Spatio-temporal distribution of sea surface chlorophyll-a in coral reefs of the South China Sea over the past decade based on Landsat-8 Operational Land Images

The concentration of chlorophyll-a (Chl-a) in seawater reflects phytoplankton growth and water eutrophication, which are usually assessed for evaluation of primary productivity and carbon source/sink of coral reefs. However, the precise delineation of Chl-a concentration in coral reefs remains a challenge when ocean satellites with low spatial resolution are utilized. In this study, a remote sensing inversion model for Chl-a was developed in fringing reefs (R2 = 0.76, RMSE =0.41 μg/L, MRE = 14 %) and atolls (R2 = 0.79, RMSE =0.02 μg/L, MRE = 8 %), utilizing reflectance data from the sensitive band of the Landsat-8 Operational Land Imagers (OLI) with a spatial resolution of 30 m. The aforementioned model was utilized to invert high-resolution distribution maps of Chl-a concentration in six major coral reef regions of the South China Sea from 2013 to 2022 and subsequently used to analyze the variations in Chl-a concentration and its influencing factors. The results indicate a Chl-a concentration gradient among coral reefs Daya Bay, Weizhou Island, Luhuitou, Xuwen, Huangyan Island, and Xisha Island in that order. The Chl-a concentration in coral reefs exhibited an overall increasing trend, with significant seasonal fluctuations, characterized by higher concentrations during winter and spring and lower concentrations during summer and autumn. The concentration of Chl-a in coral reefs was positively correlated with the average wind speed.

Prediction of heavy metal lead contamination accident in Three Gorges Reservoir Area

Water contamination incidents have become a significant ecological and environmental threat, particularly concerning the security of drinking water source areas (DWSAs). This research aimed to address this issue by integrating Geographic Information System (GIS) into bidimensional hydrodynamic water quality mathematical model developed using C +  + and FORTRAN programming languages. The focus was on the Heshangshan drinking water source area (HDWSA), and the TECPLOT360 software was utilized for visualizing pollutant migration and dispersion processes. The study specifically considered a hypothetical lead (Pb) contamination accident, which is situated in the Three Gorges Reservoir Area (TGRA). The spatio-temporal variations in Pb concentration throughout the entire DWSA were analyzed, along with a comparison of Pb concentration changes during different water seasons. The results indicate that, during the accident, the Pb concentration at the water intake in the drought season, decline season, flood season, and impounding season reached the standard limits at 76, 58, 44, and 48 min, respectively. Moreover, the entire DWSA achieved standard levels of Pb concentration at 124, 89, 71, and 74 min during the respective seasons. The study also observed an expansion and subsequent contraction of the Pb contamination area in the DWSA, with the transfer rate of Pb concentration ranked as flood season > impounding season > decline season > drought season.

Vulnerability assessment of urban agglomerations to the risk of heat waves in China since the 21st century

In the context of global warming, frequent heat wave disasters have seriously threatened the safety of human life and property. The urban agglomeration, as the main region with a high concentration of population and economy, is susceptible to heat weaves due to the existing urban heat island effect. In this study, we investigated the temporal and spatial characteristics of heat waves (heat index, HI) in China from 2000 to 2020 and assess the vulnerability of 19 urban agglomerations to heat waves from the perspective of exposure, sensitivity and adaptability. The results show that: (1) In the past 20 years, the frequency and intensity of HI (greater than 26.67 °C) both showed an upward trend. (2) Shandong Peninsula, Central Henan, Yangtze River Delta, Middle Reaches of Yangtze River, and Mid-southern Liaoning urban agglomerations always maintain a high vulnerability. (3) From 2000 to 2020, the vulnerability of Beijing-Tianjin-Hebei, Yangtze River Delta, Chengdu-Chongqing, Middle reaches of Yangtze River, Guangdong-Fujian-Zhejiang, Harbin-Changchun and Mid-southern Liaoning urban agglomerations were always dominated by exposure. The vulnerability of Shandong Peninsula, Beibu Gulf and Central Henan urban agglomeration has always been dominated by sensitivity. The vulnerability of North Tianshan Mountain, Lanzhou-Xining, Guanzhong and Hu-Bao-E-Yu urban agglomeration has always been dominated by inadequate adaptability. (4) Recently, the factors that contributed most to exposure, sensitivity and adaptability were population density, the proportion of outdoor workers and water supply, with contribution rates of 38%, 55% and 26%, respectively. This study can provide a scientific basis for the rational allocation of resources among urban agglomerations, effectively formulating policies and guiding population migration from high temperature disasters.

Gaseous elemental mercury emissions from informal E-Waste recycling facilities in Pakistan

Detrimental effects of mercury (Hg) on ecosystems and human health have been well-documented. Whereas emissions of gaseous elemental mercury (GEM) from e-waste recycling have been reported in developed countries, much less is known about the situation in the Global South. Using a total of 132 passive air samplers, seasonally resolved concentrations of GEM in air were measured continuously at 32 informal e-waste recycling facilities and background location in Pakistan for a period of one year between September 2020 and December 2021. Annual average GEM concentrations at the studied locations ranged from 1.8 to 92 ng m-3. Among the studied cities, higher concentrations were measured in Karachi (mean ± s.d: 17 ± 22, range: 4.2-92 ng m-3), Lahore (16 ± 4.2, 8.2-22 ng m-3) and Peshawar (15 ± 17, 4.9-80 ng m-3), while lower levels were measured in Hyderabad (6.9 ± 6.2, 3.1-25 ng m-3), consistent with a higher rate of informal recycling activities in metropolitan areas. Seasonally, higher GEM levels occurred during autumn (15 ± 16: 3.3-92 ng m-3) and summer (13 ± 8.7: 1.8-80 ng m-3) than in winter (12 ± 8.4: 2.5-49 ng m-3) and spring (9.2 ± 7.3: 1.8-80 ng m-3), possibly reflecting enhanced volatilization at higher temperatures and/or varying magnitude of recycling operations in different seasons. Policies and strict regulations related to e-waste management should be developed and implemented urgently in the country.

Air pollution in heavy industrial cities along the northern slope of the Tianshan Mountains, Xinjiang: characteristics, meteorological influence, and sources

The spatiotemporal characteristics, relationship with meteorological factors, and source distribution of air pollutants (January 2017-December 2021) were analyzed to better understand the air pollutants on the northern slope of the Tianshan Mountains (NSTM) in Xinjiang, a heavily polluted urban agglomeration of heavy industries. The results showed that the annual mean concentrations of SO₂, NO₂, CO, O₃, PM_2.5, and PM₁₀ were 8.61-13.76 μg m^-3, 26.53-36.06 μg m^-3, 0.79-1.31 mg m^-3, 82.24-87.62 μg m^-3, 37.98-51.10 μg m^-3, and 84.15-97.47 μg m^-3. The concentrations of air pollutants (except O₃) showed a decreasing trend. The highest concentrations were in winter, and in Wujiaqu, Shihezi, Changji, Urumqi, and Turpan, the concentrations of particulate matter exceeded the NAAQS Grade II during winter. The west wind and the spread of local pollutants both substantially impacted the high concentrations. According to the analysis of the backward trajectory in winter, the air masses were mainly from eastern Kazakhstan and local emission sources, and PM₁₀ in the airflow had a more significant impact on Turpan; the rest of the cities were more affected by PM_2.5. Potential sources included Urumqi-Changj-Shihezi, Turpan, the northern Bayingol Mongolian Autonomous Prefecture, and eastern Kazakhstan. Consequently, the emphasis on improving air quality should be on reducing local emissions, strengthening regional cooperation, and researching transboundary transport of air pollutants.

Spatio-temporal variations and drought of spring maize in Northeast China between 2002 and 2020

A lot of spring maize is grown in Northeast China (Liaoning, Jilin, and Heilongjiang), an area that is highly susceptible to drought. Here, remote sensing indexes from 2002 to 2020 were studied using the 8-day surface reflectance and land surface temperature of Moderate-resolution Imaging Spectroradiometer data. Spring maize distribution was extracted using a decision tree classification, and the results were compared to the known distribution based on field investigation data and published statistics. The results showed that mixed pixels of spring maize and soybeans had limited influence on the study of spatio-temporal variations of spring maize, and the error was acceptable. The overall accuracy of verifying the spring maize distribution from 2018 to 2020 was above 85%. The stable, fluctuating, and low-frequency planting areas of spring maize accounted for 11.86%, 17.41%, and 34.86% of the study area, respectively. In 2015, the government directed a reduction of the planting area of spring maize in the "Liandaowan" region of Northeast China. The planting area of spring maize was characterized by a continuous increase before this change (2002-2014), exhibited changes and reductions in response to the change (2015-2017), and exhibited optimization and recovery after this change (2018-2020). Compared with the fluctuating and low-frequency planting areas, moderate and severe droughts were higher in stable planting areas. From 2002 to 2020, the most severe droughts occurred in the expanded planting areas. This rapid and large-scale monitoring of spatio-temporal variations and drought of spring maize provides a foundation for improving grain yield. This method could be easily applied to the study of other regions and combined with high-resolution and hyperspectral satellite data to improve monitoring accuracy.

The characteristics of polycyclic aromatic hydrocarbons and heavy metals in water and sediment of dajiuhu subalpine wetland, shennongjia, central China, 2018-2020: Insights for sources, sediment-water exchange, and ecological risk

Polycyclic aromatic hydrocarbons (PAHs) and heavy metals (HMs) are persistent environmental issues. Secondary emissions are produced as a result of climate change and human activity. To observe spatio-temporal variations of PAHs and HMs and to discuss the sources as well as the source or sink of PAHs for sediment and peat, twelve surface sediment and surface water sites were chosen along the direction of the flow to down hole in the Dajiuhu area, simultaneously, surface peat and water samples were collected in peatland. Samples were continuously taken for three years (Sep. 2018, Sep. 2019, and Sep. 2020, respectively). The results showed that PAHs and HMs are common in sediment and peat. PAHs concentration is generally higher in peat and water, while HMs concentration is relatively higher in water and relatively low in sediment and peat, and the ecological risk of sediment was low. HMs in sediment are mainly affected by rock weathering, while PAHs are mainly affected by atmospheric deposition, biomass and coal combustion and vehicle emission. HMs and PAHs can be used as an indicator of rock weathering and human activity in Dajiuhu area, respectively. A water-sediment fugacity analysis revealed that peat is a sink for PAHs, confirming that it has a high capacity for adsorbing organic contaminants, and that sediments are secondary sources of PAHs that can release them into water. Attention should be paid to the increased fugacity fraction (ff) value in peatland, indicating that peat might be converted from a sink to a source of PAHs.

Analysis of spatio-temporal variations of river water quality and construction of a novel cost-effective assessment model: a case study in Hong Kong

Assessment of river water quality has been attracting a great deal of attention because of its important implications for the living environment of human beings and aquatic organisms. River water quality is commonly assessed using dozens of different water quality parameters. However, different parameters may contain redundant information, which could lead to the waste of monitoring efforts. Thus, this study constructed a novel cost-effective assessment model of river water quality using the 1-year monitoring data collected from 23 sampling stations in the water control zone of Tolo Harbour and Channel in Hong Kong. First, the spatio-temporal variations of water quality parameters and the overall status of river water quality were analyzed based on all 19 parameters using Kruskal-Wallis test, hierarchical cluster analysis, and the water quality index (WQI). The results indicated that most water quality parameters and overall water quality status varied significantly over space, but did not exhibit obvious seasonal differences; and 99.27% of water samples were identified to be in good or excellent status of overall WQI. Then, using principal component analysis (PCA)/factor analysis (FA) and Pearson's correlation analysis, eight parameters, including 5-day biochemical oxygen demand (BOD₅), chemical oxygen demand (COD), ammonia-nitrogen (NH₃-N), nitrate-nitrogen (NO₃-N), chlorophyll-a (Chl-a), fluoride (F^-), total suspended solids (TSS), and arsenic (As), were verified to be responsible for the greatest contributions to water quality, the assessment of overall water quality status. These eight crucial parameters were further employed to establish six cost-effective water quality assessment models. Using the overall WQI as the benchmark, the results of linear regression analysis demonstrated that the cost-effective model constructed based on BOD₅, COD, NH₃-N, NO₃-N, F^-, TSS, and As were the optimal water quality assessment model, which can achieve the most reliable results with reduced parameters.

Spatio-temporal variations of the major meteorological disasters and its response to climate change in Henan Province during the past two millennia

In China, historical documents have recorded large quantities of information related to natural disasters, and these disasters have had long-lasting effects on economic and social activities. Understanding the occurrence of the natural disasters and their spatio-temporal variation characters is crucial for sustainable of our society. Therefore, based on the collection and collation of historical documents, and adopting mathematical statistics, Kriging interpolation, correlation analysis and other methods, we systematically explored the meteorological disasters in Henan Province during the past two millennia in analyzing their spatio-temporal distribution characters and driving forces. The results demonstrate that there were five major types of meteorological disasters in Henan Province, including drought, flood, hails, low temperature and frost and insect pests, which presented obvious spatio-temporal variations and have occurred frequently during the past two millennia. According to the historical documents, the major meteorological disasters occurred 1,929 times in Henan from 221 BCE to 2000 CE. On the whole, the disaster frequency show that the occurrence cycle of the meteorological disasters has obvious changes, which mainly occurred in the middle and late stages during the past two millennia, especially after 1300 CE. Furthermore, we also find that the variation of meteorological disaster events is consistent with the variation of temperature in eastern China and the frequency of meteorological disaster increases in the cold period, but decreases in the warm period. In addition, there are obvious differences in the spatial distribution of the major meteorological disaster, which were mainly distributed in the northwest and southern part region of the Henan Province before 1911 CE. While after 1911 CE, the northern and southeastern parts were the meteorological disaster-prone areas in this region during this period. Spatial correlation analysis of each meteorological disaster before and after 1911 CE points out the droughts disaster frequency-occurring district has transferred in different periods, while the hail and low temperature and frost disasters just have a smaller transferred during these two periods. Conversely, the frequency-occurring districts of floods and insect pest disasters have no obviously transferred in different periods. These results can provide an important scientific basis for governmental decision makers and local people to prevent and mitigate meteorological disaster in the future.

Sediment migrations drive the dynamic of macrobenthic ecosystems in subtidal sandy bedforms

A traditional taxonomic approach coupled to a biological traits analysis was conducted in order to provide a new insight into macrobenthic communities associated with subtidal sandy environments. Results suggest that the macro-scale distribution of benthic communities is mainly driven by the migration rate of bedforms (sandbank, barchan dune and transversal dune) which changes the sediment grain size and reduces macrobenthic diversity. A classic scheme of species/traits succession was also observed from less to more physically disturbed areas. Finally, the high frequency of migration events homogenized macrobenthic communities between the troughs to the crest of bedforms. As bedforms areas are targeted for the commissioning of offshore windfarms the information provided by the present paper will be particularly useful to implement the environmental impact assessment required for such activities at sea.

Climate and landscape controls on spatio-temporal patterns of stream water stable isotopes in a large glacierized mountain basin on the Tibetan Plateau

The spatio-temporal variations of stream water stable isotopes are often assumed to follow atmospheric moisture transport over the Tibetan Plateau (TP). However, the isotopic composition of streamflow can be modified by the extensive variation in landscape properties in large glacierized mountain basins. In this study, the isotopic composition of stream water and its dominant controls in terms of spatial variation and potential water sources of rainfall, snow and glacier melt, and groundwater are analyzed based on synoptic water sampling from September 2018 to August 2019 over the Lhasa River basin (LRB) in the Southern TP. Results showed that: (1) δ¹⁸O variation in stream water is linearly proportional to longitude and latitude in the north. This spatial pattern is primarily controlled by cold mountainous environments, where stream water δ¹⁸O is more depleted and d-excess is higher towards the northwest and higher elevation in glacier-fed streams. Glacial melt could contribute considerably to streamflow generation, especially in the late monsoon season. (2) In the south, stream water δ¹⁸O does not simply follow depleted δ¹⁸O in precipitation along the strengthened Indian monsoon moisture gradient, but is enriched by strengthened local moisture recycling and increased groundwater contributions. The rainfall recharge is highly regulated and mixes with storage before it reaches the mainstem of the river. (3) The seasonal variations of stream water δ¹⁸O and d-excess are distinct, resulting from different contribution sources and catchment controls. In the pre-monsoon season, the strongest local moisture recycling obscures any simple stream water isotope lapse with elevation. These identified source areas and seasonal variations in the isotopic composition in stream water of LRB help us understand diverse water sources and flow paths to streams in this complex environment, which is a prerequisite for projecting potential future change.

Spatio-temporal variations in COVID-19 in relation to the global climate distribution and fluctuations

This study investigated the spatio-temporal variations in the occurrence of COVID-19 (confirmed cases and deaths) in relation to climate fluctuations in 61 countries, scattered around the world, from December 31, 2019 to May 28, 2020. Logarithm transformation of the count variable (COVID-19 cases) was used in a multiple linear regression model to predict the potential effects of weather variables on the prevalence of the disease. The study revealed strong associations (-0.510 ≤ r ≤ -0.967; 0.519 ≤ r ≤ 0.999) between climatic variables and confirmed cases of COVID-19 in majority (68.85%) of the selected countries. It showed evidences of 1 to 7-day delays in the response of the infection to changes in weather pattern. Model simulations suggested that a unit fall in temperature and humidity could increase (0.04-18.70%) the infection in 19.67% and 16.39% of the countries, respectively, while a general reduction (-0.05 to 9.40%) in infection cases was projected in 14.75% countries with a unit drop in precipitation. In conclusion, the study suggests that effective public health interventions are crucial to containing the projected upsurge in COVID-19 cases during both cold and warm seasons in the southern and northern hemispheres.

Spatio-temporal characteristics of air pollutants over Xinjiang, northwestern China

To understand the characteristics of particulate matter (PM) and other air pollutants in Xinjiang, a region with one of the largest sand-shifting deserts in the world and significant natural dust emissions, the concentrations of six air pollutants monitored in 16 cities were analyzed for the period January 2013-June 2019. The annual mean PM_2.5, PM₁₀, SO₂, NO₂, CO, and O₃ concentrations ranged from 51.44 to 59.54 μg m^-3, 128.43-155.28 μg m^-3, 10.99-17.99 μg m^-3, 26.27-31.71 μg m^-3, 1.04-1.32 mg m^-3, and 55.27-65.26 μg m^-3, respectively. The highest PM concentrations were recorded in cities surrounding the Taklimakan Desert during the spring season and caused by higher amounts of wind-blown dust from the desert. Coarse PM (PM_10-2.5) was predominant, particularly during the spring and summer seasons. The highest PM_2.5/PM₁₀ ratio was recorded in most cities during the winter months, indicating the influence of anthropogenic emissions in winters. The annual mean PM_2.5 (PM₁₀) concentrations in the study area exceeded the annual mean guidelines recommended by the World Health Organization (WHO) by a factor of ca. ∼5-6 (∼7-8). Very high ambient PM concentrations were recorded during March 19-22, 2019, that gradually influenced the air quality across four different cities, with daily mean PM_2.5 (PM₁₀) concentrations ∼8-54 (∼26-115) times higher than the WHO guidelines for daily mean concentrations, and the daily mean coarse PM concentration reaching 4.4 mg m^-3. Such high PM_2.5 and PM₁₀ concentrations pose a significant risk to public health. These findings call for the formulation of various policies and action plans, including controlling the land degradation and desertification and reducing the concentrations of PM and other air pollutants in the region.

Spatial and temporal variations of coastal microplastic pollution in Hong Kong

Further to our 2015-16 investigation, this study revealed the repeated presence of microplastics (MPs) in the coastal environment (Deep Bay, Tolo Harbour, Tsing Yi and Victoria Harbour) of Hong Kong from July 2016 to March 2017. The highest level of MPs in coastal surface water (17,182 particles/100 m³) was detected in Tsing Yi. Microplastic abundance in sediments of different sites (59 to 225 plastic particles/kg), however, did not vary significantly. MPs in the size of ≤1 mm were predominated in surface waters (53.3% to 98.6%) and sediments (79.1% to 96.8%). MPs in the shape of pellets and fragments were prevalent in surface waters and sediments respectively. Seasonal pattern of microplastic pollution was consistently observed in Victoria Harbour and Tsing Yi, where the number of MPs was always higher in dry season than in wet season for two consecutive years.

Comparison of land surface and air temperatures for quantifying summer and winter urban heat island in a snow climate city

The urban heat island (UHI) effect is an increasingly consequential problem that confronts cities. The accurate characterization and quantification of UHI are crucial for sustainable urban development. Few UHI studies, however, compare data source, spatio-temporal variations, and indicators for the same city in parallel. This study uses Changchun, a snow climate city in China, as an example and compares five different indicators of the UHI based on land surface temperature (LST) derived from Landsat 8 TIRS and hourly air temperature (AT) collected from 41 meteorological weather stations to conduct a more comprehensive comparative study of the UHI. The results show the following. (1) The relationships between LST and AT are all statistically significant, and the surface urban heat island (SUHI) intensity characterized by the LST is considerably stronger than that of AT both in summer and winter. (2) The SUHI intensity is significantly stronger in summer (6.83 °C) than in winter (1.55 °C) based on the morning LST, whereas the UHI intensity (0.27 °C in summer and 0.40 °C in winter) that is simultaneously quantified by the AT has an opposite result. The mean whole-day and daytime UHI intensity difference, which is quantified hourly by the AT between summer and winter, is not significant. The difference between nighttime and daytime UHI intensities is evident in both summer (1.26 °C) and winter (0.76 °C). Additionally, the high temperatures for both LST and AT have a more concentrated distribution in winter than in summer. (3) The values of UHI/SUHI intensity considerably vary based on different indicators. The different choices among land covers to represent "urban" and "rural" areas would significantly affect the values of UHI/SUHI intensity. The selection of appropriate indicators and data sources to quantify the UHI remains a problem that has to be resolved in future studies.

Spatio-temporal variations of licensed doctor distribution in China: measuring and mapping disparities

BACKGROUND

The licensed doctor misdistribution is one of the major challenges faced by China. However, this subject remains underexplored as spatial distribution characteristics (such as spatial clustering patterns) have not been fully mapped out by existing studies. To fill the void, this study aims to explore the spatio-temporal dynamics and spatial clustering patterns of different subtypes of licensed doctors (i.e., clinicians, traditional Chinese medicine doctors, dentists, public health doctors, general practitioners) in China.

METHODS

Data on the licensed doctor quantity and population during 2012-2016 was obtained from the National Health (and Family Planning) Yearbook. Functional boxplots were used to visualize and compare the temporal trends of densities of different subtypes of licensed doctors. This study adopted two complementary spatial statistics (space-time scan statistics and Moran's I statistics) to explore the spatio-temporal dynamics and spatial clustering patterns of licensed doctor distribution in China. The former was used to explore the spatial variations in the temporal trends of licensed doctor density during 2012-2016, and the latter was adopted to explore the spatial changing patterns of licensed doctor distribution during the research period.

RESULTS

The results show that the densities of almost all subtypes of licensed doctors displayed upward trends during 2012-2016, though some provincial units were left behind. Besides, spatial distribution characteristics varied across different subtypes of licensed doctors, with the low-low cluster area of general practitioners being the largest.

CONCLUSIONS

The misdistribution of licensed doctors is a global problem and China is no exception. In order to achieve a balanced distribution of licensed doctors, the government is suggested to introduce a series of measures, such as deliberative policy design and effective human resource management initiatives to educate, recruit, and retain licensed doctors and prevent a brain drain of licensed doctors from disadvantaged units.

Quantitative identification of nitrate sources in a coastal peri-urban watershed using hydrogeochemical indicators and dual isotopes together with the statistical approaches

Surplus nutrient load and complex migration and transformation processes are the challenges for water quality management in the peri-urban coastal watershed, leading to increasing concerns worldwide. We investigated the spatio-temporal variation of hydrogeochemical parameters in surface water of Jimei Lake watershed, and distinguished the sources and transformation of nitrate-N (NO₃^--N) using dual isotopes of nitrate (δ¹⁵N and δ¹⁸O in NO₃^-) with hydrogeochemical indicators. Principal component analysis (PCA) on hydrogeochemical parameters demonstrated that surface water was seriously polluted by nutrients, especially in the southeast of the downstream. There were signs of seawater intrusion and increased wastewater discharge in the mid-lower reaches with high ammonium concentrations. Nitrification occurred throughout the monitoring period with lower δ¹⁵N and δ¹⁸O values and NO₃^- derived from mixed pollution sources. Results of Bayesian model showed that dominant NO₃^- input originated from manure and sewage (M&S, 71% and 76% in the wet and dry season, respectively) and atmospheric deposition (22% and 16%, respectively). This result implied that the controls and treatment of M&S discharges are essential to alleviate of NO₃^- pollution. The proposed method is helpful to understand the origins of NO₃^- and may be suitable to develop measures for the reducing of nitrogen loadings in the peri-urban watershed.

Ecological risk assessment of metals in sediments and selective plants of Uchalli Wetland Complex (UWC)-a Ramsar site

Wetlands act as kidneys of land and facilitate remediation of metals and other harmful pollutants through uptake by aquatic macrophytes. The aim of the present study was to investigate metal concentrations in sediments and plants, sources of metal origin, and contamination level in Uchalli Wetland Complex. Sediment samples were collected from 15 randomly selected sites. Metal concentrations (Cd, Pb, Ni, Cu, Zn, Cr, As, Mn) in sediments and macrophytes were determined during summer and winter seasons using the inductively coupled plasma technique. Metal concentrations in sediments during summer and winter seasons were in the order as follows: As > Mn > Zn > Cr > Ni > Cd > Pb > Cu and As > Mn > Zn > Cr > Ni > Pb > Cd >Cu respectively. All analyzed metals were within European Union (EU) limits. In macrophytes, these metals were in the order as follows: Mn > As > Ni > Zn > Cr > Cd > Cu > Pb and As > Mn > Zn > Ni > Cr > Cd > Pb during summer and winter seasons respectively. Contamination degree (C_d) (1.023-5.309) for these lakes showed low contamination during both seasons; mC_d values (below 1.5) showed very little contamination degree, while the pollution load index (0.012 to 0.0386) indicated no metal pollution in these lakes. PCA applied on sediment showed that Pb, Zn, Cr, Cu, and Cd had anthropogenic sources of origin. As and Mn were due to natural processes while Ni could be resultant of both anthropogenic and natural sources. PCA on macrophytes showed that Ni, Pb, Cr, Zn, Cu; Cd, As; Mn had anthropogenic, natural, and anthropogenic + natural sources of origin. The study concluded that metal concentrations in sediments were not up to dangerous level.

The relationships between PM2.5 and aerosol optical depth (AOD) in mainland China: About and behind the spatio-temporal variations

Satellite aerosol products have been widely used to retrieve ground PM_2.5 concentration because of their wide coverage and continuous spatial distribution. While more and more studies have focused on the retrieval algorithms, the foundation for the retrieval-relationship between PM_2.5 and satellite aerosol optical depth (AOD) has not been fully investigated. In this study, the relationships between PM_2.5 and AOD were investigated in 368 cities in mainland China from February 2013 to December 2017, at different temporal and regional scales. Pearson correlation coefficients and the PM_2.5/AOD ratio were used as indicators. Firstly, we established the relationship between PM_2.5 and AOD in terms of the spatio-temporal variations, and discuss the impact of some potential factors for a better understanding of the spatio-temporal variations. Spatially, we found that the correlation is higher in the Beijing-Tianjin-Hebei and Chengyu regions and weaker in coastal areas. The PM_2.5/AOD ratio shows an obvious north-south difference, with the ratio in North China higher than South China. Temporally, the correlation coefficient tends to be higher in May and September, with the PM_2.5/AOD ratio higher in winter and lower in summer. As for interannual variations, we detected a decreasing tendency for the PM_2.5-AOD correlation and PM_2.5/AOD ratio for recent years. Then, to determine the impact of the weakening of the PM_2.5-AOD relationship on PM_2.5 remote sensing retrieval performance, a geographically weighted regression (GWR) retrieval experiment was conducted. The results showed that the performance of retrievals is also decreasing while PM_2.5-AOD relationship getting weaker. Our study investigated the PM_2.5-AOD relationship over a large extent at the city scale, and investigated the temporal variations in terms of interannual variations. The results will be useful for the satellite retrieval of PM_2.5 concentration and will help us to further understand the PM_2.5 pollution situation in mainland China.

Spatio-temporal variations in physico-chemical parameters and potentially harmful elements (PHEs) of Uchalli Wetlands Complex (Ramsar site), Pakistan

Uchalli Wetlands Complex (UWC) is located in District Khushab, Pakistan, which comprised of three lakes named Khabeki, Uchalli, and Jahlar. The UWC Pakistan is one of the Ramsar sites of international importance. However, the information regarding water quality parameters and concentration of potentially harmful elements (PHEs) is relatively short. Present study focused on spatio-temporal variations in the physico-chemical parameters and PHE (Cd, Pb, Ni, Cu, Zn, Cr, As, Mn) concentrations in water and fish samples using inductively coupled plasma. Sampling was done in summer (August 2016) and winter (January 2017) seasons. The overall concentrations of PHEs in water were in the following order: Mn > Zn > Cu > Cr > Ni > Cd > Pb > As for Khabeki; As >Ni > Cr > Mn > Zn > Cu > Cd > Pb for Uchalli; and Mn > Zn > Ni > Cu > As > Cr > Cd > Pb for Jahlar Lake. PHE concentration in fish followed the order Ni > Cd > Mn > Pb > Cu > Zn > Cr > As. PHEs analysis showed that Mn; Ni and As; and Ni and Mn in summer were above the Pakistan Environmental Quality Standards (PEQS) and World Health Organization (WHO) standards in Khabeki, Uchalli, and Jahlar Lakes respectively while in winter, Mn; Cd, Ni, and As; and Ni and Mn were higher than standard values in Khabeki, Uchalli, and Jahlar Lakes respectively. In fish samples, only Cd (0.0942) was higher in summer as compared to winter (0.0512) while other seven PHEs observed were higher in winter. Conclusively, the metal pollution index showed that water quality of UWC is not very fit for human consumption directly. The bioconcentration factor results indicated potential to accumulate PHEs, i.e., Cd (29.4375 and 9.4814), Pb (16.66 and 4.375), and Ni (4.9875 and 6.206), in fish during both sampling campaigns. Target hazard quotient (THQ), target carcinogenic risk (TR), hazard index (HI), estimated daily intake (EDI), and international safe standard limits of PHEs for fish species indicated that fish from UWC is safe for human consumption. Variations in physic-chemical parameters and PHE concentration were observed spatially and temporally that could be caused by precipitation amount or natural geochemistry of the lakes' crust. The water quality was not suitable for direct human consumption. Fish was only found in Khabeki Lake that had potential to accumulate Cd, Pb, and Ni more as compared to other studied PHEs.

Impact of city effluents on water quality of Indus River: assessment of temporal and spatial variations in the southern region of Khyber Pakhtunkhwa, Pakistan

The impact of city effluents on water quality of Indus River was assessed in the southern region of Khyber Pakhtunkhwa, Pakistan. Water samples were collected in dry (DS) and wet (WS) seasons from seven sampling zones along Indus River and the physical, bacteriological, and chemical parameters determining water quality were quantified. There were marked temporal and spatial variations in the water quality of Indus River. The magnitude of pollution was high in WS compared with DS. The quality of water varied across the sampling zones, and it greatly depended upon the nature of effluents entering the river. Water samples exceeded the WHO permissible limits for pH, EC, TDS, TS, TSS, TH, DO, BOD, COD, total coliforms, Escherichia coli, Ca²⁺, Mg²⁺, NO₃^-, and PO₄^2-. Piper analysis indicated that water across the seven sampling zones along Indus River was alkaline in nature. Correlation analyses indicated that EC, TDS, TS, TH, DO, BOD, and COD may be considered as key physical parameters, while Na⁺, K⁺, Ca²⁺, Mg²⁺, Cl^-, F^-, NO₃^-, PO₄^2-, and SO₄^2- as key chemical parameters determining water quality, because they were strongly correlated (r > 0.70) with most of the parameters studied. Cluster analysis indicated that discharge point at Shami Road is the major source of pollution impairing water quality of Indus River. Wastewater treatment plants must be installed at all discharge points along Indus River for protecting the quality of water of this rich freshwater resource in Pakistan.

Spatio-temporal variations of PM2.5 emission in China from 2005 to 2014

With the rapid development of economy, air pollution has become increasingly serious nowadays in China, especially for the PM2.5. In this paper, the Spatio-temporal variations of PM2.5 emission over the past decade, from 2005 to 2014, were researched by cartograms. Meanwhile, a complex network technology was adopted to study the spatial auto-correlation of PM2.5 emission. The results showed that every province in China suffered a disparate increment in PM2.5 emission during the past ten years and also indicated that provinces in the same region had a huge influence on each other. There were three sectors including the thermal power, biomass burning and building materials that constituted the major sources of PM2.5 emission and they had different changing trends. There existed a dramatic difference in the east and west of China considering that the amount of PM2.5 was closely related to gross domestic product (GDP) and population. With higher GDP and population, eastern provinces emitted the most amount of PM2.5. Normalization results proposed that most of the provinces were PM2.5 exporting provinces in the southeast of China while most in the northwest were importing provinces. This study can help the policy-makers understand the distribution characteristics of PM2.5 emission and propose the effective strategy to mitigate the pollution of haze.

Assessment of Mine Water Quality Using Heavy Metal Pollution Index in a Coal Mining Area of Damodar River Basin, India

A total no. of 16 mine water (underground and opencast coal mine pump discharges) samples were collected from East Bokaro coalfield during pre-monsoon, monsoon and post-monsoon seasons. The concentrations of Fe, Mn, Cu, Pb, Zn, Ni, As, Se, Al, Cd and Cr were determined using inductively coupled plasma mass spectrometry for the assessment of spatio-temporal variations, source apportionment and heavy metal pollution indexing. The results demonstrated that concentrations of the metals showed significant seasonality and most variables exhibited higher levels in the pre-monsoon season. The principle component analysis for ionic source identification was synthesized into three factors with eigen values cut off at greater than unity and explained about 64.8% of the total variance. The extracted factors seemed to be associated to the geogenic, extensive mining and allied transportation sources of the elements. The heavy metal pollution index (HPI) of the mine water calculated for the individual locations varied from 7.1 to 49.5. Most of the locations fall under low to medium classes of HPI except few locations which are under the influence of surface mining and associated transportation.

Massive land system changes impact water quality of the Jhelum River in Kashmir Himalaya

The pristine aquatic ecosystems in the Himalayas are facing an ever increasing threat from various anthropogenic pressures which necessitate better understanding of the spatial and temporal variability of pollutants, their sources, and possible remedies. This study demonstrates the multi-disciplinary approach utilizing the multivariate statistical techniques, data from remote sensing, lab, and field-based observations for assessing the impact of massive land system changes on water quality of the river Jhelum. Land system changes over a period of 38 years have been quantified using multi-spectral satellite data to delineate the extent of different anthropogenically driven land use types that are the main non-point sources of pollution. Fifteen water quality parameters, at 12 sampling sites distributed uniformly along the length of the Jhelum, have been assessed to identify the possible sources of pollution. Our analysis indicated that 18% of the forested area has degraded into sparse forest or scrublands from 1972 to 2010, and the areas under croplands have decreased by 24% as people shifted from irrigation-intensive agriculture to orchard farming while as settlements showed a 397% increase during the observation period. One-way ANOVA revealed that all the water quality parameters had significant spatio-temporal differences (p < 0.01). Cluster analysis (CA) helped us to classify all the sampling sites into three groups. Factor analysis revealed that 91.84% of the total variance was mainly explained by five factors. Drastic changes in water quality of the Jhelum since the past three decades are manifested by increases in nitrate-nitrogen, TDS, and electric conductivity. The especially high levels of nitrogen (858 ± 405 μgL(-1)) and phosphorus (273 ± 18 μgL(-1)) in the Jhelum could be attributed to the reckless application of fertilizers, pesticides, and unplanned urbanization in the area.