Forecasting Air Quality Parameters Using Hybrid Neural Network Modelling

Urban air pollution has emerged as an acute problem in recent years because of its detrimental effects on health and living conditions. The research presented here aims at attaining a better understanding of phenomena associated with atmospheric pollution, and in particular with aerosol particles. The specific goal was to develop a form of air quality modelling which can forecast urban air quality for the next day using airborne pollutant, meteorological and timing variables.Hourly airborne pollutant and meteorological averages collected during the years 1995–1997 were analysed in order to identify air quality episodes having typical and the most probable combinations of air pollutant and meteorological variables. This modelling was done using the Self-Organising Map (SOM) algorithm, Sammon's mapping and fuzzy distance metrics. The clusters of data that were found were characterised by statistics. Several overlapping Multi-Layer Perceptron (MLP) models were then applied to the clustered data, each of which represented one pollution episode. The actual levels for individual pollutants could then be calculated using a combination of the MLP models which were appropriate in that situation.The analysis phase of the modelling gave clear and intuitive results regarding air quality in the area where the data had been collected. The resulting forecast showed that the modelling of gaseous pollutants is more reliable than that of the particles.     

Effectiveness in Conservation Practice: Pointers from Medicine and Public Health

Abstract: Practical conservation activity is increasing globally and is being undertaken by many different government and nongovernmental organizations. In the majority of cases, justification for proposed actions is experience-based rather than evidence-based, action is often taken without monitoring or evaluation of effectiveness, and results are rarely widely disseminated. Conservation has been compared with medicine as a crisis discipline in which action is often required urgently in the absence of good information. The practice of medicine has recently gone through an effectiveness revolution that has improved the criteria upon which treatment strategies are based by progressing from reliance on personal experience to reliance on scientific evidence. We draw parallels between medicine and conservation and present a practical framework to encourage evidence-based conservation action. Our rationale is that conservation actions for which scarce resources are sought should be justified by good scientific evidence. In our view this will also encourage more research addressing practical issues in conservation management.     

Growth onset, senescence, and reproductive development of meadow species in mesocosms exposed to elevated O3 and CO2

We studied the effects of elevated O3 (40-50 ppb) and CO2 (+100 ppm) alone and in combination on the growth onset, relative chlorophyll meter values, and reproductive development of meadow species grown in ground-planted mesocosms using open-top chambers. The 3-year study was conducted in the summers of 2002-2004. Elevated O3 decreased the early season coverage of plant communities and delayed the flowering of Campanula rotundifolia and Vicia cracca. The relative chlorophyll meter values of Fragaria vesca leaves were decreased by O3. Ozone also reduced the overall number of produced flowers, but as far as individual species were concerned, O3 had significant effects only on Campanula rotundifolia. In the case of Fragaria vesca, O3 decreased the fresh weight of individual berries. The effects of CO2 were less pronounced, and CO2 generally did not ameliorate the negative effects of O3. Changes in reproduction may affect the long-term fate of the whole community.     

Effects of ecotourism on forest loss in the Himalayan biodiversity hotspot based on counterfactual analyses

Ecotourism is developing rapidly in biodiversity hotspots worldwide, but there is limited and mixed empirical evidence that ecotourism achieves positive biodiversity outcomes. We assessed whether ecotourism influenced forest loss rates and trajectories from 2000 to 2017 in Himalayan temperate forests. We compared forest loss in 15 ecotourism hubs with nonecotourism areas in 4 Himalayan countries. We used matching statistics to control for local-level determinants of forest loss, for example, population density, market access, and topography. None of the ecotourism hubs was free of forest loss, and we found limited evidence that forest-loss trajectories in ecotourism hubs were different from those in nonecotourism areas. In Nepal and Bhutan, differences in forest loss rates between ecotourism hubs and matched nonecotourism areas did not differ significantly, and the magnitude of the estimated effect was small. In India, where overall forest loss rates were the lowest of any country in our analysis, forest loss rates were higher in ecotourism hubs than in matched nonecotourism areas. In contrast, in China, where overall forest loss rates were highest, forest loss rates were lower in ecotourism hubs than where there was no ecotourism. Our results suggest that the success of ecotourism as a forest conservation strategy, as it is currently practiced in the Himalaya, is context dependent. In a region with high deforestation pressures, ecotourism may be a relatively environmentally friendly form of economic development relative to other development strategies. However, ecotourism may stimulate forest loss in regions where deforestation rates are low.     

Microbial community variation and its relationship with nitrogen mineralization in historically altered forests

Past land use can impart soil legacies that have important implications for ecosystem function. Although these legacies have been linked with microbially mediated processes, little is known about the long-term influence of land use on soil microbial communities themselves. We examined whether historical land use affected soil microbial community composition (lipid profiles) and whether community composition was related to potential net nitrogen (N) mineralization rates in southern Appalachian (USA) forest stands abandoned from agriculture or logging and reforested >50 yr ago. Microbial community composition was determined by a hybrid procedure of phospholipid fatty acid (PLFA) and fatty acid methyl ester (FAME) analysis. We found that community composition varied significantly with past land use. Communities in formerly farmed stands had a higher relative abundance of markers for gram-negative bacteria and a lower abundance of markers for fungi compared with previously logged and reference (i.e., no disturbance history) stands. Potential net N mineralization rates were negatively correlated with fungal and gram-negative bacterial markers in both farmed and reference stands, and fungal abundance and soil bulk density effectively predicted mineralization rates in all stands. Our results indicate that the alteration of microbial communities by historical land use may influence the ecosystem processes they mediate. This is in contrast to typical expectations about microbial community resilience to change. Here, the decrease in fungal abundance observed from disturbance appeared to result in decreased nitrogen mineralization over the long term.     

Using system dynamics to model water-reallocation

Improving the efficiency of water allocation has long been recognised as a key problem for the water resources management decision-makers. However, assessing the efficacy of management decision is difficult due to the complexity and interconnectivity of water resource systems. For this reason, it is vital that robust modelling approaches are employed to deal with the feedback loops inherent in the water resource systems. Whilst many studies have applied modelling to various aspects of water resource management, little attention has been given to innovations in modelling approaches to deal with the modelling challenges associated with improving decision-making. The aim of this study is to apply a System Dynamics modelling approach to improve the efficiency of water allocation incorporating a myriad of irrigation system constraints. The system dynamic approach allows the different system components to be organised as a collection of discrete objects that incorporate data, structure and function to generate complex system behaviour. Through the application of a system dynamic approach, a robust model (named the Economical Reallocating Water Model (ERWM)) was developed which was used to examine the options of re-allocating water resources that minimize the water cost all over an irrigated agricultural area. The EWRM incorporated a wide range of complexities likely to be encountered in water resource management: surface and ground water sources, water trading between sources, system constraint such as maximum ground water pumping, rates, maximum possible trading volumes and differential water resource prices. Two hypothetical systems have been presented here as an example. The results show that the System Dynamics approach has a significant advantages in estimating and assessing the outcomes of alternative water management strategies through time and space.     

Microbial stress-response physiology and its implications for ecosystem function

Microorganisms have a variety of evolutionary adaptations and physiological acclimation mechanisms that allow them to survive and remain active in the face of environmental stress. Physiological responses to stress have costs at the organismal level that can result in altered ecosystem-level C, energy, and nutrient flows. These large-scale impacts result from direct effects on active microbes' physiology and by controlling the composition of the active microbial community. We first consider some general aspects of how microbes experience environmental stresses and how they respond to them. We then discuss the impacts of two important ecosystem-level stressors, drought and freezing, on microbial physiology and community composition. Even when microbial community response to stress is limited, the physiological costs imposed on soil microbes are large enough that they may cause large shifts in the allocation and fate of C and N. For example, for microbes to synthesize the osmolytes they need to survive a single drought episode they may consume up to 5% of total annual net primary production in grassland ecosystems, while acclimating to freezing conditions switches Arctic tundra soils from immobilizing N during the growing season to mineralizing it during the winter. We suggest that more effectively integrating microbial ecology into ecosystem ecology will require a more complete integration of microbial physiological ecology, population biology, and process ecology.     

Use of Probabilistic Methods to Understand the Conservatism in California’s Approach to Assessing Health Risks Posed by Air Contaminants

Many state and federal agencies have prepared risk assessment guidelines, which describe methods for quantifying health risks associated with exposure to vapors and particulates emitted from point and area sources (e.g., California Air Pollution Control Officers Association [CAPCOA] under the Air Toxics “Hot Spots” Act [Assembly Bill 2588] and the U.S. Environmental Protection Agency [EPA] under the Clean Air Act). In general, these guidelines recommend or require the use of upper bound “point” estimates for numerous exposure parameters. This methodology yields a single risk estimate, which is intended not to underestimate the true risk and may significantly overstate it. This paper describes a risk assessment of a facility’s airborne emissions using a probabilistic approach, which presents a range and distribution of risk estimates rather than a single point estimate. The health risks to residents living near a food processing facility, as estimated using techniques recommended by California AB2588, are compared to the results of a probabilistic analysis. Polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs) were identified as the emitted chemicals of concern. The point estimate method recommended by CAPCOA resulted in estimates that were greater than the 99.99th percentile risk predicted by the probabilistic analysis. As shown in other assessments of persistent airborne chemicals, secondary or indirect exposure pathways (i.e., ingestion of beef, ingestion of cow’s milk, and ingestion of mother’s milk) rather than inhalation, were the greatest contributors to risk. In this analysis, the probability distributions for the cancer potency factor and ingestion of cow’s milk had the largest impact on the results of the 33 exposure factors considered.     

Monitoring and Source Apportionment of Particulate Matter near a Large Phosphorus Production Facility

ABSTRACT

A source apportionment study was conducted to identify sources within a large elemental phosphorus plant that contribute to exceedances of the National Ambient Air Quality Standards (NAAQS) for 24-hr PM₁₀. Ambient data were collected at three monitoring sites from October 1996 through July 1999, and included the following: 24-hr PM₁₀ mass, 24-hr PM_2.5 and PM_10–2.5 mass and chemistry, continuous PM₁₀and PM_2.5 mass, continuous meteorological data, and wind-direction-resolved PM_2.5 and PM₁₀ mass and chemistry. Ambient-based receptor modeling and wind-directional analysis were employed to help identify major sources or source locations and source contributions. Fine-fraction phosphate was the dominant species observed during PM₁₀ exceedances, though in general, re-suspended coarse dusts from raw and processed materials at the plant were also needed to create an exceedance. Major sources that were identified included the calciners, the CO flares, process-related dust, and electric-arc furnace operations.