Small wastewater treatment plants are often localized nearby tourist areas. Odour emissions are a major environmental issue in these plants and are considered to be the main cause of disturbance noticed by the exposed population. Odour measurement is carried out using analytical or sensorial methods. Sensorial analysis, being assigned to the “human sensor”, is the cause of a considerable uncertainty. In this study, a novel procedure based on highly innovative analytical tool was used to identify and characterise the odour sources and the volatile substances that cause annoyance in a SWWTP located in a sensitive area, with the aim to remove the subjective component in the measure of the odours and define the induced impact. At the same time key odour compounds are detected, and the relationship between their concentration and the performances of the plant are investigated. The sources and the main chemical substances responsible for the olfactory annoyances were identified. Results highlight the applicability of the highly innovative tool in odour emission monitoring. Around 39 different substances were detected, with almost half being smell relevant components as well as responsible. Dimethyl disulphide was identified as key compound connected to the efficiency of the process.

Odour emissions are a major environmental issue in wastewater treatment plants and are considered to be the main cause of disturbance noticed by the exposed population. Odour measurement is carried out using analytical or sensorial methods. Sensorial analysis, being assigned to the “human sensor”, is the cause of a considerable uncertainty. In this study a correlation between analytical and sensorial methods was investigated. A novel tool was used to both define odour indexes and characterise the odour sources and the volatile substances that cause annoyance in a wastewater treatment plant, with the aim to remove the subjective component in the measure of the odours and define the induced impact. The sources and the main chemical substances responsible for the olfactory annoyances were identified. Around 36 different substances were detected, with more than half being smell relevant components as well as responsible. Dimethyl disulphide was identified as key compound. Results highlight the applicability of highly correlation between analytical and sensorial methods in odour emission monitoring.

The main source of N₂O emissions is agriculture, and coffee monocultures have become an important part of these emissions. The demand for coffee has increased in the last five decades. Thus, its production in agricultural fields and the excess of fertilizers have increased. This study quantified N₂O emissions from different dose applications and types of nitrogen fertilizer in a region of major coffee production in Costa Rica. A specific methodology to measure N₂O fluxes from coffee plants was developed using Fourier-transform infrared spectroscopy (FTIR). Measurements were performed in a botanical garden in Germany and plots in Costa Rica, analyzing the behavior of a fertilizer in two varieties of coffee (Catuai and Geisha), and in a field experiment, testing two types of fertilizers (chemical (F1) and physical mixture (F2)) and compost (SA). As a result, the additions of synthetic fertilizer increased the N₂O fluxes. F2 showed higher emissions than F1 by up to 90% in the field experiment, and an increase in general emissions occurred after a rain event in the coffee plantation. The weak levels of N₂O emissions were caused by a rainfall deficit, maintaining low water content in the soil. Robust research is suggested for the inventories.

In the last 20 years, the demand for coffee production has increased detrimentally, heightening the need for production, which is currently driving the increase in land cultivation for coffee. However, this increase in production ultimately leads to the amplification of waste produced. This study aims to develop an experimental methodology for sustainable coffee by-products (Pulp (CP)) in Costa Rica for nutrient-rich compost. The performance of the experiments is to explore and optimize composting processes following its key parameters. This will allow quantifying the emissions rate to obtain an emission factor for CP during the open composting process and optimizing the conditions to minimize CH₄ emissions using P and green waste (GW) materials. Five CP and GW mixtures were analyzed for the composting process for ten weeks, acting P as primary input material as a by-product. Quantification of the methane emissions was performed in two areas: composting area and open field deposition. Peak temperatures of compost appeared at twenty-five days for control and five days for GW added treatments. CP emission factors provide a similar result with the standard values recommended by the literature, accomplishing the emission reductions. Thus, this study designed and validated a sustainable protocol for transforming coffee by-products into compost.

Concentrations of greenhouse gases such as carbon dioxide (CO₂), nitrous dioxide (N₂O) and methane (CH₄) in the atmosphere are rising continuously. The first step to reduce emissions from landfills is to gain better knowledge about the quantities emitted. There are several ways to quantify CH₄ emissions at landfills. Comprehensive quality analyses of individual methods for emission rate quantification at landfills are few to date. In the present paper, the authors conducted two field trials with three different remote sensing methods to gain more knowledge about the possibilities and challenges in quantification of CH₄ emissions from landfills. One release trial was conducted with released N₂O as tracer and CH₄ for quality assessment of the methods. In the second trial, the N₂O tracer was released on a landfill to gain experience under field conditions. The well-established inverse dispersion modelling method (IDMM) was used based on concentration data of TDLAS (Tunable Diode Laser Absorption Spectroscopy)-instruments and on concentration data of a partly drone based Fourier-Transformation-Infrared-Spectroscopy (FTIR)-instrument. Additionally, a tracer-method with N₂O-tracer and FTIR measurements was conducted. In both trials, IDMM based on TDLAS data and FTIR data provided the best results for high emission rates (15% deviation) and low emission rates (47% deviation). However, both methods have advantages, depending on the field of application. IDMM based on TDLAS measurements is the best choice for long-term measurements over several hours with constant wind conditions (8% deviation). The IDMM based on drone based FTIR measurements is the means of choice for measurements under changing wind conditions and where no linear measurement distances are possible.

Intensive livestock farming substantially impacts the environment, especially farm and slurry management. Slurries are significant sources of greenhouse gases and ammonia. The present study was conducted in an intensive livestock production system in Galicia, Spain. The measurements were taken at six different farms in that region along with one control using common management practices in Galicia without the addition of a bio-activator. This study aimed to quantify GHGs and NH₃ fluxes and their reductions during slurry treatment using a dynamic chamber through FTIR analysis and to examine the potential of usage of bio-activators for slurry management. In addition, gas concentrations were measured at the barns and compared with their slurry management and architectural volume to obtain influences on their management and the architectural volume of the barns. Additionally, the effects of using a bio-activator in the barns inside the facility areas were addressed. Moreover, qPCR analysis was conducted to understand the correlations between syncoms and methanogen populations when a bio-activator is added to the slurry with at least a 30% reduction in methanogenic populations. The outcomes suggest encouraging results for GHG reductions in the livestock sector, giving farmers future options for climate change mitigation among their standard practices.