徐州大气PM10污染特征研究

通过分析徐州市近几年的大气PM10监测数据和气象条件,研究了大气PM10质量浓度的时间变化规律及气象因素的影响,结果表明:PM10质量浓度年变化呈"冬重夏轻"的规律;在大气污染源数量和污染物排放量相对稳定的情况下,风和降水是影响大气颗粒物污染程度的主要气象因子,PM10浓度随温度的升高而降低,随气压的增强而减少。     

A discussion of the potential impacts of climate change on the shorelines of the Northeastern USA

An increase in the rate of sea-level rise and potential changes in storminess represent important components of global climate change that will likely affect the extensive coasts of the Northeastern USA. Raising sea level not only increases the likelihood of coastal flooding, but changes the template for waves and tides to sculpt the coast, which can lead to land loss orders of magnitude greater than that from direct inundation alone. There is little question that sea-level rise, and in particular an increased rate of rise, will result in permanent losses of coastal land. However, quantitative predictions of these future coastal change remains difficult due in part to the complexity of coastal systems and the influence of infrequent storm events, and is further confounded by coastal science’s insufficient understanding of the behavior of coastal systems over decadal timescales. Recently, dramatic improvements in technology have greatly improved our capabilities to investigate and characterize processes and sedimentary deposits in the coastal zone, allowing us, for the first time, to address some of the over-arching problems involved in shoreline change. Despite advances in many areas of coastal geology, our fundamental understanding of shoreline change has been limited by a lack of a broad and integrated scientific focus, a lack of resources, and a lack of willingness on the part of policymakers who make crucial decisions about human activity along the coast to support basic research in this area. Although quantitative predictions remain constrained, there remains little doubt that the predicted climates changes will have profound effects upon the Northeastern coast.     

Life cycle assessment of coated white board: a case study in China

Life cycle assessment was carried out using IMPACT2002+ to estimate the environmental impact of coated white board production, which is common in China. Normalized results showed that the potential impacts of respiratory inorganics, terrestrial ecotoxicity, global warming, and non-renewable energy had a dominant contributions to overall environmental impact. Specifically, emissions from chemical and energy production processes exhibited higher potential impact (more than 80% of the total contribution) on the environment than that of emissions generated from transport, landfill, wastewater treatment, and paper plants infrastructure. Energy recovery from black liquor and energy generation based on natural gas are key factors in reducing overall environmental potential impact. The current paper presents improvements on the environmental performance of a coated white board production site in China.     

基于模糊粗糙集的化工园区多米诺事故救援时机分析

本文旨在通过粗糙集约简手段研究化工园区多米诺事故救援时机问题。首先将初始事故等级、间距系数、环境等级、临近企业脆弱性、初始事故发生时间等5个因素作为多米诺事故发生条件,应用Kmeans聚类方法实现模糊粗糙集数据离散化,之后应用属性约简及属性值约简方法分析案例信息,最后提取规则并从以上5个因素角度确定火灾多米诺事故的救援最佳时机,结果表明救援规则简洁明了,可执行性较高。     

An improved grey wolf optimizer algorithm for identification and location of gas emission

Identification of the leakage of hazardous gases plays an important role in the environment protection, human health and safety of industry production. However, lots of current optimization algorithms, such as particle swarm optimization (PSO) and Grey Wolf Optimizer (GWO), suffer from poor global optimization capability and estimation accuracy. In this work, a hybrid differential evolutionary and GWO (DE-GWO) algorithm is proposed. Tested by simulation cases and Prairie Grass emission experimental data, DE-GWO shows higher estimation accuracy than GWO. Compared with the other four optimization algorithms, DE-GWO exhibits finer robust stability under different population sizes, fewer iterations, as well as higher estimation accuracy with fewer search agents. Importantly, simulation results demonstrate that DE-GWO is more suitable to apply in the scene with a small number of sensors. Therefore, the proposed in this paper outperforms other optimization algorithms for the gas emission inverse problem. DE-GWO can provide reliable estimation towards gas emission identification and positioning, which shows huge potential as the data analysis module of real-time monitoring and early warning system.     

基于DPEHA模型生态环境健康评价体系的法治化研究

生态环境健康评价包括生态环境健康风险评估和环境治理有效性的评价,是监测生态环境质量对公众健康的潜在风险和指导决策的重要技术手段。我国至今尚未形成全面有效的生态环境健康评价体系,且在评价某一区域生态环境质量对公众健康的影响时,往往忽略了生态法治的作用。为此,本文基于驱动力—压力—环境条件—健康影响—行动（DPEHA）模型构建了一套具有生态法治特色的生态环境健康评价指标体系,并以深圳市2019年和2020年生态环境健康工作为例,对模型进行验证,以推进深圳生态环境健康保护法治化建设。未来研究要将评价体系应用至不同城市,以深入推进法治中国建设。