Estimación de la concentración de material particulado PM10 y PM2.5 en el área metropolitana de Lima utilizando un modelo euleriano

Universidad Nacional Agraria La Molina. Escuela de Posgrado. Doctorado en Ingeniería y Ciencias AmbientalesLa calidad del aire de las ciudades es el resultado de relaciones complejas naturales y antropogénicas. Muchos distritos de la ciudad de Lima Metropolitana tienen concentraciones de material particulado que superan los ECA para PM10 (150 μg/m3) y PM2.5 (25 μg/m3). La exposición a concentraciones elevadas de contaminantes del aire genera efectos negativos sobre la salud. Las emisiones vehiculares son una fuente muy importante de contaminantes, los valores promedio de los contaminantes dan un mecanismo para analizar los cambios en tiempos largos. La variabilidad en esta tesis se relaciona con las concentraciones de PM10 y PM2.5 que nos indica que tan alejadas están las concentraciones del valor promedio y ayudan a tomar decisiones sociales importantes. Este trabajo de tesis tiene como objetivo estimar la concentración de material particulado PM10 y PM2.5 para Lima Metropolitana usando el modelo numérico de mesoescala euleriano Weather Research and Forecasting/ Chemistry (WRF-chem). Este modelo online sirve tanto para la investigación atmosférica y necesidades de pronóstico del tiempo-químico, para lo cual hace uso de información simultánea de meteorología y de química. Los periodos de estudios corresponden a los meses de febrero y julio del 2016, escogidos por los altos y bajos niveles de contaminantes atmosféricos. El modelo estimó las concentraciones de las especies químicas PM2.5 y PM10, información que fue comparada con datos registrados a nivel de superficie por diez estaciones de calidad del aire de SENAMHI:Campo de Marte(CMD), Ate(ATE), San Borja(SBJ), Santa Anita(STA), Carabayllo(CRB), Huachipa (HCH), Puente Piedra(PPD), San Martin de Porres(SMP), Villa María del Triunfo(VMT) y San Juan de Lurigancho(SJL). Esto nos permitió conocer en qué medida los ciclos diurnos de PM10 y PM2.5 están influenciados por las emisiones vehiculares en los dos periodos seleccionados. Un modelo numérico es euleriano cuando captura información de concentración o meteorológica en puntos fijos del espacio. El modelo WRF-chem, fue desarrollado por el National Center for Atmospheric Research (NCAR) en colaboración con otras instituciones norteamericanas, incluyendo National Oceanic and Atmospheric Administration (NOAA) y National Centers for Environmental Prediction (NCEP).The air quality of cities is the result of complex natural and anthropogenic relationships. Many districts in the city of Metropolitan Lima have concentrations of particulate material that exceed the air quality standards (ECA) for PM10 (150 μg / m3) and PM2.5 (25 μg / m3). Exposure to high concentrations of air pollutants generates negative effects on health. Vehicle emissions are a very important source of pollutants, the average values of pollutants provide a mechanism to analyze changes in long times. The variability in this thesis is related to the concentrations of PM10 and PM2.5 that tells us how far away the concentrations of the average value are and help to make important social decisions. This thesis work aims to estimate PM10 and PM2.5 particulate matter concentration for Metropolitan Lima using the Eulerian mesoscale numerical model Weather Research and Forecasting / Chemistry (WRF-chem). This online model serves both atmospheric research and weather-chemical forecasting needs, for which it makes use of simultaneous information from meteorology and chemistry. The study periods correspond to the months of February and July 2016, chosen for the high and low levels of atmospheric pollutants. The model estimated the concentrations of chemical species PM2.5 and PM10, information that was compared with data recorded at the surface level by ten SENAMHI air quality stations: Campo de Marte (CMD), Ate (ATE), San Borja (SBJ), Santa Anita (STA), Carabayllo (CRB), Huachipa (HCH), Puente Piedra (PPD), San Martin de Porres (SMP), Villa María del Triunfo (VMT) and San Juan de Lurigancho (SJL). This allowed us to know to what extent the diurnal cycles of PM10 and PM2.5 are influenced by vehicle emissions in the two selected periods. A numerical model is Eulerian when it captures concentration or meteorological information at fixed points in space. The WRF-chem model was developed by the National Center for Atmospheric Research (NCAR) in collaboration with other North American institutions, including National Oceanic and Atmospheric Administration (NOAA) and National Centers for Environmental Prediction (NCEP).Tesi

Diseño del proceso ZinCo – Ni ácido amigable con el medio ambiente

El proceso electrolítico para recubrir objetos ferrosos de bajo carbono con películas metálicas finas de cinc y así protegerlos de la corrosión utilizado en nuestro país, no es amigable con el medio ambiente, porque para el proceso es necesario utilizar cianuro de sodio (NaCN), anhídrido crómico (CrO3) y sales de cromo tales como sulfato de cromo, Cr2(SO4)3, que generan múltiples problemas de orden ambiental. Se ha desarrollando un proceso para recubrir objetos ferrosos con cinc libre de cianuro de sodio y cromo lo cual permitirá reducir el riesgo ambiental y de salud. Adicionalmente se ha mejorado el nivel de protección frente a la corrosión del cinc introduciendo en la película Ni y Co. Se han utilizado electrodos de Zn, Pb, Ti y Grafito y diferentes concentraciones de soluciones de ZnCl2, CoCl2.6H2O, NiCl2.6H2O y H3BO3 para producir una electrodeposición ternaria basada en Zn, Co y Ni. Con la finalidad de caracterizar la solución, se han realizando experimentos para estudiar la influencia del pH, así como el de la temperatura en la calidad de la película. Los análisis de las películas obtenidas vía electrolítica mediante el microscopio metalográfico permitieron definir el rango adecuado de pH [3-4], así como el de la temperatura [50-55 ºC]. Este mismo análisis, reveló la electrodeposición de una película metálica fina y brillante, libre de depósitos blancos de hidróxidos de cinc, se genera con un electrodo de grafito en un rango de pH de 3 a 4. Los análisis de Espectroscopia de Absorción Atómica permitieron determinar los porcentajes del cinc, cobalto y níquel en la película metálica electrodepositada. El análisis mediante Fluorescencia de Rayos X, Microscopía de Barrido Electrónico y Difracción de Rayos X determinó la morfología de la película y estructura cristalina de la electrodeposición ternaria formada. La resistencia de polarización Rp sobre un sustrato ferroso de acero de bajo carbono, se realizó mediante un ensayo potenciodinámico y, los valores de resistencia de polarización, así como la velocidad de corrosión comparados con los valores del cinc resultaron ser mucho más bajos, comprobando así la mejor resistencia frente a la corrosión de la película ternaria.Tesi

Estimación de la concentración de material particulado PM10 y PM2.5 en el área metropolitana de Lima utilizando un modelo euleriano

La calidad del aire de las ciudades es el resultado de relaciones complejas naturales y antropogénicas. Muchos distritos de la ciudad de Lima Metropolitana tienen concentraciones de material particulado que superan los ECA para PM10 (150 μg/m3) y PM2.5 (25 μg/m3). La exposición a concentraciones elevadas de contaminantes del aire genera efectos negativos sobre la salud. Las emisiones vehiculares son una fuente muy importante de contaminantes, los valores promedio de los contaminantes dan un mecanismo para analizar los cambios en tiempos largos. La variabilidad en esta tesis se relaciona con las concentraciones de PM10 y PM2.5 que nos indica que tan alejadas están las concentraciones del valor promedio y ayudan a tomar decisiones sociales importantes. Este trabajo de tesis tiene como objetivo estimar la concentración de material particulado PM10 y PM2.5 para Lima Metropolitana usando el modelo numérico de mesoescala euleriano Weather Research and Forecasting/ Chemistry (WRF-chem). Este modelo online sirve tanto para la investigación atmosférica y necesidades de pronóstico del tiempo-químico, para lo cual hace uso de información simultánea de meteorología y de química. Los periodos de estudios corresponden a los meses de febrero y julio del 2016, escogidos por los altos y bajos niveles de contaminantes atmosféricos. El modelo estimó las concentraciones de las especies químicas PM2.5 y PM10, información que fue comparada con datos registrados a nivel de superficie por diez estaciones de calidad del aire de SENAMHI:Campo de Marte(CMD), Ate(ATE), San Borja(SBJ), Santa Anita(STA), Carabayllo(CRB), Huachipa (HCH), Puente Piedra(PPD), San Martin de Porres(SMP), Villa María del Triunfo(VMT) y San Juan de Lurigancho(SJL). Esto nos permitió conocer en qué medida los ciclos diurnos de PM10 y PM2.5 están influenciados por las emisiones vehiculares en los dos periodos seleccionados. Un modelo numérico es euleriano cuando captura información de concentración o meteorológica en puntos fijos del espacio. El modelo WRF-chem, fue desarrollado por el National Center for Atmospheric Research (NCAR) en colaboración con otras instituciones norteamericanas, incluyendo National Oceanic and Atmospheric Administration (NOAA) y National Centers for Environmental Prediction (NCEP).The air quality of cities is the result of complex natural and anthropogenic relationships. Many districts in the city of Metropolitan Lima have concentrations of particulate material that exceed the air quality standards (ECA) for PM10 (150 μg / m3) and PM2.5 (25 μg / m3). Exposure to high concentrations of air pollutants generates negative effects on health. Vehicle emissions are a very important source of pollutants, the average values of pollutants provide a mechanism to analyze changes in long times. The variability in this thesis is related to the concentrations of PM10 and PM2.5 that tells us how far away the concentrations of the average value are and help to make important social decisions. This thesis work aims to estimate PM10 and PM2.5 particulate matter concentration for Metropolitan Lima using the Eulerian mesoscale numerical model Weather Research and Forecasting / Chemistry (WRF-chem). This online model serves both atmospheric research and weather-chemical forecasting needs, for which it makes use of simultaneous information from meteorology and chemistry. The study periods correspond to the months of February and July 2016, chosen for the high and low levels of atmospheric pollutants. The model estimated the concentrations of chemical species PM2.5 and PM10, information that was compared with data recorded at the surface level by ten SENAMHI air quality stations: Campo de Marte (CMD), Ate (ATE), San Borja (SBJ), Santa Anita (STA), Carabayllo (CRB), Huachipa (HCH), Puente Piedra (PPD), San Martin de Porres (SMP), Villa María del Triunfo (VMT) and San Juan de Lurigancho (SJL). This allowed us to know to what extent the diurnal cycles of PM10 and PM2.5 are influenced by vehicle emissions in the two selected periods. A numerical model is Eulerian when it captures concentration or meteorological information at fixed points in space. The WRF-chem model was developed by the National Center for Atmospheric Research (NCAR) in collaboration with other North American institutions, including National Oceanic and Atmospheric Administration (NOAA) and National Centers for Environmental Prediction (NCEP).TesisUniversidad Nacional Agraria La Molina. Escuela de Posgrado. Doctorado en Ingeniería y Ciencias Ambientale

Modeling Study of the Particulate Matter in Lima with the WRF-Chem Model: Case Study of April 2016

The Weather Research and Forecasting-Chemistry (WRFChem) model was used to develop an operational air quality forecast system for the Metropolitan Area of Lima-Callao (MALC), Peru, that is affected by high particulate matter concentrations episodes. In this work, we describe the implementation of an operational air quality-forecasting platform to be used in the elaboration of public policies by decision makers, and as a research tool to evaluate the formation and transport of air pollutants in the MALC. To examine the skills of this new system, an air pollution event in April 2016 exhibiting unusually elevated PM2.5 concentrations was simulated and compared against in situ air quality measurements. In addition, a Model Output Statistic (MOS) algorithm has been developed to improve outputs of inhalable particulate matter (PM10) and fine particulate matter (PM2.5) from the WRF-Chem model. The obtained results showed that MOS increased the accuracy in terms of mean normalized bias for PM10 and PM2.5 from -43.1% and 71.3% to 3.1%, 7.3%, respectively. In addition, the mean normalized gross error for PM10 and PM2.5 were reduced from 48% and 92.3% to 13.4% and 10.1%, respectively. The WRF-Chem Model results showed an appropriate relationship between of temperature and relative humidity with observations during April 2016. Mean normalized bias for temperature and relative humidity were approximately - 0.6% and 1.1% respectively. In addition, the mean normalized gross error for temperature and relative humidity were approximately 4.0% and 0.1% respectively. The results showed that this modelling system can be a useful tool for the analysis of air quality in MALC

Daytime perimeter environmental noise in the vicinity of four hospitals in the city of Lima, Peru

The present study is intended to get to know thelevels of perimeter diurnal environmental noise of fourhospitals in the city of Lima. The measurement mode usedat each hospital was A-weighting, with an integration timeof five minutes per recording. It was measured in the FASTmode with calibrations made at the beginning and end ofthe measurement day. Statistical analysis consisted of themean comparison T test which was applied at all the hospi-tals considered in the study. At the four hospitals, at all thehours of measurement and both on working days and non-working days (Sunday), LAeq mean values are higher than83 dBA. On working days, two periods of maximum noisefrom 08:00 to 10:00 in the morning and from 17:00 to 19:00in the afternoon coincide with the start and end of workinghours. The perimeter diurnal environmental noise levelsdetermined at the vicinity of four hospitals show highervalues in all cases to those established by the Peruvian Na-tional Environmental Standards for Noise for special pro-tection areas both for working days and for non-workingdays. Noise that comes from the dense and disorganizedtraffic of Lima plays a fundamental role in this behaviou

Adsorption of Cd (II) Using Chemically Modified Rice Husk: Characterization, Equilibrium, and Kinetic Studies

Cadmium (Cd) is a highly toxic heavy metal considered carcinogenic to humans. The adsorption behavior of cadmium adsorption using untreated and chemically modified rice husk was investigated. Experimental tests were carried out to evaluate the influence of the variables pH, initial concentration of cadmium, and dosage of adsorbent in the adsorption process. In optimal experimental conditions, the maximum adsorption efficiency was 92.65%. Fourier-transform infrared spectroscopy (FTIR) and scanning electron microscope (SEM) were used allowing the identification of the main functional groups and morphology of rice husk and treated rice husk, and the results showed an improvement of adsorption characteristics after rice husk treatment with NaOH. The optimum adsorption pH for both types of rice husk was 7. The maximum adsorption capacities of RH and treated RH fitted by the Langmuir model were 5.13 mg/g and 11.06 mg/g, respectively. The pseudosecond order kinetics has the best coefficients of determination for untreated (R2=0.992) and treated (R2=0.999) rice husk. The adsorption process was found to be endothermic in nature with enthalpy of 14.08 kJ/mol and entropy of 170.98 J/mol.K. The calculated activation energy was 24 kJ/mol. The results showed the potential of rice husk as a low-cost, easily managed, and efficient biosorbent for Cd removal from waters

Effect of current density on cod removal efficiency for wastewater usthe electrocoagulation process

The electrocoagulation process is an electrochemical technique that has demonstrated wide potential because it can be applied to wastewater from different industrial sectors considering the principles of electrolysis and coagulation. It is a low-cost method and of easy installation. Effluents with high concentrations of oils grease and chemical oxygen demand (COD) can be treated successfully obtaining high removal efficiencies. The purpose of this study was to analyze the effect of current density on the performance of oil/grease removal (OG), COD, and turbidity (NTU), as well as the pH variation and electrical conductivity during the process in batch mode. The effluent from the dairy industry with 172.6 mg OG/L, removed 70.30% OG, 75.38% COD with 76.92 A/m2 in 25 min of electrolysis. Two combinations of 2Fe-1Al and 1Fe-2Al anodes were analyzed at 68.38 A/m2 , reaching removals of 74.74% and 70% of OG, respectively. Regarding the domestic kitchen effluent, the COD initial was 1,766 mg/L, and working with two Fe-anodes, the OG removal efficiencies in 15 min of electrolysis were 94.9%, 96.75%, and 96.53% with current densities of 37, 56, and 74 A/m2 , respectively. The OG removal efficiencies were similar with Al-anodes. The COD removal efficiencies with Fe-anodes were 66.7%, 76.9%, and 68.7%, and with Al-anodes were 76.3%, 77.4%, and 77.5%, respectively. Both effluents were studied with an inter-electrode distance of 3 cm, and the pH in both cases varied from 7 to 8, which favors the elimination of contaminants by adsorption. The electrical conductivity did not undergo major changes, favoring the economy of the electrocoagulation process. Electrocoagulation is a low-cost electrochemical process in order to remove organic pollutants

Electrocoagulation in batch mode for the removal of the chemical oxygen demand of an effluent from slaughterhouse wastewater in Lima Peru: Fe and Al electrodes

In order to study the treatment of wastewater from a meat plant in a batch reactor, the electrocoagulation (EC) process with aluminum and iron electrodes was applied. Foams formed with iron electrodes show brown, greenish, and reddish colors, and foams formed with aluminum electrodes mainly show a whitish color. The effects of the applied voltages (6, 8, and 10 V) were analyzed over time on parameters such as current density (A/m2 ), pH, temperature, removal percentage of ionic conductivity (µS/cm), turbidity (nephelometric turbidity units), chemical oxygen demand (COD), thermotolerant coliforms, and oil–grease. The removal efficiencies for turbidity and COD in meat industry wastewater-slaughterhouse wastewater that were obtained were 99%, and 53%–59%, for aluminum, and 81.5%–88.5%, and 59%–60% for iron electrodes and 25 min EC time respectively. At 6 V the energy consumption per unit volume of treated effluent (kg/m³) and per kg COD removed (kwh/kg COD) with Al and Fe electrodes were (3.07 and 0.84) and (2.99 and 0.90), respectively. The EC process with Al and Fe electrodes proved to be a technique that removes contaminants from slaughterhouse wastewater with good yields