Wood annual average increment and K, Ca and Mg mineral compartments in soils cultivated with eucalypt

Meteorological information at an arrival airport is one of the primary variables used to determine refueling of discretionary fuel. This study evaluated the economic value of terminal aerodrome forecasts (TAF), which has not been previously quantitatively analyzed in Korea. The analysis data included 374,716 international flights that arrived at Incheon airport during 2017–2019. A cost–loss model was used for the analysis, which is a methodology to evaluate forecast value by considering the cost and loss that users can expect, considering the decision-making result based on forecast utilization. The value was divided in terms of improving fuel efficiency and reducing CO2 emissions. The results of the analysis indicate that the annual average TAF value for Incheon Airport was approximately 2.2 M–20.1 M USD under two hypothetical rules of refueling of discretionary fuel. This value is up to 26.2% higher than the total budget of 16.3 M USD set for the production of aviation meteorological forecasts by the Korea Meteorological Administration (KMA). Further, it is up to 10 times greater than the 2 M USD spent on aviation meteorological information fees collected by the KMA in 2018.

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Development of unmanned aerial vehicle (UAV) networks delivering early defibrillation for out-of-hospital cardiac arrests (OHCA) in areas lacking timely access to emergency medical services (EMS) in Germany: a comparative economic study

BMJ Open ◽

10.1136/bmjopen-2020-043791 ◽

2021 ◽

Vol 11 (1) ◽

pp. e043791

Author(s):

Jan Bauer ◽

Dieter Moormann ◽

Reinhard Strametz ◽

David A Groneberg

Keyword(s):

Cost Effectiveness ◽

Emergency Medical Services ◽

Rural Areas ◽

Medical Services ◽

Secondary Outcome ◽

Annual Average ◽

Emergency Medical ◽

Life Years ◽

Timely Access ◽

The Cost

ObjectivesThis study wants to assess the cost-effectiveness of unmanned aerial vehicles (UAV) equipped with automated external defibrillators (AED) in out-of-hospital cardiac arrests (OHCA). Especially in rural areas with longer response times of emergency medical services (EMS) early lay defibrillation could lead to a significant higher survival in OHCA.Participants3296 emergency medical stations in Germany.SettingRural areas in Germany.Primary and secondary outcome measuresThree UAV networks providing 80%, 90% or 100% coverage for rural areas lacking timely access to EMS (ie, time-to-defibrillation: >10 min) were developed using a location allocation analysis. For each UAV network, primary outcome was the cost-effectiveness using the incremental cost-effectiveness ratio (ICER) calculated by the ratio of financial costs to additional life years gained compared with current EMS.ResultsCurrent EMS with 3926 emergency stations was able to gain 1224 life years on annual average in the study area. The UAV network providing 100% coverage consisted of 1933 UAV with average annual costs of €43.5 million and 1845 additional life years gained on annual average (ICER: €23 568). The UAV network providing 90% coverage consisted of 1074 UAV with average annual costs of €24.2 million and 1661 additional life years gained on annual average (ICER: €14 548). The UAV network providing 80% coverage consisted of 798 UAV with average annual costs of €18.0 million and 1477 additional life years gained on annual average (ICER: €12 158).ConclusionThese results reveal the relevant life-saving potential of all modelled UAV networks. Furthermore, all analysed UAV networks could be deemed cost-effective. However, real-life applications are needed to validate the findings.

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Digital Mapping of Soil Organic Carbon Using Sentinel Series Data: A Case Study of the Ebinur Lake Watershed in Xinjiang

Remote Sensing ◽

10.3390/rs13040769 ◽

2021 ◽

Vol 13 (4) ◽

pp. 769

Author(s):

Xiaohang Li ◽

Jianli Ding ◽

Jie Liu ◽

Xiangyu Ge ◽

Junyong Zhang

Keyword(s):

Remote Sensing ◽

Organic Carbon ◽

Soil Organic Carbon ◽

Prediction Accuracy ◽

Lake Basin ◽

Arid Areas ◽

Annual Average ◽

Machine Learning Methods ◽

Ebinur Lake ◽

Ebinur Lake Basin

As an important evaluation index of soil quality, soil organic carbon (SOC) plays an important role in soil health, ecological security, soil material cycle and global climate cycle. The use of multi-source remote sensing on soil organic carbon distribution has a certain auxiliary effect on the study of soil organic carbon storage and the regional ecological cycle. However, the study on SOC distribution in Ebinur Lake Basin in arid and semi-arid regions is limited to the mapping of measured data, and the soil mapping of SOC using remote sensing data needs to be studied. Whether different machine learning methods can improve prediction accuracy in mapping process is less studied in arid areas. Based on that, combined with the proposed problems, this study selected the typical area of the Ebinur Lake Basin in the arid region as the study area, took the sentinel data as the main data source, and used the Sentinel-1A (radar data), the Sentinel-2A and the Sentinel-3A (multispectral data), combined with 16 kinds of DEM derivatives and climate data (annual average temperature MAT, annual average precipitation MAP) as analysis. The five different types of data are reconstructed by spatial data and divided into four spatial resolutions (10, 100, 300, and 500 m). Seven models are constructed and predicted by machine learning methods RF and Cubist. The results show that the prediction accuracy of RF model is better than that of Cubist model, indicating that RF model is more suitable for small areas in arid areas. Among the three data sources, Sentinel-1A has the highest SOC prediction accuracy of 0.391 at 10 m resolution under the RF model. The results of the importance of environmental variables show that the importance of Flow Accumulation is higher in the RF model and the importance of SLOP in the DEM derivative is higher in the Cubist model. In the prediction results, SOC is mainly distributed in oasis and regions with more human activities, while SOC is less distributed in other regions. This study provides a certain reference value for the prediction of small-scale soil organic carbon spatial distribution by means of remote sensing and environmental factors.

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A Study on Urban Inundation Using SWMM in Busan, Korea, Using Existing Dams and Artificial Underground Waterways

Water ◽

10.3390/w13121708 ◽

2021 ◽

Vol 13 (12) ◽

pp. 1708

Author(s):

Yeon-Moon Choo ◽

Sang-Bo Sim ◽

Yeon-Woong Choe

Keyword(s):

Climate Change ◽

Urban Areas ◽

Flood Damage ◽

Virtual Model ◽

Sustainable Cities ◽

Annual Average ◽

New Methods ◽

Average Rainfall ◽

Reduction Methods ◽

Urbanized Areas

The annual average rainfall in Busan area is increasing, causing frequent flooding of Busan’s Suyeong and Oncheon rivers. Due to the increase in urbanized areas and climate change, it is difficult to reduce flood damage. Therefore, new methods are needed to reduce urban inundation. This study models the effects of three flood reduction methods involving Oncheon River, Suyeong River, and the Hoedong Dam, which is situated on the Suyeong. Using EPA-SWMM, a virtual model of the dam and the rivers was created, then modified with changes to the dam’s height, the installation of a floodgate on the dam, and the creation of an underground waterway to carry excess flow from the Oncheon to the Hoedong Dam. The results of this study show that increasing the height of the dam by 3 m, 4 m, or 6 m led to a 27%, 37%, and 48% reduction in flooding, respectively, on the Suyeong River. It was also found that installing a floodgate of 10 × 4 m, 15 × 4 m, or 20 × 4 min the dam would result in a flood reduction of 2.7% and 2.9%, respectively. Furthermore, the construction of the underground waterway could lead to an expected 25% flood reduction in the Oncheon River. Measures such as these offer the potential to protect the lives and property of citizens in densely populated urban areas and develop sustainable cities and communities. Therefore, the modifications to the dam and the underground waterway proposed in this study are considered to be useful.

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Long-term effects of fine particulate matter exposure on the progression of arterial stiffness

Environmental Health ◽

10.1186/s12940-020-00688-6 ◽

2021 ◽

Vol 20 (1) ◽

Author(s):

Dianqin Sun ◽

Yue Liu ◽

Jie Zhang ◽

Jia Liu ◽

Zhiyuan Wu ◽

...

Keyword(s):

Arterial Stiffness ◽

Health Management ◽

Ankle Brachial Index ◽

Population Data ◽

Average Concentration ◽

Air Pollutant ◽

Stiffness Index ◽

Long Term Effects ◽

Annual Average

Abstract Background Prior studies have investigated the association of PM2.5 exposure with arterial stiffness measured by ankle-brachial index (ABI) and brachial-ankle pulse wave velocity (baPWV), of which conclusions are inconsistent. Moreover, limited evidence is available on the contributory role of PM2.5 exposure on the arterial stiffness index. Methods We used the population data from the Beijing Health Management Cohort and conducted a longitudinal analysis. The annual average concentration of PM2.5 for 35 air pollutant monitoring sites in Beijing from 2014 to 2018 was used to estimate individual exposure by different interpolation methods. Multivariate logistic regression and linear regression were conducted to assess the association of annual average PM2.5 concentration with the incidence of higher baPWV, the progression of ABI, and baPWV, respectively. Results The association between PM2.5 exposure and incidence of higher baPWV was not significant (OR = 1.11, 95% CI: 0.82–1.50, P = 0.497). There was − 0.16% (95% CI: − 0.43-0.11%) decrease in ABI annually and 1.04% (95% CI: 0.72–1.37%) increase in baPWV annually with each increment of 10 μg/m3 average PM2.5 concentration. Conclusions Long-term exposure to PM2.5 was associated with the progression of arterial stiffness in Beijing. This study suggests that improvement of air quality may help to prevent arterial stiffness.

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Spatial Variation of the Relationship between PM2.5Concentrations and Meteorological Parameters in China

BioMed Research International ◽

10.1155/2015/684618 ◽

2015 ◽

Vol 2015 ◽

pp. 1-15 ◽

Cited By ~ 10

Author(s):

Gang Lin ◽

Jingying Fu ◽

Dong Jiang ◽

Jianhua Wang ◽

Qiao Wang ◽

...

Keyword(s):

Negative Correlation ◽

Meteorological Parameters ◽

Semiarid Region ◽

Strong Positive Correlation ◽

Annual Average ◽

Strong Negative Correlation ◽

Positive Correlation ◽

Humid Region ◽

The Relationship ◽

Warm Temperate

Epidemiological studies around the world have reported that fine particulate matter (PM2.5) is closely associated with human health. The distribution of PM2.5concentrations is influenced by multiple geographic and socioeconomic factors. Using a remote-sensing-derived PM2.5dataset, this paper explores the relationship between PM2.5concentrations and meteorological parameters and their spatial variance in China for the period 2001–2010. The spatial variations of the relationships between the annual average PM2.5, the annual average precipitation (AAP), and the annual average temperature (AAT) were evaluated using the Geographically Weighted Regression (GWR) model. The results indicated that PM2.5had a strong and stable correlation with meteorological parameters. In particular, PM2.5had a negative correlation with precipitation and a positive correlation with temperature. In addition, the relationship between the variables changed over space, and the strong negative correlation between PM2.5and the AAP mainly appeared in the warm temperate semihumid region and northern subtropical humid region in 2001 and 2010, with some localized differences. The strong positive correlation between the PM2.5and the AAT mainly occurred in the mid-temperate semiarid region, the humid, semihumid, and semiarid warm temperate regions, and the northern subtropical humid region in 2001 and 2010.

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Year-to-year Variations in Annual Average Indoor 222Rn Concentrations

Health Physics ◽

10.1097/00004032-199109000-00012 ◽

1991 ◽

Vol 61 (3) ◽

pp. 409-413 ◽

Cited By ~ 23

Author(s):

Dowell E. Martz ◽

Arthur S. Rood ◽

Joan L. George ◽

Mark D. Pearson ◽

G. Harold Lang

Keyword(s):

Annual Average

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Design and operation of an eco-system for municipal wastewater treatment and utilization

Water Science & Technology ◽

10.2166/wst.2006.923 ◽

2006 ◽

Vol 54 (11-12) ◽

pp. 429-436 ◽

Cited By ~ 8

Author(s):

L. Wang ◽

J. Peng ◽

B. Wang ◽

L. Yang

Keyword(s):

Wastewater Treatment ◽

Constructed Wetland ◽

Municipal Wastewater ◽

Activated Sludge Process ◽

Municipal Wastewater Treatment ◽

Annual Average ◽

Total Capital ◽

Dongying City ◽

Final Effluent ◽

Better Than

An eco-system consisting of integrated ponds and constructed wetland systems is employed in Dongying City, Shandong Province for the treatment and utilization of municipal wastewater with design capacity of 100,000 m3/d. The total capital cost of this system is 680 Yuan (RMB) or US$82/m3/d, or about half that of the conventional system based on activated sludge process, and the O/M cost is 0.1 Yuan (RMB) or US$ 0.012/m3, only one fifth that of conventional treatment systems. The performance of the wastewater treatment and utilization eco-system is quite good with a final effluent COD, BOD, SS, NH3-N and TP of 45–65 mg/l, 7–32 mg/l, 12–35 mg/l, 2–13 mg/l and 0.2–1.8 mg/l respectively and the annual average removals of COD, BOD, SS, NH3-N and TP are 69.1%, 78.3%, 76.4%, 62.1% and 52.9% respectively, which is much better than that of conventional pond system or constructed wetland used separately and illustrates that the artificial and integrated eco-system is more effective and efficient than the simple natural eco-system.

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