辽宁省人为源大气污染物排放清单及特征研究

为全面评估辽宁省关键大气污染物排放状况,系统收集和整理全省基础活动水平信息,采用排放因子法建立了该省2012年人为源大气污染物排放清单.结果显示,2012年辽宁省SO_2、NO_x、CO、PM10、PM_(2.5)、BC、OC及NH_3排放总量分别为1434.8×10~3、1632.3×10~3、6682.9×10~3、1529.9×10~3、1087.8×10~3、74.5×10~3、176.1×10~3t及880.4×10~3t.BC和OC最大贡献源为生物质燃烧源,排放集中分布在辽宁中、西部;NH_3主要来自畜禽养殖与化肥施用,排放高值区位于辽宁中部农业畜牧业发达地区;其他污染物主要来自固定燃烧源和工艺过程源,集中分布在辽宁中部城市群以及大连金州区、甘井子区和普兰店区.大连、沈阳是SO_2、NO_x、NH_3和颗粒物主要排放城市,鞍山和本溪由于钢铁行业发达,成为CO排放量最大的城市.基于卫星观测获得的NO_2垂直柱浓度对NO_x排放空间分布进行评估,两者相关性系数为0.57(p0.01).辽宁省级排放清单与国家尺度排放清单在一定程度存在差异,主要原因在于采用的活动水平和污染物控制效率的不同,基于详细本地化污染源信息建立的省级排放清单可以较好地反映实际情况.建议完善点源排放特征信息并加强本地化测试,进一步降低省级排放清单不确定性.     

O3-BAC-Cl2: A multi-barrier process controlling the regrowth of opportunistic waterborne pathogens in drinking water distribution systems

Simulated drinking water distribution system (DWDS) treated with O₃-BAC-Cl₂ (ozone-biological activated carbon-chlorine) was constructed to study its effects on the regrowth of five typical opportunistic pathogens (OPs). It was found that O₃-BAC-Cl₂ could significantly reduce the regrowth of target OPs in the effluents of DWDS compared with Cl₂ and O₃-Cl₂ with the same residual chlorine levels. However, the effect of O₃-BAC-Cl₂ on the average numbers of target OPs gene markers in the biofilms of DWDS was not apparent, suggesting that OPs in the biofilms of DWDS were tolerant to the upstream disinfection process. The quantification of target OPs in the BAC-filter column demonstrated that OPs decreased with the increase of depth, which was likely due to the organic nutrient gradient and microbial competition inside the BAC-filter. Increase in the ozone dose could further reduce the OPs at the bottom of the BAC-filter. Spearman correlation analysis demonstrated that some significant correlations existed between target microorganisms, suggesting potential microbial ecological relationships. Overall, our results demonstrated that the BAC-filter may act as a “battlefield” suppressing the OPs through microbial competition. O₃-BAC-Cl₂ could be an effective multi-barrier process to suppress the proliferation of OPs in the bulk water of DWDS. However, OPs protected by the biofilms of DWDS should receive further attention because OPs may be detached and released from the biofilms.     

浙江省2008~2018年人为源氨排放清单及分布特征

以浙江省为研究区域,通过收集11个地级市各类氨排放的活动水平数据,采用排放因子法建立了2008~2018年浙江省人为源氨排放清单,并利用ArcGIS进行1 km×1 km空间网格分配.结果表明,2008~2018年浙江省人为源氨排放量总体呈现下降趋势,年均下降率约3.97%;2018年浙江省氨排放量为108.52 kt,其中农业源为90.02 kt,非农业源为18.50 kt,排放强度为1.03 t ·km^-2;杭州市、嘉兴市和温州市的氨排放量高于其他城市,分别占全省总量的14.72%、11.86%和11.80%;空间分布特征显示,氨排放主要分布在浙江省北部区域,呈现出"北高南低"的排放趋势;不确定性分析表明,氨排放量模拟平均值为108.37 kt,在95%置信区间的不确定度范围为-5.40%~5.60%.     

青岛市人为源氨排放清单及分布特征

通过调查收集各类人为源氨排放活动水平数据,选取合适的排放因子,建立了青岛市2019年人为源氨排放清单,分析了青岛市人为源氨排放贡献特征及分布特征.结果表明,2019年青岛市人为源氨排放总量为28.33×10³ t,排放强度为2.51 t·km^-2.其中,畜禽养殖是青岛市最主要的排放源,占全市氨排放总量的比例高达77.80%,其次为农田生态系统和废弃物处理,氨排放量分别占全市总量的7.64%和6.87%.2019年,平度市和莱西市氨排放量较高,分别占青岛市氨排放总量的34.18%和26.23%,而市北区和莱西市排放强度较高,分别达到7.26 t·km^-2和4.74 t·km^-2.从空间分布上,氨排放量较高的镇街主要分布在青岛市北部和西北部,而排放强度较高的镇街则集中在青岛市市区中部和北部地区.     

Microplastic contamination in Great Lakes fish

Freshwater ecosystems, generally adjacent to human population and more contaminated relative to adjacent marine ecosystems, are vulnerable to microplastic contamination. We sampled 7 species of fish from Lake Ontario and Lake Superior and assessed their gastrointestinal (GI) tracts to quantify ingested microplastics and other anthropogenic particles. A subset of the microparticles were chemically analyzed to confirm polymer types and anthropogenic origins. We documented the highest concentration of microplastics and other anthropogenic microparticles ever reported in bony fish. We found 12,442 anthropogenic microparticles across 212 fish (8 species) from nearshore Lake Ontario, 943 across 50 fish (1 species) from Humber River, and 3094 across 119 fish (7 species) from Lake Superior. Fish from Lake Ontario had the greatest mean abundance of anthropogenic microparticles in their GI tracts (59 particles/fish [SD 104]), with up to 915 microparticles in a single fish. Fish from Lake Superior contained a mean [SD] of 26 [74] particles/fish, and fish from Humber River contained 19 [14] particles/fish. Most particles were microfibers. Overall, ≥90% of particles were anthropogenic, of which 35-59% were microplastics. Polyethylene (24%), polyethylene terephthalate (20%), and polypropylene (18%) were the most common microplastics. Ingestion of anthropogenic particles was significantly different among species within Lake Ontario (p < 0.05), and the abundance of anthropogenic particles increased as fish length increased in Lake Ontario (ρ = 0.62). Although we cannot extrapolate the concentration of microplastics in the water and sediments of these fish, the relatively high abundance of microplastics in the GI tracts of fish suggests environmental exposure may be above threshold concentrations for risk.     

Parasites as conservation tools

Parasite success typically depends on a close relationship with one or more hosts; therefore, attributes of parasitic infection have the potential to provide indirect details of host natural history and are biologically relevant to animal conservation. Characterization of parasite infections has been useful in delineating host populations and has served as a proxy for assessment of environmental quality. In other cases, the utility of parasites is just being explored, for example, as indicators of host connectivity. Innovative studies of parasite biology can provide information to manage major conservation threats by using parasite assemblage, prevalence, or genetic data to provide insights into the host. Overexploitation, habitat loss and fragmentation, invasive species, and climate change are major threats to animal conservation, and all of these can be informed by parasites.     

2000～2021年成渝城市群PM2.5时空变化及驱动机制多维探测

研究成渝城市群PM_2.5浓度时空变化和驱动机制，对区域大气环境保护和国家经济可持续发展具有重要意义.基于PM_2.5遥感数据、 DEM数据、基于站点的气象数据、 MODIS NDVI数据、人口密度数据、夜间灯光数据、路网数据和土地利用类型数据，采用Theil-Sen Median趋势分析和Mann-Kendall显著性检验等方法，结合地理探测器，在多时空尺度上分析成渝城市群PM_2.5时空变化，并探测影响其变化的驱动机制.结果表明，2000～2021年成渝城市群PM_2.5浓度整体呈波动下降态势，冬季PM_2.5污染最为突出.PM_2.5浓度具有明显的空间异质性，呈现出“中间高，四周低”的空间分布特征，PM_2.5浓度高值区主要集中在自贡、内江、资阳和广安，PM_2.5浓度呈显著下降的区域主要集中在重庆西部等地.因子探测结果表明，成渝城市群PM_2.5浓度空间分异受气候、地形、植被和人文因子共同影响.高程、...