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18-Env-B6 Agricultural Waste Management · December 2019

Question 2 of 15: Composting Recipe — Broiler Litter, Sawdust and Water

Nivaar worked solution (AI-drafted; not reviewed by a licensed engineer)

Notes on this paper

National Exams, December 2019 — 18-Env-B6, Agricultural Waste Management (3 hours, open book, all 15 questions to be attempted, 100 marks total).

Reference texts: Rynk et al., On-Farm Composting Handbook (NRAES-54); OMAFRA, Nutrient Management Act, 2002 and O. Reg. 267/03 / Nutrient Management Protocol (NMAN); Metcalf & Eddy, Wastewater Engineering (anaerobic digestion chapter); ASABE Standards (manure storage, land application equipment); Environment and Climate Change Canada / Canada–Ontario Lake Erie Action Plan.

Question 2: Composting Recipe — Broiler Litter, Sawdust and Water (12 marks)

Question text not reproduced: the examination questions are © Engineers and Geoscientists BC. Open the official past paper (linked at the top of this page) to read the question, then follow the worked solution below.

Part (a) — recipe.

Given. Table A.1 "Average" rows for the two feedstocks:

Table A.1 — feedstock properties (average values)
Material%N (dry wt.)C:N ratioMoisture (% wet wt.)
Broiler litter2.71437
Sawdust0.2444239

Find. The mass ratio of broiler litter : sawdust : water that gives a blended C:N of 30:1 and a moisture content of 60% (wet basis).

Approach. Convert each material's C:N and %N into an equivalent %Carbon (dry basis), blend the two solids on a DRY-MASS basis to hit the target C:N, then add water (which carries no carbon or nitrogen) until the wet-basis moisture of the whole mix reaches 60%.

  1. Step 1 — back out %Carbon (dry basis) for each material. Since C:N = %C⁄%N (dry weight to weight), %C = (C:N)×%N. $$\%C_{\text{litter}} = 14 \times 2.7\% = 37.8\%, \qquad \%C_{\text{sawdust}} = 442 \times 0.24\% = 106.1\%$$ The sawdust figure is flagged below (part b) — a material cannot be >100% carbon by mass, so it is carried forward as printed per the attached table, with the inconsistency raised as a data-quality concern rather than silently corrected.
  2. Step 2 — blend dry solids for C:N = 30:1. Let r = (dry mass litter)⁄(dry mass sawdust), one dry mass unit of sawdust as the basis. The mix C:N is the ratio of blended %C to blended %N: $$30 = \dfrac{r(0.378) + 1.0608}{r(0.027) + 0.0024}$$ Solving, $r = 2.289$, i.e. about 2.29 kg dry broiler litter per 1 kg dry sawdust.
  3. Step 3 — convert dry masses to wet (as-received) masses. Dividing by each material's own solids fraction (1−moisture): $$W_{\text{litter}} = \dfrac{2.289}{1-0.37} = 3.633\ \text{kg wet}, \qquad W_{\text{sawdust}} = \dfrac{1.000}{1-0.39} = 1.639\ \text{kg wet}$$ Before any water is added, this blend already sits at moisture $= 1-\dfrac{2.289+1.000}{3.633+1.639}=37.6\%$ — well short of the 60% target.
  4. Step 4 — add water to reach 60% moisture. Water adds no dry solids, so the blend's 3.289 kg of dry solids must become 40% of the final wet mass: $$W_{\text{total, final}} = \dfrac{3.289}{1-0.60} = 8.222\ \text{kg}, \qquad W_{\text{water}} = 8.222-(3.633+1.639) = 2.950\ \text{kg}$$
  5. Step 5 — state the recipe on a practical basis. Scaling Step 4 so that broiler litter = 1000 kg (wet, as-received): $$\boxed{1000\ \text{kg broiler litter} \;:\; 451\ \text{kg sawdust} \;:\; 812\ \text{kg water} \quad (\text{total} \approx 2263\ \text{kg wet mix})}$$ which is a wet-mass ratio of roughly 2.2 : 1 : 1.8 (litter : sawdust : water).
Final Results — Question 2(a)
QuantityValue
Dry-mass ratio, litter : sawdust2.29 : 1
Recipe (wet basis, per 1000 kg litter)1000 kg litter : 451 kg sawdust : 812 kg water
Wet-mass ratio, litter : sawdust : water2.2 : 1 : 1.8
Resulting C:N ratio (check)30.0 : 1
Resulting moisture content (check)60.0%

Part (b) — concerns with this mixture.

Several practical concerns arise from this recipe, beyond the arithmetic itself:

Data quality of the sawdust entry. Table A.1's "average" row for sawdust implies %C = 106%, a physical impossibility (Step 1 above), because the handbook's own note states these range/average values are pooled from different literature sources and "should not be considered as the true ranges or averages, just representative values" — the %N and C:N columns were not necessarily measured on the same samples. A prudent designer would seek a paired, internally-consistent data point (or a fresh lab test of the actual sawdust on hand) rather than trust the tabulated average outright; using a more typical wood %C of ~50% instead moves the recipe to roughly 1000 kg litter : 957 kg sawdust : 1078 kg water — a materially different sawdust and water quantity, though the qualitative conclusion (substantial bulking agent and a large water addition) is unchanged.

Water addition is a large fraction of the final mix (36% by mass). Hauling and uniformly incorporating >800 kg of water per tonne of litter is a real handling and equipment burden; in practice a composter would substitute some water with a wetter co-feedstock (e.g. liquid manure or leachate) where available, rather than adding clean water.

Broiler litter's own C:N is only an ESTIMATE. The table's footnote (a) flags the C:N value as "estimated from ash or volatile solids data" rather than measured directly, so the design C:N of 30:1 carries more uncertainty than the arithmetic alone suggests.

Bulk density / mixing behaviour. Sawdust (410 lb/yd³) is much less dense than broiler litter (864 lb/yd³); by volume the pile will look far more sawdust-dominated than the 2.2:1 wet-mass ratio suggests, which can mislead field crews mixing "by eye" rather than by weight.

Pathogen and ammonia loss risk before water is added. The intermediate 37.6% moisture blend (Step 3) sits below the ideal composting range (50–65%) and the fresh, N-rich litter is prone to ammonia volatilization if it sits un-composted at that stage — water should be blended in promptly rather than staged separately.

Check: Table A.1's sawdust "average" row (%N=0.24, C:N=442) multiplies to 106% carbon, which is not physically possible. The boxed recipe above uses these values literally (as instructed, "use attached Table A-1"), consistent with the general rule of solving printed exam data as given and flagging the anomaly rather than silently substituting a different number.