Annual Hourly Research Articles

Cycling in a changed climate

The use of bicycle is substantially affected by the weather patterns, which is expected to change in the future as a result of climate change. It is therefore important to understand the resulting potential changes in bicycle flows in order to accommodate adaptation planning for cycling. We propose a framework to model the changes in bicycle flow in London by developing a negative binomial count-data model and by incorporating future projected weather data from downscaled global climate models, a first such approach in this area. High temporal resolution (hourly) of our model allows us to decipher changes not only on an annual basis, but also on a seasonal and daily basis. We find that there will be a modest 0.5% increase in the average annual hourly bicycle flows in London’s network due to a changed climate. The increase is primarily driven by a higher temperature due to a changed climate, although the increase is tempered due to a higher rainfall. The annual average masks the differences of impacts between seasons though – bicycle flows are expected to increase during the summer and winter months (by 1.6%), decrease during the spring (by 2%) and remain nearly unchanged during the autumn. Leisure cycling will be more affected by a changed climate, with an increase of around 7% during the weekend and holiday cycle flows in the summer months.

Comparison of Estimates of Travel Time Losses on High-Capacity Roads

This paper compares two approaches to estimating travel time losses on freeways that are based on a whole-year analysis. Both approaches are intended to improve the design process for freeways by accounting for the annual traffic demand profile as well as short time variance of demand and capacity. One approach estimates breakdown probability and delay-related time losses by using a probabilistic model. The other approach uses Monte Carlo simulation to estimate travel time losses at freeway bottlenecks on the basis of a queuing model with stochastic demand and capacity. Both approaches are based on annual hourly demand profiles. The approaches are compared for demand profiles and deliver similar but not equal results. Travel time losses for both approaches increase exponentially with traffic volume, with the simulation-based approach consistently generating higher time losses for higher traffic volumes. Both approaches are a substantial improvement on current design procedures, are easy to apply, and are recommended for adoption in traffic analysis guidelines.

Mean solar quiet daily variations in the earth’s magnetic field along East African longitudes

Solar quiet daily (Sq) variation in the earth’s magnetic field along the East African meridian was studied using data of the H, D and Z components recorded with Magnetic Data Acquisition System of SERC. One year data recorded at ten African geomagnetic observatories was used in the analysis of worldwide solar quiet daily variation (Wsq). The study revealed that the focus of Sq (H) in the southern hemisphere lies at the boundary of low and middle latitude region. Noon-time enhancement of Sq (H) was generally noticed at all stations along the meridian, though it is latitudinal dependent in terms of magnitude as it reduces with distance from dip equator. In addition, night-time variations also occur in small magnitude along African meridian in Sq (H) and Sq (Z) which could be attributed to non-ionospheric sources. Semi-diurnal variation was noticed in Sq (D) at all stations except in AAB that is under the influence of electrojet current. Dusk sector calm condition of Sq (D) current was notice in some stations and the same condition was also noticed at dawn sector in some other stations. The usual sunrise maximum and sunset minimum for D component at stations north of dip equator as well as sunrise minimum and sunset maximum was found to increase with distance away from dip equator. Day-time perturbation of Sq current was noticed to be more pronounced in all the three field elements. Mass plots of annual mean hourly value show contrasting phase pattern about the focus in H element and the results of the variations at each region with the associated standard error. It was concluded from the result of correlation coefficients computed that different currents system flowing in opposite directions could be responsible for contrasting patterns.

Mean Imputation Techniques for Filling the Missing Observations in Air Pollution Dataset

Almost all real life datasets consist missing values. These are usually due to machine failure, routine maintenance, changes in siting monitors and human error. The occurence of missing values requires special attention on analysing the data. Incomplete datasets can cause bias due to systematic differences between observed and unobserved data. Therefore, the need to find the best way in estimating missing values is very important so that the data analysed is ensured of high quality. In this research, three types of mean imputation techniques that are mean, mean above and mean above below methods were used to replace the missing values. Annual hourly monitoring data for PM10 were used to generate missing values. Four randomly simulated missing data were evaluated in order to test the efficiency of the methods used. They are 5%, 10%, 15%, 25% and 40%. Three types of performance indicators that are mean absolute error (MAE), root mean square error (RMSE) and coefficient of determination (R2) were calculated to describe the goodness of fit for all the method. From all the method applied, it was found that mean above below method is the best method for estimating data for all percentages of simulated missing values.

Duration and seasonality of hourly extreme rainfall in the central eastern China

Compared with daily rainfall amount, hourly rainfall rate represents rainfall intensity and the rainfall process more accurately, and thus is more suitable for studies of extreme rainfall events. The distribution functions of annual maximum hourly rainfall amount at 321 stations in China are quantified by the Generalized Extreme Value (GEV) distribution, and the threshold values of hourly rainfall intensity for 5-yr return period are estimated. The spatial distributions of the threshold exhibit significant regional differences, with low values in northwestern China and high values in northern China, the mid and lower reaches of the Yangtze River valley, the coastal areas of southern China, and the Sichuan basin. The duration and seasonality of the extreme precipitation with 5-yr return periods are further analyzed. The average duration of extreme precipitation events exceeds 12 h in the coastal regions, Yangtze River valley, and eastern slope of the Tibetan Plateau. The duration in northern China is relatively short. The extreme precipitation events develop more rapidly in mountain regions with large elevation differences than those in the plain areas. There are records of extreme precipitation in as early as April in southern China while extreme rainfall in northern China will not occur until late June. At most stations in China, the latest extreme precipitation happens in August-September. The extreme rainfall later than October can be found only at a small portion of stations in the coastal regions, the southern end of the Asian continent, and the southern part of southwestern China.

Annual hourly CFD simulation: New approach—An efficient scheduling algorithm for fast iteration convergence

Computational fluid dynamics (CFD) is one of the branches of fluid mechanics that uses numerical methods and algorithms to solve and analyze problems that involve fluid flows. Annual hourly fast flow simulations are needed for some applications in building industry, such as the conceptual design of indoor environment, or coupled with energy simulation to provide deep analysis on the performance of the buildings. Year round simulation, which consists of 8760 (365×24) independent hourly simulations, is needed to help the designer investigate the problem clearly. However, CFD computation is time consuming, and usually only two or three extreme cases can be simulated in practice. Annual hourly simulation using the traditional method can be considered as a computational intractable problem. Based on previous researches, even though the fast fluid dynamics (FFD) algorithm combined with the General Purposed Graphics Processing Unit (GPGPU) hardware acceleration can make CFD simulation much faster (400x), annual hourly simulation still requires CFD performance to be further improved by 10-20x to make it practical. In this study, a minimal spanning tree based scheduling algorithm is developed, which always gives the best CFD simulation strategy that reuses previous calculated results to generate new results, thus making iteration convergence much faster. It is shown in the paper that the annual hourly simulation by GPGPU accelerated FFD by using this new algorithm requires a similar simulation time to the one used to perform two or three extreme cases of simulation using the traditional method.

On the potential of Bartlett Lewis rectangular pulse models for simulating rainfall in Peninsular Malaysia

The applicability of two versions of the Bartlett Lewis rectangular pulse model, the original and the modified model, is discussed for describing the temporal and spatial variation of rainfall patterns observed at 15 raingauge stations in Peninsular Malaysia over the period 1971–2008; 17 different sets of moment combinations are fitted to these models based on the generalized method of moments approach. The common statistics included in all sets are the mean, variance, lag-1 autocorrelation and the probability of dry based on the hourly rainfall data. The analysis was carried out on hourly rainfall data from all 15 stations for all months of the year. Two stations, Petaling Jaya and Kemaman, located on the west and east coasts of the Peninsula, respectively, are considered for illustration of the results, taking the months of July and November, which correspond to the driest and wettest months, corresponding to the southwest monsoon (May–August) and northeast monsoon (November–February), respectively. The best moment combination found for the illustrative results is based on the common statistics, as well as the mean and variance based on 24-h aggregated rainfall data, the inclusion of which successfully improved the model performance; the errors were significantly reduced. It was also found that the performance of the fitted models based on the mean absolute deviate error varies according to the type of Bartlett Lewis model applied: errors are much smaller for the fitted model based on the modified model as compared to the original model. In addition, the fitted statistics: mean, lag-1 autocorrelation and probability of dry are quite well fitted for several aggregated time scales; however, the variances are underestimated in both models for all aggregated time scales, particularly in the case of the original model. The results of extreme value analysis indicate that the modified model failed to reproduce the annual hourly and daily rainfall extremes satisfactorily.Editor D. Koutsoyiannis; Associate editor C. OnofCitation Hanaish, I.S., Ibrahim, K., and Jemain, A.A., 2013. On the potential of Bartlett Lewis rectangular pulse models for simulating rainfall in Peninsular Malaysia. Hydrological Sciences Journal, 58 (8), 1690–1703.

Future daily PM10 concentrations prediction by combining regression models and feedforward backpropagation models with principle component analysis (PCA)

Future PM10 concentration prediction is very important because it can help local authorities to enact preventative measures to reduce the impact of air pollution. The aims of this study are to improve prediction of Multiple Linear Regression (MLR) and Feedforward backpropagation (FFBP) by combining them with principle component analysis for predicting future (next day, next two-day and next three-day) PM10 concentration in Negeri Sembilan, Malaysia. Annual hourly observations for PM10 in Negeri Sembilan, Malaysia from January 2003 to December 2010 were selected for predicting PM10 concentration level. Eighty percent of the monitoring records were used for training and twenty percent were used for validation of the models. Three accuracy measures – Prediction Accuracy (PA), Coefficient of Determination (R2) and Index of Agreement (IA), as well as two error measures – Normalized Absolute Error (NAE) and Root Mean Square Error (RMSE) were used to evaluate the performance of the models. Results show that PCA models combined with MLR and PCA with FFBP improved MLR and FFBP models for all three days in advance of predicting PM10 concentration, with reduced errors by as much as 18.1% (PCA–MLR) and 17.68% (PCA–FFBP) for next day, 19.2% (PCA–MLR) and 22.1% (PCA–FFBP) for next two-day and 18.7% (PCA–MLR) and 22.79% (PCA–FFBP) for next three-day predictions. Including PCA improved the accuracy of the models by as much as by 12.9% (PCA–MLR) and 13.3% (PCA–FFBP) for next day, 32.3% (PCA–MLR) and 14.7% (PCA–FFBP) for next two-day and 46.1% (PCA–MLR) and 19.3% (PCA–FFBP) for next three-day predictions.

An assessment of the surface ozone trend in Ireland relevant to air pollution and environmental protection

Hourly data (1994–2009) of surface ozone concentrations at eight monitoring sites have been investigated to assess target level and long–term objective exceedances and their trends. The European Union (EU) ozone target value for human health (60ppb–maximum daily 8–hour running mean) has been exceeded for a number of years for almost all sites but never exceeded the set limit of 25 exceedances in one year. Second highest annual hourly and 4th highest annual 8–hourly mean ozone concentrations have shown a statistically significant negative trend for in–land sites of Cork–Glashaboy, Monaghan and Lough Navar and no significant trend for the Mace Head site. Peak afternoon ozone concentrations averaged over a three year period from 2007 to 2009 have been found to be lower than corresponding values over a three–year period from 1996 to 1998 for two sites: Cork–Glashaboy and Lough Navar sites. The EU long–term objective value of AOT40 (Accumulated Ozone Exposure over a threshold of 40ppb) for protection of vegetation (3ppm–hour, calculated from May to July) has been exceeded, on an individual year basis, for two sites: Mace Head and Valentia. The critical level for the protection of forest (10ppm–hour from April to September) has not been exceeded for any site except at Valentia in the year 2003. AOT40–Vegetation shows a significant negative trend for a 3–year running average at Cork–Glashaboy (−0.13±0.02 ppm−hour per year), at Lough Navar (−0.05±0.02 ppm−hour per year) and at Monaghan (−0.03±0.03ppm−hour per year–not statistically significant) sites. No statistically significant trend was observed for the coastal site of Mace head. Overall, with the exception of the Mace Head and Monaghan sites, ozone measurement records at Irish sites show a downward negative trend in peak values that affect human health and vegetation.

Peculiarities in atmospheric particle number and size-resolved speciation in an urban area in the western Mediterranean: Results from the DAURE campaign

Air quality degradation problems in urban environments are mainly due to road traffic emissions. In northern and central European cities extensive investigations have been carried out on the variability of number of ultrafine particles and black carbon, whereas studies in southern-Europe have traditionally focused on chemical speciation, resulting in insufficient information to characterise urban aerosol processes. Accordingly, sources and processes controlling atmospheric pollutants were evaluated during the international DAURE campaign in Barcelona (Spain), a typical urban environment in the western Mediterranean, by means of continuous measurements of particle number, black carbon, PMx, particulate nitrate and particulate sulphate concentrations. Results provided evidence of the influence of three PM sources of interest: road traffic, construction-demolition works and shipping emissions. Road traffic governs the daily cycle of black carbon, a number of gaseous pollutants and the finer fraction of PM. Evaluation of the coarse aerosol (PM2.5-10) daily cycle furnished evidence of the influence of construction-demolition works. These activities could increase hourly PM2.5-10 levels by up to 8 μg m−3 on an annual hourly mean basis. Finally, shipping emissions were traced by means of SO2 concentrations, which peak at a time different from that of other gaseous pollutants owing to the regular daytime onshore breeze bringing harbour emissions at midday. Moreover, a major local contribution of secondary aerosols was detected with elevated particle number levels at midday when nucleation processes are favoured by photochemistry and lower pollution levels. Particle number data were also analysed in search for the primary emission of vehicle exhaust (N1) and the secondary parts from gaseous precursors, primary parts from non-traffic sources, and/or particles inherited in the air mass (N2). N2 fraction accounted for 40% of number concentrations, ranging from 37% during the morning rush hour to 61% at midday. Results proved that the combination of PM10 and BC monitoring in urban areas may constitute a good approach to evaluate the traffic impact on air quality (BC), considering also the influence of other primary and secondary sources (PM10).

Optimal allocation of energy storage system in distribution systems

In this paper, a methodology is proposed for optimally allocating energy storage system (ESS) in distribution systems with a high penetration of wind energy. The aggregated capacity of an ESS is determined so as to accommodate all amounts of spilled wind energy, and the ESS is optimally allocated in the system in order to minimize the annual electricity cost. The annual hourly wind speed and load profile are generated using the auto regression moving average (ARMA) technique and the IEEE-RTS system, respectively. Further, these data are incorporated in order to determine the annual cost of spilled energy and the optimum allocation of the ESS in the distribution system. A cost/benefit analysis was also conducted by comparing the annual cost of different ESS techniques with the total profit for both the utility and the distributed generation (DG) owner. The results show that integrating an ESS with the distribution system for the proposed application is economically feasible only when the least expensive ESS is used.

Energy performance analysis on telecommunication base station

Telecommunication base station (TBS) has high indoor IT heat dissipation rate, and cooling load exists almost all year around. Energy consumption of air-conditioning system is 30–50% of the TBS entire energy. Envelope and heat pipe assisted air-conditioning system performances are investigated using annual hourly simulation software. In cold city Harbin, high insulation envelope is recommended to avoid heating requirement in winter; and in warm city Guangzhou, low insulation envelope is recommended to reduce the annual cooling load. Shading and roof ventilation have little impact on the reduction of cooling load. Simplified analysis method based on daily average steady values is proposed, which can reveal the main performance influencing factors and clearly direct the main approach in energy saving. The simplified method can accord well with numerical results and tested results available in literature. Contribution of each heat source can be clearly gained and analyzed, solar radiation does not possess large effect in TBS. Ideal thermal resistance with no heating or cooling requirement is then derived, envelope can be easily optimized and contribution of such kind of outdoor cooling source method using heat pipe can be easily obtained.

Energy efficiency benchmarks and the performance of LEED rated buildings for Information Technology facilities in Bangalore, India

This paper provides a summary of an energy benchmarking study that uses performance data of a sample of Information Technology facilities in Bangalore. Information provided by the sample of occupiers was used to develop an Energy Performance Index (EPI) and an Annual Average hourly Energy Performance Index (AAhEPI), which takes into account the variations in operation hours and days for these facilities. The EPI and AAhEPI were modelled to identify the factors that influence energy efficiency. Employment density, size of facility, operating hours per week, type of chiller and age of facility were found to be significant factors in regression models with EPI and AAhEPI as dependent variables. Employment density, size of facility and operating hours per week were standardised and used in a separate regression analysis. Parameter estimates from this regression were used to normalize the EPI and AAhEPI for variance in the independent variables. Three benchmark ranges – the bottom third, middle third and top third – were developed for the two normalised indices. The normalised EPI and AAhEPI of LEED rated building, which were also part of the sample, indicate that, on average, LEED rated buildings outperform the other buildings.

An assessment of the air pollution data from two monitoring stations in Kuwait

This article assesses the air pollution data from two monitoring stations in Kuwait. The measurements cover major pollutants, i.e., CO, CO2, methanated and non-methanated hydrocarbons, NO x , SO2, O3, and particulate matter (PM10). The data also includes meteorological parameters, i.e., solar intensity, temperature, wind speed, and wind direction, and has been collected over a period 4 years, from 2001 to 2004. Data analysis includes the assessment of annual hourly averages and 1-h maxima. Typical pollutant concentration trends, similar to those previously reported for Kuwait and for other locations around the world, are observed except for particulate matter measurements, which have higher values because of proximity to the desert. Emissions of nitrogen oxides show a consistent increase over the years. This is caused by the increase in the number of motor vehicles and the expansion in power generation and industrial activities. The data collected is a subset of the air quality criteria, as defined by the US EPA (United States Environmental Protection Agency).

Green tide formed by free-floating Ulva spp. at Yatsu tidal flat, Japan

Green tides at Yatsu tidal flat, Tokyo Bay, Japan, were first reported in 1995 and formed by a bloom only of free-floating Ulva species. On the tidal flat, the bloom area in well-developed periods increased after 1995 and covered 27.1 ha in May 2002. Based on vertical aerial photographs, green tide remaining in winter during 1996–2007 covered 4.7 ha when first observed in 1999 and increased to 17.5 ha in January 2002 thereafter. We found that the expansion of green tide was related to such factors as an increase in Kira’s Warmth Index, a decrease in annual cumulative hourly air temperatures below 7°C in December, an increase in salinity, and unintentional introduction of Ulva ohnoi. We also found that green tide at Yatsu tidal flat occurred in the course of the improvement of water quality.

Setting acceptable odour criteria using steady-state and annual hourly weather data

In air dispersion models, the predicted distance at which odour dilutes to a certain concentration (e.g., the chosen acceptable concentration) varies if steady-state or annual hourly weather data are used. As a result, different acceptable odour concentration criteria are required for these two types of weather conditions. The objective of this study was to determine the equivalent odour criteria in terms of concentration and frequency that result in the same setback distance for both weather conditions. Odour dispersion from a typical pig farm in Saskatchewan, Canada, was simulated using the CALPUFF model using both steady-state and annual hourly weather data. Results showed that, in order to obtain long setback distances (3, 4 or 5 km), the odour occurrence frequencies should be larger under steady-state stable atmospheric conditions than under annual hourly variable weather conditions. Alternatively, for the same odour occurrence frequency, the concentration should be set higher under steady-state atmospheric conditions than under annual hourly weather conditions. To obtain short setback distances (≤2 km), the odour occurrence frequencies for the same concentration level were different for the two weather conditions and depended on the concentration level selected.

Estimation of missing values in air pollution data using single imputation techniques

Air pollution data obtained using automated machines often contain missing values which can cause bias due to systematic differences between observed and unobserved data. We used interpolation and mean imputation techniques to replace simulated missing values from annual hourly monitoring data for PM10. The most effective method for generating the missing data points was to replace each missing value with the mean of the two data points before and after the missing value. This approach was referred to as the mean-before-after method.

Spatial variations in estimated chronic exposure to traffic-related air pollution in working populations: A simulation

BackgroundChronic exposure to traffic-related air pollution is associated with a variety of health impacts in adults and recent studies show that exposure varies spatially, with some residents in a community more exposed than others. A spatial exposure simulation model (SESM) which incorporates six microenvironments (home indoor, work indoor, other indoor, outdoor, in-vehicle to work and in-vehicle other) is described and used to explore spatial variability in estimates of exposure to traffic-related nitrogen dioxide (not including indoor sources) for working people. The study models spatial variability in estimated exposure aggregated at the census tracts level for 382 census tracts in the Greater Vancouver Regional District of British Columbia, Canada. Summary statistics relating to the distributions of the estimated exposures are compared visually through mapping. Observed variations are explored through analyses of model inputs.ResultsTwo sources of spatial variability in exposure to traffic-related nitrogen dioxide were identified. Median estimates of total exposure ranged from 8 μg/m3 to 35 μg/m3 of annual average hourly NO2 for workers in different census tracts in the study area. Exposure estimates are highest where ambient pollution levels are highest. This reflects the regional gradient of pollution in the study area and the relatively high percentage of time spent at home locations. However, for workers within the same census tract, variations were observed in the partial exposure estimates associated with time spent outside the residential census tract. Simulation modeling shows that some workers may have exposures 1.3 times higher than other workers residing in the same census tract because of time spent away from the residential census tract, and that time spent in work census tracts contributes most to the differences in exposure. Exposure estimates associated with the activity of commuting by vehicle to work were negligible, based on the relatively short amount of time spent in this microenvironment compared to other locations. We recognize that this may not be the case for pollutants other than NO2. These results represent the first time spatially disaggregated variations in exposure to traffic-related air pollution within a community have been estimated and reported.ConclusionThe results suggest that while time spent in the home indoor microenvironment contributes most to between-census tract variation in estimates of annual average exposures to traffic-related NO2, time spent in the work indoor microenvironment contributes most to within-census tract variation, and time spent in transit by vehicle makes a negligible contribution. The SESM has potential as a policy evaluation tool, given input data that reflect changes in pollution levels or work flow patterns due to traffic demand management and land use development policy.

Application of multiple wind-roses to improve the modelling of ground-level ozone in the UK

The Edinburgh Lancaster Model for Ozone (ELMO) has been previously used to predict ground-level ozone concentrations in the UK. Here we make significant improvements to its modelling performance by the application of more representative meteorology. We find that when ELMO is used with a series of distance weighted (DW) wind-roses, distributed across the whole of the UK, it closely predicts the 98th percentile of the annual hourly ozone concentration typical of summertime ozone episodes as validated against observations at 15 rural monitoring sites. There is, however, still some over-prediction of this metric in urban and sub-urban areas impacted by large emissions of NO x . We use ELMO with DW wind-roses to predict the effects of reductions of precursor emissions on ozone concentrations and demonstrate the extent to which the UK Air Quality Standard (AQS) for ozone is likely to be exceeded across the country in 2010.

Alternative energy facilities based on site matching and generation unit sizing for remote area power supply

This paper presents the decision support technique and influencing factors in the design of an integrated solar-wind power system for stand-alone applications. Results of investigations on application of alternative energy facility like wind, photovoltaic (PV), and Integration of wind–PV power generating systems for Remote Area Power Supply have been presented. A weather model-based site matching of equipment and a simple numerical algorithm for generation unit sizing have been presented. The program has been used to determine the optimum generation capacity and storage needs for a stand-alone Wind, PV, and integrated wind–PV system for a remote site in India (Sukhalai situated near Suktawa in Hoshangabad district of Madhya Pradesh) that satisfies a typical load. Generation and storage units for each system are properly sized in order to meet the annual load demand for the above three scenarios. Annual average hourly values for load, wind speed, and insolation have been used for analysis. The results are used to justify the use of renewable energy source as a reliable option for remote areas.