新型伞形罩烟气洗涤器的性能研究

针对中小型燃煤锅炉的粉尘和二氧化硫等有害气体的污染问题,开发出一种新型伞形罩烟气洗涤器。以粉煤灰、空气和水为物系,测试了伞形罩烟气洗涤器的压降(ΔP)、除尘效率和动力消耗。实验的入口气速为10～18m/s,含尘浓度为2～22g/m3,液气比(L/G)0～0.8L/m3。结果表明:伞形罩洗涤器的ΔP较小,在250～750Pa范围内;当L/G为0.2L/m3时,除尘效率达98.8%以上,动力消耗约0.06×10-3kW.h/m3(气体约216Pa),实现节能高效的目的。     

清洁生产:由生产领域扩展至消费领域——结合《中华人民共和国清洁生产促进法》相关规定评析之

本文通过分析清洁生产和消费的含义,指出清洁生产的调整范围包括消费环节.我国《清洁生产促进法》的内容体现了清洁生产从生产领域扩展到消费领域这一新动向.本文论证了这一新发展的正当性和合理性,最后结合具体法条进行分析,指出相关制度手段和意义所在.     

促进农村居民消费需求扩张的对策分析

通过对影响我国农村居民消费需求不足的原因分析，认为我国农村居民收入水平偏低且增长缓慢是导致需求不足的关键因素。此外商品有效供给不足、农村的消费观念、消费环境和农村居民的文化素质也在一定程度上影响了农村居民的消费需求。     

入世带来的环境压力及其对策探讨

入世给我国带来了一定的环境压力,主要表现在资源消耗、污染进口和产业冲击三方面.外商投资增长及外国人入境消费可能引起资源过度消耗,环境风险较大的项目和危险废弃物也可能乘机而入.受国外环保产业和环保服务业的冲击,我国相关产业面临严峻挑战.现阶段,我国的法规标准和公众意识是影响入世所带来的环境压力的两个重要因素.缓解环境压力的举措需要遵循两个原则:制度改革和管理改革结合的原则;短期措施和长期战略结合的原则.     

能源安全工程研究体系探讨

随着矿物能源开采消耗量的急剧增加,煤炭开采安全、能源开采和消耗引起的生态环境改变及破坏、世界石油市场油价波动对经济增长的不利影响、水电等可再生能源所占比重较低等,构成了制约可持续发展的能源安全问题。能源安全工程研究体系由区域能源开发消费安全、合理能源结构和消费布局、能源安全战略及相关法律法规等研究内容组成。通过分层次研究和循环促进,开展能源安全战略、能源安全技术、能源生态关系、能源安全经济的系统研究,为科学解决能源安全问题、实现国家或区域社会经济的可持续发展,提供了理论支持和科技保障。     

Understanding the distribution of bushmeat hunting effort across landscapes by testing hypotheses about human foraging

Mitigating the massive impacts of defaunation on natural ecosystems requires understanding and predicting hunting effort across the landscape. But such understanding has been hindered by the difficulty of assessing the movement patterns of hunters in thick forests and across complex terrain. We statistically tested hypotheses about the spatial distribution of hunting with circuit theory and structural equation models. We used a data set of >7000 known kill locations in Guyana and hunter movement models to test these methods. Comparing models with different resistance layers (i.e., different estimates of how terrain and land cover influence human movement speed) showed that rivers, on average, limited movement rather than serving as transport arteries. Moreover, far more kills occurred close to villages than in remote areas. This, combined with the lack of support for structural equation models that included latent terms for prey depletion driven by past overhunting, suggests that kill locations in this system tended to be driven by where hunters were currently foraging rather than by influences of historical harvest. These analyses are generalizable to a variety of ecosystems, species, and data types, providing a powerful way of enhancing maps and predictions of hunting effort across complex landscapes.     

Quantifying the rebound effects of residential solar panel adoption

Customers who adopt solar panels can reduce their energy bills and lower the effective average electricity prices they pay. When the price falls, a solar consumer might consume more electricity than before – a solar rebound effect. We provide the first empirical evidence of residential solar rebound effects in the U.S. We use household level hourly and daily electricity meter data as well as hourly solar panel electricity generation data from 277 solar homes and about 4000 non-solar homes from 2013 to 2017 in Phoenix Arizona. Using matching methods and a fixed effects panel regression approach, we find that when solar electricity generation increases by 1 kWh, solar homes increase their total electricity consumption by 0.18 kWh. This indicates that solar rebound effects are estimated at 18%. Building upon our theoretical framework, the increase in consumer surplus from solar panel adoption is estimated at $972/yr.     

An investigation on the fuel savings potential of hybrid hydraulic refuse collection vehicles

Refuse trucks play an important role in the waste collection process. Due to their typical driving cycle, these vehicles are characterized by large fuel consumption, which strongly affects the overall waste disposal costs. Hybrid hydraulic refuse vehicles offer an interesting alternative to conventional diesel trucks, because they are able to recuperate, store and reuse braking energy. However, the expected fuel savings can vary strongly depending on the driving cycle and the operational mode. Therefore, in order to assess the possible fuel savings, a typical driving cycle was measured in a conventional vehicle run by the waste authority of the City of Stuttgart, and a dynamical model of the considered vehicle was built up. Based on the measured driving cycle and the vehicle model including the hybrid powertrain components, simulations for both the conventional and the hybrid vehicle were performed. Fuel consumption results that indicate savings of about 20% are presented and analyzed in order to evaluate the benefit of hybrid hydraulic vehicles used for refuse collection.     

AAO工艺低氧条件下的运行及其模拟

利用厌氧-缺氧-好氧(AAO)工艺探讨了在好氧池低溶解氧(DO)浓度条件下的水质指标变化情况.结果表明,当好氧池DO浓度从2.00 mg·L~(-1)降低到1.00 mg·L~(-1)和0.50 mg·L~(-1)时,系统仍然具有良好的除磷脱氮效果,出水水质指标均满足我国《城镇污水处理厂污染物排放标准》(GB 18918-2002)中的一级A标准.在此基础上,基于Bio Win 4.1软件建立了AAO工艺的活性污泥模型,对模型参数进行了灵敏度分析,并利用动态模拟对模型参数中的聚磷菌吸收乙酸或丙酸的聚羟基烷酸(PHA)产率系数(YP/PHA,seq)、聚磷菌好氧氧化PHA的储磷率(YP/PHA,aerobic)、氨氧化菌的最大单位生长速率(μmax,A)和亚硝酸盐氧化菌的最大单位生长速率(μmax,N)进行了校验.此外,对系统的曝气能耗进行了模拟评估,结果表明,与好氧池DO浓度为2.00 mg·L~(-1)时相比,好氧池DO浓度为1.00 mg·L~(-1)和0.50 mg·L~(-1)时的空气流量可分别节省23.8%和38.1%,氧转移效率可分别提高7.2%和11.7%.     

Predicting vehicle fuel consumption patterns using floating vehicle data

The status of energy consumption and air pollution in China is serious. It is important to analyze and predict the different fuel consumption of various types of vehicles under different influence factors. In order to fully describe the relationship between fuel consumption and the impact factors, massive amounts of floating vehicle data were used. The fuel consumption pattern and congestion pattern based on large samples of historical floating vehicle data were explored, drivers'' information and vehicles'' parameters from different group classification were probed, and the average velocity and average fuel consumption in the temporal dimension and spatial dimension were analyzed respectively. The fuel consumption forecasting model was established by using a Back Propagation Neural Network. Part of the sample set was used to train the forecasting model and the remaining part of the sample set was used as input to the forecasting model.