衡阳市区和衡山背景站臭氧浓度变化规律的对比分析

选取衡阳市区和衡山背景站臭氧自动监测数据,分析两地的臭氧污染特征。对空气质量的优良率情况、臭氧作为首要污染物的变化情况、臭氧浓度的日变化特征、典型时段的浓度变化特征、臭氧浓度的月际变化特征和臭氧与PM_(2.5)的关联情况等进行了分析。结果表明,多云及阴雨天气时,衡阳市区的臭氧浓度日变化幅度大于衡山背景站。夏季,衡阳市区和衡山背景站的臭氧浓度的日变化特征规律差异较大,臭氧浓度分布比较分散,前者为典型的单峰形,后者则波动平缓。冬季,日变化幅度不大,但衡阳市区的臭氧浓度明显低于衡山背景站。衡山背景站和衡阳市区的臭氧基本同步变化,但日均值高于衡阳市区。     

Institutional quality,financial development and sustainable economic growth among lower income countries

This article postulates strong endogenous relationships in lower income countries between institutional quality, financial development and sustained economic growth. These associations were investigated using the vector-error correction model (VECM) and Granger causality method for a sample of 79 countries from 2005 to 2022. The findings show that (1) these variables reinforce each other in the short run. (2) In the long run, both institutional quality and financial development can fuel economic growth. (3) The positive effect of institutional quality on economic growth is greater than that of financial development. Policy implications of these findings are that careful attention should be paid to co-development policies to enhance the institutional quality and the financial system in these economies. Policies should also consider economic growth strategies to enable sustainable economic growth rates.     

Mitigating Impact of Devils Lake Flooding on the Sheyenne River Sulfate Concentration

Devils Lake is a terminal lake located in northeast North Dakota. Because of its glacial origin and accumulated salts from evaporation, the lake has a high concentration of sulfate compared to the surrounding water bodies. From 1993 to 2011, Devils Lake water levels rose by ~10 m, which flooded surrounding communities and increased the chance of an overspill to the Sheyenne River. To control the flooding, the State of North Dakota constructed two outlets to pump the lake water to the river. However, the pumped water has raised concerns about of water quality degradation and potential flooding risk of the Sheyenne River. To investigate these perceived impacts, a Soil and Water Assessment Tool (SWAT) model was developed for the Sheyenne River and it was linked to a coupled SWAT and CE‐QUAL‐W2 model that was developed for Devils Lake in a previous study. While the current outlet schedule has attempted to maintain the total river discharge within the confines of a two‐year flood (36 m³/s), our simulation from 2012 to 2018 revealed that the diversion increased the Sheyenne River sulfate concentration from an average of 125 to >750 mg/L. Furthermore, a conceptual optimization model was developed with a goal of better preserving the water quality of the Sheyenne River while effectively mitigating the flooding of Devils Lake. The optimal solution provides a “win–win” outlet management that maintains the efficiency of the outlets while reducing the Sheyenne River sulfate concentration to ≤600 mg/L.     

PLS-based EWMA fault detection strategy for process monitoring

Fault detection (FD) and diagnosis in industrial processes is essential to ensure process safety and maintain product quality. Partial least squares (PLS) has been used successfully in process monitoring because it can effectively deal with highly correlated process variables. However, the conventional PLS-based detection metrics, such as the Hotelling's T² and the Q statistics are ill suited to detect small faults because they only use information from the most recent observations. Other univariate statistical monitoring methods, such as the exponentially weighted moving average (EWMA) control scheme, has shown better abilities to detect small faults. However, EWMA can only be used to monitor single variables. Therefore, the main objective of this paper is to combine the advantages of the univariate EWMA and PLS methods to enhance their performances and widen their applicability in practice. The performance of the proposed PLS-based EWMA FD method was compared with that of the conventional PLS FD method through two simulated examples, one using synthetic data and the other using simulated distillation column data. The simulation results clearly show the effectiveness of the proposed method over the conventional PLS, especially in the presence of faults with small magnitudes.     

Research on flow assurance of deepwater submarine natural gas pipelines: Hydrate prediction and prevention

The formation of hydrate will lead to serious flow assurance problems in deepwater submarine natural gas transmission pipelines. However, the accurate evaluation model of the hydrate blocking risk for submarine natural gas transportation is still lacking. In this work, a novel model is established for evaluating the hydrate risk in deepwater submarine gas pipelines. Based on hydrate growth-deposition mechanism, the mathematical model mainly consists of mass, momentum and energy conservation equations. Meantime, the model results are obtained by finite difference method and iterative technique. Finally, the model has been applied in the production of deepwater gas field (L Gas Field) in China, and the sensitivity analysis of relevant parameters has been carried out. The results show that: (a). The mathematical model can well predict the hydrate blockage risk in deepwater natural gas pipelines after verification. (b). Hydrate is easily formed at the intersection of horizontal pipeline and vertical riser, and the maximum blocking position often occurs in middle of the riser. (c). The hydrate blockage degree and length of hydrate formation region (HFR) decrease with the increase of gas transport rate. (d). The hydrate blockage degree and length of HFR decrease with the increase of gas transport temperature. (e). The hydrate blockage degree and length of HFR increase with the extension of horizontal pipeline. (f). Injecting inhibitors can effectively inhibit hydrate formation and blockage, but the improvement of transmission measures can significantly reduce the dosage of inhibitor. It is concluded that measures such as increasing gas transportation rate and temperature, shortening horizontal pipeline length, optimizing inhibitor injection point and injection rate can play a safe, economic and efficient role in hydrate preventing and controlling.     

欧盟空气质量监测现状及加强我国空气质量监测体系建设的建议

从欧盟空气质量监测政策和监测网络建设现状两个方面描述了欧盟空气质量监测发展现状。分析了我国空气污染现状和空气质量监测体系中存在的问题,并借鉴欧盟的经验,提出了加大政策支持和财政保障力度、逐步健全空气质量监测网络体系、加强空气质量监测技术研究、完善空气质量监测数据库、开展能力建设、提高公众参与度等加强我国空气质量监测体系建设的建议。     

Potential of microalgae as biopesticides to contribute to sustainable agriculture and environmental development

The loss of yields from agricultural production due to the presence of pests has been treated over the years with synthetic pesticides, but the use of these substances negatively affects the environment and presents health risks for consumers and animals. The development of agroecological systems using biopesticides represents a safe alternative that contributes to the reduction of agrochemical use and sustainable agriculture. Microalgae are able to biosynthesize a number of metabolites with potential biopesticidal action and can be considered potential biological agents for the control of harmful organisms to soils and plants. The present work aims to provide a critical perspective on the consequences of using synthetic pesticides, offering as an alternative the biopesticides obtained from microalgal biomass, which can be used together with the implementation of environmentally friendly agricultural systems.     

水中藻类对连续流动法测定总氮结果的影响

以天津市河道、水库为研究对象,在藻类增殖期采用连续流动法与碱性过硫酸钾消解法对水体中总氮进行比对监测,同时分析水中藻类分类和藻细胞密度。试验表明:虽然两种方法测定总氮的结果精密度基本相同,但二者之间的系统误差存在显著差异,连续流动法较碱性过硫酸钾消解法的测定结果低5.4%。两种方法测定总氮结果的相对偏差与水体中藻细胞密度呈正相关性,当水体中藻细胞密度﹥2.41×108L-1时,对连续流动法测定总氮的结果产生显著影响,相对偏差超过标准规范要求。     

基于SHERPA的环境空气质量减排情景模拟评估

分析了SHERPA综合评价模型的基本原理和主要建模理念,重点介绍了其在环境空气质量减排情景模拟评估方面的作用,以及在排放源与受体关系(SRR)方面的处理方法,比较了其与欧盟常用的其他情景模拟模型的优缺点。SHERPA模型的特点是空间灵活性较好,对于任何给定地点,可以快速评估不同地区对该研究地点空气质量的影响。SHERPA模型的3个主要功能为污染物来源分析、决策支持和情景模拟。基于SHERPA模型对法国环境空气中PM_(2.5)、PM_(10)和NO_2年均浓度进行污染来源分析、决策支持分析和减排情景模拟评估,展示了模型在环境治理措施优先级筛选和政府间联合治理措施协调建议方面的功能和作用,以期为中国环境空气质量预测预报、环境质量管理措施的制定和成效评估等环境服务与管理工作提供借鉴。     

A multi-path routing-inventory problem for a closed-loop supply chain considering the heterogeneous fleet of vehicles

In this paper, the inventory-routing problem is studied for a closed-loop supply chain. This closed-loop supply chain considers suppliers, manufacturers, whole-sellers, and disposal centers. To formulate this problem, a mixed integer linear programming model is proposed. This mathematical model minimizes the total costs of the supply chain, including the fixed and variable costs of vehicles, and holding inventory costs of final products and scraps. The proposed model considers the road roughness degree, multi-path setting and the heterogeneous fleet of vehicles, which increases its flexibility and the quality of solutions. Then, two symmetry-breaking constraints are proposed to reduce the complexity of the mathematical model. In order to evaluate the integrity of the proposed model, 20 instances of different sizes are randomly generated and solved. Finally, a comprehensive sensitivity analysis is conducted with respect to five key features of the problem, such as the impact of the symmetry-breaking constraints on the CPU time, multi-path setting, fixed cost of vehicles, heterogeneous fleet of vehicles, and lost sales. The results indicate that the consideration of multi-path setting and the heterogeneous fleet of vehicles improves the quality of solutions significantly.