Measuring ambient particulate matter in three cities in Cameroon, Africa

Atmospheric Environment 95 (2014) 344e354

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Measuring ambient particulate matter in three cities in Cameroon, Africa Jessica Antonel, Zohir Chowdhury* Graduate School of Public Health, San Diego State University, San Diego, CA 92182, USA

h i g h l i g h t s

g r a p h i c a l a b s t r a c t


PM1.0 particle count is monitored for the first time in Central Africa.
PM2.5 and PM10 mass concentrations are elevated in Cameroon.
Carbonaceous and non-carbonaceous PM contribute to PM2.5 in Cameroon.
Trash burning and cooking exhaust elevate PM concentrations in city outskirts.

a r t i c l e i n f o

a b s t r a c t

Article history: Received 31 October 2013 Received in revised form 24 June 2014 Accepted 26 June 2014 Available online 26 June 2014

This is the first study of particulate matter (PM) air pollution in Cameroon. In this study, mass concentration and PM size fractions as well as carbonaceous contribution to PM are measured in Bafoussam, , Cameroon. Average concentrations in Bafoussam, Bamenda, and Yaounde  of Bamenda, and Yaounde PM2.5 are 67 ± 14, 132 ± 64, and 49 ± 12 mg/m3 and PM10 are 105 ± 29, 141 ± 107, and 65 ± 21 mg/m3, respectively. Daytime levels of PM2.5 and PM10 are seen to be higher than nighttime levels in all cities except Bamenda where nighttime levels are higher for both PM sizes. In Bafoussam, the average PM1.0 particle number concentration during the day is 19,800 pt/cc and during the evening is 15,200 pt/cc. PM2.5/PM10 mass ratios are 0.65 ± 0.05, 0.75 ± 0.05, and 0.78 ± 0.09 for Bafoussam, Bamenda, and Yaounde, respectively. Elemental carbon (EC) and organic carbon (OC) contribution to PM2.5 in Bafous are 3.9%, 2.9% and 12% for EC and 17.7%, 23.6%, and 34.2% for OC, respecsam, Bamenda, and Yaounde tively. After conducting spatial variability of PM mass concentration and size fractionation sampling at various locations within each of the three cities, we find that PM2.5 averages are highest during commercial meal preparation in Bafoussam (684 ± 546 mg/m3), and on the road in Bamenda (417 ± 113 mg/  (110 ± 57 mg/m3). Additional air quality research in Central and West Africa is necessary m3) and Yaounde to begin implementing policy steps that influence change and to advocate for improved health conditions in this rapidly expanding region of the world. © 2014 Elsevier Ltd. All rights reserved.

Keywords: Cameroon Particulate matter Spatial variability Dust Carbonaceous particles

1. Introduction

* Corresponding author. E-mail address: [email protected] (Z. Chowdhury). http://dx.doi.org/10.1016/j.atmosenv.2014.06.053 1352-2310/© 2014 Elsevier Ltd. All rights reserved.

Urban outdoor air pollution is estimated to cause 2 million deaths throughout the world every year (World Health Organization [WHO], 2013), and even low concentrations of air pollutants have been related to a variety of harmful health effects. Fine particulate matter (PM) or PM2.5 (PM with an aerodynamic

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diameter  2.5 mm) is an air pollutant that causes major environmental problems and has a disproportionately harmful impact on human cardiovascular and respiratory systems (Pope et al., 2002, 2008). Urban air quality in sub-Saharan Africa is worsening throughout the continent (Environmental Protection Agency [EPA], 2012) as the urban population is growing at the highest rate in the world with a large number of urban residents living in low income slum neighborhoods (Arku et al., 2008). Over the next 41 years, Africa's population is expected to double and have 29% of the world's population (Population Reference Bureau, 2009), and by 2030, 54% of the African population is expected to be in urban areas. This increase in population and urbanization, accompanied with increased vehicle emissions, nearly nonexistent air quality regulations, and an increasing trend of industrialization, together, are the main contributors to the growing urban air quality problem throughout the African continent (EPA, 2012). A thorough literature review revealed minimal air quality research in this region, however more research has been conducted in West Africa than Central Africa. Roughly two dozen studies have been conducted amongst the 15 nations that are within West Africa. In Burkina Faso, PM1.0 levels in a rural and urban environment were found to be 8 ± 6 and 14 ± 16 mg/m3, PM10 levels were found to be between 108 ± 68 and 162 ± 144 mg/m3 (Linden et al., 2012), PM2.5 levels between 27 and 164 mg/m3, and black carbon (BC) varying between 1.3 and 8.2 mg/ m3 (Boman et al., 2009). In Ghana, roadside and residential PM2.5 levels were 39e53 mg/m3 and 30e70 mg/m3 and PM10 levels were 80e108 mg/m3 and 57e106 mg/m3, respectively (Dionisio et al., 2010a) with PM2.5 and PM10 reaching as high as 200 and 400 mg/ m3 (Dionisio et al., 2010b). In Central Africa, except for two Cameroonian studies and several Chadian atmospheric dust studies, baseline air quality research is nearly nonexistent. A total suspended PM study was , Cameroon and a conducted in 1974 (Pelassy, 1978) in Yaounde follow up study was conducted using aethalometers to find BC within PM2.5 in the same city, nearly 40 years later (Doumbia et al., 2012). Chad's dust deposition has also been researched because it is the leading contributor of dust in the world affecting countries across the globe (Prospero et al., 2002), but it has been otherwise neglected in regard to PM measurements documenting the exposure experienced by its own people (Longueville et al., 2010). Cameroon is an exemplary country to initiate research on PM in Central Africa because it serves as a representative of not only its own current atmospheric conditions but also those of its less accessible neighbors. The primary objective of this study is to conduct a baseline measurement of ambient air quality by quantifying the mass concentration of outdoor carbon monoxide and fine PM in fixed and mobile monitoring sites in three cities ) in Cameroon, Africa. (Bafoussam, Bamenda, and Yaounde 2. Materials and methods 2.1. Site selection and characterization We selected three of the largest urban cities in Cameroon ). City selection is based on the (Bafoussam, Bamenda, and Yaounde following criteria: it is a country or regional capital, it has increasing urban population growth, it has rapidly increasing quantities of transportation vehicles, and it has economic significance in the country. Air pollution sampling occurs during the dry season from January through March, 2012. Two types of sampling in each of the three cities are utilized, fixed and spatial variability monitoring. Fixed site monitoring involves stationary instruments that collect data for consecutive 24 h periods in each respective city, while spatial variability monitoring consists of on-foot sampling where instruments collect data for shorter periods by taking spatial

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measurements in various locations of interest within or nearby the same city. The Sunset Laboratories OC/EC instrument (Sunset Laboratories, OR, USA) at the Air Quality Laboratory at San Diego State University was utilized to conduct chemical analysis of PM2.5 for elemental carbon (EC) and organic carbon (OC) by taking a punch from each quartz filter obtained from the Airmetrics Minivol with methods described in Chowdhury et al. (2012) and Chowdhury et al. (2007). A total of 10 samples from Bafoussam, 14 samples from Bamenda,  were analyzed, in addition to 8 field and 10 samples from Yaounde blanks and 7 lab blanks. Daily EC and OC concentrations for each city were computed after subtracting the blank values. The statistical power of stationary sampling is limited by the sampling design of one monitoring site per city but is supplemented by spatial variability monitoring. Although some deviations of spatial variability monitoring locations exist, sampling locations generally include the commercial district, the market, a residential neighborhood, a city outskirt site, the central bus station, city-street sampling, recreational bar sampling, sampling on moto-taxis and yellow cabs, and in Bafoussam only, sampling during commercial food preparation. Spatial variability sampling monitors are placed level in backpacks and are frequently checked to ensure accurate data. Sample duration is between 5 min and 45 min depending on the real-life duration of the activity (ie. moto-taxis are generally for 5e10 min versus a bar is 30 min or more) and sampling for each location is taken on at least three different days. Instrument tubing is upright, unblocked, and external to the backpack. Table 1 provides more information on particular city characteristics and fixed monitoring sites and Supplemental Table T1 provides a list of spatial variability monitoring conditions. 2.2. Site setup and quality control Sampling in Bafoussam occurred from January 8th to 17th, in  from Bamenda from January 22nd to February 5th, and in Yaounde February 9th to 19th. DustTrak DRX (Model 8533, TSI Inc., Shoreview, MN) measures real-time PM1.0, PM2.5, Respirable PM, PM10, and PMTotal mass concentration, whereas the MiniVol Technical Air Sampler (TAS) (Airmetrics, Eugene, OR), which uses both Teflon and Quartz filters, measures only integrated PM2.5. In addition, P-TRAK Ultrafine Particle Counter (Model 8525, TSI Inc., Shoreview, MN) is utilized to monitor ultrafine PM number concentration and Q-TRAK IAQ Monitors (Model 8551, TSI Inc., Shoreview, MN) measure carbon monoxide (CO), relative humidity (RH), and temperature. Fixed site sampling utilizes DustTrak, Q-TRAK, MiniVol, and P-TRAK  monitors. However, Q-TRAK monitors are not deployed in Yaounde and are only partially deployed in Bafoussam, and P-TRAK monitors are deployed for 6 sampling days in Bafoussam only. Spatial variability sampling uses Dustrak and Q-TRAK monitors, however Q and are only partially TRAK monitors are not deployed in Yaounde deployed in Bamenda. Fixed site instruments are placed on unblocked buildings with flat roofs that are between 9 and 12 m in height and 3e15 m from the adjacent street. Air quality monitors sample 8 to 14 consecutive days and each sample lasts between 22 and 26 h. The equipment is frequently supervised and maintained in order to achieve optimal study results. Table 1 and Fig. 1 provide more information on fixed site locations and characteristics. A total of eight field blanks are captured in the three fixed sampling sites. Mean PM2.5 in field blanks is 27 ± 20 mg. High PM2.5 in field blank measurements is due to a high dust working environment in Cameroon. All samples are corrected by field blanks. All Quartz filters are baked for 8 h at 500 degrees Celsius ( C) in an oven prior to field sampling to remove any organic carbon present in the filter. Teflon filters are pre- and

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Table 1 Characteristics of three fixed sampling sites (Bafoussam, Bamenda, and Yaounde) in Cameroon.

Bafousssam

Latitude/Longitude 5.4667 N, 10.4167 E Population 239,287

Bamenda

Latitude/Longitude 5.9333 N, 10.1667 E Population 269,530

Yaounde

Latitude/Longitude 3.8667 N, 11.5167 E Population 1,817,524 (population data from Institut National de la Statistique Cameroun, 2011)

Description of city, industries, and sources of pollution

Site characteristics and sampling duration

Impact on fixed site sampling


Capital of the West Region
Inhabited by Bamileke people
Local economy is based on agriculture, pig and chicken husbandry, and regional commerce
Industries include a brewery, wood and construction factories, and coffee processing plants.
Sources of air pollution are transportation vehicles, domestic burning, trash burning, field burning, industries, and an airport.
Capital of northwest region
Inhabited by Tikari, Widikum, Fulani, and Moghamo people
Local economy is based on trading and agriculture
Industries include agricultural processing and soap production
Sources of air pollution include dust, transportation vehicles, domestic burning, trash burning, field burning, nearby Nigerian air pollution. (Wikipedia, 2013)
Country capital,
Metropolitan city
Economy is based on a strong agricultural market and trade
Industries include a brewery, sawmills, printing presses, research centers, a national university, and agriculture
Sources of air pollution include transportation vehicles, industry, domestic burning, trash burning, cigarette factory, railway and air transport, brewery, sawmills, printing presses, railway and air transport, international embassies, research centers, and a national university.(Encyclopaedia Britannica, 2013)


12 m high
4 story office building
10 m from the main 2 lane highway
Above a cement store and hardware store
Site is a mix of commercial and residential with an emphasis of commercial
8 days of 24 h fixed sampling


Significant nearby household burning, street sweeping, traffic, road construction, high incidence of domestic burning, dry cement loading, and dislodging of dirt were common practices during the sampling period


9 m high
Single story American-style residential home and immediately neighboring domestic water tower
20 m from dirt road and 1 km from city's main road
Near a local school which is the main source of daily vehicular traffic
Site is a mix of residential and commercial with an emphasis on residential
14 days of 24 h fixed sampling
12 m high
2 story apartment building
5 m from a dirt road alleyway and 2 blocks from a 6 lane highway
Immediately next to 4 small restaurants, a hotel and a grocery store
Site is a mix of residential and commercial with an emphasis on commercial 9 days of 24 h fixed sampling


Immediate dirt road used heavily for community school pickup/drop off, significant household burning and community trash burning nearby, the main road is 1 km away and has consistent stop and go traffic during the day and night and is the main artery connecting Bamenda to other villages and neighboring Cameroonian provinces

post-weighed in the same temperature and humidity controlled room at San Diego State University in San Diego, California, USA. All filters are frozen and kept inside a refrigerator within 24 h of sampling and are transferred to a 20  C freezer after field samples were transferred to America. The sampling scheme also includes several duplicate samples. PM2.5 was measured using two methods, the gravimetric and the DustTrak. The Airmetric MiniVol and filter measures PM2.5 and provides a duplicate measure for the daily average PM2.5 concentration from the DustTrak. All DustTrak data presented in the results are corrected by a two-step process. DustTrak DRX PM2.5 concentrations are first corrected for humidity effects and then calibrated for the local ambient aerosol using the co-located MiniVol for each of the three cities. Since these correction factors were similar for each city, a single factor of 1.83 was computed for the entire study. Relative humidity effects are corrected by applying the equation as presented in Chakrabarti et al.


Main six lane highway has frequent day and night traffic, main six lane highway is prone to vehicle and pedestrian traffic, the sampling site is 200 m from the national soccer stadium, frequent domestic and commercial burning is common nearby, small episodes of rain were frequent during sampling

(2004). Archived wind direction and wind trajectory into Cameroon is obtained from the National Oceanic and Atmospheric Administration (NOAA)-Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) (NOAA, 2013a). Local temperature, dewpoint, wind speed and wind direction is available for  only, using NOAA's National Climatic Data Center at the Yaounde  International Airport (NOAA, 2013b). Yaounde 3. Results and discussion 3.1. Bafoussam PM2.5 and PM10 concentrations in Bafoussam are highest during the day particularly from the hours of noon to sunset (106 ± 30 mg/ m3 and 169 ± 69 mg/m3) and lowest from midnight to sunrise (43 ± 10 and 62 ± 22 mg/m3) (see Table 2). This is similar to results

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Fig. 1. Location of the three sampling sites (Bamenda, Bafoussam, Yaounde) in Cameroon. ‘A’ is a city map of Bafoussam. A1: Fixed site machine location, A2: Residential district, A3: Outdoor city market, A4: Entertainment district, A5: Transportation hub, A6: Background site in Kouka. B is a city map of Bamenda. B1: Fixed site machines in residential area, B2: Outdoor market, B3: Commercial intersection, B4: Commercial district, B5: Busy intersection, B6: Background site. C is a map of Yaounde. C1: Fixed site machine location, C2: Entertainment district, C3: Outdoor commercial intersection, Cathedral, C4: Background site, Mount Febe, C5: Residential area at the university, C6: International airport and transportation hub further south. Source: Google Maps, 2013.

found in Ghana where PM2.5 and PM10 in a contrasting residential area ranged from 30 to 70 mg/m3 and 57 to 106 mg/m3, respectively (Dionisio et al., 2010a). P-values using a single factor ANOVA test among all categories of Day, Night, Sunrise to Noon, Sunset to 10 pm, Sunset to Midnight, and Midnight to Sunrise are statistically significant and have a value of less than 0.05 for concentrations of both PM2.5 and PM10 (see Table 2). Hourly graphs show consistently that during weekdays, peaks of PM2.5 occur from 5 am to 8 am in the morning and from 5 pm to 7 pm at night. As indicated by Supplemental Fig. S1, peaks of PM2.5 on Wednesday, January 11, 2012, the overall least polluted day, is between 100 mg/m3 and 200 mg/m3 and on the most polluted day,

Monday, January 16th, 2012, is between 100 mg/m3 and 300 mg/m3. These peaks in PM2.5 are similar to maximum PM2.5 concentrations found in Ghana of 200 mg/m3 (Dionisio et al., 2010b). Carbon monoxide is lowest (as low as 0 ppm) during these PM2.5 peaks; and is highest when PM2.5 is low with peaks between 8 and 10 ppm for Bafoussam's cleanest day and 4 and 6 ppm on Bafoussam's most polluted day (see Supplemental Fig. S1). The PM2.5 peaks from 5 to 8 am and 5 to 7 pm indicate rush hour traffic to and from work in the area and include the effect of long distance commercial transport. In Bafoussam, traffic is most congested during the day. Lack of security in the area increases when the sun sets and thus the daily commercial commuter trucks must

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Table 2 ; ± indicates one standard deviation from the mean. DustTrak DRX humidity corrected (a) PM2.5 (b) PM10 by time of day in Bafoussam, Bamenda, and Yaounde

a.) PM2.5 Bafoussam Jan 7 to 16, 2012 Bamenda Jan 22 to Feb 4, 2012 Yaounde Feb 9 to 18, 2012 p-value ANOVA b.) PM10 Bafoussam Jan 7 to 16, 2012 Bamenda Jan 22 to Feb 4, 2012 Yaounde Feb 9 to 18, 2012 p-value ANOVA

N

Day (mg/m3)

Night (mg/m3)

Sunrise to noon (mg/m3)

Noon to sunset (mg/m3)

Sunset to 10 pm (mg/m3)

Sunset to midnight (mg/m3)

Midnight to sunrise (mg/m3)

10

96 ± 26

54 ± 11

84 ± 24

106 ± 30

78 ± 19

67 ± 16

43 ± 10

14

115 ± 36

138 ± 101

128 ± 47

99 ± 35

181 ± 130

170 ± 123

101 ± 79

10

59 ± 15

41 ± 11

39 ± 13

82 ± 23

65 ± 18

55 ± 15

23 ± 7

0.00018

0.0017

0.0000052

0.22

0.0034

0.0021

0.0023

10

151 ± 58

79 ± 23

128 ± 50

169 ± 69

114 ± 37

97 ± 31

62 ± 22

14

165 ± 60

182 ± 153

177 ± 71

153 ± 65

256 ± 213

236 ± 199

121 ± 106

10

80 ± 27

51 ± 15

52 ± 20

112 ± 41

81 ± 23

69 ± 20

30 ± 12

0.0011

0.0069

0.000048

0.11

0.0099

0.0073

0.011

pass through the large western city during daylight on the one main paved arterial road as it passes to neighboring regions in the country. Bar graphs of daily PM1.0, PM2.5 and PM10 (Fig. 2) demonstrate that Bafoussam experiences the second highest concentrations of all three particulate size categories. For all three cities, the WHO guideline for PM2.5 is represented with a bold line at 25 mg/m3 per 24 h mean, and the WHO guideline for PM10 is marked with a hashed line at 50 mg/m3 per 24 h period (WHO, 2014). PM2.5 and PM10 levels exceed WHO guidelines in all cities. PM1.0 to PM2.5 and PM2.5 to PM10 ratios are calculated for each day by using the daily DustTrak DRX size segregated data (see Supplemental Fig. S2). Overall average PM1.0 to PM2.5 ratios are consistent in the three cities and are near 1.0 indicating that nearly all of the PM2.5 in the fixed site locations is fine PM of PM1.0. The calculated p-value across the three cities for PM1.0 to PM2.5 using a single factor ANOVA test is 0.0038. Although this may be due to high measurement precision, the p-value indicates statistical significance in the measurements (see Table 3). The PM1.0 to PM2.5 ratio differs between Bafoussam and Bamenda by 0.022 ± 0.005,  by 0.007 ± 0.008, and between between Bafoussam and Yaounde  by 0.015 ± 0.009. Overall average PM2.5 to Bamenda and Yaounde PM10 ratios among the three cities had greater variation within and ) among cities (0.65 ± 0.05 in Bafoussam to 0.78 ± 0.09 in Yaounde than the PM1.0 to PM2.5 ratios, but the PM2.5 to PM10 ratios remained high (see Table 3). The calculated p-value across the three cities for the PM2.5 to PM10 ratio using a single factor ANOVA test is 0.0008 indicating statistical significance in the measurements (see Table 3). The PM2.5 to PM10 ratio differs between Bafoussam and  by Bamenda by 0.097 ± 0.036, between Bafoussam and Yaounde  by 0.135 ± 0.054, and between Bamenda and Yaounde 0.038 ± 0.053. In Bafoussam, the daily PM2.5 to PM10 ratios are between 0.58 and 0.73 but rise above 0.7 slightly on January 12th and 13th only to fall below 0.6 from January 14th to January 16th (a Saturday, Sunday, and Monday) (see Supplemental Fig. S2). The overall PM2.5/PM10 ratio for Bafoussam is 0.65 ± 0.05 (See Table 3), which indicates that the particulates are likely related to combustion activities such as food preparation or trash burning, as well as, to biogenic sources, in addition to dust re-suspension from unpaved roads. Bafoussam has the highest presence of coarse particles  which reiterates the rural followed by Bamenda and Yaounde environment of Bafoussam and Bamenda and their lack of infra. The high PM2.5/PM10 ratio structure (paved roads) versus Yaounde  coupled with the overall lower concentration of PM2.5 of Yaounde and PM10, reinforces that although Bafoussam and Bamenda have

higher overall PM2.5 concentrations, within the smaller portion of , a higher fraction of PM2.5 versus PM that is produced in Yaounde PM10 is present. The overall lower dust content can be explained by 's proximity to the cleansing ocean that buffers the city Yaounde from long range dust transport and its longer distance from Chad, the largest dust producer in the world (Prospero et al., 2002). As  is a more developed city, there are more paved well, since Yaounde roads and there is more infrastructure. These aspects of big city life reduce re-suspended dust. Bafoussam is lined with businesses, offices, grocery stores, several large markets, and government buildings. Daily work commute requires that private cars, moto-taxis, or public taxis also access the main paved arterial road. Because January is the peak of the dry season in Cameroon, as well as the traditional burial season for people who passed away over the past year, overwhelming amounts of citizens flock to Bafoussam using public transportation and private vehicles such as moto-taxis. Because much of this activity is on dirt roads, increased re-suspended dust and combustion activity throughout the city are seen on a consistent basis. 3.2. Bamenda Bamenda, in contrast to Bafoussam, has a higher PM2.5 and PM10 concentration during the night (138 ± 101 and 182 ± 153 mg/m3). This difference is particularly high from sunset to 10 pm where the average concentration in Bamenda is 181 ± 130 and 256 ± 213 mg/ m3 (see Table 2) and falls to 170 ± 123 and 236 ± 199 mg/m3 between sunset and midnight and then bottoms at 101 ± 79 and 21 ± 106 mg/m3 from midnight to sunrise (see Table 2). Levels this high are seen in Burkina Faso where PM2.5 ranged from 27 to 164 mg/m3 (Boman et al., 2009). Bamenda has steady morning and heavy evening commute traffic and experiences a grand nightlife. Although consistent vehicle thoroughfare is present at all hours of the day, commute to and from work and the booming nightlife increases traffic as supported by the hourly PM2.5 graphs (Supplemental Fig. S1), during the morning commute from 7 am to 9 am and the evening commute from 7 pm to 9 pm. As indicated by Supplemental Fig. S1 (minute-by-minute averaged data for each day) in Bamenda, peaks for both the least polluted (Tuesday January 31) and most polluted day (Saturday January 28) are between 450 and 900 mg/m3. The overall 14 day average PM2.5/PM10 ratio for Bamenda is 0.75 ± 0.05 (see Table 3), which similar to Bafoussam indicates that the particulates are likely related to combustion activities such as food preparation and trash burning, as well as to biogenic sources, such as vegetative detritus, lipids

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Table 3 Daily PM1.0 to PM2.5 and PM2.5 to PM10 ratios obtained from DustTrak DRX size segregated data averaged over the sampling period in Bafoussam, Bamenda, and . Yaounde N Bafoussam Jan 7 to 16, 2012 Bamenda Jan 22 to Feb 4, 2012 Yaounde Feb 9 to 18, 2012 p-value ANOVA

PM1.0/PM2.5

PM2.5/PM10

9

0.959 ± 0.010

0.649 ± 0.053

14

0.981 ± 0.004

0.746 ± 0.050

9

0.966 ± 0.015

0.784 ± 0.094

0.0038

0.0008

trading hub because of its proximity to Nigeria. Vehicular activity enhanced by local and Nigerian trade, more re-suspended dust, increased field burning to prepare for the encroachment of the rainy season, and the pollution cap that traps the re-suspended dust and exhaust in this valley city, explains the increase in PM2.5 and PM10.

3.3. Yaound e

Fig. 2. Daily averaged PM1.0, PM2.5, and PM10 values (midnight to midnight) using the . The solid line DustTrak DRX size segregated data in Bafoussam, Bamenda, Yaounde represents the WHO 24 h mean air quality guideline for PM2.5 (25 mg/m3) and the dashed line represents the WHO 24 h air quality guideline for PM10 (50 mg/m3).

from microorganisms, etc. On the other hand PM2.5/PM10 ratios that are calculated daily are between 0.7 and 0.84 (see Supplemental Fig. S2) except for a strong decrease on the final full day of sampling, February 4th, a Saturday, and also a celebrated Muslim holiday, prophet Muhammad's birthday, Mawlid al-Nabi. Bamenda's lowest daily PM2.5/PM10 ratio is nearly 0.65 (see Supplemental Fig. S2). In Bamenda, one main road is paved and connects surrounding regions. The large city in the northwest of the country is densely populated (population of 269,530 (Institut National de la Statistique Cameroun, 2011)) and serves as an international

, the overall average levels of PM2.5 and PM10 are In Yaounde always lower than the other cities (often more than half). When , listed PM2.5 to PM10 respeccontrasting day to night in Yaounde tively, day (59 ± 15 and 80 ± 27 mg/m3) is higher than night (41 ± 11 and 51 ± 15 mg/m3) and the highest concentration occurs from noon to sunset (82 ± 23 and 112 ± 41 mg/m3) and falls off from sunset to 10 pm with a concentration of 65 ± 18 and 81 ± 23 mg/m3, further falling after 10 pm with an overall average PM2.5 and PM10 concentration from sunset to midnight of 55 ± 15 and 69 ± 20 mg/m3 (see Table 2). The peaks in PM during the day are due to lunch break vehicle exhaust and rush hour traffic (which increases PM2.5). This increased traffic re-suspends dust which increases PM10 concentrations as well. Conversely, the low PM in the evenings is due to restrictions on commercial travel after sundown as mandated by the government and decreased vehicular thoroughfare overall. These results are similar to a study in Accra, Ghana that found PM2.5 to be between 39 and 53 mg/m3 in roadside locations (Dionisio et al., 2010a) and although slightly lower, is similar to a study in Burkina Faso where PM10 results were found to be between 108 ± 68.4 mg/ m3 in a rural environment (Linden et al., 2012). As indicated by the hourly PM2.5 graphs (see Supplemental  exhibits peaks of PM2.5 at 8:30 am, 1:30 pm, Fig. S1), Yaounde and 7 pm. The peaks accompany the morning and evening commute between 7 am and 9 am, and 6 pm and 9 pm respectively,  has a third peak similar to Bafoussam and Bamenda, yet Yaounde between noon and 2 pm every day representing the combustion associated with a lunch break. As demonstrated by the best-day, the least polluted day of minute to worst-day graphs for Yaounde minute averaged data (Thursday February 16) exhibits peaks of PM2.5 between 50 and 150 mg/m3 and the most polluted day (Monday February 13) overall exhibits peaks of PM2.5 between 100 and 350 mg/m3 (see Supplemental Fig. S1). , the first five sampling days from February 10 to In Yaounde February 14 exhibit a lower PM2.5 to PM10 ratio equaling between ’s sampling from February 0.65 and 0.8. In the latter half of Yaounde 15th to February 18th, 2012 however, the ratio jumps to between 0.80 to nearly 0.95 (see Supplemental Fig. S2). The overall 9 day PM2.5/PM10 average ratio is 0.78 ± 0.09 (see Table 3). In the daily PM , from February 10th to February 15th, the bar graph in Yaounde coarse PM fraction is nearly double the remaining sampling days and PM1.0 and PM2.5 increase by almost 50% (see Fig. 2) when comparing any of the lower days to the highest day on February

Fig. 3. Archived wind direction and wind trajectory from the National Oceanic and Atmospheric Administration (NOAA) e using Hybrid Single Particle Lagrangian Integrated Tra. jectory Model (HYSPLIT) representing low (left) and high (right) pollution days in Bafoussam, Bamenda, Yaounde

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surrounding the city likely contribute to PM2.5 levels. In comparison  use to Bafoussam and Bamenda however, residents of Yaounde more gas cooking fuel and there is a higher prevalence of modern vehicles. As well, paved roads are more predominant. 3.4. ECOC Prior to this study, EC and OC analysis of PM2.5 in Cameroon had not been conducted. In terms of concentrations, both Bamenda and Bafoussam have higher concentrations of carbonaceous particles  indicating that the likely combustion sources emit than Yaounde significantly more carbonaceous PM in these smaller cities as mentioned in the earlier sections. Total carbonaceous PM is computed as the sum of EC and organic matter (OM), where OM ¼ 2.1  OC in Bafoussam and Bamenda because of high impact  because of the from woodsmoke, and OM ¼ 1.85  OC in Yaounde urban nature of this location (refer to Turpin and Lim, 2001 for a detailed explanation of OC conversion into OM). Total carbonaceous  are PM concentrations in Bafoussam, Bamenda, and Yaounde 33.0 ± 2.9 mg/m3, 64.4 ± 27.0 mg/m3, and 33.5 ± 6.3 mg/m3, respectively. In addition, EC concentrations in Bafoussam, Bamenda, and  are 3.1 ± 0.4 mg/m3, 3.6 ± 1.6 mg/m3, and 5.5 ± 1.1 mg/m3, Yaounde respectively. Both total carbonaceous PM and EC values are near two-fold to three-fold the concentrations observed downwind of Los Angeles freeways (Phuleria et al., 2007). As a fraction of PM2.5, carbonaceous PM is lowest in Bafoussam (<50%) followed by  (much greater Bamenda (generally  50%) and highest in Yaounde , the ratio of EC to PM2.5 is higher (12%) than 50%). In fact, in Yaounde than Bafoussam (3.9%) and Bamenda (2.9%) indicating a larger contribution to PM2.5 from combustion sources than noncombustion sources (see Fig. 4). Additionally, although the PM1.0/ PM2.5 ratio is roughly 1 (see Table 3), the carbonaceous aerosol is typically below 75% (see Fig. 4) indicating the presence of additional likely non-carbonaceous contributing sources to levels of PM1.0 that include silt, silica from cement production, metal fumes and metal oxides from small scale industrial emission exhaust, and biogenic sources from the forest in the southern part of the country. Ratios of EC/PM2.5 remain fairly even for Bafoussam and Bamenda throughout the sampling period with significant contribution of non-crustal  where the ratio becomes higher species except for Yaounde (0.09e0.14 toward the beginning as compared to 0.13e0.20 toward the end) toward the end of the sampling period. The change in EC/ PM2.5 ratio indicates a shift in the source contributions to PM2.5 in this city during the end of the sampling. 3.5. Local and long range sources of dust

Fig. 4. Daily contributions of non-carbonaceous, elemental carbon, and organic matter . within PM2.5 in Bafoussam, Bamenda, Yaounde

13th. February 11th, a Saturday, is Youth Day and is one of Cameroon's most celebrated holidays. All citizens, government officials, and important political representatives attend parades in nearby cities.  As mentioned above, likely sources of air pollution in Yaounde include residential and commercial burning. The testing site was near a 6 lane highway and the national soccer stadium and parking lot; the stadium is an atypical space unavailable to the public for daily burning activities. dditionally, the dense forests of the southern part of the country and the flora, fauna, and undergrowth

Dust sources in the three fixed sampling sites have local and long term contributors. One of the most prominent wind systems in Africa is the Harmattan which is a ground level stream of dry desert air that sweeps from the northeast Chad Basin to the Guinean coast tangential to Cameroon (Schwanghart and Schutt, 2008). Part of the Harmattan wind comes from the Tibesti Mountains and the Ennedi le  Depression and is Ridge in neighboring Chad within the Bode estimated to produce about half the mineral aerosols emitted from the Sahara, the world's largest source of dust (Washington et al., 2009). Archived wind direction and wind trajectory from the NOAAHYSPLIT exhibit evidence of high concentrations of PM10 in Bafoussam to be correlated with Harmattan winds sweeping into the country from North Africa preceding Cameroon most recently in Nigeria (see Fig. 3a e left) and Chad (see Fig. 3b). Fig. 3a e left correlates with Bafoussam's lowest 24-h PM10 concentration and Fig. 3a e right correlates with Bafoussam's highest 24-h PM10 concentration. Bafoussam's lowest day (Fig. 3a e left) does not

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Table 4 Mean PM1.0 number concentration expressed in pt/cc using the P-TRAK in Bafoussam. PM1.0 pt/cc

Day

Night

Sunrise to noon

Noon to sunset

Sunset to 10 pm

Sunset to midnight

Midnight to sunrise

Mean Std dev Median Min Max N

19,800 10,200 18,100 4050 118,000 817

15,200 12,700 10,300 1870 93,000 1464

23,100 12,600 20,000 8000 118,000 162

18,900 9330 17,500 4050 63,100 655

27,600 13,400 24,000 8990 93,000 426

21,600 13,100 18,300 5390 93,000 736

8600 8050 5840 1870 50,400 727

sweep through Chad, the largest dust contributor in the world (Prospero et al., 2002), and Bafoussam's highest day (Fig. 3a e right) does. This provides supporting evidence that the Chad Basin does contribute to long range dust transport within Cameroon; in particular within Bafoussam. Bamenda is in a valley that reduces local wind sources from dispersing particulates outside of the city. Long range transport as tracked by the NOAA-HYSPLIT model shows significant dust sweeping in from neighboring Nigeria roughly 200 km away (see Fig. 3b e right) that was preceded by significant activity within Chad on Bamenda's highest 24-h PM10 concentration day. In addition, pollution in Bamenda valley is trapped by the stagnant surrounding mountains and heavy pollution layer that caps the entire city. Each day, as daily activity re-suspends the dust from dirt roads, city streets, dried fields, and neighboring countries, the geography of the area traps it and the coarse particulates accumulate. Additionally, as shown in Fig. 3b e left, the lowest 24-h PM10 concentration in Bamenda demonstrates long range transport entering from the ocean. This provides evidence that the ocean does decrease incoming dust concentrations entering Bamenda and that routes of long range dust from the north of Africa that do not pass through the ocean increase Bamenda's dust concentrations. For the most part, long range wind transport entering into  is cleansed by the ocean before it rises from southern Yaounde Africa (see Fig. 3c e left). On Yaounde's lowest 24-h PM10 concentration day, the long range dust transport enters from the ocean (although there is evidence of some influence of particulate accumulation in the industrial and highly polluted city of Douala before ’s highest it reaches the city's capital (Fig. 3c e left)). On Yaounde 24-h PM10 concentration day (3c-right), the NOAA-HYSPLIT model shows activity in Nigeria before entering the capital and perhaps even evidence of passing through Bamenda prior to its entry in . This is reinforced by Yaounde 's overall lower PM10 conYaounde centrations (see Fig. 2) in comparison to Bamenda and Bafoussam  in relation to throughout the study. Overall PM10 levels in Yaounde Bafoussam and Bamenda remain low. In Bafoussam, local sources such as road construction a dozen meters from the fixed testing site, and a cement business on the bottom floor of the testing site building likely contribute to high PM10. Most of Bafoussam's streets are dirt roads that re-suspend dust each time a moto-taxi passes or by frequent gusts of wind. Neighboring fields to Bafoussam's city center that have long lost their abundant fertility after overplanting cocoa beans in the late 20th century remain dry and are threatened by desertification. , increased PM10 is Similar to Bafoussam, in Bamenda and Yaounde due to redistributed dust caused by active thoroughfare on the main paved roads. In contrast to Bafoussam, in Bamenda this increased thoroughfare occurs during the evening and the dust is re-suspended then. 3.6. PM1.0 number concentration P-TRAK data is available from January 7th to January 9th, 2012 in Bafoussam only and is the first measurement of PM1.0 in West and

Central Africa. Day (sunrise to sunset), night (sunset to sunrise), sunrise to noon, noon to sunset, sunset to 10 pm, sunset to midnight, and midnight to sunrise data is calculated as an overall average across the 3 days. As seen in Table 4, sunset to 10 pm ultrafine data is always highest among the categories midst the 3 sampling days averaging at 27,600 ± 13,400 pt/cc with peaks at 7 pm indicating peak cooking time, and midnight to sunrise is always the lowest at 8600 ± 8050 pt/cc (see Table 4) because commercial transport and food preparation at this time is lowest. The overall average for the day is 19,800 ± 10,200 pt/cc and day peaks are at noon and 2 pm indicating lunch break traffic and food preparation (see Table 4). These numbers compare to hourly ultrafine particle concentrations (0.02e0.10 mm) of 14,400 ± 11,400 pt/cc averaged over 20 days during the winter in Chamizal, El Paso, TX, USA (Noble et al., 2003) and of 15,000 ± 7200 pt/cc, in a highly polluted slum neighborhood, in Saidpur, Bangladesh (Chowdhury et al., 2012). 3.7. Spatial variability sampling Citizens in Bamenda experience the highest overall spatial variability particulate matter concentrations (see Table 5) except for one value sampled in Bafoussam only that measured commercial food preparation of women selling chicken or fish, a practice very common in Bafoussam only. This value sampled in Bafoussam only is the highest sampled value in all three cities and has a PM2.5 value of 684 ± 586 mg/m3. In Bamenda, PM2.5 concentrations are highest on moto-taxis (417 ± 113 mg/m3) with a concentration that is roughly 30 percent higher than the second highest concentration, yellow taxis, with a PM2.5 concentration value of 286 ± 73 mg/m3. Bafoussam has the second highest spatial variability concentration values with the commercial food preparation exception mentioned above. Bafoussam's second highest PM2.5 concentration is on mototaxis with a concentration value of 272 ± 150 mg/m3 which is less than half of its highest spatial variability sampling concentration. In , the highest spatial variability concentration of PM2.5 is in Yaounde a yellow taxi with a value of 110 ± 57 mg/m3. This value is roughly one third of the concentration in Bamenda and Bafoussam. The second highest PM2.5 concentration is in the market area of  and has a value of 100 ± 20 mg/m3. Yaounde City outskirt concentrations were often found to be higher than within the city itself. This is because although trash burning is common anywhere in the city, it is custom to burn large amounts of informally collected trash farther away from the city center. As well, in the city outskirts, there is an increase in the small village lifestyle that is accompanied by a greater affinity for biomass burning in food preparation. In Bafoussam, the overall city outskirt PM2.5 concentration is 160 ± 102 mg/m3 which is similar to spatial variability measurements at the bus station (172 ± 67 mg/m3). The sampling took place in the outskirts of Bafoussam in the corn and yam fields roughly 10 km from the city center. Sampling took place weeks before the rainy season and thus random field burning in preparation for the rains was evident. In Bamenda, the city outskirt sampling site was taken on top of one side of the valley roughly 15 km from the city center on a cliff with little human inhabitance.

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Table 5 . Spatial variability sampling averages ± standard deviation per intra-city location in Bafoussam, Bamenda, and Yaounde Commercial (mg/m3) Bafoussam PM1.0 PM2.5 PM10 Bamenda PM1.0 127 PM2.5 130 PM10 182  Yaounde PM1.0 88 89 PM2.5 PM10 111

Market (mg/m3)

Residential (mg/m3)

City outskirts (mg/m3)

Bus station (mg/m3)

Street (mg/m3)

Bar (mg/m3)

142 ± 43 145 ± 43 194 ± 88

107 ± 22 109 ± 23 139 ± 38

157 ± 100 160 ± 102 224 ± 159

169 ± 67 172 ± 67 214 ± 70

148 ± 84 151 ± 85 207 ± 85

223 ± 107 226 ± 108 280 ± 132

157 ± 125 160 ± 125 255 ± 211

225 ± 80 229 ± 80 327 ± 96

204 ± 66 208 ± 67 326 ± 100

204 ± 71 208 ± 72 287 ± 88

56 ± 11 57 ± 11 76 ± 17

68 ± 44 69 ± 45 95 ± 65

41 ± 10 42 ± 11 55 ± 16

88 ± 20 89 ± 20 111 ± 20

± 63 ± 63 ± 85

225 ± 80 229 ± 80 327 ± 96

± 20 ± 20 ± 20

98 ± 20 100 ± 20 127 ± 28

40 ± 10 41 ± 11 48 ± 17

As demonstrated in Table 5, the PM2.5 concentration is 160 ± 125 mg/m3 and is nearly equal to the commercial district concentration of 130 ± 63 mg/m3. This extremely high PM2.5 concentration value indicates a pollution layer sitting on top of the , the city outskirt location site has a Bamenda valley. In Yaounde PM2.5 spatial variability concentration of 57 ± 11 mg/m3. Although this concentration is roughly 2.5 times smaller than Bamenda and Bafoussam, it is similar to the concentration of the street and res (42 ± 11 mg/m3). This location was high on idential areas in Yaounde a hill 15 km outside of the city center. This relatively high con is due to field clearing (similar to Bafouscentration for Yaounde sam) in preparation for the rains that take place outside of the city center in addition to visible trash burning. The overall higher spatial variability concentrations (see Table 5) in Bamenda are due to the contributing higher ambient PM concentrations and the pollution cap on the city that disrupts the dispersion of particulates outside the city. Bafoussam has the second highest overall spatial variability concentrations. Its absence of a pollution layer decreases the overall ambient concentrations contributing to each unique  has the lowest spatial variability location tested. Finally, Yaounde  and overall ambient concentrations. As mentioned above, Yaounde has a populous that can afford newer and more fuel efficient cars and moto-taxis and methods of food preparation such a gas stoves (versus biomass burning). The city's population is distributed over a larger area thus decreasing specific site concentrations.

4. Conclusions This is the first PM size fractionation study in West and Central Africa and the first carbonaceous carbon study in Cameroon.  of Average concentrations in Bafoussam, Bamenda, and Yaounde PM2.5 are 67 ± 14, 132 ± 64, and 49 ± 12 mg/m3 and PM10 are 105 ± 29, 141 ± 107, and 65 ± 21 mg/m3. The average particle count concentration during the day is 19,800 pt/cc and during the evening is 15,200 pt/cc. The PM1.0/PM2.5 ratio for all three cities is nearly 1.0 and PM2.5/PM10 ratios are 0.65 ± 0.05, 0.075 ± 0.05, and , respectively. EC/ 0.78 ± 0.09 for Bafoussam, Bamenda, and Yaounde PM2.5 ratio is 3.9%, 2.9% and 12% in Bafoussam, Bamenda, and , respectively. Archived wind direction and wind trajectory Yaounde into Cameroon obtained from NOAA's HYSPLIT indicate that influences of long range dust and pollution from Chad and Nigeria in addition to the Harmattan wind likely contribute to these findings. Spatial variability sampling found the highest concentrations of PM2.5 in commercial food preparation in Bafoussam (684 ± 546 mg/ m3), on moto-taxis in Bamenda (417 ± 113 mg/m3), and in yellow  (110 ± 57 mg/m3). High PM2.5 values in the city taxis in Yaounde  outskirt sites in Bafoussam (160 ± 102 mg/m3) and Yaounde , trash (57 ± 11 mg/m3) were due to field burning. In Yaounde

Taxi (mg/m3)

Commercial food preparation (mg/m3)

268 ± 149 272 ± 150 384 ± 217

239 ± 113 243 ± 113 334 ± 114

682 ± 545 684 ± 546 709 ± 546

403 ± 109 417 ± 113 1009 ± 350

280 ± 72 286 ± 73 424 ± 180

Moto-taxi (mg/m3)

108 ± 56 110 ± 57 161 ± 94

burning at the site was also evident. The PM2.5 city outskirt site concentration in Bamenda (160 ± 125 mg/m3) is due to a pollution layer that caps the Bamenda valley. There is a need for newer studies measuring PM, BC, and size distribution in Central and West Africa. For example, this study fails to monitor northern Cameroon where desert is ubiquitous, desertification is a growing threat, and the location is in much closer proximity to the dust sources of the  le  Depression, and the pollution of Nigeria. Chad Basin and the Bode Countries such as Gabon, the Central African Republic, and the Democratic Republic of the Congo have had no published air quality research conducted in their countries to date. Additional air quality research in Central and West Africa is necessary to begin implementing policy steps that influence change and to advocate for improved health conditions in this rapidly expanding region of the world. Acknowledgments Laboratory and instrumentation assistance in San Diego was provided by Abigail Erasquin, Kathy Datuin, and Sondra Antonel. Logistical support, site location, and cultural guidance were provided by Theophile Sobngwi and Mama Ntieche at the Research Institute for Development in Bafoussam. Appendix A. Supplementary data Supplementary data related to this article can be found at http:// dx.doi.org/10.1016/j.atmosenv.2014.06.053. References Arku, R.E., Vallarino, J., Dionisio, K.L., Willis, R., Choi, H., Wilson, J.G., Hemphill, C., Agyei-Mensah, S., Spengler, J.D., Ezzati, M., 2008. Characterizing air pollution in two low-income neighborhoods in Accra, Ghana. Sci. Total Environ. 402, 217e231. http://dx.doi.org/10.1016/j.scitotenv.2008.04.042. Boman, J., Linden, J., Thorsson, S., Holmer, B., Eliasson, I., 2009. A tentative study of urban and suburban fine particles (PM2.5) collected in Ouagadougou, Burkina Faso. X-ray Spectrom. 38, 354e362. http://dx.doi.org/10.1002/xrs.1173. Chakrabarti, B., Fine, P.M., Delfino, R., Sioutas, C., 2004. Performance evaluation of the active-flow personal DataRAM PM2.5 mass monitor (Thermo Anderson pDR1200) designed for continuous personal exposure measurements. Atmos. Environ. 38, 3329e3340. http://dx.doi.org/10.1016/j.atmosenv.2004.03.007. Chowdhury, Z., Zheng, M., Schauer, J., Sheesley, R., Salmon, L., Cass, G., Russell, A., 2007. Speciation of ambient fine organic carbon particles and source apportionment of PM2.5 in Indian cities. J. Geophys. Res. Atmos. 112, D15303. http:// dx.doi.org/10.1029/2007JD008386. Chowdhury, Z., Le, L.T., Masud, A.A., Chang, K.C., Alauddin, M., Hossain, M., Zakaria, A.B.M., Hopke, P.K., 2012. Quantification of indoor air pollution from using cookstoves and estimating its health effects in Northwest Bangladesh. J. Aerosol Air Qual. Res. 12 (4), 463e475. Dionisio, K.L., Arku, R.E., Hughes, A.F., Vallarino, J., Carmichael, H., Spengler, J.D., Agyei-Mensah, S., Ezzati, M., 2010a. Air pollution in Accra, neighborhoods: spatial, socioeconomic, and temporal patterns. Environ. Sci. Technol. 44, 2270e2276. http://dx.doi.org/10.1021/es903276s.

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