Soil erosion vulnerability under scenarios of climate land-use changes after the development of a large reservoir in a semi-arid area

Climate and land-use/cover changes (LUCC) influence soil erosion vulnerability in the semi-arid region of Alqueva, threatening the reservoir storage capacity and sustainability of the landscape. Considering the effect of these changes in the future, the purpose of this study was to investigate soil erosion scenarios using the Revised Universal Soil Loss Equation (RUSLE) model. A multi-agent system combining Markov cellular automata with multi-criteria evaluation was used to investigate LUCC scenarios according to delineated regional strategies. Forecasting scenarios indicated that the intensive agricultural area as well as the sparse and xerophytic vegetation and rainfall-runoff erosivity would increase, consequently causing the soil erosion to rise from 1.78 Mg ha^?1 to 3.65 Mg ha^?1 by 2100. A backcasting scenario was investigated by considering the application of soil conservation practices that would decrease the soil erosion considerably to an average of 2.27 Mg ha^?1. A decision support system can assist stakeholders in defining restrictive practices and developing conservation plans, contributing to control the reservoir's siltation.     

Assessing field vulnerability to phosphorus loss in Beijing agricultural area using Revised Field Phosphorus Ranking Scheme

Guanting Reservoir,one of the drinking water supply sources of Beijing,suffers from water eutrophication.It is mainly supplied by Guishui River.Thus,to investigate the reasons of phosphorus(P)loss and improve the P management strategies in Guishui River watershed are important for the safety of drinking water in this region.In this study,a Revised Field P Ranking Scheme(PRS)was developed to reflect the field vulnerability of P loss at the field scale based on the Field PRS.In this new scheme,six factors are included, and each one was assigned a relative weight and a determination method.The affecting factors were classified into transport factors and source factors,and,the standards of environmental quality on surface water and soil erosion classification and degradation of the China were used in this scheme.By the new scheme,thirty-four fields in the Guishui River were categorized as"low","medium"or"high"potential for P loss into the runoff.The results showed that the P loss risks of orchard and vegetable fields were higher than that of corn and soybean fields.The source factors were the main factors to affect P loss from the study area.In the study area,controlling P input and improving P usage efficiency are critical to decrease P loss.Based on the results,it was suggested that more attention should be paid on the fields of vegetable and orchard since they have extremely high usage rate of P and high soil test of E Compared with P surplus by field measurements,the Revised Field PRS was more suitable for reflecting the characteristics of fields,and had higher potential capacity to identify critical source areas of P loss than PRS.     

Predicting RUSLE (Revised Universal Soil Loss Equation) Monthly Erosivity Index from Readily Available Rainfall Data in Mediterranean Area

Summary Seasonal rainerosivity is important in the structure and dynamics of Mediterranean ecosystems. The present paper contributes to the quantitative assessment of RUSLE's monthly erosion index in a data-scarce Mediterranean region. Therefore, a regionalized relationship for estimating monthly erosion index (EI_30-month) from only three rainfall parameters has been obtained. Knowledge of the seasonal and annual distribution of erosivity index, permit soil and water conservationists to make improved designs for erosion control, water harvesting or small hydraulic structures. Although a few long data sets were used in the analysis, validation with established monthly erosivity index values from other Italian locations, suggest that the model presented (r² = 0.973) is robust. It is recommended to monthly erosivity estimates when experimental data-scarce rainfall become available.     

基于Revised IMPROVE方法和MIE方法计算北京地区气溶胶消光系数的对比分析

目的对比分析IMPROVE方程的改进算法(Revised IMPROVE)和MIE方法在北京地区计算消光系数的适用性。方法基于2012年6月3日至6月30日北京地区大气颗粒物成分的浓度观测数据,分别采用Revised IMPROVE和MIE方法计算颗粒物的消光系数,其中MIE方法的粒径分布采用总量双峰分布体积谱和化学组分体积谱两种方案进行循环试验获取最优拟合结果,使用散射积分浊度计和黑碳仪的实测数据对计算结果进行对比分析。结果 RevisedIMPROVE方程、总量双峰体积谱MIE方法和化学组分体积谱MIE方法都能较好地计算出了大气颗粒物消光系数,与观测结果回归方程的相关系数R分别达到0.952、0.9686和0.9734。体积谱分布参数的循环试验方法还同时可以获得气溶胶的体积谱分布参数,总量双峰体积谱和化学组分体积谱MIE方法得到的细颗粒和粗颗粒几何平均粒径分别为0.74、7.5μm和0.48、6.0μm。结论采用化学组分体积谱MIE方法计算的消光系数与观测结果最为接近,Revised IMPROVE方程也有较好的准确性,采用化学组分体积谱MIE方法得到的颗粒物体积谱峰值与实际观测结果也较为一致。     

Trends and sources of particulate matter in the Superstition Wilderness using air trajectory and aerosol cluster analysis

Ambient aerosols adversely affect human health and visibility and impact climate. Identification of sources of particulate matter and its precursors is necessary for developing control strategies. The goal of this research is to utilize long-term speciated particulate matter data and back-trajectory cluster analyses to determine trends and sources of particulate matter in the Superstition Wilderness, a rural area east of Phoenix, Arizona. Twenty-four hour back-trajectories were calculated for every hour of every 24-h particulate matter sample obtained by IMPROVE from 1991 to 2004. Days that included back-trajectories with considerable spatial variance were excluded from further analyses. To minimize uncertainties inherent in single trajectories, all calculated trajectories for each sampling day were averaged to represent the air mass sampled during that day. Cluster analysis of trajectories identified four unique regions, including a region with Phoenix, a region with copper smelters, and one with coal-fired power plants. Yearly averages of sulfate, nitrate, soil, and carbon concentrations were calculated for each region. Statistically significant trends in species concentrations by region and independent of region and differences in concentrations between regions were examined.Sulfate concentrations from the region with smelters were higher than other regions but decreased during the study period. Emissions data from the smelters indicate that much of the sulfate from the region was due to the smelters. The overall 2.2% year⁻¹ decrease in sulfate concentrations at TNM is likely due to decreased emissions from the copper smelters. A 3.6% year⁻¹ increase in nitrate concentrations was driven largely by increasing NO_x concentrations from Phoenix and to a lesser extent the region southwest of the site which includes Tucson and suburban/urban areas between Phoenix and Tucson. Soil concentrations were higher from regions with deserts than the region without desert. This method could not identify trends or source regions of carbonaceous aerosols at this site.     

浅谈油烟的危害以及相关标准的修订

伴随着经济的繁荣和人民物质生活质量的提高,餐饮业日益繁荣起来,再结合中国素来"民以食为天",传统饮食文化的特殊性及复杂性,导致烹饪过程复杂,同时也带来了各种各样的油烟污染问题。油烟已经成为继噪声、尾气、沙尘之后的又一大污染问题,并且成为百姓环保投诉的热点问题之一。《饮食业油烟排放标准》(GB18483-2001)是目前我国环保行业监测饮食业油烟的唯一标准方法,在实际工作中存在一定的局限性和不完备性,对现行标准进行修订势在必行。     

水土保持生态补偿定量计算探究 ——以潘家口库区东北沟流域为例

水土保持生态补偿对于我国的水土流失治理意义重大,水土保持补偿标准的确定是建立生态补偿机制的核心问题。基于潘家口水库上游东北沟流域1990年和2009年土地利用数据和气候、 土壤、 植被、 DEM及农户调查等数据,应用通用土壤侵蚀方程模型(RUSLE)计算该流域采取预防水土流失措施后的土壤侵蚀减少量,在此基础上采用环境经济学的方法核算水土保持生态功能的提供方和受益方两个主体的成本和收益,并构建了水土保持生态补偿标准计算模型,实现了水土保持生态补偿标准定量计算。结果显示:流域生态系统的年土壤保持量为6.49×10⁴ t·a^-1;水土保持服务提供方损失为24.48×10⁴元,所得收益来自减少土地损失和肥力损失的价值共计44.21×10⁴元;水土保持服务受益方主要指下游潘家口水库所得收益来自减少泥沙淤积和减少富营养化共计84.88×10⁴元;流域所得的补偿介于24.48×10⁴元(222.55元/人)到46.90×10⁴元(426.36元/人)之间。     

Humidity and PM2.5 composition determine atmospheric light extinction in the arid region of northwest China

Atmospheric visibility can directly reflect the air quality. In this study, we measured water-soluble ions (WSIs), organic and element carbon (OC and EC) in PM_2.5 from September 2017 to August 2018 in Urumqi, NW China. The results show that SO₄^2?, NO₃^? and NH₄⁺ were the major WSIs, together accounting for 7.32%–84.12% of PM_2.5 mass. Total carbon (TC=OC+EC) accounted for 12.12% of PM_2.5 mass on average. And OC/EC > 2 indicated the formation of secondary organic carbon (SOC). The levels of SO₄^2?, NO₃^? and NH₄⁺ in low visibility days were much higher than those in high visibility days. Relative humidity (RH) played a key role in affecting visibility. The extinction coefficient (b_ext) that estimated via Koschmieder formula with visibility was the highest in winter (1441.05 ± 739.95 Mm^?1), and the lowest in summer (128.58 ± 58.00 Mm^?1). The b_ext that estimated via IMPROVE formula with PM_2.5 chemical component was mainly contributed by (NH₄)₂SO₄ and NH₄NO₃. The b_ext values calculated by both approaches presented a good correlation with each other (R² = 0.87). Multiple linear regression (MLR) method was further employed to reconstruct the empirical regression model of visibility as a function of PM_2.5 chemical components, NO₂ and RH. The results of source apportionment by Positive Matrix Factorization (PMF) model showed that residential coal combustion and vehicle emissions were the major sources of b_ext.     

北京城区不同组分PM2.5散射特性及来源分析

近年来北京城区PM_2.5浓度下降伴随其中二次离子占比升高,为探索不同组分PM_2.5散射特性及其来源,于2020年12月至2021年11月开展了小时分辨率的PM_2.5及其组分浓度和散射系数的连续在线监测,分析了PM_2.5组分及散射的特征和来源.结果表明,研究期间北京城区PM_2.5最主要组分为NO^-₃,PM_2.5中ω(NO^-₃)和ω(SNA)分别为24%和46%.根据浓度和组分占比将PM_2.5划分为6种类型：优型出现频率最高,为56%,四季分布均匀,PM_2.5中ω(SNA)、ω(OM)和ω(FS)相当,分别为32%、 32%和28%;沙尘(D)型和OM(O)型全年出现频率较低,分别以FS和OM为主要组分,PM_2.5中ω(FS)和ω(OM)分别为66%和46%,主要分布于春季和夏季;OM+SO₄     

基于GIS和RUSLE的三峡库区小流域土壤侵蚀量估算研究

本研究以三峡库区菱角塘小流域为研究对象,在GIS技术的支持下,通过遥感技术和野外调查进行信息采集,对修正的通用土壤流失方程(RUSLE)各因子进行量化分析,从而对三峡库区菱角塘小流域土壤侵蚀量进行定量评价,并对土壤侵蚀强度进行分级;在此基础上分析不同坡度和土地利用类型的土壤侵蚀空间分布特征。结果表明,菱角塘小流域年土壤侵蚀量为208.32t/a,土壤侵蚀模数为1 987.75t/(km2·a),属于轻度侵蚀。28.62%的区域为中度、强度或极强度侵蚀,但是其侵蚀量却占总侵蚀量的82.36%,是预防和加强水土流失治理的重点区域。土壤侵蚀主要发生在坡度为15°~35°的区域,其中15°~25°的坡度土壤侵蚀属于中度侵蚀;坡耕地侵蚀最为严重,15°~25°的坡耕地侵蚀量占总侵蚀量的57.15%,表明坡耕地是该小流域水土流失的主要策源地。同时用137 Cs核素示踪技术测定的坡耕地和林地土壤侵蚀模数证实了RUSLE模型具有较高的准确性和可靠性,该模型在库区地块尺度具有一定的推广价值。