Determination of CO₂, CH₄ and N₂O: a Case Study for the City of Rio de Janeiro Using a New Sampling Method

Abstract

A new sampling method using polypropylene syringes and chemical analysis by gas chromatography was proposed and applied to determine CO₂, CH₄ and N₂O. The samples' stability was evaluated and compared with the stability of the samples in stainless steel canisters and Tedlar^® bags. This methodology was applied to a case study in the urban area of the city of Rio de Janeiro, Brazil. In 2012, annual averages of 507.6 ± 13.2 µmol mol^-1 for CO₂, 1.95 ± 0.06 µmol mol^-1 for CH₄ and 325.3 ± 3.4 nmol mol^-1 for N₂O were obtained. The results for CO₂ and CH₄ showed peak values in the warmer months and lower values in winter. This CO₂ behavior is the opposite of that observed in studies performed in many other cities around the world and may be climate-related. CH₄ and N₂O inputs are probably due to the evaporation of liquid and solid waste both from landfill sites located within the city boundaries and from polluted rivers and canals. Additionally, other anthropogenic sources may be considered, such as the release of CH₄ by the gas fuel network of the urban area and the emissions due to the use of compressed natural gas by light vehicles.

Keywords: urban atmosphere; greenhouse gas; carbon dioxide; methane; sampling

Introduction

According to the National Oceanic and Atmospheric Administration (NOAA), the highest globally averaged temperature for land and ocean surfaces since records began in 1880 was measured in 2014.¹ Additionally, in 2014, for the first time since carbon dioxide has been measured at Mauna Loa Observatory, Hawaii, its peak levels surpassed 400 µmol mol^-1 during three consecutive months in the atmosphere.²

The highest carbon dioxide global average concentration was 398.83 µmol mol^-1 in May 2014, according to NOAA.² Although this value has not yet reached 400 µmol mol^-1, these global concentrations of the main greenhouse gases (GHG) represent the highest historical values.

Carbon dioxide (CO₂) is the most important anthropogenic greenhouse gas in the atmosphere;³ however, two other gases, i.e., methane (CH₄) and nitrous oxide (N₂O), are important, and they are all closely related to anthropogenic activities, such as fossil fuel combustion, agriculture, biomass burning and waste management.

Brazil is the largest country in Latin America. It is the world's fifth largest country by both geographical area and population.⁴ It is considered part of the BRICS (Brazil, Russia, India, China and South Africa) group of countries, which are similar in terms of area, large populations and growing economies and, together, are responsible for 18% of the world's gross domestic product (GDP).⁵

The BRICS group emits an average of 4.5 metric tons per capita of CO₂, whereas the entire world, including the developed countries, emits an average level of 4.9 metrics tons per capita, according to the World Bank.⁶ This points the need for the effective monitoring of GHG emissions in these countries.

Many studies have been published involving the measurement of GHG that originate from different sources, including stationary sources, mobile sources and ambient air. For example, GHG measurements have been included in studies involving emissions from human activities in the soil,^7-11 ships,^12,13 hydroelectric reservoirs,¹⁴ vehicles^15-17 and thermoelectric power plants.¹⁸ However, to our knowledge, the available literature contains no information on the variation in GHG concentrations in Rio de Janeiro and other Brazilian cities, despite their high level of urbanization and economical activities. The annual emissions of CO₂, CH₄ and N₂O in Rio de Janeiro have been estimated as 8,734 Gg, 112,616 t and 800 t, respectively.¹⁹ The total emissions was calculated as 11,352 Gg CO₂, which means that the CH₄ and N₂O contribution to GHG is approximately 25%.¹⁹

A variety of methods for determining trace gases in the atmosphere has been developed. Discontinuous methods can be performed, without pre-concentration, by using stainless steel canisters or Tedlar^® bags to collect air samples and for further chromatographic analysis.²⁰

The collection of ambient air samples in canisters is common practice, and it is mainly done for the determination of volatile organic compounds (VOCs) in the atmosphere.^21,22 These canisters have advantages such as inertness, ruggedness, reuse and durability. Despite the high collection efficiency, there are some disadvantages when it is necessary to collect multiple samples at different sampling points, such as the high costs and greater difficulties in transporting the samples.

In most of the published studies regarding the measurement of GHG in ambient air from stationary and mobile sources, online analysis methods are employed, such as chromatographic and spectroscopic techniques.^23-25 Commercial analyzers, which have the advantage of providing continuous measurements, are available for automatic GHG monitoring. The high cost of these instruments and the installation requirements are their main disadvantages.

GHG are not currently monitored in Brazilian cities. To our knowledge, there are no data for Rio de Janeiro, which is the second largest city in Brazil. The following investigation was conducted to evaluate the efficacy of low-cost polypropylene (PP) syringes for the sampling and storage of CO₂, CH₄ and N₂O. The method was applied in a study case in Rio de Janeiro to evaluate the concentration of these three compounds at representative locations to determine the hourly concentrations over a typical day and seasonal variations throughout one year.

Experimental

Sampling media

In this experiment, 6.0 L internally electropolished (Restek SUMMA^® coating) stainless steel canisters, 3.0 L Tedlar^® bags (SKC), and 100 mL medical graduate PP syringes with Luer caps were used. The syringes' features include easy handling and transportation and a very low cost per unit. These types of syringes are also used in medical procedures and contain a PP body and rubber plunger. PP syringes might be a suitable substitute when continuous measurements are not available or when sampling with other well-developed sampling media, such as canisters and Tedlar^® bags, cannot be implemented due to the related costs or difficult-to-reach sampling locations. For a blank test, each sampling material was filled with 99.999% synthetic air provided by Linde Gas.

Chemical analyses

The samples were analyzed by gas chromatography with multiple detectors. Chemical analyses were performed using an Agilent 7890A Gas Chromatograph with three detectors: a thermal conductivity detector (TCD) to measure CO₂ at high levels as well as molecular oxygen and nitrogen, an electron capture detector (ECD) to measure N₂O and a flame ionization detector (FID) to measure CH₄ and CO₂ at low levels.

The chromatography system used two separated channels with 1/8" packed columns (HayeSep Q80/100). The first channel had two valves for the TCD and FID, which were organized in series to measure CO₂ by using a methanizer to convert CO₂ to CH₄. The other channel, which also had two valves, was used to measure N₂O on the micro ECD. Two pre-columns were used to retain heavier compounds and to purge oxygen and water through the vent.

The system used a 1.0 mL sampling loop, and the columns, valves, FID, ECD and TCD were operated at 60 °C, 100 °C, 250 °C, 350 °C and 200 °C, respectively. Helium 5.0 was used as the mobile phase at a flow rate of 21 mL min^-1. Quantification was performed using triplicate external calibration curves and three standard reference GHG mixtures provided by Linde Gas. The certified concentrations for CO₂, CH₄ and N₂O were 351 ± 7; 1.510 ± 0.075 and 0.250 ± 0.012 µmol mol^-1, respectively, according to the standard number 2040/11; 401 ± 7, 1.760 ± 0.088 and 0.300 ± 0.015 µmol mol^-1, respectively, according to the standard number 041/11; and 451 ± 9; 2.010 ± 0.100 and 0.350 ± 0.017 µmol mol^-1, respectively, according to the standard number 04/11. The determination coefficients (R²) for the triplicate calibration curves were higher than 0.99 for CO₂ and CH₄ and 0.98 for N₂O.

Stability tests

First, a stability test was performed comparing the most common sampling methods (stainless steel canisters and Tedlar^® bags) with the new proposed method (PP syringes) by checking the sample stability for 10 days of a certified standard mixture containing CO₂ (401 ± 7 µmol mol^-1), CH₄ (1.760 ± 0.088 µmol mol^-1) and N₂O (300 ± 15 nmol mol^-1) in synthetic air, supplied by Linde Gas (Linde, certificate number 2041/11).

Then, to verify the interaction of the GHGs with other gases and their stabilities, control atmospheres were prepared with different concentrations, stored in the three sampling medias for 10 days, and compared with the initial concentrations.

The control atmospheres were prepared inside 10 L black Tedlar^® bags using 99.999% nitrogen as the dilution gas. The others gases (CO₂, CH₄, N₂O, CO, NO and NO₂) were supplied by Linde Gas.

A Sierra Mass Flow controller was used in the dilution process. The GHG were determined by gas chromatography, as previously described, and CO, NO, and NO₂ were determined using Thermo Scientific analyzers (models 48i for CO and 42i for NO and NO₂). Water content was controlled by injection, using a syringe at 20 °C and 101 kPa. The composition of the control atmospheres is shown in Table 1. The selected values for GHG concentrations were in the same range as those expected for the atmospheric samples.

Table 1
Composition of the control atmospheres used for the stability tests in μmol moL^-1; CO₂, CH₄ and N₂O concentrations were determined by gas chromatography at the conditions described in the text

Atmosphere	CO2 / (μmol moL-1)	CH4 / (μmol moL-1)	N2O / (μmol moL-1)	CO / (μmol moL-1)	NO / (μmol moL-1)	NO2 / (μmol moL-1)	H2O / (μmol moL-1)
ATM 1	351	1.56	0.252	0.555	0.052	0.049	9.351
ATM 2	351	1.56	0.253	1.04	0.114	0.100	14.097
ATM 3	353	1.49	0.255	2.00	0.198	0.201	18.902
ATM 4	401	1.76	0.303	0.510	0.051	0.045	9.358
ATM 5	401	1.76	0.303	1.07	0.112	0.104	14.103
ATM 6	401	1.76	0.303	1.96	0.190	0.197	18.893
ATM 7	457	2.01	0.349	0.570	0.050	0.045	9.344
ATM 8	455	2.09	0.349	1.10	0.110	0.101	14.101
ATM 9	455	2.02	0.345	1.99	0.191	0.202	18.900

Ambient air collection

PP syringes were used to collect ambient air samples in Rio de Janeiro. The city has a population of 6,453,682²⁶ and contains 2,451,155 vehicles²⁷ in an area of 1,224 km². Air circulation is greatly affected by topographical conditions; the Tijuca Forest, a mountainous rainforest area, forms a natural barrier to air circulation and divides the city into northern and southern sections.²⁸ As described below, all of the samples were collected in the northern area of the city in locations that are strongly affected by vehicle emissions.

No samples were collected during rainy days or days with atypical anthropogenic emissions. The distance from the sampling positions to obstacles was at least twice the height of the obstacle, and the surrounding environment was free of interference from obstacles. Sampling was performed at a height of approximately 1.5 m above the ground, and the syringe was rinsed five times with the same ambient air before sampling. A 0.2 µm fiberglass filter was linked to the syringe to prevent the entry of particulate matter, which could damage the chromatographic system. The duration of the sampling for one syringe was approximately 10 seconds. After sampling, the syringes were sealed with Luer caps, protected from light with aluminium foil and stored at room temperature.

Initially, 3 samples were collected in 2011 at different times in each of seven districts in the city, as described in Table 2. The sampling locations were mainly residential areas with intense vehicular traffic and commercial activity that are representative of the city. A map of the city indicating the sampling locations is shown in the Supplementary Information section, Figure S1. The exact localization of each sampling point is shown in the Supplementary Information section, Table S1. A brief description of each location is presented in Table 2. Data collected during the sampling period at three monitoring stations of the Environmental Municipal Secretary (SMAC) showed a predominance of weak winds (0-4 km h^-1) in the southeast and northwest directions and ambient temperatures between 20 and 35 °C. The mixing height profiles were measured using radiosondes at Rio de Janeiro International Airport, which is located approximately 10-15 km from the sampling sites.²⁹ At 10:00 a.m. on each day, the mixing heights were 388-858 m, as detailed in Table S1. Other meteorological data are presented in Table S2.

Table 2
Description of sampling districts in Rio de Janeiro

District	Population (inhabitants)26	Main streets (St.), avenues (Av.) and roadways	Site description
Bonsucesso	18,711	Brasil Av., Linha Vermelha, Linha Amarela, Teixeira de Castro Av., Dona Isabel St. and Leopoldo Bulhões St.	residential area with high commercial and medium industrial activity; public transport by bus and train
Cidade Nova	5,466	Presidente Vargas Av., Av. Paulo de Frontin, Av. Trinta e Um de Março, Av. Salvador de Sá, Frei Caneca St. and Júlio do Carmo St.	low commercial and industrial activities; public transport by bus and subway; heavy traffic
Maracanã	25,256	Presidente Castelo Branco Av., Maracanã Av., São Francisco Xavier St., Mariz e Barros St. and General Canabarro St.	low commercial and industrial activities; the area is home of the Maracanã stadium and two university campus; public transport by bus and subway; heavy traffic; samples were taken at the Rio de Janeiro state university
Méier	49,828	Linha Amarela, Dias da Cruz St., Vinte Quatro de Maio St., Arquias Cordeiro St., Getúlio Stand Hemengarda St.	high commercial activity; low industrial activity. transport by bus and train
Penha	78,678	Brasil Av., Lobo Júnior Av., Brás de Pina Av., Ibiapina St. and Leopoldina Rego St.	medium commercial and industrial activities; transport by bus
São Cristóvão	26,510	Brasil Av., Linha Vermelha, Pedro II Av., Francisco Bicalho Av., São Luiz Gonzaga St., São Januário St. and Campo de São Cristóvão St.	medium commercial activity and high industrial activity; public transport by bus and subway; heavy traffic
Tijuca	163,805	Maracanã Av., Conde de Bonfim St., Uruguai St., São Miguel St., General Rocca St., São Francisco Xavier St. and Hadock Lobo St.	residential area with high commercial and medium industrial activity; public transport by bus and subway; heavy traffic; samples were taken at the Saenz Pena square

Later, to check the evolution of the hourly concentrations, 12 samples were collected during the period from 6:00 a.m. to 6:00 p.m. on January 3, 2012, at the Maracanã Campus of the Rio de Janeiro State University, where an automatic air quality monitoring station was located. The mixing height at 10:00 a.m. was 290 m. Meteorological and criteria pollutants concentration data were collected at the station. The minimum temperature was 20 °C at 6:00 a.m., and the maximum temperature was 30 °C at midday. Wind was from the southeast direction and was weak (approximately 1.5 km h^-1).

Finally, 38 samples were collected at Maracanã Campus of the Rio de Janeiro State University during the year of 2012. Samples were always collected in triplicate on Mondays at 1:00 p.m. Samples were collected at a height of 70 m to avoid the possible contribution of local sources of GHG. Additionally, no samples were taken on rainy days or holidays (14 days).

Statistical analysis

The experimental data were analyzed using Statistica 7.0 (Statsoft) to define descriptive statistics before extended analyses. A multivariate statistical analysis was performed that included linear correlation analysis (Pearson coefficients) and principal component analysis (PCA). Both calculations were achieved using the individual experimental values for each sample and sampling site.

Results and Discussion

A typical chromatogram for the GHG standard, in which the three detectors operated simultaneously, is shown in the Supplementary Information section, Figure S2.

The results for the stability test performed with the GHG standard are shown in Table 3. The values for the three sampling media are the arithmetic means and standard deviations for six results obtained over 10 days of storage.

Table 3
Mean concentration and standard deviation values of CO₂, CH₄ and N₂O in three sampling media along 10 days of storage at ambient temperature protected from light

	Mean concentration value			Standard deviation / %
	CO2 / (μmol moL-1)	CH4 / (μmol moL-1)	N2O / (nmol moL-1)	CO2	CH4	N2O
Initial valuea	401	1.76	300	−	−	−
Canister	402.83	1.72	302.47	0.10	0.45	0.23
Tedlar bag	403.55	1.71	300.69	0.15	0.28	1.01
PPb syringe	402.31	1.72	304.18	0.13	0.80	0.45

• ^a
  Initial concentration value for each gas in the standard gas (Linde Gases number 2041/11)
• ^b
  PP: polypropylene.

These results show that the stability of GHG samples is similar in the syringes to that found in the more usual sampling devices (stainless steel canisters and Tedlar^® bags). The difference between the initial value and the mean value is always less than 3%, which suggests that syringes are an effective sample storage approach.³⁰ For volatile organic compounds, a difference less than 25% is considered satisfactory.²²

The results for the stability test of GHG in the control atmospheres (Table 1) are shown in Table 4. The values are the mean concentrations for three replicate determinations of samples after 10 days of storage and the deviations from the initial value.

Table 4
Mean concentrations of CO₂, CH₄ and N₂O in the control atmospheres and deviations from the initial value for three replicate determinations of samples after 10 days of storage

Sampling media	Average concentration / (μmol moL-1)				Deviation / %
	CO2	CH4	N2O		CO2	CH4	N2O
atmosphere 1
Canister	354	1.51	0.252		0.85	−3.2	0.0
Tedlar bag	353	1.52	0.251		0.85	−2.6	−0.40
PPa syringe	351	1.52	0.254		0.00	−2.6	0.79
atmosphere 2
Canister	350	1.53	0.252		−0.28	−1.9	−0.39
Tedlar bag	352	1.53	0.254		−0.57	−1.9	0.39
PPa syringe	352	1.52	0.255		−0.57	−2.6	0.79
atmosphere 3
Canister	350	1.50	0.218		−0.85	0.67	−14.5
Tedlar bag	350	1.49	0.217		−0.85	0.00	−14.9
PPa syringe	349	1.52	0.215		−1.1	2.2	−15.7
atmosphere 4
Canister	403	1.72	0.302		0.50	−2.3	−0.33
Tedlar bag	404	1.72	0.301		0.75	−2.3	−0.66
PPa syringe	402	1.72	0.304		0.25	−2.3	0.33
atmosphere 5
Canister	401	1.70	0.305		0.00	−3.4	0.65
Tedlar bag	402	1.72	0.301		0.25	−2.3	−0.66
PPa syringe	402	1.71	0.305		0.25	−2.8	0.65
atmosphere 6
Canister	401	1.73	0.248		0.00	−1.7	−18.1
Tedlar bag	402	1.74	0.257		0.25	−1.1	−15.2
PPa syringe	402	1.73	0.254		0.25	−1.7	−16.2
atmosphere 7
Canister	451	2.01	0.351		−1.31	0.00	0.57
Tedlar bag	451	2.02	0.351		−1.31	0.50	0.57
PPa syringe	450	2.02	0.355		−1.56	0.50	1.72
atmosphere 8
Canister	451	2.04	0.351		−0.88	−2.4	0.57
Tedlar bag	452	2.04	0.350		−0.66	−2.4	0.28
PPa syringe	452	2.01	0.350		−0.66	−3.8	0.28
atmosphere 9
Canister	452	2.01	0.311		−0.66	−0.49	−9.85
Tedlar bag	452	2.03	0.319		−0.66	0.49	−7.54
PPa syringe	451	2.04	0.313		−0.88	0.99	−9.27

• ^a
  PP: polypropylene.

Considering the mean values and concentrations of the standard mixture and the uncertainties from the manufacturer (1.75% for CO₂, 5.11% for CH₄ and 5.00% for N₂O), it can be concluded that all of the sample media evaluated were effective in storing GHG for a period of 10 days under different concentration conditions.

No effect was observed in the presence of different levels of CO₂, CH₄, N₂O, CO, NO and NO₂. However, in the mixtures with higher water content, which was equivalent to a relative humidity of 80%, a reduction in N₂O value was observed. In the ATM 6 mixture, a reduction of 18.1, 15.2 and 16.2% was observed for the canister, Tedlar^® bag (14.33%) and PP syringe, respectively. This may be explained by possible water condensation on the inner wall and the partial solubilization of N₂O.

After the calibration procedure, samples were collected at seven locations in Rio de Janeiro at three different hours of the day. The mean concentrations are shown in Table 5.

Table 5
Concentrations of CO₂, CH₄ and N₂O in seven districts of Rio de Janeiro. Samples were collected using syringes, as described in the text

Date	Hour	District	Concentration / (μmol moL-1)
			CO2	CH4	N2O
2011/10/28	06:30 a.m.	Bonsucesso	577	1.86	0.341
	12:00 a.m.		575	1.83	0.351
	04:00 p.m.		602	1.94	0.361
2011/11/25	07:25 a.m.	Cidade Nova	NDa	NDa	NDa
	01:40 p.m.		528	2.07	0.330
	04:15 p.m.		484	2.38	0.292
2011/11/25	07:45 a.m.	Maracanã	481	2.26	0.288
	01:15 p.m.		475	2.18	0.290
	04:30 p.m.		515	2.01	0.330
2011/10/27	06:45 a.m.	Méier	603	1.94	0.354
	01:00 p.m.		607	1.94	0.362
	04:45 p.m.		609	1.93	0.357
2011/11/25	06:40 a.m.	Penha	525	1.97	0.330
	01:00 p.m.		484	2.44	0.288
	05:00 p.m.		526	2.00	0.319
2011/11/25	07:45 a.m.	São Cristóvão	526	2.01	0.327
	01:25 p.m.		527	1.98	0.327
	04:15 p.m.		512	2.03	0.325
2011/11/25	07:05 a.m.	Tijuca	524	2.00	0.327
	02:00 p.m.		523	2.02	0.468
	04:00 p.m.		522	1.96	0.324

• ^a
  ND = not determined.

The CO₂ concentrations were higher than 400 µmol mol^-1 for all samples. The reported values, which were between 475 and 609 µmol mol^-1, are typical of urban areas, as previously determined in many other places throughout the world. The persistence of CO₂ over urban areas as a result of anthropogenic contribution to the CO₂ budget has been reported in many cities and is known as the urban dome. The typical concentrations of CO₂ in urban areas are between 350 and 600 µmol mol^-1 and depend on meteorological parameters and urban agglomeration.^31,32 In this work, samples were collected in the spring (October and November) in residential areas that are highly affected by vehicle emissions, which were expected to be the main source of CO₂.³³

As shown in Table 5 and in the Supplementary Information section, Figure S3, when the sample locations are compared, higher levels of CO₂ can be observed in two districts, Bonsucesso and Méier, which is probably due to the preferential dispersion of pollutants affected by the topography of these districts and a higher local anthropogenic contribution related to intense commercial activity, high vehicular flux and traffic jams.

According to literature data, the typical concentrations of CH₄ in urban areas are between 1.70 and 2.50 µmol mol^-1 and are influenced by meteorological parameters and urban agglomeration. The most significant sources of methane come from the anaerobic decomposition of organic matter.³ The values obtained in this work were in the range of 1.83-2.44 µmol mol^-1, which is in good agreement with the reported values for other urban centers. As shown in Table 5 and in the Supplementary Information section, Figure S4, the higher values were obtained in the Penha, Maracanã and Cidade Nova Districts, and they may be attributed to the proximity of polluted rivers with a high organic matter content. The available emission inventories for the city attribute approximately 90-95% of the total CH₄ emissions to the disposal of residential, commercial and industrial solid waste in sanitary landfills and to untreated liquid waste.³³

As shown in Table 5 and in the Supplementary Information section, Figure S5, N₂O concentrations were in the range of 292-360 nmol mol^-1, except for one atypical value (468 nmol mol^-1). The anthropogenic contribution of N₂O is mainly related to the disposal of solid and liquid waste.³³

Diurnal variations in the concentrations were also observed, as shown in Figure 1. For CO₂, the concentrations varied between 490 and 616 µmol mol^-1. The results indicate that for this compound, higher values were observed in the morning and evening hours, which indicates the effect of the rush hours, and the lowest values were obtained at midday, as previously observed in other cities.³⁴ The methane concentrations varied between 1.50 and 1.77 µmol mol^-1, which is in the same range as the natural levels (1.65 µmol mol^-1). A slight diurnal variation due to the boundary layer height and potential photochemical decay was observed. These effects are probably compensated by methane release through evaporation, which, in turn, depends on temperature. N₂O concentrations varied between 335 and 349 nmol mol^-1, with a slight decrease near midday that was probably due to the superposition of two effects: the dilution effect of the boundary layer height and the increase of emissions through the evaporative process.

Figure 1
Concentrations of CO₂, CH₄, and N₂O on January 3, 2012, at the Maracanã Campus of the Rio de Janeiro State University (UERJ).

Correlation coefficients were calculated between CO₂, CH₄ and N₂O and the criteria pollutants' concentrations, which were determined at the monitoring station. The CO₂ concentrations showed correlation coefficients over the 0.6 threshold with all of the primary pollutants, CO (0.84), NO_x (0.91) and inhalable particulate matter (0.66). Because the main emission source in the studied area of the criteria pollutants are vehicles, it could be assumed that this is also the main source of CO₂ and that anthropogenic emissions are the primary source of the urban CO₂ dome. The correlation of CH₄ with the criteria pollutants was poor except for with NO_x (0.60). N₂O showed correlations with CO (0.74) and NO_x (0.78).

Figure 2 shows the results of samples collected from January to December 2012 at the Maracanã campus of Rio de Janeiro State University (UERJ). GHG have seasonal variations, which are called annual cycles, as previously reported by several authors.^35-38 These annual cycles vary according to geographical location, altitude and meteorological conditions. Correlation coefficients were calculated between our data and the meteorological data (temperature, relative humidity and wind speed). These correlations were poor, and the analysis of regression coefficients showed that all of the values were lower than the 0.6 threshold. The highest value was observed for the CO₂-temperature correlation (0.46). A high correlation was observed for CO₂ and CH₄ (0.85), which may be due to a common source or to an indirect correlation with another parameter, such as the mixed layer height. This correlation suggests that anthropogenic activities, particularly vehicle traffic, are an important source of methane in the urban atmosphere.³⁴ PCA analysis highlighted three principal components, P1 (CO₂, CH₄ and temperature), P2 (relative humidity) and P3 (N₂O), which account for 82% of the total variance.

Figure 2
Concentrations of CO₂, CH₄, and N₂O in 2012 at the Maracanã of the Rio de Janeiro State University. Samples were collected at a height of 70 m.

The results in Figure 2 indicate strong seasonal variations of CO₂ and CH₄, with peak values in the warmer months and lower values in winter and with averages of 507.6 ± 13.2 µmol mol^-1 for CO₂, 1.95 ± 0.06 µmol mol^-1 for CH₄ and 325.3 ± 3.4 nmol mol^-1 for N₂O. The values for N₂O were not related to the seasons, with an average standard deviation of 1.0%.

This CO₂ behavior was the opposite of that observed in studies performed in many other cities around the world. In general, for CO₂, the largest values were recorded in autumn, at the end of the biological cycle of plants, and during the winter, and the CH₄ concentrations showed a seasonal variation, with maxima in the summer and minima in the autumn and spring.³⁴ The observed behavior in Rio de Janeiro may be related to the climatic and geographical characteristics. The city has a tropical wet and dry/savanna climate, with a pronounced dry season in the low-sun months, no cold season and a wet season (October-March) during the high-sun months. The city surrounds Tijuca National Park (TNP), a secondary rainforest, which occupies 32 km² (3.5% of the area of Rio de Janeiro), and is home to hundreds of species of plants and wildlife, of which many are threatened by extinction and are found only in the Atlantic Rainforest.³⁹ The concentrations of CO₂ and CH₄ were higher during the high-sun months (November-March). The annual CO₂ cycle with the highest values in summer and the lowest values in winter may reflect the high increase in energy consumption, especially that generated by thermo-electrical units, related to the use of refrigeration systems and the increase in tourism in the city. It may also be related to the growth and decay of vegetation in TNP, which is surrounded by the city. The TNP vegetation is characterized by large trees, palms, ferns, epiphytes and lianas. The more frequent plant families are Leguminosae, Sapotaceae, Bombacaceae, Lecythidaceae, Mraceae and Melastomataceae.⁴⁰ To our knowledge, no studies about CO₂ sequestration have been conducted for this forest. As discussed in the literature, the global estimates of atmospheric CO₂ exchange indicate that the tropics are near equilibrium or are a source with respect to carbon, though there remain considerable uncertainties as to the contribution of different processes.⁴¹

Regarding CH₄, the variations may be related to the input from evaporation of liquid and solid waste from landfill sites located within the city boundaries and from polluted rivers and canals. Additionally, other anthropogenic activities that may be considered are the release of methane by the gas fuel network of the urban area and emissions due to the use of compressed natural gas in taxis and light vehicles.^42,43

The mean concentration values for each compound, calculated as the arithmetic mean of data obtained from January to December 2012, and the concentrations from the pre-industrial period and global values are shown in Table 6.⁴⁴ The pre-industrial global-scale trace-gas concentrations from prior to 1750 are assumed to be practically uninfluenced by human activities such as increasingly specialized agriculture, land clearing, and combustion of fossil fuels. Recent tropospheric concentrations of most gases tend to vary systematically over the course of a year, and the global values given in Table 6 represent averages over a specific 12-month period for all gases (the year of 2013 for CO₂ and 2012 for CH₄ and N₂O).

Table 6
CO₂, CH₄ and N₂O tropospheric concentrations in the preindustrial period (pre-1750), average global data and values determined in Rio de Janeiro (annual averages)

GHG	Pre-1750 / (μmol moL-1)	Recent valuesa / (μmol moL-1)	Rio de Janeiro / (μmol moL-1)
CO2	280	395.4	507.6
CH4	0.70	1.893/1.762	1.95
N2O	0.270	0.326/0.324	0.325

• ^a
  Averages over a specific 12-month period for all gases (the year of 2013 for CO₂ and 2012 for CH₄ and N₂O).⁴⁴

Comparing the data in Table 6, it can be observed that in Rio de Janeiro, the concentration of CO₂, the main compound responsible for the greenhouse effect, is 30% higher than the mean global value, thus confirming the presence of a CO₂ dome over the studied urban area. For CH₄ and N₂O, the values obtained in this work are, respectively, 11.5 and 1% higher than the global concentrations. Values reported in this work should be considered with caution because samplings were always made at noontime on non-rainy workdays and were thus not obtained in the conditions of global values and are not representative of diurnal and weekly variations. However, they do indicate a contribution of urban emissions to CO₂ and CH₄ levels.

Conclusions

The proposed method of sampling provided good results, lower costs and easier implementation in comparison to other sampling devices. It seems to be a good alternative for investigating the CO₂, CH₄ and N₂O concentrations in cities where global monitoring is not performed, such as Brazilian and other Latin American cities.

In the studied urban area in Rio de Janeiro, the concentration of CO₂, which is the main compound responsible for the greenhouse effect, is 30% higher than the mean global value, confirming the presence of a CO₂ dome over the studied urban area. The results for CO₂ and CH₄ show peak values in the warmer months and lower values in winter. This CO₂ behavior is the opposite to that observed in studies performed in many other cities around the world and may reflect the summer increase in energy use due to the higher temperatures and the vegetation cycle in the rainforest, which is part of the urban area. These particular characteristics suggest that further study of the role of the urban rainforest, wetlands and rivers in the air quality of the city may be significant and that the carbon cycle of the vegetation in the rain forest should be studied.

Supplementary Information

Supplementary Information (Tables S1 and S2 and Figures S1-S5) is available free of charge at http://jbcs.sbq.org.br as PDF file.

https://minio.scielo.br/documentstore/1678-4790/RtfCqmHwnTh9rHkfvWRBjyr/aa358aca80457a86e9062a50fbba8b337ae0107b.pdf

Acknowledgments

The authors thank the Rio de Janeiro State Foundation for Research Support (FAPERJ) and National Research Council (CNPq) for their partial financial support. They also thank the Rio de Janeiro Environmental Municipal Secretary (SMAC) for providing some data.

References

• ¹ http://www.ncdc.noaa.gov/sotc/global/2014/12, accessed in November 2015.
  » http://www.ncdc.noaa.gov/sotc/global/2014/12
• ² http://www.esrl.noaa.gov/gmd/, accessed in November 2015.
  » http://www.esrl.noaa.gov/gmd/
• ³ http://www.wmo.int/pages/themes/climate/causes_of_climate_change.php, accessed in November 2015.
  » http://www.wmo.int/pages/themes/climate/causes_of_climate_change.php
• ⁴ Philander, S. G., ed.; Encyclopedia of Global Warming and Climate Change, 2^nd ed.; Sage: London, 2012.
• ⁵ http://brics6.itamaraty.gov.br/pt_br/sobre-o-brics/dados-economicos, accessed in November 2015.
  » http://brics6.itamaraty.gov.br/pt_br/sobre-o-brics/dados-economicos
• ⁶ http://data.worldbank.org/country/, accessed in April 2015.
  » http://data.worldbank.org/country/
• ⁷ van Groenigen, J. K.; Osenberg, C. W.; Hungate, B. A.; Nature 2011, 475, 214.
• ⁸ Zervas, G.; Tsiplakou, E.; Atmos. Environ. 2012, 49, 13.
• ⁹ Salm, J.; Maddison, M.; Tammik, S.; Soosaar, K.; Truu, J.; Mander, U.; Hydrobiologia 2012, 692, 41.
• ¹⁰ Chen, G. C.; Tam, N. F. Y.; Ye, Y.; Sci. Total Environ. 2010, 408, 2761.
• ¹¹ Sneath, R. W.; Beline, F.; Hilhorst, M. A.; Peu, P.; Agric. Ecosyst. Environ. 2006, 112, 122.
• ¹² Villalba, G.; Gemechu, E. D.; Energy Policy 2011, 39, 1363.
• ¹³ Sames, P. C.; Kopke, M.; Procedia Soc. Behav. Sci. 2012, 48, 1.
• ¹⁴ Demarty, M.; Bastien, J.; Energy Policy 2011, 39, 4197.
• ¹⁵ Hao, H.; Wang, H.; Ouyang, M.; Energy Policy 2012, 43, 244.
• ¹⁶ Reynolds, C. C. O.; Kandikar, M.; Badami, M. G.; Transport. Res. D-Tr. E. 2011, 16, 160.
• ¹⁷ Graham, L. A.; Rideout, G.; Rosenblatt, D.; Hendren, J.; Atmos. Environ. 2008, 42, 4665.
• ¹⁸ Chakraborty, N.; Mukherjee, I.; Santra, A. K.; Chowdhury, S.; Chakraborty, S.; Bhattacharya, S.; Mitra, A. P.; Sharma, C.; Atmos. Environ. 2008, 42, 1073.
• ¹⁹ Rio, 2011, http://www.rio.rj.gov.br/dlstatic/10112/1712030/DLFE-222982.pdf/NelsonSINVENTARIOFINALMAC_Resumo_Geral_Inv_e_Cenario_v05abr_E.pdf, accessed in November 2015.
  » http://www.rio.rj.gov.br/dlstatic/10112/1712030/DLFE-222982.pdf/NelsonSINVENTARIOFINALMAC_Resumo_Geral_Inv_e_Cenario_v05abr_E.pdf
• ²⁰ Finalyson-Pitts, B. J.; Pitts Jr., J. N.; Chemistry of the Upper and Lower Atmosphere: Theory, Experiments, and Applications; Academic Press: California, 2000.
• ²¹ http://www.epa.gov/ttnamti1/files/ambient/airtox/to-14ar.pdf, accessed in November 2015.
  » http://www.epa.gov/ttnamti1/files/ambient/airtox/to-14ar.pdf
• ²² http://www.epa.gov/ttnamti1/files/ambient/airtox/to-15r.pdf, accessed in November 2015.
  » http://www.epa.gov/ttnamti1/files/ambient/airtox/to-15r.pdf
• ²³ Coutts, A. M.; Beringer, J.; Tapper, N. J.; Atmos. Environ. 2007, 41, 51.
• ²⁴ George, K.; Ziska, L. H.; Bunce, J. A.; Quebedeaux, B.; Atmos. Environ. 2007, 41, 7654.
• ²⁵ Idso, S. B.; Idso, C. D.; Balling, R. C.; Atmos. Environ. 2002, 36, 1655.
• ²⁶ http://www.cidades.ibge.gov.br/xtras/perfil.php?lang=&codmun=330455&search =||infogr%E1ficos:-informa%E7%F5es-completas, accessed in November 2015.
  » http://www.cidades.ibge.gov.br/xtras/perfil.php?lang=&codmun=330455&search =||infogr%E1ficos:-informa%E7%F5es-completas
• ²⁷ http://www.denatran.gov.br/frota2013.htm, accessed in November 2015.
  » http://www.denatran.gov.br/frota2013.htm
• ²⁸ Oliveira, R. L.; Loyola, J.; Minho, A. S.; Quiterio, S. L.; Azevedo, D. A.; Arbilla, G.; Bull. Environ. Contam. Toxicol. 2014, 93, 781.
• ²⁹ http://tempo.cptec.inpe.br/aeroportos/pt accessed in November 2015.
  » http://tempo.cptec.inpe.br/aeroportos/pt
• ³⁰ Kelly, T. J.; Holdren, M. W.; Environ. Sci. Technol. 1995, 44, 2497.
• ³² Idso, C. D.; Idso, S. B.; Balling, R. C.; Atmos. Environ. 2001, 35, 995.
• ³³ http://www.centroclima.coppe.ufrj.br/new2/ccpdf/inventario_rj.1.pdf, accessed in November 2015.
  » http://www.centroclima.coppe.ufrj.br/new2/ccpdf/inventario_rj.1.pdf
• ³⁴ Haiduc, I.; Beldean-Galea, M. S.; Variation of Greenhouse Gases in Urban Areas-Case Study: CO2, CO and CH4 in Three Romanian Cities, Air Quality-Models and Applications; Popovic, D., ed.; ISBN: 978-953-307-307-1, InTech, 2011. Available from: http://www.intechopen.com/books/air-quality-models-and-applications/variation-of-greenhouse-gases-in-urban-areas-case-study-co2-co-and-ch4-in-three-romanian-cities accessed in November 2015.
  » http://www.intechopen.com/books/air-quality-models-and-applications/variation-of-greenhouse-gases-in-urban-areas-case-study-co2-co-and-ch4-in-three-romanian-cities
• ³⁵ Angelbratt, J.; Mellqvist, J.; Blumenstck, T.; Borsdorff, T.; Brohede, S.; Duchatelet, P.; Forster, F.; Hase, F.; Mahieu, E.; Murtagh, D.; Petersen, A. K.; Schneider, M.; Sussmann, R.; Urban, J.; Atmos. Chem. Phys. 2011, 11, 6167.
• ³⁶ Dlugokencky, E. J.; Houweling, S.; Bruhwiler, L.; Masarie, K. A.; Lang, P. M.; Miller, J. B.; Tans, P. P.; Geophys. Res. Lett. 2003, 30, 1992.
• ³⁷ Haszpra, L.; Barcza, Z.; Hidy, D.; Szilagyi, I.; Dlugokencky, E.; Tans, R.; Atmos. Environ. 2008, 42, 8707.
• ³⁸ http://www.ipcc.ch/pdf/assessment-report/ar5/wg1/WG1AR5_Chapter02_FINAL.pdf accessed in November 2015.
  » http://www.ipcc.ch/pdf/assessment-report/ar5/wg1/WG1AR5_Chapter02_FINAL.pdf
• ³⁹ Pougy, N.; Martins, E.; Verdi, M.; de Oliveira, J. A.; Maurenza, D.; Amaro, R.; Martinelli, G.; Nat. Conservação 2014, 12, 170.
• ⁴⁰ Freitas, S. R.; Neves, C. L.; Chernicharo, P.; Braz. J. Biol. 2006, 66, 975.
• ⁴¹ Richey, J. E.; Melack, J. M.; Aufdenkampe, A. K.; Ballester, V. M.; Hess, L. L.; Nature 2002, 416, 617.
• ⁴² Corrêa, S. M.; Arbilla, G.; Marques, M. R. C.; de Oliveira, K. M. P. G.; Atmos. Poll. Res. 2012, 3, 163.
• ⁴³ Corrêa, S. M.; Arbilla, G.; Martins, E. M.; Quiterio, S. L.; Guimaraes, C. S.; Gatti, L. V.; Atmos. Environ. 2010, 44, 2302.
• ⁴⁴ http://cdiac.ornl.gov/pns/current_ghg.html, accessed in November 2015.
  » http://cdiac.ornl.gov/pns/current_ghg.html

Publication Dates

• Publication in this collection
  Apr 2016

History

• Received
  01 Sept 2015
• Accepted
  25 Nov 2015