How Green is my Occupation Classification?

Economic growth that prevents environmental degradation, biodiversity loss, and reduces climate change is dependent on the identification of new statistical measures, particularly in the way society works. The challenge is to define green jobs and identify green skills and incorporate them into a statistical framework to facilitate integration of economic, social, and environmental components of the labour market. What jobs will stay, what jobs will go and what jobs will emerge? How will the way we work change and can a statistical occupation classification adapt accordingly? The current concept of skill which underpins the Australian and New Zealand Standard Classification of Occupations (ANZSCO) classification may impose a constraint limiting the immediate opportunity for change within the classification structure. However the current ANZSCO classification should be flexible enough to provide an avenue for beginning the process of identifying new occupations in this emerging area of the New Zealand economy. Are green jobs actually new jobs as per existing classification principles or are they just new names for existing jobs? Are there actually new skill requirements that change the way current occupations are described? What are the attributes that need to be measured? This paper seeks to explore the feasibility of defining and classifying green jobs and green skills within the existing ANZSCO framework which may be able to be addressed at the next minor review of the classification

Where Have They Gone? Changes In Occupations Using 1991-2013 New Zealand Census Data

Over the period 1991 to 2013 they way in which occupations have been reported and classified in the New Zealand Census of Population and Dwellings has changed. To look at the high level trends, an analysis of the top thirty occupations that have the highest counts in census data in that time period based on the New Zealand Standard Classification of Occupations (NZSCO) has been undertaken. The purpose of this analysis is to have a time-series barometer to see whether respondents change the way in which they respond, and to determine if occupation reporting is reflecting changes in the real world of the New Zealand labour market. A comparison is made using the Australian and New Zealand Standard Classification of Occupations (ANZSCO) to identify if classification changes have an impact. Have some of the old occupations really disappeared or are they being reported differently? Has the way the occupations are classified, and the changes in the classifications caused some interesting trends. What impact has been experienced with the introduction of a trans-Tasman classification? Are there new and emerging occupations in this top group and are there any labour market sectors that are not appropriately represented? The paper discusses the role of an occupational classification in relation to the processing of the responses given to the five yearly population census question on occupation, and questions whether the statistical need for processing survey responses has affected the viability of the classification for labour market analysis

The Review/Development of the Australian and New Zealand Standard Classification of Occupations (ANZSCO)

Statistics New Zealand and the Australian Bureau of Statistics are undertaking a joint project to produce a new Australian and New Zealand Standard Classification of Occupations (ANZSCO). This paper will discuss the reasons and background for the project. In addition there will be discussion on the use of skill level and skill specialisation as conceptual criteria and how this is utilised to produce an intuitive classification structure. The paper will also look at the issues being faced by both statistical agencies to produce a relevant 'real-world' classification that ensures that contemporary and future user needs are met

Towards adaptive operational requirements for optimal application of evaporation-suppressing monolayer to reservoirs via a 'universal design framework'

Much of the chemical monolayer-based evaporation mitigation research was generated in the 1950s, 60s and 70s centred on the use of spreading long-chain fatty alcohols, such as hexadecanol (C16) and octadecanol (C18), on the water surface. Many researchers from this era have reported highly variable performance results (anywhere from 0-30% efficiency) attributing the highly variable evaporation reduction achieved to film volatilisation, drift, beaching on the lee shore and waves which can break-up or submerge the film.Failure to address this requirement has undoubtedly contributed to the lack of development in the use of monolayers despite some demonstration of useful evaporation suppression performance. In addition recent studies have also indicated that all water bodies have a naturally-occurring surface film, referred to as a microlayer, which can interact with artificial (chemical) monolayers. Natural microlayers are produced by hydrophobic plant waxes, phenolic compounds and other humified material, which concentrates populations of micro-organisms capable of utilizing these materials as organic substrates. This explains why common artificial monolayers (with carbon chain lengths of up to 16) are highly susceptible to biodegradation. Studies on Australian brown water storages reveal highly concentrated microbial microlayer communities, due to the coincidence of leaf and bark fall with low rainfall (Pittaway and van den Ancker 2009). This variation in the concentration of humified organic compounds in the storages is associated with both the volume of the storage, and the riparian vegetation within the water catchment. This paper sets out a strategic approach to the use of monolayer on a reservoir for evaporation mitigation. The approach recognises that every reservoir will have a specific set of user and environmental considerations which leads to a unique set of operational requirements. In order to capture and utilise this information a Universal Design Framework (UDF) has been developed. The UDF serves two purposes, firstly to inform the selection of monolayer material and system design for any given site (‘Planning Mode’), and secondly to inform (and potentially autonomously manage) day-to-day operations, i.e. the timing and amounts of monolayer application (‘Operational Mode’). The UDF takes into account the following parameters: • Critical water requirement periods: These will vary from location to location and at different times of the year. Hence, this is a user determined input. • Economics: The dollars-per-megalitre value of water will also vary from location to location and at different time of the year with respect to critical water requirement periods (e.g. irrigated cropping close to harvest). Included in this input is a user defined annual maximum cost outlay for the monolayer-based system. • Water storage factors: Inputs differ slightly depending on storage type (i.e. ring tank versus gully dam), but generally require information of length, width, shape, bank height, freeboard, full supply volume and geographical co-ordinate points for storage orientation. This would be determined by a basic on-site analysis • Climate and weather factors: Monthly average evaporation demand, rainfall and ambient air temperature information is required, including particularly wind speed frequency and prevailing wind direction, (e.g. from a local Automatic Weather Station (AWS) or via the Bureau of Meteorology SILO database, http://www.longpaddock.qld.gov.au/silo/). In the Planning Mode mean and extreme historical climate data are used; and in the Operational Mode prevailing conditions are required. • Water quality and biological factors: Assessments are made of water source/s (e.g. runoff versus bore), water colour, turbidity, water chemistry (pH, electrical conductivity and UV absorbency), plus density of local catchment vegetation and catchment area. Once the above parameters are known, the UDF is used to determine (in Planning Mode) the most suitable monolayer material/s and optimal arrangement of application equipment, including number of applicators, their arrangement and application strategies for the particular reservoir and monolayer product. In Operational Mode the UDF will guide (or if required, fully control) operational procedures, i.e. the implementation of a unique application strategy for a specific product according to the hour-by-hour prevailing conditions. This paper also outlines decision-making processes within the UDF. Firstly, to determine suitable monolayer materials the UDF compares water quality and biological characteristics of the particular site to those of six benchmark reservoirs in SE Queensland which have been studied in detail (Pittaway and van den Ancker 2009). The biologically-closest informs the choice of appropriate monolayer material/s. Once the selection of a monolayer is made there are a number of unique characteristics that material possesses that will substantially influence the application strategies. Secondly, a simulation platform has been developed to determine the application strategies and operational requirements for the reservoir. The simulation enables rapid evaluation of a range of different sample water bodies to populate a decision chart similar to that for monolayer material selection. A central component of the simulation platform is a fluid-mechanical model of the dispersal of monolayer across a water surface area under the influence of environmental variables, principally wind speed and wind direction, which (in Planning Mode) determines: • optimal spacing between application points, • amount of monolayer applied from each applicator as well as the total amount applied, • placement of applicators to achieve optimal surface coverage, • number of applicator types required, and • percentage of surface coverage under a range of wind speeds and directions. The above simulated output information is unique to the particular reservoir and is essentially a specification for the design and operation of a monolayer application system for that specific site, and is used firstly (Planning Mode) to select appropriate application equipment capable of satisfying the monolayer application requirements; and secondly, if installed as planned, as the basis for day-to-day monolayer application (Operational Mode). Simulation results to date indicate that from large reservoirs, optimal surface coverage is best achieved by a number of fixed application points surrounding and within the reservoir spaced no further than 12 metres apart; and that a greater concentration of applicators is required upwind from the prevailing wind direction in addition to higher rates of monolayer application