scholarly journals Satellite Observations of PM2.5 Changes and Driving Factors Based Forecasting Over China 2000–2025

2020 ◽  
Vol 12 (16) ◽  
pp. 2518
Author(s):  
Ying Zhang ◽  
Zhengqiang Li ◽  
Wenyuan Chang ◽  
Yuanxun Zhang ◽  
Gerrit de Leeuw ◽  
...  
Keyword(s):  
Satellite Data ◽  
Average Rate ◽  
Fine Particulate Matter ◽  
Driving Factors ◽  
Control Measures ◽  
Anthropogenic Factors ◽  
Historical Period ◽  
A Value ◽  
Meteorological Influences

In China, atmospheric fine particulate matter (PM2.5) pollution is a challenging environmental problem. Systematic PM2.5 measurements have started only in 2013, resulting in a lack of historical data which is a key obstacle for the analysis of long-term PM2.5 trends and forecasting the evolution over this hot region. Satellite data can provide a new approach to derive historical PM2.5 information provided that the column-integrated aerosol properties can adequately be converted to PM2.5. In this study, a recently developed formulation for the calculation of surface PM2.5 concentrations using satellite data is introduced and applied to reconstruct a PM2.5 time series over China from 2000 to 2015. The formulated model is also used to explore the PM2.5 driving factors related to anthropogenic or meteorological parameters in this historical period. The results show that the annually averaged PM2.5 over China’s polluted regions increased rapidly between 2004 and 2007 (with an average rate of 3.07 μg m−3 yr−1) to reach values of up to 61.1 μg m−3 in 2007, and decreased from 2011 to 2015 with an average rate of −2.61 μg m−3 yr−1, to reach a value of 46.9 μg m−3 in 2015. The analysis shows that the increase in PM2.5 before 2008 was mainly associated with increasing anthropogenic factors, further augmented by the effect of meteorological influences. However, the decrease in PM2.5 after 2011 is mainly attributed to the effect of pollution control measures on anthropogenic factors, whereas the effects of meteorological factors have continued to increase since 2000. The results also suggest that further reduction in anthropogenic emissions is needed to accelerate the decrease in PM2.5 concentrations to reach the target of 35 μg m−3 over major polluted areas in China before 2025.

scholarly journals Trends in PM2.5 Concentration in Nagoya, Japan, from 2003 to 2018 and Impacts of PM2.5 Countermeasures

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 590
Author(s):  
Makiko Yamagami ◽  
Fumikazu Ikemori ◽  
Hironori Nakashima ◽  
Kunihiro Hisatsune ◽  
Kayo Ueda ◽  
...  
Keyword(s):  
Fine Particulate Matter ◽  
Control Measures ◽  
Source Control ◽  
Atmospheric Concentration ◽  
Construction Machinery ◽  
Emission Regulations ◽  
Volatile Organic ◽  
Stationary Sources ◽  
Pm2.5 Concentration

In Japan, various countermeasures have been undertaken to reduce the atmospheric concentration of fine particulate matter (PM2.5). We evaluated the extent to which these countermeasures were effective in reducing PM2.5 concentrations by analyzing the long-term concentration trends of the major components of PM2.5 and their emissions in Nagoya City. PM2.5 concentrations decreased by 53% over the 16-year period from fiscal years 2003 to 2018 in Nagoya City. Elemental carbon (EC) was the component of PM2.5 with the greatest decrease in concentration over the 16 years, decreasing by 4.3 μg/m3, followed by SO42− (3.0 μg/m3), organic carbon (OC) (2.0 μg/m3), NH4+ (1.6 μg/m3), and NO3− (1.3 μg/m3). The decrease in EC concentration was found to be caused largely by the effect of diesel emission control. OC concentrations decreased because of the effects of volatile organic compound (VOC) emission regulations for stationary sources and reductions in VOCs emitted by vehicles and construction machinery. NO3− concentrations decreased alongside decreased contributions from vehicles, construction machinery, and stationary sources, in descending order of the magnitude of decrease. Although these findings identify some source control measures that have been effective in reducing PM2.5, they also reveal the ineffectiveness of some recent countermeasures for various components, such as those targeting OC concentrations.

SATELLITE DATA FOR INVESTIGATION OF RECENT STATE AND PROCESSES IN THE SIVASH BAY

2017 ◽  
Author(s):  
Ekaterina Shchurova ◽  
Ekaterina Shchurova ◽  
Rimma Stanichnaya ◽  
Rimma Stanichnaya ◽  
Sergey Stanichny ◽  
...  
Keyword(s):  
Satellite Data ◽  
Water Exchange ◽  
High Salinity ◽  
Meteorological Data ◽  
Sea Surface ◽  
Azov Sea ◽  
Seasonal Wind ◽  
Ice Regime ◽  
Very High

Sivash bay is the shallow-water lagoon of the Azov Sea. Restricted water exchange and high evaporation form Sivash as the basin with very high salinity. This factor leads to different from the Azov Sea thermal and ice regimes of Sivash. Maine aim of the study presented to investigate recent state and changes of the characteristics and processes in the basin using satellite data. Landsat scanners TM, ETM+, OLI, TIRS together with MODIS and AVHRR were used. Additionally NOMADS NOAA and MERRA meteorological data were analyzed. The next topics are discussed in the work: 1. Changes of the sea surface temperature, ice regime and relation with salinity. 2. Coastal line transformation – long term and seasonal, wind impact. 3. Manifestation of the Azov waters intrusions through the Arabat spit, preferable wind conditions.

THE USE OF HISTORICAL DATA IN ACCOUNTING RESEARCH: THE CASE OF THE AMERICAN SUGAR REFINING COMPANY

1997 ◽  
Vol 24 (2) ◽  
pp. 1-24 ◽  
Author(s):  
Robert Bricker ◽  
Kevin Brown
Keyword(s):  
Capital Market ◽  
Historical Data ◽  
Abnormal Returns ◽  
Deep Understanding ◽  
Historical Record ◽  
Historical Period ◽  
Financial Condition ◽  
A Value ◽  
Time Period ◽  
And Performance

In 1908, the American Sugar Refining Company (ASR) reversed its long-held policy of secrecy as to its financial condition and performance. Prior work, applying contemporary capital market methods to ASR security price data of that period, has suggested a value to ASR shareholders of this policy reversal. This paper examines the historical record of that time and presents additional evidence on this matter, particularly in terms of identifying potentially confounding events occurring during the period under study. The results of this analysis suggest a difficulty in attributing observed abnormal returns to ASR's secrecy policy reversal on the basis of the results obtained from applying capital markets methods. This analysis is useful for scholars interested in applying modern capital market methods to historical data. It highlights the significance of the possible effects of contemporaneous historical events, focuses attention on the importance of a deep understanding of the historical period studied, and suggests a value in combining historical and empirical-markets methods to gain a richer understanding of the events and conditions in the time period under study.

scholarly journals Climate drivers of plague epidemiology in British India, 1898–1949

2020 ◽  
Vol 287 (1928) ◽  
pp. 20200538
Author(s):  
Warren S. D. Tennant ◽  
Mike J. Tildesley ◽  
Simon E. F. Spencer ◽  
Matt J. Keeling
Keyword(s):  
Predictive Models ◽  
Control Measures ◽  
Climate Data ◽  
British India ◽  
Middle Income ◽  
Middle Income Countries ◽  
Complex Interactions ◽  
The World ◽  
Spatio Temporal

Plague, caused by Yersinia pestis infection, continues to threaten low- and middle-income countries throughout the world. The complex interactions between rodents and fleas with their respective environments challenge our understanding of human plague epidemiology. Historical long-term datasets of reported plague cases offer a unique opportunity to elucidate the effects of climate on plague outbreaks in detail. Here, we analyse monthly plague deaths and climate data from 25 provinces in British India from 1898 to 1949 to generate insights into the influence of temperature, rainfall and humidity on the occurrence, severity and timing of plague outbreaks. We find that moderate relative humidity levels of between 60% and 80% were strongly associated with outbreaks. Using wavelet analysis, we determine that the nationwide spread of plague was driven by changes in humidity, where, on average, a one-month delay in the onset of rising humidity translated into a one-month delay in the timing of plague outbreaks. This work can inform modern spatio-temporal predictive models for the disease and aid in the development of early-warning strategies for the deployment of prophylactic treatments and other control measures.

scholarly journals Studies on the Occurrence of Viruses in Planting Material of Grapevines in Southwestern Germany

Viruses ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 248
Author(s):  
Noemi Messmer ◽  
Patricia Bohnert ◽  
Stefan Schumacher ◽  
René Fuchs
Keyword(s):  
Preventive Measures ◽  
Control Measures ◽  
Grapevine Fanleaf Virus ◽  
Arabis Mosaic Virus ◽  
Planting Material ◽  
General Decline ◽  
Grapevine Pinot Gris Virus ◽  
Propagation Material

Viral diseases in viticulture lead to annual losses in the quantity and quality of grape production. Since no direct control measures are available in practice, preventive measures are taken to keep the vines healthy. These include, for example, the testing of propagation material for viruses such as Arabis mosaic virus (ArMV), Grapevine fanleaf virus (GFLV) or Grapevine leafroll-associated virus 1 (GLRaV-1) and 3 (GLRaV-3). As long-term investigations have shown, GLRaV-1 (2.1%) occurs most frequently in southwestern German wine-growing regions, whereas GLRaV-3 (<0.1%) is almost never found. However, tests conducted over 12 years indicate that there is no general decline in virus-infected planting material. Thus, it can be assumed that a spread of the viruses via corresponding vectors still takes place unhindered. Beyond the examinations regulated within the German Wine Growing Ordinance, one-time tests were carried out on Grapevine Pinot gris virus (GPGV). This analysis showed that GPGV was found in 17.2% of the samples.

scholarly journals COVID-19: first long-term care facility outbreak in the Netherlands following cross-border introduction from Germany, March 2020

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Mitch van Hensbergen ◽  
Casper D. J. den Heijer ◽  
Petra Wolffs ◽  
Volker Hackert ◽  
Henriëtte L. G. ter Waarbeek ◽  
...  
Keyword(s):  
The Netherlands ◽  
Long Term Care ◽  
Care Facility ◽  
Control Measures ◽  
Border Region ◽  
Term Care ◽  
Term Care Facility ◽  
Long Term Care Facility ◽  
Cross Border

Abstract Background The Dutch province of Limburg borders the German district of Heinsberg, which had a large cluster of COVID-19 cases linked to local carnival activities before any cases were reported in the Netherlands. However, Heinsberg was not included as an area reporting local or community transmission per the national case definition at the time. In early March, two residents from a long-term care facility (LTCF) in Sittard, a Dutch town located in close vicinity to the district of Heinsberg, tested positive for COVID-19. In this study we aimed to determine whether cross-border introduction of the virus took place by analysing the LTCF outbreak in Sittard, both epidemiologically and microbiologically. Methods Surveys and semi-structured oral interviews were conducted with all present LTCF residents by health care workers during regular points of care for information on new or unusual signs and symptoms of disease. Both throat and nasopharyngeal swabs were taken from residents suspect of COVID-19, based on regional criteria, for the detection of SARS-CoV-2 by Real-time Polymerase Chain Reaction. Additionally, whole genome sequencing was performed using a SARS-CoV-2 specific amplicon-based Nanopore sequencing approach. Moreover, twelve random residents were sampled for possible asymptomatic infections. Results Out of 99 residents, 46 got tested for COVID-19. Out of the 46 tested residents, nineteen (41%) tested positive for COVID-19, including 3 asymptomatic residents. CT-values for asymptomatic residents seemed higher compared to symptomatic residents. Eleven samples were sequenced, along with three random samples from COVID-19 patients hospitalized in the regional hospital at the time of the LTCF outbreak. All samples were linked to COVID-19 cases from the cross-border region of Heinsberg, Germany. Conclusions Sequencing combined with epidemiological data was able to virtually prove cross-border transmission at the start of the Dutch COVID-19 epidemic. Our results highlight the need for cross-border collaboration and adjustment of national policy to emerging region-specific needs along borders in order to establish coordinated implementation of infection control measures to limit the spread of COVID-19.

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