water velocity of 0.54 m/s, which are expected to meet the development needs of fish species, the analysis for both study rivers found the minimum river discharge values with the frequency probability in the period of 20 years needs to be maintained. While, based to the simulation in the Petuang River, the maximum discharge is only 0.08 m3/s, the maximum depth is 0.4 m, and the maximum water speed is 0.04 m/s, which is adequate for a small number of small-sized fish species. With output deficiency of less than 20% from an actual situation, the two lowest values later obtained were adopted as input in low flow analysis. A more effective management approach ensures the ecosystem's sustainability and maintains an optimal equilibrium among the many uses. Environmental flows aren't considered a luxury but instead an integral component of contemporary water management given the global misuse of water resources and the resulting degradation of ecosystems and their functions. It is a strategy that requires widespread adoption.

Techno-economic and environmental evaluation of a supercritical CO2 coal-fired circulating fluidized bed boiler power generation

Replacing the steam cycle with the supercritical CO2 (S–CO2) cycle applied in coal-fired power generation is a demonstrated approach to greatly improving efficiency and flexibility. This promotes carbon reduction through efficient use of fossil fuels and improving utilization rate of renewable energy by deep peak shaving. Unlike most studies focusing on conceptual design and efficiency-based investigation, the techno-economic and environmental performance evaluations of the S–CO2 power generation are still rare and undiscovered. In this paper, techno-economic and environmental investigation of a 600 MW S–CO2 coal-fired circulating fluidized bed (CFB) boiler power plant is firstly considered. During this process, a series of economic cost and environmental assessment models and methods integrated with process simulation were proposed. The results showed that there exits an optimum turbine inlet temperature of 635 °C from the techno-economic perspective. The total cost of the S–CO2 power plant increases by ∼10 % and the cost of electricity (COE) decreases by 4.6 % compared to the same-capacity steam plants. The life cycle assessment (LCA) environmental impact potential of the S–CO2 power is far less compared to steam power plants. Its environmental impact is greatest on a global scale and relatively low on a regional scale, such as a country or region.

Retracted: Construction of College English Teaching Environment Assessment Model Based on BP Neural Network and Multiple Intelligence Theory.

[This retracts the article DOI: 10.1155/2022/9479755.].

An analysis approach for building collapse accident using system thinking approach and SEA model

The frequent occurrence of building collapse accidents not only causes significant casualties, but also jeopardizes local economies. This paper adopts a combinatory assessment approach to showcase the lessons learned from a recent building collapse in Changsha, China. The proposed approach blends the system thinking approach and strategic environmental assessment (SEA) model. It delineates the causes of collapse and provide key leverage points for safety management. The results show that the primary causes for the collapse are the poor construction quality, illegal alterations, and lack of regulations enforcement. The management of rural housing construction in Hunan Province achieved a total score of 4 out of 30. It was also determined that the key prevention measures for abating these deleterious phenomena involve ensuring quality assurance/quality control, efficiently assessing safety risk, and timely performing structural health monitoring. This study is bound to enhance the understanding of collapse accidents and foster the achievement of sustainable cities and communities.

Building envelopes with radiative cooling materials: A model for indoor thermal environment assessment based on climate adaptation

To create a comfortable thermal environment in buildings, building cooling account for a large part of building energy consumption in summer. The spectral radiative properties of radiant cooling materials as a passive cooling technology have been extensively studied. However, there are few studies that address the application of radiant cooling materials to building envelopes. This paper proposed a radiative cooling glass composite structure for windows based on existing radiant cooling materials and established a climate adaptive radiant cooling building indoor thermal environment assessment model. This assessment model combines the spectral selectivity of radiative cooling materials with climate characteristics. An indoor thermal environment test system and an ambient climate measurement system are designed under the influence of external windows, and the average error of the assessment model is verified to be no more than 4.83%. Based on this assessment model, three applicability analyses were conducted: Firstly, it is concluded that the daytime indoor temperature with radiative cooling glass (RCG) is 26.43°C lower than that with the ordinary glass. Secondly, RCG can effectively improve the indoor thermal environment for rooms facing each direction, and the indoor temperature is 45.06°C lower than that of ordinary glass in the east and west directions, and 15.05°C lower than that of ordinary glass in the north and south directions. Finally, analysis of the correlation between indoor temperature and outdoor temperature shows that the indoor temperature tends to rise as the outdoor temperature rises. The analysis of the application of RCG in different cities shows that the performance of radiative cooling is relatively weak in areas with high relative humidity.

Construction of a carbon neutral enterprise environmental performance assessment model based on transformer-GRU

IntroductionCarbon-neutral enterprise environmental performance assessment is an important method for evaluating the impact and benefits of enterprises on the environment during the process of achieving carbon neutrality. This paper proposes a method for evaluating the environmental performance of carbon-neutral enterprises using the Transformer-GRU model.MethodsThe proposed method combines the Transformer and GRU models to accurately predict and analyze the environmental performance of carbon-neutral enterprises. The Transformer model is used to extract features, and the GRU model is used for sequence modeling, which improves the model's prediction accuracy and generalization ability. The method is validated using actual enterprise data for experimental verification.ResultsThe experiments show that the proposed method has significant practical significance in evaluating the environmental performance of carbon-neutral enterprises. The method accurately predicts and analyzes the enterprise's carbon emissions, energy consumption, wastewater and gas discharge, and solid waste treatment.DiscussionThe proposed method provides a new approach for evaluating the environmental performance of carbon-neutral enterprises. The combination of the Transformer and GRU models can effectively improve the accuracy and generalization ability of the model. The method can be used to help enterprises evaluate their environmental performance and make decisions to achieve carbon neutrality.

Estimating the environmental impacts of backup generation after power outages: A case study of China

Backup generators (BG) are indispensable to address the potential electricity security risks caused by extreme weather, cyber attack and infrastructure failure. Diesel generators, the major BG component, are more polluting than grid electricity, which are in the blind spot of environmental regulation and statistics. To contribute to better environmental policies for the electricity sector, this study estimates the environmental impacts of backup generation in China. A BG capacity evaluation model is firstly developed based on the safety design rules of different buildings. Then, an environmental cost assessment model is constructed to quantify the impacts of pollutant emissions from BG after power outages. At last, this paper uses an improved Monte Carlo method to re-examine the estimated results considering multiple uncertain factors and analyzes their contributions to the total cost variance. Our major findings are: (1) The estimated total BG capacity is 169.46 GW in 2020, representing 7.70% of the total generation capacity in China. (2) The environmental cost of BG generation is 6.60 billion yuan in 2020. (3) Sichuan and Hubei suffer the highest environmental impacts at the provincial level.

Carbon footprint of residents' online consumption in China

Although China boasts the largest online consumption market, there has been no prior case study addressing the carbon footprint of online consumption. The rapid expansion of online consumption has posed a challenge to China's carbon neutrality pledge. This paper aims to fill this crucial gap by conducting a pioneering study based on survey data collected from 6000 households. To achieve this goal, this study has combined provincial Multi-Regional Input-Output (MRIO) tables with residents' online consumption calculated by the Non-Linear Optimization model, and applied the Environmental Input-Output Life Cycle Assessment (EIO-LCA) model to calculate the carbon footprint of residents' online consumption. Result indicated that the average carbon footprint of residents' online consumption was 0.46 tCO2e in 2016, accounting for 12.30% of the total consumption carbon footprint. Notably, high-emission regions include Beijing-Tianjin, Jiangsu-Zhejiang-Shanghai, and Hubei. Moreover, the dominant sources of the online consumption carbon footprint were electricity, food, clothing, and beauty products. Furthermore, we found that the carbon footprint of online consumption tends to increase with income, with differential income elasticities observed for various products and income groups. We also quantified the average expenditure-based life-cycle carbon coefficient for parcel delivery (0.22 kgCO2e/yuan) and conducted two scenario analyses to assess its impact. From a policy perspective, our research on measuring the carbon footprint of residents' online consumption can provide valuable insights for designing future policies and decisions related to e-commerce and key sectors along the supply chains. Additionally, it will further encourage Chinese residents to adopt low-carbon lifestyles.

Carbon footprints in pork production and consumption in China from 2005 to 2020

Livestock farming accounts for 14.5% of global total anthropogenic greenhouse gas (GHG) emissions. China has been a major contributor to global GHG emissions from livestock and is the biggest pork producer and consumer worldwide. However, those factors driving GHG emissions from pork production and consumption in China have not been thoroughly assessed. Here, we used the Global Livestock Environmental Assessment Model (GLEAM) and the Logarithmic Mean Divisia Index (LMDI) method to identify and assess the major drivers contributing to the life-cycle carbon emissions embodied in China's pork production and consumption from 2005 to 2020. Our results show that CO2 emissions accounted for 99% of the total GHG emissions in the pig industry, primarily released from the processing and transporting of pig feed. These two sectors contributed more than 90% to the total CO2 emission. CH4 was mainly emitted from enteric fermentation and manure management of pigs, which accounted for a tiny portion of total carbon emissions in the pork industry. Among the primary factors driving pork-induced carbon emissions in China, the reduction of pork emission intensity (PPE) significantly slowed down growing carbon emissions, attributed to the improvements in pork production technology and the promotion of green farming. Our finding reveals that the growing population primarily contributed to elevated carbon emissions before 2015 due to increasing demands for pork meat. Since 2015, the rapid growth of the aged population in China has decreased pork consumption capacity and carbon emissions from pork consumption. The result indicates, for the first time, that the population aging in China, the largest pork consumer in the world, would play a vital role in reducing pork consumption-induced carbon emissions. Such an effect would become more significant in the future, along with the growing aged population in China, favoring the country's GHG emission mitigation increasingly.

The economic feasibility and life cycle carbon emission of developing biomass-based renewable combined heat and power (RCHP) systems

The utilization of biomass resources is considered a viable solution for addressing energy supply scarcity and reducing greenhouse gas emissions. Miscanthus is a type of energy crop with very low planting cost and high calorific value. Using miscanthus for combined heat and power (CHP) production can be a promising option for clean energy production. In this work, a detailed techno-economic analysis and life-cycle environmental assessment model were built for developing the Renewable CHP (RCHP) using miscanthus in central China. The integrated benefits of biochar were also investigated under different utilization pathways, such as heat supply (HS), soil amendment (SA), and activated carbon (AC). Under a capacity of 5 t/h dried miscanthus, the highest overall efficiency of the system was found to be 79.9%, and the optimal power selling price was calculated as 0.367 CNY/kWh with a desirable profit margin. Sensitivity analysis indicated that reducing capital costs and increasing annual power generation could maximize project viability. In addition, the life-cycle analyses showed the optimal net emission and fossil energy intensity of the system were −79.91 kgCO2e/MWh and 791.33 MJ/MWh, indicating a satisfactory carbon fixation capacity.

Radiological Impact Assessment of Acute Tritium Releases in Environment—A Soil Dynamic Model

Radiological and environmental impact assessment models are important tools that support nuclear safety. The present study summarizes the upgrades of a research-grade model (CROPTRIT) with an emphasis on a soil submodel and the balance between air-to-plant and soil-to-plant pathways, together with the needs that must be accomplished by an operational model in order to be applied to nuclear facilities involving large tritium loads.