整数规划用于固废系统环境影响模型的研究

采用整数线性规划的系统分析方法建立模型,以整数规划解决运输路线及处理方式扩容方案的选择问题,以系统经济成本为优化目标,并着重考虑了运输过程产生的3种恶臭气体扩散对周围特殊区域造成的环境影响,优化固体废弃物运输路线.结果表明:不同时期不同的垃圾回收站适合回收的垃圾类别不同;不同时期不同回收站的运输路线最优选择不同;垃圾填埋处理由于处理费用低,一直是垃圾处理的优选方案,但热解处理量较大,增长幅度最大,且运输处理总费用最低,从长远看,热解厂的未来发展趋势较好;该模型能够有效解决城市固体废弃物系统资源优化配置问题,为决策者提供可靠的依据.     

北京市2014~2020年PM2.5和O3时空分布与健康效应评估

细颗粒物（PM_2.5）和臭氧（O₃）是我国的主要大气污染物,严重危害人群健康.北京市自2013年以来大力开展大气污染治理工作,现已取得显著成效.通过分析2014~2020年北京市34个大气环境监测站的PM_2.5和O₃浓度变化特征并评估大气污染防治的健康效应,对推进大气污染防治具有重要意义.结果表明,2014年北京市PM_2.5年均值和4~9月平均O₃日最大小时（O_{3_max}）值分别为92.0 μg·m^-3和81.9 nmol·mol^-1.2014~2020年PM_2.5平均每年降低7.5 μg·m^-3,但是O_{3_max}持续偏高.在季节尺度,冬季的12月和1月PM_2.5浓度最高,夏季的8月浓度最低.相反地,O_{3_max}在每年6月浓度最高.PM_2.5浓度日变化规律为,夜间22：00至次日00：00最高,14：00~16：00最低.而O₃浓度在07：00最低,随后逐步升高并在午后达到最高.在空间分布上,PM_2.5在2014和2019年都呈现南高北低的趋势,O_{3_max}在全市范围内均较高,仅在道路区域偏低.大气污染对人群健康影响的评估结果表明,2014年北京市与PM_2.5相关的心血管和呼吸道疾病超额死亡人数分别为1580人和821人,与O₃相关的呼吸道疾病超额死亡人数为2180人.2019年与PM_2.5相关的超额死亡人数仅为2014年的50%,而与O₃相关的超额死亡人数与2014年持平.北京市细颗粒物治理成效显著,但是O₃污染问题凸显,O₃已经成为危害北京市居民健康的首要大气污染物.未来需要加强PM_2.5和O₃协同治理.     

Impact assessment of a hydroelectric project on the flora in the Western Himalayan region based on vegetation analysis and socio-economic studies

This study provides an overview of the impacts of a proposed hydroelectric power project in the Western Himalayan region in India, using a primary database on floristic diversity and vegetation analysis. The remote sensing data revealed that in the submergence zone only mixed deciduous forest that occupies 807.5 ha area and has a wood biomass volume of 4,027,503 m³ is likely to be lost due to impoundment. A total of 165 plant species found in the submergence zone also occur in the influence and free draining catchment area of the project. In the influence zone of the project area only one tree species (Acer oblongum) is found under conservation threat category, which is also present in the free draining catchment of the project. The project affected population (6716 people) residing in the submergence and influence zone depend upon the surrounding forests for fuel wood, fodder, wild edibles etc., and most likely they will settle in the nearby areas, thus mounting more pressure on residual forests of the influence zone for various forest products. Further, from the vegetation analysis it is evident that several tree species (e.g. Lannea coromandelica, Terminalia alata, T. bellerica etc.), may face more pressure from exploitation as they provide a number of useful products and are represented in lower numbers in the forests of the project area. To compensate for the loss of various goods and services provided by the forests falling in the submergence zone and to offset the increased pressure of the project affected families on the forests of influence zone, a biodiversity management plan is suggested incorporating socio-economic considerations.     

Rewriting the Plot: Sustaining allotments in the UK and Japan

In the search for a model form of allotment garden in the late 1980s, capable of absorbing surplus farmland while sustaining the capacity of the land to support agriculture, Japanese experts rejected the UK allotment, which was perceived to be of low status and in decline, in favour of the German Kleingarten. This paper suggests that it may be time to reconsider the UK experience, in the light of subsequent moves to rewrite the image and practice of allotment gardening in the UK within the local sustainable development agenda, and the problems which the Japanese version of the Kleingarten model has encountered in the changed economic circumstances of the 1990s.     

Assessing sensitivities of marine areas to stressors based on biological traits

Analysis of the biological traits (e.g., feeding mode and size) that control how organisms interact with their environment has been used to identify environmental drivers of, or impacts on, species and to explain the importance of biodiversity loss. Biological trait analysis (BTA) could also be used within risk-assessment frameworks or in conservation planning if one understands the groups of traits that predict the sensitivity of habitats or communities to specific human activities. Deriving sensitivities from BTA should extend sensitivity predictions to a variety of habitats, especially those in which it would be difficult to conduct experiments (e.g., due to depth or risk to human life) and to scales beyond the norm of most experiments. We used data on epibenthos, collected via video along transects at 27 sites in a relatively pristine region of the seafloor, to determine scales of natural spatial variability of derived sensitivities and the degree to which predictions of sensitivity differed among 3 stressors (extraction of species, sedimentation, and suspended sediments) or were affected by underlying community compositions. We used 3 metrics (weighted abundance, abundance of highly sensitive species, and number of highly sensitive species) to derive sensitivity to these stressors and simulated the ability of these metrics to detect a range of stressor intensities. Regardless of spatial patterns of sensitivities across the sampled area, BTA distinguished differences in sensitivity to different stressors. The BTA also successfully separated differences in community composition from differences in sensitivity to stressors. Conversely, the 3 metrics differed widely in their ability to detect simulated impacts and likely reflect underlying ecological processes, suggesting that use of multiple metrics would be informative for spatial planning and allocating conservation priorities. Our results suggest BTA could be used as a first step in strategic prioritization of protected areas and as an underlying layer for spatial planning.