吕梁山连片贫困区南部水资源实物量表特征

为实现区域水资源的优化配置及区域经济、社会和水资源的协调持续发展,查明区域水资源实物量,选取水资源生态极为脆弱的吕梁山连片贫困区的南部地区,基于2008—2017年的水资源数据,编制区域水资源实物量表,分析水资源实物量的时空分布特征。结果表明：（1）吕梁山南部贫困区水资源实物存量在研究期内呈明显增加趋势,增长值（含重复计算量）高达6101×10⁴m³,其中地表水实物存量期间增长最快,地下水实物存量期间增长较慢;第一产业用水增加明显,这与区域高耗水的经果林大面积推广种植有关。（2）居民生活用水增长明显,人均生活用水量增加较快,居民生活用水是当地水资源实物存量变化的主要影响因素。（3）研究区各县水资源实物量空间分布差异大,县域间水资源平均存量最大相差3971.4 m³;单位面积平均水资源存量及单位面积平均水资源实际使用量均为隰县最多,吉县最少;隰县人均生活用水量最多,汾西县人均生活用水量最少。（4）实际用水量与水资源总量相关程度高,水资源的存量在一定程度上制约了水资源的实际使用量。研究结果对于区域水资源优化配置及吕梁山连片贫困区早日实现脱贫攻坚具有重要的科学指导意义。     

皖江经济带土壤Cd空间分布特征与生态风险评价

选取2.5 km×2.5 km网格布点法,在皖江经济带A、B、C三地分别采集土壤样品35个、34个、106个,利用ICP-AES分析测定Cd含量特征,运用单项污染指数法、地累积指数法和潜在生态风险指数法对三地土壤Cd污染状况进行生态风险评价。结果表明：（1）A、B、C三地土壤的Cd含量的算术平均值分别为0.40 mg?kg ^-1、0.66 mg?kg ^-1、0.84 mg?kg ^-1,均高于江淮流域Cd含量土壤背景值;（2）三地土壤pH在5.06~7.58之间,整体上处于酸性和弱碱性之间,pH小于7.0的样品167个,占比95.43%;（3）研究区三个地块土壤Cd污染特征存在明显的空间分异,低污染区在空间上呈带状分布,高污染区在空间上呈岛状分布,污染区分布面积C地>B地>A地。（4）三地土壤环境均受重金属Cd污染的影响,存在生态安全风险,风险大小为C地>B地>A地,风险程度均为潜在生态风险高于地累积生态风险高于单项污染生态风险。本区域土壤农业安全利用需要加以重视并进行分类管控。     

东南亚地区中国海外耕地投资项目的空间分布及影响因素分析

为探究中国在东南亚地区的海外耕地投资活动规律,利用文献资料法、空间分析法和灰色关联分析法,从空间分布和影响因素两方面进行分析。结果表明：（1）中国海外耕地投资项目多位于中南半岛,且有沿边分布特点;（2）中国在东南亚海外耕地投资意向项目、合同项目的空间分布相似性较高,而生产项目与前两者存在差异;（3）中国海外耕地投资受地缘经济、地缘文化、资源基础和地缘政治的影响且受影响程度依次减弱,其中年均进出口总值、年均中国对外直接投资存量等指标对中国企业的投资选择具有显著影响。东南亚地区作为当前中国海外耕地投资的重要区域,强化同东南亚国家间的经济、文化交流,对中国企业顺利开展海外耕地投资活动具有重要促进作用。     

我国主要粮产区PM2.5、PM10时空分布特征及影响因素——以河南省为例

利用2018年河南省PM_2.5、PM₁₀监测数据,结合统计学方法及克里格插值技术,分析河南省PM_2.5、PM₁₀的时空分布特征及影响因素,结果表明:（1）PM_2.5、PM₁₀日均、月均浓度均呈现出“U”型变化特征,PM_2.5/PM₁₀月均值呈现出“W”型变化特征,PM_2.5、PM₁₀季均浓度及其比值均呈现出冬季>秋季>春季>夏季的规律;（2）PM_2.5、PM₁₀月均浓度的空间分布差异较大,而年均浓度则呈现出相似的分布规律,PM_2.5/PM₁₀季均值呈现出不同的空间分布规律,总体上东部及东南部较高,中西部区域较低;（3）PM_2.5、PM₁₀与NDVI、年降水量呈显著负相关,与人口密度、第二产业占比呈显著正相关。研究结论可为粮产区大气污染防治及粮食安全生产提供重要的科学依据。     

民用燃煤不同燃烧阶段细颗粒物排放特征

研究了民用燃煤在不同燃烧阶段排放PM_2.5的质量浓度分布特征.结果表明,散煤与正烧炉在旺火阶段排放颗粒物粒径主要集中在0.2μm以下（d₅₀=0.15μm）,加煤和封火阶段在0.2~0.5μm （d₅₀=0.38mm）,质量占比46.6%~68.97%.型煤与正烧炉在各阶段排放的颗粒物均以0.2μm以下颗粒物为主,质量占比44.64%~56.24%.扫描电镜（SEM）观察到燃煤排放PM_2.5为大量超细颗粒物聚集形成的簇团状结构.用碳平衡法计算得到散煤加煤阶段的PM_2.5排放因子为4.72g/kg,分别是旺火和封火阶段的12和11倍.将散煤更换为型煤,能够使得加煤阶段的PM_2.5排放因子减少90.9%,从而显著降低PM_2.5排放.     

京津冀“以电代煤”替代大气污染物排放清单

本研究建立了基于人工神经网络的民用散煤燃用量估算模型,得到了京津冀地区“以电代煤”替代民用散煤大气污染物排放清单.结果表明：截止到2018年,京津冀地区“以电代煤”替代散煤用户约259万户,每年可减少散煤燃烧约706.6万t,减少PM_2.5、NO_x、SO₂的排放量分别约为2.81,0.76,2.17万t.其中,北京市和天津市实施效果较为明显,占京津冀地区“以电代煤”散煤替代总量的62.01%和22.82%.基于调研数据得到京津冀各市燃煤量月分布系数,1月份分布系数最大,燃煤量占比为27%~40%.     

我国林地土壤有效态镉的影响因素及拟合模型

选取全国13个具有代表性的不同气候带和植被类型的森林土壤,通过外源添加重金属镉（Cd）,比较分析土壤Cd的固-液分配系数（K_d）和有效态Cd的分布特征,探讨了土壤/土壤溶液性质对K_d及土壤有效态Cd的影响,并建立了土壤K_d及有效态Cd的拟合模型.结果表明,在不同浓度Cd处理的土壤中,其K_d值的变化范围为0.91~623.66L/kg,平均值为53.11L/kg,最大值和最小值的差异达到684.37倍;土壤孔隙水中Cd浓度（PW-Cd）的变化范围为0.309~104.450mg/L,其最大值与最小值的差异为338;DTPA提取态Cd含量（DTPA-Cd）从未添加Cd处理的本底土壤C0至最大添加量128mg/kg,其最大值与最小值的差异分别为9和1.4倍.土壤溶液pH值与lgK_d呈显著正相关（R²=0.49,P<0.001）,其与PW-Cd含量呈显著负相关（R²=0.41,P<0.05）;单一的土壤溶液Mg²⁺可解释46%的DTPA-Cd的变异.在对土壤性质的回归分析中,并未发现有单一的主控土壤性质影响Cd的固液分配,当回归方程中加入其它土壤或溶液性质时,可在一定程度上提高拟合模型的预测能力.总之,土壤溶液pH值和Mg²⁺对K_d和有效态Cd含量的影响比较显著.     

BPA和EE2在PA微塑料上竞争吸附的位点能量

为研究微塑料上雌激素共存的吸附行为,以17α-乙炔基雌二醇（EE2）和双酚A （BPA）为目标污染物,微塑料聚酰胺（PA）为吸附剂,通过等温吸附实验研究二者在单溶质和双溶质体系下的吸附性能,基于位点能量分布理论进一步剖析二者在PA微塑料上的的吸附特性.同时,采用X射线光谱（XPS）以及傅里叶变换红外光谱（FTIR）对吸附前后的PA微塑料进行表征,探究其可能存在的吸附机理.等温吸附拟合结果及XPS、FTIR的表征结果表明BPA和EE2及二者混合溶液在PA上的吸附属于非均质吸附,疏水分配及氢键作用为主要的吸附机制.位点能量分布分析结果表明,相同浓度（1～4mg/L）条件下,BPA吸附位点主要分布于高能量区;单溶质体系的EE2吸附位点主要集中于低能量区.双溶质体系下,相同浓度的两种物质位点分布函数均随着位点能量的增大而呈指数降低,BPA下降趋势较为平缓,吸附位点分布更集中.两种体系相比较,BPA平均位点能量和位点能量非均质性分别增加了0.749%和2.483%,吸附位点数量减少了10.852%;双溶质体系下EE2平均位点能量降低0.813%,位点能量非均质性增加1.870%,吸附位点数量增加42.429%.双酚A和EE2在PA微塑料上的竞争吸附中,EE2占优势.     

Distribution and chemical speciation of arsenic in different sized atmospheric particulate matters

The distribution and chemical speciation of arsenic (As) in different sized atmospheric particulate matters (PMs), including total suspended particles (TSP), PM₁₀, and PM_2.5, collected from Baoding, China were analyzed. The average total mass concentrations of As in TSP, PM₁₀, and PM_2.5 were 31.5, 35.3, and 54.1 µg/g, respectively, with an order of PM_2.5 >PM ₁₀ > TSP, revealing that As is prone to accumulate on fine particles. Due to the divergent toxicities of different As species, speciation analysis of As in PMs is further conducted. Most of previous studies mainly focused on inorganic arsenite (iAs^III), inorganic arsenate (iAs^V), monomethylarsonate (MMA), and dimethylarsinate (DMA) in PMs, while the identification and sensitive quantification of trimethylarsine oxide (TMAO) were rarely reported. In this study, a high-performance liquid chromatography coupled to inductively coupled plasma mass spectrometry system was optimized for As speciation including TMAO in PMs. An anion exchange column was used to separate MMA, DMA and iAs^V, while a cation exchange column to separate TMAO and iAs^III. Results showed that iAs^V was the dominate component in all the samples, corresponding to a portion of 79.2% ± 9.3% of the total extractable species, while iAs^III, TMAO and DMA made up the remaining 21%. Our study demonstrated that iAs^III accounted for about 14.4% ± 11.4% of the total extracted species, with an average concentration of 1.7 ± 1.6 ng/m³. It is worth noting that TMAO was widely present in the samples (84 out of 97 samples), which supported the assumption that TMAO was ubiquitous in atmospheric particles.     

Distribution and source of microplastics in China's second largest reservoir - Danjiangkou Reservoir

Fresh water microplastic pollution is of pressing concern globally, but its distribution and sources in reservoirs are poorly documented. Danjiangkou Reservoir is the second largest reservoir in China and is divided into the Han Reservoir and Dan Reservoir. In this work, microplastic abundances and morphological characteristics of the reservoir were investigated. The microplastic abundance of 15 main tributaries of the reservoir was also measured. The vertical distribution (in water column and sediment), horizontal distribution (in Han Reservoir and Dan Reservoir) and source of microplastics were analyzed. Microplastics accumulated in the middle layer of the reservoir, and the size and color of the microplastic particles changed from the surface to the bottom, which implies that surveys of surface water are not enough to determine the microplastic contamination for deep water reservoirs. In the surface water, the microplastic abundance in the Han Reservoir was lower than that in the Dan Reservoir (p < 0.05), but microplastic abundance did not differ significantly in the intermediate and bottom water. Tributaries were one of the main sources of microplastics for Han Reservoir but not for Dan Reservoir. Agricultural cultivation in the hydro-fluctuation belt might be an important source of microplastics in the Dan Reservoir, which should be given additional attention. The results of this study can provide valuable information for developing microplastic sampling strategies in deep water reservoirs. Further studies are recommended to investigate the process through which microplastics in the hydro-fluctuation belt enter the reservoir and the sinking behavior of microplastics in the reservoir.