Deep learning architecture for air quality predictions

With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance.     

The influence of Chinese population policy change on resources and the environment

Universal two-child policy has been implemented since the end of 2015 in China. This policy is anticipated to bring a significant increase in the total population, with profound influences on the resources and environment in the future. This paper analyzes the changing dynamics of urban and rural population, and forecasts urban and rural population from 2016 to 2030 at national and provincial scale using a double log linear regression model. Drawing upon the results of these two predictions, the impact of the population policy change on Chinese resources consumption and environmental pollution are predicted quantitatively. Given the future total population maintains current levels on resources consumption and environmental emission, the additional demand of resources and environment demand for the new population is forecasted and compared against the capacity on supply side. The findings are as follows: after implementing the universal two-child policy, China’s grain, energy consumption, domestic water demand, and pollutant emissions are projected to increase at different rates across provinces. To meet the needs arising from future population growth, food and energy self-sufficiency rate will be significantly reduced in the future, while relying more on imports. Stability of the water supply needs to be improved, especially in Beijing, Henan, Jiangsu, Qinghai, and Sichuan where the gap in future domestic water demand is comparatively larger. Environmental protection and associated governing capability are in urgent need of upgrade not least due to the increasing pressure of pollution.     

洞庭湖区血吸虫病疫水人水相互作用关系及防控方案研究

研究洞庭湖区血吸虫病人水相互作用关系及传染防控,是推进湖区社会经济稳定健康发展的重要保障。从水文情势、产业发展、居民行为、城乡建设四方面探讨了洞庭湖区血吸虫病疫水人水相互作用关系,并运用系统动力学模型,设置教育优先方案、生态保护优先方案和城镇化推进方案对其防控方案进行系统仿真模拟和对比分析,研究结果表明:(1)水文等生态因素对于人水接触的影响逐步减少,而社会经济因素则显得越来越重要。(2)系统动力学模型能有效展示血吸虫病各影响因素之间的关系,是研究血吸虫病防控的有效方法之一。(3)依据仿真模拟结果,城镇化推进方案是经济增长、城乡协调、环境友好的最优血防方案。     

Pollination ecology of <Emphasis Type="Italic">Eomecon chionantha</Emphasis> Hance (Papaveraceae), an endemic species in China

Eomecon chionantha Hance, the only species in the genus Eomecon, is an angiosperm species endemic to China. Here we investigated the pollination syndrome, pollinator generalization of E. chionantha. Our results showed that the individual flower longevity of E. chionantha was 3–5 days. The flowering phenology of E. chionantha can be divided into five phases. We found significant differences in the pollination efficiency of the different insects visiting E. chionantha with bees and flies being the most efficient pollinators. This, in addition to floral morphology and phenology, suggests that E. chionantha is generalized on bees and flies and possesses an outcrossing, partially self-compatible and pollinator-dependent breeding system.     

Decline of traditional rice farming constrains the recovery of the endangered Asian crested ibis (Nipponia nippon)

Traditional agriculture benefits a rich diversity of plants and animals. The winter-flooded rice fields in the Qinling Mountains, China, are the last refuge for the endangered Asian crested ibis (Nipponia nippon), and intensive efforts have been made to protect this anthropogenic habitat. Analyses of multi-temporal satellite data indicate that winter-flooded rice fields have been continuously reduced across the current range of crested ibis during the past two decades. The rate of loss of these fields in the core-protected areas has unexpectedly increased to a higher level than that in non-protected areas in the past decade. The best fit (R² = 0.87) numerical response model of the crested ibis population shows that a reduction of winter-flooded rice fields decreases population growth and predicts that the population growth will be constrained by the decline of traditional winter-flooded rice fields in the coming decades. Our findings suggest that the decline of traditional rice farming is likely to continue to pose a threat to the long-term survival and recovery of the crested ibis population in China.

Electronic supplementary material

The online version of this article (doi:10.1007/s13280-015-0649-5) contains supplementary material, which is available to authorized users.     

中型污水处理厂中药物和个人护理品的分布与去除

为了解15种药物及个人护理用品(PPCPs)在中小型污水处理厂中的分布及其去除效果,采用液相色谱-串联质谱(LC-MS/MS)技术对3座A2/O工艺的污水处理厂水样进行分析研究。结果显示,除普萘洛尔、吉非罗平和吲哚美辛在3座中小型污水处理厂各个工艺单元中均未被检出外,其余12种目标化合物的检出频率在90%~100%之间。进水水样中PPCPs的平均检出浓度为2 285.4 ng/L,其中咖啡因(CF)的平均检出浓度最高为973.3 ng/L,酮洛芬(KP)的平均检出浓度次之为844.7 ng/L,两者之和占进水水样中PPCPs平均含量的79.5%,表明污水处理厂的主要污染物为CF和KP。3座污水处理厂对CF的去除效果最为显著,平均去除率为95.3%,对15种PPCPs总去除效率在39.3%~82.8%之间。     

磷酸铵镁碱促(Mg(OH)_2)热解产物氨氮去除性能

磷酸铵镁热解循环技术可以有效降低磷酸铵镁结晶技术的药剂费用。同时,在磷酸铵镁热解过程中添加Mg(OH)2碱促媒介,能阻止磷酸氢镁向焦磷酸镁的转化,并降低热解产物氨氮去除过程中上清液磷酸盐的残留。在Mg(OH)2∶NH+4摩尔比为1∶1,热解温度为110℃条件下,热解产物沉氨效率接近84%,上清液磷酸盐残留量为0.02 mg/L。     

高效液相色谱-串联质谱法同时检测地表水中13种药物及个人护理品

采用高效液相色谱-串联质谱(HPLC-MS/MS)检测,建立了地表水中13种药物及个人护理品的测定方法。水样用盐酸与氢氧化钠溶液调p H值至7.0左右,过固相萃取小柱进行富集,用14 m L甲醇洗脱。以C18柱为分离柱,0.01%甲酸的甲醇-0.01%甲酸水溶液为流动相,目标物在10 min内分离,在0.50~250μg/L范围内,13种化合物峰面积与内标物质峰面积之比与质量浓度的线性关系良好(0.99),检出限在0.05~0.5 ng/L范围内。基质加标实验结果表明,13种化合物在水中的回收率分别在56.2%~123.2%之间(加标水平5 ng/m L)和58.0%~107.8%(加标水平50 ng/m L),相对标准偏差在1.60%~19.9%(n=6)之间。应用该方法测定了从2条纳污河流采集的10份水样,结果表明,除美托诺尔和普洛萘尔未被检出外,其余11药物的检出频率在30%~100%之间。在13种目标物质中,咖啡因的检测浓度最高达287.5ng/L,舒必利次之,为277.5 ng/L。本方法快速、准确,适用于地表水中PPCPs类的快速测定。