Spatial analysis of resources and environmental carrying capacity in Iran

Urbanization and mass movement of the population from rural areas and small cities to megacities have led to environmental, economic, and social problems in Iran. In dealing with these challenges, assessing resource and environmental carrying capacity (RECC) is considered an effective method to leverage space and capital to achieve sustainable development. This study aimed to rank the provincial RECC in Iran. Toward this purpose, environmental indices were generated from remotely sensed and statistical census data. Then, the provinces were scored in terms of environmental, economic, and infrastructural carrying capacities, and RECC using the mean variance analysis method. Results demonstrated that in most areas, there is no relationship between economic and infrastructural capacities and development. Statistically, a correlation coefficient of −0.53 between economic and environmental carrying capacities indicated excessive use of environmental capacities. Moreover, the spatial distribution pattern of environmental, economic, and infrastructural carrying capacity was entirely heterogeneous between the provinces; there was a northeast–southwest pattern in terms of infrastructural capacity and an economic pattern from north to south. The distribution pattern of RECC is most consistent with the environmental capacity, pointing at the high weight of the indicators of the RECC model. In conclusion, this research offers a new vision for policymakers and provides a theoretical and applicable framework for implementing sustainable strategies in land-use planning. It is recommended that the RECC concept and tools can be used not only for planning but also for measuring the efficiency of spatial development programs and establishing land balances in the region.     

Temporal trends in agricultural water use and the relationships to hydroclimatic factors in the High Plains aquifer region

The High Plains aquifer (HPA) is the primary water source for agricultural irrigation in the US Great Plains. The water levels in many locations of the aquifer have declined steadily over the past several decades because the rate of water withdrawals exceeds recharge, which has been a serious concern to the water resources management in the region. We evaluated temporal trends and variations in agricultural water use and hydroclimatic variables including precipitation, air temperature, reference evapotranspiration, runoff, groundwater level, and terrestrial water storage across the HPA region for different periods from 1985 to 2020 at the grid, county, or region scale. The results showed that water withdrawals decreased from 21.3 km³/year in 1985 to 18.2 km³/year in 2015, while irrigated croplands increased from 71,928 km² in 1985 to 78,464 km² in 2015 in the entire HPA. The hydroclimatic time-series showed wetting trends in most of the northern HPA, but drying and warming trends in the southern region from 1985 to 2020. The groundwater level time-series indicated flat trends in the north, but significant declining in the central and southern HPA. Trends in irrigation water withdrawals and irrigation area across the HPA were controlled by the advancement of irrigation systems and technologies and the management of sustainable water use, but also were affected by dynamical changes in the hydroclimatic conditions.     

基于地理探测器的土壤重金属影响因子分析及其污染风险评价

地理探测器能快速定量化揭示驱动重金属含量影响因素的强度,这对于重金属空间预测模型构建变量的确定和土壤污染修复措施的精准实施具有重要意义。利用地理探测器模型,对5种土壤重金属元素Cu、Zn、Pb、Cr、Ni的空间分布和11种环境因子的交互作用进行定量评估,通过单因子指数法进行重庆市土壤重金属污染风险评价。结果表明:研究区内土壤Cu、Zn、Cr和Pb的平均含量是重庆市土壤背景值的1.3—1.4倍,Ni含量低于背景值;其中Cu、Pb达到重度污染水平,其余3种重金属为中度或轻度污染水平。5种重金属元素中Cu和Pb为高度变异(变异系数为0.57、0.4),Zn、Cr和Ni为中等变异(变异系数为0.22—0.29),且各重金属元素之间呈显著正相关性,表明研究区重金属富集受人为干扰影响较大,且污染具有复合性或同源性。地理探测器的因子探测发现高程、坡度和土壤类型对5种土壤重金属含量的解释力最显著,说明地势和土壤类型是土壤重金属含量分布差异的最主要影响因素。交互作用探测发现,高程与其他因子交互作用是重金属空间分异的主导因素,气候条件和土壤类型也是重要影响因子。土壤重金属空间分布是多种因素共同作用的结果,而高程、坡度和土壤类型具有较强的解释力,这些因子可作为土壤重金属含量空间预测模型的辅助变量,也可促进重金属污染治理措施的靶向实施。     

A framework for allocating conservation resources among multiple threats and actions

Land managers decide how to allocate resources among multiple threats that can be addressed through multiple possible actions. Additionally, these actions vary in feasibility, effectiveness, and cost. We sought to provide a way to optimize resource allocation to address multiple threats when multiple management options are available, including mutually exclusive options. Formulating the decision as a combinatorial optimization problem, our framework takes as inputs the expected impact and cost of each threat for each action (including do nothing) and for each overall budget identifies the optimal action to take for each threat. We compared the optimal solution to an easy to calculate greedy algorithm approximation and a variety of plausible ranking schemes. We applied the framework to management of multiple introduced plant species in Australian alpine areas. We developed a model of invasion to predict the expected impact in 50 years for each species-action combination that accounted for each species’ current invasion state (absent, localized, widespread); arrival probability; spread rate; impact, if present, of each species; and management effectiveness of each species-action combination. We found that the recommended action for a threat changed with budget; there was no single optimal management action for each species; and considering more than one candidate action can substantially increase the management plan's overall efficiency. The approximate solution (solution ranked by marginal cost-effectiveness) performed well when the budget matched the cost of the prioritized actions, indicating that this approach would be effective if the budget was set as part of the prioritization process. The ranking schemes varied in performance, and achieving a close to optimal solution was not guaranteed. Global sensitivity analysis revealed a threat's expected impact and, to a lesser extent, management effectiveness were the most influential parameters, emphasizing the need to focus research and monitoring efforts on their quantification.     

北京市典型废弃物焚烧源2010—2017年二NFDA1英排放特征和减排效果分析

分析2010—2017年北京市三类典型废弃物焚烧源的废气二NFDA1英排放监测数据,计算排放因子和排放量,评估减排政策成效,并分析不同排放源达标排放时同类物分布特征异同和变化规律,探讨影响排放的重要因素。结果表明: 5家焚烧源平均排放浓度为 0.008～0.069 ng/m³(以TEQ计,下同),废气二NFDA1英排放因子为 0.027～1.7 μg/t,2016年向空气中排放的二NFDA1英量为 0.002 5～0.058 g；生活垃圾、危险废物和医疗废物焚烧源的低、高氯代同类物质量分数比的平均值分别为接近于 0.5、大于0.5和小于0.5,危险废物焚烧源的 ∑PCDFs、∑PCDDs质量分数比的平均值大于2； 123478-HxCDF和123678-HxCDF质量浓度接近且线性相关,具有相近的生成机理和去除效率； I-TEQ变化趋势与∑PCDFs质量分数的变化趋势基本一致,活性炭喷射和布袋除尘的去除效率是影响二NFDA1英排放的重要因素之一；危险废物焚烧源HWI1随运行时间增加排放浓度增加,而及时更换烟道管壁有助于消除“记忆效应”的不良影响。     

A proactive process risk assessment approach based on job hazard analysis and resilient engineering

Complex systems often experience a long period of incubation before accidents occur. Therefore, a proactive risk assessment is essential for process safety. The conventional job hazard analysis (JHA) method has been an effective tool to conduct a process risk assessment in the high-risk industrial field. However, the conventional JHA is inadequate for the proactive risk assessment since it is usually conducted during and before one specific operation process. Operations such as startup and maintenance are performed repeatedly on the lifecycle of a plant. Therefore, the risk reduction measures for the industrial process should include not only preventive actions obtained from the conventional JHA but also recovery ones. Resilience engineering (RE) has proven to be helpful for the recovery analysis of a complex system. The objective of this paper is to propose a proactive and comprehensive process risk assessment approach based on JHA and RE. The mechanism of applying RE to address operation process risk is illustrated. The integrated approach can provide guidelines to establish proactive risk reduction measures as well as maintain a low-risk level. Finally, a gas transmission startup process risk assessment case is presented to demonstrate its applicability.     

夏季渭河西安段溶解性有机质(DOM)的特征、分布及来源分析

通过紫外吸收光谱,三维荧光光谱结合平行因子分析(EEMs-PARAFAC)方法及主成分分析(PCA),研究了夏季渭河西安段水体中的溶解性有机质(DOM)的组成、来源,及其与水质指标的相关性.在研究区域共检出2种类别5个不同的DOM组分,分别为类腐殖质荧光组分C1、C2、C3、C5和1个类蛋白类荧光组分C4,5个组分具有同源性.对比分析光谱斜率S、SUVA₂₅₄、α355和DOC浓度,上游(S1—S5)和下游(S13—S17)各组分分子量和腐殖化程度接近但来源有所差异,中游(S6—S12、S18—S19)分子量和腐殖化程度最低;研究区域DOM和CDOM浓度值变化基本保持一致.通过三维光谱参数和主成分分析进行DOM源解析,内源贡献率为72.36%,外源贡献率为12.45%,累计方差贡献率为84.81%;污废水排放是组分C1、C4的主要来源,C2、C3、C5则来源于城市景观水体和湿地公园中微生物和浮游动植物的活动产生,TN与外源具有较好的相关性而TP与内源相关性较高.水质指标DO、DOC、COD、TN、TP与DOM组分有较强的相关性.在此基础上建立了多元线性回归方程,一定程度上能够利用荧光组分组成和特征反映渭河夏季的水质状况.     

基于共词分析的城市生活垃圾治理公共政策变迁量化分析

以1979—2020年我国中央政府颁发的411份城市生活垃圾治理政策文本作为研究对象,运用共词与聚类分析方法研究了我国不同时期城市生活垃圾治理公共政策焦点的演变规律。结果发现:纵观我国城市生活垃圾治理公共政策焦点的演变轨迹,在"技术路线"、"垃圾属性"、"管理手段"、"治理结构"和"保障机制"方面发生了显著的政策主题变迁,呈现出垃圾治理朝更加绿色、更加经济方向发展的趋势。未来,应从监管体系、资源评估、财政补贴、空间布局4个方面保障生活垃圾零污染、高价值资源化治理。     

磺胺氯哒嗪在海水中的间接光降解

以有色溶解有机物(CDOM)作为主要光敏剂研究磺胺氯哒嗪(SCP)间接光降解行为和机理,分析CDOM组成、盐度和pH值对SCP间接光降解的影响.SCP间接光降解速率随CDOM浓度升高而逐渐加快.CDOM产生的光化学反应活性中间体对SCP间接光降解的贡献率不同,其中³CDOM^*起主要作用,对SCP间接光降解的贡献率高达77.94%.所用CDOM由4种荧光组分组成,包含3种外源腐殖质(C1,C2,C3)和1种内源腐殖质(C4), SCP间接光降解去除率和³CDOM^*浓度分别与荧光组分的相关性大小顺序均为C3>C2>C4>C1.其中C3和C2与[³CDOM^*]具有较高线性相关性(R²>0.97),是³CDOM^*的主要贡献者.盐度和pH值对SCP间接光降解的影响作用显著.在盐度为15‰时,SCP的间接光降解速率最大.在低盐度范围(0~15‰)内,离子强度效应对间接光降解的促进作用大于无机阴离子带来的抑制作用,使得间接光降解速率随着盐度的升高而加快.溶液pH=(5.00±0.10)时,SCP的间接光降解速率最大.SCP的间接光降解速率随着溶液pH值的升高而减慢,中性和碱性环境不利于SCP的间接光降解.     

砷尾矿污染土壤的细菌群落结构多样性及其相关环境影响因子分析

以湖南石门雄黄尾矿污染土壤为对象,研究纵向不同深度、横向不同距离土样中的重金属污染程度以及细菌群落结构变化规律,查明砷污染土壤的核心微生物组成并将其与土壤理化指标进行共存网络图分析。结果表明:该尾矿区的土壤各项重金属指标严重超标,尤以铅(626.54 mg·kg^?1,Ei=105.48)、砷(1804.75 mg·kg^?1,Ei=565.75)、镉(31.46 mg·kg^?1,Ei=7491.5)的生态危害性最强;土壤采样深度与重金属综合潜在生态风险指数(RI)呈显著正相关(r=0.79,P=0.000),而横向样品中RI与采样距离显著负相关(r=?0.85,P=0.000)。在污染土壤中,变形杆菌门(Proteobacteria,54.35%±17.16%)和放线杆菌门(Actinobacteria,22.39%±10.64%)占主导地位,属层级中假单孢杆菌属(Pseudomonas,16.47%±11.84%)、不动杆菌属(Acinetobacter,8.07%±7.11%)以及硫酸状杆菌属(Acidithiobacillus,7.53%±14.68%)相对丰度较高;而26个共享类群占据了该尾矿污染土壤中微生物群落总平均相对丰度90%以上,尽管不同属的具体相对丰度在不同样品间的分布趋势差异较大。纵剖采集的污染土样中,铁原体属(Ferroplasma)、硫酸状杆菌属(Acidithiobacillus)、硫化杆菌属(Sulfobacillus)、乳杆菌属(Lactobacillus)和硝化螺旋菌属(Nitrospira)占优势,与理化的共存网络图分析(相关系数|r|≥0.6,P<0.05)显示部分类群与亚铁、游离态砷和镉成显著正相关,而与pH成显著负相关;横向采集的土样中,以嗜酸菌属(Acidiphilium)、假单孢杆菌属(Pseudomonas)、棒状杆菌属(Corynebacterium)、硫杆菌属(Thiobacillus)等为主,部分类群与总砷、铅成显著正相关,而与结合态或包蔽型砷成显著负相关。综上,该研究不仅对目标区域尾矿不同重金属污染程度进行了分析,同时探讨了污染土壤中核心响应类群的组成多样性,为筛选潜在重金属抗性菌群或工程菌群提供理论基础。