Source identification and prediction of nitrogen and phosphorus pollution of Lake Taihu by an ensemble machine learning technique

● A machine learning model was used to identify lake nutrient pollution sources. ● XGBoost model showed the best performance for lake water quality prediction. ● Model feature size was reduced by screening the key features with the MIC method. ● TN and TP concentrations of Lake Taihu are mainly affected by endogenous sources. ● Next-month lake TN and TP concentrations were predicted accurately. Effective control of lake eutrophication necessitates a full understanding of the complicated nitrogen and phosphorus pollution sources, for which mathematical modeling is commonly adopted. In contrast to the conventional knowledge-based models that usually perform poorly due to insufficient knowledge of pollutant geochemical cycling, we employed an ensemble machine learning (ML) model to identify the key nitrogen and phosphorus sources of lakes. Six ML models were developed based on 13 years of historical data of Lake Taihu’s water quality, environmental input, and meteorological conditions, among which the XGBoost model stood out as the best model for total nitrogen (TN) and total phosphorus (TP) prediction. The results suggest that the lake TN is mainly affected by the endogenous load and inflow river water quality, while the lake TP is predominantly from endogenous sources. The prediction of the lake TN and TP concentration changes in response to these key feature variations suggests that endogenous source control is a highly desirable option for lake eutrophication control. Finally, one-month-ahead prediction of lake TN and TP concentrations (R² of 0.85 and 0.95, respectively) was achieved based on this model with sliding time window lengths of 9 and 6 months, respectively. Our work demonstrates the great potential of using ensemble ML models for lake pollution source tracking and prediction, which may provide valuable references for early warning and rational control of lake eutrophication.     

浙江省环境质量演变趋势分析及预测研究

选择2011—2020年浙江省地表水、空气和酸雨监测数据,结合社会经济发展统计数据,从社会经济与环境质量间协调性角度探讨“十二五”及“十三五”浙江省环境质量演变趋势,并在此基础上对“十四五”期间环境质量进行科学合理的预测。分析结果表明,2011—2020年环境质量不断向良好状态发展,通过动态耦合模型得到的耦合度由2011年的34.6°上升到2020年的55.4°,社会经济发展与环境质量协调发展水平呈现上升态势。采用灰色预测法和时间序列模型对环境质量进行预测,模拟结果显示,预计到2025年地表水优良率将达到92%,满足功能要求断面比例达到95%,设区城市空气质量优良天数比例达到92%,酸雨率平均为40%。正确认识社会经济发展与环境质量变化之间的耦合规律,并对环境质量进行合理预测,能够为促进社会经济与生态环境的协调发展提供理论依据,为深入打好污染防治攻坚战提供有力支撑。     

东南沿海经济发达地区发展趋势与问题

东南沿海经济发达地区是我国改革开放和现代化建设的先行地区。在持续十几、二十几年的经济快速发展过程中,该地区产业结构进一步优化,经济实力迅速提高,已经基本形成城乡一体化、城市连绵化的格局,为我国综合实力的增强做出了巨大贡献。随着经济全球化、一体化的发展,该地区将继续担负我国国际竞争力提升和国内经济发展示范的重要作用。然而,产业自主创新能力不强、能源缺口较大、耕地流失严重、粮食安全问题、产业发展空间受限、生态环境恶化等已成为该地区可持续发展的瓶颈。在分析该地区发展状况与问题的基础上,从协调经济、环境与社会的角度出发,以科学发展观为指导,对东南沿海地区经济可持续发展提出了建议。     

基于城市地铁实证分析的突发事件风险发展趋势评价模型研究

为了更好地完善突发事件风险评价过程,运用风险发展趋势评价模型对风险评价过程进行补充。采用Daniel趋势函数、灰色理论和模糊理论建立突发事件的风险发展趋势评价模型,并对广州市地铁运营风险发展趋势进行实证分析。结果表明,从执行过程看,该模型改善了突发事件风险评价的范围和评价结果的准确度,评价过程具有一定的可行性和客观性,可以推广应用到各类突发事件的风险发展趋势评价中。通过实证分析,该城市的地铁运营风险当前处于临界状态以下,可以保持当前的运营状态,与该城市的地铁运营状况相符合,对于单个子系统,乘客和员工素质系统目前处于临界状态,对整个地铁系统的安全性有较大影响,城市居民和员工素质需要进一步提高。     

我国工伤事故死亡率分析及其ARIMA预测

对我国工伤事故死亡率的历史数据进行分析,介绍ARIMA模型预测法。根据统计学理论,运用ARIMA模型,借助相关软件预测我国工伤事故死亡率,可知未来几年,工伤事故的千人死亡率总体上呈逐年下降的趋势;与移动平均法、指数平滑法预测结果作比较,可知ARIMA模型预测效果最佳;同时,由于影响工伤事故的因素很多,与长期预测相比,ARIMA模型更适合于对工伤事故死亡率作短期预测。     

土岩爆破与宅楼损伤因果关系分析--以湖北某电厂爆破工程为例

对某工程公司平基爆破对附近宅楼的损伤事故进行鉴定。通过实地勘测、调查取证,从宅楼的裂缝走向、爆破产生的爆破地震效应和空气冲击波作用三方面对附近宅楼损伤的可能性进行分析．认为该平基爆破不会对该宅楼造成损伤破坏。     

天山北坡城市群PM2.5浓度时空分布特征及影响因素分析

针对天山北坡城市群开展PM_2.5浓度时空分布特征和影响因素分析,对区域经济建设和环境保护具有积极的意义.通过地理加权回归（GWR）模型,利用MCD19A2气溶胶产品结合气象因子,反演得到天山北坡城市群2015~2021年3~11月的PM_2.5浓度时空分布,继而实现变化趋势和影响因素分析.结果如下：①研究区PM_2.5浓度高值主要分布在天山北麓和古尔班通古特沙漠之间的绿洲城市群地带,呈现“四周低,中间高”和“西低东高”的空间分布特征,2015~2021年研究区的ρ（PM_2.5）年均值为16.98 μg·m^-3,高值主要聚集在乌鲁木齐市市区部分,并向昌吉市和阜康市延伸递减;ρ（PM_2.5）月均值分布规律与年均一致,但存在季节差异,表现为：秋季（20.32 μg·m^-3）>春季（18.25 μg·m^-3）>夏季（12.47 μg·m^-3）,春季和冬季聚集现象会更明显;②研究区PM_2.5浓度年均值在2015~2021年呈现下降趋势,3~10月均值同样表现为下降趋势,仅11月表现为略有升高;从PM_2.5浓度变化趋势空间分布分析,下降集中在主要城市市区部分,尤其是乌鲁木齐市市区部分及其周边地区减少幅度最大,变化最为剧烈;③研究区气温、气压与PM_2.5浓度呈现正相关效应,而相对湿度,风速,大气边界层高度,降水量与PM_2.5浓度呈现负相关效应;各因子影响程度从高向低排列为：大气边界层高度>相对湿度>气压>气温>风速>降水量.     

An integrated river basin-coast-sea modelling scenario for nitrogen management in coastal waters

Linked river basin and coastal water models were applied to analyse the effects of an optimal nitrogen management scenario in the Oder/Odra river basin on water quality in the Oder (Szczecin) Lagoon and the Pomeranian Bay (Baltic Sea). This scenario would reduce nitrogen loads into the coastal waters by about 35%, a level which is similar to the load of the late 1960’s. During summer the primary production and algae biomass in the Oder estuary is limited by nitrogen, which makes a nitrogen management reasonable. The comparison of the late 1960’s and the mid 1990’s shows that an optimal nitrogen management has positive effects on coastal water quality and algae biomass. However, this realistic nitrogen reduction scenario would not ensure a good coastal water quality according to the European Water Framework Directive. A good water quality in the river will not be sufficient to ensure a good water quality in the lagoon. Nitrogen load reductions bear the risk of increased potentially toxic, blue-green algae blooms, especially in the Baltic coastal sea. However, to reach water quality improvements in lagoons and inner coastal waters, nitrogen cuts are necessary. A mere focus on phosphorus is not sufficient.     

磷矿浮选废水治理的现状及发展趋势

阐述了我国磷矿浮选废水的危害性及处理现状,指出其处理方法的优点与不足。对磷矿废水处理的发展趋势进行了探讨,给出了生物处理法的简易流程,并就防治废水污染提出了几点建议。     

城市景观河流夏季污染状况及营养水平动态分析--以天津市津河为例

以CODMn、氨氮、总氮、总磷和叶绿素a等为主要指标。对天津市一条典型的景观河流——津河进行了调查分析。结果表明,津河水质介于地表水环境标准(GB3838—2002)的Ⅳ和Ⅴ类之间,营养状态为重富营养。且在多个采样点出现蓝藻水华。水体中的各项指标的变化趋势为,CODMn与叶绿素a都是在7月达到最高,随后逐渐降低。总溶解性氮夏季变化曲线呈倒“S’形。7月最低。8月最高。河道上游总溶解性磷一直比较稳定,而下游在8月上旬急剧升高。藻类演替过程大致为粉末微囊藻-皮状席藻-多种蓝藻。与改造之初相比。水质状况有所改善。