13 RBCIAMB | n.54 | dez 2019 | 13-33 - ISSN 2176-9478 Layse Teixeira Pinheiro Master’s degree student in the Post-Graduation Program in Environmental Science at Universidade Federal do Pará – Belém (PA), Brazil. José Henrique Cattanio Professor in the Post-Graduation Program in Environmental Science at Universidade Federal do Pará – Belém (PA), Brazil. Breno Imbiriba Professor in the Post-Graduation Program in Environmental Science at Universidade Federal do Pará – Belém (PA), Brazil. Saul Edgardo Martinez Castellon Doctoral candidate in the Post-Graduation Program in Environmental Science at Universidade Federal do Pará – Belém (PA), Brazil. Silvia Adriane Elesbão Student in the Faculty of Meteorology at Universidade Federal do Pará – Belém (PA), Brazil. Jade Rebeka de Souza Ramos Student in the Faculty of Meteorology at Federal Universidade Federal do Pará – Belém (PA), Brazil. Correspondence address: Jose Henrique Cattanio – Federal University of Pará – Rua Augusto Correa, n° 1 – bairro Guamá – CEP: 66075-110 – Belém (PA), Brazil – E-mail: cattanio@ufpa.br Received on: 05/29/2019 Accepted on: 12/06/2019 ABSTRACT Dumps are important anthropogenic sources of greenhouse gas emissions into the atmosphere, mostly CH 4 . However, few studies on the subject have been carried out in the Amazon region. Several factors affect the production and emission of dumps gases. The objective of this study was to quantify the spatial variation of CO 2 and CH 4 production in an Amazonian dump and seek the relationship between the relative importance of some environmental factors and the gas fluxes. This study was carried out in an open-air dump in the metropolitan region of Belém, where approximately 11.0 million Mg of waste was deposited within 25 years, of which 6.4 million Mg were organic. The CH 4 and CO 2 emission rates from the surface of the dump were determined using the closed dynamic flux chamber technique. The study was conducted in three cells of different ages, sampled in two times between the rainy and the dry season in Amazon. The Aurá dump has an area of 30 ha and emits a total of 51.49 Mg CO 2 ha-1 month-1 and 3.16 Mg CH 4 ha-1 month-1 to the atmosphere. This results in an expressive production of 1,359,961.04 Mg CO 2 -e y-1, being that 58.54% is due to CH 4 flux. The spatial variability in CO 2 and CH 4 fluxes is very large, especially for CH 4 , forming hotspots of high concentrations. Perhaps for this reason, the flow has not been correlated with micrometeorological variations. Keywords: pollution; flux chamber; open dumping; Amazon. RESUMO Lixões são importantes fontes antropogênicas de emissão de gases de efeito estufa na atmosfera, principalmente CH 4 . No entanto, poucos estudos sobre o assunto foram realizados na região amazônica. Diversos fatores afetam a produção e emissão de gás de aterro. O objetivo deste estudo foi quantificar a variação espacial da produção de CO 2 e CH 4 em um lixão da Amazônia e tentar associar a importância relativa de alguns fatores ambientais e os fluxos de gás. Este estudo foi realizado em um lixão ao ar livre na região metropolitana de Belém, onde aproximadamente 11,0 milhões de Mg de resíduos foram depositados em 25 anos, dos quais 6,4 milhões de Mg eram orgânicos. As taxas de emissão de CH 4 e CO 2 da superfície do aterro foram determinadas usando a técnica de câmara de fluxo dinâmico fechado. O estudo foi realizado em três células de diferentes idades, amostradas em dois momentos entre a estação chuvosa e seca da Amazônia. O lixão Aura tem uma área de 30 ha e emite um total de 51,49 Mg CO 2 ha-1 mês-1 e 3,16 Mg CH 4 ha-1 mês-1 para a atmosfera. Isso resulta em uma produção expressiva de 1.359.961,04 Mg CO 2 -e ano-1, sendo 58,54% devido ao fluxo de CH 4 . A variabilidade espacial no fluxo de CO 2 e CH 4 é muito grande, especialmente para CH 4 , formando pontos ativos (“hotspots”) de altas concentrações, e talvez por isso, o fluxo não tenha sido correlacionado com variações micrometeorológicas. Palavras-chave: poluição; câmaras de fluxo; lixão a céu aberto; Amazônia. DOI: 10.5327/Z2176-947820190021 CARBON DIOXIDE AND METHANE FLUX MEASUREMENTS AT A LARGE UNSANITARY DUMPING SITE IN THE AMAZON REGION MEDIDAS DE FLUXO DE DIÓXIDO DE CARBONO E METANO EM UM DEPÓSITO DE RESÍDUOS INSALUBRE NA AMAZÔNIA https://orcid.org/0000-0002-6728-5106 https://orcid.org/0000-0001-8335-9593 https://orcid.org/0000-0003-2311-1486 https://orcid.org/0000-0003-2455-1678 https://orcid.org/0000-0003-2667-7215 https://orcid.org/0000-0002-6118-9607 mailto:cattanio@ufpa.br Pinheiro, L.T. et al. 14 RBCIAMB | n.54 | dez 2019 | 13-33 - ISSN 2176-9478 INTRODUCTION Atmospheric methane (CH 4 ) concentrations have increased to over 1,800 ppb in 2016 (IPCC, 2013; REAY et al., 2018), of which 70% result from an- thropogenic activities such as rice cultivation, domestic ruminants, biomass burning, leakage of natural gas, coal mining, landfills, and the remain- der from natural wetlands (MATTHEWS; THEME- LIS, 2007). Aerobic soil consumes and oxidizes at- mospheric CH4 (6% of total sink), while anaerobic soils can be a significant source of CH 4 (BIAN et al., 2018a; DALAL et al., 2008). The sink/source ratios and controls on the production and emission of CH 4 in the Amazon basin come mainly from stud- ies on individual wetlands, lakes, and floodplains (POTTER et al., 2014). No studies have addressed how much Amazonian dumps produce and how long these deactivated dumps have contributed to global warming with carbon dioxide (CO2) and CH 4 emissions. Landfills are a significant global source of anthro- pogenic atmosphere CH 4 (BARLAZ et al., 2010) and a non-negligible source of CO 2 (AGAMUTHU, 2013). Global CH 4 emissions are responsible for approxi- mately 40% of the global warming in the last 150 years (HANSEN et al., 2013), given that its global warming potential (GWP, molar basis, 100-year peri- od) is about 21 to 27 times greater than that of CO2 (AGAMUTHU, 2013; LELIEVELD et al., 1998). This is due to the high ultraviolet absorption coefficient and long residence time in the atmosphere (IPCC, 2013; LELIEVELD et al., 1998). Currently, landfills contribute with about 22% of the total anthropogenic emissions of CH4, which are expected to increase globally from 58 Mt to 365 Mt by 2030, assuming no further implementation of control measures (BAJAR et al., 2017). Current es- timates from the Intergovernmental Panel on Cli- mate Change (IPCC) for the annual CH4 emissions from landfills range from 67 to 90 Mt CH 4 y-1, which is equivalent to a CO 2 emission (CO 2 -e) of 500 to 800 Mt CO 2- e (IPCC, 2013). Brazil has a consider- able unexplored potential for landfill biogas pro- duction (LIMA et al., 2018), which is lost due to the lack of technology in the construction of land- fills (AHOUGHALANDARI; CABRAL, 2017b; BARROS et al., 2018). The characterization of landfill emissions is a com- plicated task, mainly because emissions are the result of a complex matrix of biological, physi- cal and engineering factors (SPOKAS et al., 2003). These factors depend on parameters such as organ- ic content, age and distribution of residues (GEOR- GAKI et al., 2008), climate (CHANTON et al., 2011), soil porosity, water content, nutrient availability, pH, texture, cracks and fissures (BOGNER et al., 2008; GEBERT et al., 2011). These factors are nu- merous and variable. Therefore, CH4 emissions may exhibit prominent spatial and temporal variations (ABICHOU et al., 2011; GONZALEZ-VALENCIA et al., 2016; SPOKAS et al., 2003). Landfill gases consist mainly of CH4 (50–70% v/v) and CO 2 (30–50% v/v), nitrogen, hydrogen sulfide and non-methane hydrocarbons (SCHEUTZ et al., 2009). In Brazil, there are three main destinations for solid urban waste: landfills, controlled landfills and open- air dumps (LIMA et al., 2018). The biological process is commonly applied, for being a simple and eco- nomical approach and is often the only technique used in most municipalities (COSTA et al., 2019). Open-air dumps are the least recommended way to dispose solid waste as they have no cover layers, no leachate collection or treatment systems, and the gas produced is not used as an energy source (ABRELPE, 2016). The objective of this study was to quantify both CO2 and CH4 production in an open-air dump (Aurá dump) that is located in the Amazon region and has emitted a total 9.4 to 9.8 Tg of CO 2 equivalent (IMBIRIBA et al., 2018) after it was closed, and to evaluate the relative importance of some environ- mental factors to gas surface fluxes, in both time and space. The main hypothesis is that there is a high production of greenhouse gases and that the substrate humidity and temperature would influ- ence CO2 and CH4 fluxes, even assuming a high spa- tial variability. Carbon dioxide and methane flux measurements at a large unsanitary dumping site in the Amazon region 15 RBCIAMB | n.54 | dez 2019 | 13-33 - ISSN 2176-9478 MATERIALS AND METHODS Study area The Aurá open-air waste dump (1°25’19.04”S and 48°23’18.68”W) has an area of 30 ha (Figure 1) and began activities in 1987, receiving waste from the metropolitan area of Belém, which comprises the municipalities of Belém, Ananindeua and Marituba (estimated population of over two million people) (MATOS et al., 2011). The initial project included an incineration, and a recycling and composting plant. However, neither were implemented (SIQUEIRA et al., 2016). Therefore, all the solid wastes were deposit- ed and distributed sequentially in layers, and com- pacted with track loaders, forming an open-dump with no environmental control and protection tech- niques. As such, this dump disrespects the technical specification of the Brazilian Association of Technical Standards (ABNT, 2010). Until now, leachate materi- al infiltrates the soil or reaches the water resources through runoff, while all the gas produced escapes to the atmosphere. The Aurá open-air dump received approximate- ly 1,200 Mg of waste per day from 1989 to 2014, of which 58% was organic (SANTO, 2014). This is equiv- alent to approximately 11.0 million Mg of waste de- posited in twenty-five years, of which 6.4 million Mg was organic. The deposition of domestic waste was forbidden on 2015, being allowed only the deposition of civil construction and urban cleaning waste. No soil Universidade Federal do Pará Author: Silvia Adriane Elesbão Graduation in Meteorology 48°30’0”W 48°28’0”W 48°26’0”W 48°24’0”W 48°22’0”W 48°30’0”W 48°28’0”W 48°26’0”W 48°24’0”W 48°22’0”W 1° 28 ’0 ”S 1 °2 6’ 0” S 1 °2 4’ 0” S 1 °2 2’ 0” S 1° 28 ’0 ”S 1 °2 6’ 0” S 1 °2 4’ 0” S 1 °2 2’ 0” S 0 1 2 4 6 8 10 km Guamá river Marajó Bay G ua ja rá B ay Belém Ananideua Marituba Água Prata reservoir Águas Lindas Aurá Subtitle Sampled points Drainage network Aurá neighborhood Water Belém Figure 1 – Location of the Aurá open-air dump with the identification of the studied sites. Pinheiro, L.T. et al. 16 RBCIAMB | n.54 | dez 2019 | 13-33 - ISSN 2176-9478 layer was placed over the waste, layer which could act as a reactive biological barrier, reducing CH 4 emission into the atmosphere (BÖRJESSON; SVENSSON, 1997). Thus, the soil in this study will be called substrate from here on. The Köppen climate classification of the study area is Afi, with an annual average air temperature of 26.7°C, relative humidity of 84%, precipitation of 3,001 mm, and 2,338 hours of sunshine (BASTOS et al., 2002). There are two well-defined rainy pe- riods, one is rainier (December to June), called here wet season, and the other is less rainy (July to No- vember), called dry season. In 2007, a biogas burning project, predicted to last 10 years, was established by Conestoga-Rovers and Associates (CRA). The landfill gas was captured us- ing a technology that consists on a network of ducts and wells connected to a central ventilation system by vacuum induction. A total of 2,608,401.0 Mg CO 2 -e (tons of carbon dioxide equivalent) was burnt from April 2007 to June 2016, according to a CRA report (CRA, 2006) available on the United Nations web- site on Certified Emissions Reductions (CER), and 139,092.0 Mg CO 2 -e in the last CERs measurement (01/01/2016 to 06/30/2016). The most efficient sys- tems are able to capture 75% of the biogas generated in a landfill (HASNAIN et al., 2012). However, in most cases, the efficiency ranges from 40 to 60% (BARLAZ et al., 2004). The measurements of CO 2 and CH 4 flux- es showed in this study were obtained in 2017, after the pipes used for conduction and flaring of the gases were removed. Three different sites were selected to measure CH 4 and CO 2 fluxes. The municipal urban waste was de- posited in the first site (S1, Figure 1) for a five-year period and street cleaning and commercial waste are currently deposited. At this site, there is no vegeta- tion cover and the gas fluxes were measured on May 11th and June 8th, 2017. The second site (S2, Figure 1) is still receiving municipal waste, however in smaller amounts than when it was officially active. S2 is ap- proximately 12 years old and has no vegetation cov- er, and the gas flux measurement was performed on June 29th, 2017. The third site (S3) was located in an older area (approximately 13 years old), where mu- nicipal waste was deposited until 2016. S3 is currently covered with undergrowth and was sampled on No- vember 9th, 2017. The measurements at S1 and S2 were made in the middle of the site, forming a circle (10 m radius), where eight flow chambers (samples or point) were randomly distributed. A rectangular area of 16 × 22 m was delimited within S3. The chambers were placed every 2 m in each direction of the area, yielding of 88 samples. Carbon dioxide and methane flux measurements Emission rates of CO 2 and CH 4 from the surface of the open-air dump were determined using the closed dynamic flux chamber technique, which measures variation of gas concentration inside the chambers (NORMAN et al., 1997). The Ultra-Portable Green- house Gas Analyzer (Los Gatos Research, Mountain View, CA, USA) model 915-0011 was used for simulta- neous measurements of CO 2 , CH 4 , and H 2 O (MAHESH et al., 2015). Two devices were used for simultaneous measurements. The chambers consisted of polyvinyl chloride (PVC) rings (diameter of 0.20 m and height of 0.12 m) and were inserted 0.05 m deep into the substrate at each sample location (within the sites). The rings that didn’t pierce the substrate were placed on the sur- face of the dump and externally sealed with clay soil. Any vegetation found inside the chamber was previ- ously removed. All rings were then closed with a PVC cap, forming a 4-liter chamber. An air circulation was established between the Ultra-Portable LGR analyzer and the flux chamber through polytetrafluoroeth- ylene (PTFE) tubes using a vacuum circulation pump at a rate of 0.50 L min-1. CO 2 and CH 4 concentrations (ppmv) were record- ed at 1 s intervals over a 3–4 min period. Flux- es were calculated from the rate of increase in concentration using the steepest linear portion of the accumulation curve as a function of time elapsed after the chamber was closed, adjusting to chamber volume and covered area, as proposed by Abichou et al. (2006). For a significantly non-zero flow, r2 would have to be less than 0.3 (SUNDQVIST et al., 2014). Carbon dioxide and methane flux measurements at a large unsanitary dumping site in the Amazon region 17 RBCIAMB | n.54 | dez 2019 | 13-33 - ISSN 2176-9478 Environmental variables Wind velocity (m s-1), relative humidity (%), air tem- perature (°C) and barometric pressure were measured with an AK821 thermo-hydro anemometer at each flux measurement interval. Substrate humidity (%) was analyzed with a Soil Water Measurement System (Hy- drosense; Campbell Scientific Inc.), and the substrate temperature (°C) was measured with a digital soil thermometer when the flow chambers were closed. The monthly rainfall and climatology data (1961–1990) were made available by the National Institute of Me- teorology (INMET), which has an automatic weather station at a site relatively near the Aurá dump. Geospatial analysis Geostatistical analysis tools were used to evaluate the spatial variation of the carbon dioxide and methane fluxes and to detect spatial dependence. This analysis was performed at S3 with 88 sampling units distribut- ed in a grid design (OPROMOLLA et al., 2006). The semi variance function is one of the tools in geostatistics most used to determine spatial dependence of a vari- able, generating a variogram (MELLO et al., 2005; OPRO- MOLLA et al., 2006). The variogram shows the spatial variability among the samples and the dependence level among the sites. A variogram γ(h) describes the variance of the quadratic difference of a spatial varia- tion between pairs of samples at distance h. Variograms were constructed, assuming isotropic spatial variation (i.e., independent of direction). In the absence of spa- tial dependence, i.e., in cases of large sample-to-sample variation at short distances, the variogram will show a nugget effect (OPROMOLLA et al., 2006). Statistical analysis Data normality was analyzed through the Shapiro-Wilk test, and the data were log-transformed when the res- idues did not present a normal distribution. The exper- iments were performed with at least eight chambers for each hour analyzed. In addition, 88 chambers were used in the geospatial (S3) analysis, as described above. The analysis of variance was used to assess the signif- icance of the variation. When the differences were significant, the Tukey test was used to evaluate which samples differed from each other. Pearson’s and Spear- man’s correlation were used to analyze the correlation between fluxes and environmental variables. Pearson’s correlation evaluates the linear relationship between two continuous variables, while Spearman’s measures the monotonic relationship between two continuous or ordinal variables, which tend to change together, but not necessarily at a constant rate. All analyzes were performed using the software InfoStat. RESULTS AND DISCUSSION Precipitation Precipitation in 2017 was 328.2 mm higher than the climatological average (1961–1990). The precipi- tation recorded for the months of May, June, July, September, and November was below the climato- logical average (Figure 2), and the remaining months exhibited above average precipitation records. Precipitation values when samples were collect- ed were below the climatological average, and the highest variation occurred in May 2017, when the precipitation was 94.9 mm below the climatological average. The precipitation in the months of June and November 2017 was, respectively, 3.9 and 8.0 mm below the average. An increased response time between a precipitation event and a change in the dump humidity may occur, given the direct relationship between landfill depth and response time (SCHEUTZ et al., 2017). These time inter- vals between humidity waves do influence the produc- tion of gas fluxes (RISK et al., 2008). In other words, when humidity decreases, the oxidative regions increase CH 4 production, with a consequent flux increase (TIAN et al., 2016; YANG; SILVER, 2016). In contrast, an increased CO 2 production is expected as humidity increases, with a consequent increased flow (DAVIDSON et al., 2000). The study was conducted at the end of the rainy season, and the beginning and the end of the dry season. Pinheiro, L.T. et al. 18 RBCIAMB | n.54 | dez 2019 | 13-33 - ISSN 2176-9478 Carbon dioxide and methane fluxes at two sites that were simultaneously analyzed CO 2 and CH 4 fluxes were measured at S1 on May 11th, 2017, where two areas were simultaneously analyzed (Figure 3). The distance between sites was approxi- mately 30 m. The fluxes had a non-normal distribution (p < 0.05). Therefore, the data was log-transformed to carry out the statistical analysis, thus reaching statisti- cal normality (p > 0.05) for the two gases investigated. The average CO2 flux at S1 and S2 was 133.04 ± 51.47 g m-2 d-1 and 370.80 ± 184.84 g m-2 d-1 (mean ± stan- dard error, n = 8), respectively. The mean CH 4 flow at the same sites was 40.00 ± 22.59 g m-2 d-1 and 77.32 ± 54.36 g m-2 d-1, respectively. No significant difference (p > 0.05) was found between the two sites studied for either of the gases analyzed. Air temperature var- ied significantly (p < 0.05) in the first chamber, ranging initially from 33.97 to 36.26°C on the last measure- ment. The mean temperature was 35.19 ± 0.26°C, and the relative humidity and wind velocity were 89.13 ± 0.63% and 1.10 ± 0.43 m s-1, respectively. Both flux measurements showed large variability, with CO 2 fluxes ranging from 61.69 to 1,655.43 g m-2 d-1 (co- efficient variation — CV = 140.99%), and CH 4 fluxes ranging from 2.77 to 455.95 g m-2 d-1 (CV = 67.04%). These results confirm that the surface emissions in Precipitation 1961–1990 (mm) 600 500 400 300 200 100 0 Ja nu ar y Fe br ua ry M ar ch Ap ril M ay Ju ne Ju ly Au gu st Se pt em be r O ct ob er N ov em be r D ec em be r Precipitation (mm) *Data provided by INMET. Figure 2 – Cumulative monthly precipitation for 2017 and climatological mean (1961–1990) at the metropolitan region of Belém*. Carbon dioxide and methane flux measurements at a large unsanitary dumping site in the Amazon region 19 RBCIAMB | n.54 | dez 2019 | 13-33 - ISSN 2176-9478 dumps are not uniform, with paths of lower resis- tance, creating hotspots (AHOUGHALANDARI; CABRAL, 2017b; ALLEN et al., 2019; GONZALEZ-VALENCIA et al., 2016; RACHOR et al., 2013). It is possible that emission areas have a higher air-filled porosity or improved pore connectivity compared to the larger dump area (BIAN et al., 2018b; RACHOR et al., 2013), resulting in pre- ferred pathways for gases. The high CO 2 emissions in the Aurá open-air dump may be consequence of the ecosystem respiration, and aerobic decomposition of organic matter was as well as of the indirect CO 2 emis- sions generated by CH 4 oxidation (BIAN et al., 2018a; FJELSTED et al., 2019). The hotspots of CH 4 was the same for CO 2 , meaning that the methanotrophic bac- teria are possibly consuming CH 4 and producing CO 2 when CH 4 is transported from deeper layers to the sur- face (ROSLEV; KING, 1996). This can be confirmed be- cause both CO 2 (p = 0.0548) and CH 4 (p = 0.0402) fluxes are negatively correlated with temperature (Figure 4). Carbon dioxide and methane fluxes at different periods of the day CO 2 and CH 4 fluxes were measured at the same site (S2, Figure 1), at different hours of the day, on June 8th, 2017. Samples were conducted at the end of the rainy season and the beginning of the dry sea- son (Figure 2). The air temperature was significant- ly different for all measurement hours (p < 0.01), ranging from 37.55 ± 0.32 to 42.55 ± 0.07°C (Figure 5). The CO 2 fluxes measured at the site were 198.22 ± 20.17, 188.93 ± 25.94, 216.53 ± 48.14 and 222.40 ± 31.73 g m-2 d-1 for the hours of 10 a.m., 11 a.m., 12 and 12:30 p.m., respectively (Figure 5). CH 4 fluxes were 2.65 ± 1.46, 4.91 ± 1.92, 4.47 ± 3.34 and 2.99 ± 1.78 g m-2 d-1, respectively, for the afore- mentioned hours. CO 2 and CH 4 fluxes didn’t vary sig- nificantly (p > 0.05) among measurements. Temperature was not correlated with either CO 2 or CH 4 fluxes (p > 0.05), despite the significant variation (p < 0.05) in air temperature observed among measure- ment hours (ABUSHAMMALA et al., 2013) (Table 1). Atmospheric pressure was 1013.0283 ± 0.0004 mb, and did not vary significantly (p > 0.05). Wind speed ranged from 1.51 ± 0.42 to 1.90 ± 0.46 m s-1, and no significant difference was found (p > 0.05) among mea- surements (Table 1). The parameters analyzed were ex- tremely homogeneous during the hours studied, except CO 2 fl ux (g m -2 d ay -1 ) 1,800 1,600 1,400 1,200 1,000 800 600 400 200 0 1 2 Place CH 4 fl ux (g m -2 d ay -1 ) 500 400 300 200 100 0 1 2 Place * Each box represents eight chambers, and bars show the standard error of the mean. Vertical lines represent the distribution of the chamber values, and horizontal lines inside the gray box indicate the mean value. The box height indicates the standard deviation of the mean. Figure 3 – The flow of carbon dioxide and methane measured simultaneously on both locations at S1 within the Aurá open-air dump, on May 11th, 2017*. Pinheiro, L.T. et al. 20 RBCIAMB | n.54 | dez 2019 | 13-33 - ISSN 2176-9478 44 42 40 38 36 34 Te m pe ra tu re (° C) 10 a.m. 11 a.m. 12 p.m. 12.30 p.m. Time 600 500 400 300 200 100 0C O 2 fl ux (g m -2 d ay -1 ) 10 a.m. 11 a.m. 12 p.m. 12.30 p.m. Time30 25 20 15 10 5 0C H 4 fl ux (g m -2 d ay -1 ) 10 a.m. 11 a.m. 12 p.m. 12.30 p.m. Time * Each box represents the mean of eight chambers and the bars, the standard error of the mean. Figure 5 – Variation of temperature (°C) and fluxes of carbon dioxide and methane measured at 10 a.m., 11 a.m., 12 p.m. and 12:30 p.m., on June 8th, 2017, at S2*. Lo g CO 2 ( g m -2 d ay -1 ) 3.4 3.2 3.0 2.8 2.6 2.4 2.2 1.8 1.6 1.4 33.5 34.0 34.5 35.0 35.5 36.0 36.5 Temperature (°C) Lo g CH 4 ( g m -2 d ay -1 ) 3.0 2.5 2.0 1.5 1.0 0.5 0.0 33.5 34.0 34.5 35.0 35.5 36.0 36.5 Temperature (°C) Figure 4 – Regression analysis between the logarithm of CO 2 and CH 4 fluxes (g m-2 d-1) and the temperature (°C) in cell 1 (S1) in the Aurá dump. Carbon dioxide and methane flux measurements at a large unsanitary dumping site in the Amazon region 21 RBCIAMB | n.54 | dez 2019 | 13-33 - ISSN 2176-9478 for temperature. However, no variable was significantly correlated (R2 < 0.1218) with either CO 2 or CH 4 fluxes. The maximum CH 4 oxidation activity was recorded at 15 to 20% moisture contents (ABICHOU et al., 2015; VISVANATHAN et al., 1999). In our study, 81.25% of the analyzed points had moisture values below 10%. Thus, CH 4 fluxes were expected to be larger than CO 2 fluxes (HANSON; HANSON, 1996; MEI et al., 2015), suggest- ing that CH 4 oxidation in depth is occurring (BIAN et al., 2018a; FJELSTED et al., 2019). Spatial variation in substrate permeability, air porosity, methane concentration in substrate gas and humidity content affect CH 4 emission rates (SPOKAS et al., 2003). Some advective mechanisms may be locally important for gas fluxes (SCHEUTZ et al., 2009). Inductive mecha- nisms of advective gas movement in the substrate may be: variations in atmospheric pressure (AGHDAM et al., 2019; FJELSTED et al., 2019; XU et al., 2014), tempera- ture (CHRISTOPHERSEN et al., 2001; FENG et al., 2017; PARK; SHIN, 2001; UYANIK et al., 2012), wind velocity in the substrate surface (AGHDAM et al., 2019; XIN et al., 2016), substrate humidity and water percolation (HAN- SON; HANSON, 1996; BOGNER et al., 2008), and differ- ences in substrate density (BIAN et al., 2018b; RACHOR et al., 2011). However, the results presented here show no variation in the fluxes, and no correlation between the variables analyzed and the gas emissions, despite the significant variation in temperature (Table 1). Carbon dioxide and methane fluxes in three locations and at three different hours CO 2 and CH 4 fluxes were measured on three differ- ent locations at S2 on June 29th, 2017 (Figure 1), with three sequential measurements on each location (Figure 6). Mean CO 2 fluxes were 222.43 ± 52.47, 299.52 ± 155.32 and 153.56 ± 47.82 g m-2 d-1 at S2.1; 346.88 ± 133.06, 265.69 ± 76.99 and 280.39 ± 75.21 g m-2 d-1 at S2.2; and 126.73 ± 25.78, 124.78 ± 33.65 and 105.28 ± 23.08 g m-2 d-1 at S2.3. Residues of CO 2 fluxes did not reach a normal varia- tion, were log-transformed, and did not exhibit a sig- nificant variation (n = 8, p > 0.05) among the sampled locations. A significant difference was recorded only between locations S2.2 and S2.3 (Tukey test, n = 24; p < 0.05) in the CO 2 flux (Figure 6). In the same experiment, mean CH 4 fluxes were 18.91 ± 5.03, 22.58 ± 7.57 and 4.48 ± 2.24g m-2 d-1 at S2.1; 33.43 ± 26.00, 23.56 ± 6.88 and 17.76 ± 7.32g m-2 d-1 at S2.2; and 2.78 ± 1.63, 2.17 ± 1.99 and 9.46 ± 6.08 g m-2 d-1 at S2.3 (Figure 6). The residues did not have a normal distribution, and hence were log-transformed. No significant variation (n = 8; p > 0.05) was found with- in either studied location. Comparison among locations showed that only S2.3 differed significantly (Tukey’s test, n = 24; p < 0.01) from the other two analyzed lo- cations (Table 2). Air temperature varied significantly (Tukey’s test, n = 8, p < 0.05) throughout the analyzed hours (Table 2), where the temperature during the gas emission measurement at S2.3 was statistically higher than at S2.2 (Tukey’s test, n = 24, p < 0.05), which was greater than S2.1 (Tukey’s test, n = 24, p < 0.05). Thus, air temperature ranged from 33.53 ± 0.39 to 41.57 ± 0.06°C, with a difference of 8.04°C. Wind speed did not vary significantly among hours and locations analyzed, ranging between 1.10 ± 0.20 and 2.43 ± 0.29 m s-1. Relative atmosphere humidity (Table 2) varied signifi- cantly within each hour analyzed (Tukey’s test, n = 8, p < 0.05). It was significantly higher at location S2.1 than at S2.2 (Tukey’s test, n = 24, p < 0.05), which did not differ significantly from S2.3 (Table 2). Substrate Table 1 – Variation of CO 2 and CH 4 fluxes (g m-2 d-1), air temperature (°C), barometric pressure (mb), wind speed (m s-1), relative humidity (%) and substrate humidity (%) analyzed on June 8th, 2017*. Hour (hr) CO 2 flux (g m-2 d-1) CH 4 flux (g m-2 d-1) Air temperature (°C) Pressure (mbar) Wind velocity (m s-1) Relative humidity (%) Substrate humidity (%) 10 a.m. 199.41 ± 20.29a 2.67 ± 1.47a 37.55 ± 0.32d 1013.0274 ± 0.0002 1.90 ± 0.46a 51.48 ± 1.70a 11.63 ± 3.91a 11 a.m. 190.04 ± 26.08a 4.94 ± 1.93a 39.60 ± 0.10c 1013.0288 ± 0.0001 1.51 ± 0.42a 37.58 ± 1.72b 9.00 ± 3.71a 12 p.m. 217.77 ± 48.41a 4.50 ± 3.36a 41.49 ± 0.22b 1013.0301 ± 0.0001 1.55 ± 0.27a 37.93 ± 1.43b 4.38 ± 1.78a 12.30 p.m. 223.65 ± 31.91a 3.01 ± 1.79a 42.55 ± 0.07a 1013.0309 ± 0.0001 1.76 ± 0.37a 41.73 ± 0.32b 4.25 ± 1.08a *Numbers represent the mean ± standard error, and the different letters represent the significance in the difference among the means by Tukey’s test (n = 8, p < 0.05). Pinheiro, L.T. et al. 22 RBCIAMB | n.54 | dez 2019 | 13-33 - ISSN 2176-9478 1,600 1,400 1,200 1,000 800 600 400 200 0 CO 2 fl ux (g m -2 d ay -1 ) S2.1 S2.2 S2.3 08:54 09:30 10:00 Time 250 200 150 100 50 0 CH 4 fl ux (g m -2 d ay -1 ) 08:54 09:30 10:00 Time 1,600 1,400 1,200 1,000 800 600 400 200 0 CO 2 fl ux (g m -2 d ay -1 ) 10:32 11:05 11:37 10:32 11:05 11:37 Time 250 200 150 100 50 0 CH 4 fl ux (g m -2 d ay -1 ) Time 1,600 1,400 1,200 1,000 800 600 400 200 0 CO 2 fl ux (g m -2 d ay -1 ) 12:14 12:44 13:17 12:14 12:44 13:17 Time 250 200 150 100 50 0 CH 4 fl ux (g m -2 d ay -1 ) Time *Each box represents the mean of eight chambers and the bars are the standard error of the mean. Figure 6 – CO 2 and CH 4 fluxes (g m-2 d-1) at the three hours, and three different locations in the Aurá dump (sampled on June 29th, 2017)*. Carbon dioxide and methane flux measurements at a large unsanitary dumping site in the Amazon region 23 RBCIAMB | n.54 | dez 2019 | 13-33 - ISSN 2176-9478 humidity (%) did not vary significantly within each hour analyzed and between sites (Table 2). CO 2 and CH 4 flux- es were not correlated with the environmental param- eters analyzed. However, the figures show that an air temperature increase to over 40°C causes a significant decrease (p < 0.05) in CO 2 and CH 4 fluxes (Table 2). The advective movement of gases through the sub- strate can be induced by variations on atmospheric pressure (AGHDAM et al., 2019; FJELSTED et al., 2019; XU et al., 2014), air temperature (ABICHOU et al., 2015; BOWDEN et al., 1998; XU et al., 2014), surface wind speed (AGHDAM et al., 2019; XIN et al., 2016), displacement of the water that infiltrates the substrate (ABICHOU et al., 2009; BAJAR et al., 2017; HANSON; HANSON, 1996; ROSLEV; KING, 1996; WHALEN et al., 1990), and differences in dump compaction (GEBERT et al., 2011; KAUSHAL; SHARMA, 2016; RÖWER et al., 2011). CH 4 is less dense than the atmospheric air, and therefore tends to rise, while CO 2 and almost all of the vapors produced by volatile organic liquids are denser than air, tending to sink when released into the gaseous portion of the substrate (SEINFELD; PANDIS, 2006). These results found on the Aurá open-air dump con- firm what has been stated throughout this paper, that both CO 2 and CH 4 fluxes do not depend on the external factors of the site, nor on substrate humidity. The main flow of the landfill gas seems to be driven by gas con- centration and free pathways (porosity) to reach the surface. Large amounts of plastic material placed in the dump can produce hotspots (MØNSTER et al., 2015; RACHOR et al., 2013; SCHEUTZ et al., 2017), operating as small “chimneys” for CO 2 and CH 4 fluxes (Figure 6). Specialization of the carbon dioxide and methane fluxes The geospatial analysis performed on November 9th, 2017 (at the end of the dry season), for CO 2 and CH 4 fluxes, showed a non-uniform distribution of gases emission into the atmosphere (Figure 7). The CO 2 flux ranged from 20.54 to 413.73 g m-2 d-1, and CH 4 , from -0.11 to 25.32 g m-2 d-1. Large hotspots were found on the surface of the dump at different points for CO 2 flow and only at one point for CH 4 flow (Figure 7). On the Table 2 – Variation of CO 2 and CH 4 fluxes (g m-2 d-1), at different locations in S2, at different sampling hours (hour) on June 29th, 2017, compared to air temperature (°C), wind speed (m s-1), relative air humidity (%) and substrate humidity (%), in the Aurá dump*. Location Hour CO 2 flow (g m-2 d-1) CH 4 flow (g m-2 d-1) Air temperature (°C) Wind speed (m s-1) Relative humidity (%) Substrate humidity (%) S2.1 1 222.43 ± 52.47a 18.91 ± 5.03a 33.53 ± 0.39c 2.43 ± 0.29a 60.80 ± 2.13a 4.50 ± 1.09a 2 299.52 ± 155.32a 22.58 ± 7.57a 35.58 ± 0.15b 1.38 ± 0.24b 39.65 ± 1.50b 1.88 ± 0.40b 3 153.56 ± 47.82a 4.48 ± 2.24a 36.59 ± 0.22a 1.16 ± 0.17b 40.55 ± 1.71b 2.00 ± 0.27b Mean 225.17 ± 55.80AB 15.32 ± 3.40A 35.23 ± 0.31C 1.65 ± 0.18A 47.00 ± 2.27A 2.79 ± 0.45A S2.2 1 346.88 ± 133.06a 33.43 ± 26.00a 38.39 ± 0.17c 1.41 ± 0.42a 51.65 ± 1.49a 3.75 ± 0.98a 2 265.69 ± 76.99a 23.56 ± 6.88a 39.56 ± 0.16b 1.10 ± 0.20a 34.50 ± 1.70b 1.63 ± 0.38a 3 280.39 ± 75.21a 17.76 ± 7.32a 40.19 ± 0.15a 1.58 ± 0.25a 29.79 ± 1.10b 1.50 ± 0.19a Mean 297.65 ± 55.01A 24.92 ± 8.98A 39.38 ± 0.18B 1.36 ± 0.17A 38.65 ± 2.12B 2.29 ± 0.40A S2.3 1 126.73 ± 25.78a 2.78 ± 1.63a 40.35 ± 0.16c 1.73 ± 0.21a 45.94 ± 0.70a 2.75 ± 0.77a 2 124.78 ± 33.65a 2.17 ± 1.98a 41.57 ± 0.06a 1.33 ± 0.35a 35.70 ± 1.43c 1.50 ± 0.27a 3 105.28 ± 21.59a 9.46 ± 6.08a 40.69 ± 0.18b 1.29 ± 0.36a 41.44 ± 1.44b 1.38 ± 0.18a Mean 119.52 ± 15.72B 5.01 ± 2.14B 40.48 ± 0.43A 1.45 ± 0.18A 41.03 ± 1.13AB 1.88 ± 0.30A Total 215.45 ± 27.98 15.23 ± 3.42 *Numbers represent the mean ± standard error, and the different letters represent the statistical difference (p < 0.05) between the averages by the Tukey test, where lowercase letters compare the hours within each site (n = 8), and capital letters between the sites (n = 24). Pinheiro, L.T. et al. 24 RBCIAMB | n.54 | dez 2019 | 13-33 - ISSN 2176-9478 A A 2 2 1 1 3 3 4 4 5 5 6 6 7 7 8 8 2 1 3 4 5 6 7 8 9 10 11 21 3 4 5 6 7 8 9 10 11 80 80 80 80 80 80 80 80 80 1 1 1 3 57 9 140 140140 140 140 140 140 200 Figure 7 – Geospatial variation (with flow chambers allocated every two meters) for CO 2 and CH 4 fluxes (g m-2 d-1), studied on November 9th, 2017 in the Aurá open-air dump. Carbon dioxide and methane flux measurements at a large unsanitary dumping site in the Amazon region 25 RBCIAMB | n.54 | dez 2019 | 13-33 - ISSN 2176-9478 other hand, in this older area, which has not been re- ceiving residues from many years, several places had a zero CH 4 flow, and some exhibited a sink of atmospher- ic CH 4 (SAUNOIS et al., 2016; STERN et al., 2007). The presence of preferential emission points was probably due to changes in gas concentrations within the dump (ABICHOU et al., 2006; BAJAR et al., 2017; KRAUSE, 2018). These changes are due to the uneven spreading of residues, lack of substrate layers or no use of plas- tic waterproofing between residue layers, or any gas collection strategy. These intense CO 2 fluxes may be consequence of the oxidation rate of CH 4 by the meth- anotrophs located in the substrate under the chambers (BIAN et al., 2018a; CHRISTOPHERSEN et al., 2001). This methane oxidation may be intensifying due to the less rainy period of the region (Figure 2), with November being the last month of the dry season. These results confirm the enormous spatial variability of gas fluxes in the Aurá dump, which shows an uneven residue distribution (AHOUGHALANDARI; CABRAL, 2017b; RÖWER et al., 2011). The variogram is an es- sential tool in a geospatial analysis, determining the amount of spatial dependence (autocorrelation) in the spatial data underlying the variations (SPOKAS et al., 2003). It is calculated from sampling sites in a uniform geospatial distribution and at least 100 sites are re- quired for a good variogram accuracy using a stationary random function (SPOKAS et al., 2003). The variogram data presented in this study used 88 sampling sites, measured with two devices simultaneously on oppo- site sides of the geospatial design. Results from the semi variance analysis (variogram) re- vealed that CO 2 fluxes at 4 to 10 m from the samples are independent and that, before and after this distance, the samples are dependent on the sampling site (Figure 8). However, the distance explains very little of the variation in CO 2 flux (R2 = 0.04, p = 0.668). The semi variance of CH 4 showed that the fluxes are dependent on the sampling site and that there are possible spots with a higher flux between 2 and 6 m, and the distance among the sites reasonably explains the CH 4 flux variation (R2 = 0.69; p = 0.022). However, the results for the gas emissions in- dicated that the non-spatial variability was high in com- parison with the spatial variability. Most studies show intense spatial variability (ABUSHAMMALA et al., 2016; AHOUGHALANDARI; CABRAL, 2017b; CHANTON et al., 2011; DI TRAPANI et al., 2013). However, if the variables had been studied in greater detail, the heterogeneity defined as non-spatial variability may have exhibited a spatial structure. However, substrate temperature does not appear to vary spatially (Figure 8), and substrate hu- midity was not measurable due to a device malfunction. CO 2 and CH 4 fluxes spatialization did not depend on the substrate temperature, but only on the enormous spatial variability as seen above (ABUSHAMMALA et al., 2013). The dump was constructed in a disorderly manner, without waterproofing and without covering the layers with substrate, isolating the concentration of organic material among plastics and other materi- als of difficult degradation (KARANJEKAR et al., 2015; SPOKAS et al., 2006). At the same time, this disordered arrangement can produce paths that facilitate gas flow, creating a hotspot (RACHOR et al., 2013; TAYLOR et al., 2018). Due to the hotspots and the methanotrophic activity, the use of CH4 to generate energy for a long time in open dumps in Brazil is unfeasible (AHOUGHA- LANDARI; CABRAL, 2017a; COSTA et al., 2019). On the other hand, the presence of hotspots implies in a lim- ited recovery effort to produce significant recovery re- sults (GONZALEZ-VALENCIA et al., 2016). The fluxes during the analyzed months were on average 171.62 ± 13.46 and 10.54 ± 2.70 g m-2 d-1 for CO2 and CH 4 , respectively. Thus, total monthly emissions from the Aurá dump to the atmosphere were 51.49 ± 4.04 Mg CO 2 ha-1 month-1 and 3.16 ± 0.81 Mg CH 4 ha-1 month-1. World landfill production ranges from 518.28 ± 448.28 and 184.11 ± 112.70 g m-2 d-1 of CO 2 and CH 4 , respec- tively (GOLLAPALLI; KOTA, 2018). As a result, the CO 2 flow in Aurá’s dump remains similar to the measured flux in other active landfills, with a rapid decrease in CH 4 flux. Also, exploiting Aurá dump for energy production may be economically unfeasible due to the large CH 4 flux spatial variation and the low generation. Since the Aurá dump area is 30 ha, the total gas emit- ted to the atmosphere is 1,544.61 and 94.84 Mg CH4 month -1. Thus, when converting CH 4 to CO 2 equiva- lent (CO 2 -e), we consider the global warming potential of CH 4 in 100 years to be 23 times greater than of CO 2 (IPCC, 2013), which results in a production of 1,359.96 Gg CO 2 -e y-1. That is, even after being closed for the domestic waste deposit and burned 2,608.40 Gg CO 2 -e (between 2007 and 2016), Aurá dump is still a signif- icant contributor to the intensification of the green- house effect. Pinheiro, L.T. et al. 26 RBCIAMB | n.54 | dez 2019 | 13-33 - ISSN 2176-9478 Va rio gr am s (g C O 2 m -2 d ay -1 ) 10,000 8,000 6,000 4,000 2,000 0 0 2 4 6 8 10 12 Distance (m) Va rio gr am s (g C H 4 m -2 d ay -1 ) 14 12 10 8 6 4 2 0 -2 0 2 4 6 8 10 12 Distance (m) Va rio gr am s (° C) 10 8 6 4 2 0 0 2 4 6 8 10 12 Distance (m) Figure 8 – Variogram of the (A) CO 2 flux, (B) CH 4 flux, and (C) temperature: variance γ(h) per distance h (m). Carbon dioxide and methane flux measurements at a large unsanitary dumping site in the Amazon region 27 RBCIAMB | n.54 | dez 2019 | 13-33 - ISSN 2176-9478 CONCLUSION Based on the results, we can conclude that: • The gas emission did not show a significant differ- ence between the end of the rainy period and the end of the dry period; • The spatial variability in the flux of CO 2 and CH 4 , es- pecially, is very large, forming hotspots of high con- centrations; • Aurá’s dump generates approximately 172.0 and 11.0 g m-2 d-1 for CO 2 and CH 4 , respectively; • The fluxes were not clearly correlated with any mi- crometeorological variable studied, i.e., only the gas concentration and the free paths to the surface flow motivate the release to the atmosphere; • The oxidation of CH 4 is apparently the main source of high CO 2 production on the surface, which is due to the low relative humidity of the open-air dump surface; • Aurá open-air dump was active for 28 years and has been closed for three. In addition, a significant amount of CO 2 -e was taken from the open-air dump by the CRA Company. Still it continues to release 1,359.96 Gg CO 2 -e y-1 into the atmosphere; • This result can be used with the IPCC waste mod- el to accurately estimate the total CH 4 emissions from the open-air dump in Amazon, which can be used to assess how much the CO 2 -eq emissions from the Amazonian dump contributes to the global warming. ACKNOWLEDGMENT This study was partially financed by the Coordination of Improvement of Higher Education Personnel (Coor- denação de Aperfeiçoamento de Pessoal de Nível Su- perior of Brazil — CAPES), to which we thank for the master’s scholarship granted. We are also grateful for the assistance of the Postgraduate Program in Environ- mental Sciences, of the Federal University of Pará, and to the Secretariat of Sanitation of the State of Pará, which has been enabling the development of this study in Aurá dump. 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