Environment Pollution and Climate Change
Open Access

The worldwide concern with global climate has highlighted the challenges faced by both industrialized and developing countries on the issue of increasing greenhouse gas emissions. These gases are chlorofluorocarbons (CFC), carbon dioxide (CO₂), methane (CH₄), and nitrogen oxides (NO_x) which absorbs the radiation in the earth atmospheric system. Excess of these gases often affect the environment causing global warming [1]. While the greenhouse effect has been beneficial to maintain global temperatures compatible to human life, recent increases in average temperatures due to human activities are causing great alarm.

Of all greenhouse gases responsible for global warming, CO₂ is of major concern. Atmospheric CO₂ is produced naturally from volcanic out gassing, the combination of organic matter and the respiration processes of living anaerobic organisms [2] and artificially from combustion of various fossil fuels and deforestation etc. The artificial sources of CO₂ emissions are generally thought to be responsible for global warming causing increase in atmospheric CO₂ by about 43 % since the beginning of the age of industrialization. In 2016, the Earth's atmosphere CO₂ concentration is averagely 402 parts per million (by volume) which continues to increase [3].

The concentrations of carbon dioxide in the atmosphere as well as climatic parameters such as temperature and relative humidity fluctuate slightly with the seasons and on regional basis. This is evident in some studies conducted from different areas of the world [4-11], in sub-Saharan West Africa [12-15] and Nigeria has been reviewed [16-18]. The predictions of global future climate change rely mostly on the ability to quantify fluxes of greenhouse gases, especially CO₂, at regional scales. However, micronutrients along river banks are equally influenced by greenhouse gases and so the current project is important.

The aim of the study is to determine the dry season variation of atmospheric carbon dioxide along River Nworie, Owerri Municipal, Imo state, Nigeria. Since oceans with land sequesters about half of the anthropogenic emissions of atmospheric CO₂ [16-19]. Wetlands along many rivers have not been characterized for greenhouse gases emissions or absorption; hence the current research contributes to information on this subject. Also, measurements over the wetland are very helpful for understanding emissions growth as well as verifying the mitigation policies.

Study area

Nworie River is a first order stream that runs about 5 km course across Owerri metropolis in Imo State before emptying into Otamiri River. It is about 9.2 km long. Imo state is situated in the southern rain forest vegetation belt of Nigeria, it has between latitude 5 o and longitude 7o 34oE. It has an annual rainfall of about 1700-2500 mm. The climate of the study area follows a tropical pattern with the rainy season lasting between seven and eight months between April and October with interruption in August and dry season running through November to March. Average humidity of 80%-85% occurs during the rainy season. Temperature is similar all over the state, with maximum values ranging from 280oC to 350oC and minimum values from 190oC to 240oC.

Control point

The control is a land area that is saturated with water from the rainy season. The area experiences no anthropogenic disturbance and located around Bishop’s Court, Owerri which is more than 7 km away from river Nworie. Geographically, it is located at Latitude-N 5o 29.3623’, Longitude-E 7o 1.4622’ and area is filled with grassland Figure 1a and 1b.

Figure 1a: Map showing sampling points along Nworie River.

Figure 1b: Photographs each sampling point along the longitudinal course of Nworie River.

Atmospheric CO₂ measurement

AZ 77535 CO₂ gas analyzer (AZ Technologies, Taiwan) was the instrument used to determine the CO₂ on the surface/air above the water. The instrument is designed with NDIR (Non-Dispersive Infrared) waveguide technology sensor. The instrument carried out automatic analysis of the sample of ambient air with the use of the physical properties that gives continuous output signal to the analyzer which returns the values of the CO₂, temperature and relative humidity, which were read from the screen. The instrument which was held at arm length and about 10 cm above the water was used to obtain the concentration of CO₂ in the air. Sampling was carried at the hours of morning, afternoon and evening at six different points and the control point for seven weeks with mean reported for each week. These hours were chosen based on the fact that they are meteorological hours recommended for weather observation by world meteorological organization.

The data were collected in year 2016 dry season from November to December.

Method of data analysis

Data analysis was done using Microsoft excel 2007 and values of all the results from the sampling points was recorded as calculated mean values of ambient temperature, relative humidity and air CO₂ concentrations for morning, afternoon and evening hours. The standard deviation (SD) was determined and co-efficient of variation (CV %) was used to determine variation in the concentration of CO₂ between samplings points using equation 1.

(1)

Variation was categorized as little variation (CV% <20), moderate variation (CV%=20-50) and high variation (CV% >50) [20-22].

Anthropogenicity was estimated according to [23] given in equation 2. It is the ratio actual carbon dioxide concentration to reference concentrations expressed in percentage. This estimates the impact of human activities on ambient concentration of carbon dioxide along river Nworie.

(2)

The control data were used as the reference concentrations.

The results for variability and basic descriptive statistical summary for temperature, relative humidity and ambient CO₂ concentration obtained at various points of the river for seven weeks during November and December 2016 is presented in Table 1. The weekly variations of meteorological parameters: (a) relative humidity (%) and (b) temperature (°C) along river Nworie during 2016 dry season (November and December) are shown in Figures 2 and 3. Mean reported for data collected daily in morning, afternoon and evening hours.

Figure 2: Trends for ambient CO₂ concentrations recorded during the study.

Figure 3: Trends for RH recorded during the study.

Table 1: The result for the CO₂ concentration in air, temperature and relative humidity along river Nworie for dry season of 2016.

The trend for CO₂ concentrations for the sampling points and control is presented in Figure 2. The concentration of atmospheric CO₂ ranged from 550 ppm to 572 ppm in week one, from 547 ppm to 572 ppm in week two, from 544 ppm to 563 ppm in week three, from 536 ppm to 575 in week four, from 568 ppm to 579 ppm in week six while week seven showed ranges of 509 ppm to 574 ppm respectively. Higher concentrations were recorded in the present study when compared with concentration of 402 ppm recorded in early 2016 for average global concentration of CO₂. The obtained concentrations at river Nworie was generally higher than the control with range of 480 ppm (week one) to 490 ppm (week seven) and mean of 470.71 ± 15.43 ppm. The present study also showed higher concentrations when compared to annual average atmospheric CO₂ concentrations observed in Ahmedabad in western India (413.0 ± 13.7 ppm) in 2015 [24]. The high CO₂ is due mainly to anthropogenic activities carried out along the river such as the use of potable water, generation of wastewater, the generation of solid waste and vehicle exhaust [25,26]. The cycles of CO₂ is mostly governed by the strength of emission sources, sinks and transport patterns. NASA [27] reported that human-made carbon dioxide (CO₂) continues to increase above levels not seen before and is not absorbed by vegetation and the oceans. The increase in atmospheric concentration of CO₂, and thus in the CO₂ induced greenhouse effect, is the reason for the rise in average global temperature causing global warming [8,27].

The variability of CO₂ along the river show little variations as all coefficients of variations are less than 20% (Table 1). However, the highest variability was recorded in the seventh week of the study (4.5%) while in week six the lowest was recorded (0.5). The reason for the little variations could be due to the sampling points falling in the same geographical location.

The trends of temperature from week one to seven is introduced in Figure 4. In week one temperature ranged from 31.9oC at point C to 33.8 at point F. During week two, the temperatures at the sampling point dropped (as low as 30.5oC) except for point B and F with slight and heavy increase in temperature respectively. From week three, there was temperature rise and drop from the week four to five. In the sixth, the highest temperature was recorded at point F while B and D recorded lowest. There was a significant increase at point B and D, temperature rising from 30.7oC to 39.9oC respectively. There were also temperature rise at points C, E, and F while reducing temperature was observed at point A. Throughout the study, all points showed higher temperature when compared to control where we recorded a range of 28 to 30oC and mean of 29 ± 0.82oC.

Figure 4: Trends for ambient temperature recorded during the study.

Though temperatures were high, it showed little variability like all other parameters revealed little variability (<20%, Table 1). High temperature in urban areas such as Lagos (33oC), Warri (32.1oC), Benin (31.3oC), Portharcourt (30.3oC), Calabar (31.5oC), Abuja (33.8oC), Lokoja (33.3oC), Ilorin (33.4oC), Jos (31.8oC), Kano (39.8oC), Maiduguru (39.8oC) and Sokoto (39.7oC) respectively in Nigeria has been reported [28]. This rise in temperature implies that there is rise in CO₂. Soon [29] using climate modeling asserted that increase in atmospheric CO₂ increases with increasing atmospheric temperature. This is evident in the current study where high temperatures along river Nworie showed high CO₂ concentrations as opposed to the observation at the control where low temperature followed low CO₂ concentrations.

Generally, from week one to week seven low humidity was recorded in all points, except for week two where a maximum RH of 71.8% was recorded Figure 4. However, the control showed high humidity when compared with observations made at river Nworie except in week one. The range of RH was 60 to 73.9% with mean of 66.70 ± 6.37%. The low humidity could be due to the season of study. There is generally high temperature during dry season and thus little amount water vapors in the environment. Relative humidity gives amount of water vapour in the environment and depends on the temperature. Therefore, the high humidity recorded at the control points is due to the low temperature observed in that area.

Relationship between climatic parameters and CO₂ concentration during the study

In order to establish a relationship between ambient CO₂ concentrations and climatic parameters measured, we conducted a linear, exponential and power regression analysis. Table 2 shows the summary of the relationships showing equations and regression coefficients. A good correlation equation between temperature and CO₂ as well as RH and CO₂ was shown in Table 2. Regression analysis revealed that increasing temperatures could lead to increasing CO₂ concentration while CO₂ concentrations increased for decreasing relative humidity. Since, all R² values (regression coefficient) are positive. Regression coefficient is adjudged on the scale of -1, 0, +1. Positive relationship suggests the dependent variable and independent variable have direct relationship and vice versa for negative relationships while zero suggests no relationship.

Table 2: Relationship between climatic parameters and CO₂ concentration during the study.

All relationships showed positive slope during the study except in week 5 for temperature-CO₂ relationship. Meanwhile, negative slope were obtained in week 2, 5, 6 and 7 for relative humidity-CO₂ relationship. The relationship equations showed that the plots didn’t follow the origin (0) and thus having high intercept. This observation follows the regression coefficient obtained suggesting that the relationship isn’t perfect (<1). Positive relationship was also reported for CO₂ emissions from the lower Red River in Vietnam [30].

To determine which relationship is more pronounced with CO₂ concentration, we created a trend plot which compared the different relationships. The trend results are presented in Figure 5. Looking at Figure 5a critically, it could be observed that the relationship between CO₂ and temperature is better described by an exponential equation especially in the fourth week. Although a power and linear relationships followed closely. However, with relative humidity the trend follows similar pattern (Figure 5b). There was high relationship was recorded in week 1 and 2 of the study which drops with weeks.

Figure 5: Comparing the different relationships for CO₂ and other climatic parameters.

Anthropogenicity (Human Impact Estimation)

We estimated the impact of human activities on the high concentration of carbon dioxide along river Nworie using anthropogenic model as described in equation 2. When discussing climate change, it is often used to refer to emissions produced as a result of human activities. We estimate the impact based on data obtained from the control point. The computed anthropogenicity is presented in Table 3.

Table 3: Computed Anthropogenicity for CO₂ concentrations for different sampling points throughout the study period.

Generally, high anthropogenic impact estimate were obtained throughout the study period which ranged from 103.88% to 127.25%. The high estimate obtained suggested that the many activities experienced along the river is causing high temperature and thus high CO₂ concentrations. Activities experienced along this area include waste dumpsite which contains organic matter and in the presence of warmer temperature and moisture decomposes and oxidizes, releasing CO₂ in the atmosphere. Other activities include emission for automobile exhaust, automobile workshop, building constructions, road construction, destroyed vegetation mostly grasses and polluted water, sand mining and dredging on both sides of the Nworie River. The drainage and destruction can result in substantial carbon emission [31-33].

The week-wise trend for anthropogneicity is introduced in Figure 6. Week-wise impact showed that the highest human impact on CO₂ concentration was observed in the fifth week (126.04%) while the least in week one (100.26%). The week-wise impact follows the trend; week 5>week 6>week 4>week 2>week 7>week 1 respectively. Meanwhile, site-wise trend is introduced in Figure 7. The highest estimated value was obtained at point F (121.08%) and least recorded at point C (117.92%). The site-wise impact follows the trend; point F>point E>point B>point A>point D>point C respectively.

Figure 6: Week-wise trend for anthropogneicity.

Figure 7: Site-wise trend for anthropogneicity.

Conclusion

With the rising global warming, awareness results from this work confirm elevated CO₂ concentrations over 44% above early 2016 average global CO₂ concentration. The concentrations according to sampling points varied with low % variability but it was observed that temperature had more linear and exponential relationships with CO₂ concentrations. Relative humidity exhibited similar trend for linear, exponential and power relationships with CO₂ concentrations. The various human activities have contributed to rising CO₂ concentrations along river Nworie which is confirmed by the high annthropohenicity (103.88% to 127.25%) recorded with respect to the control point. However, a bigger study with more study sites is required over multiple years to elucidate more accurate distributions of emissions and their source regions for tracking the changes associated with anthropogenic activities and emission mitigation policies.