The Response of Pollution Load from Coastal River Waterfront on Red Tides in South Sea

Iqbal, Muhammad Mazhar; Shoaib, Muhammad; Agwanda, Paul Omondi

doi:10.2112/si91-047.1

Cited by 5 publications

(5 citation statements)

References 13 publications

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“…Human beings already facing significant global challenges of water scarcity, food security, and climate change (Iqbal et al, 2018a;Iqbal et al, 2019;Iqbal et al, 2018b;Yokomatsu et al, 2020), came under a swear attack of epidemic COVID-19 in December 2019, in Wuhan, a city of China (Burki, 2020;Chinazzi et al, 2020;World Health Organization, 2020a). Initially, the virus was acknowledged by the Chinese health care administration as of January 07, 2020 (Millán-Oñate et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

The effects of regional climatic condition on the spread of COVID-19 at global scale

Iqbal

Abid

Hussain

et al. 2020

Science of The Total Environment

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107

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Section: Introductionmentioning

confidence: 99%

The effects of regional climatic condition on the spread of COVID-19 at global scale

Iqbal

Abid

Hussain

et al. 2020

Science of The Total Environment

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107

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“…According to current estimations, the global population has reached about 7.8 billion and continues to increase by more than 81 million people per year in recent years [1]. The fast-growing population around the world increases pressure on daily anthropogenic activities such as industrial and processing activities [2,3] to fulfill the daily demands of more food, shelter and other services [4,5], which subsequently threatens the sustainability of the global ecosystem [6,7]. Nowadays, more than 55% of the global population is living in metropolitan areas [8].…”

Section: Introductionmentioning

confidence: 99%

Unprecedented Temporary Reduction in Global Air Pollution Associated with COVID-19 Forced Confinement: A Continental and City Scale Analysis

et al. 2020

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Shortly after the outbreak of the novel infectious disease (COVID-19) started at the end of 2019, it turned into a global pandemic, which caused the lockdown of many countries across the world. Various strict measures were adopted to reduce anthropogenic activities in order to prevent further spread and infection of the disease. In this study, we utilized continental scale remotely sensed data along with city scale in situ air quality observations for 2020 as well as data from the baseline period (2015–2019) to provide an early insight on air pollution changes in response to the COVID-19 pandemic lockdown, by combining both continental and city scales. For the continental scale analysis, data of NO2, SO2, and O3 were acquired from the ozone monitoring instrument (OMI) and data of aerosol optical depth (AOD) were collected from the moderate resolution imaging spectroradiometer (MODIS). For city scale analysis, data of NO2, CO, PM2.5, O3, and SO2 were derived from ground-based air quality observations. Results from satellite observations at the continental scale showed that concentrations of NO2, SO2, and AOD substantially dropped in 2020 during the lockdown period compared to their averages for the baseline period over all continents, with a maximum reduction of ~33% for NO2 in East Asia, ~41% for SO2 in East Asia, and ~37% for AOD in South Asia. In the case of O3, the maximum overall reduction was observed as ~11% in Europe, followed by ~10% in North America, while a slight increase was found in other study regions. These findings align with ground-based air quality observations, which showed that pollutants such as NO2, CO, PM2.5, and SO2 during the 2020 lockdown period decreased significantly except that O3 had varying patterns in different cities. Specifically, a maximum reduction of ~49% in NO2 was found in London, ~43% in CO in Wuhan, ~38% in PM2.5 in Chennai, and ~48% in SO2 in Beijing. In the case of urban O3, a maximum reduction of ~43% was found in Wuhan, but a significant increase of ~47% was observed in Chennai. It is obvious that restricted human activities during the lockdown have reduced the anthropogenic emissions and subsequently improved air quality, especially across the metropolitan cities.

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“…Because of technological advancements, surface water quality (SWQ) modelling tools have been greatly improved in the twenty-first century, which has led to a wide range of SWQ models being developed. Several water-quality models are currently in use for decision-making and policy development in various water ecosystems around the world [16,17]. In recent years, numerous water quality models (WQM), such as the WASP model, QUASAR, and WASP-2 models, and the MIKE and BASINS models, have been developed for simulating the importance of the water quality of water bodies like rivers and lakes containing contaminants.…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, numerous water quality models (WQM), such as the WASP model, QUASAR, and WASP-2 models, and the MIKE and BASINS models, have been developed for simulating the importance of the water quality of water bodies like rivers and lakes containing contaminants. These models were widely used in the United States, Europe, Australia, and the rest of the world [17][18][19][20][21]. However, WASP is the best open source model [22] for modelling the fate and transport of contaminants in rivers, lakes, and reservoirs, according to a recent analysis of the existing open source models.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Seasonal Variations in Surface Water Quality over Wet and Dry Regions

Iqbal

Hussain

Lee

et al. 2022

Water

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Water quality is highly affected by riverside vegetation in different regions. To comprehend this research, the study area was parted into wet and dry regions. The WASP8 was applied for the simulations of water quality profile over both Waterways selected from each region. It was found that the Ara Waterway, located in the wet regions, has a higher water quality variation in seasonal scale than that of the Yamuna Waterway, which is in the dry region. The interrelationship between river water quality variables and NDVI produce higher association for water quality variables with Pearson correlation coefficient values of about 0.66, 0.68 and −0.58, respectively, over the annual and seasonal scales in the energy limited regions. This approach will help in monitoring the seasonal variation and effect of the vegetation biomass on water quality for the sustainable water environment.

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The Response of Pollution Load from Coastal River Waterfront on Red Tides in South Sea

Cited by 5 publications

References 13 publications

The effects of regional climatic condition on the spread of COVID-19 at global scale

The effects of regional climatic condition on the spread of COVID-19 at global scale

Unprecedented Temporary Reduction in Global Air Pollution Associated with COVID-19 Forced Confinement: A Continental and City Scale Analysis

Analysis of Seasonal Variations in Surface Water Quality over Wet and Dry Regions

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