Average Visibility Research Articles

Anticipated Inversion and Visibility Conditions over Glacier Bay with a Changing Climate

A RCP4.5 simulation from the Community Earth System Model was downscaled by the Weather Research and Forecasting Model, inline coupled with chemistry, to examine how climate change may affect inversions and visibility in Glacier Bay in the presence of cruise-ship visitations. Mean downscaled climate conditions for the tourist seasons for 2006-2012 were compared with downscaled conditions for 2026-2032 with identical cruise-ship entries and operating conditions thereby isolating pollutant retention and visibility differences caused by atmospheric climate change. Notable changes in future temperature, humidity, precipitation, and wind-speed occurred for large areas of Southeast Alaska and the Gulf of Alaska, although the anticipated differences were less pronounced in Glacier Bay due to the presence of the large glaciers and ice fields. While increased sensible heat and water vapor in the atmospheric boundary layer contributed to on average 4.5 h reduced inversion duration in Glacier Bay, the on average 0.23 m·s-1 reduced wind speeds increased inversion frequency by 4% on average. The future on average wetter conditions and altered precipitation patterns in Glacier Bay affected the removal of gases and particulate matter emitted by cruise ships locally or advected from areas outside the park. Season-spatial averaged visibility in Glacier Bay remained the same. However, visibility was degraded in the future scenario later in the season and slightly improved during spring. The warmer conditions contributed to decreased visibility indirectly by tieing up less NO2 in PAN and increasing biogenic NOx emissions. The wetter conditions contributed to reduced visibility in the last third of the tourist season.

Precipitation and air pollution at mountain and plain stations in northern China: Insights gained from observations and modeling

AbstractWe analyzed 40 year data sets of daily average visibility (a proxy for surface aerosol concentration) and hourly precipitation at seven weather stations, including three stations located on the Taihang Mountains, during the summertime in northern China. There was no significant trend in summertime total precipitation at almost all stations. However, light rain decreased, whereas heavy rain increased as visibility decreased over the period studied. The decrease in light rain was seen in both orographic‐forced shallow clouds and mesoscale stratiform clouds. The consistent trends in observed changes in visibility, precipitation, and orographic factor appear to be a testimony to the effects of aerosols. The potential impact of large‐scale environmental factors, such as precipitable water, convective available potential energy, and vertical wind shear, on precipitation was investigated. No direct links were found. To validate our observational hypothesis about aerosol effects, Weather Research and Forecasting model simulations with spectral‐bin microphysics at the cloud‐resolving scale were conducted. Model results confirmed the role of aerosol indirect effects in reducing the light rain amount and frequency in the mountainous area for both orographic‐forced shallow clouds and mesoscale stratiform clouds and in eliciting a different response in the neighboring plains. The opposite response of light rain to the increase in pollution when there is no terrain included in the model suggests that orography is likely a significant factor contributing to the opposite trends in light rain seen in mountainous and plain areas.

A multi-year evolution of aerosol chemistry impacting visibility and haze formation over an Eastern Asia megacity, Shanghai

A multi-year (2004–2008) study of horizontal visibility and factors controlling its variations was conducted in Shanghai. The seasonal average visibility in spring, summer, autumn, and winter was 7.7 km, 8.4 km, 8.1 km, and 6.5 km, respectively, significantly exceeding the haze criteria of 10 km throughout all four seasons. Although SO2 and NO2 concentrations gradually shifted to lower levels on an annual basis, no distinct improvement of the annual mean visibility was noticed. Via a grouping method, it was found that the water soluble ions and black carbon were the major contributors to haze formation while the role of mineral aerosol was negligible. Of the ions, SO42−, NO3−, NH4+, K+, and C2O42− were most associated with the formation of heavy haze. SO42− and NO3− were both found to have significant decreasing trends with annual decreasing rates of 0.96 and 0.56 μg/m3/yr, respectively. Conversely, NH4+ showed a significant increasing trend with the annual increasing rate of 0.52 μg/m3/yr. Based on a quantitative correlation analysis, the roles of NH4+ and Ca2+ on the acids neutralization were almost equivalent in the earlier years of 2004–2005. While the role of Ca2+ had tremendously dropped to less than 23% in the later years of 2006–2008. Intense control measures on the emissions of construction works and roadside dust were the main driving force for the evident decreasing trend of annual Ca2+ concentrations. This study found that the gradual replacement of CaSO4 and Ca(NO3)2 by (NH4)2SO4 and NH4NO3 in aerosol was the major cause of no improvement of the visibility impairment in Shanghai during recent years.

Combining Automatic Tube Current Modulation with Adaptive Statistical Iterative Reconstruction for Low-Dose Chest CT Screening

ObjectiveTo reduce radiation dose while maintaining image quality in low-dose chest computed tomography (CT) by combining adaptive statistical iterative reconstruction (ASIR) and automatic tube current modulation (ATCM).MethodsPatients undergoing cancer screening (n = 200) were subjected to 64-slice multidetector chest CT scanning with ASIR and ATCM. Patients were divided into groups 1, 2, 3, and 4 (n = 50 each), with a noise index (NI) of 15, 20, 30, and 40, respectively. Each image set was reconstructed with 4 ASIR levels (0% ASIR, 30% ASIR, 50% ASIR, and 80% ASIR) in each group. Two radiologists assessed subjective image noise, image artifacts, and visibility of the anatomical structures. Objective image noise and signal-to-noise ratio (SNR) were measured, and effective dose (ED) was recorded.ResultsIncreased NI was associated with increased subjective and objective image noise results (P<0.001), and SNR decreased with increasing NI (P<0.001). These values improved with increased ASIR levels (P<0.001). Images from all 4 groups were clinically diagnosable. Images with NI = 30 and 50% ASIR had average subjective image noise scores and nearly average anatomical structure visibility scores, with a mean objective image noise of 23.42 HU. The EDs for groups 1, 2, 3 and 4 were 2.79±1.17, 1.69±0.59, 0.74±0.29, and 0.37±0.22 mSv, respectively. Compared to group 1 (NI = 15), the ED reductions were 39.43%, 73.48%, and 86.74% for groups 2, 3, and 4, respectively.ConclusionsUsing NI = 30 with 50% ASIR in the chest CT protocol, we obtained average or above-average image quality but a reduced ED.

Spatiotemporal pattern and regional characteristics of visibility in China during 1976–2010

Degradation in visibility occurs extensively across China, creating the urgent need to better understand visibility patterns and characteristics in China. Using daily observation data from the U.S. National Climatic Data Center (NCDC) during 1976–2010, the spatial distribution and temporal trends of visibility in China, as well as seasonal and regional characteristics, were determined. The distribution of visibility was characterized by a longitudinal gradient between west and east China. The northwest of China generally experienced consistent high visibility of >20 km, while central and eastern China experienced visibility degradation and increase in haziness. The 133 stations with significant downward trends in visibility were clustered around central-east China and the average reduction rate was −1.65 km/decade (from 18.5 km). The 96 stations with increasing trends of visibility were mostly on the Qinghai–Tibet Plateau and Xinjiang and were closely related to a reduction in local sand storms. The average visibility in 12 key regions in China varied between 9.9–17.8 km (except for 23.9 km in Urumqi), which was lower than the national average of 18.7 km. The Taiyuan–Hohhot, Guanzhong, Yangtze River Delta, Pearl River Delta and Fuzhou–Xiamen areas all encountered significant decreases in visibility, while minor increases were observed in Beijing–Tianjin–Hebei and the Cheng-Yu region. At most stations, the worst visibility was measured in winter, but the season with best visibility varied between regions. A comparison of visibility trends with the emission trends of various pollutants revealed that SO2 emissions dominated the visibility degradation in eastern China with NO x and volatile organic compounds playing ascending roles during the 2000s.

Comparative study on long-term visibility trend and its affecting factors on both sides of the Taiwan Strait

The rapid industrial development and urbanization has lead to increasing particulate matter pollution in the Cross Taiwan Strait Region, which has significant impacts on atmospheric visibility degradation. Long-term visibility trends in five typical cities over the cross-strait region (i.e., Xiamen and Fuzhou in the Western Taiwan Strait (WTS) region and Taipei, Taichung and Tainan in Taiwan) and its correlation with air quality and meteorological conditions were investigated using visibility and meteorological data during 1973–2011 and air pollution data during 2009–2011. For the entire period, the overall average visibilities in the WTS region were better than those in Taiwan, with an average of 16.8, 16.6, 8.5, 10.3 and 9.0km in Fuzhou, Xiamen, Taipei, Taichung and Tainan, respectively. Decline trends with decreasing rates of −0.5–0.1km/yr existed in all cities except Taipei, which had an improvement in visibility after 1992. All seasons had decreasing trends during the 39-year period except in Taipei. The WTS region had the worse change trend compared with Taiwan. No statistically significant weekend effect in visibility is found over the region. Visibilities were better in summer and autumn, while worse in winter and spring. Correlation analysis revealed that significant negative correlations existed between visibility and NO2 and airborne particles (i.e., PM10 and PM2.5); PM2.5 played an important role in visibility degradation. High temperature and low pressure is beneficial for better visibility. Principal component analysis further confirmed the impacts of high concentrations of air pollutants, stable synoptic systems and humid air with high relative humidity on visibility impairment. In addition, case studies highlighted characteristics and potential causes of typical regional low visibility episodes over the region.

Climate effects on performance of free space optical communication systems in Yemen

Free space optical (FSO) communication has been considered as an alternative to radio relay link line-of- sight (LOS) communication systems. The total attenuation is a combination of atmospheric attenuation in the atmosphere and geometric losses. The purpose of this paper is to study the geometric loss versus link range (in km), divergence angle, transmitter aperture diameter, and receiver aperture diameter. Total attenuation versus low visibility, average visibility, beam divergence, link range and rainfall rate were presented in this paper. Atmospheric attenuation (in dB) and scattering coefficient (in km -1 ) for several Yemeni main cities were explored. The study was concentrated on received power versus low and average visibilities and link range. Series of related simulation results were illustrated and discussed in this paper about the climate effects on performance of FSO communication systems in Yemen.

Seasonal Variation of Physical and Chemical Properties in TSP, PM10 and PM2.5 at a Roadside Site in Beijing and Their Influence on Atmospheric Visibility

In Beijing, capital of China, decreasing visibility has become a serious problem on people’s life, thus a hot environmental concern. An urban roadside site in Beijing was chosen to collect 24-h TSP, PM10 and PM2.5 samples for one month each season from June 2009 to March 2010. The PM mass concentrations, and the concentrations of ions, EC, OC and metals in PM10 and PM2.5 were measured, and their correlation with visibility, as well as the influence of weather factors on visibility were studied. The results showed that daily mean concentrations of TSP, PM10 and PM2.5 were 75–1350 µg/m3 (mean 275.8), 29–448 µg/m3 (mean 187) and up to 300 µg/m3 (mean 92.6), with the number of days exceeding the secondary standard (GB3095-2012) representing 33.3%, 59.8% and 51.0%, respectively. All PM concentrations were higher in spring than in other seasons. Obvious seasonal variations were observed for certain ions, OC, EC and metal concentrations in PM10 and PM2.5. Average mean visibility was low (5.64 km), showing better visibility in summer than in other seasons. PM10 and PM2.5 showed stronger negative correlation with visibility giving coefficients of –0.52 and –0.50. Almost all significant correlations were negative and occurred in autumn for visibility with TSP, PM10 and PM2.5, and with ions, EC and OC in both PM10 and PM2.5. The only positive and significant correlation was found between fine OC and visibility. Negative and significant correlations were also observed for visibility with humidity in autumn and winter, and with minimum temperature in all seasons but summer.

Relative Visibility of the Diagnostic Catheter

In this study a new algorithm was presented as an objective approach to quantify the relative visibility of diagnostic catheters. This method is suitable for the classification and comparison of diagnostic catheters with different levels of visibility, so as to attain an objective overall picture by measuring a product's properties, instead of relying on subjective values specified by the manufacturer. Our algorithm can be used when examining the distal section of a diagnostic catheter. Two sampling methods were tested on four diagnostic catheters with same diameter and material, but different shape of the distal end. The first sampling method can only be used in case of shapes that have straight sections at the distal end, but the second sampling method can be used for all types of shape. The first sampling method used a longer rectangular (4 mm x 8.6 mm) sample site and the second sampling method used two shorter rectangular (4 mm x 2.2 mm) sample sites. The two testing methods were used so as to check repeatability and reproducibility (R&R) so as to establish how far measurement repeatability with different measuring equipment, when carried out by different people, tracked differences between the different items being measured. This R&R testing helped us isolate where errors in our testing method might originate. It was established that the first (longer rectangle) sample-testing method had a nearly acceptable degree of variation (R&R% = 11.2), but the second method's degree (shorter rectangle) of variation was much worse (R&R% = 41). The value for average X-ray visibility obtained with the first method (18.24% ± 1.08%) when compared to the value for the second method (17.60% ± 1.66%), showed a significance level of 5.47%, and this approaches the borderline for significance. Precision and development of the measurement methods presented here will be treated as an integral part of further research so that they can be used equally with diagnostic catheters of all forms and shapes.

Open Courseware Repositories: An Analysis of Content Diversity and Visibility

Open Courseware (OCW) is one of the www's indispensable tools which are highly useful for stakeholders. But the utility and visibility of such resources can increase manifolds if they are highly index-able and visible through search engines. This paper is an endeavour to assess format diversity, web traffic, and visibility of select OCW repositories. The work sheds light on retrieval efficiency of different search engines vis-a-vis OCW. Open Courseware repositories that were enlisted under science and Technological Subjects in ‘Catalogue of Open Courseware Consortium’ were sifted and selected after thorough review of their OA policies. Out of 20 repositories indentified only 18 proved to be AO. A total of four repositories were short listed by way of random sampling for in-depth study in terms of their content diversity and visibility by prominent and special search engines (07). Among various formats, pdf is the most common format (52.31 per cent) archived by OCW repositories. OCW visibility differs from search engine. ‘Google’ turned to be most reliable tool by retrieving 73.58 per cent OCWs while ‘incywincy’ retrieved none. General search engines (73.58 per cent − 52.44 per cent) have shown very good performance compared to special search engines (42.68 per cent − 0 per cent). Among the repositories ‘Open Michigan’ is most visible Open Courseware repository with 70 per cent average visibility whereas ‘NJIT’ is least visible (29.82 per cent.)

Bayesian Model Averaging: An Application to the Determinants of Airport Departure Delay in Uganda

Bayesian model averaging was employed to study the dynamics of aircraft departure delay based on airport operational data of aviation and meteorological parameters collected on daily basis for the period 2004 through 2008 in matrix X. Models were evaluated using the R programming language mainly to establish the combinations of variables that could formulate the best model through assessing their importance. Findings showed that out of the sixteen covariates, 62.5% were suitable for model inclusion to determine aircraft departure delay of which 40% exhibited negative coefficients. The following parameters were found to negatively affect departure delay; number of aircrafts that departed on time (-0.562), number of persons on board of the arriving aircrafts (-0.002), daily average visibility (-0.001) and year (-1.605). Comparison between Posterior Model Probabilities (PMP Exact) and that based on Markov Chain Monte Carlo (PMP MCMC) revealed a high correlation (0.998; p<0.01).The study recommended the MCMC as providing a more efficient approach to modelling the determinants of aircraft departure delay at an airport.

Статистический анализ эволюции прозрачности атмосферы в г. Москве

The co-authors discuss the statistical analysis results of the atmospheric transparency evolution in Moscow territory within the last 35 years. The analysis shows the statistical increase of the global warming impact on the growing daily average visibility or the atmospheric transparency. The article presents statistical regularities of the risk increase of the atmosphere transparency deviations from its multiyear averages. The article notes the impact of atmospheric transparency on the risk of the increase in the weather anomalies, roof icing, as well as icing of power supply systems and communication, roads, bridges and other transport construction objects. It is also noted that the increase in temperature fluctuations amplitude, humidity, rainfall and other climatic loads leads to accelerated deterioration of building structures. The average increase in the number of atmospheric high transparency realizations increased almost 1.5 times for the last 35 years.If the trend persists for the current urban planning period (e.g., 100 years), the3,37 times increase in the number of days with high transparency is very realistic. The increase in atmosphere transparency will be accompanied by the concomitant rise of temperature, humidity, precipitation and wind speed oscillations.With the increasing duration of windless seasons we should also expect the concomitant growing risks of dry, hot and fire seasons. Such a global climate change process is of great importance for investors, self-regulatory organizations, owners of construction objects, managing and energy companies and insurers. It is also essential for municipal, regional and Federal urban planning companies.This problem in Russia and abroad is significantly intensified by previously unexpected growth of hazardous man-made and natural, climatic, geological and geophysical processes. These factors cause new and, as a result, non-normalized loads and impacts on buildings, structures and geoecological systems of the urbanized territories, which are beyond the project. In addition to the statistical data analysis of the Moscow atmospheric transparency evolution the authors also performed similar research on daily average visibility in different locations and on different continents.Such studies have been conducted by the authors in such cities as New-York, Anchorage, Buenos Aires, Niamey, London, Tokyo, Canberra and other cities of the planet. The analysis of geographical manifestations of atmosphere transparency evolution as a result of global climate change showed that the daily average visibility evolution observed in Moscow is of global nature. These results will be published by the authors in the coming series of articles on the subject.Global warming creates the problems of food security, urban population sustainment and construction adaptation to the new climatic realities in long perspective of urban planning. Solar radiation effect on the structures of buildings are among the most important climatic loads, which are taken into account in the regulations in the process of buildings and structures design.However, the excising regulatory documents contain no data about the evolution of solar irradiation over the building constructions throughout the buildings life cycle as a result of the continuing global warming. This remark also refers to the radiation intensity change as a result of the transparency or daily average visibility evolution.

The Impact of Air Pollutants and Meteorological Variables on Visibility in Delhi

A study has been made to analyze the impact of air pollutants and meteorological variables on visibility in Delhi, for the years 2003–2006. The correlation matrix of daily visibility, meteorological variables, and air pollutants concentration during the period has been studied. The matrix reflects the negative values of the correlation coefficient of visibility with respirable suspended particulate matter, suspended particulate matter, relative humidity, and, positive values with dry bulb temperature, maximum temperature, minimum temperature, and sunshine hours. The annual average visibility has been estimated as approximately 2.77 km. Furthermore, it is found to be maximum in monsoon, followed by summer, post-monsoon, and winter seasons. It is also noticeable that the visibility is always higher in rainy days when compared with that in dry days. Similarly, the annual average visibility during the weekends is found to be higher than that in the weekdays. The daily visibility has been forecasted through two statistical techniques namely, multiple linear regression (MLR) and principal component regression (PCR). The results obtained from these two techniques have been evaluated by comparing with observed data. This proves satisfactory performance of both the techniques. In addition, it reflects that the PCR performs better than the MLR technique.

VisibilityCluster: Average Directional Visibility for Many-Light Rendering

This paper proposes the VisibilityCluster algorithm for efficient visibility approximation and representation in many-light rendering. By carefully clustering lights and shading points, we can construct a visibility matrix that exhibits good local structures due to visibility coherence of nearby lights and shading points. Average visibility can be efficiently estimated by exploiting the sparse structure of the matrix and shooting only few shadow rays between clusters. Moreover, we can use the estimated average visibility as a quality measure for visibility estimation, enabling us to locally refine VisibilityClusters with large visibility variance for improving accuracy. We demonstrate that, with the proposed method, visibility can be incorporated into importance sampling at a reasonable cost for the many-light problem, significantly reducing variance in Monte Carlo rendering. In addition, the proposed method can be used to increase realism of local shading by adding directional occlusion effects. Experiments show that the proposed technique outperforms state-of-the-art importance sampling algorithms, and successfully enhances the preview quality for lighting design.

Study on atmospheric visibility variations and the impacts of meteorological parameters using high temporal resolution data: an application of Environmental Internet of Things in China

Atmospheric visibility degradation in China is an important environmental issue because it has been demonstrated to be associated with air pollution. One-year of high temporal resolution visibility data and meteorological parameters including precipitation, relative humidity (RH), wind speed (WS), and wind direction (WD) during June 2011–May 2012 were obtained at Long-term Urban Ecosystems Observation and Research Station in Xiamen (Xiamen LUEORS) by means of Environmental Internet of Things (EIoT) technology. The visibility and meteorological data were analyzed to study the temporal variation of atmospheric visibility and its relationship with meteorological parameters in this region. Optimal empirical regression models were also developed to predict visibility based on meteorological parameters. The annual average visibility during the study period is 8969 m, with 63.2% of the total measurements less than 10 km. ‘Bad’ visibility (i.e., visibility < 10 km) is prone to occur in late winter to early spring. Visibility exhibited a distinct diurnal variation with the minimum of 6508 m at 6:00 Local Time (LT) and the maximum of 11,378 m at 13:00 LT. Visibility is higher in summer (11,410 m) and autumn (10,589 m) than in winter (7070 m) and spring (6807 m), with the highest (12,141 m) and lowest (5376 m) value occurred in August and February, respectively. During hazy, foggy, and rainy periods, the average visibilities were 5020 m, 1044 m, and 3967 m, respectively, much lower than those during normal period (15,970 m). Precipitation decreased the frequency of ‘good’ visibility (i.e., visibility ≥ 10 km) by 1.4% and increased the frequency of ‘extremely bad’ visibility (i.e., visibility < 2 km) by 1.5% during the year. Visibility was mostly below 10 km when the 10-min precipitation was larger than 0.6 mm. No significant correlation exists between visibility change and precipitation. For RH ≥ 80%, over 90% of the visibilities are below 10 km. The average visibility is below 8 km for RH ≥ 70%. For WS < 1.0 m/s, over 80% of the visibilities are below 10 km. When WS < 2.0 m/s, the average visibility is below 9 km. Visibility is negatively correlated with RH and positively correlated with WS, with the annual correlation coefficients of –0.507 and 0.494, respectively. It is prone to have ‘bad’ visibility when the wind is blowing from west and northwest. An optimal empirical multiple regression model based on meteorological parameters can moderately simulate the visibility. The results provide new knowledge for better understanding the characteristics of visibility and its relationship with meteorological parameters, based on which a statistical model for predicting the visibility in this region was developed.

Long-term trends and characteristics of visibility in two megacities in southwest China: Chengdu and Chongqing

Visibility is a good indicator of air quality because it reflects the combined influences of atmospheric pollutants and synoptic processes. Trends in visibility and relationships with various factors in Chengdu and Chongqing, two megacities in southwest China, were analyzed using daily data from National Climatic Data Center and the Air Pollution Index (API) of the Ministry of Environmental Protection of China. Average annual visibility during the period of 1973–2010 was 8.1 ± 3.9 in Chengdu and 6.2 ± 4.3 km in Chongqing. PM10 dominates the reported primary pollutants in both cities, although concentrations have decreased from a high of 127.9 and 150 µg m3 before 2005 to 100.4 and 93.5 µg m−3 in Chengdu and Chongqing, respectively. Low average visibility and extremely high levels of PM10 were observed in winter, whereas relative humidity had irregular and weak seasonal variations. Visibility in both cities has deteriorated in comparison to the 1960s and 1970s, mostly due to the elevation of optical depth caused by anthropogenic pollution. Correlations and principal component analysis (PCA) were undertaken to determine the key factors affecting visibility. Visibility was only moderately correlated with PM10. In Chengdu, visibility displayed weak correlations with various factors, whereas visibility in Chongqing was most strongly related to relative humidity due to the atmospheric particulates in the region containing more hygroscopic components. PCA results further confirmed that high relative humidity and low wind speed increased the occurrence of low visibility events under high PM10 concentrations. Temperature and pressure, as indicators of weather systems, also played important roles in affecting visibility. Mathematical models of visibility prediction indicated that wind speed had the largest coefficients among all meteorological factors, and reductions in PM10 concentration only led to minor improvements in visibility. Implications: Long-term data indicates that visibility in Chengdu and Chongqing has been lower than 10 km since the 1970s, and the poor visibility primarily results from anthropogenic pollution. Although PM10 concentrations have decreased consistently to around 100 μg m−3, trends of visibility have shown no improvement but much fluctuation. Correlation and principal component analysis demonstrate that low visibility in Chengdu is influenced by high relative humidity, while in Chongqing the degrading visibility is related with high relative humidity and pressure and low wind speed under a stable weather system. The results are important to understand the widespread haze event in the two megacities of southwest China. Supplemental Materials: Supplemental materials are available for this paper. Go to the publisher's online edition of the Journal of the Air & Waste Management Association.

Estimating the Impact of Impaired Visibility on the Demand for Visits to National Parks

The authors fitted a number of time-series econometric models to monthly visitation data of a national park to examine the effect of impaired visibility on visitation demand. Using a polynomial distributed lag model, the long-run elasticity of demand with respect to visibility in the Great Smoky Mountain National Park (GSMNP) was estimated. The GSMNP, the most visited national park in the USA, has significant air quality issues. Although the park has observed some fluctuation in visitation, the results indicate that the demand for visitation in general and for specific recreational visits are mean reverting and highly stable. Further, park visitation in a given month is significantly affected by the cumulative effect of the visibility condition in both the current and preceding months. Estimated elasticity reveals that a programme aiming to improve the average visibility by 10% (5.5 km) from the current level could result in an increase of roughly one million recreational visits annually, and that the increase would be higher for overnight visitors than for day visitors because of overnight visitors' relatively elastic demand. This demand model could assist park managers in their planning as they weigh the anticipated benefits of a visibility improvement programme against increased visitation and its associated costs.

Global Warming: The Instability of Desert Climate is Enhancing in the Northwest Area in China: A Case Study in the Desert Area in Northwestern China

To disclose the relation between the sandstorms change and the temperature changes, a case study in the desert area in northwestern china is investigated. The results showed that: the instability of climate in Minqin desert area is enhancing in the arid desert region in northwest China. Mainly as follows: Variation the annual extreme maximum temperature increasing. Variation of extreme minimum temperature also an increasing trend. Average visibility of sandstorms significantly reduced and the fluctuation trend increased significantly. In the past two years, there have been some unusual climate events in other regions in China. They reflect the fact that the deterioration of the stability of the climate change. The instability of the climate change impact on human life and production is increased more than global warming, more worthy of global concern.

Analysis of long-term ozone trend over Delhi and its meteorological adjustment

Present study deals with the statistical analysis of long-term ground level ozone (O3) trend and the influence of meteorological variables on its variation over Delhi, India. Daily mean and maximum of O3 and meteorological data, obtained from India Meteorological Department, were arranged for the period of 9 years (1998–2006). Based on the preliminary correlation study of all the data with O3, six variables viz. daily maximum temperature, daily average relative humidity, dew point, wind speed, visibility, and total sunshine were selected. Classical additive time series decomposition technique was used to obtain seasonally adjusted long-term trend. To analyze the masking effect of meteorology, adjustment was made using Kolmogorov–Zurbenko filters followed by stepwise regression analysis to the smoothed series of O3 maximum and meteorological variables, which showed that long-term trend was independent of sunshine duration. Results indicate a significant increasing trend with annual increase of 1.13 % for O3 mean and 3 % for O3 maximum. Annual deseasonalized trend for seasonal cycle shows bimodal oscillations. About 43 % of O3 variation was explained by the selected meteorological factors and rest of variation attributed to factors like emission of precursor gases, pollutant transport, policy changes, etc. Among the three tested regression models, performance of Model 2 with variable temperature, wind speed, and visibility was found to be best that resulted in lowering of O3 trend. Large variability (23 %) was explained by the variable visibility depicted that the emission of primary pollutants not only provides the precursor gases but also control the local photochemical reactions.

A route-based visibility analysis for landscape management

Viewsheds and similar visibility analyses are used for a wide range of applications. These analyses were not originally designed for applications which are human-centered, such as with landscape planning. In these cases, a viewshed should be able to link a visibility evaluation to aspects of vision and perception. Visual Magnitude provides a way to calculate the amount of visibility by quantifying the effect of slope, aspect and distance of an area relative to the observer. We propose a new way of adapting Visual Magnitude for route-based applications so that planners can better understand not just how much is visible, but how what is visible may relate to an individual's judgment and response. The approach is tested using a popular tourist highway route through the Clayoquot Sound UNESCO Biosphere Reserve located on Vancouver Island of British Columbia, Canada. The outputs are: a probability surface of the average visibility of the visual space on the landscape, the maximum visibility from along the route, and from where this occurs. The results are 2D GIS-based images that enable the planner to identify areas where emotional peak responses may occur, in order to maximize viewing opportunities of beautiful areas or mitigate potential negative responses from these locations. This research represents a shift toward the development of geographic information system tools that provide vital information important for making decisions with people as the focus.