**3. Results and discussion**

## **3.1. Concentrations of PM mass**

Mean PM mass concentrations and associated standard deviations and ranges as derived from the two low-volume samplers are shown in Table 1. The results showed that mean mass concentration of PM2.5 and PM10 aerosols during the campaign were 13±3.5 μg/m3 and 16±2.3 μg/m3, respectively. The percentages of PM2.5 mass in PM10 size fraction (Fig. 2) found to range from 44–99% with a mean of 83±29%. These results indicate that most of PM mass was in PM2.5 size fraction. High PM2.5/PM10 ratios for PM mass indicate that there is small contribution from soil dust, which is known to be mostly associated with PM10 aerosols. Currently in Tanzania, the ambient air quality standard limit values for inhalable particulate matter are 60 to 90 μg/m3 for PM10 (TBS, 2006). The mean concentrations for PM10 mass at our site in Morogoro were below these average limit values. In addition, the current data sets were in line with levels reported in our previous studies (Mkoma et al., 2009a,b; Mkoma et al., 2010). Nevertheless, when compared PM mass data from our rural site in Tanzania are in line with few available other data sets for rural sites in Southern Africa (Nyanganyura et al., 2007). They are also comparable to or lower to other sites in Europe and Asia (Van Dingenen et al., 2004; Gu et al., 2010; Maenhaut et al., 2011; Ram & Sarin, 2011).

## **3.2. Concentrations of carboxylates ions**

206 Atmospheric Aerosols – Regional Characteristics – Chemistry and Physics

weightings were done under these conditions.

anions and 0.063 and 0.252 ng/L for cations**.**

**3. Results and discussion** 

**3.1. Concentrations of PM mass** 

thermometer clock at a temperature of 20 °C and relative humidity of 40% for 48 h and the

For determination of carboxylic acids and water-soluble ions one-half of 12.88 cm2 portions punched from of each PTFE filter was extracted using 5 ml Milli-Q ultrapure water (resistivity of 18.2 MΩcm, Barnstead International, USA) in a shaker tubes Model AT56 (Fanem Ltd, Sao Paulo, Brazil) for 5 minutes, followed by filtering through Polytetrafluoroethylene (PTFE) filter (0.45 μm pore size, Sartorius Stedim, Germany). The concentrations of aqueous extracts were determined by Dionex ion chromatography ICS 1100 and ICS 2100 for acids/anions and cations respectively which was equipped with an auto sampler (Dionex ICS Series AS-DV). An analytical column AS16 (3 x 50 mm) with AG16 guard column (3 x 50 mm) and CSRS-300 I (2 mm) suppressor in ion-exchange mode was used to determine carboxylates (monocarboxylates: formate and acetate; dicarboxylates: oxalate, malonate, succinate, and maleate; ketocarboxylate: pyruvate) and water-soluble anions (chloride Cl−, nitrate NO3− and sulphate SO42−). The eluent gradient programme was sweeping from 6.0 to 8.0 mmol/L KOH in 35 minutes under flow rate of 0.38 μL/min, except for acetic acid which was determined in another run, reducing injection time to avoid overlap of peaks. For determination of water-soluble cations (NH4+, Na+, K+, Mg2+ and Ca2+) an analytical column CS16 and Guard column CG16 (both 3 x 50 mm) and CSRS-I (2 mm) suppressor in a chemical mode were used. An eluent of 17.5 mmol/L H2SO4 was used at flow rate of 0.35 μL/min. The injection volume was 25 μL for all detection. Peak identification was confirmed based on a match of ion chromatograph retention times and standard samples. Limit of detection determined as mean equal to 3 times standard deviation of the field blank value corresponded to a range of 0.008 to 0.017 ng/L for carboxylates, 0.008 to 0.023 ng/L for anions and 0.021 to 0.083 ng/L for cations. Limits of quantification were between 0.026 and 0.058 ng/L for carboxylates, 0.028 and 0.078 ng/L for

Mean PM mass concentrations and associated standard deviations and ranges as derived from the two low-volume samplers are shown in Table 1. The results showed that mean mass concentration of PM2.5 and PM10 aerosols during the campaign were 13±3.5 μg/m3 and 16±2.3 μg/m3, respectively. The percentages of PM2.5 mass in PM10 size fraction (Fig. 2) found to range from 44–99% with a mean of 83±29%. These results indicate that most of PM mass was in PM2.5 size fraction. High PM2.5/PM10 ratios for PM mass indicate that there is small contribution from soil dust, which is known to be mostly associated with PM10 aerosols. Currently in Tanzania, the ambient air quality standard limit values for inhalable particulate matter are 60 to 90 μg/m3 for PM10 (TBS, 2006). The mean concentrations for PM10 mass at our site in Morogoro were below these average limit values. In addition, the current data sets were in line with levels reported in our previous studies (Mkoma et al., 2009a,b; Mkoma et al., 2010). Nevertheless, when compared PM mass data from our rural Table 1 present mean total concentrations and range of carboxylates (TCAs) which were 23.7±6.5 ng/m3 (range: 13.3-36.5 ng/m3) in PM2.5 and 36.4±12 ng/m3 (range: 10.7-58.2 ng/m3) in PM10 aerosols. Oxalate and malonate were most abundant carboxylates in PM2.5 accounting for 32.5% and 31.85% of total carboxylates, respectively, whereas in PM10 acetate was most abundant accounted for 62.5% of total carboxylates followed by oxalate which accounted for 32.6% of total carboxylates. Other studies have also reported oxalates to be most abundant carboxylate in aerosol samples (Mochida et al., 2003; Warneck, 2003). Pyruvate was also found in substantial amount and formate the least abundant counting on average 3% of total carboxylates in each of the aerosol fractions. Succinate and malonate were below detection limit in PM2.5 and PM10 aerosols, respectively. The total carboxylates accounted for 0.18% to total PM2.5 mass and 0.22% to PM10 mass. In comparison with other studies, the mean concentrations of all measured carboxylates in Tanzania were lower to those reported in urban and rural sites around the world (Souza et al., 1999; Kerminen et al., 2000; Yao et al., 2003; Kawamura & Yasui, 2005).

## **3.3. Water-soluble inorganic ions and ratios**

Chemical characteristics of water-soluble inorganic ions and their relative abundances in PM2.5 and PM10 aerosols are also shown in Table 1. In both aerosol fractions, water-soluble Mg2+ was the most important cation and SO42– the main anionic species. On average Mg2+ accounted for 44.4% of total water-soluble ions in PM2.5 and 24.7% in PM10 whereas SO42– accounted for 22.8% and 35.2% of total ions in PM2.5 and PM10, respectively. High levels of crustal element Mg2+ together with Ca2+ are essentially attributable to soil/mineral dust dispersal. As to reasonable NH4+ levels (8% of total ions) in PM2.5, this may be due to presence of ammonia gas from biomass burning especially during smoldering combustion (Andreae & Merlet, 2001) and from agricultural activities in particular cattle raising (Street et al., 2003; Stone et al., 2010). Water-soluble K+, a good indicator for biomass burning, was second most abundant cation in PM2.5 accounted for 10.6% of total water-soluble ions.

For SO42– the higher levels could be attributed to its efficient formation by in-cloud processing of SO2 (Yao et al., 2003) and from secondary formation processes (Allen et al., 2004). As to low NO3– levels, this is likely due to the fact that the site is rural with little or no traffic and undoubtedly there are less anthropogenic emissions of precursor gas NOx. Also as to low concentrations of Na+ which is mainly derived from sea-salt, this is presumably due to long distance (about 200 km) from the Indian Ocean to our sampling site. The observed levels for water-soluble ions are comparable with those reported in our previous work in Morogoro (Mkoma et al., 2009a; Mkoma et al., 2010). It appears that the levels of


SO42−, NO3−, and NH4+ in PM10 fractions are substantially lower in Tanzania than at European rural sites (Putaud et al., 2004) and Asia (Aggarwal & Kawamura, 2009; Pavuluri et al., 2011).

Characteristics of Low-Molecular Weight

0

40

80

120

Conc. of nss-SO4 (ng/m3

)

160

200

Carboxylic Acids in PM2.5 and PM10 Ambient Aerosols From Tanzania 209

heterogeneous reaction of airborne sea-salt with acidic gases and aerosol species

Time series of PM mass, selected acids and ions species in PM2.5 and PM10 fractions as a function of sampling time are shown in Figs. 2 and 3. Nss-SO42– in Fig. 2 was hereby obtained by subtracting sea-salt contribution from measured SO42– data. Sea-salt contribution of SO42– was obtained as 0.252Na+, whereby Na+ is the measured concentration of Na+ and 0.252 is SO42–/Na+ ratio in the bulk seawater composition given by Riley and Chester (1971). As can be observed in Fig. 2, selected species in both size fractions showed no clear trends that can be noted but showed slightly variation during sampling period especially for PM10 aerosols. The observed behaviour of the species could be resulted from variations in sources strengths and meteorological conditions, such as mixing height. Additionally, high relative humidity (mean: 73%) during the campaign could serve as

In this study, oxalate concentrations were high to a factor of 10 than those of formate during the sampling period and in both PM2.5 and PM10 aerosol particles. These results indicate that formate was mainly from photochemical oxidation, while oxalates might have other sources besides photochemical oxidation. On the other hand, the concentrations of acetate were high than those of oxalate. Acetic acid in the atmosphere has been reported to be produced by oxidations of longer-chain dicarboxylic acids (Kawamura et al., 1996). Therefore, the observed acetate levels suggest that longer-chain dicarboxylic acids were possibly available at our site. Unfortunately, no data for high molecular weight dicarboxylic

PM2.5 mass Acetate Formate

Pyruvate nss-SO4

**3.4. Time series of PM mass and selected aerosol species** 

removal mechanisms hence lead to a daily variation in carboxylates levels.

**Figure 2.** Time series of PM mass, carboxylates and nss-SO42− in PM2.5 fraction at Morogoro

26 27 28 29 30 1 2 3 4 5 6 7 8 9 10

Day of April and May 2011

(Millero, 2006).

acids measured for the campaign.

0

10

20

30

Conc.of carboxylates (ng/m3) &

PM mass (µg/m3

)

40

50

Rel. Ab. = Relative abundances

**Table 1.** Mean concentrations, ranges and relative abundances (%) of carboxylates and water-soluble inorganic ions in PM2.5 and PM10 aerosols from Morogoro.

To determine the impact of marine sources on chemical composition of aerosol particles in PM2.5 and PM10 fractions, sea-salt ratios were calculated for each inorganic ion using Na as a reference element, assuming all Na to be of marine origin. The ratios for Cl–/Na+, SO42–/Na+, K+/Na+, Mg2+/Na+ and Ca2+/Na+ in PM2.5 were 0.15 (0.25), 6.48 (1.81), 2.95 (0.04), 12.97 (0.04), 2.44 (0.12), respectively. The corresponding values in PM10 were 0.10 (0.25), 2.51 (1.81), 0.43 (0.04), 1.68 (0.04), 0.75 (0.12), respectively. Values in brackets represent average ratios for each ion in sea-water (Brewer, 1975). Larger ratios of ions indicate incorporation of non-marine constituents in aerosols. As to low mean Cl–/Na+ ratios than sea-water ratio indicates that a minor fraction of Na+ may be contributed from other sources such as mineral dust. But also low ratio could be due to modifications of sea-salt fraction by non-marine constituents. Chloride loss may be explained by heterogeneous reaction of airborne sea-salt with acidic gases and aerosol species (Millero, 2006).

## **3.4. Time series of PM mass and selected aerosol species**

208 Atmospheric Aerosols – Regional Characteristics – Chemistry and Physics

et al., 2011).

PM mass (μg/m3)

Carboxylates ions (ng/m3)

Water-soluble ions (ng/m3)

Rel. Ab. = Relative abundances

inorganic ions in PM2.5 and PM10 aerosols from Morogoro.

SO42−, NO3−, and NH4+ in PM10 fractions are substantially lower in Tanzania than at European rural sites (Putaud et al., 2004) and Asia (Aggarwal & Kawamura, 2009; Pavuluri

Formate, FA 0.71 0.30 0.38 1.27 3.00 1.2 0.6 0.5 2.6 3.4 Acetate, Ac 5.4 2.2 0.4 7.8 22.9 22.7 3.3 16.3 27.5 62.5 Oxalate, Oxa 7.7 2.7 4.7 13.1 32.5 11.8 7.2 4.5 31.0 32.6 Malonate, Mal 7.5 3.9 4.8 18.3 31.8 - - - - - Succinate, Suc - - - - - 1.6 2.4 0.2 6.5 4.5 Pyruvate, Pyr 2.4 0.7 1.5 3.8 9.9 2.2 0.7 0.9 3.3 6.1 Total carboxylate 23.7 6.5 13.3 36.5 - 36.4 12.0 10.7 58.2 -

NH4+ 37.8 11.7 21.0 66.5 8.4 26.2 12.5 10.7 54.0 4.1 NO3– 4.5 1.6 1.2 8.0 1.0 25.1 12.4 10.5 52.0 3.9 SO42– 102 27 69.1 160 22.8 237 125 38.8 487 36.6 Cl– 2.3 0.4 1.6 3.1 0.5 9.6 5.7 3.3 20.2 1.5 Na+ 15.6 2.5 13.2 21.5 3.5 98.5 42.0 41.1 174.8 15.2 K+ 47.5 24.1 22.0 97.0 10.6 37.6 28.2 6.3 88.5 5.8 Mg2+ 199 33.7 155 265 44.4 158 69 16.4 228 24.5 Ca2+ 39.3 8.5 28.1 58.8 8.8 56.2 42.9 1.0 107 8.7 Total ions 448 88 348 585 - 646 214 256 1108 -

**Table 1.** Mean concentrations, ranges and relative abundances (%) of carboxylates and water-soluble

To determine the impact of marine sources on chemical composition of aerosol particles in PM2.5 and PM10 fractions, sea-salt ratios were calculated for each inorganic ion using Na as a reference element, assuming all Na to be of marine origin. The ratios for Cl–/Na+, SO42–/Na+, K+/Na+, Mg2+/Na+ and Ca2+/Na+ in PM2.5 were 0.15 (0.25), 6.48 (1.81), 2.95 (0.04), 12.97 (0.04), 2.44 (0.12), respectively. The corresponding values in PM10 were 0.10 (0.25), 2.51 (1.81), 0.43 (0.04), 1.68 (0.04), 0.75 (0.12), respectively. Values in brackets represent average ratios for each ion in sea-water (Brewer, 1975). Larger ratios of ions indicate incorporation of non-marine constituents in aerosols. As to low mean Cl–/Na+ ratios than sea-water ratio indicates that a minor fraction of Na+ may be contributed from other sources such as mineral dust. But also low ratio could be due to modifications of sea-salt fraction by non-marine constituents. Chloride loss may be explained by

Mean SD Min. Max. Rel. Ab. Mean SD Min. Max. Rel. Ab.

13.3 3.5 8.2 19.5 - 16.2 2.3 12.5 20.5 -

Species PM2.5 PM10

Time series of PM mass, selected acids and ions species in PM2.5 and PM10 fractions as a function of sampling time are shown in Figs. 2 and 3. Nss-SO42– in Fig. 2 was hereby obtained by subtracting sea-salt contribution from measured SO42– data. Sea-salt contribution of SO42– was obtained as 0.252Na+, whereby Na+ is the measured concentration of Na+ and 0.252 is SO42–/Na+ ratio in the bulk seawater composition given by Riley and Chester (1971). As can be observed in Fig. 2, selected species in both size fractions showed no clear trends that can be noted but showed slightly variation during sampling period especially for PM10 aerosols. The observed behaviour of the species could be resulted from variations in sources strengths and meteorological conditions, such as mixing height. Additionally, high relative humidity (mean: 73%) during the campaign could serve as removal mechanisms hence lead to a daily variation in carboxylates levels.

In this study, oxalate concentrations were high to a factor of 10 than those of formate during the sampling period and in both PM2.5 and PM10 aerosol particles. These results indicate that formate was mainly from photochemical oxidation, while oxalates might have other sources besides photochemical oxidation. On the other hand, the concentrations of acetate were high than those of oxalate. Acetic acid in the atmosphere has been reported to be produced by oxidations of longer-chain dicarboxylic acids (Kawamura et al., 1996). Therefore, the observed acetate levels suggest that longer-chain dicarboxylic acids were possibly available at our site. Unfortunately, no data for high molecular weight dicarboxylic acids measured for the campaign.

**Figure 2.** Time series of PM mass, carboxylates and nss-SO42− in PM2.5 fraction at Morogoro

Characteristics of Low-Molecular Weight

Carboxylic Acids in PM2.5 and PM10 Ambient Aerosols From Tanzania 211

emissions and crustal source could be an important source for K+ aerosols at this site with

**Figure 4.** Mean contribution (%) of PM2.5 aerosols mass and selected aerosol species in PM10 fraction

NH4

NO3

nss-SO4

Cl

Na

K

Mg

Ca

Correlation coefficients of PM mass, carboxylates and source indicators, shown in Table 2 were performed in order to understand their possible sources and formation mechanisms. The selected source indicators include K+ for biomass burning and vegetation emissions, Na+ and Cl− for sea spray or waste burning, and SO42− for secondary formation of different mechanisms. Temperature and wind speed have been used as additional parameters to illustrate the atmospheric behaviours of carboxylic acids. In this study K+ had good correlation with formate (r2=53) and moderate to poorly correlations with other carboxylates in PM10. This indicates that formate could be originated from biomass and/or waste burning emissions but other carboxylates are considered to have other important sources than biomass burning. It can also be observed from Table 2 that there were possible similar sources for formate and other carboxylates (oxalate, Succinate and pyruvate) as verified by good correlation between them in PM2.5 and PM10 aerosols. Pyruvate shows good correlation with acetate (r2 = 54) and succinate (r2=51) in PM10 aerosols. These indicate a feature of photochemical decomposition of succinic acid (Yao et

Sea-salt derived aerosols have been reported to have particle with aerodynamic diameter between 1 and 5 μm (Kerminen et al., 2000). In this study, we found Na+ has pronounced

**3.6. Sources of carboxylates and water-soluble ions in aerosols** 

Pyruvate

small impact from biomass burning activities.

during the campaign in Morogoro.

PM mass

Formate

Acetate

Oxalate

0

20

40

Mean %

60

80

100

*3.6.1. Correlation analysis* 

al., 2002).

**Figure 3.** Time series of PM mass, carboxylates and Na+ and Cl− in PM10 fraction at Morogoro

## **3.5. PM2.5 to PM10 ratios**

The average PM2.5 (fine) to PM10 (coarse) percentage ratios and associated standard deviations for PM mass, carboxylates and various water-soluble inorganic ions are shown in Fig. 4. The ratios were calculated on the basis of data for PM2.5 and PM10 samples taken in parallel and then averaged over all samples from the sampling period. The mean fine to coarse ratios for all species with exception of those for acetate, Na+, Ca2+, NO3– and Cl– were predominantly associated with fine fraction (for more than 55%). High fine/coarse ratio for PM mass may be due to a less contribution from soil dust, which is known to be mostly associated with coarse particles. For carboxylates, high ratios (even larger than 70%) are considered to be attributed from secondary organic aerosols (SOA), biomass burning activities and high temperature (average: 26.8 °C during sampling period). Concentrations of oxalate in PM2.5 showed strong correlations (r2 = 0.70) with those in PM10 aerosols. The slope of linear regression equations (PM2.5 = 2.48 x PM10) indicated that oxalate was mainly present in fine fraction during sampling period. On the other hand, different size distributions between oxalate and acetate could be related to their different physical characteristics. Acetate in PM2.5 fraction could easily volatilize (more volatile than oxalate) to gas phase, part of which could be absorbed on PM10 particles.

For water-soluble inorganic ions, as expected, sea-salt elements (Na, Cl) and indicator element for crustal matter (Ca) were predominantly (for more than 62%) associated with PM10 aerosols. NH4+ and nss-SO42– were mainly present in the fine aerosols suggesting that these species originated from high temperature sources and/or gas-to-particle conversion. The nss-SO42– is due to oxidation of SO2, which is predominantly from anthropogenic origin (e.g. biomass burning). A well-known indicator for biomass burning, K was associated with the fine particles (about 100%) suggesting vegetative emissions and crustal source could be an important source for K+ aerosols at this site with small impact from biomass burning activities.

**Figure 4.** Mean contribution (%) of PM2.5 aerosols mass and selected aerosol species in PM10 fraction during the campaign in Morogoro.

## **3.6. Sources of carboxylates and water-soluble ions in aerosols**

## *3.6.1. Correlation analysis*

210 Atmospheric Aerosols – Regional Characteristics – Chemistry and Physics

**3.5. PM2.5 to PM10 ratios** 

0

20

40

Conc. of carboxylates

(ng/m3) & PM mass (µg/m3

)

60

80

**Figure 3.** Time series of PM mass, carboxylates and Na+ and Cl− in PM10 fraction at Morogoro

to gas phase, part of which could be absorbed on PM10 particles.

The average PM2.5 (fine) to PM10 (coarse) percentage ratios and associated standard deviations for PM mass, carboxylates and various water-soluble inorganic ions are shown in Fig. 4. The ratios were calculated on the basis of data for PM2.5 and PM10 samples taken in parallel and then averaged over all samples from the sampling period. The mean fine to coarse ratios for all species with exception of those for acetate, Na+, Ca2+, NO3– and Cl– were predominantly associated with fine fraction (for more than 55%). High fine/coarse ratio for PM mass may be due to a less contribution from soil dust, which is known to be mostly associated with coarse particles. For carboxylates, high ratios (even larger than 70%) are considered to be attributed from secondary organic aerosols (SOA), biomass burning activities and high temperature (average: 26.8 °C during sampling period). Concentrations of oxalate in PM2.5 showed strong correlations (r2 = 0.70) with those in PM10 aerosols. The slope of linear regression equations (PM2.5 = 2.48 x PM10) indicated that oxalate was mainly present in fine fraction during sampling period. On the other hand, different size distributions between oxalate and acetate could be related to their different physical characteristics. Acetate in PM2.5 fraction could easily volatilize (more volatile than oxalate)

26 27 28 29 30 1 2 3 4 5 6 7 8 9 10

PM10 mass Acetate Formate Pyruvate Cl Na

0

50

100

Conc. of Na (µg/m3

)

150

200

Day of April and May 2011

For water-soluble inorganic ions, as expected, sea-salt elements (Na, Cl) and indicator element for crustal matter (Ca) were predominantly (for more than 62%) associated with PM10 aerosols. NH4+ and nss-SO42– were mainly present in the fine aerosols suggesting that these species originated from high temperature sources and/or gas-to-particle conversion. The nss-SO42– is due to oxidation of SO2, which is predominantly from anthropogenic origin (e.g. biomass burning). A well-known indicator for biomass burning, K was associated with the fine particles (about 100%) suggesting vegetative Correlation coefficients of PM mass, carboxylates and source indicators, shown in Table 2 were performed in order to understand their possible sources and formation mechanisms. The selected source indicators include K+ for biomass burning and vegetation emissions, Na+ and Cl− for sea spray or waste burning, and SO42− for secondary formation of different mechanisms. Temperature and wind speed have been used as additional parameters to illustrate the atmospheric behaviours of carboxylic acids. In this study K+ had good correlation with formate (r2=53) and moderate to poorly correlations with other carboxylates in PM10. This indicates that formate could be originated from biomass and/or waste burning emissions but other carboxylates are considered to have other important sources than biomass burning. It can also be observed from Table 2 that there were possible similar sources for formate and other carboxylates (oxalate, Succinate and pyruvate) as verified by good correlation between them in PM2.5 and PM10 aerosols. Pyruvate shows good correlation with acetate (r2 = 54) and succinate (r2=51) in PM10 aerosols. These indicate a feature of photochemical decomposition of succinic acid (Yao et al., 2002).

Sea-salt derived aerosols have been reported to have particle with aerodynamic diameter between 1 and 5 μm (Kerminen et al., 2000). In this study, we found Na+ has pronounced

amount in PM10 aerosol and to slightly extent Cl−, suggesting sea spray could be one of the contributing sources of the aerosol components at the site. But even though Na+ correlate well (r2=73) with Cl−, the calculated Cl− to Na+ mass ratio to sea-salt component in aerosol particles had mean value between 0.15 (PM2.5) and 0.10 (PM10). This suggest that continental contributions was most important than marine contribution since Cl−/Na+ ratio in marine aerosols varies between 1.0 and 1.7 (Chesselet et al., 1972).

Characteristics of Low-Molecular Weight

Carboxylic Acids in PM2.5 and PM10 Ambient Aerosols From Tanzania 213

The ratio of acetic to formic acid has been used as good indicator of contributions of primary (high ratio) and secondary sources (low ratio) to carboxylic acids (Talbot et al., 1988, 1990; Grosjean, 1992). As can be seen in Table 3, low acetate/formate ratios for both PM2.5 and PM10 aerosols particles indicate that secondary formation was an important contributing source of carboxylates at our site. This suggestion is supported by the fact that high mean average temperature during sampling period (mean: 26.8 oC) might be controlling factor in determining the contribution of primary and secondary sources to these carboxylates. However, there are various types of the atmospheric reactions forming carboxylic acids (e.g. formic, acetic, and oxalic) in urban and near urban atmospheres, which include oxidation of unsaturated fatty acids originating from cooking activities, ozone oxidation of olefins emitted from vehicular exhausts (Scheff & Wadden, 1993) and oxidation of aromatic

The ratio of oxalic acid to total dicarboxylic acid (for this study oxalic, malonic, succinic acids) can be used to evaluate aging process of organic aerosols (Kawamura & Sakaguchi, 1999), because diacid such as oxalic acid can be produced by oxidations of longer-chain dicarboxylic acids (Kawamura et al., 1996). In this study oxalate to total dicarboxylates ratios show low values in both aerosol fractions, indicating that aerosols emitted from various sources and transported to this site were less and equally aged. Since there relative humidity was high during the campaign (up to 73% on average), it is supposed that oxalate was also produced in aqueous phase. Aqueous phase chemistry in aerosol and/or cloud droplets is important in production of oxalic acid (Warneck, 2003). On the other hand, mean ratio of oxalate to K+ in PM2.5 aerosols was 0.19±0.08, somewhat close to or higher than those reported range (0.03−0.1) for flaming and smoldering phases in burning plumes (Yamasoe et al., 2000). This suggests that carboxylates might be originated from biogenic sources with

Ratio PM2.5 PM10

Acetate/Formate 0.24±0.31 0.07−1.07 0.05±0.03 0.03−0.10 Oxalate/Total dicarboxylates 0.33±0.08 0.23−0.49 0.33±0.17 0.15−0.83 Oxalate/K+ 0.19±0.08 0.07−0.36 − − **Table 3.** Mean ratios and ranges for carboxylates and K+ in PM2.5 and PM10 aerosols in Morogoro.

PM2.5 and PM10 aerosols samples were collected from a rural site Morogoro, Tanzania and analysed for low molecular weight carboxylates and water-soluble inorganic ions. Oxalate and malonate were dominant species in PM2.5 while acetate was most prominent species in

Mean±Stdev Range Mean±Stdev Range

*3.6.2. Concentrations ratios* 

hydrocarbons (Kawamura & Ikushima, 1993).

contribution from biomass burning emissions.

**4. Conclusion** 

Sulphate has been used as reference to investigate major formation routes of carboxylic acids (Yu et al., 2005). As shown in Table 2, formate and pyruvate showed good correlation with SO42− in PM2.5, suggesting that in-cloud and heterogeneous formations play an important role in the formation of carboxylates. On the other hand, poor correlation of malonic with SO42− in PM2.5 suggests that possibly the acid is volatile at ambient temperatures (Peng et al., 2001). Acetate and oxalate showed poor correlations with SO42− in both aerosol fractions, indicating that they mainly originated from primary emissions sources and/or the atmospheric processes different from those of SO42−. This is contrary to what have been observed in other studies that in-cloud and heterogeneous formations can yield a good correlation between oxalate and SO42− (Yu et al., 2005).

Wind speed poorly correlated with most carboxylates except with acetate (r2=51) in PM10 aerosols. This indicates that in addition to secondary formation carboxylates were mainly generated from local sources, while acetate might be related to long range aerosols transport to the sampling site. It should also be noted that primary emissions are major sources of precursors for most carboxylic acids (Kawamura & Yasui, 2005).


WS = Wind speed

**Table 2.** Correlation coefficients for PM mass, carboxylates, selected ions and wind speed in PM2.5 (upper diagonal triangle) and PM10 fractions (lower diagonal triangle) in Morogoro. Correlation coefficients that are larger than 0.50 are indicated in bold.

## *3.6.2. Concentrations ratios*

212 Atmospheric Aerosols – Regional Characteristics – Chemistry and Physics

in marine aerosols varies between 1.0 and 1.7 (Chesselet et al., 1972).

yield a good correlation between oxalate and SO42− (Yu et al., 2005).

precursors for most carboxylic acids (Kawamura & Yasui, 2005).

coefficients that are larger than 0.50 are indicated in bold.

WS = Wind speed

amount in PM10 aerosol and to slightly extent Cl−, suggesting sea spray could be one of the contributing sources of the aerosol components at the site. But even though Na+ correlate well (r2=73) with Cl−, the calculated Cl− to Na+ mass ratio to sea-salt component in aerosol particles had mean value between 0.15 (PM2.5) and 0.10 (PM10). This suggest that continental contributions was most important than marine contribution since Cl−/Na+ ratio

Sulphate has been used as reference to investigate major formation routes of carboxylic acids (Yu et al., 2005). As shown in Table 2, formate and pyruvate showed good correlation with SO42− in PM2.5, suggesting that in-cloud and heterogeneous formations play an important role in the formation of carboxylates. On the other hand, poor correlation of malonic with SO42− in PM2.5 suggests that possibly the acid is volatile at ambient temperatures (Peng et al., 2001). Acetate and oxalate showed poor correlations with SO42− in both aerosol fractions, indicating that they mainly originated from primary emissions sources and/or the atmospheric processes different from those of SO42−. This is contrary to what have been observed in other studies that in-cloud and heterogeneous formations can

Wind speed poorly correlated with most carboxylates except with acetate (r2=51) in PM10 aerosols. This indicates that in addition to secondary formation carboxylates were mainly generated from local sources, while acetate might be related to long range aerosols transport to the sampling site. It should also be noted that primary emissions are major sources of

Species FA Ac Oxa Mal Suc Pyr SO42<sup>−</sup> NO3− Cl− Na+ K+ Ca2+ WS FA 0.26 0.10 0.19 − **0.91 0.60** 0.31 0.10 − 0.38 − -0.23 Ac 0.42 0.21 0.11 − 0.28 -0.04 0.45 0.27 − -0.09 − -0.21 Oxa **0.77** 0.29 0.31 − 0.11 0.34 0.23 0.17 − 0.30 − -0.07 Mal − − − − 0.17 0.17 **0.51** 0.33 − 0.13 − 0.08 Suc **0.57** 0.42 -0.11 − − − − − − − − − Pyr 0.48 **0.54** 0.13 − **0.51 0.52** 0.21 -0.01 − 0.31 − -0.20 SO42<sup>−</sup> − 0.26 0.30 − 0.31 -0.10 -0.16 -0.06 − **0.93** − 0.06 NO3<sup>−</sup> **0.88** 0.17 **0.74** − **0.55** 0.30 0.11 0.78 − -0.41 − -0.03 Cl<sup>−</sup> **0.55** -0.29 **0.56** − 0.28 -0.11 0.05 **0.81** − -0.26 − -0.12 Na+ **0.81** 0.18 **0.74** − 0.39 0.36 0.23 **0.87 0.73** − − − K+ **0.53** 0.35 0.38 − 0.45 0.45 0.22 0.39 0.18 0.45 − -0.02 Ca2+ **0.65** 0.23 **0.52** − 0.30 0.32 0.25 **0.58** 0.32 **0.58 0.51** − WS -0.10 **0.51** 0.25 − -0.44 -0.23 0.28 -0.06 -0.08 -0.19 0.11 0.26

**Table 2.** Correlation coefficients for PM mass, carboxylates, selected ions and wind speed in PM2.5 (upper diagonal triangle) and PM10 fractions (lower diagonal triangle) in Morogoro. Correlation

The ratio of acetic to formic acid has been used as good indicator of contributions of primary (high ratio) and secondary sources (low ratio) to carboxylic acids (Talbot et al., 1988, 1990; Grosjean, 1992). As can be seen in Table 3, low acetate/formate ratios for both PM2.5 and PM10 aerosols particles indicate that secondary formation was an important contributing source of carboxylates at our site. This suggestion is supported by the fact that high mean average temperature during sampling period (mean: 26.8 oC) might be controlling factor in determining the contribution of primary and secondary sources to these carboxylates. However, there are various types of the atmospheric reactions forming carboxylic acids (e.g. formic, acetic, and oxalic) in urban and near urban atmospheres, which include oxidation of unsaturated fatty acids originating from cooking activities, ozone oxidation of olefins emitted from vehicular exhausts (Scheff & Wadden, 1993) and oxidation of aromatic hydrocarbons (Kawamura & Ikushima, 1993).

The ratio of oxalic acid to total dicarboxylic acid (for this study oxalic, malonic, succinic acids) can be used to evaluate aging process of organic aerosols (Kawamura & Sakaguchi, 1999), because diacid such as oxalic acid can be produced by oxidations of longer-chain dicarboxylic acids (Kawamura et al., 1996). In this study oxalate to total dicarboxylates ratios show low values in both aerosol fractions, indicating that aerosols emitted from various sources and transported to this site were less and equally aged. Since there relative humidity was high during the campaign (up to 73% on average), it is supposed that oxalate was also produced in aqueous phase. Aqueous phase chemistry in aerosol and/or cloud droplets is important in production of oxalic acid (Warneck, 2003). On the other hand, mean ratio of oxalate to K+ in PM2.5 aerosols was 0.19±0.08, somewhat close to or higher than those reported range (0.03−0.1) for flaming and smoldering phases in burning plumes (Yamasoe et al., 2000). This suggests that carboxylates might be originated from biogenic sources with contribution from biomass burning emissions.


**Table 3.** Mean ratios and ranges for carboxylates and K+ in PM2.5 and PM10 aerosols in Morogoro.
