Nutrients and suspended solids in dry weather and storm flows from a tropical catchment with various proportions of rural and urban land use

The results of an investigation characterizing the nutrients and suspended solids contained in stormwater from Kranji Catchment in Singapore are reported in this paper. Stormwater samples were collected from 4 locations and analyzed for the following eleven analytes: TOC, DOC, TN, TDN, NH₄⁺, NO₂⁻ + NO₃⁻ (NO_x), TP, TDP, OP, SiO₂ and TSS. Stormwater was sampled from catchments with various proportions of rural and urban land use, including forested areas, grassed areas, agricultural and residential and commercial areas. The event mean concentrations (EMCs) of nutrients and TSS from sampling stations which have agricultural land use activities upstream were found to be higher. Comparison of site EMCs (SMCs) with published data showed that the SMCs of the nutrients and TSS are generally higher than SMCs reported for forested areas but lower than published SMCs for urban areas. Positive correlations (p < 5%) were found between loading and peak flow at locations most impacted by ubanisation or agricultural activities. Correlation between loading and rainfall variables was less distinct. EMC was found to correlate less with rainfall and flow variables compared to pollutant loading. Unlike loading, no consistent pattern exists linking EMC to any particular storm or flow variable in any of the catchments. Lastly, positive correlations were obtained between the particulate forms of nitrogen and phosphorus and TSS.     

基于L-THIA模型的四川省濑溪河流域非点源污染负荷分析

非点源污染是造成流域水环境恶化的重要原因之一,掌握非点源污染的时空分布特征是流域水环境污染防治和流域综合管理的基础性工作.为落实国家《水污染防治行动计划》,四川省启动了濑溪河等流域综合治理达标方案编制工作,探明濑溪河流域非点源污染负荷及其分布特征是该方案编制的前提.以四川省境内濑溪河流域为研究区域,基于GIS（地理信息系统）,利用L-THIA（long-term hydrologic impact assessment,长期水文影响评价）模型,基于2015年土地利用地图数据、土壤水文数据以及长时间序列（2009—2014年）逐日降雨数据,调整模型参数,使模型模拟径流量符合水文站监测数据,进而模拟2014—2015年流域内的非点源污染负荷空间分布.L-THIA模型模拟得到濑溪河流域径流量约为5.10×108 m3,和控制水文站实测径流量相比,模型模拟相对误差为5%,表明模型模拟质量较好,模拟结果可信度较高.结果表明,流域内TP、NH₃-N、COD_Cr非点源污染负荷分别为204.10、353.12、5 162.53 t;农业用地对研究区的非点源污染影响最大,林地最小;根据濑溪河水系分布特点将研究区划分为16个控制单元,各控制单元TP、NH₃-N、COD_Cr的空间分布特征及比例相似,研究区非点源污染平均负荷强度为3.72 t/km2,TP、NH₃-N、COD_Cr的输出范围分别为（0.08~0.15）（0.14~0.27）（2.19~3.89）t/km2.研究显示,流域非点源污染产生量的估算和空间分布特征的揭示为编制濑溪河流域水污染治理方案提供了科学参考.      

降水和风对苏州地区PM2.5浓度影响分析

为了解降水和风对苏州地区细颗粒物（PM_2.5）质量浓度的影响,利用2018—2022年逐日降水量、风向风速和环境空气质量数据,分析苏州市降水和ρ PM_2.5）的月变化特征及日降水强度、降水时长和风向风速对ρ（PM_2.5）变化的作用。结果表明,降水对PM_2.5存在一定湿清除作用,全年雨日ρ（PM_2.5）平均值较非雨日低21%,1—2月和11—12月最为显著。降水的湿清除效率受日降水量级和日降水时长等因素的影响,当日降水量达到中雨及以上量级时,ρ（PM_2.5）下降样本数超过总样本数的60%,降水的湿清除效率随着降水量级的增加而显著提高;当日降水时长＞6 h时,降水对污染物浓度的改善作用明显,ρ（PM_2.5）下降样本数超过总样本数的50%。不同风向、风速的清除作用也有差异,静风或微风状态下,高温高湿的西南风最易造成苏州地区的霾污染;当西北风速＞4m/s时,受到冷锋前的污染气团南下扩散影响,ρ（PM_2.5）升高;对于东北风、西南风和东南风这3个风向,当风速达到5m/s时,对污染物具有有效的干清除作用。