Determination and evaluation of spatio-temporal trends on the example of PM10 concentration in Poland (2000−2018)

Abstract Increasing amounts of rapidly growing data are the driving force behind proposing and automating new processing, enabling the extraction of useful information from data. One of such possibilities is determining trends to consider in terms of time and space. Thus far, the analysis of these aspects has been separate and lacked automated tools. Therefore, the authors proposed, implemented, and tested a tool for analyzing spatio-temporal linear trends. The tool was tested on PM10 concentration data in the years 2000–2018. The results, presented as cartographic visualization, were then evaluated, both in terms of time and space. The proposed approach facilitates analyzing spatio-temporal trends and assessing their accuracy; it can be developed using other types of analyzed trends or considering additional factors that influence the trend by using cokriging.

Download Full-text

A Spatio-Temporal Visualization Approach of PM10 Concentration Data in Metropolitan Lima

Atmosphere ◽

10.3390/atmos12050609 ◽

2021 ◽

Vol 12 (5) ◽

pp. 609

Author(s):

Alexandra Abigail Encalada-Malca ◽

Javier David Cochachi-Bustamante ◽

Paulo Canas Rodrigues ◽

Rodrigo Salas ◽

Javier Linkolk López-Gonzales

Keyword(s):

Air Quality ◽

Temporal Correlation ◽

Quality Standard ◽

Temporal Variations ◽

Particulate Material ◽

Pm10 Concentration ◽

Spatial Behavior ◽

Concentration Data ◽

Visualization System ◽

Spatio Temporal

Lima is considered one of the cities with the highest air pollution in Latin America. Institutions such as DIGESA, PROTRANSPORTE and SENAMHI are in charge of permanently monitoring air quality; therefore, the air quality visualization system must manage large amounts of data of different concentrations. In this study, a spatio-temporal visualization approach was developed for the exploration of data of the PM10 concentration in Metropolitan Lima, where the spatial behavior, at different time scales, of hourly concentrations of PM10 are analyzed using basic and specialized charts. The results show that the stations located to the east side of the metropolitan area had the highest concentrations, in contrast to the stations located in the center and north that reported better air quality. According to the temporal variation, the station with the highest average of biannual and annual PM10 was the HCH station. The highest PM10 concentrations were registered in 2018, during the summer, highlighting the month of March with daily averages that reached 435 μμg/m3. During the study period, the CRB was the station that recorded the lowest concentrations and the only one that met the Environmental Quality Standard for air quality. The proposed approach exposes a sequence of steps for the elaboration of charts with increasingly specific time periods according to their relevance, and a statistical analysis, such as the dynamic temporal correlation, that allows to obtain a detailed visualization of the spatio-temporal variations of PM10 concentrations. Furthermore, it was concluded that the meteorological variables do not indicate a causal relationship with respect to PM10 levels, but rather that the concentrations of particulate material are related to the urban characteristics of each district.

Download Full-text

Cropland Spatio-temporal Change and Driving Force in Three Gorges Reservoir Area

Geo-information Science ◽

10.3724/sp.j.1047.2011.00297 ◽

2011 ◽

Vol 13 (3) ◽

pp. 297-304 ◽

Cited By ~ 2

Author(s):

Lei ZHANG ◽

Bingfang WU ◽

Liang ZHU ◽

Peng WANG

Keyword(s):

Driving Force ◽

Three Gorges Reservoir ◽

Temporal Change ◽

Three Gorges Reservoir Area ◽

Three Gorges ◽

Reservoir Area ◽

Spatio Temporal

Download Full-text

Spatio-temporal trends in the flow and water quality: response of river Yamuna to urbanization

Environmental Monitoring and Assessment ◽

10.1007/s10661-021-08873-x ◽

2021 ◽

Vol 193 (3) ◽

Author(s):

Shweta Lokhande ◽

Vinod Tare

Keyword(s):

Water Quality ◽

Temporal Trends ◽

Spatio Temporal ◽

River Yamuna ◽

Quality Response

Download Full-text

Evolution of Gaseous and Particulate Pollutants in the Air: What Changed after Five Lockdown Weeks at a Southwest Atlantic European Region (Northwest of Spain) Due to the SARS-CoV-2 Pandemic?

Atmosphere ◽

10.3390/atmos12050562 ◽

2021 ◽

Vol 12 (5) ◽

pp. 562

Author(s):

Jorge Moreda-Piñeiro ◽

Joel Sánchez-Piñero ◽

María Fernández-Amado ◽

Paula Costa-Tomé ◽

Nuria Gallego-Fernández ◽

...

Keyword(s):

Air Quality ◽

Road Traffic ◽

Statistical Significance ◽

Temporal Trends ◽

Air Pollutant ◽

Concentration Data ◽

Southwest Atlantic ◽

Pollutant Concentrations ◽

Air Quality Monitoring Stations ◽

Almost All

Due to the exponential growth of the SARS-CoV-2 pandemic in Spain (2020), the Spanish Government adopted lockdown measures as mitigating strategies to reduce the spread of the pandemic from 14 March. In this paper, we report the results of the change in air quality at two Atlantic Coastal European cities (Northwest Spain) during five lockdown weeks. The temporal evolution of gaseous (nitrogen oxides, comprising NOx, NO, and NO2; sulfur dioxide, SO2; carbon monoxide, CO; and ozone, O3) and particulate matter (PM10; PM2.5; and equivalent black carbon, eBC) pollutants were recorded before (7 February to 13 March 2020) and during the first five lockdown weeks (14 March to 20 April 2020) at seven air quality monitoring stations (urban background, traffic, and industrial) in the cities of A Coruña and Vigo. The influences of the backward trajectories and meteorological parameters on air pollutant concentrations were considered during the studied period. The temporal trends indicate that the concentrations of almost all species steadily decreased during the lockdown period with statistical significance, with respect to the pre-lockdown period. In this context, great reductions were observed for pollutants related mainly to fossil fuel combustion, road traffic, and shipping emissions (−38 to −78% for NO, −22 to −69% for NO2, −26 to −75% for NOx, −3 to −77% for SO2, −21% for CO, −25 to −49% for PM10, −10 to −38% for PM2.5, and −29 to −51% for eBC). Conversely, O3 concentrations increased from +5 to +16%. Finally, pollutant concentration data for 14 March to 20 April of 2020 were compared with those of the previous two years. The results show that the overall air pollutants levels were higher during 2018–2019 than during the lockdown period.

Download Full-text

Real-time spatio-temporal event detection on geotagged social media

Journal Of Big Data ◽

10.1186/s40537-021-00482-2 ◽

2021 ◽

Vol 8 (1) ◽

Author(s):

Yasmeen George ◽

Shanika Karunasekera ◽

Aaron Harwood ◽

Kwan Hui Lim

Keyword(s):

New York ◽

Social Media ◽

Event Detection ◽

Detection System ◽

Time And Space ◽

Social Media Data ◽

Event Time ◽

Spatio Temporal ◽

Geographical Space ◽

Media Data

AbstractA key challenge in mining social media data streams is to identify events which are actively discussed by a group of people in a specific local or global area. Such events are useful for early warning for accident, protest, election or breaking news. However, neither the list of events nor the resolution of both event time and space is fixed or known beforehand. In this work, we propose an online spatio-temporal event detection system using social media that is able to detect events at different time and space resolutions. First, to address the challenge related to the unknown spatial resolution of events, a quad-tree method is exploited in order to split the geographical space into multiscale regions based on the density of social media data. Then, a statistical unsupervised approach is performed that involves Poisson distribution and a smoothing method for highlighting regions with unexpected density of social posts. Further, event duration is precisely estimated by merging events happening in the same region at consecutive time intervals. A post processing stage is introduced to filter out events that are spam, fake or wrong. Finally, we incorporate simple semantics by using social media entities to assess the integrity, and accuracy of detected events. The proposed method is evaluated using different social media datasets: Twitter and Flickr for different cities: Melbourne, London, Paris and New York. To verify the effectiveness of the proposed method, we compare our results with two baseline algorithms based on fixed split of geographical space and clustering method. For performance evaluation, we manually compute recall and precision. We also propose a new quality measure named strength index, which automatically measures how accurate the reported event is.

Download Full-text

Spatio-temporal trends and climatology of atmospheric chlorinated hydrocarbons over Pakistan

Arabian Journal of Geosciences ◽

10.1007/s12517-021-07809-6 ◽

2021 ◽

Vol 14 (15) ◽

Author(s):

Ahmad Hasnain ◽

Yong Zha ◽

Muhammad Zaffar Hashmi ◽

Fatima Rahim ◽

Yufeng He ◽

...

Keyword(s):

Temporal Trends ◽

Chlorinated Hydrocarbons ◽

Spatio Temporal

Download Full-text

Spatio-temporal impacts of aerial adulticide applications on populations of West Nile virus vector mosquitoes

Parasites & Vectors ◽

10.1186/s13071-021-04616-6 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Karen M. Holcomb ◽

Robert C. Reiner ◽

Christopher M. Barker

Keyword(s):

West Nile Virus ◽

Temporal Trends ◽

Larval Habitat ◽

Post Treatment ◽

Additive Models ◽

Dispersal Ability ◽

Stochastic Variation ◽

West Nile ◽

Spatial Coverage ◽

Spatio Temporal

Abstract Background Aerial applications of insecticides that target adult mosquitoes are widely used to reduce transmission of West Nile virus to humans during periods of epidemic risk. However, estimates of the reduction in abundance following these treatments typically focus on single events, rely on pre-defined, untreated control sites and can vary widely due to stochastic variation in population dynamics and trapping success unrelated to the treatment. Methods To overcome these limitations, we developed generalized additive models fitted to mosquito surveillance data collected from CO2-baited traps in Sacramento and Yolo counties, California from 2006 to 2017. The models accounted for the expected spatial and temporal trends in the abundance of adult female Culex (Cx.) tarsalis and Cx. pipiens in the absence of aerial spraying. Estimates for the magnitude of deviation from baseline abundance following aerial spray events were obtained from the models. Results At 1-week post-treatment with full spatial coverage of the trapping area by pyrethroid or pyrethrin products, Cx. pipiens abundance was reduced by a mean of 52.4% (95% confidence intrval [CI] − 65.6, − 36.5%) while the use of at least one organophosphate pesticide resulted in a mean reduction of 76.2% (95% CI − 82.8, − 67.9%). For Cx. tarsalis, at 1-week post-treatment with full coverage there was a reduction in abundance of 30.7% (95% CI − 54.5, 2.5%). Pesticide class was not a significant factor contributing to the reduction. In comparison, repetition of spraying over three to four consecutive weeks resulted in similar estimates for Cx. pipiens and estimates of somewhat smaller magnitude for Cx. tarsalis. Conclusions Aerial adulticides are effective for achieving a rapid short-term reduction of the abundance of the primary West Nile virus vectors, Cx. tarsalis and Cx. pipiens. A larger magnitude of reduction was estimated in Cx. pipiens, possibly due to the species’ focal distribution. Effects of aerial sprays on Cx. tarsalis populations are likely modulated by the species’ large dispersal ability, population sizes and vast productive larval habitat present in the study area. Our modeling approach provides a new way to estimate effects of public health pesticides on vector populations using routinely collected observational data and accounting for spatio-temporal trends and contextual factors like weather and habitat. This approach does not require pre-selected control sites and expands upon past studies that have focused on the effects of individual aerial treatment events.

Download Full-text

Recessive Transition Mechanism of Arable Land Use Based on the Perspective of Coupling Coordination of Input–Output: A Case Study of 31 Provinces in China

Land ◽

10.3390/land10010041 ◽

2021 ◽

Vol 10 (1) ◽

pp. 41

Author(s):

Yi Lou ◽

Guanyi Yin ◽

Yue Xin ◽

Shuai Xie ◽

Guanghao Li ◽

...

Keyword(s):

Land Use ◽

Evaluation Model ◽

Arable Land ◽

Temporal Trends ◽

Mainland China ◽

Input Output ◽

Transition Mechanism ◽

Input And Output ◽

Spatio Temporal ◽

Arable Land Use

In the rapid process of urbanization in China, arable land resources are faced with dual challenges in terms of quantity and quality. Starting with the change in the coupling coordination relationship between the input and output on arable land, this study applies an evaluation model of the degree of coupling coordination between the input and output (D_CCIO) on arable land and deeply analyzes the recessive transition mechanism and internal differences in arable land use modes in 31 provinces on mainland China. The results show that the total amount and the amount per unit area of the input and output on arable land in China have presented different spatio-temporal trends, along with the mismatched movement of the spatial barycenter. Although the D_CCIO on arable land increases slowly as a whole, 31 provinces show different recessive transition mechanisms of arable land use, which is hidden in the internal changes in the input–output structure. The results of this study highlight the different recessive transition patterns of arable land use in different provinces of China, which points to the outlook for higher technical input, optimized planting structure, and the coordination of human-land relationships.

Download Full-text