\r\n\tManagement of these disorders requires good clinical evaluation, diagnostic tests, appropriate therapy and huge healthcare cost. Sometimes multiple specialties (gastroenterologists, \r\n\tgastrointestinal motility specialists, otolaryngologists, surgeons, speech therapists, medical oncologists and radiation oncologists) are involved in the management of dysphonia and dysphagia. In the recent years, there have been many updates in the management of these disorders. This book will discuss systematically the different etiologies and management of dysphonia, maxillofacial, oropharyngeal and esophageal dysphagia. This book will be a good \r\n\tguide to the practicing physicians for the management of voice and swallowing disorders.
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1. Introduction
Continuous increase in environmental pollution caused by the expansion and amplification of domestic, industrial, and agricultural waste generation has resulted in steadily growing number of contaminants release into the environment [1]. The uncontrolled discharge of pollutants into natural sinks such as aquatic ecosystems in developing countries like Nigeria has prompted a need for periodic assessment of the level of pollutants released into the environment. Contamination of water resources and soil with toxic metals and priority organic pollutants represents a major environmental challenge being a source of human exposure to these toxicants with potential deleterious human health effects. Soils in several parts of Nigeria have accumulated considerable amount of toxic elements arising largely from unsustainable consumption and production activities such as illegal mining of solid minerals, uncontrolled land filling of post-consumer hazardous wastes including electronic waste or e-waste [2, 3], uncontrolled industrial emissions, and vehicular emissions; as well as environmentally unsound petroleum exploration, production and exploitation activities, and accidental crude and petroleum products oil spills etc., [3].
Soil is the foundation of terrestrial ecosystems and a non- renewable fundamental agricultural resource, inextricably linked to productivity, land development and environmental quality [4]. Soils may contain many organic and inorganic compounds of natural and anthropogenic origin. The concentrations and toxicity of these compounds present in environmental media range very widely and depend on possible interactions (synergies) among chemicals. The continuous introduction of these contaminants into the environment has resulted in their accumulation. Soil pollution with heavy metals occurs not only near mines and smelters, but also on agricultural land because of the application of sewage sludge as fertiliser and metal-based pesticides [5]. Extensive soil contamination with hazardous pollutants including inorganic (i.e. Cd, Pb, Cu, Hg, As etc) and organic (i.e. pesticides, dioxins, polyaromatic hydrocarbons etc) pollutants has increasingly been of global concern over the last decades, especially in Asian [6] and other developing countries, where urbanization and industrialization have occured rapidly and haphazardly.
Heavy metals continue to receive increasing attention due to a better understanding of their fate as well as toxicological relevance in ecosystems and human health [7]. Pollution of soils by heavy metals represents one of the most important ecological problems today [8]. Anthropogenic emission of heavy metals in the environment during the last century has led to increasing accumulation of metals in soils and natural waters in both urban and rural areas. Heavy metals are ecologically harmful because they tend to bio-accumulate over time in soils and plants with ability to have a negative influence on the physiological activities of plants (e.g. photosynthesis, gaseous exchange and nutrient absorption), influencing reductions in plant growth, dry matter accumulation and yield [9]. Heavy metal pollution exerts toxic effects on soil microbial biomass [10] and microbial processes such as soil respiration, nitrogen mineralization, and enzyme activities [11]. Soil contamination by heavy metals has also been shown to inhibit soil microbial activities [12], in turn reducing soil fertility and inhibiting the germination of certain seed plants [13]. Heavy metals contamination may also produce nutrient imbalance in plants with adverse effects on the synthesis and functioning of many biologically active compounds [14]. Subsequent accumulation of metals in the food chain [15] is detrimental to human health.
Heavy metals transport in soil profile is a major environmental concern because even slow transport through the soil may eventually lead to deterioration of groundwater quality. Preferential flow can accelerate the movement of water and solutes through soil profile [16]. Soil pollution can lead to water pollution if toxic chemicals leach into groundwater, or if contaminated runoff reaches streams, lakes, or oceans. The decomposition of organic materials in soil can release sulphur dioxide and other sulphur compounds, causing acid rain which can leach heavy metals from soil. Thus, there is need to reduce the introduction of heavy metals into the environment from anthropogenic sources since metals are persistent, toxic and non- biodegradable [3]. In addition, chemicals that are not water-soluble contaminate plants that grow on polluted soils, and they also tend to accumulate increasingly toward the top of the food chain. Both organic and inorganic contaminants are important in soil management. The most prominent chemical groups of organic contaminants are petroleum hydrocarbons, Polycyclic Aromatic Hydrocarbons (PAHs), Polychlorinated Biphenyls (PCBs), chlorinated aromatic compounds, detergents, and pesticides. Inorganic species include nitrates, phosphates, and heavy metals such as cadmium, chromium and lead.
Organochlorine pesticides not only accumulate in animal tissues; many are extremely stable and persist in soil and plants, and if soluble enough can reach groundwater or surface waters. They can therefore enter the food chain not only via their target and non-target organisms, but also imbibed water and via plants eaten by herbivores, including cattle [17]. Their persistence in soils depends both on the nature of the soil and their own physico-chemical properties. Light soils facilitate the water-borne transport of soluble pesticides [18]. Soils with high clay and organic matter contents tend to retain both the more soluble pesticides (because of their high water storage capacity) and the more hydrophobic pesticides (because of their high specific surface area and other sorption-favouring properties) [19,20]. Because of the dangers they pose to non-target organisms, DDT and a number of other organochlorine pesticides were banned in most countries in the 1970s and 1980s, at least for agricultural use. However, because of their resistance to degradation processes and immobility, many are still found in high concentrations in soils to which they were formerly applied, where they constitute a reservoir and secondary source of ongoing contamination of waters, wildlife, and crops [21,22,23].
1.1. Health and environmental effects of heavy metals
Metals are particularly toxic to the sensitive, rapidly developing systems of foetuses, infants, and young children, otherwise known as ‘’vulnerable group’’. Some metals, such as lead and mercury, easily cross the placenta of mothers and damage the brain of foetuses. Childhood exposure to some metals such as lead and mercury can result in learning difficulties, memory impairment, damage to the nervous system, and behavioural problems such as aggressiveness and hyperactivity. At higher doses, heavy metals can cause irreversible brain damage. Children may receive higher doses of metals from food than adults, since they consume more food for their body weight than adults [24].
Exposure to manganese (Mn) is usually via inhalation, which results in the main cause of its toxicity. Mn toxicity has been reported through occupational (e.g. welder, miner) and dietary overexposure and is evidenced primarily in the central nervous system, although lung, cardiac, liver, reproductive and fetal toxicity have been noted [24]. Mn neurotoxicity results from an accumulation of the metal in brain tissue [25]. Brain permeability to manganese is higher than that to iron and zinc. Manganese is easily concentrated in the brain, especially in the basal ganglia, and can cause an irreversible neurological syndrome similar to Parkinson’s disease [24].
Following long-term exposure to cadmium, the main health concerns are its toxicity to the kidney and bones, arising via ingestion and inhalation, and its lung carcinogenicity seen in exposed workers following inhalation [26]. Over a period of time, cadmium accumulates in the kidney and, if the organ concentration exceeds a critical threshold, the tubule cells become damaged and renal function impaired. This cadmium build-up also affects vitamin D metabolism, disturbing the calcium balance within the body, which may lead to a decrease in the mineral content within the bones, resulting in osteoporosis and osteomalacia [26,27]. Its toxicity is linked with reproduction problem because it affects sperm and reduces birth weight. It is a potential carcinogen and seems to be a causal factor in cardiovascular diseases and hypertension. Large concentrations of Cd in the soil are associated with parent material (black slates) and most are manmade (burning of fossil fuels, application of fertilizers, sewage sludge, and plastic waste) [28,29]. In humans, long-term exposure is associated with renal dysfunction. The average daily intake for humans is estimated as 0.15 µg from air and 1 µg from water. Smoking a packet of cigarettes can lead to the inhalation of around 2-4 µg of cadmium, but levels may vary widely [27].
Mercury is a toxic substance which has no known function in human biochemistry or physiology and does not occur naturally in living organisms [27]. Mercury is a toxic heavy metal and a persistent environmental pollutant. Known sources of Hg in soil e.g. mercury-in-bulb thermometers used in hospitals; alkyl mercury compounds especially methyl mercury used as fungicide in agriculture, present in coal and hydrocarbon gas etc. Exposure to mercury is associated with serious adverse health and developmental effects, especially in pregnant women, developing foetuses, and young children [24]. This heavy metal is toxic even at low concentration to a wide range of organisms including humans. The organic form of mercury can be particularly toxic, and the methyl-and ethyl-forms have been the cause of several major epidemics of poisoning in humans resulting from the ingestion of contaminated food, e.g. fish. Two major epidemics in Japan were caused by the release of methyl and other mercury compounds from an industrial site followed by accumulation of the chemicals in edible fish. The poisoning became well-known as Minamata disease [28,29]. Inorganic mercury poisoning is associated with tremors, gingivitis and/or minor psychological changes, together with spontaneous abortion and congenital malformation. Monomethylmercury causes damage to the brain and the central nervous system, while foetal and postnatal exposure have given rise to abortion, congenital malformation and developmental changes in young children [27]. The negotiations under UNEP of a new Minamata Mercury Convention is under way to underscore international concerns about the environmental and health impact of mercury and the need for coordinated global action to address the issue effectively. Average concentrations of mercury in soil are 6.6 mg/kg, 6.6 mg/kg, 24 mg/kg and 50 mg/kg in agricultural, residential/parkland, commercial and industrial soils, respectively [30].
Lead has been known to be toxic since the 2nd century BC in Greece. It is a widespread contaminant in soils. Lead poisoning is one of the most prevalent public health problems in many parts of the world. It was the first metal to be linked with failure in reproduction. It can cross the placenta easily. It also affects the brain, causing hyperactivity and deficiency in the fine motor functions, thus, it results in damage to the brain. The nervous systems of children are especially sensitive to Pb leading to retardation. It is also cardiotoxic and contributes to cardiomyopathy (disease of the heart muscle leading to the enlargement of the heart) [28,29]. Lead affects almost every organ system in the human body. The central nervous system is particularly vulnerable in infants and children under age six. The effects are the same whether it is breathed or swallowed. Large amounts of lead exposure may lead to blood anaemia, severe stomach ache, muscle weakness, and brain damage. Lower levels of exposure, may affect a child\'s mental and physical growth leading to learning disabilities and seizures [24]. Major sources of human exposure to lead include old lead water pipes, tetraethyl lead from gasoline, lead in paint and improper disposal of used lead acid battery (ULAB) in dump sites. In humans, exposure to lead can result in a wide range of biological effects depending on the level and duration of exposure. Various effects occur over a broad range of doses, with the developing foetus and infant being more sensitive than the adult. High levels of exposure may result in toxic biochemical effects in humans, which in turn cause problems in the synthesis of haemoglobin, effects on the kidneys, gastrointestinal tract, joints and reproductive system, and acute or chronic damage to the nervous system. Lead poisoning, which is so severe as to cause evident illness, is now less common. This could be due to international efforts at phasing out lead in gasoline and paints in many parts of the world including developing countries [31] indeed. At intermediate concentrations, however, there is persuasive evidence that lead can have small, subtle, subclinical effects, particularly on neuropsychological developments in children. Some studies suggest that there may be a loss of up to 2 IQ points for a rise in blood lead levels from 10 to 20 µg/dl in young children [26]. Uncontaminated soil contains lead concentrations less than 50 ppm but soil lead levels in many urban areas exceed 200 ppm [32]. The EPA\'s standard for lead in bare soil in play areas is 400 ppm by weight and 1200 ppm for non-play areas [33].
Arsenic is well-known as a poison and a carcinogen. It has an average concentration in the soil of 5 to 6 mg/kg [28]. Its amount in the soil is related to rock type and industrial activity [34]. It is used in combination with other materials in pigments, poison gases and insecticides (such as Paris green, calcium arsenate and lead arsenate) and is well known from former use as a rat poison. Arsenic has a long history of medical applications; before penicillin was developed an arsenic compound was used to treat syphilis and yaws. It is used in ammunition manufacturing, semi-conductor manufacturing, as a preservative in tanning and taxidermy, as well as on the exterior of wood such as deck and playground materials as well as by-product of copper smelting [34]. Acute (short-term) arsenic poisoning may cause nausea, vomiting, diarrhea, and weakness, loss of appetite, shaking, cough and headache while chronic (long-term) exposure may lead to a variety of symptoms including skin pigmentation, numbness, cardiovascular disease, diabetes, and vascular disease. Arsenic is also known to cause a variety of cancers including skin cancer (non-melanoma type), kidney, bladder, and lung, prostate and liver cancer.
Chromium is required for carbohydrate and lipid metabolism and the utilization of amino acids. Its biological function is also closely associated with that of insulin and most Cr-stimulated reactions depends on insulin. However, excessive amount of the metal can cause toxicity. Toxic levels are common in soils applied with sewage sludge [28,29]. Chromium is used in metal alloys and pigments for paints, cement, paper, rubber, and other materials. Low-level exposure can irritate the skin and cause ulceration. Long-term exposure can cause kidney and liver damage, and damage to circulatory and nerve tissue. Chromium often accumulates in aquatic life, adding to the danger of eating fish that may have been exposed to high levels of chromium [27].
Nickel occurs in the environment only at very low levels. Humans use nickel for many applications like the use of nickel as an ingredient of steel and other metal products [27], in the metallurgical, chemical and food processing industries, especially as catalysts and pigments [35]. Foodstuffs have low natural content of nickel but high amounts can occur in food crops growing in polluted soils. Humans may also be exposed to nickel by inhalation, drinking water, smoking, and eating contaminated food [27]. Uptake of high quantities of nickel can cause death, systemic effects, respiratory effects, cardiovascular effects, gastrointestinal, haematological musculoskeletal, hepatic, renal, endocrine, metabolic, immunological and lymphoreticular, neurological, reproductive, developmental effects and cancer [36]. Nickel occurs naturally in the Earth\'s crust with an average concentration of 0.0086% (86 ppm). The nickel content of soil may vary depending on local geology [37].
Copper is an essential substance to human life, but in high doses it can cause anaemia, liver and kidney damage, and stomach and intestinal irritation. People with Wilson\'s disease are at greater risk for health effects from overexposure to copper. Copper normally occurs in drinking water from copper pipes, as well as from additives designed to control algal growth [28]. The major sources of environmental copper releases include the mining, smelting and refining of copper, industries producing products from copper such as wire, pipes and sheet metal, and fossil fuel combustion [38].
1.2. Health and environmental effects of some common Persistent Organic Pollutants (POPs)
Persistent organic Pollutants (POPs) are associated with serious human health problems, including cancer, neurological damage, birth defects, sterility, and immune system defects. US Environmental Protection Agency (USEPA) and the Stockholm Convention have classified certain POPs as probable human carcinogens, including aldrin, dieldrin, chlordane, Dichlorodiphenyltrichloroethane (DDT), heptachlor, Hexachlorobenzene (HBC), toxaphene, and Polychlorinatedbiphenyls (PCBs) [39,40,41]. Laboratory studies have shown that low doses of POPs may affect organ systems. Chronic exposure to low doses of certain POPs may affect the immune and reproductive systems. Exposure to high levels of certain POPs can cause serious health effects or death. The primary potential human health effects associated with POPs are cancer; immune system suppression; nervous system disorder; reproductive damage; altered sex ratio; reduced fertility; birth defects; liver, thyroid, kidney, blood, and immune system damage; endocrine disruption; developmental disorders; shortened lactation in nursing women; and chloracne and other skin disorders.
Studies have linked POPs exposure to declines, diseases, or abnormalities in a number of wildlife species, including certain kinds of fish, birds, and mammals [39,42]. Wildlife also can act as sentinels for human health: abnormalities or declines detected in wildlife populations can sound an early warning bell for people. For example, the behavioural abnormalities and birth defects in fish, birds, and mammals in and around the Great Lakes. People are mainly exposed to POPs through contaminated foods. Less common exposure routes include drinking contaminated water and direct contact with the chemicals. In people and other mammals alike, POPs can be transferred through the placenta and breast milk to developing offspring. In addition, sensitive populations, such as children, the elderly, and those with suppressed immune systems, are typically more susceptible to many kinds of pollutants, including POPs. Because POPs have been linked to reproductive impairments due to their endocrine disrupting properties, men and women of child-bearing age may also be at risk [43-47].
Organochlorine pesticides are a large class of multipurpose chlorinated hydrocarbon chemicals, some of which are POPs. They break down slowly in the environment and accumulate in the fatty tissues of animals. Thus, they stay in the environment and food web long after being applied [48]. Many organochlorine pesticides are endocrine disrupting chemicals, meaning they have subtle toxic effects on the body’s hormonal systems [27]. Endocrine disrupting chemicals often mimic the body’s natural hormones, disrupting normal functions and contributing to adverse health effects. Organochlorine pesticide is ubiquitous environmental contaminants because they break down very slowly. The effects that some of the most common organochlorine pesticides have on humans as well as animal’s health are as follows:
Acute exposure to chlordane can possibly cause neurological effects while long-term exposure can damage the liver, kidney, and other internal organs. Significant immune system changes have also been reported in exposed workers. There is some evidence of carcinogenicity [49]. Research has also indicated that chlordane is an endocrine disruptor. The half-life of chlordane in soil has been reported to be from one to three years. Chlordane binds to aquatic sediments and bioconcentrates in the fat of organisms.
DDT is a possible human carcinogen; some of its metabolites Dichlorodiphenyldichloroethylene (DDE) and Dichlorodiphenyldichloroethane (DDD) are probable human carcinogens [49]. DDT and its breakdown products are thought to be endocrine disruptors. DDT is lipophilic and will both bio-concentrate and bio-magnify. It is present almost everywhere in the environment, and residue has been detected in the arctic. DDT breaks down into the related compounds; DDE and DDD. In the environment, DDT and its metabolites have a half life of 10 to 15 years in soil. DDT is highly toxic to birds and fish, DDE and DDD are also toxic and persistent [50]. Some DDT may evaporate from soil and enter the air, and some may be broken down by the sun or microorganisms.
Heptachlor is metabolised in animals to heptachlor epoxide, whose toxicity is similar to that of heptachlor [49]. Both binds to animal fat. Heptachlor and heptachlor epoxide are possible human carcinogens and are thought to be endocrine disruptors. At high levels or from chronic exposure, they can cause central nervous system and liver damage. The half life of heptachlor in temperate soil is up to two years. Heptachlor has been found in treated wastewater from industrial processes including coal mining, foundries, and nonferrous metals manufacturing. It has been detected in the blood of cattle in the U.S. and heptachlor has been strongly implicated in the decline of several wild bird populations [50].
Mirex is probably a carcinogen and is also thought to be an endocrine disruptor. It may cause damage to skin, liver, nervous, and reproductive systems at high levels [49]. Crustaceans may be the most sensitive organisms to mirex. It can bio-accumulate and bio-magnify and is very persistent, with a half life of up to 10 years in soil. It has been detected in arctic freshwater.
Lindane, which belongs to the class of new POPs under the Stockholm Convention may be a carcinogen and is thought to be an endocrine disruptor. It can cause nervous system effects and pulmonary oedema from short, and acute exposures. Long-term exposure can cause liver and kidney damage, as well as various blood disorders [49]. Lindane bio-concentrates slightly in fish and crustaceans, and can remain in the air for up to 17 weeks and travel long distances. It is broken down quickly in water [50]. Lindane exposure has been associated with recurrent miscarriage. Lindane also disrupts natural levels of estrogens, androgens and thyroid hormones in rodents [51]. Lindane produces behavioural and neurochemical changes in developing rats at doses that do not produce symptoms in adults. This is significant because it suggests that lindane may have the greatest effect during development [52]. Both acute and sub-chronic exposures to lindane were found to reduce dopamine concentrations in the brains of rats by about 46%. Dopamine is an important neurotransmitter with effects on mood and behaviour [53]. Lindane exposure during postnatal development in rats was associated with alterations in levels of detoxification enzymes in the brain that lasted until adulthood. It is not known how this alteration might affect the outcome of future exposures [54]. Exposure to lindane decreased both thyroid hormones and progesterone in developing lambs [55S].
Dieldrin can cause poisoning in humans and mammals following exposure via the skin, oral intake or inhalation. It acts as a stimulant to the central nervous system and accumulates in fatty tissue causing severe damage to the liver and kidneys. Animal experiments have revealed a carcinogenic effect, but as yet no teratogenic action. Residue levels of aldrin (mostly present as dieldrin) do not accumulate indefinitely, as the result of yearly applications at a constant dosage rate, but will reach a maximum level which is, in practice, of the order of that resulting from a single annual dose [56,57]. There is virtually no leaching of aldrin into deeper soil layers and thus no contamination of groundwater, which is eventually used as drinking or irrigation water [58,59].
Endosulfan is highly toxic to the nervous system and can cause circulatory problems, headache, vomiting and diarrhea. Thus, it is one of the new POPs under the Stockholm Convention. It is also a suspected hormone disruptor [49]. Endosulfan has shown no potential to accumulate over time in animals. It is more water soluble than other organochlorine pesticides, such as DDT, and is less persistent in the body because it metabolises quickly [60].
1.3. Health and environmental effects of Polycyclic Aromatic Hydrocarbons (PAHs)
Because of combustion of fossil fuels and organic waste, PAHs are ubiquitous in the environment. Studies show that certain PAHs metabolites interact with DNA and are genotoxic, causing malignancies and heritable genetic damage in humans. Many of these compounds have carcinogenic and mutagenic activities and present a hazard for human health [61]. In humans, heavy occupational exposure to mixtures of PAHs entails a substantial risk of lung, skin, or bladder cancer. PAHs generally have a low degree of acute toxicity to humans. The most significant endpoint of PAHs toxicity is cancer. Increased incidences of lung, skin, and bladder cancers are associated with occupational exposure to PAHs. It is difficult to ascribe observed health effects in epidemiological studies to specific PAHs because most exposures are to PAHs mixtures. Animal studies show that certain PAHs affect the hematopoietic, immune, reproductive, and neurologic systems and cause developmental effects [62].
1.4. Soil contamination by cattle wastes
Cattle manure is a major waste product of agricultural practice involving the breeding and rearing of cattle. Inappropriate disposal of manure can create environmental problems such as odours and leaching of nitrate ion and other pollutants into groundwater. Repeated annual application of manure with high salt content caused a build up of soluble salts in soils, sufficient to lower their productivity [63]. During the last three decades, dairy farm facilities have received attention from the public and regulations due to increased environmental concern. These facilities concentrate in certain regions of the USA (e.g. California, New York, Minnesota, and Pennsylvania) and generate considerable amount of manure, which can harm soil and water quality. Manure varies in mineral composition depending on the type of animal and the ration fed. It was reported that cattle (Bos Taurus) manure contains 2.7 to 9.5% N, 0.5 to 0.8% O, 1.7 to 2.9% K, 1.4 to 20% Ca, and 0.61 to 0.76% Mg (% dry waste basis) [64]. In addition, varying amounts of Al, Fe, Mn, S, Cl, Cu, Zn, and B and trace concentrations of Co, Cd, Cr, Ni, As and Se are present. Large fractions of these elements are present in a water-soluble form. With high precipitation, almost all regions where dairy farm facilities concentrate, great qualities of these elements are lost through surface runoff and leaching into groundwater. Manure contains a large amount of soluble and insoluble organic substances. Organic matter content ranges between 80% and 90% (dry weight basis) [64]. Pyrolysis field ionization mass spectroscopy (Py-FIMS) was also used to analyse cow manure samples [65]. The organic components that were identified include lignins, dimeric lignins, pesticides, lipids, monoesters, fatty acid, sterols, and heterocyclic nitrogen compounds.
The aim of this study was to determine the distribution, concentration and profiles of some ubiquitous environmental pollutants such as heavy metals, polycyclic aromatic hydrocarbons (PAHs) and organochlorine pesticides in soil of a cattle market around River Ogun Basin, Isheri, Nigeria so as to ascertain the level of contamination of the soil resulting from the anthropogenic activities taking place in the area.
2. Experimental
2.1. General description of ogun river basin
The River Ogun basin is situated in south western part of Nigeria covering a total area of 22.44 cubic kilometres. It arises in Oyo state, on the southern side of Yoruba plateau, and runs south into Ogun state, passing through Abeokuta before entering Lagos state and finally discharging into the Lagos Lagoon. The elevation of the northern, eastern, southern, and western boundaries are 457 m, 366 m, 426 m, and 230 m, respectively above the sea level [66]. Various organizations are active in the development of socio-economic conditions of the Ogun river basin. The Ogun-Osun River Basin Development Authority (OORBDA) is responsible for the management of the water resources. The Ogun river basin is among others contributing a diversion at Mokoloki for irrigated farming of the upland. Another is the Ogun State Agricultural Development Project, which has incorporated a fishery component to increase fish production and availability. Ogun River is used as a source of water supply for domestic, industrial, agricultural, and recreational purposes along the states it traverses. This site has become a place of interest considering its constant and continuous pollution owing to the fact that it serves as a focal point of some commercial activities in the ever growing cattle market around the basin [67]. Figure 1 shows the map of the study area.
Figure 1.
Map of river Ogun showing the Sampling Points
2.2. Sampling design
The soil samples were collected from the cattle market situated around the Ogun River, Isheri along Lagos-Ibadan Express Road. The soil samples were collected at two different depths of 0-15 cm and 15-30 cm with non-metallic sampler. The sampling site was divided into three zones as follows:
Samples were collected at five different spots (SA1-SA5) upstream the market across the river at a distance of about 100 m to the market. The major human activities on this side of the river were sand mining and fishing. The fishing activity was simple and involved the use of paddled canoe and boat with fishing net and hooks. The natural physical feature of these areas was shrub growth. The samples from this area were pooled together to form a representative sample, A1S1 (representing composite sample of the random samples collected from 0-15 cm depth), and A2S2 (representing composite sample of the random samples collected from 15-30 cm depth).
Random samples were also collected at five different locations including the market centre and the areas surrounding it. The activities and the features observed at the different points were;
SB1: Old car scraps, marshy area located about 50 m to the market centre
SB2: Auto-mechanic workshop and residential tents built with planks and polypropylene materials
SB3: Cattle rearing and selling with other petty trading
SB4: Slaughter houses, wastewater discharge point, animal hair and horn burning with tyres, animal blood cooking and processing, and solid waste dumpsite
SB5: Children playground at the river bank
The samples from this area were pooled together and a representative sample, B1S1 (representing composite sample of the random samples collected from 0-15 cm depth), and B2S2 (representing composite sample of the random samples collected from 15-30 cm depth) were obtained for the analysis.
Two samples were collected downstream the market from two points to form a composite samples C1S1 and C2S2 for the 0-15 cm and 15-30 cm depths, respectively. The activities around this point are
SC1: Petty commercial activities around a police post in a slum with most houses built with plank, rust iron sheet and polypropylene material;
SC2: A dumpsite that was almost swept off by erosion into the river situated at the river bank.
2.3. Sample collection, treatment and preservation
Two samples were collected from each area of sampling around the cattle market to form a composite. Control sample was also collected in a rural community, Lalupon in Ibadan. The sample portion that is to be analysed for PAHs and organochlorine pesticides were collected in a glass bottle wrapped with aluminium foil to prevent exposure to sunlight, as organochlorine pesticides are known to be sensitive to sunlight, while the sample to be analysed for heavy metals and physico-chemical parameters were collected in a polythene bag. The samples were preserved in an ice chest for onward transportation to the laboratory, where they were kept in a refrigerator. The samples collected for heavy metals and physico-chemical parameters were air-dried at room temperature until they were properly dried and large objects (sticks, stones, wood, and e.t.c) were manually removed. The samples were then gently ground with a porcelain mortar and pestle, and sieved through a 2 mm sieve and stored in polythene bags until sample digestion. The samples collected for PAHs and organochlorine pesticides analyses were not air-dried to minimise loss of those components which can vaporise easily [68].
2.4. Analytical procedure
2.4.1. Determination of soil pH
Approximately 20.0 g each of the air-dried and sieved soil samples (< 2 mm) were weighed, 50 ml distilled water was added and then mixed and allowed to stand for 30 minutes. Suspension was stirred every 10 minutes during this period. The suspension was allowed to settle for another 30 minutes and a pH meter electrode (Jenway 3510) was placed in the suspension and the reading was taken after some seconds. The electrode was removed from the suspension and rinsed thoroughly with distilled water and excess water was carefully dried.
2.4.2. Determination of soil organic matter
About 0.70 g each of the air-dried and sieved soil samples were weighed and 10.0 ml of 1.0 N K2CrO7 solution and 20.0 ml concentrated H2SO4 were added immediately [69]. The solution was mixed for 1 minute by swirling until the soil and reagents were thoroughly mixed. The mixture was allowed to stand for 30 minutes after which 100 ml distilled water was added and then allowed to cool under running water. 3-4 drops of Ferroin indicator was added and then titrated with 0.5 N Ferrous Ammonium Sulphate. Near the end-point, the solution took a greenish colour and later changed to dark green. At this point, the 0.5 N Ferrous Ammonium Sulphate was added drop by drop until the colour changed from green to reddish-brown at the end point. The Ferrous Ammonium Sulphate solution was standardized using 1 N potassium dichromate before use. Blank titration was carried out in the same manner, but without the soil sample.
meq- Milligram equivalent = normality of solution x ml of solution used.
2.4.3. Determination of soil particle size by the Bouyoucos hydrometer method
This is a measure of the size distribution of individual particles in a soil sample. Particle size distribution analysis is often used in soil science to evaluate soil texture. The soil texture is based on different combination of sand, silt, and clay separately, that makes up the particle size distribution. The size range of sand is 2.0 mm-0.05 mm, silt is 0.05 mm-0.002 mm and clay is less than 0.002 mm (< 0.002 mm). Particle size distribution analysis result can be used to predict the water retention capacity and unsaturated hydraulic conductivity of soils [70]. About 50.0 g of air-dried soil sample sieved to < 2 mm was weighed into 250 ml beaker. 20 ml of 5.0 % Sodium Hexametaphosphate was added along with 350 ml distilled water. The mixture was stirred mechanically on an end-to-end shaker at 100 revolutions per minutes for 5 minutes. The water-soil slurry was transferred to a sedimentation cylinder and sufficient water was added to bring the level to the 1000 ml mark. The top of the cylinder was covered and inverted several times until all the soil particles are in suspension. The cylinder was placed on the flat surface and the time was recorded. The soil hydrometer was placed on the suspension carefully and slided slowly into the suspension until the hydrometer was floating. The first reading was taken on the hydrometer at 60 s after the cylinder was set down. The hydrometer was removed and the temperature of the suspension was measured. After the first hydrometer reading, the suspension was left standing for 3 hours and the second reading was taken. The temperature of the suspension was also measured at this point. The first reading measured the percentage of silt and clay in suspension while the second reading indicated the percentage of clay in the suspension. When taking the hydrometer reading, the hydrometer was carefully lowered into the cylinder about 25 s before the reading was taken to ensure that it came to rest before the appointed reading time. The readings were taken at the top of the meniscus formed by the suspension around the stem of the hydrometer. As soon as the reading was taken, the hydrometer was carefully removed and rinsed with distilled water. The results were corrected to a temperature of 20 oC and 2.0 were subtracted to compensate for the added dispersing agent.
Correction factor for Temperature = 0.3 [Observed Temperature (T oC) – 20 oC]
% Clay + % Silt = [H1 + 0.3 (T1 - 20) – 2.0] 2
% Clay = [H2+ 0.3 (T2 - 20) – 2.0] 2
Sand = 100 – [H1 + 0.3 (T1 - 20) – 2.0] 2
Silt = 100.0 – (% Sand + % Clay)
Where,
H1 = Hydrometer reading at 60 s
T1 = observed Temperature at 60 s (= 28 oC)
H2 = Hydrometer reading at 3 hours
T2 = observed Temperature at 3 hours (= 28 oC)
2.4.4. Metal analysis
Acid digestion procedure was employed for the determination of the concentrations of the environmentally available metals in the soil samples. Prior to the determination of the metal concentration in soil, sample digestion is a necessary pre-treatment step. The most common method for determining the concentrations of metal contained in a soil sample is the total elemental analysis. The review on total metal concentration determination in soil samples revealed that heavy metals bound to non-silicates and silicate structures were determined with concentrated acids such as HCl, HClO4, and HF [71]. However, in recent times, strong acid extractant such as concentrated nitric acid, aqua regia (a mixture of concentrated HCl and concentrated HNO3 in ratio 3:1) and dilute form of the acids are used to determine total metals in contaminated soils [72]. The acids dissolve almost all elements that could become environmentally available especially metal oxides and carbonates [73].
However, heavy metals bound to silicate structures are not normally dissolved since they are not usually mobile in the environment [74] but the extractant normally give a reliable measure of metals added to soils as non-silicates from industrial sources that has potential for natural leaching and biological processes. The use of perchloric acid and hydrofluoric acid is generally fading away since complete dissolution of the soil is no longer required for total metal analysis in environmental work [75].
Most current environmental analysis work that involved total metal analysis has employed the use of 2 M HNO3 [3,76,77]. The levels of heavy metals extracted with 2 M HNO3 have been reported to represent maximum contents of potentially available metals for plants [77]. In this study, approximately 1.0 g each of the composite soil samples were digested with 20 ml of 2 M HNO3 by heating the vessel in a water bath between 90-100oC for 2 hours with shaking every 20 minutes. The vessel was allowed to cool to room temperature. The digestate was filtered and made up to mark with distilled water. Two replicate samples were digested in the same way together with a reagent blank and all the samples were analyzed using Buck 200A Atomic Absorption Spectrophotometer using air-acetylene flame.
2.5. Organochlorine pesticides and PAHs analysis
2.5.1. Soil sample extraction
A solvent mix of pesticide residue (PR) grade acetone and methylene chloride (50:50) was prepared and 50 ml of the solvent mix was added to about 10 g of the sample, spiked with 1 ml of surrogate standard [78,79]. The sample was placed in the ultrasonic bath (Grant Instruments) and sonicated for about 10-15 minutes at 70oC. Then 10 g of anhydrous sodium sulphate (Na2SO4) was added to the sample to remove the water present initially in the sample and shaken gently until a clear extract was developed. The procedure was repeated once more with an additional 50 ml of solvent mix. The solvent was then concentrated on a rotary evaporator (Buchi equipment) and exchanged with 5 ml of n-hexane then re-concentrated to 1 ml. The concentration of the sample extract was necessary to remove the acetone and methylene chloride used in the extraction. In the course of the concentration of the solvent on the evaporator, the acetone and methylene chloride was removed leaving n-hexane with the extract. This is necessary to prepare the extract for clean-up and fractionation in a column containing n-hexane-mixed silica slurry. The extracted sample was then fractionated into the aliphatic and aromatic fractions (PAHs) using silica gel column [80]. The same procedure was repeated for the extraction of organochlorine pesticide in the sample using acetone and dichloromethane (DCM) solvent mixture (50:50).
2.5.2. Column packing for fractionation and clean-up of extract
Glass column was packed with 10 g of 100-200 mesh silica gel preconditioned (baked) at 105oC overnight. The silica was mixed with n-hexane to form slurry. The column was then eluted with about 15 ml of PR grade n-hexane and the solvent was collected to waste. Caution was taken not to allow the column to dry up. Using 1 ml pipette, 1 ml of the extract in n-hexane was added onto the column and then eluted with 60 ml of n-hexane. The aliphatic fraction was collected and the column was then eluted with 40 ml of PR grade dichloromethane (DCM) and another fraction was collected, which is the Polycyclic Aromatic Hydrocarbons (PAHs) fraction. Each of these fractions was concentrated to 1 ml using a rotary evaporator. After concentrating the PAH fraction to 1 ml, 5 ml of PR grade n-hexane was added and was further concentrated to remove the DCM using the rotary evaporator. The concentrates were later transferred into 2 ml sample vials using the graduated 2 ml pipettes. The final volumes of the extracts were noted and the sample extracts were subjected to GC-MS analysis. The same clean-up procedure was carried out on the organochlorine pesticide extract by eluting the column with PR grade n-hexane.
2.5.3. Instrumental analysis
The extracts were analysed for PAHs and organochlorine pesticides using a GC equipped with MS detector. Separation was achieved by injecting about 1 μL of each extract into the GC system (in a splitless mode) through a capillary column (3.0 m length, 0.25 mm internal diameter, 0.25 μm film thickness). Helium gas was used as the carrier gas. Table 1 summarize the GC/MS condition. The quantification limit of the PAHs in the standard and the samples was 0.001 ppm, while that of the organochlorine pesticide residue was 0.002 ppm. The average response factor for the weight ranges were calculated and used for sample quantification.
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t\tGC/MS condition\n\t\t\t
\n\t\t\t
\n\t\t\t\tPAHs\n\t\t\t
\n\t\t\t
\n\t\t\t\tOrganochlorine pesticide\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
Instrument
\n\t\t\t
Shimadzu GC-MS QP2010
\n\t\t\t
Shimadzu GC-MS QP2010
\n\t\t
\n\t\t
\n\t\t\t
Column
\n\t\t\t
HP-1MS (Cross linked PH ME siloxane) 19091S-933 Film thickness: 0.25 µm, Length: 3.0 m, Column ID: 0.25 mm
\n\t\t\t
HP-1MS (Cross linked PH ME siloxane) 19091S-933 Film thickness: 0.25 µm, Length: 3.0 m, Column ID: 0.25 mm
\n\t\t
\n\t\t
\n\t\t\t
Injection method
\n\t\t\t
Splitless mode
\n\t\t\t
Splitless mode
\n\t\t
\n\t\t
\n\t\t\t
Injection volume
\n\t\t\t
1.0 μL
\n\t\t\t
1.0 μL
\n\t\t
\n\t\t
\n\t\t\t
Carrier gas
\n\t\t\t
Helium (1.2 ml/min)
\n\t\t\t
Helium (1.18 ml/min)
\n\t\t
\n\t\t
\n\t\t\t
Injection temperature
\n\t\t\t
250 ºC
\n\t\t\t
250 ºC
\n\t\t
\n\t\t
\n\t\t\t
Oven temperature programme
\n\t\t\t
GC oven temperature was kept 60 ºC for 1 min First ramp at 5 ºC/ min to 180 ºC Second ramp at 10 ºC/min to 280 ºC Final temperature at 10 ºC/min to 300 ºC
\n\t\t\t
GC oven temperature was kept 80 ºC for 1 min First ramp at 5 ºC/ min to 200 ºC Final temperature at 10 ºC/min to 270 ºC
\n\t\t
\n\t\t
\n\t\t\t
MS mode
\n\t\t\t
Total ion current (TIC) mode
\n\t\t\t
Selected Ion Monitoring Mode (SIM)
\n\t\t
\n\t\t
\n\t\t\t
Ion source temperature
\n\t\t\t
200 ºC
\n\t\t\t
200 ºC
\n\t\t
\n\t\t
\n\t\t\t
Interface temperature
\n\t\t\t
250 ºC
\n\t\t\t
250 ºC
\n\t\t
\n\t
Table 1.
Operational conditions of GC/MS for PAHs and organochlorine pesticide
The concentration of each analyte was determined by calculating the amount of analyte or hydrocarbon range injected from the peak response in area ratio. The contribution from the solvent front and the surrogate compound were excluded from the total area of the sample.
Cf=A(p)xRfxVfxDfx1000Wi
Where,
Cf = Final Sample concentration (µg/L)
A(p) = Measured area of peak (peaks)
Wi = Initial weight extracted (g dry weight)
Vf = Final extract volume (ml).
Df = Dilution factor of sample or extract if diluted.
Rf= Response factor from the calibration standard calculation
Rf=Concentration(P)Area(P)
Concentration (p) = Total concentration of range
3. Results and discussion
3.1. Soil pH
Soil pH is one of the most important physico-chemical properties which control many other soil physical, chemical, and biological properties. The pH of a soil is affected by the concentration of CO2 in the soil air, salt concentration (salt effect), and the presence of colloidal particles (suspension effect). The higher the CO2 concentration in the soil solution, the lower the pH, and the pH of a neutral or calcareous soil is very sensitive to small changes in CO2 concentration. pH greatly affects the solubility of minerals in soils. Most minerals are more soluble in acid soils than in neutral or slightly basic solutions [81]. The pH of a soil is related to the bioavailability of metals in the soil to plants. At low pH, metals are easily bioavailable because there is increase in the solubility of metals. However, at high pH i.e. slightly alkaline to highly alkaline conditions, metals are not easily mobilized, because they are not easily soluble at high pH, hence not easily bio available [82]. The pH of the composite soils collected at the five different points (SA1-SA5) opposite the market at a distance of about 100 m to the market was slightly acidic with the pH of the topsoil (0-15cm) slightly lower than that of the subsoil (15-30cm) except at the downstream of the river (sampling area C) (Table 2).
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t\t
PhysicalParameter
\n\t\t\t
\n\t\t\t\tSampling Area A\n\t\t\t
\n\t\t\t
\n\t\t\t\tSampling Area B\n\t\t\t
\n\t\t\t
\n\t\t\t\tSampling Area C\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t\tA1S1\n\t\t\t\t\n\t\t\t
\n\t\t\t
\n\t\t\t\tA2S2\n\t\t\t\t\n\t\t\t
\n\t\t\t
\n\t\t\t\tB1S1\n\t\t\t\t\n\t\t\t
\n\t\t\t
\n\t\t\t\tB2S2\n\t\t\t\t\n\t\t\t
\n\t\t\t
\n\t\t\t\tC1S1\n\t\t\t\t\n\t\t\t
\n\t\t\t
\n\t\t\t\tC2S2\n\t\t\t\t\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t
(0-15cm)
\n\t\t\t
(15-30cm)
\n\t\t\t
(0-15cm)
\n\t\t\t
(15-30cm)
\n\t\t\t
(0-15cm)
\n\t\t\t
(15-30cm)
\n\t\t
\n\t\t
\n\t\t\t
pH
\n\t\t\t
5.43
\n\t\t\t
5.58
\n\t\t\t
6.69
\n\t\t\t
7.19
\n\t\t\t
6.82
\n\t\t\t
6.11
\n\t\t
\n\t\t
\n\t\t\t
% Organic matter content
\n\t\t\t
0.83
\n\t\t\t
1.05
\n\t\t\t
0.97
\n\t\t\t
1.80
\n\t\t\t
0.88
\n\t\t\t
1.31
\n\t\t
\n\t\t
\n\t\t\t
% Clay
\n\t\t\t
24.8
\n\t\t\t
20.8
\n\t\t\t
22.8
\n\t\t\t
26.8
\n\t\t\t
24.8
\n\t\t\t
28.8
\n\t\t
\n\t\t
\n\t\t\t
% Silt
\n\t\t\t
20
\n\t\t\t
24
\n\t\t\t
18
\n\t\t\t
28
\n\t\t\t
24
\n\t\t\t
22
\n\t\t
\n\t\t
\n\t\t\t
% Sand
\n\t\t\t
55.2
\n\t\t\t
55.2
\n\t\t\t
59.2
\n\t\t\t
45.2
\n\t\t\t
51.2
\n\t\t\t
49.2
\n\t\t
\n\t
Table 2.
Summary of Soil physicochemical parameters
3.2. Soil Organic Matter
Soil organic matter is any material produced originally by living organisms (plant or animal) that is returned to the soil and goes through the decomposition process. At any given time, it consists of a range of materials from the intact original tissues of plants and animals to the substantially decomposed mixture of materials known as humus. Most soil organic matter originates from plant tissue. Plant residues contain 60-90 percent moisture. The remaining dry matter consists of carbon (C), oxygen, hydrogen (H) and small amounts of sulphur (S), nitrogen (N), phosphorus (P), potassium (K), calcium (Ca) and magnesium (Mg). Although present in small amounts, these nutrients are very important from the viewpoint of soil fertility management [83]. Soil organic matter (SOM) serves as a soil conditioner, nutrient reservoir, substrate for microbial activity, preserver of the environment, and major determinant for sustaining and increasing agricultural productivity. The OM content of soils ranges from less than1% in desert soils to close to 100% in organic soils. A typical agricultural soil may contain between 1 and 5% OM in the top 15 cm [84]. The percentage organic matter of the soil samples collected around the site is shown in Table 2. Generally, the subsoil has more organic matter content than their respective topsoil. The top soil contains less than 1% OM while the subsoil contains higher values. Soil organic matter performs very important functions in the soil such as: acts as a binding agent for mineral particles, this is responsible for producing friable (easily crumbled) surface soils; increases the amount of water that a soil may hold; and provides food for organisms that inhabit the soil. Humus is an integral component of organic matter because it is fairly stable and resistant to further decomposition. Humus is brown or black and gives soils its dark colour. Like clay particles, humus is an important source of plant nutrients.
3.3. Particle size distribution (soil texture)
Particle size is a fundamental property of any sediment, soil or dust deposit that can provide important clues to nature and provenance and influences a variety of other properties [85]. Soil particle size distribution is of greta importance to soil water movement, soil erosion and soil solute migration [86]. It is the determination of the proportion of each soil fraction in the samples and includes the % clay, % silt and % sand. Generally, in all the soil samples collected, sand has the highest percentage. The topsoil of the site has the highest percentage of sand in all the sampling areas. Figure 2 shows the variation in the physico-chemical parameters in the soil.
3.4. Concentration of heavy metals in soil
The results of heavy metals analyzed in the soil samples are shown in Table 3 while Figure 3 shows the distribution around the study site. There is variation in the distribution of the metals around the market with some of the metals such as lead (23.8 mg/kg) and copper (10.4 mg/kg) having the highest concentrations in the subsoil (15-30 cm). The concentrations of all the metals around the market is the highest when compared to the downstream and upstream of the river. This may be attributed to the anthropogenic activities in this area. In most cases, the subsoil has higher concentration of the metals than their respective topsoil, except Zn, Cd, and Ni. However, Cadmium compounds being of very low solubility in water will have little downward movement and accumulate in the topsoil [87]. This may be due to strong adsorption of Cd by the surface soils, which have a higher organic matter content and higher pH; factors which are known to increase Cd adsorption in soils [88]. Also, it was reported that Cd accumulated in the soil surface layers and had low vertical movement when mobility of heavy metals contained in the sludge and the wastewater used for the irrigation was studied in the soil samples collected from the soil profiles from the surface to 100 cm depth of farmland [89]. The mean concentrations and standard deviation of Pb, Zn, Cu, Cr, Cd and Ni in the topsoil (0 – 15cm) and subsoil (15 – 30cm) around the river basin at Isheri are 14.6 ± 4.5 mg/kg and 18.1 ± 8.1 mg/kg; 38.0 ± 27 mg/kg and 44.6 ± 28 mg/kg; 6.41 ± 3.3 mg/kg and 7.77 ± 3.7 mg/kg; 7.35 ± 0.1 mg/kg and 10.5 ± 0.4 mg/kg; 0.74 ± 0.3 mg/kg and 0.63 ± 0.03 mg/kg ; and 3.81 ± 0.5 mg/kg and 5.70 ± 0.3 mg/kg, respectively.
Comparing the results of heavy metal concentrations obtained in this study with the control sample collected at a rural community, Lalupon in Ibadan and some typical values in rural and urban soil around the world (Table 4). The average metal concentrations in both the top and subsoil were higher than the values obtained from the control sample. There are no background and baseline data on toxic metals concentrations in Nigeria. Metal concentrations in the study site when compared to the control sample suggested that anthropogenic inputs have occurred over the years. The concentrations of all the metals were below the values reported [90] except Cd which appeared higher in both the top and the subsoil of the study area.
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t\tMetals\n\t\t\t
\n\t\t\t
\n\t\t\t\tSampling Area A\n\t\t\t
\n\t\t\t
\n\t\t\t\tSampling Area B\n\t\t\t
\n\t\t\t
\n\t\t\t\tSampling Area C\n\t\t\t
\n\t\t\t
\n\t\t\t\tMean Conc.\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t\tA1S1\n\t\t\t\t\n\t\t\t
\n\t\t\t
\n\t\t\t\tA2S2\n\t\t\t\t\n\t\t\t
\n\t\t\t
\n\t\t\t\tB1S1\n\t\t\t\t\n\t\t\t
\n\t\t\t
\n\t\t\t\tB2S2\n\t\t\t\t\n\t\t\t
\n\t\t\t
\n\t\t\t\tC1S1\n\t\t\t\t\n\t\t\t
\n\t\t\t
\n\t\t\t\tC2S2\n\t\t\t\t\n\t\t\t
\n\t\t\t
\n\t\t\t\tTopsoil\n\t\t\t
\n\t\t\t
\n\t\t\t\tSubsoil\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t
(0-15cm)
\n\t\t\t
(15-30cm)
\n\t\t\t
(0-15cm)
\n\t\t\t
(15-30cm)
\n\t\t\t
(0-15cm)
\n\t\t\t
(15-30cm)
\n\t\t\t
(mg/kg)
\n\t\t\t
(mg/kg)
\n\t\t
\n\t\t
\n\t\t\t
Pb
\n\t\t\t
12.9
\n\t\t\t
13.9
\n\t\t\t
17.7
\n\t\t\t
23.8
\n\t\t\t
11.4
\n\t\t\t
12.4
\n\t\t\t
14.6±4.5
\n\t\t\t
18.1±8.1
\n\t\t
\n\t\t
\n\t\t\t
Zn
\n\t\t\t
20.8
\n\t\t\t
20.7
\n\t\t\t
57.0
\n\t\t\t
64.7
\n\t\t\t
19.0
\n\t\t\t
24.5
\n\t\t\t
38.0±4.5
\n\t\t\t
44.6±28
\n\t\t
\n\t\t
\n\t\t\t
Cu
\n\t\t\t
6.12
\n\t\t\t
6.19
\n\t\t\t
8.73
\n\t\t\t
10.4
\n\t\t\t
4.09
\n\t\t\t
5.14
\n\t\t\t
6.41±3.3
\n\t\t\t
7.77±3.7
\n\t\t
\n\t\t
\n\t\t\t
Cr
\n\t\t\t
10.4
\n\t\t\t
10.4
\n\t\t\t
7.3
\n\t\t\t
10.7
\n\t\t\t
7.4
\n\t\t\t
10.2
\n\t\t\t
7.35±0.1
\n\t\t\t
10.5±0.4
\n\t\t
\n\t\t
\n\t\t\t
Cd
\n\t\t\t
0.73
\n\t\t\t
0.55
\n\t\t\t
0.93
\n\t\t\t
0.61
\n\t\t\t
0.55
\n\t\t\t
0.65
\n\t\t\t
0.74±0.3
\n\t\t\t
0.63±0.03
\n\t\t
\n\t\t
\n\t\t\t
Ni
\n\t\t\t
5.27
\n\t\t\t
4.72
\n\t\t\t
4.19
\n\t\t\t
5.91
\n\t\t\t
3.43
\n\t\t\t
5.48
\n\t\t\t
3.81±0.5
\n\t\t\t
5.70±0.3
\n\t\t
\n\t
Table 3.
Heavy metal concentrations (mg/kg) in the soil around the cattle market in Isheri, Nigeria
There is positive and significant correlation between Zn, Pb and Cu and Ni with Cr. Atmospheric fallout of the metals such as lead from the motor vehicle exhaust from the nearby busy Lagos-Ibadan express road as well as movement of goods around the market may have contributed to the high concentrations of heavy metals in the soil. Also, there is positive and significant correlation between organic matter and Ni, Pb, and Cu.
Figure 2.
Variation in the physicochemical parameters in the soil around the cattle market in Isheri, Nigeria
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t
\n\t\t\t\tPb\n\t\t\t
\n\t\t\t
\n\t\t\t\tZn\n\t\t\t
\n\t\t\t
\n\t\t\t\tCd\n\t\t\t
\n\t\t\t
\n\t\t\t\tCu\n\t\t\t
\n\t\t\t
\n\t\t\t\tCr\n\t\t\t
\n\t\t\t
\n\t\t\t\tNi\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
Topsoil (this study)
\n\t\t\t
14.6
\n\t\t\t
38
\n\t\t\t
0.74
\n\t\t\t
6.41
\n\t\t\t
7.35
\n\t\t\t
3.81
\n\t\t
\n\t\t
\n\t\t\t
Subsoil (this study)
\n\t\t\t
18.1
\n\t\t\t
44.6
\n\t\t\t
0.63
\n\t\t\t
7.77
\n\t\t\t
10.5
\n\t\t\t
5.70
\n\t\t
\n\t\t
\n\t\t\t
Control site (0-15cm)
\n\t\t\t
9.12
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
4.57
\n\t\t\t
4.83
\n\t\t\t
0.57
\n\t\t
\n\t\t
\n\t\t\t
Rural–urban Soils average (Bowen, 1979)
\n\t\t\t
35
\n\t\t\t
90
\n\t\t\t
0.35
\n\t\t\t
30
\n\t\t\t
70 \n\t\t\t
\n\t\t\t
- \n\t\t\t
\n\t\t
\n\t
Table 4.
Comparison of mean concentrations (mg/kg) of metals in this study with the control sample and typical soil values around the world
Figure 3.
Heavy metal distribution in the soil around the cattle market in Isheri, Nigeria
3.5. Concentration of Polynuclear Aromatic Hydrocarbons (PAHs)
The results of the PAHs in the soil samples collected along the River Ogun basin at Isheri, along Lagos-Ibadan Express road are shown in the Table 5. Regular burning of all kinds of waste, tyres etc. was observed in this area and this might be responsible for the presence of PAHs around the study site. Some of the PAHs such as naphthalene, phenanthrene, fluoranthene, chrysene benzo(a)anthracene and perylene, were found at significantly higher concentrations around the area. Out of the seven species regarded as potential carcinogenic compounds, namely: chrysene, benzo(a)anthracene, benzo(k)flouranthene, benzo(g,h,i)perylene, dibenzo(a,h)anthracene, indeno(1,2,3-cd)pyrene, and benzo(a)pyrene, chrysene has the highest concentration in the samples collected at all the sampling points. Its concentration was relatively higher in the subsoil (15-30cm) than the topsoil (0-15cm) except at sampling point C (downstream), where there is little variation in the concentrations in both layers. Figure 4 shows the variation in the concentration of PAHs with depth.
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t\tPAHs Component\n\t\t\t
\n\t\t\t
\n\t\t\t\tSampling area A\n\t\t\t
\n\t\t\t
\n\t\t\t\tSampling area B\n\t\t\t
\n\t\t\t
\n\t\t\t\tSampling area C\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t\tA1S1\n\t\t\t\t\n\t\t\t
\n\t\t\t
\n\t\t\t\tA2S2\n\t\t\t\t\n\t\t\t
\n\t\t\t
\n\t\t\t\tB1S1\n\t\t\t\t\n\t\t\t
\n\t\t\t
\n\t\t\t\tB2S2\n\t\t\t\t\n\t\t\t
\n\t\t\t
\n\t\t\t\tC1S1\n\t\t\t\t\n\t\t\t
\n\t\t\t
\n\t\t\t\tC2S2\n\t\t\t\t\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t\t(0-15 cm)\n\t\t\t
\n\t\t\t
\n\t\t\t\t(15-30 cm)\n\t\t\t
\n\t\t\t
\n\t\t\t\t(0-15 cm)\n\t\t\t
\n\t\t\t
\n\t\t\t\t(15-30 cm)\n\t\t\t
\n\t\t\t
\n\t\t\t\t(0- 15 cm)\n\t\t\t
\n\t\t\t
\n\t\t\t\t(15-30 cm)\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
Naphthalene
\n\t\t\t
419
\n\t\t\t
244
\n\t\t\t
159
\n\t\t\t
663
\n\t\t\t
668
\n\t\t\t
609
\n\t\t
\n\t\t
\n\t\t\t
2-methyl Naphthalene
\n\t\t\t
158
\n\t\t\t
103
\n\t\t\t
64.3
\n\t\t\t
234
\n\t\t\t
245
\n\t\t\t
227
\n\t\t
\n\t\t
\n\t\t\t
Acenaphthylene
\n\t\t\t
8.1
\n\t\t\t
4.0
\n\t\t\t
8.4
\n\t\t\t
24.2
\n\t\t\t
20.2
\n\t\t\t
25.8
\n\t\t
\n\t\t
\n\t\t\t
Acenaphthene
\n\t\t\t
3.7
\n\t\t\t
19.7
\n\t\t\t
3.8
\n\t\t\t
9.3
\n\t\t\t
9.1
\n\t\t\t
69.2
\n\t\t
\n\t\t
\n\t\t\t
Flourene
\n\t\t\t
17.9
\n\t\t\t
9.3
\n\t\t\t
18.3
\n\t\t\t
18.1
\n\t\t\t
29.6
\n\t\t\t
18.4
\n\t\t
\n\t\t
\n\t\t\t
Phenanthrene
\n\t\t\t
60.4
\n\t\t\t
47.5
\n\t\t\t
91.7
\n\t\t\t
76.4
\n\t\t\t
129
\n\t\t\t
85.7
\n\t\t
\n\t\t
\n\t\t\t
Anthracene
\n\t\t\t
14.8
\n\t\t\t
11.9
\n\t\t\t
17.2
\n\t\t\t
8.3
\n\t\t\t
22.9
\n\t\t\t
6.4
\n\t\t
\n\t\t
\n\t\t\t
Flouranthene
\n\t\t\t
41.2
\n\t\t\t
121
\n\t\t\t
69.1
\n\t\t\t
31.8
\n\t\t\t
69.8
\n\t\t\t
38.9
\n\t\t
\n\t\t
\n\t\t\t
Pyrene
\n\t\t\t
14.8
\n\t\t\t
69.1
\n\t\t\t
57.5
\n\t\t\t
18.7
\n\t\t\t
43.7
\n\t\t\t
19.6
\n\t\t
\n\t\t
\n\t\t\t
Chrysene
\n\t\t\t
93.4
\n\t\t\t
273
\n\t\t\t
81.4
\n\t\t\t
239
\n\t\t\t
193
\n\t\t\t
192
\n\t\t
\n\t\t
\n\t\t\t
Benzo(a)anthracene
\n\t\t\t
105
\n\t\t\t
115
\n\t\t\t
ND
\n\t\t\t
53.2
\n\t\t\t
50.3
\n\t\t\t
ND
\n\t\t
\n\t\t
\n\t\t\t
Benzo(k)flouranthene
\n\t\t\t
19.8
\n\t\t\t
59.3
\n\t\t\t
25.2
\n\t\t\t
7.1
\n\t\t\t
12.0
\n\t\t\t
9.3
\n\t\t
\n\t\t
\n\t\t\t
Benzo(b)flouranthene
\n\t\t\t
5.8
\n\t\t\t
18.0
\n\t\t\t
4.1
\n\t\t\t
18.5
\n\t\t\t
51.1
\n\t\t\t
49.5
\n\t\t
\n\t\t
\n\t\t\t
Perylene
\n\t\t\t
10.6
\n\t\t\t
30.3
\n\t\t\t
181
\n\t\t\t
ND
\n\t\t\t
641
\n\t\t\t
399
\n\t\t
\n\t\t
\n\t\t\t
Benzo(g,h,i)perylene
\n\t\t\t
ND
\n\t\t\t
12.5
\n\t\t\t
8.5
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t
\n\t\t
\n\t\t\t
Dibenzo(a,h)anthracene
\n\t\t\t
ND
\n\t\t\t
12.6
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t
\n\t\t
\n\t\t\t
Indeno(1,2,3-cd)pyrene
\n\t\t\t
3.6
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
32.0
\n\t\t\t
ND
\n\t\t
\n\t\t
\n\t\t\t
Total PAHs Concentration (µg/kg)
\n\t\t\t
976
\n\t\t\t
1150
\n\t\t\t
790
\n\t\t\t
1400
\n\t\t\t
2220
\n\t\t\t
1750
\n\t\t
\n\t
Table 5.
PAHs concentration (µg/kg) in the soil around the cattle market in Isheri, Nigeria
Figure 4.
Variation in the concentration of PAHs with respect to depth in the soil around the cattle market in Isheri, Nigeria
Comparing the values obtained in this study with background soil concentrations of PAHs (Table 5) [91], the concentrations obtained in this study was higher than the concentrations in rural and agricultural soils in most cases except benzo(g,h,i) perylene and indeno(1,2,3-cd)pyrene. There is a significant and positive correlation between phenanthrene versus flourene and perylene; flouranthene versus pyrene, benzo(k)flouranthene, dibenzo(a,h)anthracene and benzo(g,h,i)perylene; and benzo(k) flouranthene versus benzo(g,h,i)perylene and dibenzo(a,h)anthracene.
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t\tCompounds\n\t\t\t
\n\t\t\t
\n\t\t\t\tConcentrations (x 10-3 mg/kg)\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t
\n\t\t\t\tRural Soil\n\t\t\t
\n\t\t\t
\n\t\t\t\tAgricultural Soil\n\t\t\t
\n\t\t\t
\n\t\t\t\tUrban Soil\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
Acenaphthene
\n\t\t\t
1.7
\n\t\t\t
6
\n\t\t\t
NE
\n\t\t
\n\t\t
\n\t\t\t
Acenaphthylene
\n\t\t\t
NE
\n\t\t\t
5
\n\t\t\t
NE
\n\t\t
\n\t\t
\n\t\t\t
Anthracene
\n\t\t\t
NE
\n\t\t\t
11-13
\n\t\t\t
NE
\n\t\t
\n\t\t
\n\t\t\t
Benzo(a)anthracene
\n\t\t\t
5-20
\n\t\t\t
56-110
\n\t\t\t
169-59,000
\n\t\t
\n\t\t
\n\t\t\t
Benzo(a)pyrene
\n\t\t\t
2-1,300
\n\t\t\t
4.6-900
\n\t\t\t
165-220
\n\t\t
\n\t\t
\n\t\t\t
Benzo(b)fluoranthene
\n\t\t\t
20-30
\n\t\t\t
58-220
\n\t\t\t
15,000-62,000
\n\t\t
\n\t\t
\n\t\t\t
Benzo(c)perylene
\n\t\t\t
NE
\n\t\t\t
53-130
\n\t\t\t
60-14,000
\n\t\t
\n\t\t
\n\t\t\t
Benzo(g,h,i)perylene
\n\t\t\t
10-70
\n\t\t\t
66
\n\t\t\t
900-47,000
\n\t\t
\n\t\t
\n\t\t\t
Benzo(k)fluoranthene
\n\t\t\t
10-110
\n\t\t\t
58-250
\n\t\t\t
300-26,000
\n\t\t
\n\t\t
\n\t\t\t
Chrysene
\n\t\t\t
38.3
\n\t\t\t
78-120
\n\t\t\t
251-640
\n\t\t
\n\t\t
\n\t\t\t
Fluoranthene
\n\t\t\t
0.3-40
\n\t\t\t
120-210
\n\t\t\t
200-166,000
\n\t\t
\n\t\t
\n\t\t\t
Fluorine
\n\t\t\t
NE
\n\t\t\t
9.7
\n\t\t\t
NE
\n\t\t
\n\t\t
\n\t\t\t
Indeno(1,2,3-cd)pyrene
\n\t\t\t
10-15
\n\t\t\t
63-100
\n\t\t\t
8,000-61,000
\n\t\t
\n\t\t
\n\t\t\t
Phenanthrene
\n\t\t\t
30.0
\n\t\t\t
48-140
\n\t\t\t
NE
\n\t\t
\n\t\t
\n\t\t\t
Pyrene
\n\t\t\t
1-19.7
\n\t\t\t
99-150
\n\t\t\t
145-147,000
\n\t\t
\n\t
Table 6.
Background soil concentrations of PAHs
Note: NE-Not established
3.6. Organochlorine pesticides
There is variation in the concentrations of the organochlorine pesticides (OCP) in the soil samples collected around the cattle market (Table 6). The major OCP residue identified in the area with their percentage concentrations were p,p\'-DDT, 344 µg/kg (24.5%), δ-BHC, 290 µg/kg (20.7%), Endosulfan sulphate, 186 µg/kg (13.2%), lindane (γ-BHC), 129 µg/kg (9.1%), Endrin, 110 µg/kg (7.8%), Aldrin, 93.9µg/kg (6.7%), Dieldrin, 93.8 µg/kg (6.7%), o,p-DDE, 45.0 µg/kg (3.2%), β-BHC, 42.1 µg/kg (3.0%), Endosulfan II, 34.5 µg/kg (2.5%), and Heptachlor, 22.8 µg/kg (1.6%). The variation in the concentrations of the organochlorine pesticides with respect to depth around the cattle market is presented in Figure 4. Dieldrin, a metabolite of aldrin is present at higher concentration in most of the sampling points when compared to the parent aldrin. The presence of o,p’ DDE revealed that there is historical use as well as recent us of the parent DDT in the vicinity of the cattle market. Though, DDT has been banned for over 20 years, it’s presence around the cattle market indicate that it is illegally imported into the country as it is not produced in Nigeria. Also, lindane, one of the nine new POPs was found at high concentration around the market. The presence of some of the banned chemical residue around the cattle market revealed that there is weak regulation and low enforcement on banned chemicals in the country.
In most cases, the concentrations of organochlorine pesticides is highest at the sampling point C which could be attributed to the use of pesticides to control household pests and insects in the area; as the area is a slum with most houses built of planks, rust iron sheets and polypropylene material and a dumpsite at the bank of the river. There is very strong and significant correlation at the 0.01 levels (2-tailed) between DDT versus δ-BHC, heptachlor, aldrin and dieldrin; dieldrin versus δ-BHC, heptachlor and aldrin; aldrin versus heptachlor as well as endrin versus δ-BHC.
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t
\n\t\t\t\tSampling area A\n\t\t\t
\n\t\t\t
\n\t\t\t\tSampling area B\n\t\t\t
\n\t\t\t
\n\t\t\t\tSampling area C\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
\n\t\t\t
\n\t\t\t\tA1S1\n\t\t\t\t\n\t\t\t
\n\t\t\t
\n\t\t\t\tA2S2\n\t\t\t\t\n\t\t\t
\n\t\t\t
\n\t\t\t\tB1S1\n\t\t\t\t\n\t\t\t
\n\t\t\t
\n\t\t\t\tB2S2\n\t\t\t\t\n\t\t\t
\n\t\t\t
\n\t\t\t\tC1S1\n\t\t\t\t\n\t\t\t
\n\t\t\t
\n\t\t\t\tC2S2\n\t\t\t\t\n\t\t\t
\n\t\t
\n\t\t
\n\t\t\t
Organochlorine Pesticide
\n\t\t\t
(0-15cm)
\n\t\t\t
(15-30cm)
\n\t\t\t
(0-15cm)
\n\t\t\t
(15-30cm)
\n\t\t\t
(0-15cm)
\n\t\t\t
(15-30cm)
\n\t\t
\n\t\t
\n\t\t\t
α-BHC
\n\t\t\t
13.2
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t
\n\t\t
\n\t\t\t
β-BHC
\n\t\t\t
34.5
\n\t\t\t
7.6
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t
\n\t\t
\n\t\t\t
Lindane
\n\t\t\t
108.5
\n\t\t\t
12.0
\n\t\t\t
7.5
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t
\n\t\t
\n\t\t\t
δ-BHC
\n\t\t\t
47.4
\n\t\t\t
ND
\n\t\t\t
53.7
\n\t\t\t
60.8
\n\t\t\t
64.4
\n\t\t\t
63.5
\n\t\t
\n\t\t
\n\t\t\t
Heptachlor
\n\t\t\t
3.3
\n\t\t\t
ND
\n\t\t\t
3.7
\n\t\t\t
5.3
\n\t\t\t
6.0
\n\t\t\t
4.5
\n\t\t
\n\t\t
\n\t\t\t
Aldrin
\n\t\t\t
13.6
\n\t\t\t
ND
\n\t\t\t
14.2
\n\t\t\t
16.4
\n\t\t\t
34
\n\t\t\t
14.7
\n\t\t
\n\t\t
\n\t\t\t
Heptachlor-epoxide
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t
\n\t\t
\n\t\t\t
cis-Chlordane
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t
\n\t\t
\n\t\t\t
Endosulfan I
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t
\n\t\t
\n\t\t\t
trans-Chlordane
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t
\n\t\t
\n\t\t\t
DDE
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
14.0
\n\t\t\t
14.3
\n\t\t\t
16.7
\n\t\t\t
ND
\n\t\t
\n\t\t
\n\t\t\t
Dieldrin
\n\t\t\t
15.2
\n\t\t\t
ND
\n\t\t\t
15.1
\n\t\t\t
16.4
\n\t\t\t
22.2
\n\t\t\t
24.9
\n\t\t
\n\t\t
\n\t\t\t
Endrin
\n\t\t\t
23.4
\n\t\t\t
ND
\n\t\t\t
28.0
\n\t\t\t
23.7
\n\t\t\t
13.5
\n\t\t\t
20.9
\n\t\t
\n\t\t
\n\t\t\t
Endosulfan II
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
15.8
\n\t\t\t
18.7
\n\t\t
\n\t\t
\n\t\t\t
Endosulfan sulphate
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
186
\n\t\t\t
ND
\n\t\t
\n\t\t
\n\t\t\t
p,p\' DDT
\n\t\t\t
45.6
\n\t\t\t
ND
\n\t\t\t
59.4
\n\t\t\t
66.0
\n\t\t\t
97.8
\n\t\t\t
75.2
\n\t\t
\n\t\t
\n\t\t\t
Methoxychlor
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t\t
ND
\n\t\t
\n\t\t
\n\t\t\t
Total organochlorine pesticides concentration (µg/kg)
\n\t\t\t
305
\n\t\t\t
19.6
\n\t\t\t
196
\n\t\t\t
203
\n\t\t\t
456
\n\t\t\t
222
\n\t\t
\n\t
Table 7.
Organochlorine pesticides concentrations (µg/kg) in the soil around the cattle market in Isheri, Nigeria
Figure 5.
Variation in organochlorine pesticides residue concentrations with respect to depth in the soil around the cattle market in Isheri, Nigeria
4. Conclusion
In this study, the distribution, concentration and profiles of some ubiquitous environmental pollutants such as heavy metals (Pb, Ni, Cu, Cr, Zn and Cd), polycyclic aromatic hydrocarbons (PAHs) and organochlorine pesticides in soil of a cattle market around River Ogun Basin, Isheri, Nigeria were assessed as well as some soil physico-chemical characteristics. The pH of the top soil was observed to be lower than the corresponding subsoil in most of the areas sampled except the areas downstream of the river. The pH of the topsoil being lower than the subsoil may be responsible for the high metal concentrations in the subsoil. Low pH of top soil means more heavy metals will be dissolved in top soil and the texture of the soil being sandy and loose also might favour the migration/leaching of heavy metals to lower fractions. The solubilising heavy metals in the top soil may be migrating into the subsoil, except in cadmium, which was concentrated in the top soil. The soil of the entire sample area was sandy loamy soil with low concentration of organic matter. The cattle wastes released in the area might have relatively increased the organic matter content of the soil. Though, the topography of the area and the location of the cattle market, being sloppy and close to the river basin favoured the washing away of the top soil by run-off into the river and this might be responsible for the high organic matter in the subsoil. The pH of the soil of the area was slightly acidic to neutral. The soil sample with high organic matter content has high metal concentrations in most cases except Cd, Pb, Cu and Cr. Generally, there is positive and significant correlation between the organic matter content versus Pb, Zn, Cu, Ni and Cr. There is variation in the concentrations of PAHs and organochlorine pesticides residues with depth around the river basin. The detection of banned organochlorine pesticides in the soil of the area could be attributed to both the historical use as well as recent use of these chemicals in the area. Thus, there is need for stricter regulations on banned chemicals to safe our environment from ubiquitous and persistent environmental pollutants.
\n',keywords:null,chapterPDFUrl:"https://cdn.intechopen.com/pdfs/46340.pdf",chapterXML:"https://mts.intechopen.com/source/xml/46340.xml",downloadPdfUrl:"/chapter/pdf-download/46340",previewPdfUrl:"/chapter/pdf-preview/46340",totalDownloads:1929,totalViews:473,totalCrossrefCites:4,totalDimensionsCites:6,hasAltmetrics:1,dateSubmitted:"September 20th 2013",dateReviewed:"December 28th 2013",datePrePublished:null,datePublished:"March 26th 2014",readingETA:"0",abstract:null,reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/46340",risUrl:"/chapter/ris/46340",book:{slug:"environmental-risk-assessment-of-soil-contamination"},signatures:"A.A. Adeyi, O.M. Omidiran and O. Osibanjo",authors:[{id:"51675",title:"Dr.",name:"Adebola",middleName:"Abosede",surname:"Adeyi",fullName:"Adebola Adeyi",slug:"adebola-adeyi",email:"bolaoketola@yahoo.com",position:null,institution:null},{id:"58376",title:"Prof.",name:"Oladele",middleName:null,surname:"Osibanjo",fullName:"Oladele Osibanjo",slug:"oladele-osibanjo",email:"oosibanjo@yahoo.com",position:null,institution:{name:"University of Ibadan",institutionURL:null,country:{name:"Nigeria"}}},{id:"169944",title:"Dr.",name:"Oludele Michael",middleName:"Michael",surname:"Omidiran",fullName:"Oludele Michael Omidiran",slug:"oludele-michael-omidiran",email:"deomidiran@yahoo.com",position:null,institution:null}],sections:[{id:"sec_1",title:"1. Introduction ",level:"1"},{id:"sec_1_2",title:"1.1. Health and environmental effects of heavy metals",level:"2"},{id:"sec_2_2",title:"1.2. Health and environmental effects of some common Persistent Organic Pollutants (POPs)",level:"2"},{id:"sec_3_2",title:"1.3. Health and environmental effects of Polycyclic Aromatic Hydrocarbons (PAHs)",level:"2"},{id:"sec_4_2",title:"1.4. Soil contamination by cattle wastes",level:"2"},{id:"sec_6",title:"2. Experimental ",level:"1"},{id:"sec_6_2",title:"2.1. General description of ogun river basin",level:"2"},{id:"sec_7_2",title:"2.2. Sampling design ",level:"2"},{id:"sec_8_2",title:"2.3. Sample collection, treatment and preservation",level:"2"},{id:"sec_9_2",title:"2.4. Analytical procedure",level:"2"},{id:"sec_9_3",title:"2.4.1. Determination of soil pH",level:"3"},{id:"sec_10_3",title:"2.4.2. Determination of soil organic matter ",level:"3"},{id:"sec_11_3",title:"2.4.3. Determination of soil particle size by the Bouyoucos hydrometer method",level:"3"},{id:"sec_12_3",title:"2.4.4. Metal analysis",level:"3"},{id:"sec_14_2",title:"2.5. Organochlorine pesticides and PAHs analysis",level:"2"},{id:"sec_14_3",title:"2.5.1. Soil sample extraction",level:"3"},{id:"sec_15_3",title:"2.5.2. Column packing for fractionation and clean-up of extract",level:"3"},{id:"sec_16_3",title:"Table 1.",level:"3"},{id:"sec_19",title:"3. Results and discussion",level:"1"},{id:"sec_19_2",title:"3.1. Soil pH",level:"2"},{id:"sec_20_2",title:"3.2. Soil Organic Matter",level:"2"},{id:"sec_21_2",title:"3.3. Particle size distribution (soil texture)",level:"2"},{id:"sec_22_2",title:"3.4. Concentration of heavy metals in soil",level:"2"},{id:"sec_23_2",title:"3.5. Concentration of Polynuclear Aromatic Hydrocarbons (PAHs) ",level:"2"},{id:"sec_24_2",title:"3.6. Organochlorine pesticides ",level:"2"},{id:"sec_26",title:"4. Conclusion ",level:"1"}],chapterReferences:[{id:"B1",body:'Oketola AA, Fagbemigun KT. Determination of Nonylphenol, Octylphenol and Bisphenol-A in Water and Sediments of Two Major Rivers in Lagos, Nigeria. Journal of Environmental Protection 2013;4(7A) 38-45. '},{id:"B2",body:'Ogundiran MB, Osibanjo O. 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Journal of Toxicology and Environmental Health Part A 1999;58 (8)509–530.'},{id:"B56",body:'Decker GC, Bruce WN, Bigger JH. The Accumulation and Dissipation of Residues Resulting from the Use of Aldrin in Soils. Journal of Economic Entomology 1965;58(2) 266-271.'},{id:"B57",body:'Elgar KR. Analysis of Crops and Soils for Residues of the Soil Insecticides Aldrin and Telodrin. Journal of the Science of Food and Agriculture 1966;17(12) 541-545.'},{id:"B58",body:'Lichtenstein EP. Persistence and Behaviour of Insecticidal Residues in Soils and their Translocation into Crops. Archives of Environmental Health 1965; 10(6) 825-826.'},{id:"B59",body:'Edwards CA. Insecticide Residues in Soils. Residue Review 1966; 13 83-132.'},{id:"B60",body:'New Zealand Food Safety Authority. Endosulfan. Wellington, New Zealand. http://www.nzfsa.govt.nz/consumers/chemicals-nutrients-additives-and toxins/endosulfan/index.htm (accessed 25 March 2009).'},{id:"B61",body:'Tsibart AS, Gennadiev AN. Polycyclic Aromatic Hydrocarbons in Soils: Sources, Behavior, and Indication Significance (A Review). Eurasian Soil Science 2013; 46(7) 728-741.'},{id:"B62",body:'Agency for Toxic Substances and Disease Registry (ATSDR) Case Studies in Environmental Medicine. Toxicity of Polycyclic Aromatic Hydrocarbons (PAHs). US Department of Health and Human Services. Public Health Service. 2009.'},{id:"B63",body:'Wallingford GW, Powers WL, Murphy LS. Present knowledge of the effect of land application of animal wastes. 1975 International Symposium on Livestock Waste April 21-24 1975. ASAE, St Joseph, MI.'},{id:"B64",body:'Eck H.V., Stewart B.A. Manure. In: Rechcial J.E. (ed.) Soil Amendment and Environmental Quality. Lewis Publisher, New York: 1995. p169-198.'},{id:"B65",body:'Liang BL, Gregorick EG, Schnitzer M, Schulten HR. Characterization of Water Extracts of Two Manures and their Adsorption on Soils. Soil Science Society of America 1996; 60(6) 1758-1763.'},{id:"B66",body:'Teckon and Associate. Federal Republic of Nigeria, Federal Department of Water Resources. Improvement of River Channels along River Ogun (Lagos Lagoon to Olokemeji). Final Report. 1987. p163.'},{id:"B67",body:'Oketola AA, Adekolurejo SM, Osibanjo O. Water Quality of Rivr Ogun using Multivariate Statistical Techniques. Journal of Environmental Protection 2013; 4(5) 466-478.'},{id:"B68",body:'United State Environmental Protection Agency. Polycyclic aromatic Hydrocarbons (PAHs). Office of Solid Waste, Washinton DC 20460, 2008. '},{id:"B69",body:'Walkey A, Black IA. An Examination of Degtjareff Method for Determining Soil Organic Matter and a Proposed Modification of the Chromic Acid Titration Method. Soil Science 1934; 37(1) 29-38.'},{id:"B70",body:'Brady N.C. 1984. The Nature and Properties of Soils. Macmillan Publishing Co., New York; 1984. 9th ed. p366.'},{id:"B71",body:'Abdul-Saheb I, Schwab AR, Banks MK, Hetrick BA. Chemical Characterization of Heavy-metal Contaminated Soil in Southeast Kansas. Water, Air and Soil Pollution 1994;78(1-2) 73-82.'},{id:"B72",body:'Myung CJ, Thornton I. Heavy Metal Contamination of Soils and Plants in the Vicinity of a Lead-Zinc Mine, Korea. Applied Geochemistry 1996;11(1-2) 53-59.'},{id:"B73",body:'Kennedy JH. Analytical Chemistry: Principles. Sanders Company: United States of America; 1990. 2nd Ed.'},{id:"B74",body:'USEPA Report. Recent Development for In-situ Treatment of Metals Contaminated Soils, U.S. Environmental Protection Agency, Office of Solid Waste and Emergency Response; 1996.'},{id:"B75",body:'Ogundiran MA. Assessment and Chemical Remediation of Soil Contaminated by Lead-Acid Battery Waste in Lalupon, Oyo State, Nigeria. Ph.D thesis. University of Ibadan, Ibadan, Nigeria; 2007.'},{id:"B76",body:'Smejkalova M, Mikanova L, Boruvka L. Effects of Heavy Metal Concentrations on Biological Activity of Soil Microorganisms. Plant Soil Environment 2003; 49(7) 321-326.'},{id:"B77",body:'Onianwa PC, Fakayode SO. Lead Contamination of Topsoil and Vegetation in the Vicinity of a Battery Factory in Nigeria. Environmental Geochemistry and Health 2000; 22(3) 211-218.'},{id:"B78",body:'American Society for Testing and Materials. Methodology for Comparison of Petroleum Oil by Gas Chromatography. ASTM Method D 3328-78, 1982.'},{id:"B79",body:'United State Environmental Protection Agency. Polynuclear Aromatic Hydrocarbons. Washington DC, 1986.'},{id:"B80",body:'Massachusetts Department of Environmental Protection (DEP). Methods for the Determination of Extractable Petroleum Hydrocarbons (EPH). Massachusetts DEP, Wall Experiment Station; 1995.'},{id:"B81",body:'Bolan N.S., Kandaswamy K. pH. In: Daniel Hillel (ed.) Encyclopedia of Soils in the Environment. Elsevier Ltd; 2005. p196-202.'},{id:"B82",body:'Chuan MC, Shu GY, Liu JC. Solubility of Heavy Metals in a Contaminated Soil: Effects of Redox Potential and pH. Water, Air and Soil Pollution 1996;90(3-4) 543-556.'},{id:"B83",body:'Bot A., Benites J. The Importance of Soil Organic Matter. FAO Soil Bulletin; 2005.'},{id:"B84",body:'Schnitzer M. Organic Matter, Principle and Processes. In: Daniel Hillel (ed.) Encyclopedia of Soils in the Environment. Elsevier Ltd: 2005. p86-93.'},{id:"B85",body:'Ward A. The Importance of Particle Size Distributions to the Characterization of Soils. Caribbean Institute for Meteorology and Hydrology; 2012.'},{id:"B86",body:'Hu HC, Tian FQ, Hu HP. Soil Particle Size Distribution and its Relationship with Soil Water and salt under Mulched Drip Irrigation in Xinjiang of China. Science China Technological Sciences 2011;54(6) 1568-1574.'},{id:"B87",body:'Sidle RC, Kardos LT. Van Genuchten M.Th. Transport of Heavy Metals in Sludge-treated Forested Area. Journal of Environmental Quality 1977;6(4) 438-443.'},{id:"B88",body:'Loganathan P, Hedley MJ. Downward movement of Cadmium and Phosphorus from Phosphate Fertilisers in a Pasture Soil in New Zealand. Environmental Pollution 1997; 95(3) 319-324.'},{id:"B89",body:'Behbahaninia A, Mirbagheri AS, Javid AHT. Heavy Metals Transport in the Soil Profiles under the Application of Sludge and Wastewater. World Academy of Science, Engineering and Technology 2008;9 53-55.'},{id:"B90",body:'Bowen HJM. Environmental Chemistry of the Elements. Academic Press, London. 1979.'},{id:"B91",body:'Jones KC, Stratford JA, Waterhouse k. Polynuclear Aromatic Hydrocarbons in U.K Soils: Long Term Temporal Trends and Current Levels. Trace Subst. Environmental Health 1987 2: 140-148.'}],footnotes:[],contributors:[{corresp:null,contributorFullName:"A.A. Adeyi",address:null,affiliation:'
Analytical and Environmental Chemistry Unit, Department of Chemistry, University of Ibadan, Ibadan, Nigeria
Analytical and Environmental Chemistry Unit, Department of Chemistry, University of Ibadan, Ibadan, Nigeria
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1. Introduction
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Climate change is a debatable subject these days. Dealing with this topic is considered an enormous challenge of the coming years [1]. There are many definitions of climate; however, the common term of climate is the long-term pattern of meteorological conditions in a specific area [2]. It is measured by evaluating variations in temperature, humidity, atmospheric pressure, wind, precipitation, atmospheric particle, and other meteorological variables. Climate change can have significant impacts on weather conditions around the world, such as storms and heavy rainfall. Climate changes can occur due to different processes internal to the earth, external forces (e.g., variations in sunlight intensity), and human activities that have been increasing recently. Many shreds of strong evidence in many regions regarding the climate changes and variability that is impacted by anthropogenic activities, industries and natural specifications of climate systems are recently available. Among these factors that caused climate change due to changing of the composition of the atmosphere are the greenhouse gas emissions, CO2, CH4, and N2O [3, 4, 5].
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Many studies related to climate change have emphasized that there is an increase in the rainfall events recently regarding frequency and intensity [6, 7, 8, 9, 10, 11, 12, 13, 14]. Rainfall patterns and rate over a region are reliant on the ambient and global water evaporation and to a significant extent on altitude, latitude, and level of humidity [15]. Warmer conditions brought out from increased emissions of greenhouse gases through industrialization cause evaporation and precipitation with varying degree of intensity on individual regions [16].
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Various environmental impacts have been witnessed according to climate change including change in the hydrological cycles, availability of water resources, unprecedented rainfalls and floods, unexpected drought frequencies, and changes in natural ecosystems [5, 14, 17, 18, 19, 20]. Rain is an essential natural phenomenon which can influence the human life and properties. There are many factors which affect rainfall, such as geographical position, monsoon, topographic, and other factors. Flash flood frequency and severity in the desert areas are generally unpredictable and vary from year to year due to variability in the rainfall values [21, 22, 23]. Rainfall in arid areas is spatially variable than that of humid regions and is often described as “spotty,” and the impacted area is often limited by the radius of the clouds [24].
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It is tough for hydrologists to use unreliable hydrological data (rainfall data) in the design of water-related structures. In most cases, the available rainfall data are limited (few records) and contain some gaps in the time series; rainfall stations are far from each other, with no intensity records; and records are not authentic values due to human errors. Previous studies used historical information to carry out the rainfall frequency analysis to understand the flooding behavior [25, 26]. These studies generally show that the use of historical information can be of great value in the reduction of the uncertainty in flood quantity estimators. A frequency analysis of the data is the most commonly applied method. Several studies were found dealing with the analysis of rainfall intensity in many areas [27, 28, 29, 30, 31, 32].
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A rain gauge is an instrument that measures how much rain falls in a given set time. Automatic rain gauges are rain gauges that electronically start working once it feels rain on the gauge. They automatically record the data, from measuring to removing the rainfall afterward [33]. Automatic rain gauge systems are required to collect rainfall data at remote locations, especially oceanic sites where logistics prevent regular visits [34]. It is usually based on tipping-bucket rainfall sensor and data logger for measuring the rainfall quantity and intensity during a given period and transmits the data through the GSM/GPRS modem to the desired e-mails and server at user-defined time intervals, and records obtained are of high reliability.
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The Kingdom of Saudi Arabia (KSA) is one of the other countries that is impacted by severe events of rainfall in the last decade due to climate change. The intensity and frequency of the rainfalls are unprecedented and cause devastating floods in many KSA regions. Due to the lack of short-duration data in the Kingdom in general and in Jeddah in particular, and the limited number of studies that have determined the pattern of rainstorms, the current research will be a cornerstone in establishing rainfall pattern and behaviors. Determination of rainstorm pattern and method of distribution is one of the most critical factors affecting peak flow calculations. In this work, the Jeddah area was chosen as a unique example of unprecedented rainfall events in the last decade. The rainfall rate and patterns of the Jeddah area will be discussed in detail to extract the adequate rainfall intensity patterns that could be used for future predictions. In the current study, the short duration rainfall data recorded by climate stations of the Saudi Geological Survey during the period from 2011 to 2017, as well as the data available at station J134 of the Ministry of Environment, Water and Agriculture, And the conclusion of the general pattern prevailing in these storms, as well as their comparison with the distribution of SCS-Type II, and the conclusion of the intensity curves based on available data. Many rainfall storms were analyzed in this study. It includes the following events (intensity records) 2011, 2014, 2015, 2016 and 2017. However, in the devastating floods that occur in 2009, we do not have intensity records for that event.
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2. Rainfall distribution in the KSA and recent problems
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The KSA climate is mainly arid and semiarid, except in the northern and southern areas. The arid and semiarid regions have an extreme continental climate with warm and dry summer and very cold winter especially in the central regions of the KSA. To assess rainfall pattern over the study area, it is necessary to define the dominant climatic patterns that have an influence on rainfall distribution over the western province of the KSA. The climatic pattern can best be described by considering the various air masses that affect the rainfall distribution over the KSA area. The influence of the different air masses and the rainfall patterns over the KSA has been discussed and mapped by several investigators [35, 36, 37, 38].
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Different air masses, which influence the Kingdom’s climate, are illustrated in Figure 1. These air masses include (1) the monsoon front during the late autumn (maritime tropical air mass) reaches the area from the south, southwest, and southeast. This front that originates in the Indian Ocean and the Arabian Sea during the autumn brings warm and moist air. Outbreaks of westerly air become more frequent, characterized by medium to high intensity over the western and northwesterly regions of the country. This front often picks up further moisture while moving through the Red Sea Trough. (2) The continental tropical air masses are warm and moist coming from the Atlantic Ocean through the Central and North African continent. (3) The maritime polar air masses are derived from the Eastern Mediterranean Sea. In early winter the Mediterranean-borne maritime air increasingly disturbs the monsoonal air movement and displaces it in the low altitudes. These maritime depressions draw the tropical continental air masses into the warm sectors, and extreme weather conditions occur that are associated with the passage of a hot sector. Both (2) and (3) move toward the east and prevail in the winter season. During this season, the western region, particularly the coastal area, is characterized by its relatively low rate of rainfall [38], whereas, due to the topographic effects, the highlands receive a considerable amount of rainfall. In spring, the impact of the Mediterranean air movement diminishes, whereas the monsoon from the south takes its place, penetrating the southern part of the Kingdom. During summer, the cyclonic flow sweeps along the Mediterranean Sea from the west toward the east and continues moving over the northern and central regions of the country preventing the maritime air masses of the northeasterly monsoon from penetrating the north regions of the Kingdom. Due to this, the summer season will be somewhat dry in the area considered.
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Figure 1.
Air masses affecting the climate of the KSA: (1) maritime tropical air masses, (2) continental tropical air masses, and (3) maritime polar air masses [39].
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The mean annual rainfall (from 1960 to 2018) over the KSA can be shown in Figure 2. The rainfall rate in the KSA (except for the Empty Quarter desert) is 109 mm per year. The southwestern region is characterized by a heavy rainfall compared with the rest of the Kingdom. Rainfall is more than 500 mm per year in some locations. The peaks of the Sarawat Mountains, which extend from the northern part of the Kingdom to the south, parallel to the Red Sea, are the dividing line for the distribution of surface water. The rains that fall in the east of this line take place in the valleys heading east, and in the west, the valleys are steep and flowing towards the Red Sea.
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Figure 2.
Average annual rainfall values for 270 rainfall stations distributed across the KSA area (from 1960 to 2018).
\n
Recently, there is a definite increasing trend in rainfall in frequency and intensity in the KSA. Many areas in the KSA have shown an increasing trend in the annual rainfall and flood events. Most of the rainfall in the KSA occurs during the monsoon. Monsoon is a term derived from the Arabic word “mausim,” meaning season. It was used to describe the seasonal winds of the Arabian Sea. The Jeddah area is characterized by wet and dry seasons that generally occur from November to May and from June to October, respectively. One example is Jeddah city which has shown an increasing trend in the rainfall events. These events cause disasters that result in human, property, and economic loss. These unprecedented events have affected the KSA, causing considerable damage to highways, railroads, urban zones, and agricultural areas [39]. Most of the flash flood hazards in the KSA are caused by a combination of natural conditions (heavy rainfall and climate changes) and human interference (poor drainage systems and urban expansion). Recently, heavy rainfall events have triggered flash floods in various areas of the KSA (e.g., Jeddah city flash floods in the years 2009, 2011, 2015, 2017, and 2018 and Al Riyadh flash floods in 2015 and 2018). The severely hit areas are generally in the western part of the KSA, particularly in the city of Jeddah during November 2009 and January 2011 [39, 40]. These events were characterized by 70 and 111 mm of rainfall, respectively, within 3 h and were considered catastrophic flash floods for Jeddah city. They caused a death toll of 113 people in 2009, and, together, they damaged more than 10,000 homes and destroyed approximately 17,000 vehicles. Other areas impacted by flash floods are As Sail Al Kabir area, Taef; Najran city; Ar Riyadh city; Ha’il city; Makkah city; and Tabuk city [41, 42, 43, 44, 45, 46, 47, 48].
\n
\n
\n
3. Study area and its characteristics
\n
The study area, the Jeddah area, is located in the western region of the KSA covering an area of ~1731 km2 and lies between latitudes 21°15′ and 21°57′N and longitudes 39°06′ and 39°31′E (Figure 3). From the latitude point of view, the Jeddah area is considered to be in the arid zone (Köppen’s climate classification). The Jeddah area has different geomorphological features. It represents a part of the Red Sea coastal zone. Jeddah drainage system comes from the east (a series of hills) toward the city which is located to the west. The catchment areas have a variety of landforms such as low- and midsize hills and flattened foothills in some places followed to the west by the floodplain areas. The monthly average relative humidity ranges between ~85% from September to October and ~34% from April to June. The Jeddah area is characterized by scarce rainfalls with high variability, which occur most often in November–December–January (the winter season). Additionally, monsoonal rainstorms take place in March and April due to the moist air currents from the Indian Ocean and the Arabian Sea. The average annual precipitation is ~52.5 mm/year. The maximum rainfall was recorded in 1996, with ~284 mm/year. Recently these thunderstorms increased in their frequencies and intensities causing flash floods and inundation events within Jeddah city.
\n
Figure 3.
Study area and its meteorology station locations.
\n
\n
\n
4. Characteristics
\n
In this study, all the current stations have automatic rain gauges that can record the intensity of the rainfall events (minute-base). This technique did not occur before, and most of the hydrological studies were depending on the daily rainfall data analysis which brings some uncertainty to the hydrological results. The stations used in the current study are shown in Figure 3. In the present work, trend and pattern analysis is based on intensity rainfall values for each rainfall station. Detailed analysis and discussion of the different recently occurred storms will be carried out in the following sections. This analysis and comparison work will give us the ability to deduce the general pattern prevailing in the storms in the city of Jeddah. Table 1 has a list of different storms that will be considered in this study.
\n
\n
\n
\n
\n
\n
\n
\n\n
\n
No.
\n
Date
\n
Location
\n
Name
\n
Total rainfall (mm)
\n
Duration (h)
\n
\n\n\n
\n
1
\n
January 26, 2011
\n
SGS site
\n
SGS
\n
112.0
\n
4.7
\n
\n
\n
2
\n
November 22, 2014
\n
SGS site
\n
SGS
\n
43.0
\n
10.0
\n
\n
\n
3
\n
November 17, 2015
\n
Radwa farms
\n
Radwa
\n
21.7
\n
2.7
\n
\n
\n
4
\n
November 17, 2015
\n
Khulays, Ad Daff
\n
Khulays
\n
20.6
\n
2.7
\n
\n
\n
5
\n
November 17, 2015
\n
Old Jeddah airport
\n
J134
\n
79.0
\n
3.2
\n
\n
\n
6
\n
November 17, 2015
\n
Wadi Qaws
\n
Qaws
\n
61.0
\n
1.77
\n
\n
\n
7
\n
December 02, 2016
\n
SGS site
\n
SGS
\n
44.91
\n
2.75
\n
\n
\n
8
\n
November 21, 2017
\n
SGS site
\n
SGS
\n
88.04
\n
15.75
\n
\n\n
Table 1.
Rainstorms occurred between 2011 and 2017 in the Jeddah area and the stations’ names.
\n
\n
4.1 Rainstorm occurred on January 26, 2011
\n
The data recorded by the rainfall station located at the headquarter of the Saudi Geological Survey shows that the precipitation began at 10:56 am on Saturday, January 26, 2011; continued until 12:27 noon, for ~91 min; and remained after a short break until 3:38 pm. The total precipitation is ~112.0 mm. It is difficult to distinguish two separate storms, but this rainstorm can be separated into two phases. The first phase of rainfall was ~54 mm, while the second one was ~58 mm. Figure 4a shows the rainfall recorded plotted against the whole rainfall time (4.7 h), which shows ~48% of the rainfall depth is fallen in the first phase for a period of ~78 min. The first phase is shown in Figure 4b.
\n
Figure 4.
The rainstorm on January 26, 2011, at SGS station. (a) Distribution of cumulative rainfall intensity of the total storm. (b) Distribution of cumulative rainfall intensity of the first phase.
\n
\n
\n
4.2 Rainstorm occurred on November 22, 2014
\n
This event was recorded in one rainfall station located at the headquarter of the Saudi Geological Survey. The data recorded by this station shows that the precipitation began at 0:22 am on Saturday, November 22, 2014; continued until 1:03 am, for ~41 min; then resumed at 9:53; and stayed until 10:19 am. The total precipitation is ~42.87 mm. This rainstorm can be separated into two storms. The rainfall of the first storm was ~33 mm, while the second one was ~9.61 mm. Figure 5a shows the rainfall recorded plotted against the whole rainfall time (10 h), which shows ~77% of the rainfall depth is fallen in the first storm for a period of ~41 min. The first storm is shown in Figure 5b.
\n
Figure 5.
The rainstorm on November 22, 2014, at SGS station. (a) Distribution of cumulative rainfall intensity of the total storm. (b) Distribution of cumulative rainfall intensity of the first storm.
\n
\n
\n
4.3 Rainstorm occurred on November 17, 2015
\n
This event was recorded in four rainfall stations including Radwa farms, Wadi Khulays, Station J134, and Wadi Qaws.
\n
The data recorded by the rainfall station at Radwa farms shows that the precipitation began with a slow rate at 8:44 am on Tuesday, November 17, 2015; continued until 9:51 am, for ~67 min; and remained with a moderate rate until 11:25 am of the same day. The total precipitation is ~21.7 mm. The main storm in this event lasted ~41 min and reached a precipitation amount of ~19 mm. Figure 6a1 shows the rainfall recorded plotted against the whole rainfall time (2.7 h), which shows ~88% of the rainfall depth is fallen at a period of ~41 min (the main storm; see Figure 6a2).
\n
Figure 6.
The rainstorm on November 17, 2015, at Radwa, Khulays, J134, and Qaws stations. (a1, b1, c1, d1) Distribution of cumulative rainfall intensity of the total storm. (a2, b2, c2, d2) Distribution of cumulative rainfall intensity of the first storm.
\n
The data recorded by the rainfall station at Wadi Khulays shows that the precipitation began at 9:18 am on Tuesday, November 17, 2015; continued until 9:45 am, for ~27 min; and continued intermittently until 12:00 noon. The total precipitation is ~20.6 mm. The main storm in this station lasted ~27 min and reached a precipitation amount of ~18 mm. Figure 6b1 shows the rainfall recorded plotted against the whole rainfall time (2.7 h), which shows ~87% of the rainfall depth is fallen at a period of ~27 min. The first storm is shown in Figure 6b2.
\n
The data recorded by rainfall station J134 (located in the old Jeddah airport) shows that the precipitation began at 10:00 am on Tuesday, November 17, 2015; continued until 12:20 am, for ~140 min; and continued intermittently until 1:10 pm. The total precipitation is ~79.0 mm. The main storm in this station lasted ~140 min and reached a precipitation amount of ~60 mm. Figure 6c1 shows the rainfall recorded plotted against the whole rainfall time (3.2 h), which shows ~76% of the rainfall depth is fallen at a period of ~140 min. The first storm is shown in Figure 6c2.
\n
The data recorded by the rainfall station at Wadi Qaws shows that the precipitation began at 10:48 am on Tuesday, November 17, 2015; continued until 11:41 am, for ~53 min; halted at 12:09; and then continued intermittently until 12:34 pm. The total precipitation is ~61.0 mm. The main storm in this station lasted ~53 min and reached a precipitation amount of ~58.7 mm. Figure 6d1 shows the rainfall recorded plotted against the whole rainfall time (1.8 h), which shows ~96% of the rainfall depth is fallen at a period of ~53 min. The first storm is shown in Figure 6d2.
\n
\n
\n
4.4 Rainstorm occurred on December 2, 2016
\n
This event was recorded in one rainfall station located at the headquarters of the Saudi Geological Survey. The data recorded by this station shows that the precipitation began at 7:18 am on Friday, December 2, 2016 and continued until 7:38 am, for ~20 min; then it resumed at 8:11 and stayed until 8:43 am, followed by a precipitation of 0.25 mm at 10.03 am. The total rainfall is ~44.91 mm. This rainstorm can be separated into two storms. The rainfall of the first storm was ~12.43 mm, while the second one was ~31.47 mm. Figure 7a shows the rainfall recorded plotted against the whole rainfall time (2.75 h), which shows ~28% of the rainfall depth is fallen in the first storm for a period of ~20 min and the second storm which lasted 43 min shows 70% of the total rainfall depth. Figure 7b shows the main storm which lasted 43 min (the second storm).
\n
Figure 7.
The rainstorm on December 2, 2016 at SGS station. (a) Distribution of cumulative rainfall intensity of the total storm. (b) Distribution of cumulative rainfall intensity of the second storm.
\n
\n
\n
4.5 Rainstorm occurred on November 21, 2017
\n
This event was recorded in one rainfall station located at the headquarters of the Saudi Geological Survey. The data recorded by this station shows that the precipitation began at 8:19 am on Tuesday, November 21, 2017; continued until 10:50 am, for ~152 min; then resumed at 11:30 pm; and continued until 12:01 night. The total precipitation is ~88.04 mm. This rainstorm can be separated into two storms. The rainfall of the first storm was ~76 mm, while the second one was ~12.0 mm. Figure 8a shows the rainfall recorded plotted against the whole rainfall time (15.75 h), which shows ~85% of the rainfall depth is fallen in the first storm for a period of ~152 min. The first storm is shown in Figure 8b.
\n
Figure 8.
The rainstorm on November 21, 2017, at SGS station. (a) Distribution of cumulative rainfall intensity of the total storm. (b) Distribution of cumulative rainfall intensity of the first storm.
\n
\n
\n
\n
5. Comparison of different storms
\n
In the current work, a comparison between the storms which occurred in the Jeddah area during the period (2011–2017) was carried out. The results indicated that there is some similarity in the behavior of these storms. The presence of the two main storms characterizes most of them during the rainfall time which is usually separated by a period of partial cessation. The most substantial amount of rainfall always exceeding 70% of the recorded rainfall appears in the first storm. Also, it was found that there is one exception in this rule which seems in the storm recorded on January 26, 2011, at the Saudi Geological Survey Station, which is different from other storms in terms of the amount of precipitation where the rain value reached 112 mm. Figure 9a shows a comparison of the major storms that have been occurred in the Jeddah area. Figure 9b shows comparison between storms which exceeded a rain value (50 mm). The results also indicated that based on the rainstorm that hit the city of Jeddah on November 21, 2017, with the storms that had a definite impact in the Jeddah city, we find that all these storms exceeded the amount of rainfall 50 mm during the first 100 min (Table 2).
\n
Figure 9.
A comparison between different rainstorms occurred in the period between 2011 and 2017: (a) all storms and (b) storms recorded rainfall more than 50 mm (the first 100 min).
\n
\n
\n
\n
\n
\n
\n
\n\n
\n
Source
\n
Return period
\n
\n
\n
5
\n
10
\n
25
\n
50
\n
100
\n
\n\n\n
\n
SGS 2016 (mm)
\n
53.1
\n
71.1
\n
93.4
\n
110.0
\n
125.0
\n
\n
\n
AECOM 2011 (mm)
\n
57.6
\n
75.6
\n
98.4
\n
115.0
\n
132.0
\n
\n
\n
Average (mm)
\n
55.4
\n
73.4
\n
95.9
\n
112.5
\n
128.5
\n
\n\n
Table 2.
Rainfall analysis of the historical records for the Jeddah area.
\n
The storm recorded at Wadi Qaws station on November 17, 2011, is the highest intensity, followed by the storms occurred at J134 on November 17, 2015; then the station at the headquarters of the Saudi Geological Survey on November 21, 2017; and then the storm recorded at the station at the headquarter of the Saudi Geological Survey on January 26, 2011. However, the storm occurred on January 26, 2011, left a massive damage and problems to the Jeddah area. It caused failure of the Umm al-Khair dam and paralyzed traffic in the province. Maybe the reason for that is related to the duration time of the storm on January 26, 2011. The impact of the storm on November 21, 2017, was within the city of Jeddah and led to the flooding of a large number of roads and tunnels, although considers moderate intensity, however, the storm was concentrated in the center of the city, where almost urban areas are located. The lack of a proper drainage system inside the city has increased the impact of this storm.
\n
\n
\n
6. Prevailing patterns of precipitation in Jeddah
\n
To deduce the characteristic patterns of rainfall in the Jeddah area, we need a large number of reordering storms which are not available in the whole KSA. However, in the current work depending on the storms collected in the Jeddah area from the new installed automated rainfall stations, some suggestions can be made to understand the behavior of storms in the Jeddah area. To achieve this, the data available for each storm were converted to dimensionless data (Figure 10). The behavior of all possible storms was compared with the SCS-type II distribution curve. It is noticed that these storms can be divided into two groups. The first group represents the storms, which exceeded 50 mm of precipitation (Figure 11a). This group is represented by the storms recorded at the headquarters of the SGS station on November 21, 2017; January 26, 2011; and November 17, 2011, in both the Wadi Qaws and J134 stations. The second group represents short-term storms which recorded precipitation quantities less than 50 mm (Figure 11b). This group includes the storms registered at the headquarters of the SGS station on November 22, 2014, and December 2, 2016. For both groups, the average curves of each storm set were derived. To verify that these two storm groups are different from each other and have different behaviors, a distribution histogram of the average curve for each storm group was extracted and simplified as shown in Figure 12.
\n
Figure 10.
Cumulative dimensionless hyetographs for rainstorms occurred in the period 2011–2017.
\n
Figure 11.
Cumulative dimensionless hyetographs: (a) for storms above 50 mm and (b) for storms below 50 mm.
\n
Figure 12.
(a) Dimensionless histogram for storms above 50 mm. (b) Dimensionless histogram for storms below 50 mm.
\n
\n
\n
7. The relation of the storms to the depth of the rain calculated for different return periods in the Jeddah area
\n
Rainfall depth of return periods 5–100 years was estimated by the Saudi Geological Survey and AECOM company (Table 2). The values are due to the analysis of the historical records of all rain stations located in and around the Jeddah area. An average value for each return period was calculated and used in the current study.
\n
By comparing the average data of Table 2 with the rainfall amounts recorded in the recent storms, it was found that the storms of the first group, which exceeded the amount of rainfall of 55 mm, fall within the rainfall depth above the 5-year return period. The storm recorded on January 26, 2011, 111.6 mm, falls below the 50-year return period; the storm recorded on November 21, 2017, 88 mm, falls below the rainfall value of the 20-year return period; the storm recorded on November 17, 2015, in the Wadi Qaws, 61 mm, falls under the value of the 10-year return period; and the storm recorded on November 17, 2011, at the J134 station, 79 mm, falls under the storms of the 12-year return period, while in the second group storms, they did not exceed the amount of rainfall of 50 mm, which falls below the return period of 5 years.
\n
Accordingly, our results indicated that instead of using the SCS distribution curve type II which has happened before in our studies, we can use these new distribution curves. For storms that exceed 50 mm, we can use the distribution curve extracted from the first group (average curve) (Figures 11a and 12a). However, for storms less than 50 mm, we can use the average distribution of the second group (small storm distribution can be applied) (Figures 11b and 12b).
\n
\n
\n
8. Conclusion
\n
Our findings indicated that Jeddah rainfall is characterized by two patterns: one for the rain values less than 50 mm and the other one for the rain values above 50 mm. The study shows that dealing with rainfall data in the Jeddah area required the following points to be considered: (1) it is necessary to pay attention to the details of rainstorms (intensity values) and not only to the recorded daily values. (2) There is a convergence of the nature of storms with impact (greater than 30 mm), which begins to rise after the onset of the storm almost immediately and continue the same tendency to the end of the storm. (3) There is a slight difference between the nature of these storms and the SCS-type II distribution, which assumes that about 60% of the depth of the rain falls in a fraction of the duration of the storm ranging from 8 to 20% and the rest distributed over the rest of the storm. (4) The average length of storms should be considered within the study areas. (5) In short-term storms of less than 2 h or even (with some reservation) up to 3 h, the distribution of SCS type II can be used safely but with duration limited to the same span of the storm rather than 24 h.
\n
\n
Acknowledgments
\n
The authors would like to thank the Saudi Geological Survey for providing scientific and logistical support for this work.
\n
Conflict of interest
The authors declare no conflict of interest.
\n',keywords:"rainfall patterns, floods, impacts, Jeddah, KSA, statistical analysis",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/67666.pdf",chapterXML:"https://mts.intechopen.com/source/xml/67666.xml",downloadPdfUrl:"/chapter/pdf-download/67666",previewPdfUrl:"/chapter/pdf-preview/67666",totalDownloads:221,totalViews:0,totalCrossrefCites:0,dateSubmitted:"November 21st 2018",dateReviewed:"May 10th 2019",datePrePublished:"June 14th 2019",datePublished:"November 13th 2019",readingETA:"0",abstract:"Recently, the Kingdom of Saudi Arabia (KSA) has been facing significant changes in rainstorm patterns (rainstorm intensities, frequencies, distributions) causing many flash flood events. The city of Jeddah is located in a coastal plain area, in the middle of the western side of the KSA, which represents a clear case of changing rainstorm patterns. Jeddah has been hit by many rainstorm events, which increased dramatically since 2009 (e.g., one in 2009, one in 2011, one in 2015, and another one happened in 2017). However, in 2018 about six rainstorms occurred. Two major flash flood events occurred in the city in November 2009 and in January 2011. There were significant impacts of these two events causing severe flooding. During these events, 113 persons were announced dead (in the 2009 event), and infrastructures and properties were damaged (roads and highways, more than 10,000 homes and 17,000 vehicles). In addition to that, dam failure occurred in the 2011 event. This situation gives clear evidence in changing the climate system that could cause more storms in the future across the KSA. Generally, Jeddah city has a lack of short-duration data in rainfall stations. In addition to that, there are a limited number of studies that have been done in determining rainstorm patterns. Consequently, the approach of the current study will focus on understanding and determining rainstorm patterns in the period between 2011 and 2017 depending on some digital rainfall stations that have been installed recently in Jeddah city. Rainstorm pattern and the method of distribution are the most crucial factors affecting peak flow and volume calculations. Our findings showed that there are two pattern types for the rainstorms in Jeddah city. Finally, a comparison with SCS-type II distribution was carried out.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/67666",risUrl:"/chapter/ris/67666",signatures:"Mazen M. Abu Abdullah, Ahmed M. Youssef, Fawzy Nashar and Emad Abu AlFadail",book:{id:"7767",title:"Rainfall",subtitle:"Extremes, Distribution and Properties",fullTitle:"Rainfall - Extremes, Distribution and Properties",slug:"rainfall-extremes-distribution-and-properties",publishedDate:"November 13th 2019",bookSignature:"John Abbot and Andrew Hammond",coverURL:"https://cdn.intechopen.com/books/images_new/7767.jpg",licenceType:"CC BY 3.0",editedByType:"Edited by",editors:[{id:"225780",title:"Dr.",name:"John",middleName:null,surname:"Abbot",slug:"john-abbot",fullName:"John Abbot"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:[{id:"188462",title:"Dr.",name:"Ahmed",middleName:null,surname:"Youssef",fullName:"Ahmed Youssef",slug:"ahmed-youssef",email:"amyoussef70@yahoo.com",position:null,institution:null},{id:"289794",title:"Mr.",name:"Mazen",middleName:"Mustafa",surname:"Abu Abdulla",fullName:"Mazen Abu Abdulla",slug:"mazen-abu-abdulla",email:"mazenaa@yahoo.com",position:null,institution:null},{id:"296737",title:"Mr.",name:"Fawzy",middleName:null,surname:"Nashar",fullName:"Fawzy Nashar",slug:"fawzy-nashar",email:"Nashar.ft@sgs.org.sa",position:null,institution:null},{id:"296738",title:"Mr.",name:"Emad",middleName:null,surname:"Abu AlFadail",fullName:"Emad Abu AlFadail",slug:"emad-abu-alfadail",email:"abualfadhael@gmail.com",position:null,institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Rainfall distribution in the KSA and recent problems",level:"1"},{id:"sec_3",title:"3. Study area and its characteristics",level:"1"},{id:"sec_4",title:"4. Characteristics",level:"1"},{id:"sec_4_2",title:"4.1 Rainstorm occurred on January 26, 2011",level:"2"},{id:"sec_5_2",title:"4.2 Rainstorm occurred on November 22, 2014",level:"2"},{id:"sec_6_2",title:"4.3 Rainstorm occurred on November 17, 2015",level:"2"},{id:"sec_7_2",title:"4.4 Rainstorm occurred on December 2, 2016",level:"2"},{id:"sec_8_2",title:"4.5 Rainstorm occurred on November 21, 2017",level:"2"},{id:"sec_10",title:"5. Comparison of different storms",level:"1"},{id:"sec_11",title:"6. Prevailing patterns of precipitation in Jeddah",level:"1"},{id:"sec_12",title:"7. The relation of the storms to the depth of the rain calculated for different return periods in the Jeddah area",level:"1"},{id:"sec_13",title:"8. Conclusion",level:"1"},{id:"sec_14",title:"Acknowledgments",level:"1"},{id:"sec_17",title:"Conflict of interest",level:"1"}],chapterReferences:[{id:"B1",body:'Aerts J, Droogers P, editors. Climate Change in Contrasting River Basins: Adaptation Strategies for Water, Food, and Environment. London: CABI Books; 2004. p. 288\n'},{id:"B2",body:'Mander WJ. Dictionary of Global Climatic Change. 2nd ed. London: VCL; 1994\n'},{id:"B3",body:'Domroes M, El-Tantawi A. Recent temporal and spatial temperature changes in Egypt. International Journal of Climatology. 2005;25:51-63\n'},{id:"B4",body:'Hunt BG. Natural climatic variability and Sahelian rainfall trends. Global and Planetary Change. 2000;24:107-131\n'},{id:"B5",body:'Raziei T, Arasteh PD, Saghafian B. Annual rainfall trend in arid & semi-arid regions of Iran. In: ICID21st European Regional Conference; 15-19 May, 2005; Frankfurt (Oder) and Slubice—Germany and Poland; 2005. pp. 20-28\n'},{id:"B6",body:'Ali SA, Aadhar S, Shah HL, Mishra V. 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Feb 1997;188-189:1067-1079\n'},{id:"B22",body:'Reid I, Powell DM, Laronne JB, Garcia C. Flash floods in desert rivers: Studying the unexpected. EOS. Transactions of the American Geophysical Union. 1994;452:75-39\n'},{id:"B23",body:'Warner TT. Desert Meteorology. Edinburgh: Cambridge University Press; 2004. p. 612\n'},{id:"B24",body:'Laity JE. Deserts and Desert Environments. Oxford, UK: Wiley-Blackwell; 2008. p. 360\n'},{id:"B25",body:'Ouarda TBMJ, Cunderlik JM, St-Hilaire A, Barbet M, Bruneau P, Bobee B. Data-based comparison of seasonality-based regional flood frequency methods. Journal of Hydrology. 2006;330:329-339\n'},{id:"B26",body:'Parent E, Bernier J. Bayesian POT modelling for historical data. Journal of Hydrology. 2003;274:95-108\n'},{id:"B27",body:'Dairaku K, Emori S, Oki T. Rainfall amount, intensity, duration and frequency relationships in the Mae Chaem watershed in Southeast Asia. Journal of Hydrometeorology. 2004;5:458-470\n'},{id:"B28",body:'De Paola F, Giugni M, Topa ME, Bucchignani E. Intensity-duration-frequency (IDF) rainfall curves, for data series and climate projection in African cities. Springerplus. 2014;3:133. DOI: 10.1186/2193-1801-3-133\n'},{id:"B29",body:'Lu E, Zhao W, Gong L, Chen H, Wang H, Li X, et al. Determining starting time and duration of extreme precipitation events based on intensity. Climate Research. 2015;63(1):31-41\n'},{id:"B30",body:'Mirhosseini G, Srivastava P, Stefanova L. The impact of climate change on rainfall intensity-duration-frequency (IDF) curves in Alabama. Regional Environmental Change. 2013;13:25-33. DOI: 10.1007/s10113-012-0375-5\n'},{id:"B31",body:'Wagesho N, Claire M. Analysis of rainfall intensity-duration-frequency relationship for Rwanda. Journal of Water Resource and Protection. 2016;08:706-723. DOI: 10.4236/jwarp.2016.87058\n'},{id:"B32",body:'Zainudini MA, Sardarzaei A. 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Regional variations of monthly rainfall amounts in the Kingdom of Saudi Arabia. Journal of King Abdulaziz University: Earth Science. 1992;6:113-133\n'},{id:"B38",body:'McLaren International Ltd. Water and agricultural development studies, Arabian Shield South. Report prepared for the Ministry of Water and Agriculture, Riyadh; 1979\n'},{id:"B39",body:'Sen Z. Hydrology of Saudi Arabia. In: Symposium on Water Resources in Saudi Arabia; Riyadh, Saudi Arabia: King Saud University; 1983. pp. 68-94\n'},{id:"B40",body:'Youssef AM, Pradhan B, Sefry SA. Flash flood susceptibility mapping in Jeddah city (Kingdom of Saudi Arabia) using bivariate and multivariate statistical models. Environment and Earth Science. 2016;75:12. DOI: 10.1007/s12665-015-4830-8\n'},{id:"B41",body:'Youssef AM, Sefry SA, Pradhan B, Abu Al Fadail E. Analysis on causes of flash flood in Jeddah city (Kingdom of Saudi Arabia) of 2009 and 2011 using multi-sensor remote sensing data and GIS. Geomatics, Natural Hazards and Risk. 2016;7:1018-1042. DOI: 10.1080/19475705.2015.1012750\n'},{id:"B42",body:'Abdul Karim AAA. Effect of spatial changes of urban growth and land uses on increasing flood risks in the Saudi City: Case study of Ha’il city using geographical information systems and remote sensing (GIS & RS). Arab Journal of Geographic Information Systems, Saudi Geographical Society. 2013;6(2)\n'},{id:"B43",body:'Abushandi E. Flash flood simulation for Tabuk City catchment, Saudi Arabia. Arabian Journal of Geosciences. 2016;9:188. DOI: 10.1007/s12517-015-2192-x\n'},{id:"B44",body:'Al-Ghamdi K, Elzahrany R, Mirza M, Dawod G. Impacts of urban growth on flood hazards in Makkah City, Saudi Arabia. International Journal of Water Resources and Environmental Engineering. 2012;4(2):23-34\n'},{id:"B45",body:'Elkhrachv I. Flash flood Hazard mapping using satellite images and GIS tools: A case study of Najran City, Kingdom of Saudi Arabia (KSA). The Egyptian Journal of Remote Sensing and Space Sciences. 2015;18:261-278. DOI: 10.1016/j.ejrs.2015.06.007\n'},{id:"B46",body:'El Shinnawy I, Bestawy A, El Tahawy T. Assessment and Management of flash floods for sustainable development in Al-Sail Al Kabir area, Kingdom of Saudi Arabia. International Journal of Applied Engineering Research. 2017;12:2807-2814\n'},{id:"B47",body:'Embaby A, Abu Halawa A, Ramadan M. Integrating geotechnical investigation with hydrological modeling for mitigation of expansive soil hazards in Tabuk City, Saudi Arabia. Open Journal of Modern Hydrology. 2017;7(1):11-37. DOI: 10.4236/ ojmh.2017.71002\n'},{id:"B48",body:'Sharif HO, Al-Juaidi FH, Al-Othman A, Al-Dousary I, Fadda E, Jamal-Uddeen S, et al. Flood hazards in an urbanizing watershed in Riyadh, Saudi Arabia. Geomatics, Natural Hazards and Risk. 2014;7:702-720. DOI: 10.1080/19475705.2014.945101\n'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Mazen M. Abu Abdullah",address:"mazenaa@yahoo.com",affiliation:'
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Openness - We communicate honestly and transparently. We are open to constructive criticism and committed to learning from it.
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IntechOpen is a dynamic, vibrant company, where exceptional people are achieving great things. We offer a creative, dedicated, committed, and passionate environment but never lose sight of the fact that science and discovery is exciting and rewarding. We constantly strive to ensure that members of our community can work, travel, meet world-renowned researchers and grow their own career and develop their own experiences.
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If this sounds like a place that you would like to work, whether you are at the beginning of your career or are an experienced professional, we invite you to drop us a line and tell us why you could be the right person for IntechOpen.
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