Identification of nitrous oxide emissions from green areas of Chihuahua City irrigated with treated wastewater.

UNLABELLED: Since 2000, the city of Chihuahua had a distribution system of treated wastewater for irrigation of green areas and has replaced this water for processes that do not require the consumption of drinking water. This replacement was necessary in order to meet the growing demand for potable water which has exceeded the current supply of 700 L (184,88 gallons) per second. Nowadays it is necessary to identify and assess the risks to public health and the environment due to the substitution of drinking water by treated wastewater in the last 10yr. Treated wastewater contains compounds whose effects have not been evaluated when used for irrigation in public green areas. Therefore, it is not known whether there is a danger to the health of park visitors due to exposure and/or inhalation of the emitted gases, accidental ingestion of water, or impact to the environment. The purpose of the research, using an experimental prototype, is to identify the changes from nitrogen present in the treated wastewater to nitrous oxide. The research objective is the generation of data to simulate a regional scale at this stage, which will be analyzed and statistically validated using Minitab and Origin software. The experiment was performed using three different samples to compare water quality: drinking water treated wastewater, and water with nitrogen-based fertilizer (urea). Prototypes were filled with two types of soil: sand and clay Each type of water was sprinkled on the prototype, grass was planted in it, and the prototype was equipped with samplers to capture the gas in the root zone. The authors found high emissions of nitrous oxide in the clay-filled lysimeters, and climate and growing conditions of vegetation were the most important factors for producing nitrous oxide. IMPLICATIONS: Major problems in the ecosystem arise from solutions that are not based on environmental public policy research or experimentation. For example, before application a specific policy or regulation, research should be performed to evaluate long term effects to the ecosystem and this can be done through close monitoring. This study raises awareness about the public policy of substituting potable water with treated wastewater for irrigation of green areas in Chihuahua City. The present study was performed during a sufficient period of time in order to assess the impact to the environment.

Desagregación temporal de lecturas acumuladas de consumo de agua potable por medio de métodos estocásticos / Time disaggregation of water consumption readings by means of stochastic methods / Desagregação temporal de leituras acumuladas de consumo de água potável por meio de métodos estocásticos

El consumo doméstico de agua potable tiene carácter estocástico y puede ser representado como series de pulsos rectangulares de Poisson (PRP). Para generar las series de consumo se requieren parámetros tales como intensidad, duración y frecuencia de los pulsos, representados por su valor medio, varianza y distribución de probabilidad. La obtención de estos parámetros se basa en la medición directa de la demanda instantánea con intervalo de registro de 1s por varios días, lo que genera una enorme cantidad de datos a manejar y es impráctica al requerir de equipos especiales. Aquí se presenta un método para estimar los parámetros necesarios para generar las series de consumo instantáneo, con base en mediciones con intervalos >1s (p.e. 1min). El método considera principios del proceso de Neyman-Scott (N-S) en la desagregación temporal del volumen acumulado. La estimación de los parámetros se fundamenta en la comparación de los momentos observados producto de las mediciones en campo, con los momentos teóricos obtenidos del proceso estocástico. Se plantea una función objetivo que expresa la relación entre ambos momentos, la cual se minimiza obteniéndose los parámetros que caracterizan estadísticamente al consumo instantáneo. Una vez estimados tales parámetros, el modelo estocástico permite abordar el problema de la generación de series sintéticas de consumo, empleando cualquier intervalo de agregación temporal. El método fue validado por medio de una comparación entre series generadas con los parámetros resultantes del método propuesto y series medidas en campo.

Residential water demand is highly unsteady and stochastic, motivating the development of methods that model it as a series of rectangular pulses following a Poisson process (PRP methods). In order to generate the demand series, these methods require parameters of the instantaneous water demand, such as frequency of water use, and intensity and duration of stochastic demand pulses, each of them defined by its mean, variance and probability distribution. Procedures for obtaining those parameters are generally based on direct observation of instantaneous water demand by registering it every second at selected homes for several days. That direct technique is impractical, because of the enormous amount of data generated and processed, and the need of special equipment. A method for estimating the necessary parameters for simulating the instantaneous water demand from meter readings of >1s (e.g. 1min) is presented. The proposed method considers some principles from the Neyman-Scott (N-S) process, such as the disaggregation of the accumulated water volume, based on a comparison between statistical moments of the observed larger interval demand series and theoretical moments of the instantaneous water demand. An objective function expressing the relation between theoretical and observed moments is formulated and minimized by non linear programming. The intensity, duration and frequency or arrival rate of the instantaneous demand pulses are thus obtained. Using these results, instantaneous water demand series, or demand series with any averaging interval, can be generated. The method is validated by comparing the generated demand series with observed demand series.

O consumo doméstico de água potável tem caráter estocástico e pode ser representado como séries de pulsos retangulares de Poisson (PRP). Para gerar as séries de consumo se requerem parâmetros tais como intensidade, duração e freqüência dos pulsos, representados por seu valor médio, variância e distribuição de probabilidade. A obtenção de estes parâmetros se baseia na medição direta da demanda instantânea com intervalo de registro de 1s por vários dias, o que gera uma enorme quantidade de dados a manejar e é nada prática por requerer de equipamentos especiais. Aqui se apresenta um método para estimar os parâmetros necessários para gerar as séries de consumo instantâneo, baseados em medições com intervalos >1s (p.e. 1min). O método considera princípios do processo de Neyman-Scott (N-S) na desagregação temporal do volume acumulado. A estimação dos parâmetros se fundamenta na comparação dos momentos observados, produto das medições em campo, com os momentos teóricos obtidos do processo estocástico. Estabelece-se uma função objetivo que expressa a relação entre ambos os momentos, a qual se minimiza obtendo-se os parâmetros que caracterizam estatisticamente ao consumo instantâneo. Uma vez estimados tais parâmetros, o modelo estocástico permite abordar o problema da geração de séries sintéticas de consumo, empregando qualquer intervalo de agregação temporal. O método foi validado por meio de uma comparação entre séries geradas com os parâmetros resultantes do método proposto e séries medidas em campo.