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There is increasing demand for cheap and rapid screening tests for soil contaminants in environmental consultancies. Diffuse reflectance spectroscopy (DRS) in the visible-near infrared (vis-NIR) and mid infrared (MIR) has the potential to meet this demand. The aims of this paper were to develop diagnostic screening tests for heavy metals and polycyclic aromatic hydrocarbons (PAH) in soil using vis-NIR and MIR DRS. Cadmium, copper, lead, and zinc were analysed, as were total PAH and benzo[a]pyrene. An ordinal logistic regression technique was used for the screening and predictions of either contaminated or uncontaminated soil at different thresholds. We calculated the rates of false positive and false negative predictions and derived Receiver Operating Characteristic curves to explore how the choice of a threshold affects their proportion. Zinc and copper had the best prediction accuracies of the heavy metals, with 89% and 85%, respectively. Cadmium and lead had the lowest prediction accuracies, with 68% and 67%, respectively. PAH predictions averaged 78.9%. With an average prediction accuracy of 79.9%, MIR analysis was only slightly more accurate than vis-NIR analysis, which had an average prediction accuracy of 77.5%. However, vis-NIR may be used in situ, thereby reducing cost and time of analysis and providing diagnosis in ‘real-time’. DRS in the vis-NIR can substantially decrease both the time and cost associated with screening for soil contaminants.

There is increasing demand for cheap and rapid screening tests for soil contaminants in environmental consultancies. Diffuse infrared reflectance spectroscopy in the visible-near-infrared (vis-NIR) and mid-infrared (MIR) has the potential to meet this demand. The aims of this chapter are to develop diagnostic screening tests for heavy metals and polycyclic aromatic hydrocarbons (PAHs) in soil using vis-NIR and MIR diffuse reflectance spectroscopy. Cadmium, copper, lead, and zinc were analysed, as were total PAHs and benzo [a]pyrene. An ordinal logistic regression technique was used for predictions in the screening tests and to determine false-positive and false-negative rates. Zinc had the best prediction accuracy (89%) and copper predictions were consistently above 75%. Cadmium and lead were the least well predicted of the heavy metals (67 and 70%, respectively), and PAH predictions averaged 78.9%. MIR analysis (average prediction accuracy of 79.9%) was only slightly more accurate than vis-NIR analysis (average prediction accuracy of 77.1%), but the latter may currently be used in situ, thereby reducing cost and time of analysis and providing diagnosis in real time. Diffuse reflectance spectroscopy in the vis-NIR can substantially decrease both the time and the cost associated with screening for soil contaminants.

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Voluntary sustainability standards are used as both a means of securing coffee supply by large coffee firms and a development intervention to address rural poverty and environmental management in the Global South. Using a case‐study approach, we have examined the interface between a value‐chain sustainability programme and the livelihood trajectories of smallholder producers in upland Sumatra. Our research found the programme has had minimal impacts for coffee producers to date. The level of commitment required of producers appears incompatible with the particular way that coffee is currently embedded within local landscapes, livelihoods and poverty alleviation pathways. Various sustainability standards articulate a narrative of rural development underpinned by an assumption that agricultural modernisation is the preferred pathway out of poverty for rural households. As a result, there is some risk that sustainability programmes may be inadvertently attempting to encourage household investment in a particular kind of agriculture, which is intended to assist sustainability of supply, but is poorly aligned with prevailing processes of poverty alleviation. These observations are based on a detailed study of agrarian change among the Semendo people of South Sumatra province, where processes of rural development are far more complex than assumptions presented by mainstream sustainability standards.

Lead roasting firms are operating through Indonesia's coffee exporters to introduce voluntary sustainability standards (VSS) in an attempt to secure supply, and to simultaneously meet corporate social responsibility requirements, even as empirical studies continue to show uncertain benefits for producer livelihoods. Value chain interventions like VSS, however, are not rolled out over a blank canvas, and many contributing factors determine their overall impact on livelihoods, particularly the local institutional environment. This study assesses the extent to which variability of empirical outcomes is determined by the institutional environment, by identifying specific processes through which VSS interact with pre‐existing social, political and economic institutions to influence livelihood outcomes. These include: firm‐specific corporate strategies (including producer training); livelihood strategies of households (including access to assets); government programs; and local political economy, as manifest particularly through patronage between traders and suppliers. VSS have thereby become an additional institutional layer shaping livelihood strategies and regional development outcomes, best viewed as providing access to a new social network that may be exploited by producers. The interaction between VSS programs, livelihood strategies and pre‐existing institutional environments in a particular place often dictates the variable outcomes for producers, making attribution of impact causation to VSS enrolment problematic.