China’s carbon neutrality: an extensive and profound systemic reform

● China has pledged ambitious carbon peak and neutrality goals for mitigating global climate change. ● Major challenges to achieve carbon neutrality in China are summarized. ● The new opportunities along the pathway of China’s carbon neutrality are discussed from four aspects. ● Five policy suggestions for China are provided. China is the largest developing economy and carbon dioxide emitter in the world, the carbon neutrality goal of which will have a profound influence on the mitigation pathway of global climate change. The transition towards a carbon-neutral society is integrated into the construction of ecological civilization in China, and brings profound implications for China’s socioeconomic development. Here, we not only summarize the major challenges in achieving carbon neutrality in China, but also identify the four potential new opportunities: namely, the acceleration of technology innovations, narrowing regional disparity by reshaping the value of resources, transforming the industrial structure, and co-benefits of pollution and carbon mitigation. Finally, we provide five policy suggestions and highlight the importance of balancing economic growth and carbon mitigation, and the joint efforts among the government, the enterprises, and the residents.     

Approaching the upper boundary of driver-response relationships: identifying factors using a novel framework integrating quantile regression with interpretable machine learning

● A novel framework integrating quantile regression with machine learning is proposed. ● It aims to identify factors driving observations to upper boundary of relationship. ● Increasing N:P and TN concentration help fulfill the effect of TP on CHL. ● Wetter and warmer decrease potential and increase eutrophication control difficulty. ● The framework advances applications of quantile regression and machine learning. The identification of factors that may be forcing ecological observations to approach the upper boundary provides insight into potential mechanisms affecting driver-response relationships, and can help inform ecosystem management, but has rarely been explored. In this study, we propose a novel framework integrating quantile regression with interpretable machine learning. In the first stage of the framework, we estimate the upper boundary of a driver-response relationship using quantile regression. Next, we calculate “potentials” of the response variable depending on the driver, which are defined as vertical distances from the estimated upper boundary of the relationship to observations in the driver-response variable scatter plot. Finally, we identify key factors impacting the potential using a machine learning model. We illustrate the necessary steps to implement the framework using the total phosphorus (TP)-Chlorophyll a (CHL) relationship in lakes across the continental US. We found that the nitrogen to phosphorus ratio (N׃P), annual average precipitation, total nitrogen (TN), and summer average air temperature were key factors impacting the potential of CHL depending on TP. We further revealed important implications of our findings for lake eutrophication management. The important role of N׃P and TN on the potential highlights the co-limitation of phosphorus and nitrogen and indicates the need for dual nutrient criteria. Future wetter and/or warmer climate scenarios can decrease the potential which may reduce the efficacy of lake eutrophication management. The novel framework advances the application of quantile regression to identify factors driving observations to approach the upper boundary of driver-response relationships.     

A new prediction method of industrial atmospheric pollutant emission intensity based on pollutant emission standard quantification

● Established a quantification method of pollutant emission standard. ● Predicted the SO₂ emission intensity of single coking enterprises in China. ● Evaluated the influence of pollutant discharge standard on prediction accuracy. ● Analyzed the SO₂ emissions of Chinese provincial and municipal coking enterprises. Industrial emissions are the main source of atmospheric pollutants in China. Accurate and reasonable prediction of the emission of atmospheric pollutants from single enterprise can determine the exact source of atmospheric pollutants and control atmospheric pollution precisely. Based on China’s coking enterprises in 2020, we proposed a quantitative method for pollutant emission standards and introduced the quantification results of pollutant emission standards (QRPES) into the construction of support vector regression (SVR) and random forest regression (RFR) prediction methods for SO₂ emission of coking enterprises in China. The results show that, affected by the types of coke ovens and regions, China’s current coking enterprises have implemented a total of 21 emission standards, with marked differences. After adding QRPES, it was found that the root mean squared error (RMSE) of SVR and RFR decreased from 0.055 kt/a and 0.059 kt/a to 0.045 kt/a and 0.039 kt/a, and theR² increased from 0.890 and 0.881 to 0.926 and 0.945, respectively. This shows that the QRPES can greatly improve the prediction accuracy, and the SO₂ emissions of each enterprise are highly correlated with the strictness of standards. The predicted result shows that 45% of SO₂ emissions from Chinese coking enterprises are concentrated in Shanxi, Shaanxi and Hebei provinces in central China. The method created in this paper fills in the blank of forecasting method of air pollutant emission intensity of single enterprise and is of great help to the accurate control of air pollutants.     

电子废弃物中持久性有机污染物分析检测方法的研究进展

针对目前电子废弃物中持久性有机污染物(POPs)尚未形成有效快速分析检测方法的问题,介绍了溶剂萃取、固相萃取、微波萃取和超临界流体萃取等POPs前处理技术的研究进展,总结了POPs的分析方法,如:气相色谱、液相色谱、气相色谱-质谱法、高分辨率气相色谱-高分辨质谱法等化学分析方法,以及生物传感器测定法、表面胞质团共振检测法、酶联免疫检测法等生物分析方法。分析了各方法的优劣,并提出了展望。     

邯郸市妇女空气污染暴露对妊娠期高血压的影响

选择河北省邯郸市某医院孕妇数据,探讨了6项空气污染物暴露对孕妇患妊娠期高血压(GH)的影响和不同人群的效应差异,采用传统Logistic回归模型评估了各项污染物的效应,采用主成分改进的Logistic回归模型评估了各项污染物在额外调整其它污染物后的效应.结果显示,单污染物模型中,妊娠期前26周每20μg/m3增量的O3...     

三峡水库入库溪流中麦氏花翅蜉(蜉蝣目:四节蜉科)的生活史研究

开展水生昆虫生长过程研究对掌握研究区域水生生物的生物学特征和研究区域生态环境状况等均具有重要作用,可为构建和完善研究区域河流生态环境保护体系提供科学参考。于2017年逐月对香溪河库湾入库支流(螃蟹溪)中的一种水生昆虫——麦氏花翅蜉(Baetiella macani)的种群进行了研究,基于大小频率法、幼虫期有效积温条件进行了生活史性状分析和验证。结果显示:麦氏花翅蜉为三化性昆虫,包含一个冬季世代和两个夏季世代。冬季世代幼虫的发育历期为3~4个月,所需有效积温为1 286 ℃;夏季世代幼虫的发育历期为1~2个月,所需有效积温为757 ℃。研究结果丰富了中国地区水生昆虫的生活史性状信息,并首次呈现了花翅蜉属的生活史特征。     

EBPR中两类细菌PAOs和GAOs竞争的研究进展

强化生物除磷(EBPR)工艺可以获取高效的除磷效果,已在很多污水处理厂得到广泛应用。但是大型污水处理厂在相当多的条件下,EBPR工艺也会出现周期性除磷效果的波动和不充分。针对这一难题,研究者试图采用许多手段来研究工艺中的主要微生物。文章针对典型的EBPR工艺和碳源、pH值、温度等因素对EBPR工艺中两类细菌聚磷菌(PAOs)和聚糖菌(GAOs)竞争的研究进展进行了论述,并展望了未来的研究方向。     

Volatilization of heavy metals during incineration of municipal solid wastes

Incineration experiments with MSW, which had been impregnated with heavy metals, were presented to obtain information on the volatilization behavior of the elements cadmium (Cd), lead (Pb), and zinc (Zn) under different conditions. Experiments were carried out in a bubbling fluid bed system connected to a customized inductively coupled plasma optical emission spectroscopy(ICP-OES) for analyzing metals in the flue gas. The results indicated that the combustion temperature, the gas atmosphere, and the chlorine content in the flue gas could affect the volatilization behavior of heavy metals. In the fluidized bed combustion, a large surface area was provided by the bed sand particles, and they may act as absorbents for the gaseous ash-forming compound. Comparer with the metals Cd and Pb, the vaporization of Zn was low. The formation of stable compounds such as ZnO.Al2O3 could greatly decrease the metals volatilization. The presence of chlorine would enhance the volatilization of heavy metals by increasing the formation of metal chlorides. However, when the oxygen content was high, the chlorinating reaction was kinetically hindered, which heavy metals release would be delayed.     

矿物棉填料孔隙率对生物滴滤池水处理效果的影响

针对生物滴滤池因接触时间短而导致出水不达标的问题,采用3种容重(80、100、120 kg· m-3)的矿物棉作为滤池填料,考察了填料孔隙率对保水性的影响,分析了不同容重填料的生物滴滤池去除污染物的效能,探究了填料孔隙率对微生物群落特征的影响.结果 表明,矿物棉载体的吸水、保水性能随其孔隙率增加呈现先增加后减小的趋势;...     

脱硫石膏对酸化森林土壤短期修复效果的研究

以电厂脱硫石膏为修复剂,选取重庆铁山坪地区典型的酸化森林土壤为修复对象,进行了为期1 a的修复效果研究.对不同土层土壤溶液pH值、主要阴阳离子和重金属浓度的动态变化展开观测,并对土壤和脱硫石膏的重金属含量进行分析,以评价脱硫石膏的修复效果及存在的风险.结果表明,与对照样地相比,修复样地各层土壤溶液Ca2＋和SO24-的浓度随时间依次升高,pH值也略有上升,且年均n（Ca）/n（Al）摩尔比从2.16、1.35和0.88升高到2.58、1.52和1.12.土壤溶液中As、Cu、Cr、Ni和Zn的浓度并未检测到明显上升,只是Cr、Ni和Zn在土壤上层出现了轻微富集.脱硫石膏的处理对酸化土壤起到了改良作用,且未造成土壤溶液重金属浓度明显的升高,但重金属在土壤层的积累会造成潜在的风险,需要进一步开展研究.