城市街道空气污染物扩散模型综述

城市街道是城市居民的活动场所,其空气质量与居民健康密切相关.空气污染扩散模型是模拟和评估街道空气质量的重要方法,近年来广受关注,但模型应用存在问题,亟待解决.本文介绍了4种常用的空气污染物扩散模型:ENVI-met、FLUENT、MISKAM和OSPM.通过工作原理、运算流程、时空分辨率等的对比分析,明确了各模型的适用范围及其对街道峡谷内空气质量模拟能力的差异,阐述了各模型在时间尺度、物理建模、天气模拟、湍流模拟及光化学污染方面处理能力的局限性,提出了模型优化途径.通过综合分析4种模型的研究案例,总结了模型应用中存在的问题,提出未来研究可以通过激光雷达等新技术提高模型参数的获得精度,并强调综合模拟污染效应与热效应等对评估城市街道空气质量的重要性.     

Model evaluation and spatial interpolation by Bayesian combination of observations with outputs from numerical models

Constructing maps of dry deposition pollution levels is vital for air quality management, and presents statistical problems typical of many environmental and spatial applications. Ideally, such maps would be based on a dense network of monitoring stations, but this does not exist. Instead, there are two main sources of information for dry deposition levels in the United States: one is pollution measurements at a sparse set of about 50 monitoring stations called CASTNet, and the other is the output of the regional scale air quality models, called Models-3. A related problem is the evaluation of these numerical models for air quality applications, which is crucial for control strategy selection. We develop formal methods for combining sources of information with different spatial resolutions and for the evaluation of numerical models. We specify a simple model for both the Models-3 output and the CASTNet observations in terms of the unobserved ground truth, and we estimate the model in a Bayesian way. This provides improved spatial prediction via the posterior distribution of the ground truth, allows us to validate Models-3 via the posterior predictive distribution of the CASTNet observations, and enables us to remove the bias in the Models-3 output. We apply our methods to data on SO2 concentrations, and we obtain high-resolution SO2 distributions by combining observed data with model output. We also conclude that the numerical models perform worse in areas closer to power plants, where the SO2 values are overestimated by the models.     

Can dispersions be used for discriminating water quality status in coastal ecosystems? A case study on biofilm-dwelling microbial eukaryotes

Multivariate dispersions are an effective ecological indicator to evaluate the environmental heterogeneity and human disturbance in global ecological research. To explore the feasibility of the dispersions for assessing water quality status, a dataset of the biofilm-dwelling microbial eukaryote communities was studied in coastal waters of the Yellow Sea, northern China at two numerical resolutions. The community dispersion patterns represented a significant variability in both community structure and species composition in response to environmental heterogeneity. Multivariate approaches revealed that the species composition was the primary contributor to the community dispersion. Mantel analysis showed that the spatial variations in both community structure and species composition were significantly correlated with the changes of the nutrients, pH, dissolved oxygen (DO) and chemical oxygen demand (COD). The dispersion measures at both numerical resolutions were found to be remarkably related to the nutrient ammonium nitrogen and DO. Thus, we suggest that multivariate dispersions of the microbial eukaryote communities may be used as a potential bioindicator of water quality status in marine ecosystems.     

Temporal resolutions in species distribution models of highly mobile marine animals: Recommendations for ecologists and managers

While ecologists have long recognized the influence of spatial resolution on species distribution models (SDMs), they have given relatively little attention to the influence of temporal resolution. Considering temporal resolutions is critical in distribution modelling of highly mobile marine animals, as they interact with dynamic oceanographic processes that vary at time‐scales from seconds to decades. We guide ecologists in selecting temporal resolutions that best match ecological questions and ecosystems, and managers in applying these models. We group the temporal resolutions of environmental variables used in SDMs into three classes: instantaneous, contemporaneous and climatological. We posit that animal associations with fine‐scale and ephemeral features are best modelled with instantaneous covariates. Associations with large scale and persistent oceanographic features are best modelled with climatological covariates. Associations with mesoscale features are best modelled with instantaneous or contemporaneous covariates if ephemeral processes are present or interannual variability occurs, and climatological covariates if seasonal processes dominate and interannual variability is weak.     

Dynamic graph convolution neural network based on spatial-temporal correlation for air quality prediction

Air pollution is a serious threat to both the ecological environment and the physical health of individuals. Therefore, accurate air quality prediction is urgent and necessary for pollution mitigation and residents’ travel. However, few existing models are established based on the dynamic spatiotemporal correlation of air pollutants to predict air quality. In this paper, a novel deep learning model combining the dynamic graph convolutional network and the multi-channel temporal convolutional network (DGC-MTCN) is proposed for air quality prediction. To efficiently represent the time-varying spatial dependencies, a new spatiotemporal dynamic correlation calculation method based on gray relation analysis is proposed to construct dynamic adjacency matrices. Then, the spatiotemporal features are sufficiently extracted by the graph convolutional network and the multi-channel temporal convolutional network. Two real-world air quality datasets collected from Beijing and Fushun are applied to verify the performance of our proposed model. The experimental results show that compared with other baselines, the DGC-MTCN model has excellent prediction accuracy. Especially for the prediction of multi-step and different stations, our model performs better temporal stability and generalization ability.     

A Dispersion Modeling Study of Major VOCs from Non‐Point Emission Sources in the Urban Atmosphere

To assist with the understanding and solving of toxic air pollutant problems in urban areas, an atmospheric dispersion model, SKYDM, was developed with three preprocessors (meteorology, emission, and topography), and a physical process and chemical decay term based on NO_x‐O₃‐RH photochemistry in the actual atmosphere. SKYDM can work with multicomponents in a single model run, as well as with a single compound in a model run and produces 2D meteorological field results due to an integration approach. The present study aims to develop and evaluate a SKYDM at local spatial scales, in the short term. A comparative study is conducted to estimate the effects of model parameters in defining the applicability limits of dispersion models and to examine the integration approach methodology. All simulations are run for volatile organic compounds (VOCs) such as BTXS (Benzene, Toluene, Xylene, and Styrene) emitted from non‐point sources, located at 151 villages in seven divisions, in a northeastern portion of Seoul, Korea, with eight different meteorological data sets during 2002. Modeled toluene concentrations are compared with those observed at ten monitoring sites. The main findings of the present study are as follows: (a) Model uncertainties are obviously caused by limitations of meteorological conditions and emission and topographical information, by removal processes, and by user errors or application skills – the chemical decay term was a comparatively significant parameter in the removal of toxic air pollutants, (b) the integration approach indicated a correlation between observations and the model, and (c) the SKYDM showed potential as a useful tool for assessing the air quality in urban areas. In further work, the SKYDM will be upgraded to an improving model algorithm with fully detailed input information, and evaluated in comparison with other Gaussian dispersion models.     

考虑气候因子变化的湖泊富营养化模型研究进展

气候因子是影响湖泊营养状态和进程的主要自然因素.在全球气候变化的趋势下,将气候因子的变化纳入湖泊富营养化模型中,可以为湖泊演化趋势分析和环境管理决策提供技术支持.本文首先分析了气温、降水、光照和大气等气候因子对湖泊富营养化的影响,进而对考虑气候因子变化的数理统计与分析模型、生态动力学模型、系统生态学模型及智能算法等的研究进行了综述.在此基础上,对完善气候因子变化下湖泊营养状态变化的模型研究进行了展望：1)加强气候因子作用于湖泊营养状态的机理研究;2)选择合适的气候模拟模型,合理设置气候变化情景,在不同模型嵌套时保证时空尺度的匹配;3)以水动力学模型为基础,耦合生态模型及智能算法等,并结合良好的气候模拟模型,以精确模拟预测气候变化下湖泊富营养化的演化过程和趋势.     

Development of Exposure Characterization Regions for Priority Ambient Air Pollutants

To evaluate the relationship between air pollution and morbidity and mortality in epidemiological studies, the exposure of populations must be defined. Generally, ambient air monitoring networks are the source of the exposure data for these studies. In this study, we developed methods to define population exposure regions that represent minimal variation in air pollutant concentrations. We evaluated the spatial and temporal variation in concentrations for particulate matter less than 2.5 μm (PM_2.5) and 10 μm (PM₁₀) and ozone (O₃) across New York State. The results from the PM_2.5 and ozone analysis indicate a significant degree of regional transport and showed regions of consistent concentrations of 100 and 50 miles, respectively, around each monitor. PM₁₀ analysis indicated little temporal and spatial variation for this pollutant and larger regions were adopted. The exposure characterization regions for PM_2.5, PM₁₀, and ozone have been used in ecological epidemiological investigations by the New York State Department of Health. This work was conducted under the Environmental Public Health Tracking grant from the Centers for Disease Control and Prevention.     

A characterization model with spatial and temporal resolution for life cycle impact assessment of photochemical precursors in the United States

Background, aim, and scope  Traditional life cycle impact assessment methodologies have used aggregated characterization factors, neglecting spatial and temporal variations in regional impacts like photochemical oxidant formation. This increases the uncertainty of the LCA results and diminishes the ease of decision-making. This study compares four common impact assessment methods, CML2001, Eco-indicator 99, TRACI, and EDIP2003, on their underlying models, spatial and temporal resolution, and the level at which photochemical oxidant impacts are calculated. A new characterization model is proposed that incorporates spatial and temporal differentiation. Materials and methods  A photochemical air quality modeling system (CAMx-MM5-SMOKE) is used to simulate the process of formation, transformation, transport, and removal of photochemical pollutants. Monthly characterization factors for individual US states are calculated at three levels along the cause–effect chain, namely, fate level, human and ecosystem exposure level, and human effect level. Results and discussion  The results indicate that a spatial variability of one order of magnitude and a temporal variability of two orders of magnitude exist in both the fate level and human exposure and effect level characterization factors for NO_x. The summer time characterization factors for NO_x are higher than the winter time factors. However, for anthropogenic VOC, the summer time factors are lower than the winter time in almost half of the states. This is due to the higher emission rates of biogenic VOCs in the summer. The ecosystem exposure factors for NO_x and VOC do not follow a regular pattern and show a spatial variation of about three orders of magnitude. They do not show strong correlation with the human exposure factors. Sensitivity analysis has shown that the effect of meteorology and emission inputs is limited to a factor of three, which is several times smaller than the variation seen in the factors. Conclusions  Uncertainties are introduced in the characterization of photochemical precursors due to a failure to consider the spatial and temporal variations. Seasonal variations in photochemical activity influence the characterization factors more than the location of emissions. The human and ecosystem exposures occur through different mechanisms, and impacts calculated at the fate level based only on ozone concentration are not a good indicator for ecosystem impacts. Recommendations and perspectives  Spatial and temporal differentiation account for fate and transport of the pollutant, and the exposure of and effect on the sensitive human population or ecosystem. Adequate resolution for seasonal and regional processes, like photochemical oxidant formation, is important to reduce the uncertainty in impact assessment and improve decision-making power. An emphasis on incorporating some form of spatial and temporal information within standard LCI databases and using adequately resolved characterization factors will greatly increase the fidelity of a standard LCA. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Epiphytic lichens as biomonitors of airborne heavy metal pollution

The research aims to assess the performance of the lichen Parmotrema reticulatum as an air pollution biomonitor of four heavy metals, namely, chromium (Cr), copper (Cu), lead (Pb) and zinc (Zn). Four contrasting land use sites within the greater Auckland region of New Zealand are used. One site is located within the relatively clean air shed of conservation land, the others within residential, commercial, and industrial areas, characterised by increasingly polluted air sheds, respectively. Three groups of lichens are monitored over a two-year period using active and passive biomonitoring methods to assess ‘on-thallus’ and ‘in-thallus’ concentrations of heavy metals. Seasonal transplants are used to quantify heavy metals accumulated by the lichen during each season. Long-term transplants are used to measure how fast lichens accumulate heavy metals and to better understand how and when heavy metals within the lichen thallus achieve equilibrium with air pollutant concentrations over time. The results show that the lichens continuously accumulates pollutants from the air until equilibrium is reached, thus transplanted lichens are useful for monitoring air pollution concentrations over time. Since pollutant concentration in the transplanted lichen at equilibrium stabilises, at this point the lichen ceases to be useful for monitoring temporal trends in air pollution, but may useful for spatial air pollution monitoring. The industrial location has the highest total accumulation for all four heavy metals, followed by the commercial and residential locations, respectively. Overall, the results show that the lichen P. reticulatum may be successfully used to monitor spatial and temporal pollution patterns caused by even very low concentrations of Cr, Cu, Pb and Zn.     

One size does not fit all: flexible models are required to understand animal movement across scales

1. Large data sets containing precise movement data from free-roaming animals are now becoming commonplace. One means of analysing individual movement data is through discrete, random walk-based models. 2. Random walk models are easily modified to incorporate common features of animal movement, and the ways that these modifications affect the scaling of net displacement are well studied. Recently, ecologists have begun to explore more complex statistical models with multiple latent states, each of which are characterized by a distribution of step lengths and have their own unimodal distribution of turning angles centred on one type of turn (e.g. reversals). 3. Here, we introduce the compound wrapped Cauchy distribution, which allows for multimodal distributions of turning angles within a single state. When used as a single state model, the parameters provide a straightforward summary of the relative contributions of different turn types. The compound wrapped Cauchy distribution can also be used to build multiple state models. 4. We hypothesize that a multiple state model with unimodal distributions of turning angles will best describe movement at finer resolutions, while a multiple state model using our multimodal distribution will better describe movement at intermediate temporal resolutions. At coarser temporal resolutions, a single state model using our multimodal distribution should be sufficient. We parameterize and compare the performance of these models at four different temporal resolutions (1, 4, 12 and 24 h) using data from eight individuals of Loxodonta cyclotis and find support for our hypotheses. 5. We assess the efficacy of the different models in extrapolating to coarser temporal resolution by comparing properties of data simulated from the different models to the properties of the observed data. At coarser resolutions, simulated data sets recreate many aspects of the observed data; however, only one of the models accurately predicts step length, and all models underestimate the frequency of reversals. 6. The single state model we introduce may be adequate to describe movement data at many resolutions and can be interpreted easily. Multiscalar analyses of movement such as the ones presented here are a useful means of identifying inconsistencies in our understanding of movement.     

基于RANS的城市广场空气质量评价及健康场所指引

空气中污染物及病菌的浓度直接影响人类健康。在污染源不变的情况下,有效通风决定了空气质量的优劣。因此,建立有效通风的定量判定指标,并利用此指标对特定区域空气质量进行实时评价,引导居民选择健康的室外活动场所成为迫切需要解决的问题。本研究采用雷诺平均Navier-Stokes(RANS)方法建立了基于计算流体力学(CFD)技术的城市空气污染模拟系统,研究了风速、污染物浓度和污染物扩散效率之间的关系。在此基础上,借助实时气象数据,对城市广场空间不同时段进行了风场模拟及空气质量评价。结果表明: 行人高度(1.5 m)空气中污染物有效扩散的临界风速值为1.0 m·s^-1,此指标可作为某一具体区域空气质量评价标准。参照此判定指标,链接实时天气系统,通过模拟得到的行人高度风速分布,可实时、可视化地显示该场所空气质量优劣分布,实现公平、效率、合理地利用城市空间资源,为人们选择健康的室外活动场地提供指引,为公众疾病预防和健康促进提供技术和手段。     

Survey completeness of a global citizen-science database of bird occurrence

Measuring the completeness of survey inventories created by citizen-science initiatives can identify the strengths and shortfalls in our knowledge of where species occur geographically. Here, we use occurrence information from eBird to measure the survey completeness of the world's birds in this database at three temporal resolutions and four spatial resolutions across the annual cycle during the period 2002 to 2018. Approximately 84% of the earth's terrestrial surface contained bird occurrence information with the greatest concentrations occurring in North America, Europe, India, Australia and New Zealand. The largest regions with low levels of survey completeness were located in central South America, northern and central Africa, and northern Asia. Across spatial and temporal resolutions, survey completeness in regions with occurrence information was 55–74% on average, with the highest values occurring at coarser temporal and coarser spatial resolutions and during spring migration within temperate and boreal regions. Across spatial and temporal resolutions, survey completeness exceeded 90% within ca 4–14% of the earth's terrestrial surface. Survey completeness increased globally from 2002 to 2018 across all months of the year at a rate of ca 3% yr^–1. The slowest gains occurred in Africa and in montane regions, and the most rapid gains occurred in India and in tropical forests after 2012. Thus, occurrence information from a global citizen-science program for a charismatic and well-studied taxon was geographically broad but contained heterogeneous patterns of survey completeness that were strongly influenced by temporal and especially spatial resolution. Our results identify regions where the application of additional effort would address current knowledge shortfalls, and regions where the maintenance of existing effort would benefit long-term monitoring efforts. Our findings highlight the potential of citizen science initiatives to further our knowledge of where species occur across space and time, information whose applications under global change will likely increase.     

环境影响评价的尺度约束性及技术框架

尺度约束是地表复杂系统的基本规律,环评尺度约束常隐存于主观经验或零存于环评导则中,环评尺度约束较少被明确关注。讨论了环境影响尺度约束、环评尺度约束和环评技术框架尺度约束。研究发现,环境影响的尺度约束性内在原因在于环境影响主体、客体和影响内容存在等级结构;环评受空间、时间和分析三类尺度约束,空间尺度约束体现于空间范围和空间信息分辨率对环评影响,时间尺度约束体现于环评的时长和时频,分析尺度约束表现为环评技术方法和环境影响主观认知水平对评价的影响,三类尺度约束同时贯穿于环评过程,任何环评都可以在三类尺度空间中定位;环评技术框架的关键环节都受空间、时间和分析尺度约束,且以环境影响主体的空间、时间尺度为核心,具有一定弹性,一般空间或时间范围先放大再缩小、分辨率由粗到细。     

An approach to identifying potential surrogates of periphytic ciliate communities for monitoring water quality of coastal waters

For identifying the potential surrogate of periphytic ciliate communities for monitoring marine water quality, the different taxonomic resolutions/taxa as surrogates and different data transformations were studied based on two datasets of ciliate communities in Korean coastal waters. Multivariate analyses showed that: (1) a dominant Zoothamnium duplicatum significantly masked the temporal patterns of periphytic ciliate community; (2) the order level resolution maintained sufficient information to evaluate the efficient patterns of ciliate communities in response to environmental impacts; (3) the vagile-ciliate assemblage at species-level resolution was as costly as whole periphytic ciliate communities without Z. duplicatum at the order level; and (4) the severity of data transformations played a crucial role for effectiveness of surrogates, e.g., heavy transformation for species level and mild for higher. These results suggest that the use of lower taxonomic resolutions is time-efficient and would allow improving sampling strategies of large spatial/temporal scale monitoring researches in the marine ecosystem.     

武钢厂区绿地景观类型空间结构及滞尘效应

应用景观生态学原理和对比分析方法分别对武钢厂区绿地景观类型的空间结构及滞尘效应进行了研究。结果表明,武钢厂区绿地斑块数目多,破碎化指数高,体现了工业区见缝插绿的绿化特点,以道路绿带为骨架,成片防护林和观赏绿地为中心,将各分厂绿地连接成四大绿化区域的武钢厂区绿地系统已初步形成,其滞尘效应主要表现为对交流污染物及二次飞扬的阻滞作用,以乔木为主的防护林斑块平均面积大,滞尘效果好,滞尘率达38.9%-46.1%,但优势度不高,专类园和观赏草坪斑块植物种类丰富,景观效果好,但滞尘效果较差,道路绿带优势度和破碎化指数最高,构成了厂区绿色廊道网络,并在阻滞交通污染中起着重要作用,其中多行复层绿带的滞尘率（46.2%-60.8%)比单行乔木绿带的滞尘率（14.8%-39.2%)高,但道路绿带仍不完整,多行复层绿带的比例不高。     

The Use of Quantile Regression to Forecast Higher Than Expected Respiratory Deaths in a Daily Time Series: A Study of New York City Data 1987-2000

Forecasting higher than expected numbers of health events provides potentially valuable insights in its own right, and may contribute to health services management and syndromic surveillance. This study investigates the use of quantile regression to predict higher than expected respiratory deaths.Data taken from 70,830 deaths occurring in New York were used. Temporal, weather and air quality measures were fitted using quantile regression at the 90th-percentile with half the data (in-sample). Four QR models were fitted: an unconditional model predicting the 90th-percentile of deaths (Model 1), a seasonal / temporal (Model 2), a seasonal, temporal plus lags of weather and air quality (Model 3), and a seasonal, temporal model with 7-day moving averages of weather and air quality. Models were cross-validated with the out of sample data. Performance was measured as proportionate reduction in weighted sum of absolute deviations by a conditional, over unconditional models; i.e., the coefficient of determination (R1).The coefficient of determination showed an improvement over the unconditional model between 0.16 and 0.19. The greatest improvement in predictive and forecasting accuracy of daily mortality was associated with the inclusion of seasonal and temporal predictors (Model 2). No gains were made in the predictive models with the addition of weather and air quality predictors (Models 3 and 4). However, forecasting models that included weather and air quality predictors performed slightly better than the seasonal and temporal model alone (i.e., Model 3 > Model 4 > Model 2)This study provided a new approach to predict higher than expected numbers of respiratory related-deaths. The approach, while promising, has limitations and should be treated at this stage as a proof of concept.     

Development and testing of a chemical mechanism for atmospheric photochemical transformations of 1,3-butadiene

1,3-Butadiene (BD) in the atmosphere is a highly reactive hazardous air pollutant, which has a short lifetime and is quickly transformed to reaction products, some of which are also toxic. The ability to predict exposure to BD and its' products requires models with chemical mechanisms which can simulate these transformations. The atmospheric photochemical reactions of BD have been studied in the University of North Carolina Outdoor smog chamber, which has been used for over 30 years to test photochemical mechanisms for air quality simulation models for ozone. Experiments have been conducted under conditions of real sunlight and realistic temperature and humidity to study the transformations of BD and to develop and test chemical mechanisms for the simulation of these processes. Experimental observation of time-concentration data of BD decay and the formation of many products is compared to simulation results. This chemical mechanism can be incorporated into air quality simulation models which can be used to estimate ambient concentrations needed for exposure estimates.     

城市街谷大气污染物分布研究进展

城市街谷是现代城市最重要的空间形式与特征之一,是城市中使用频率最高、汽车尾气污染最严重、日常人口密度最大的公共空间类型之一。城市街谷不合理的空间配置和结构会造成城市通风自净能力降低,大气污染物浓度增高。本文综述了城市街谷形态、行道树配置、机动车车流量和气象因素等对街谷大气污染物分布的影响,以及数值模拟、风洞试验和实地监测等用于街谷大气污染物分布及扩散研究的相关方法。建议未来以实地监测数据为基础,综合考虑多种因素对街谷大气污染物分布的研究,提出适宜城市大气污染物扩散的城市街谷构建模式,从城市规划和格局优化的角度为城市大气污染物的减控提出科学支撑和优化方案。     

Imaging pHluorin-tagged Receptor Insertion to the Plasma Membrane in Primary Cultured Mouse Neurons

A better understanding of the mechanisms governing receptor trafficking between the plasma membrane (PM) and intracellular compartments requires an experimental approach with excellent spatial and temporal resolutions. Moreover, such an approach must also have the ability to distinguish receptors localized on the PM from those in intracellular compartments. Most importantly, detecting receptors in a single vesicle requires outstanding detection sensitivity, since each vesicle carries only a small number of receptors. Standard approaches for examining receptor trafficking include surface biotinylation followed by biochemical detection, which lacks both the necessary spatial and temporal resolutions; and fluorescence microscopy examination of immunolabeled surface receptors, which requires chemical fixation of cells and therefore lacks sufficient temporal resolution^1-6 . To overcome these limitations, we and others have developed and employed a new strategy that enables visualization of the dynamic insertion of receptors into the PM with excellent spatial and temporal resolutions ^7-17 . The approach includes tagging of a pH-sensitive GFP, the superecliptic pHluorin ¹⁸, to the N-terminal extracellular domain of the receptors. Superecliptic pHluorin has the unique property of being fluorescent at neutral pH and non-fluorescent at acidic pH (pH < 6.0). Therefore, the tagged receptors are non-fluorescent when within the acidic lumen of intracellular trafficking vesicles or endosomal compartments, and they become readily visualized only when exposed to the extracellular neutral pH environment, on the outer surface of the PM. Our strategy consequently allows us to distinguish PM surface receptors from those within intracellular trafficking vesicles. To attain sufficient spatial and temporal resolutions, as well as the sensitivity required to study dynamic trafficking of receptors, we employed total internal reflection fluorescent microscopy (TIRFM), which enabled us to achieve the optimal spatial resolution of optical imaging (~170 nm), the temporal resolution of video-rate microscopy (30 frames/sec), and the sensitivity to detect fluorescence of a single GFP molecule. By imaging pHluorin-tagged receptors under TIRFM, we were able to directly visualize individual receptor insertion events into the PM in cultured neurons. This imaging approach can potentially be applied to any membrane protein with an extracellular domain that could be labeled with superecliptic pHluorin, and will allow dissection of the key detailed mechanisms governing insertion of different membrane proteins (receptors, ion channels, transporters, etc.) to the PM.